Insights into Glomerular Cell Biology in Health and Disease

by

Tamadher Alghamdi

A thesis submitted in conformity with the requirements for the degree of the Doctor of Philosophy

Institute of Medical Science University of Toronto

© Copyright by Tamadher Alghamdi 2019

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Insights into Glomerular Cell Biology

in Health and Disease

Tamadher Alghamdi

Doctor of Philosophy

Institute of Medical Science

University of Toronto

2019

Abstract

The integrity of the kidney glomerular filtration barrier relies on the health of its components,

which include podocytes forming the final layer of the filtration barrier, and endothelial cells

lining the glomerular capillaries. Both cell types are important for kidney development and

normal kidney homeostasis, and their injury is implicated in a range of kidney diseases, notably

diabetic kidney disease, the most common cause of kidney failure. Here, I used podocytes to

explore novel autophagic regulation and paracrine communication mechanisms. By examining

the phenotypic effects of JAK2 absence in podocytes, I identified a role for JAK2 in regulating

podocyte autophagy completion, specifically through regulating the expression of a master

regulator of lysosomal gene expression known as transcription factor TFEB. Since JAK2 has

garnered attention as a promising therapeutic target for the treatment of diabetic kidney disease, I

explored the effects of systemic JAK2 inhibition, and JAK2 deletion from podocytes in

experimental models of diabetes. Pharmacological inhibition of JAK2 prevented progression of

albuminuria and reduced urine excretion of the chemokine CCL2. Likewise, podocyte-specific

JAK2 knockout resulted in a marked reduction in urine excretion of CCL2, which was also

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enriched in culture media conditioned by podocytes exposed to high glucose. Podocyte secreted

CCL2 signaling via its receptor CCR2 induced glomerular endothelial activation, characterized

by VCAM-1 upregulation, through a pathway regulated by p38 MAPK, MSK1/2, and

phosphorylation of histone protein H3 on serine residue 10 (phospho-histone H3Ser10).

Moreover, increased phospho-histone H3Ser10 levels were observed in the kidneys of diabetic

endothelial nitric oxide synthase knockout mice and in the glomeruli of humans with diabetic

kidney disease. Collectively, these findings: i) identified the homeostatic actions of JAK2 in

podocyte autophagy, also raising the possibility that therapeutically modulating TFEB activity

may improve podocyte health in glomerular disease; ii) highlight the anti-inflammatory effects of

JAK2 inhibition and podocyte-specific JAK2 deletion in diabetes; and iii) demonstrate the

influence that histone protein phosphorylation may have on gene activation in diabetic kidney

disease.

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Acknowledgments

The completion of my doctoral research studies and dissertation would not have been possible

without the support of key mentors and remarkable individuals, whom I had the pleasure to learn

from and work with over the past few years.

First and foremost, I would like to express my heartfelt gratitude to my supervisor, my mentor,

and my lifelong teacher, Dr. Andrew Advani. No words, not even in my native language, can

describe how grateful and thankful I am for his guidance, excellent mentorship, and unswerving

support throughout my PhD journey. It has been an absolute pleasure to learn from him, and

observe him over the past few years wearing multiple hats—an outstanding scientist, a

remarkable physician, and an exceptional mentor. I am profoundly thankful for his mentorship

and for the countless opportunities throughout the years that helped me grow as a scientist, and

independent thinker. I also thank him for his patience, for always challenging me with his lofty

expectations, and for pushing me to be the best version of myself, academically and personally. I

thank him for his faith in me and for the doses of encouragement that helped me persevere even

when faced with adversities and uncertainty. Beyond my research, I thank him for the

opportunity to shadow him on multiple occasions in the Diabetes Clinic at St. Michael’s Hospital,

an experience that has been a constant reminder to not lose sight of the big picture, and of the

potential impact that scientific research can have on people’s lives. Under his mentorship, I have

been able to develop invaluable skills and achieve several milestones beyond what I could

imagine. My time in his lab has been instrumental in shaping my career aspirations, and I

genuinely value the great life lessons that came with his mentorship. I sincerely thank him for his

dedication and for his tremendous efforts throughout these years, without which this thesis would

not have come to fruition. Dr. Advani has been and will continue to be an excellent role model

for me and for aspiring clinician scientists.

I would like to extend my thanks to the members of my advisory committee, Dr. Minna Woo, and

Dr. James Scholey for their mentorship and guidance. I am genuinely thankful for their

continuous support, their insightful suggestions, constructive feedback, and for the fruitful

discussions during our committee meetings that ensured my progress and helped shaping my

thesis research. Their time and continuous support throughout my PhD studies are deeply

appreciated. Special thanks also go to Dr. Richard Gilbert, the Head of the Division of

Endocrinology at St. Michael’s Hospital in Toronto and Canada Research Chair in Diabetes

Complications, for reviewing my thesis and for his valuable comments and feedback. I would

also like to thank the members of my Final Oral Examination committee, Dr. Pedro Geraldes and

Dr. York Pei for their insightful feedback and for participating in my PhD thesis defense.

I would also like to convey my sincere gratitude to the wonderful members of Advani Lab for

their immense support and contributions to this thesis work. Specifically, I would like to thank

Bridgit Bowskill for teaching me excellent animal handling skills during my first year, and for

her indispensable help in maintaining the mouse colonies required for the in vivo studies. I also

thank her for always offering to help when I am overwhelmed and for being there to share a

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laugh. I would also like to thank Suzanne Advani, also distinctively known as the Queen of

Histology, for sharing her passion for microscopy with me over the years, and for teaching me

about essential histological techniques that helped with the contents of this thesis. I also thank her

for always being supportive especially when the going gets tough, and for her dedication, all

while juggling work and family responsibilities. I would also like to thank Dr. Youan Liu for her

excellent assistance in maintaining cultured cells for the in vitro experiments. Her motherly hugs

and generous treats are deeply appreciated. I would also like to thank Dr. Golam Kabir for his

outstanding surgical skills and for the enjoyable conversations that made the long hours in the

OR so much fun. Outside the lab, I would like to thank the Advani family (Suzanne, Andrew,

Mathew, and Katie) for celebrating several milestones throughout the years, and for their

kindness and generosity. The international potluck and the annual lab Christmas party at their

house made the cold days in Toronto bearable.

Special thanks go to former and current post-doctoral fellows in the Advani Lab. In particular, I

would like to thank Dr. Sri Batchu, Dr. Syamantak Majumder, and Dr. Karina Thieme. I thank

each one of you for your unwavering support every step of the way. I am grateful to have been

able to conduct my PhD studies with such talented individuals who became dear friends. I thank

them for the countless intellectually stimulating discussions over coffee, and for teaching me a

range of excellent research skills and scientific techniques especially during the first few years of

my PhD. I also thank them for the opportunity to collaborate on several publications beyond my

thesis work. I would also like to thank Dr. Hana Vakili and Dr. Veera Ganesh Yerra for their

incredible support especially during the last two years of my PhD. I am also grateful for the

support of current and former graduate and summer students. Specifically, I would like to thank

my awesome friend Angela Brijmohan for being part of this journey. I truly enjoyed her company

at the bench and I thank her for her support throughout the years, and for making the long hours

in the lab and the late night experiments a wonderful time to show off our dancing skills. I would

also like to thank Ben Markowitz for his friendship, and for the great memories that I will always

cherish. I am also thankful for Mitchell Hadden for giving me a hand when I needed especially

during crunch time. I also thank my wonderful fellow PhD student Razan for always being

supportive and for her words of encouragement. To all my fellow graduate students at the Keenan

Research Centre for Biomedical Science, I thank you all dearly for helping me in one way or

another throughout this journey, whether it is through exchanging ideas, sharing lab equipment,

or engaging in social events.

I am thankful for the critical insights and the scholarly peer-review by several reviewers and the

editors of the Journal of the American Society of Nephrology and Diabetes that helped enhance

the quality of my thesis work. Sincere thanks go to our collaborators Dr. Laurette Geldenhuys

and Dr. Ferhan Siddiqi from Dalhousie University in Halifax, and Dr. Kathryn White from

Newcastle University in the UK. The contributions of our collaborators and their feedback during

manuscript revision are sincerely appreciated.

The generous support of the King Abdullah Foreign Scholarship Program and the Canadian

Institutes of Health Research that have made it possible for me to achieve my academic goals are

greatly appreciated. I would also like to thank the St. Michael’s Hospital research community and

the Institute of Medical Science at the University of Toronto for providing such a wonderfully

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rich academic and research experience. I also thank the Institute of Medical Science Students

Association (IMSSA) and the St. Michael’s Hospital Research Students Association for the

opportunity to take on several leadership positions to serve students, connect with my peers, and

engage in several events that enriched my academic experience beyond the lab.

Outside the lab, I have been blessed with a group of friends who have been my support system

over the past years. In particular, I would like to thank my dear friend Samah and her adorable

son Rashad for being part of this educational journey. I thank you for your incredible support and

for all the stress therapy and yoga sessions that shamefully did not count towards your psychiatry

residency training. I would also like to thank my dear friend Hanin, who has been more than just

a friend. Thank you for your unconditional support all the way from Kingston. Despite the

distance and being in the same boat with your own PhD studies, you have always been there for

me, and for that, I am deeply grateful. M5 friends, you know who you are! I thank every one of

you for your support, for finding every reason to celebrate my successes no matter how small, for

the wonderful adventures across Canada, and for everything you have done that made this

journey an exceptional one.

Most importantly, I am grateful for having a loving and caring family. My dear mother Norah

and my dear father Abdullah, I thank you for your unconditional love, support, and sacrifice.

Thank you for instilling in me the value of education, and for always supporting me to live up to

my potential even if it takes me away from you for a while. I also thank my dear brother Turki for

being my true inspiration to become a scientist, my dear sister-in-law Ameera for being my

cheerleader, and my precious little nephew Abdullah junior for being my source of joy. I am

indebted to my beloved brother Tameem for being the best companion since the beginning of my

educational journey in Canada. I could not have made it throughout these years without your love

and support. I also thank my dear cousin Rofan for the great times we had and for being by my

side during the most stressful times. Last, but not least, I would like to thank my one and only

loving sister Tasneem for being my best friend, for sharing my passion for science and education,

and for always finding a reason to make me laugh. Finally, my humble gratitude goes to God for

his endless blessings, and for giving me the strength to achieve this major milestone.

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To my late grandfathers,

May Allah rest their souls,

and to the people who have battled a chronic illness,

this work is dedicated to you.

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Table of Contents

Acknowledgments ......................................................................................................................... iv

Table of Contents ....................................................................................................................... xiii

Contributions .............................................................................................................................. xiii

Publications generated from thesis work ............................................................................... xviv

Other publications ...................................................................................................................... xvi

List of Tables .............................................................................................................................. xvii

List of Figures ........................................................................................................................... xviii

List of Abbreviations .................................................................................................................. xxi

List of Appendices .................................................................................................................... xxiv

CHAPTER 1: LITERATURE REVIEW .................................................................................... 1

1.1. Chronic kidney disease: scope of the problem .................................................................... 2

1.1.1. Prevalence and challenges .......................................................................................................... 2

1.2. Causes of chronic kidney disease ........................................................................................ 4

1.3. Diabetic kidney disease ....................................................................................................... 5

1.3.1. Pathophysiology of DKD ........................................................................................................... 6

1.3.1.1. Hyperglycemia ....................................................................................................... 8

1.3.1.2. Hemodynamic changes ........................................................................................ 10

1.3.1.3. Inflammation ........................................................................................................ 12

1.3.1.4. Growth factors and fibrotic factors ...................................................................... 13

1.3.2. Current available treatments for diabetic kidney disease .......................................................... 15

1.3.3. Emerging treatments for diabetic kidney disease ...................................................................... 16

1.3.3.1. The JAK/STAT pathway ...................................................................................... 16

1.3.3.1.1. Role of the JAK/STAT pathway in diabetic kidney disease ........................ 20

1.3.3.1.2. Development of JAK inhibitors ................................................................... 21

1.3.3.2. CCL2/CCR2 signaling pathway ........................................................................... 22

1.3.3.2.1. Development of CCL2/CCR2 blockers........................................................ 23

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1.4. Understanding podocyte (patho)biology: a key driver of therapeutic interventions for

glomerular diseases .................................................................................................. 24

1.4.1. Podocyte structure and function ............................................................................................... 25

1.4.2. Podocytopathies in glomerular diseases ................................................................................... 27

1.4.3. Podocytes and repair mechanisms ............................................................................................ 29

1.4.3.1. The autophagy-lysosomal pathway ...................................................................... 30

1.4.3.2. Role of TFEB: a major regulator of the autophagy-lysosomal pathway .............. 32

1.4.4. Podocytes as a model for paracrine communication ................................................................. 34

1.5. Glomerular endothelial cells .............................................................................................. 35

1.5.1. Podocyte-glomerular endothelial cell crosstalk ......................................................................... 37

1.5.1.1. Role of VEGF ....................................................................................................... 37

1.5.1.2. Other mediators of endothelial-podocyte communication ................................... 38

1.5.2. Glomerular endothelial dysfunction in DKD ............................................................................ 40

1.6. The emerging role of epigenetics in DKD......................................................................... 41

1.7. Research aims and hypotheses .......................................................................................... 44

CHAPTER 2: Janus Kinase 2 Regulates Transcription Factor EB Expression and

Autophagy Completion in Glomerular Podocytes ................................................................... 46

2.1. INTRODUCTION ............................................................................................................. 47

2.2. RESEARCH DESIGN AND METHODS ......................................................................... 48

2.2.1. Animal studies ........................................................................................................................... 48

2.2.1.1. Generation of Podocin-cre+R26Rfl/fl mice ......................................................... 48

2.2.1.2. Generation of podocyte-specific JAK2 knockout mice .................................... 48

2.2.2. β-Galactosidase expression ....................................................................................................... 49

2.2.3. Primary culture of podocytes .................................................................................................... 49

2.2.4. Immunoblotting ......................................................................................................................... 51

2.2.5. Immunofluorescence staining .................................................................................................... 51

2.2.6. Transmission electron microscopy ............................................................................................ 52

2.2.7. Conditionally immortalized mouse podocytes .......................................................................... 52

2.2.8. Real-Time PCR ......................................................................................................................... 52

2.2.9. Promoter Reporter Assay .......................................................................................................... 53

2.2.10. Chromatin Immunoprecipitation .......................................................................................... 53

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2.2.11. Albumin Permeability Assay ............................................................................................... 53

2.2.12. Statistical Analyses .............................................................................................................. 54

2.3. RESULTS .......................................................................................................................... 54

2.3.1. Knockout of JAK2 from podocytes impairs autophagy completion in mice ............................ 54

2.3.2. JAK2 knockdown impairs autophagy completion in differentiated immortalized podocytes.. 61

2.3.3. JAK2 knockdown downregulates the transcription factor TFEB ............................................. 66

2.3.4. TFEB overexpression restores podocyte function after JAK2 knockdown .............................. 71

2.4. DISCUSSION .................................................................................................................... 73

CHAPTER 3: Podocyte-specific JAK2 Deletion and JAK Inhibition Have an Anti-

inflammatory Effect in the Diabetic Kidney ............................................................................. 78

3.1. INTRODUCTION ............................................................................................................. 79

3.2. RESEARCH DESIGN AND METHODS ......................................................................... 80

3.2.1. Animal studies ........................................................................................................................... 80

3.2.1.1. JAK inhibition study in streptozotocin (STZ)-diabetic eNOS-/- mice ............... 80

3.2.1.2. Generation of STZ-diabetic podocyte-specific JAK2 knockout mice .............. 80

3.2.2. Mesangial matrix index ............................................................................................................. 81

3.2.3. Cell culture studies .................................................................................................................... 82

3.2.4. Statistical analysis ..................................................................................................................... 82

3.3. RESULTS ................................................................................................................ 83

3.3.1. JAK2 inhibition attenuates albuminuria in STZ-diabetic eNOS knockout mice ...................... 83

3.3.2. JAK inhibition attenuates urine CCL2 excretion and mesangial matrix accumulation in STZ-

diabetic eNOS knockout mice ................................................................................................... 85

3.3.3. Podocyte-specific JAK2 deletion does not influence urine albumin excretion in STZ-diabetic

mice ........................................................................................................................................... 87

3.3.4. Podocyte-specific JAK2 deletion attenuates urine CCL2 excretion ......................................... 89

3.3.5. The chemokine CCL2 is enriched in culture media conditioned by podocytes exposed to high

glucose ....................................................................................................................................... 90

3.4. DISCUSSION .................................................................................................................... 92

CHAPTER 4: Histone H3 Serine 10 Phosphorylation Facilitates Endothelial Activation in

Diabetic Kidney Disease .............................................................................................................. 95

4.1. INTRODUCTION ............................................................................................................. 96

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4.2. RESEARCH DESIGN AND METHODS ......................................................................... 97

4.2.1. Cell culture ............................................................................................................................... 97

4.2.2. Immunoblotting ........................................................................................................... 98

4.2.3. Animal Studies ......................................................................................................................... 98

4.2.4. Chromatin Immunoprecipitation .............................................................................................. 99

4.2.5. Quantitative reverse transcriptase PCR .................................................................................... 99

4.2.6. Human tissue study ................................................................................................................. 100

4.2.7. In situ hybridization ................................................................................................................ 100

4.2.8. Statistical Analysis ................................................................................................................. 101

4.3. RESULTS ........................................................................................................................ 102

4.3.1. Podocyte-derived CCL2 promotes VCAM-1 upregulation in human glomerular endothelial cells

and knockout of the CCL2 receptor, CCR2 decreases glomerular VCAM-1 upregulation in

diabetic mice ............................................................................................................ 102

4.3.2. CCL2/CCR2 signaling controls glomerular endothelial cell VCAM-1 expression through p38

MAPK and MSK1/2 dependent pathways .............................................................................. 109

4.3.3. CCL2 induces histone H3 serine 10 phosphorylation, which is enriched at the VCAM-1

promoter in human glomerular endothelial cells and the Vcam-1 promoter in mouse kidneys

112

4.3.4. Histone H3 serine 10 phosphorylation is increased in murine and human diabetic kidney

disease ..................................................................................................................................... 114

4.4. DISCUSSION .................................................................................................................. 118

CHAPTER 5: SUMMARY AND LIMITATIONS ................................................................ 124

5.1. Summary of results .......................................................................................................... 125

5.2. Limitations ....................................................................................................................... 128

CHAPTER 6: GENERAL DISCUSSION AND FUTURE DIRECTIONS ......................... 136

6.1. TFEB and the autophagy-lysosomal pathway as potential therapeutic targets in kidney

disease .. ..................................................................................................................................... 137

6.2. Targeting inflammatory mediators for treatment of diabetic kidney disease ............................ 141

6.2.1. JAK2 as a therapeutic target for DKD .................................................................. 141

6.2.2. CCL2/CCR2 signaling as a therapeutic target for DKD ....................................... 145

6.3. Histone phosphorylation in DKD .............................................................................................. 148

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6.4. Conclusion ....................................................................................................................... 151

Appendices ................................................................................................................................. 152

List of primer sequences used in the studies. ......................................................................... 152

Copyright Acknowledgments ................................................................................................... 155

CHAPTER 7: REFERENCES ................................................................................................. 156

xiii

Contributions

Chapter 2:

T.A.A. designed and performed the experiments, analyzed the data, and wrote the manuscript.

S.M., K.T., and S.N.B. contributed to the experiments and generation of data, specifically Figure

2.4B and C, Figure 2.6C and E, Figure 2.8, Table 2.2, Table 2.3, Figure 2.9G, Figure 2.10, Figure

2.11A and E. K.W. contributed to the transmission electron microscopic data. Y.L. assisted with

the in vitro experiments. A.S.B. contributed to the immunofluorescence staining data presented in

Figure 2.9F. B.B.B assisted with the animal studies. S.L.A. contributed to the

immunohistological data presented in Figure 2.5. M.W. contributed to the in vivo data and

revised the manuscript. A.A. designed the experiments, supervised the study, and wrote the

manuscript.

Chapter 3:

T.A.A. designed and performed the experiments, analyzed the data, and wrote this chapter.

S.N.B. contributed to the data presented in Table 3.2. B.B.B. assisted with the animal studies.

S.L.A. assisted with the immunohistological experiments. A.A. designed the experiments,

supervised the study, and revised and edited this chapter.

Chapter 4:

T.A.A. designed and performed the experiments, analyzed the data, and wrote the manuscript.

S.N.B. contributed to the experiments, generation and analysis of the data presented in Figure

4.1B-D, Figure 4.3, and Figure 4.7. M.J.H. contributed to the immunohistochemical image

analysis presented in Figure 4.4B. V.G.Y. contributed to the experiments, generation and analysis

of the data presented in Figure 4.2. Y.L. assisted with in vitro experiments. B.B.B. assisted with

animal studies. S.L.A. contributed to the experiments and generation of data presented in Figure

4.5, 4.10D, and 4.11. L.G. and F.S.S. contributed to the human data presented in Figure 4.11.

S.M. contributed to data analysis and revised the manuscript. A.A. designed the experiments,

supervised the study, and wrote the manuscript.

xiv

Publications generated from thesis work

International peer-reviewed articles:

1. The study described in Chapter 2 was published and reproduced with permission from:

Alghamdi, T.A., Majumder, S., Thieme, K., Batchu, S.N., White, K., Liu,Y., Brijmohan,

A.S., Bowskill, B., Advani, S.L., Woo, M., Advani, A. (2017). JAK2 regulates

transcription factor EB expression and autophagy completion in glomerular podocytes.

The Journal of American Society of Nephrology. 28(9):2641-2653.

2. Table 3.2 in Chapter 3 and the study described in Chapter 4 were published and

reproduced with permission from: Alghamdi, T.A., Batchu, S.N., Hadden, M.J., Yerra,

V.G., Liu, Y., Bowskill, B.B., Advani, S.L., Geldenhuys, L., Siddiqi, F.S., Majumder, S.,

Advani, A. (2018) Histone H3 serine 10 phosphorylation facilitates endothelial activation

in diabetic kidney disease. Diabetes. 67(12): 2668-2681.

Abstracts:

1. Part of the results from Chapter 2 was presented as an abstract and received the first prize

for an oral presentation at the Annual Research Day, St. Michael’s Hospital, Toronto, ON,

Canada. (April 18th, 2016).

2. Part of the results from Chapter 2 was presented as a poster abstract at the Annual

Institute of Medical Science (IMS) Scientific Day at the University of Toronto, Toronto,

ON, Canada. (May 20th, 2016).

3. Part of the results from Chapter 2 was presented as a poster abstract (#SA-PO355) at

Kidney Week 2016, the Annual Meeting of American Society of Nephrology, Chicago,

IL, USA. (Nov 15-20, 2016).

4. The study described in Chapter 2 was presented as a manuscript for the Jack Laidlaw

Manuscript Competition in the format of a letter to “Nature: International Weekly Journal

of Science”. It was orally presented at the IMS50 Scientific Day and obtained the first

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prize of the Jack Laidlaw Manuscript Award for the best research paper from the

University of Toronto IMS, Toronto, ON, Canada. (May 9th, 2018).

5. Part of the results from Chapter 3 and 4 were presented as a poster abstract (#0095-PD)

and as an electronic poster selected for a moderated discussion at the World Diabetes

Congress, Vancouver, BC, Canada. (November 30th- Dec 4th, 2015).

6. Part of the results from Chapter 3 and 4 was presented as a poster abstract (#492-P) and

was selected for a moderated discussion at the 78th Scientific Sessions of the American

Diabetes Association, Orlando, FL, USA. (June 22-26, 2018).

xvi

Other publications

1. Batchu, S.N., Thieme, K., Zadeh, F.H., Alghamdi, T.A., Hadden, M.J., Majumder, S., Kabir,

M.G., Bowskill, B.B., Ladha, D., Klein, T., Gramolini, A.O., Connelly, K.A, Advani, A.

(2018). The dipeptidyl peptidase-4 substrate CXCL12 has opposing cardiac effects in young

mice and aged diabetic mice mediated by Ca2+ flux and phosphoinositide-3 kinase γ.

Diabetes. 67(11):2443-2455.

2. Majumder, S., Thieme, K., Batchu, S.N., Alghamdi, T.A., Bowskill, B.B., Kabir, M. G., Liu,

Y., Advani, S.L., White, K.E., Geldenhuys, L., Tennankore, K.K., Poyah, P., Siddiqi, F.S.,

Advani, A. (2018). Shifts in podocyte histone H3K27me3 regulate mouse and human

glomerular disease. Journal of Clinical Investigation. 128(1):483-499.

3. Brijmohan, A.S., Batchu, S.N., Majumder, S., Alghamdi, T.A., McGaugh, S., Liu, Y.,

Advani, S.L., Bowskill, B.B., Kabir, M.G., Geldenhuys, L., Siddiqi, F.S., Advani, A. (2018).

HDAC6 inhibition promotes transcription factor EB activation and is protective in

experimental kidney disease. Frontiers in pharmacology. 9:34

4. Thieme, K., Majumder, S., Brijmohan, A.S., Batchu, S.N., Bowskill B.B., Alghamdi, T.A.,

Advani, S.L., Kabir, M.G., Liu, Y., Advani, A. (2017). EP4 inhibition attenuates the

development of diabetic and non-diabetic experimental kidney disease. Scientific

Reports.13;7(1):3442.

5. Siddiqi, F.S., Chen, L.H., Advani, S.L. Thai, K. Batchu, S.N. Alghamdi, T.A. White, K.E.,

Sood, M.M. Gibson, I. W., Connelly, K.A. Marsden P.A., Advani, A. (2014). CXCR4

promotes renal tubular cell survival in male diabetic rats: implications for ligand inactivation

in the human kidney. Endocrinology. 156(3):1121-32.

xvii

List of Tables

Chapter 2

Table 2.1: Body weight, kidney weight and systolic blood pressure (SBP) in JAK2Ctrl and

JAK2podKO mice.

Table 2.2: Relative mRNA levels of genes involved in the fusion of autophagosomes with

lysosomes.

Table 2.3: Relative mRNA levels of likely direct targets of TFEB with a known role in lysosome

function in mouse podocytes transfected with JAK2 siRNA or scramble.

Chapter 3

Table 3.1: Functional characteristics of control and streptozotocin-diabetic (STZ) wildtype (WT)

and endothelial nitric oxide synthase knockout (eNOS-/-) mice treated with vehicle or AZD1480 .

Table 3.2: Chemokine and cytokine content of culture medium of human podocytes under control

conditions or after incubation with high (25 mM) glucose or mannitol for 48 h.

xviii

List of Figures

Chapter 1

Figure 1.1: The prevalence rate of chronic kidney disease (CKD) per 100,000 of the global

population across age groups and by sociodemographic index (SDI) quintiles.

Figure 1.2: Chronic kidney disease classification based on glomerular filtration rate (GFR) and

albuminuria.

Figure 1.3: Glomerular filtration barrier.

Figure 1.4: The JAK/STAT signaling pathway.

Figure 1.5: JAK2 structure.

Figure 1.6: The intricate beauty of podocytes.

Figure 1.7: Autophagy process.

Chapter 2

Figure 2.1: An isolated Dynabeads-perfused glomerulus.

Figure 2.2: Characterization of Podocin-cre+ R26Rfl/fl mice.

Figure 2.3: Characterization of JAK2 deletion from podocytes in mice.

Figure 2.4: Representative periodic acid-Schiff stained kidney sections from JAK2Ctrl and

JAK2podKO mice aged 10 weeks.

Figure 2.5: JAK2 deletion impairs podocyte autophagy completion in vivo.

Figure 2.6: JAK2 knockdown with siRNA causes autophagosome and lysosome accumulation in

cultured immortalized mouse podocytes.

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Figure 2.7: Representative flow cytometry histograms from primary cultured cells stained for

nephrin.

Figure 2.8: JAK2 knockdown or knockout impairs lysosome function and decreases TFEB

expression in mouse podocytes.

Figure 2.9: Putative binding sites for STAT1 within the mouse TFEB promoter.

Figure 2.10: TFEB overexpression restores lysosome function and albumin permselectivity in

JAK2-deficient mouse podocytes.

Figure 2.11: JAK2 regulates autophagy completion in podocytes.

Chapter 3

Figure 3.1: Effect of JAK2 inhibition on urine CCL2 excretion and mesangial matrix

accumulation in the glomeruli of STZ-diabetic eNOS-/- mice.

Figure 3.2: Effect of podocyte-specific JAK2 deletion on kidney function in STZ-diabetic mice.

Figure 3.3: Effect of JAK2 knockout from podocytes on urine CCL2 excretion in STZ-diabetic

mice.

Chapter 4

Figure 4.1: Anti-CCL2 neutralizing antibody diminishes VCAM-1 upregulation induced by

exposure of human glomerular endothelial cells (hGECs) to culture media conditioned by high

glucose-exposed podocytes.

Figure 4.2: Immunoblotting hGECs for VCAM-1 under control conditions or following

incubation with recombinant angiopoietin-1, angiopoietin-2 or endothelin-1.

Figure 4.3. Effect of high glucose on CCR2 and CCL2 expression in cultured hGECs.

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Figure 4.4: Knockout of the CCL2 receptor, CCR2 decreases glomerular VCAM-1 upregulation

in diabetic mice.

Figure 4.5: In situ hybridization for VCAM-1 and immunostaining for nephrin and CD31 in

mouse and human kidneys.

Figure 4.6: CCL2 increases human glomerular endothelial cell (hGEC) VCAM-1 levels through

CCR2, p38 MAPK, MSK1/2 regulated mechanisms.

Figure 4.7: Immunoblotting for ICAM-1, E-selectin and P-selectin in hGECs under control

conditions or following incubation with recombinant CCL2.

Figure 4.8: CCL2 increases hGEC histone H3 serine 10 (H3Ser10) phosphorylation and phospho-

histone H3Ser10 is enriched at the VCAM-1 promoter in hGECs and mouse kidneys.

Figure 4.9: qRT-PCR for miR-93 in hGECs under control conditions or following incubation

with recombinant CCL2.

Figure 4.10: Urine CCL2 excretion and renal histone H3 serine 10 phosphorylation and VCAM-

1 expression are increased in STZ-diabetic endothelial nitric oxide synthase (eNOS) knockout

(eNOS-/-) mice.

Figure 4.11: Histone H3 serine 10 phosphorylation is increased in human diabetic kidney

disease.

Figure 4.12: Schematic illustration of the role histone H3 serine 10 (H3Ser10) phosphorylation

plays in regulating glomerular endothelial VCAM-1 expression and endothelial activation in

diabetes.

Chapter 5

Figure 5.1. Summary of key findings.

xxi

List of Abbreviations

ACE Angiotensin converting enzyme

ACEi ACE inhibitors

AGEs Advanced glycation end products

Ang I Angiotensin I

Ang II Angiotensin II

AKI Acute kidney injury

ARBs Angiotensin receptor blockers

ANOVA Analysis of variance

ATG Autophagy related gene

CB Cell body

CCL2 C-C motif chemokine ligand 2

CCL5 C-C motif chemokine ligand 5

CCR2 C-C motif chemokine receptor 2

CKD Chronic kidney disease

CLEAR Coordinated lysosomal expression and regulation

CSTN Cystinosin

CTGF Connective tissue growth factor

CX3CL1 CX3-C motif chemokine 1

CXCL12 C-X-C motif ligand 12

CVD Cardiovascular disease

DAPI 4′,6-diamidino-2-phenylindole

DKD Diabetic kidney disease

EBSS Earl’s Balanced Salt Solution

eGFR Estimated glomerular filtration rate

EGF Epidermal growth factor

eNOS Endothelial nitric oxide synthase

ESAM Endothelial cell-selective adhesion molecule

ESKD End-stage kidney disease

ESL Endothelial surface layer

FP foot processes

FPE foot process effacement

FSGS Focal segmental glomerulosclerosis

GAPDH Glyceraldehyde 3-phosphate dehydrogenase

GBM Glomerular basement membrane

GFB Glomerular filtration barrier

HbA1c Hemoglobin A1c

HBSS Hank’s Balanced Salt solution

HG High glucose (25 mmol/L)

H3K9ac Histone H3 lysine 9 acetylation

H3K27me3 Histone H3 lysine 27 trimethylation

H3Ser10 Histone H3 serine 10 phosphorylaion

IC50 Concentration at which the inhibition of activity is reduced by 50%

ICAM-1 Intraceullar adhesion molecule 1

xxii

IL-1 Interleukin 1

IL-6 Interleukin 6

IL-18 Interleukin 18

JAK Janus kinase

JH JAK homology

KIM-1 Kidney injury molecule 1

Lamβ1 Laminin β1

LAMP2 Lysosome-associated membrane protein 2

LC3 microtubule-associated protein 1 light chain 3

lncRNAs Long non-coding RNAs

MCD Minimal change disease

MCOLN1 Mucolipin 1

MCP-1 Monocyte chemoattractant protein 1

MET Mesenchymal–epithelial-transition

miRNAs micro ribonucleic acid

MiT Microphthalmia

MN Membranous nephropathy

MP Major processes

Msk1/2 Mitogen and stress-activated kinase 1/2

mTOR mammalian target of rapamycin

NO Nitric oxide

NFκB Nuclear factor kappa-light-chain-enhancer of activated B cells

p38 MAPK p38 mitogen-activated protein kinase

PBS Phosphate-buffered saline

PDGF Platelet-derived growth factor

PDGF-B Platelet-derived growth factor B

PDGFR-β Platelet-derived growth factor receptor β

PE Phosphatidylethanolamine

PIAS Protein inhibitors of activated STAT

PKD Polycystic kidney disease

PtdIns3K Phosphatidylinositol 3-kinase

PTHMs Post-translational histone modifications

PTMs Post-translational modifications

RAAS Renin-angiotensin-aldosterone system

RANTES regulated on activation, normal T cell expressed and secreted

RPLP0 Large ribosomal protein P0

ROS reactive oxygen species

SD Slit diaphragm

SD Standard deviation

SDF-1 Stromal cell–derived factor-1

SEM Standard error of the mean

SGLT2 sodium-dependent glucose transporter 2

siRNA short interfering RNA

SOCS suppressors of cytokine signaling

SP Secondary processes

xxiii

SQSTM1 Sequestosome 1

STAT Signal transducer and activator of transcription

STK4 Serine/threonine kinase 4

TGF-β Transforming growth factor β

TFEB Transcription factor EB

TNF-α Tumor necrosis factor-α

TYK2 Tyrosine kinase 2

UACR Urine albumin/creatinine ratio

ULK1/2 Unc-51-like autophagy activating kinase 1 and 2

VCAM-1 Vascular cell adhesion protein 1/ vascular adhesion molecule 1

VEGF Vascular endothelial growth factor

xxiv

List of Appendices

List of primer sequences used in the studies

1

CHAPTER 1: LITERATURE REVIEW

2

1.1. Chronic kidney disease: scope of the problem

1.1.1. Prevalence and challenges

Since the first successful kidney transplant in animals almost a century ago and six decades later

in humans, the global nephrology community has come a long way and made major advances in

the care and treatment of chronic kidney disease (CKD) (reviewed in Klintmalm 2004).

Nonetheless, the global health challenge of CKD continues to impose a high epidemiological and

economic burden on health care systems (Kassebaum, Arora et al. 2016, reviewed in Jager and

Fraser 2017). Today, almost one in 10 people worldwide are affected by CKD and the number is

on the rise (Mills, Xu et al. 2015, Hill, Fatoba et al. 2016, reviewed in Levin, Tonelli et al. 2017).

The prevalence rate of CKD has increased substantially and it correlates with aging and socio-

demographic status (Figure 1.1) (Xie, Bowe et al. 2018). In Canada alone, the number of people

living with kidney disease has increased to 36% since 2007, and of the 4,500 Canadians on the

waiting list for an organ transplant, almost 77% are waiting for a kidney (Canadian Organ

Replacement Register Annual Statistics 2016).

Figure 1.1: The prevalence rate of chronic kidney disease (CKD) per 100,000 of the global

population across age groups and by sociodemographic index (SDI) quintiles. Adapted from

(Xie, Bowe et al. 2018) with no copyrights permission required as per Creative Commons

Attribution-NonCommercial-No Derivatives License (CC BY NC ND).

3

The term CKD denotes abnormalities of kidney structure or function, present for more than three

months regardless of the underlying cause (Mills, Xu et al. 2015). Improper kidney function

results in loss of essential proteins such as albumin into the urine (albuminuria) and reduction in

estimated glomerular filtration rate (eGFR), which are standard measures for the diagnosis and

the stage classification of CKD (Figure 1.2) (reviewed in Romagnani, Remuzzi et al. 2017). If

left untreated, CKD can progress to end-stage kidney disease (ESKD), the most severe form of

CKD, commonly known as kidney failure.

Figure 1.2: Chronic kidney disease classification based on glomerular filtration rate (GFR) and

albuminuria. Adapted from (reviewed in Romagnani, Remuzzi et al. 2017) with permission from

Springer Nature ©.

Renal replacement therapies in the form of dialysis or kidney transplantation are the only

available treatment options for patients with ESKD (reviewed in Romagnani, Remuzzi et al.

2017). Although renal replacement therapies are life saving treatments, they are often associated

with low life expectancy, impaired quality of life, and adverse health outcomes including risk of

cardiovascular disease (CVD), death, acute kidney injury (AKI), infection and hospitalization

4

(Go, Chertow et al. 2004, reviewed in Pannu 2013). Moreover, inequity in access to renal

replacement therapies and health services increases the high risk of mortality in patients with

CKD (reviewed in Liyanage, Ninomiya et al. 2015). Furthermore, the number of deaths from

CKD has nearly doubled over the past three decades and CKD became the 11th leading cause of

death in 2016 (Naghavi, Abajobir et al. 2017).

The staggering costs of dialysis and kidney transplantation impose a financial burden to patients

and their families, and a global economic burden to health care systems. For instance, dialysis

and kidney transplantation alone cost between US$35,000 and $100,000 per year per patient

(reviewed in Levin, Tonelli et al. 2017). Current treatment strategies to prevent or slow CKD

progression remain limited and little progress has been made to find better diagnostic markers,

prognostic tools, and therapeutic targets (reviewed in Levin, Tonelli et al. 2017). Multiple

prominent interventional trials of potential therapies for CKD have shown no significant benefits

(Pfeffer, Burdmann et al. 2009, Mann, Green et al. 2010, Walz, Budde et al. 2010, Parving,

Brenner et al. 2012, De Zeeuw, Akizawa et al. 2013, Fried, Emanuele et al. 2013). Furthermore,

the pathophysiology and the underlying mechanisms of CKD are still not fully understood

(reviewed in Levin, Tonelli et al. 2017). Based on these challenges a global initiative led by

Kidney Disease Improving Global Outcomes (KDIGO) recently proposed an action plan to close

gaps in kidney care, research, and policy (reviewed in Levin, Tonelli et al. 2017). In line with the

proposed action plan, my doctoral thesis research was conducted to: i) advance understanding of

renal biology at the fundamental level, ii) contribute to the knowledge surrounding the causes of

kidney damage in CKD, and iii) provide insights that would lead to the development of better

therapeutic strategies for CKD.

1.2. Causes of chronic kidney disease

Identifying the underlying causes of CKD is essential for proper CKD management and

treatment. Globally, diabetes followed by hypertension are the leading causes of CKD (Xie,

Bowe et al. 2018). Between 1990 and 2016, it has been estimated that diabetes and hypertension

account for 50.62% and for 23.26% respectively of the overall increase in CKD disability-

adjusted life years (Xie, Bowe et al. 2018). Although agents that aim at lowering blood pressure

5

and blood glucose levels have been the standard therapy for patients with CKD, kidney

dysfunction continues to progress in many of these patients (Ismail-Beigi, Craven et al. 2012).

Moreover, the majority of patients with CKD die prematurely from CVD before progression to

ESKD (reviewed in Go, Chertow et al. 2004, Tonelli, Wiebe et al. 2006, reviewed in Dalrymple,

Katz et al. 2011). Other causes, although less common, can also contribute to the development of

CKD, which could be hereditary, developmental, or acquired (reviewed in Romagnani, Remuzzi

et al. 2017). Mutations in certain genes have been shown to contribute to development of CKD.

For instance, a loss of kidney function in Alport syndrome is caused by a mutation in the genes

encoding type IV collagen, which is an essential structural component of the glomerular

basement membrane (Barker, Hostikka et al. 1990). Developmental defects may also accelerate

progression of CKD. For example, those born with congenital defects such as low number of

nephrons are more prone to kidney dysfunction leading to CKD (reviewed in Brenner, Garcia et

al. 1988). Other factors such as infections, exposure to drugs and toxins, genetics, ethnicity,

aging, and gender also play a role in increasing the risk for CKD (reviewed in Webster, Nagler et

al. 2017). Early detection of these risk factors is important to mitigate progression of CKD.

However, out of all causes of CKD, diabetes is of particular global concern as the prevalence of

diabetes in adults is expected to increase from 8.8% in 2015 to 10.4% in 2040 across the globe

(Ogurtsova, da Rocha Fernandes et al. 2017). As the incidence of diabetes is expected to rise in

the next few decades, diabetes complications notably diabetic kidney disease will continue to

develop, urging for better prevention and treatment strategies.

1.3. Diabetic kidney disease

Diabetes is the leading cause of kidney failure worldwide (reviewed in Reidy, Kang et al. 2014).

Nearly half of all patients with type 2 diabetes and one third of patients with type 1 diabetes will

likely develop CKD (reviewed in Thomas, Brownlee et al. 2015). Development of CKD due to

diabetes is referred to as diabetic kidney disease (DKD), which was initially described in the

1980s (Mogensen, Christensen et al. 1983). Historically, the term diabetic nephropathy was

coined to characterize a condition that progress through a series of stages; a mild increase in

albuminuria (microalbuminuria; 30-300 mg/day), which subsequently progresses to overt

albuminuria (macroalbuminuria; >300 mg/day), followed by a decline in GFR (<60 ml/min/1.73

6

m2) and ultimately to ESKD (de Boer, Rue et al. 2011). Histologically, renal impairment in

patients with this form of diabetic nephropathy is often associated with specific structural

changes in the kidney such as nodular glomerulosclerosis (the classic Kimmelstiel-Wilson

nodule) (reviewed in Umanath and Lewis 2018). However, a growing body of evidence suggests

that not all patients with DKD follow the historically described path. In fact, patients with DKD

can develop albuminuria with no structural changes in the kidney, and microalbuminuria may not

progress or it may even regress, and patients may develop a significant reduction in GFR without

albuminuria (Kramer, Nguyen et al. 2003, Perkins, Ficociello et al. 2003, De Boer, Rue et al.

2011, reviewed in Umanath and Lewis 2018). Accordingly, DKD has recently been recognized as

a heterogeneous condition of disorders affecting the kidney in patients with diabetes and the

definition continues to evolve (reviewed in Persson and Rossing 2018).

1.3.1. Pathophysiology of DKD

The human kidney consists of approximately one million nephrons on average (Hinchliffe,

Sargent et al. 1991) and each nephron is composed of a single glomerulus, the main site of blood

filtration that has historically been much of the focus of the investigation in DKD research. A

single glomerulus consists of a small network of capillaries surrounded by Bowman’s capsule

connected to a segmented tubular reabsorption compartment. Within the glomerulus, there are

four types of cells: endothelial cells lining the capillaries, mesangial cells that reside in between

the capillaries, specialized epithelial cells known as podocytes covering the capillaries, and

parietal epithelial cells lining Bowman’s capsule (reviewed in Scott and Quaggin 2015). Each

cell plays an important role in maintaining proper glomerular filtration and each of these cells is

affected by diabetes (Holderied, Romoli et al. 2015). Endothelial cells and podocytes are

separated by a glomerular basement membrane (GBM) and together they form the glomerular

filtration barrier (GFB) that prevents passage of valuable large molecules such albumin into the

urine (Figure 1.3).

7

Figure 1.3: Glomerular filtration barrier. Depiction of the glomerular filtration barrier and its

components within the kidney glomerulus including fenestrated endothelial cells lining the

capillary lumen, GBM, and podocytes lining the urinary space and forming the final layer of the

filtration barrier.

In the normal kidney, the blood enters the glomerulus through the afferent arteriole and flows

through glomerular capillaries where permselectivity occurs. Filtered blood containing essential

macromolecules exits the glomerulus through the efferent arteriole and the primary urinary

filtrate passes through the glomerular filtration barrier to tubule cells for reabsorption of leaked

proteins (reviewed in Scott and Quaggin 2015). In the diabetic state, however, this normal blood

filtration process is disturbed by several factors that induce structural and functional

abnormalities in the kidney glomerulus and ultimately lead to renal dysfunction (reviewed in

Thomas, Brownlee et al. 2015). The mechanisms leading to DKD are still not fully understood

and the pathogenesis of DKD is multifactorial. However, preclinical and clinical studies of DKD

have improved our understanding of the underlying pathophysiology of DKD. A number of key

players implicated in the pathogenesis of DKD including hyperglycemia, hemodynamic changes,

inflammation and fibrotic factors are summarized below.

8

1.3.1.1. Hyperglycemia

DKD is one of the classical microvascular complications of diabetes. The implication of

hyperglycemia in the development of DKD has been extensively studied and two landmark trials

in particular, the Diabetes Control and Complications Trial (DCCT) and the United Kingdom

Prospective Diabetes Study (UKPDS) established that strict glycemic control slows development

and progression of DKD in patients with diabetes (DCCT 1993, UKPDS 1998). Further

highlighting the importance of hyperglycemia in the pathogenesis of DKD, diabetic glomerular

lesions have been reported to be reversed following pancreas transplantation in patients with type

1 diabetes with 10 years of normoglycemia (Fioretto, Barzon et al. 2014). In the healthy kidney,

180 g/day of glucose is filtered in the glomeruli and almost all of the filtered glucose is

reabsorbed by the proximal tubules (reviewed in Mather and Pollock 2011). In diabetes,

prolonged exposure of the kidney to the diabetic milieu causes metabolic changes that result in

modulation of signaling pathways implicated in kidney injury (reviewed in Reidy, Kang et al.

2014).

Kidney cells exposed to high glucose concentrations are amenable to functional abnormalities

and structural changes and these may be manifested as mesangial matrix expansion, loss of

endothelial fenestrations, effacement of podocyte foot processes, podocyte loss, and tubule

epithelial cell atrophy (reviewed in Reidy, Kang et al. 2014). The increase in cellular glucose

uptake is largely attributable to the expression and activity of glucose transporters (GLUTs),

which vary depending on the cell type (reviewed in Brownlee 2001). For instance, mesangial

cells and endothelial cells lack the ability to downregulate their glucose transporters when

exposed to hyperglycemia resulting in an increase in intracellular glucose levels, which in turns

induces mesangial extracellular matrix synthesis and endothelial dysfunction (Kaiser, Sasson et

al. 1993, Heilig, Concepcion et al. 1995). Moreover, a marked increase in the expression levels of

glucose transporters, namely sodium-dependent glucose transporter 2 (SGLT2) and GLUT2, was

observed in primary proximal tubule cells isolated from the urine of patients with type 2 diabetes

compared to cells from healthy individuals, suggesting that dysregulation of glucose metabolism

is implicated in the pathogenesis of DKD (Rahmoune, Thompson et al. 2005). However,

conflicting data from several studies showed that SGLT2 expression could be either upregulated

or downregulated in kidney biopsies from patients with diabetes highlighting the heterogeneity of

9

SGLT2 expression (Rajasekeran, Reich et al. 2017, Solini, Rossi et al. 2017, Wang, Levi et al.

2017).

Excessive glucose flux into kidney cells induces generation of toxic metabolites such as reactive

oxygen species (ROS), which is a feature of mitochondrial dysfunction in the diabetic kidney and

can activate pathogenetic pathways that lead to cellular dysfunction, vascular injury,

inflammation, apoptosis and fibrosis (reviewed in Forbes, Coughlan et al. 2008, Dugan, You et

al. 2013, Coughlan, Nguyen et al. 2016).

Hyperglycemia has also been shown to affect nutrient-sensing pathways in the kidney essential

for cellular homeostasis such as autophagy, mitochondrial biogenesis, and apoptosis. High levels

of glucose causes dysregulation of key players in nutrient-sensing pathways such as mammalian

target of rapamycin (mTOR) (reviewed in Kume, Thomas et al. 2012). Several studies in

streptozotocin-induced diabetes showed that hyperglycemia induces mTOR-dependent kidney

hypertrophy and inhibition of mTOR activity using the specific mTOR inhibitor rapamycin

reduced secretion of profibrotic and proinflammatory cytokines and chemokines within the

kidney (Lloberas, Cruzado et al. 2006, Sakaguchi, Isono et al. 2006, Yang, Wang et al. 2007).

Moreover, rapamycin caused marked reduction in albuminuria and ameliorated renal

hypertrophy, glomerular basement membrane thickening, and accumulation of mesangial matrix

(Lloberas, Cruzado et al. 2006, Sakaguchi, Isono et al. 2006, Yang, Wang et al. 2007). However,

other studies have shown opposing effects of mTOR inhibition in animal models and patients

including proteinuria and glomerulosclerosis (Torras, Herrero-Fresneda et al., 2009;

Munivenkatappa, Haririan et al., 2010; Letavernier, Bruneval et al., 2007). In comparison,

activation of mTOR specifically in podocytes has been shown to facilitate DKD in mice and

humans (Inoki, Mori et al. 2011). The role of mTOR signaling in the kidney in health and in

DKD has been demonstrated by Gödel and colleagues in a series of elegant experiments in

genetically modified mouse models (Gödel, Hartleben et al., 2011). In this study, podocyte-

specific deletion of rapamycin-sensitive adaptor protein of mTOR (Raptor), and rapamycin-

insensitive subunit (Rictor), which are essential components of mTORC1 and mTORC2,

respectively, worsened glomerular lesions, suggesting that both mTOR complexes are required

for podocyte homeostasis and development. However, reducing mTORC1 activity by genetically

deleting one allele of Raptor prevented progression of glomerular disease in diabetic mice. These

10

findings suggest that tight regulation of mTOR signaling is essential for podocyte homeostasis

and preventing progressive glomerular dysfunction (Gödel, Hartleben et al., 2011).

Dysregulation of autophagy, a highly conserved self-repair mechanism essential for cell survival,

has also been reported in the kidneys of experimental models and humans with diabetes

(reviewed in Ding and Choi 2015). Studies from multiple groups reported an accumulation of the

autophagy substrate p62/Sequestosome 1 (SQSTM1), indicative of impaired autophagic

clearance, in kidneys of experimental models of type 1 diabetes (Vallon, Rose et al. 2012) and

type 2 diabetes (Kitada, Kume et al. 2011), and in kidney biopsy samples obtained from patients

with type 2 diabetes (Yamahara, Kume et al. 2013). In addition, a study from our own group

revealed that not only accumulation of p62 was observed, but the transcription factor termed

transcription factor EB (TFEB), a master regulator of the autophagy-lysosomal pathway, was also

downregulated in kidney biopsies from patients with DKD (Brijmohan, Batchu et al. 2018).

Despite the importance of intensive glucose lowering, follow up of the DCCT trial participants

showed that in some patients, poor glycemic control can have a lasting effect in the kidney even

after strict glycemic control (De Boer, Rue et al. 2011). This phenomenon is commonly referred

to as ‘metabolic memory’ whereby exposure to the diabetic milieu results in a deleterious effect

that lasts despite glucose normalization and this has been suggested to be attributable to persistent

epigenetic changes (reviewed in Brownlee 2001, reviewed in Giacco and Brownlee 2010,

reviewed in Reddy, Zhang et al. 2015). Furthermore, it has been recently suggested that high

variability in blood glucose levels may also contribute to the development of DKD (reviewed in

Subramanian and Hirsch 2018).

1.3.1.2. Hemodynamic changes

The causes of kidney damage in diabetes are not solely attributed to the direct cellular effect of

hyperglycemia. Interaction of metabolic abnormalities with hemodynamic changes also

contributes to the development of DKD. The seminal work by Brenner’s group in experimental

models of diabetes and CKD revealed that glomerular hyperfiltration contributes to the

development of glomerulosclerosis and progression of kidney dysfunction (Hostetter, Olson et al.

1981, Hostetter, Troy et al. 1981). The renin-angiotensin-aldosterone system (RAAS) is one of

11

the main hormonal pathways that control blood pressure and fluid balance in the kidney

(reviewed in Brewster and Perazella 2004). The RAAS consists of hormones that control

systemic blood pressure and glomerular perfusion by maintaining the balance between

vasoconstriction and vasodilation of the glomerular afferent and efferent arterioles. Key

stimulants of the RAAS include low blood pressure, reduced renal perfusion pressure, low

concentration of sodium and chloride ions in the distal tubules, and increase in the activity of the

sympathetic nervous system (reviewed in Brewster and Perazella 2004). When the RAAS is

stimulated, the juxtaglomerular cells located in the glomerular arterioles release the hormone

renin into the blood, which subsequently converts the circulating substrate angiotensinogen

(secreted from the liver) to angiotensin I (Ang I). Vascular endothelial cells then convert Ang I to

Ang II by angiotensin converting enzyme (ACE), which cleaves the C-terminal dipeptide of Ang

I to form the active vasoconstrictor Ang II. Ang II in turn acts on multiple targets leading to an

increase in systemic and renal pressure, glomerular hyperperfusion, and sodium and fluid

retention (reviewed in Brewster and Perazella 2004).

The role of the RAAS in the development of DKD is well documented (reviewed in Tuttle,

Bakris et al. 2014, reviewed in Yamout, Lazich et al. 2014). Elevated levels of RAAS

components notably Ang II have been observed to be associated with renal injury and

albuminuria in rodent models and in patients with diabetes (Rudberg, Rasmussen et al. 2000,

Huang, Gallois et al. 2001). In the diabetic setting, increased Ang II stimulates both

hemodynamic and non-hemodynamic changes. Hemodynamic changes include systemic and

renal vasoconstriction, high intraglomerular pressure, and increase in permeability of the GFB.

On the other hand, non-hemodynamic abnormalities include: ROS production, glomerular and

tubule cell proliferation, accumulation of extracellular matrix, and stimulation of secretion of

growth factors such as transcription growth factor β (TGF-β), vascular endothelial growth factor

(VEGF), and endothelin (reviewed in Leehey, Singh et al. 2000). Therapeutically, several studies

have demonstrated the renoprotective effects of RAAS blockade and its critical role in slowing

disease progression in patients with DKD (Lewis, Hunsicker et al. 1993, Brenner, Cooper et al.

2001, Lewis, Hunsicker et al. 2001, Sarafidis and Ruilope 2014). Thus, to date, RAAS blockers

including ACE inhibitors (ACEi) or angiotensin receptor blockers (ARBs) are standard of care

therapy for DKD (reviewed in Yang and Xu 2017).

12

1.3.1.3. Inflammation

Inflammation is a natural response triggered by infections and tissue injury (reviewed in

Medzhitov 2008). Dysregulation of inflammatory responses can lead to irreversible tissue

damage resulting in chronic inflammatory diseases including DKD (reviewed in Medzhitov 2008,

reviewed in García-García, Getino-Melián et al. 2014). Kidney injury in DKD was traditionally

attributed to metabolic and hemodynamic changes (reviewed in Zatz, Meyer et al. 1985).

However, it was not until the 1990s that inflammatory mechanisms were proposed to be

implicated in the pathogenesis of DKD (Hasegawa, Nakano et al. 1991). Hasegawa and

colleagues showed that peritoneal macrophages secreted higher levels of proinflammatory

cytokines specifically tumor necrosis factor (TNF)-α and interleukin 1 (IL-1) when incubated

with glomerular basement membranes isolated from diabetic rats compared to non-diabetic rats,

suggesting that inflammation plays a role in the development of DKD (Hasegawa, Nakano et al.

1991). Since then, a growing body of evidence has supported the notion that DKD is an

inflammatory disease (reviewed in García-García, Getino-Melián et al. 2014, reviewed in

Donate-Correa, Martín-Núñez et al. 2015).

Several activated inflammatory molecules have been shown to mediate kidney damage and

leukocyte infiltration in diabetes including transcription factors, cytokines, chemokines, and their

receptors, and adhesion molecules (reviewed in García-García, Getino-Melián et al. 2014).

Moreover, activated inflammatory molecules have been identified in urine samples from patients

with diabetes and recently have been regarded as being predictors of kidney dysfunction in

diabetes preceding the onset of microalbuminuria (reviewed in Van, Scholey et al. 2017). Nuclear

factor kappa-light-chain-enhancer of activated B cells (NFκB) is among the key transcription

factors that regulate expression of genes implicated in the inflammatory response in DKD

(reviewed in Sanz, Sanchez-Niño et al. 2010). Activation of NFκB has been reported in kidneys

of humans and rodents with diabetes (Mezzano, Aros et al. 2004, Iwamoto, Mizuiri et al. 2005)

and has been shown to increase expression of proinflammatory cytokines, chemokines and

adhesion molecules (reviewed in Baker, Hayden et al. 2011). Hemodynamic and metabolic

changes in DKD promote secretion of proinflammatory cytokines and chemokines, which can be

produced by kidney resident cells as well as inflammatory cells including macrophages,

13

neutrophils, and lymphocytes (reviewed in García-García, Getino-Melián et al. 2014, reviewed in

Donate-Correa, Martín-Núñez et al. 2015). The actions of key inflammatory cytokines such as

IL-1, IL-6 and IL-18 have been shown to contribute to inflammatory responses in the diabetic

kidney (reviewed in Navarro-Gonzalez and Mora-Fernández 2008). For instance, upregulation of

IL-18 induces chemokine receptor expression in mesangial cells (Schwarz, Wahl et al. 2002) and

promotes tubulointerstitial lesions (reviewed in Turner, Arulkumaran et al. 2014). Moreover, it

has been demonstrated that IL-18 correlates with albuminuria in the early stages of DKD (Kim,

Song et al. 2012). Proinflammatory cytokines promote activation of adhesion molecules that

mediate intracellular binding and cell migration such as vascular cell adhesion protein 1 (VCAM-

1; also known as vascular adhesion molecule 1), intraceullar adhesion molecule 1 (ICAM-1), E-

selectin, endothelial cell-selective adhesion molecule (ESAM), and α-actinin-4 (reviewed in

Navarro-González, Mora-Fernández et al. 2011). Several chemokines, which function as

chemoattractants for inflammatory cells, are also implicated in the development of DKD,

including C-C motif chemokine 2 (CCL2) also known as monocyte chemoattractant protein 1

(MCP-1), CX3-C motif chemokine 1 (CX3CL1) also known as fractalkine, and C-C motif

chemokine 5 (CCL5) also known as regulated on activation, normal T cell expressed and secreted

(RANTES). (reviewed in Navarro-González, Mora-Fernández et al. 2011).

Upregulation of inflammatory signalling pathways notably the Janus kinase/signal transducer and

activator of transcription (JAK/STAT) and CCL2/CCR2 signalling pathways has been reported in

kidneys of patients with DKD (Morii, Fujita et al. 2003, Berthier, Zhang et al. 2009, Tarabra,

Giunti et al. 2009). Pharmacological agents have been developed to target both of these pathways

for the treatment of DKD although none of these agents have yet received regulatory approval for

this indication and their mechanisms of action remain incompletely understood (de Zeeuw,

Bekker et al. 2015, Tuttle K 2015, Menne, Eulberg et al. 2016).

1.3.1.4. Growth factors and fibrotic factors

Kidney fibrosis is the final common pathway to ESKD in all forms of CKDs including DKD

(reviewed in Choi, Ding et al. 2012). All the diverse mechanisms implicated in the pathogenesis

of DKD mentioned thus far can ultimately lead to kidney fibrosis. TGF-β is one of the main

14

growth factors that promotes formation of tissue scarring and it exists in three different isoforms:

TGF-β1, TGF-β2, and TGF-β3 (reviewed in Massague 1990). Out of the three isoforms, TGF-β1

is the main driver of kidney fibrosis (Ketteler, Noble et al. 1994). Studies in mouse models of

type 1 diabetes that were genetically engineered to express various levels of TGF-β1

demonstrated that severity of DKD is directly proportional to high expression levels of TGF-β1

(Hathaway, Gasim et al. 2015). TGF-β1 mediates fibrosis by canonical or noncanonical

signalling pathways that are beyond the scope of this thesis (Fujimoto, Maezawa et al. 2003).

However, these signalling pathways ultimately facilitate the development of glomerulosclerosis

and tubulointerstitial fibrosis in DKD by stimulation of extracellular matrix deposition,

dedifferentiation of kidney cells, increase in excretion of urine albumin, and suppression of

water, electrolyte and glucose reabsorption (reviewed in Chang, Hathaway et al. 2015).

Several research efforts have been focused on targeting TGF-β1 for the treatment of DKD. For

instance, neutralizing anti-TGF-β antibodies have been shown to mitigate glomerulosclerosis,

interstitial fibrosis, and excess matrix gene expression in mouse models of type 1 and type 2

diabetes (Sharma, Jin et al. 1996, Ziyadeh, Hoffman et al. 2000). Although TGF-β1 neutralizing

antibody treatment was observed to have renoprotective effects in experimental models of

diabetes, results from a recent phase 2 clinical trial showed that this therapeutic approach added

to RAAS inhibitors, failed to slow progression of DKD, suggesting that global blockade of TGF-

β1 signalling may not be a suitable therapeutic strategy (Voelker, Berg et al. 2017). Other growth

factors have also been identified to induce kidney fibrosis including endothelin 1, VEGF,

connective tissue growth factor (CTGF), epidermal growth factor (EGF), and platelet-derived

growth factor (PDGF) (reviewed in Kok, Falke et al. 2014, reviewed in Gagliardini, Zoja et al.

2015, reviewed in Majumder and Advani 2017).

Having highlighted the diverse mechanisms that can lead to the development of DKD, it is

important to note that these mechanisms and their underlying signalling pathways are interrelated

and whereas a large body of literature has described the multifactorial pathophysiology of DKD,

the implicated molecular mechanisms and the cell-specific roles of implicated signalling

pathways have not been fully defined.

15

1.3.2. Current available treatments for diabetic kidney disease

The current available biomarkers routinely used for the clinical assessment and the classification

of DKD are albuminuria and eGFR based on serum creatinine concentrations (reviewed in Rocco

and Berns 2012, reviewed in Tuttle, Bakris et al. 2014). Although these biomarkers have been

valuable in assessing and managing kidney diseases, they are not constantly reflective of kidney

damage and both eGFR and albuminuria have been shown to underestimate the early stages of

DKD in some cases (Krolewski, Niewczas et al. 2014). In addition to albuminuria and eGFR,

histopathological manifestations of DKD can be evaluated by kidney biopsy samples obtained

from patients although renal biopsy is not routine practice in DKD and obtaining kidney biopsy

specimen is associated with risk of severe bleeding and kidney injury (Corapi, Chen et al. 2012).

The current treatment strategies for patients with DKD aim to prevent or delay the progression of

kidney dysfunction by maintaining intensive glycemic and blood pressure control (reviewed in

Rocco and Berns 2012, reviewed in Tuttle, Bakris et al. 2014). Blockade of the RAAS with ACE

inhibitors (ACEi) or ARB medications remains standard of care therapy for patients with DKD

(reviewed in Ruggenenti, Cravedi et al. 2010, reviewed in Breyer and Susztak 2016). ACEi/ARB

therapy has been shown to be effective in diminution of albuminuria in patients with DKD and

reduces the yearly incidence of dialysis for patients with diabetes (Lewis, Hunsicker et al. 1993,

Brenner, Cooper et al. 2001, Lewis, Hunsicker et al. 2001). Although RAAS blockers have been

effective in slowing progression of kidney disease, they cannot halt progression of kidney

dysfunction and the prevalence of DKD continues to grow (Ruggenenti, Mosconi et al. 1999, de

Boer, Rue et al. 2011). Beyond RAAS blockers, efforts have been made to apply intensive

glycemic control in patients with diabetes, which has been proven to slow development and

progression of kidney disease and retinopathy (DCCT 1993). More recently, the glucose-

lowering agents SGLT2 inhibitors have demonstrated favorable effects in patients with type 2

diabetes including improved renal and cardiovascular outcomes (Wanner, Inzucchi et al. 2016,

Neal, Perkovic et al. 2017). Similarly, short-term treatment with the SGLT2 inhibitor

empagliflozin reduced kidney hyperfiltration in patients with type 1 diabetes (Cherney, Perkins et

al. 2013). Despite their benefits, however, treatment with SGLT2 inhibitors is not recommended

for advanced stage CKD and SGLT2 inhibition has been shown to be associated with increased

16

risk of ketoacidosis in patients with type 1 diabetes (Yale, Bakris et al. 2013, Kohan, Fioretto et

al. 2014, Krumholz, Wang et al. 2017, Rosenstock, Marquard et al. 2018).

As the diabetes pandemic continues to grow and given the limitations of the current available

treatments for DKD, there is an urgent need to identify new biomarkers and novel therapeutic

targets beyond standard therapy for DKD.

1.3.3. Emerging treatments for diabetic kidney disease

In an attempt to explore better therapeutic targets, researchers have investigated targeting

inflammatory signaling pathways for the treatment of DKD. Among these signaling pathways are

the JAK/STAT pathway and the CCL2/CCR2 pathway, which have been targeted in clinical trials

and have been the focus of my thesis research.

1.3.3.1. The JAK/STAT pathway

The JAK/STAT pathway is a major ubiquitously expressed signalling pathway that regulates

gene expression and fundamental cellular processes including cellular growth, proliferation,

differentiation, and immune response (Marrero, Banes-Berceli et al. 2006, reviewed in Chuang

and He 2010). Activation of the JAK/STAT pathway is initiated when an extracellular cytokine

or growth factor binds to its cognate receptor. The ligand-receptor binding results in recruitment

of JAK tyrosine kinases to the intracellular domain of the receptor followed by tyrosine

phosphorylation (reviewed in Chuang and He 2010, Ortiz-Munoz, Lopez-Parra et al. 2010).

Activated JAK kinases subsequently phosphorylate tyrosine motifs on the cytoplasmic domain of

the receptor, which serve as binding sites for STATs on the receptor. STATs are then recruited to

the receptor and activated STATs translocate to the nucleus to facilitate gene expression. The

JAK/STAT signalling cascade is illustrated in Figure 1.4. Activation of the JAK/STAT pathway

is controlled by a number of negative regulators including tyrosine phosphatases, suppressors of

cytokine signaling (SOCS) (reviewed in O'Sullivan, Liongue et al. 2007, reviewed in Yoshimura,

Naka et al. 2007, Ortiz-Munoz, Lopez-Parra et al. 2010), and protein inhibitors of activated

STAT (PIAS) (reviewed in Rakesh and Agrawal 2005, reviewed in Valentino and Pierre 2006).

17

Figure 1.4: The JAK/STAT signalling pathway. Ligand-receptor binding initiates a signalling

cascade that starts with autophosphorylation of JAK, followed by phosphorylation of STAT by

the activated JAK. Phosphorylation of STAT induces activation and dimerization. The activated

STAT dimer then translocates to the nucleus and binds to target genes to facilitate gene

expression.

18

There are four types of JAKs: JAK1, JAK2, JAK3, and tyrosine kinase 2 (TYK2); and seven

types of STATs: STAT1, STAT2, STAT3, STAT4, STAT5A, STAT5B, and STAT7, expressed

in mammals (reviewed in Darnell, Kerr et al. 1994, reviewed in Schindler and Darnell 1995,

reviewed in Chuang and He 2010, Pang, Ma et al. 2010). All types of JAK kinases are

ubiquitously expressed except for JAK3, which is expressed exclusively in hematopoietic cells

(reviewed in Yamaoka, Saharinen et al. 2004, reviewed in Kurdi and Booz 2009). Different

combinations of JAKs and STATs are specifically activated depending on the cytokine or growth

factor that initiates the signaling cascade (reviewed in Rawlings, Rosler et al. 2004).

The best-studied member of the JAK family is the cytosolic tyrosine kinase JAK2, which was

first cloned by Harpur and colleagues in 1992 (Harpur, Andres et al. 1992). The kinase JAK2 is a

130 kDa protein consisting of seven JAK homology domains (JH1-7) including: a tyrosine kinase

(JH1) domain in the C-terminus, a pseudokinase (JH2) domain that regulates the catalytic activity

of the JH1 domain, and non-catalytic JH3-7 domains that contain a FERM domain essential for

cytokine receptor binding in the N-terminus (reviewed in Amiri, Shaw et al. 2002, Banes, Shaw

et al. 2004, LaFave and Levine 2012). The primary structure of JAK2 is depicted in Figure 1.5.

19

Figure 1.5: JAK2 structure. Adapted from (Wallace and Sayeski 2006) with permission from

Springer Nature ©.

20

1.3.3.1.1. Role of the JAK/STAT pathway in diabetic kidney disease

A range of cytokines and growth factors that mediate activation of the JAK/STAT pathway have

been shown to contribute to the pathogenesis of DKD including PDGF (Wang, Wharton et al.

2000, Vij, Sharma et al. 2008), TGF- β1 (Yamamoto, Matsuda et al. 2001), IL-6 (Kretzschmar,

Dinger et al. 2004, Lim, Phan et al. 2009), EGF (Ruff-Jamison, Zhong et al. 1994), and Ang II

(Marrero, Schieffer et al. 1995, Amiri, Venema et al. 1999, Amiri, Shaw et al. 2002). Moreover,

upregulation of the JAK/STAT pathway has been reported in the diabetic kidney of both humans

and rodent models (Berthier, Zhang et al. 2009, Hodgin, Nair et al. 2013).

Several studies have highlighted the pathogenetic role of JAK/STAT activation in the kidney. In

cultured mesangial cells, studies showed that activation of the JAK/STAT pathway plays a role in

mesangial cell growth and proliferation and results in an augmentation of fibrotic growth factor

expression following exposure to Ang II and high glucose concentrations (Amiri, Shaw et al.

2002, Wang, Shaw et al. 2002). In kidney fibroblasts, JAK2 activation plays a role in collagen

synthesis and fibroblast mitogenesis and inhibition of its downstream transcription factor STAT3

was shown to reduce fibroblast activation in a model of CKD (Huang, Guh et al. 1999, Guh,

Huang et al. 2001, Huang, Guh et al. 2001, Pang, Ma et al. 2010). In podocytes, however, studies

examining the fundamental actions of the JAK/STAT pathway have been lacking and the few

studies that have explored this pathway in podocyte injury are not entirely consistent. For

instance, inducing apoptosis in cultured immortalized mouse podocytes showed that intact JAK2

is required for the pro-survival effect of erythropoietin, suggesting a protective role for JAK2

(Logar, Brinkkoetter et al. 2007). Conversely, initial studies by Brosius’s group in kidney

biopsies from patients with early DKD reported a marked increase in JAK2 expression in

glomerular cells including podocytes, suggesting that upregulation of podocyte JAK2 contributes

to the development of DKD (Berthier, Zhang et al. 2009). More recently, Brosius’s group

reported that overexpression of JAK2 in podocytes exacerbates kidney dysfunction in a mouse

model of DKD (Zhang, Nair et al. 2017). However, the detrimental effects of JAK2

overexpression in podocytes were only observed under diabetic conditions with modest effects

under normal conditions, suggesting that the effects of JAK2 expression are context-dependant

(Zhang, Nair et al. 2017).

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1.3.3.1.2. Development of JAK inhibitors

The discovery of an activating JAK2 mutation (V617F) within the region of the gene encoding

the JH2 domain as the underlying cause of myelofibrosis has increased interest in targeting the

JAK/STAT pathway therapeutically (Baxter, Scott et al. 2005, James, Ugo et al. 2005).

Consequently, the first JAK inhibitor, ruxolitinib was clinically approved in 2011 for the

treatment of myelofibrosis and other myeloproliferative disorders (reviewed in Moran 2012).

Concurrently, preclinical studies have implicated JAK/STAT pathway activation in a range of

diseases including cancer (Hedvat, Huszar et al. 2009), inflammatory conditions and autoimmune

diseases (West 2009). Following these studies, there has been a growing interest in the

development of a number of other small molecule JAK inhibitors with varying levels of

selectivity. Moreover, the multiple reports demonstrating enhanced activity of the JAK/STAT

pathway in the diabetic kidney and its association with DKD progression encouraged targeting

this pathway for treatment of DKD (Amiri, Shaw et al. 2002, Banes, Shaw et al. 2004, Berthier,

Zhang et al. 2009, Hodgin, Nair et al. 2013, Zhang, Nair et al. 2017). Baricitinib is a selective

JAK1 and JAK2 inhibitor that was initially developed for the treatment of chronic inflammatory

conditions such as rheumatoid arthritis (Keystone, Taylor et al. 2015). In 2012, Eli Lilly and

Company and Incyte Corporation launched a phase 2 repurposing trial of baricitinib for the

treatment of DKD (NCT01683409). The study involved 129 participants with type 2 DKD

already receiving RAAS blockers, with impaired kidney function (eGFR 25–75 ml/min/1.73 m2)

and overt albuminuria (>300 mg/day) (Tuttle, Brosius et al. 2018). The participants received

placebo or baricitinib orally at low-high daily doses for 24 weeks. In comparison to the placebo

group, treatment with baricitinib resulted in an approximately 40% reduction in albuminuria in

the highest dose group accompanied by a decrease in urinary proinflammatory markers including

CCL2 and CXCL10 (IP-10), which both have been implicated in DKD pathophysiology. Despite

the benefits, the study has several limitations including modest sample size and short time frame,

lack of diversity in the study population, and adverse events such as hypoglycemia, and anemia.

In addition, it is not clear whether the beneficial effects of baricitinib were specific to JAK1 or

JAK2; thus, additional studies are required to determine whether JAK2 inhibition represents a

viable treatment strategy for DKD.

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It is worth noting that while drug repurposing provides a strategic approach for finding novel

treatments for DKD, lessons from past trials caution against rushing into clinical trials without

adequate preclinical studies. The importance of rigorous evaluation of therapeutic targets in

preclinical studies is evidenced by the disappointing clinical outcome of the Bardoxolone

Methyl Evaluation in Patients with Chronic Kidney Disease and Type 2 Diabetes Mellitus: the

Occurrence of Renal Events (BEACON) trial (De Zeeuw, Akizawa et al. 2013). In the phase 3

BEACON trial, bardoxolone methyl, an anti-oxidant and anti-inflammatory agent, was

evaluated for its effects on delaying progression of DKD to ESKD and cardiovascular death.

Although the data from a phase 2 trial showed that bardoxolone methyl treatment increased

eGFR (Pergola, Raskin et al. 2011), the phase 3 trial was terminated prematurely due to severe

adverse effects including mortality, heart failure, high blood pressure, and increase in

albuminuria (De Zeeuw, Akizawa et al. 2013). These severe adverse events were recapitulated

in animal studies (Zoja, Corna et al. 2012). More recently, the United Kingdom Heart and

Renal Protection-III (UK HARP-III) trial aiming to repurpose and compare the effects of

sacubitril/valsartan (approved for the treatment of patients with heart failure) versus irbesartan

(a licenced ARB for DKD) failed to have any additional effects on kidney function in patients

with CKD (Haynes, Judge et al. 2018). Taken together, these findings highlight the need for

proper understanding of pathomechanisms in preclinical studies, which may inform our

interpretation of clinical trial results.

1.3.3.2. CCL2/CCR2 signaling pathway

Migration of immune cells to the sites of inflammation in the kidney is one of the early events

that lead to kidney damage in diabetes (reviewed in Galkina and Ley 2006). In the diabetic

setting, hemodynamic and metabolic changes promote secretion of a wide range of

proinflammatory cytokines and chemokines that mediate kidney injury through autocrine,

paracrine, or juxtacrine actions (reviewed in Navarro-Gonzalez and Mora-Fernández 2008).

MCP-1 (also known and hereafter referred to as CCL2) is one of the most extensively studied

chemokines playing a major role in migration of monocytes and macrophages (reviewed in

Panzer, Steinmetz et al. 2006). Upon stimulation, CCL2 is secreted and binds to its cognate

receptor CCR2, which is predominantly expressed by monocytes, to mediate

23

monocyte/macrophage recruitment to inflammatory sites (reviewed in Panzer, Steinmetz et al.

2006). Upregulation of CCL2 and its cognate receptor CCR2 has been reported in kidney

biopsies from patients with DKD (Wada, Furuichi et al. 2000, Tarabra, Giunti et al. 2009). An

increase in urine CCL2 excretion has been observed in patients with DKD, which positively

correlated with albuminuria (Tashiro, Koyanagi et al. 2002). Moreover, knockout of CCL2 has

been shown to play a protective role in rodent models of diabetes including reduced

macrophage infiltration and attenuated albuminuria (Chow, Nikolic-Paterson et al. 2007,

Tarabra, Giunti et al. 2009).

A number of cell types in the kidney express CCL2 including glomerular endothelial cells

(Kakizaki, Waga et al. 1995), mesangial cells (Gruden, Setti et al. 2005), podocytes (Gu,

Hagiwara et al. 2005), and tubule epithelial cells (Wada, Furuichi et al. 2000, Mezzano, Aros

et al. 2004). However, podocytes are the predominant source of CCL2 in the glomerulus

(Prodjosudjadi, Gerritsma et al. 1995, Chow, Ozols et al. 2004, Hartner, Veelken et al. 2005) .

Exposure of mesangial cells to CCL2 results in increased expression of the adhesion molecule

ICAM-1 and interstitial matrix molecules such as fibronectin (Giunti, Pinach et al. 2006,

Giunti, Tesch et al. 2008). Similarly, CCL2 induces ICAM-1 expression and IL-6 secretion in

human tubule epithelial cells (Viedt, Dechend et al. 2002). Activation of CCL2/CCR2

signalling caused a migratory response in podocytes with marked reduction in the expression

of the podocyte cytoskeleton protein, nephrin (Burt, Salvidio et al. 2007), and was observed to

be implicated in diabetes-induced podocyte apoptosis (Nam, Paeng et al. 2012). Data from

recent studies in transgenic mice with podocyte-specific CCR2 overexpression demonstrated

that CCL2/CCR2 contributes to the pathogenesis of DKD by directly affecting podocytes

possibly through podocyte loss, suggesting that the CCL2/CCR2 system plays a role in the

renal glomerulus independently of monocyte/macrophage recruitment (Awad, Kinsey et al.

2011, You, Gao et al. 2017).

1.3.3.2.1. Development of CCL2/CCR2 blockers

Targeting inflammatory pathways as a new strategy to slow DKD along with the implication

of CCL2/CCR2 in DKD pathophysiology has led the pharmaceutical industry to develop

24

CCL2 and CCR2 inhibitors for these indications. Findings from recent clinical trials aimed at

inhibition of CCL2/CCR2 signalling for treatment of DKD appear promising. In a phase 2

clinical trial, inhibition of CCL2/CCR2 signalling with the CCL2 antagonist emapticap pegol

(NOX-E36) significantly lowered urinary albumin/creatinine ratio (UACR) and hemoglobin

A1c (HbA1c) in patients with type 2 diabetes and albuminuria (Menne, Eulberg et al. 2016).

Similarly, inhibition of CCL2/CCR2 signalling with the selective CCR2 antagonist CCX140-B

decreased UACR after 52 weeks of treatment in patients with type 2 diabetes (de Zeeuw,

Bekker et al. 2015). Recently, two CCR2/CCR5 antagonists have been investigated in clinical

trials although the data from these trials are yet to be published (NCT01752985,

NCT01712061).

Although these developed anti-inflammatory agents may be promising treatments for DKD,

their mechanisms of benefit in the kidney are not completely understood. Moreover, in each of

the examples I have cited of promising anti-inflammatory therapies for DKD, there has been a

central role of glomerular podocytes as either sites of action (JAK/STAT) or sites of

expression (CCL2).

1.4. Understanding podocyte (patho)biology: a key driver of therapeutic interventions for glomerular diseases

Podocytes are one of four resident cell types in the kidney glomerulus, along with endothelial

cells, mesangial cells, and parietal epithelial cells. They are important for kidney development

and normal kidney homeostasis and their injury is implicated in a range of kidney diseases.

Podocytes are highly specialized epithelial cells that form the final layer of the glomerular

filtration barrier, and therefore they act as the last gatekeeper by allowing passage of water and

small solutes and preventing large proteins from passing through the filtration barrier (reviewed

in Pavenstadt, Kriz et al. 2003). Over two decades ago, a landmark study by Pagtalunan and

colleagues demonstrated that podocyte loss plays a role in kidney disease progression in patients

with diabetes (Pagtalunan, Miller et al. 1997). Following this study, other research groups have

shown that podocyte depletion correlates with proteinuria, glomerulosclerosis, and kidney disease

progression in glomerular diseases (Lemley, Lafayette et al. 2002, Wharram, Goyal et al. 2005,

25

Weil, Lemley et al. 2012). Moreover, podocyte injury has been shown to contribute to the

pathogenesis of multiple glomerular diseases including membranous nephropathy (MN), minimal

change disease (MCD), focal segmental glomerulosclerosis (FSGS), and DKD (reviewed in

Mallipattu and He 2016).

Podocyte injury is far from the sole cause of glomerular disease and other glomerular cells,

notably mesangial cells, likely play a greater role in the progression of glomerular scarring

(Nahman, Leonhart et al. 1992, Amiri, Shaw et al. 2002, Giunti, Tesch et al. 2008). However,

there are a number of aspects about podocytes that make them particularly useful to model

(patho)biological mechanisms in glomerular diseases. Firstly, they are terminally differentiated

(reviewed in Mundel and Kriz 1995). Because they cannot regenerate, podocytes employ other

strategies to maintain their health. In particular, they have a high rate of autophagy, a self-repair

process that removes unnecessary or dysfunctional cellular components (Sato, Kitamura et al.

2006). Secondly, they communicate closely with other cells within the glomerulus (especially

endothelial cells), which makes them a good model to study paracrine signaling mechanisms

(reviewed in Siddiqi and Advani 2013). Thirdly, they are amenable to in vivo genetic

manipulation, thus the specific role of specific genes can be studied in experimental rodents

(reviewed in Bierzynska, Soderquest et al. 2015). Although advances in podocyte research in

recent decades have improved our understanding of the glomerular filtration process and helped

to unravel the underlying mechanisms of glomerular diseases, a better understanding of podocyte

biology in health and disease may lead to the discovery of new avenues to improve podocyte

function in glomerular diseases.

1.4.1. Podocyte structure and function

Podocytes have a fascinating cellular architecture that is uniquely tailored to their biological role

in the kidney (Figure 1.6). Under electron microscopy, podocytes can be seen to have a zipper-

like morphology that covers the GFB, which reflects their crucial role in preserving glomerular

integrity and function (Figure 6) (reviewed in Mundel and Shankland 2002). The term ‘podocyte’

derives from the Greek roots ‘podo’ (foot) and ‘cyte’ (cell) (reviewed in Weller and Wiley 1985).

A single podocyte consists of a cell body, major processes, and foot processes (reviewed in Kriz,

26

Kobayashi et al. 1998). The cell body faces the urinary space and it contains the main organelles

of the cell including nucleus, Golgi apparatus, rough and smooth endoplasmic reticulum,

lysosomes, and mitochondria (reviewed in Kriz, Kobayashi et al. 1998). Major processes

branching off the cell body are enriched in microtubules and they split into foot processes, which

are enriched in actin filaments. Podocyte foot processes interdigitate on the outer surface of the

GBM and they are linked by a unique junction referred to as the slit diaphragm (SD). The SD

consists of several proteins that play a pivotal role in maintaining the integrity of the podocyte

cytoskeleton (Kelly, Aaltonen et al. 2002).

Figure 1.6: The intricate beauty of podocytes. A scanning electron micrograph of podocytes

demonstrates podocyte morphology across the glomerulus. A single podocyte consists of a cell

body (CB), major processes (MP), secondary processes (SP), and foot processes (FP)

interdigitating with adjacent podocyte FP. Adapted from (Welsh and Saleem 2012) with

copyright permission from Springer Nature ©.

27

Advances in genetic tools allowed identification of podocyte cytoskeleton proteins such as

nephrin, podocin, and synaptopdin, and they commonly serve as podocyte-specific markers

(reviewed in Welsh and Saleem 2012). Dysregulation of the molecular machinery of the

podocyte cytoskeleton results in abnormal podocyte morphology notably foot process effacement

(FPE), which is one of the key features observed in proteinuric glomerular diseases (reviewed in

Mundel and Shankland 2002).

1.4.2. Podocytopathies in glomerular diseases

Podocytopathy is a term used to refer to a group of glomerular diseases that develop as a result of

podocyte loss or dysfunction (Pollak 2002). The unique position of podocytes in the glomerulus

and their inability to proliferate make them prone to various stressors (reviewed in Mundel and

Shankland 2002). When these stressors exceed the podocyte physiological limit, development of

podocytopathy occurs, which can be manifested as podocyte cytoskeleton remodeling, podocyte

loss, podocyte dedifferentiation, and abnormal crosstalk between podocytes and adjacent

glomerular cells.

One of the most common morphological features of podocytopathies is FPE, which can result

from disorganization of the podocyte cytoskeleton and impaired SD function (reviewed in

Brinkkoetter, Ising et al. 2013). Alterations in key podocyte cytoskeleton and SD genes have

been implicated in a range of glomerular diseases including DKD, MCD, FSGS, and MN

(reviewed in Kerjaschki 2001). For instance, hemodynamic and metabolic changes in DKD have

been shown to reduce expression of proteins essential for SD function such as nephrin, resulting

in FPE and an increase in albuminuria (Langham, Kelly et al. 2002, Doublier, Salvidio et al.

2003). Moreover, mutations in the gene encoding nephrin, NPHS1 has been found to cause

congenital nephrotic syndrome, which was first identified in Finnish patients and is characterized

by massive proteinuria shortly after birth (Huttunen, 1976; Kestilä, Lenkkeri et al., 1998). Other

mutations in genes critical for the actin cytoskeleton have been also identified including the gene

encoding α-actinin, which has been shown to contribute to the development of FSGS (Kaplan,

Kim et al. 2000). In addition to alterations in expression of genes essential for the podocyte

cytoskeleton, mechanical forces such as increased glomerular capillary pressure can also result in

28

remodeling of the podocyte cytoskeleton leading to podocyte loss and glomerulosclerosis (Kriz

and Lemley 2015).

Podocyte loss has been shown to contribute to proteinuric glomerular diseases (reviewed in

Tharaux and Huber 2012). Although the underlying mechanism of podocyte loss has been the

subject of debate, several studies have demonstrated that podocyte loss can result from podocyte

apoptosis or detachment from the GBM. Most of the data supporting podocyte apoptosis as a

leading mechanism for podocyte loss come from in vitro studies whereas podocyte apoptosis is

rarely observed in vivo, suggesting that podocyte loss is most likely attributable to detachment

(reviewed in Braun, Becker et al. 2016). Podocyte detachment was first observed in seminal

studies conducted in urine samples from patients with kidney diseases (Hara, Yamamoto et al.

1995, Hara, Yanagihara et al. 1998, Nakamura, Ushiyama et al. 2000, Nakamura, Ushiyama et al.

2000, Nakamura, Ushiyama et al. 2000). In these studies, podocytes were detected in urine

sediments from patients with several forms of glomerular diseases. In a subsequent study, the

investigators showed that the majority of the podocytes found in urine samples from patients with

glomerular diseases are viable, suggesting that podocyte depletion results from detachment from

the GBM rather than apoptosis (Vogelmann, Nelson et al. 2003). Irrespective of its underlying

mechanisms, podocyte loss leads to ‘bare’ regions of the GBM, which causes the denuded GBM

to come into direct contact with the Bowman’s capsule contributing to the development of FSGS

(reviewed in Kriz, Gretz et al. 1998).

Podocytes normally arise from mesenchymal cells via a mesenchymal–epithelial-transition

(MET) event (reviewed in May, Saleem et al. 2014). Mature podocytes have to be maintained in

their uniquely differentiated state to function properly. However, in the disease setting, mature

podocytes can undergo dedifferentiation, a process whereby cells lose their differentiated

characteristics to gain features of mesenchymal cells (reviewed in Jopling, Boue et al. 2011).

Reactivation of developmental pathways has been shown to contribute to the development of

kidney fibrosis (reviewed in Edeling, Ragi et al. 2016). Moreover, the phenotypic changes seen in

dedifferentiated podocytes have been observed to be associated with podocyte dysfunction and

proteinuria (Li, Kang et al. 2008). Recent work from our lab showed that reactivation of

developmental pathways in podocytes sensitized mice to glomerular disease and this has been

29

partly attributed to a decrease in the repressive histone H3 lysine 27 trimethylation (H3K27me3)

mark (Majumder, Thieme et al. 2018).

Accumulating evidence also supports the role of crosstalk between different glomerular cells in

the development and maintenance of glomerular function (reviewed in Menon, Chuang et al.

2012, reviewed in Siddiqi and Advani 2013). The podocyte response to external signals such as

growth factors or hormones and their communication with neighbouring cells are crucial for

podocyte health. Dysregulation of paracrine signalling pathways between podocytes and resident

cells such as endothelial cells in the glomerulus has been shown to contribute to podocytopathy

and heavy albuminuria in diabetic mice (Yuen, Stead et al. 2012).

1.4.3. Podocytes and repair mechanisms

Given that podocytes are terminally differentiated cells, they employ certain strategies to

maintain their health and adapt to stress. For instance, they have high levels of autophagy under

basal conditions compared to other cell types in the kidney (Asanuma, Tanida et al. 2003,

Mizushima, Yamamoto et al. 2004, Sato, Kitamura et al. 2005, Periyasamy-Thandavan, Jiang et

al. 2008, Hartleben, Gödel et al. 2010, Kimura, Takabatake et al. 2011). Autophagy is a self-

degradative process that involves delivering damaged proteins and organelles into double

membrane structures known as autophagosomes to lysosomes for digestion (reviewed in

Klionsky 2005). The presence of autophagosomes in podocytes has been reported in cultured

cells (Lemley, Lafayette et al. 2002, Cinà, Onay et al. 2012), in mice (Mizushima, Yamamoto et

al. 2004), and in human kidney biopsies (Sato, Kitamura et al. 2006). Several studies have

emphasized the similarity between podocytes and neuronal cells (reviewed in Kobayashi, Gao et

al. 2004, Rastaldi, Armelloni et al. 2006). Similar to neurons, autophagy has been recognized as a

key homeostatic mechanism to maintain podocyte integrity that is particularly essential for

postmitotic cells (reviewed in Hartleben, Wanner et al. 2014). A study conducted by Hartleben

and colleagues demonstrated that podocyte-specific deletion of autophagy related gene 5 (Atg5)

resulted in impaired autophagy, a remarkable increase of proteinuria, and glomerulosclerosis

(Hartleben, Gödel et al. 2010). Moreover, autophagy was shown to play a protective role in

hyperglycemia-induced podocyte injury (Fang, Zhou et al. 2013).

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1.4.3.1. The autophagy-lysosomal pathway

Autophagy is a tightly regulated and conserved cellular process essential for eukaryotic cells to

survive and cope with stress. This process enables the cells to digest and recycle their own

damaged components, hence, the name autophagy– a Greek term that means self-eating

(reviewed in Klionsky 2008). There are three types of autophagy: microautophagy, chaperone-

mediated autophagy, and macroautophagy (reviewed in Mizushima and Komatsu 2011).

Microautophagy involves the direct lysosomal engulfment of cytoplasmic materials whereas

chaperone-mediated autophagy is a selective process that involves lysosomal degradation of

unfolded proteins delivered via specific chaperone proteins. Of the three types, the best-studied

and characterized process is macroautophagy, which is generally referred to as autophagy.

Autophagy is a dynamic process that involves multiple steps (reviewed in Mizushima and

Komatsu 2011). Activation of autophagy is normally induced by cellular stress or starvation. The

process begins by formation of a cup-like double-membrane structure that originates from the

endoplasmic reticulum known as a phagophore, which sequesters a portion of the cytoplasm.

This is followed by elongation and nucleation of the phagophore to form a sealed double-

membrane vesicle known as an autophagosome, which contains damaged organelles and cellular

components destined for degradation. The autophagosome then fuses with lysosomes for

digestion and the degraded substances are subsequently recycled back to the cytoplasm to be used

as a source of energy. A summary of autophagy steps is depicted in Figure 1.7.

31

Figure 1.7: Autophagy process. Activation of autophagy initiates a series of steps: 1) Initiation,

which involves assembly of initiation protein complexes and formation of the phagophore; 2)

Autophagosome formation, which involves elongation of the phagophore and autophagosome

maturation mediated by LC3 and ATG conjugation systems (recognition of damaged organelles

and cellular components is mediated by ubiquitin like proteins such as p62); 3) Fusion, a step in

which the autophagosome fuses with a lysosome for cargo delivery; and 4) Degradation, the final

step in which lysosomal enzymes facilitate breakdown of damaged cellular materials into

building blocks for recycling.

Each of the steps in the autophagy-lysosomal pathway is highly regulated by specific molecular

machinery. Several ATG proteins and protein complexes essential for autophagy processes have

been identified (reviewed in Yang and Klionsky 2010). Formation of the phagophore is regulated

by two initiation complexes: Unc-51-like autophagy activating kinase 1 and 2 (ULK1/2)

complex, and the class III phosphatidylinositol 3-kinase (PtdIns3K) complex. Activation of

ULK1 promotes recruitment of the initiation complexes essential for phagophore formation.

Phagophore elongation and autophagosome formation is mediated by microtubule-associated

protein 1 light chain 3 (LC3, the mammalian homologue of yeast ATG8) and ATG5-ATG12-

32

ATG16 conjugation systems. Activation of autophagy stimulates cleavage of the inactive pro-

LC3 precursor by the cysteine protease Atg4 to form the cytosolic protein LC3-I, which is then

converted to LC3-II via conjugation with phosphatidylethanolamine (PE). The lipidated LC3-II

acts as a cargo receptor and is incorporated into the autophagosomal membrane and therefore, it

is one of the reliable autophagosome markers commonly used to study autophagy (Kabeya,

Mizushima et al. 2000). The Atg5–Atg12 conjugation system is required for membrane tethering

and facilitates formation of LC3-II. Increase in LC3-II reflects an upregulation of autophagy

either as a result of increase in autophagic activity or a defect in autophagy completion. To

differentiate between the two, autophagy inhibitors and other markers are commonly used. For

instance, p62, a ubiquitin- and LC3-binding protein typically destined for degradation in the

lysosome, is used as a marker to assess autophagy turnover. Accumulation of p62 is indicative of

defective autophagic degradation. Moreover, chemical autophagy inhibitors (e.g. bafilomycin A1

and wortmannin) are also used in combination with autophagy markers to evaluate autophagic

activity.

The serine/threonine kinase mTOR complex 1 (mTORC1) plays a central role in autophagy

regulation (Roczniak-Ferguson, Petit et al. 2012). Under fed conditions, mTORC1 suppresses

autophagy via phosphorylation-dependent inhibition of ULK1/2 and class III PtdIns3K

complexes. At the transcriptional level, mTORC1 regulates the autophagy-lysosomal pathway by

regulating the activity of the transcription factor TFEB, a master regulator of autophagy and

lysosomal biogenesis (Settembre, Di Malta et al. 2011). Under basal conditions, mTORC1

phosphorylates TFEB at the lysosomal surface to remain in its inactive state in the cytoplasm.

However, when autophagy is activated, TFEB de-phosphorylates and translocates to the nucleus

to coordinate expression of genes essential for autophagy and lysosomal function.

1.4.3.2. Role of TFEB: a major regulator of the autophagy-lysosomal pathway

TFEB is a member of the microphthalmia (MiT) family of basic helix-loop-helix and leucine-

zipper transcription factors (reviewed in Steingrímsson, Copeland et al. 2004). Work by

Ballabio’s group nearly a decade ago revealed that expression of lysosomal genes is coordinated

at the transcription levels (Sardiello, Palmieri et al. 2009). In this study, the investigators

33

discovered that lysosomal genes share a palindromic conserved 10-base E-box-like sequence in

their promoter region, named coordinated lysosomal expression and regulation (CLEAR)

network, and that this motif was shown to be regulated by and bound to a single transcription

factor (i.e. TFEB). Moreover, TFEB overexpression in HeLa cells resulted in a significant

increase in the mRNA levels and the enzymatic activity of lysosomal genes (Sardiello, Palmieri

et al. 2009). Following this study, the same group showed that TFEB also regulates cellular

clearance pathways including autophagy and lysosomal exocytosis (Palmieri, Impey et al. 2011,

Settembre, Di Malta et al. 2011). TFEB has been shown to induce autophagy by enhancing the

expression of genes implicated in various autophagic steps including autophagosome synthesis

and autophagosome-lysosome fusion (Settembre, Di Malta et al. 2011). Furthermore, TFEB

activates the lysosomal Ca2+ channel Mucolipin 1 (MCOLN1) essential for Ca2+ release in

lysosomal exocytosis, a process that involves removal of lysosomal contents outside the cell via

fusion of lysosomes with the plasma membrane (Medina, Fraldi et al. 2011).

The importance of TFEB has been evidenced by the embryonic lethality of TFEB knockout in

mice (Steingrímsson, Tessarollo et al. 1998) and by subsequent studies that have explored the

tissue specific role of TFEB. The role of TFEB has been described in the liver (Settembre, De

Cegli et al. 2013), bone tissue (Ferron, Settembre et al. 2013), skeletal muscle (Mansueto,

Armani et al. 2017), and immune system (Visvikis, Ihuegbu et al. 2014, Samie and Cresswell

2015). Deletion of TFEB in the liver was shown to impair lipid break down and its

overexpression was able to prevent weight gain and enhance lipid catabolism in two mouse

models of obesity (Settembre, De Cegli et al. 2013). Moreover, absence of TFEB in osteoclasts

was demonstrated to cause a defect in bone resorption and reduction in expression of lysosomal

genes, highlighting the role of TFEB in lysosomal function in these cells (Ferron, Settembre et al.

2013). Activation of TFEB in macrophages and dendritic cells was reported to be required for

host defense in response to bacterial infection, suggesting that TFEB plays a protective role in the

immune response (Visvikis, Ihuegbu et al. 2014, Samie and Cresswell 2015). The protective role

of TFEB was also reported in skeletal muscle in which TFEB was observed to control glucose

homeostasis and mitochondrial biogenesis (Mansueto, Armani et al. 2017).

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Although several studies have demonstrated that gene translocation in MiT family transcription

factors including TFEB is implicated in kidney cancers (reviewed in Kauffman, Ricketts et al.

2014, Argani 2015), comparatively little has been known about the functional role of TFEB in

the kidney and its implication in CKD. However, one study demonstrated that activation of TFEB

restored lysosomal dysfunction in proximal tubule cells isolated from urine of patients with

nephropathic cystinosis, a lysosomal storage disease caused by mutation in the lysosomal enzyme

cystinosin (CSTN) (Rega, Polishchuk et al. 2016). Moreover, decreased nuclear TFEB

localization was recently reported in podocytes from mice and humans with DKD and TFEB

overexpression was shown to rescue impaired autophagy completion in cultured podocytes

induced by advanced glycation end products (AGEs) (Zhao, Chen et al. 2018). In a separate

study, inhibition of TFEB has been reported to suppress podocyte autophagy following amino

acid starvation (Chen, Zhao et al. 2018). Collectively, these studies highlight the important role

of TFEB in maintaining cellular homeostasis in the kidney. Understanding the cell specific role

of TFEB in the kidney and enhancing cellular clearance by modulating TFEB activity may serve

as an attractive therapeutic strategy for CKD.

1.4.4. Podocytes as a model for paracrine communication

The integrity of the kidney glomerulus depends on the normal communication between its

components. Each of the glomerular components, which include mesangial cells, endothelial

cells, GBM, podocytes and parietal cells, has a unique position in the glomerulus tailored to their

function. Mesangial cells are located in between the glomerular capillaries to maintain the

structure and function of the capillary loops (reviewed in Scott and Quaggin 2015). The

glomerular vasculature is separated from the urine by the GBM, a thick matrix primarily made of

collagen IV and laminin, that acts as a scaffold for both glomerular endothelial cells lining the

glomerular capillaries and podocytes facing the urinary space; and all together they form the GFB

(reviewed in Miner 2012). Parietal epithelial cells line Bowman’s capsule and they have been

proposed to be involved in podocyte regeneration (reviewed in Shankland, Freedman et al. 2017).

Several studies have investigated crosstalk between podocytes and each of these components. For

instance, podocytes have been shown to be the principal source of collagen IV, which is one of

the essential proteins present in the fully mature GBM (Abrahamson, Hudson et al. 2009).

35

Moreover, podocyte-specific overexpression of laminin β1 (Lamβ1), a homolog of the major

laminin in the GBM known as Lamβ2, has been shown to prevent the development of nephrotic

syndrome in Lamβ2 knockout mice, a model of Pierson syndrome caused by Lamβ2 mutation in

humans (Suh, Jarad et al. 2011). Furthermore, podocyte-generated growth factors have been

shown to contribute to the development of mesangial matrix accumulation and

glomerulosclerosis in glomerular diseases, highlighting possible paracrine effects on mesangial

cells (Eremina, Cui et al. 2006, Lenoir, Milon et al. 2014). Podocytes have been also implicated

in activation of parietal epithelial cells in crescentic glomerulonephritis, demonstrating the

interaction between podocytes and parietal epithelial cells (reviewed in Shankland, Smeets et al.

2014). Additionally, dysregulated podocyte-endothelial crosstalk has been observed to contribute

to the development of DKD (Eremina, Sood et al. 2003, Yuen, Stead et al. 2012). The intimate

association of podocytes with glomerular cells, notably endothelial cells and the availability of

genetic tools that allow alterations of gene expression in podocytes make podocytes and

endothelial cells an ideal model to study paracrine communication within the glomerulus.

1.5. Glomerular endothelial cells

The vascular endothelium is a vital organ that plays multiple roles in the body to maintain

vascular homeostasis. Under physiological conditions, the vascular endothelium secretes

vasodilators (e.g. nitric oxide) and vasoconstrictors (e.g. endothelin) to control vascular tone

(reviewed in Deanfield, Halcox et al. 2007). Moreover, the vascular endothelium regulates

biological processes essential for maintaining vascular health including thrombosis, platelet

activation, leukocyte interaction, and fibrinolysis (reviewed in Deanfield, Halcox et al. 2007).

Being constantly exposed to the blood stream in the capillaries, glomerular endothelial cells are

placed at the front line of the filtration process and therefore, their integrity is crucial for normal

glomerular function. Glomerular endothelial cells control transcellular permeability through their

sieve-like fenestrations covered by a negatively charged layer of glycocalyx and an outer layer of

proteins known as the endothelial surface layer (ESL) (reviewed in Pries, Secomb et al. 2000,

reviewed in Reitsma, Slaaf et al. 2007). These integral components of the endothelium play a

central role in vascular permeability and regulate paracrine signalling between endothelial cells

36

and circulating blood or surrounding tissues (reviewed in Satchell and Braet 2009). The

glycocalyx is made up of glycoproteins and proteoglycans and is enriched with heparan sulphate

proteoglycans responsible for the negative charge characteristics of the endothelium (reviewed in

Reitsma, Slaaf et al. 2007). Disruption of the glycocalyx results in an increase in vascular protein

permeability, suggesting that the glycocalyx has an important role in restricting the passage of

large molecules across the filtration barrier (Singh, Satchell et al. 2007).

The role of glomerular endothelial cells extends beyond maintaining vascular homeostasis. For

instance, glomerular endothelial cells contribute to GBM formation (reviewed in Abrahamson

2012). Moreover, knockout studies have revealed the influence of glomerular endothelial cells on

mesangial cell growth via the actions of the growth factor platelet-derived growth factor B

(PDGF-B) and its receptor PDGFR-β (reviewed in Floege, Eitner et al. 2008). Mice lacking

PDGF-B in glomerular endothelial cells fail to form mesangial cells and similar phenotypes has

also been observed in PDGFR-β knockout mice (Leveen, Pekny et al. 1994, Soriano 1994).

Glomerular endothelial cells secrete and respond to a wide range of signalling factors that are

important for maintaining vascular tone and glomerular homeostasis. Nitric oxide (NO) is one of

the important factors synthesized by the enzymatic action of endothelial NO synthase (eNOS)

that mediates vasodilation, inhibition of inflammation, thrombosis, and cellular proliferation

(reviewed in Takahashi and Harris 2014). Loss of eNOS has been shown to predispose podocytes

to acute injury and accelerates kidney damage in diabetes, suggesting that the integrity of

glomerular endothelial cells is important for preserving podocyte function (Yuen, Stead et al.

2012). The role of glomerular endothelial cells in maintaining podocyte health has also been

evidenced by the protective role of the endothelial thrombomodulin–protein C system implicated

in thrombosis, inflammation, and fibrinolysis (Esmon 2001, Isermann, Vinnikov et al. 2007).

Increased thrombomodulin-mediated activation of protein C inhibits endothelial and podocyte

apoptosis, and protects against kidney dysfunction in diabetes (Isermann, Vinnikov et al. 2007).

Emerging research indicates that paracrine communication between podocytes and glomerular

endothelial cells is crucial for maintaining the integrity of the GFB, and abnormal podocyte-

endothelial crosstalk has been proposed as contributing to the development of albuminuria in

DKD (reviewed in Siddiqi and Advani 2013).

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1.5.1. Podocyte-glomerular endothelial cell crosstalk

Glomerular endothelial cells are an integral component of the glomerular filtration barrier. Unlike

other endothelial cells, glomerular endothelial cells are highly specialized fenestrated cells lining

the glomerular capillaries with a glycocalyx layer coating the luminal surface essential for

regulating vascular permeability (Singh, Satchell et al. 2007). Loss- and gain-of- function studies

have identified several paracrine factors that mediate podocyte-endothelial crosstalk including

stromal cell–derived factor-1 (SDF-1) (Takabatake, Sugiyama et al. 2009), angiopoietins (Davis,

Dei Cas et al. 2007, Jeansson, Gawlik et al. 2011), semaphorins (Reidy, Villegas et al. 2009), and

VEGF (Eremina, Sood et al. 2003, Eremina, Jefferson et al. 2008). Here, the role of VEGF and

other mediators implicated in podocyte-endothelial crosstalk are reviewed as a means of

highlighting the biological importance of podocyte-endothelial communication.

1.5.1.1. Role of VEGF

VEGF is one of the podocyte-derived factors that has been most extensively studied in the

glomerulus (reviewed in Advani 2014, reviewed in Bartlett, Jeansson et al. 2016, reviewed in

Majumder and Advani 2017). VEGF is a member of the VEGF/ PDGF family that plays an

important role in blood vessel (patho)biology. There are five members of the VEGF family

identified in mammals including VEGF-A, VEGF-B, VEGF-C, VEGF-D and placental growth

factor (PGF). VEGF-A is the best-studied member of the VEGF family and its role is critical for

glomerular development and function. Although VEGF-A expression has been reported in other

cell types in the kidney, podocytes are the major source of VEGF-A in the renal glomerulus

(Cooper, Vranes et al. 1999). VEGF-A exerts its actions via binding to two cognate receptors

VEGFR-1 and VEGFR-2, and two co-receptors neuropilin-1 and neuropilin-2 (reviewed in

Advani 2014). However, most of the biological actions of VEGF-A occur mainly through

signaling by binding to VEGF-R2, which is expressed by the glomerular endothelial cells

(Cooper, Vranes et al. 1999). VEGF-A plays a central role in blood vessel formation,

angiogenesis, and proliferation, differentiation, and survival of endothelial cells (reviewed in

Eremina and Quaggin 2004). Moreover, the actions of VEGF-A have been reported in several

physiological and pathological conditions including tumor angiogenesis (reviewed in Ferrara

38

2002), wound healing (Nissen, Polverini et al. 1998), diabetic retinopathy (Awata, Inoue et al.

2002), age-related macular degeneration (Heier, Brown et al. 2012), and glomerular diseases

(reviewed in Advani 2014).

VEGF-A has five different isoforms in humans as a result of alternative splicing including

VEGF121, VEGF145, VEGF165, VEGF189, and VEGF206 (reviewed in Majumder and Advani 2017).

In humans, VEGF-A165 is the most abundant isoform. The paracrine effect of podocyte-secreted

VEGF-A on glomerular endothelial cells has been well documented (reviewed in Advani and

Gilbert 2012, reviewed in Siddiqi and Advani 2013, reviewed in Advani 2014, reviewed in

Bartlett, Jeansson et al. 2016, reviewed in Majumder and Advani 2017). Podocyte-derived VEGF

has a primary role in fenestrae formation (Breier, Albrecht et al. 1992, Esser, Lampugnani et al.

1998, reviewed in Quaggin and Kreidberg 2008). Moreover, upregulation of both VEGF-A and

VEGFR-2 has been reported in diabetic rodents (Cooper, Vranes et al. 1999, Braun, Kardon et al.

2001, Cheng, Wang et al. 2002), and its blockade has been demonstrated to attenuate albuminuria

and kidney dysfunction in experimental models of diabetes (De Vriese, TILTON et al. 2001,

Flyvbjerg, Dagnæs-Hansen et al. 2002). Gene manipulations of VEGF-A in the podocytes of

experimental animals and later studies in human kidney biopsies have improved our

understanding of VEGF-A role in the glomerulus. Complete knockout of VEGF-A in podocytes

was shown to result in impaired formation of the GFB and prenatal death whereas podocyte-

specific VEGF-A heterozygous deletion causes proteinuria and endotheliosis (Eremina, Sood et

al. 2003). Overexpression of VEGF-A165 in podocytes also had detrimental effects in the kidney

including causing progressive proteinuria, and considerable glomerular hypertrophy as a result of

podocyte hypertrophy, and augmented proliferation of mesangial cells and glomerular capillaries

(Liu, Morimoto et al. 2007).

1.5.1.2. Other mediators of endothelial-podocyte communication

During embryonic development, podocytes produce the chemokine SDF-1 (also known as

chemokine C-X-C motif ligand 12 (CXCL12) , which binds to the G-protein coupled receptor

CXCR4 expressed by endothelial cells to mediate renal vessel formation (Takabatake, Sugiyama

et al. 2009). Blocking SDF-1/CXCR4 signalling was shown to prevent progression of

39

glomerulosclerosis and albuminuria in an experimental model of diabetes (Sayyed, Hägele et al.

2009).

Angiopoietins are another family of vascular growth factors implicated in normal vascular

development. Angiopoietin-1 and angiopoietin-2 are two members of angiopoietin proteins that

have been well investigated. Both angiopoietin-1 and angiopoietin-2 mediate their actions via

binding to their tyrosine kinase receptor Tie2 expressed by glomerular endothelial cells.

However, they have opposing effects in endothelial cells (Maisonpierre, Suri et al. 1997).

Podocyte-derived angiopoietin-1 is essential for vascular development and has been shown to

protect glomerular vasculature in DKD (Jeansson, Gawlik et al. 2011). Angiopoietin-2 is a

natural antagonist for Tie-2 expressed in endothelial cells and its upregulation has been reported

in DKD (Sun, Zheng et al. 2007). Podocyte-specific overexpression of angiopoietin-2 was

observed to result in glomerular endothelial cell apoptosis and albuminuria (Davis, Dei Cas et al.

2007).

Semaphorins are membrane-associated proteins expressed in most tissues and best known for

their roles in axonal growth (reviewed in Yazdani and Terman 2006). In the kidney, the

semaphorin, Sema3a, is produced by podocytes and it plays an essential role in glomerular

development (Reidy, Villegas et al. 2009). Overexpression of Sema3a in podocytes has been

shown to promote glomerular endothelial apoptosis, and its deletion results in endothelial

overgrowth (Villegas and Tufro 2002). Moreover, the phenotypic effect of Sema3a

overexpression in podocytes, particularly dysregulated αvβ3 integrin activity, is similar to that

seen with podocyte-specific VEGF-A deletion, suggesting a convergence between semaphorin

signalling and VEGF signalling (Veron, Villegas et al. 2012, Reidy, Aggarwal et al. 2013).

Taken together, these observations highlight the intimate association between podocytes and

glomerular endothelial cells and the importance of paracrine communication between the two cell

types in preserving the permselectivity of the GFB and maintaining the integrity of the kidney

glomerulus.

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1.5.2. Glomerular endothelial dysfunction in DKD

Several studies have emphasized both the role of glomerular endothelial cells in the maintenance

of glomerular homeostasis, and the impact of the diabetic milieu on glomerular endothelial cells.

Endothelial dysfunction is a term used frequently in the literature to describe the inability of the

endothelium to maintain vascular homeostasis (reviewed in Widlansky, Gokce et al. 2003). In

diabetes, imbalance in metabolic, hemodynamic and inflammatory factors induced by persistent

hyperglycemia contributes to glomerular endothelial dysfunction, which is regarded as an early

event that leads to microalbuminuria occurrence in DKD (Deckert, Feldt-Rasmussen et al. 1989,

reviewed in Stehouwer 2004, Nieuwdorp, Mooij et al. 2006). Loss of the glomerular ESL

containing glycocalyx has been observed to be associated with albuminuria in rodent models of

diabetes (Kuwabara, Satoh et al. 2010), in patients with type 1 diabetes (Nieuwdorp, Mooij et al.

2006), and in patients with type 2 diabetes (Broekhuizen, Lemkes et al. 2010). Loss of the

glomerular ESL has been attributed to high levels of ROS resulting in upregulation of the ESL

degrading enzyme, heparanase, and the development of albuminuria (Kuwabara, Satoh et al.

2010). The diabetic milieu was also shown to cause a reduction in eNOS expression in

glomerular endothelial cells leading to impaired production of NO, which has been shown to

accelerate DKD progression in experimental models of diabetes (Zhao, Wang et al. 2006,

reviewed in Nakagawa 2007, reviewed in Brosius, Alpers et al. 2009, Yuen, Stead et al. 2012). In

a recent study, restoration of glomerular endothelial glycocalyx by the selective endothelin A

receptor antagonist, atrasentan, was shown to be associated with an increase in NO levels, and

reduction in albuminuria in streptozotocin (STZ)-diabetic apolipoprotein E knockout (apoE KO)

mice, a model of DKD that combines renal and vascular injury (Boels, Avramut et al. 2016).

The role of the vascular endothelium in controlling inflammatory activities is also well

recognized (reviewed in Trepels, Zeiher et al. 2006). Under physiological conditions, NO limits

leukocyte adhesion and maintains an anti-inflammatory effect in the blood vessel wall (reviewed

in Widlansky, Gokce et al. 2003). In diabetes, elevation of proinflammatory cytokines and

chemokines contributes to endothelial activation, an inflammatory response that results in

upregulation of adhesion molecules such as VCAM-1, ICAM-1, and E-selectin (reviewed in

Galkina and Ley 2006). Upregulation of adhesion molecules in response to pro-inflammatory

cytokines promotes migration of leukocytes to the vessel wall leading to vascular damage, and

41

kidney dysfunction (reviewed in Galkina and Ley 2006). Although many studies have

demonstrated the involvement of glomerular endothelial cells in the pathogenesis of DKD, the

molecular mechanisms that lead to glomerular endothelial activation remain incompletely

understood. In the case of activated protein C, however, activated protein C in endothelial cells

was shown to regulate glucose-mediated mitochondrial ROS production in podocytes via changes

in DNA hypomethylation and histone modification (i.e. histone H3 acetylation) (Bock, Shahzad

et al. 2013), two processes that are involved in a set of gene regulatory mechanisms termed

epigenetics.

1.6. The emerging role of epigenetics in DKD

The term epigenetics, originally coined by Conrad Waddington (Waddington 1939), has been

commonly used in the literature to refer to the study of external modifications that alter gene

expression without changing the DNA base sequence (Waddington 1939, reviewed in Lewin

1998). Epigenetic mechanisms have been postulated as underlying the mechanism of the

‘metabolic memory’ phenomenon in diabetes, which refers to increase in complication risk

following an early exposure to hyperglycemia even after glycemic control improvement

(reviewed in Reddy, Zhang et al. 2015). This phenomenon emerged after the publication of an

observational study of the DCCT cohort, the Epidemiology of Diabetes Interventions and

Complications (EDIC) trial (DCCT/EDIC and Group 2000). The data from the EDIC trial

showed that reduction in microvascular complications as a result of intensive glycemic control in

the DCCT trial was notably maintained despite increasing hyperglycemia (DCCT/EDIC 2011). A

biochemical basis for glycemic memory is supported by a former study in which the investigators

demonstrated that the effect of hyperglycemia on increased expression of fibronectin in

endothelial cells and in kidneys from diabetic rats persisted even after restoration of

normoglycemic conditions (Roy, Sala et al. 1990). Because epigenetic processes provide a means

by which a transient environmental insult (e.g. hyperglycemia) can cause persistent phenotypic

changes (e.g. long term complications), they have been postulated as being responsible for the

paradigm of metabolic memory, and a number of studies support this assertion. For instance,

transient exposure of mice and cultured endothelial cells to high glucose has been shown to cause

persistent epigenetic changes (in this case increased monomethylation of histone 3 H3 lysine 4)

42

in the promoter of the NF-B p65 subunit, a major transcription factor that drive

proinflammatory gene expression (El-Osta, Brasacchio et al. 2008).

Epigenetic changes can be mediated by DNA methylation, post-translational histone

modifications (PTHMs), and non-protein coding RNA, including long non-coding RNAs

(lncRNAs) and microRNAs (miRNAs) (reviewed in Goldberg, Allis et al. 2007). However, DNA

methylation and PTHMs are the most extensively investigated epigenetic mechanisms in

metabolic memory (Brasacchio, Okabe et al. 2009, reviewed in Keating and El Osta 2013).

Hyperglycemia can induce irreversible modifications in DNA methylation and PTHMs overtime,

which may explain the lasting detrimental effects of metabolic memory (reviewed in Reddy,

Zhang et al. 2015).

DNA methylation involves addition of a methyl group to DNA cytosine residues (reviewed in

Portela and Esteller 2010). The implication of DNA methylation changes in kidney disease was

discovered more than a decade ago when Stenvinkel and colleagues reported that high levels of

global DNA methylation are associated with inflammation and increased mortality in patients

with CKD (Stenvinkel, Karimi et al. 2007). The observation coincided with emerging reports

connecting hyperglycemia, DKD, and metabolic syndrome with epigenetic changes (Heijmans,

Tobi et al. 2008, Holman, Paul et al. 2008, DCCT/EDIC 2011). Subsequent studies examined

the effect of DNA methylation on the expression of key pathological genes implicated in

CKDs. For instance, DNA methylation was identified in enhancer regions of key fibrotic genes

in human kidney tissues from patients with hypertensive and diabetic CKD, suggesting that

DNA methylation contributes to fibrogenesis in CKD (Ko, Mohtat et al. 2013). Furthermore,

DNA hypomethylation has also been reported to contribute to heritable glycemic memory in

zebrafish (Olsen, Sarras et al. 2012).

Epigenetic changes due to chromatin remodelling play a central role in regulating gene

expression via changing the conformation of the DNA-histone complex between a

transcriptionally accessible or inaccessible state (reviewed in Goldberg, Allis et al. 2007). This

is mainly mediated by post-translational modifications (PTMs) of octameric core histone

proteins known as H2A, H2B, H3 and H4, around which DNA approximately 147 base pairs

long are coiled to form the nucleosome. These histones are subject to different types of PTMs

43

regulated by specific enzymes including methylation, phosphorylation, acetylation,

ubiquitylation, and sumoylation (reviewed in Portela and Esteller 2010). The best studied of

these modifications are histone acetylation and histone methylation, which both have been

associated with the development of diabetes complications (El-Osta, Brasacchio et al. 2008,

reviewed in Villeneuve and Natarajan 2010, Advani, Huang et al. 2011, Gilbert, Huang et al.

2011). Each of these modifications denotes epigenetic signatures associated with gene silencing

or activation and they can exert their effects in a combinatorial fashion (reviewed in Strahl and

Allis 2000). For example, H3K27me3 is a repressive epigenetic mark whereas acetylation of

histone H3 lysine 9 (H3K9ac) at gene promoters is an activating epigenetic mark, and both

coordinate to regulate gene expression (Ha, Ng et al. 2011). Decreased H3K27me3

trimethylation has been shown to contribute to pathophysiological mechanisms in DKDs

(Siddiqi, Majumder et al. 2016). Moreover, recent work from our own group showed that

decreased H3K27me3 levels in adult glomerular podocytes promoted podocyte

dedifferentiation and enhanced glomerular disease progression whereas gain of H3K27me3

levels restored kidney function in several experimental models of glomerular disease

(Majumder, Thieme et al. 2018). Contribution of other histone modifications to the

pathogenesis of DKD has only begun to be explored. For instance, upregulation of the

epigenetic phospho-serine 10 modification of histone H3 (H3Ser10) has recently been reported

to be implicated in chromatin remodelling in podocytes of diabetic mice with key features of

DKD (Badal, Wang et al. 2016). In this work, the investigators showed that attenuation of

H3Ser10 phosphorylation by modulating two upstream regulators including miRNA-93 and

mitogen and stress-activated kinase-2 (Msk2) improved biochemical and histological features

of DKD. Unravelling the epigenetic processes implicated in glomerular dysfunction in diabetes

and mapping the sites and the cell type of epigenetic marks in kidney in health and disease may

open new avenues for targeted drug development that can improve outcomes in patients with

CKD including CKD caused by diabetes.

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1.7. Research aims and hypotheses

As reviewed in this Chapter, CKD is a global health problem and diabetes is a major contributor

to the pandemic predicted to increase over the next decade (reviewed in Zimmet, Magliano et al.

2014). CKD caused by diabetes accounts for the majority of kidney disease cases, which can

progress to kidney failure despite current available treatments, urging for new therapies to

prevent or slow the disease progression. In my doctoral research, I have explored emerging

(patho)biological processes in glomerular cell health and disease. I began by exploring the

actions of JAK2 in podocytes identifying a key role for the kinase in regulating podocyte

autophagy (Chapter 2). I then explored the effects of JAK2 deletion or inhibition in the setting

of diabetes and identified a pivotal importance of proinflammatory pathway upregulation, in

particular, upregulation of the chemokine CCL2 (Chapter 3). Finally, I examined the signalling

process by which CCL2 affects glomerular endothelial cell activation in diabetes, identifying

that this involves epigenetic processes, specifically, phosphorylation of histone 3 H3 on seine

residue 10 (Chapter 4).

Study 1

Rationale:

Podocyte integrity is important for proper glomerular filtration. To maintain their health,

podocytes rely on homeostatic cellular processes such as autophagy and intrinsic signaling

pathways including the JAK/STAT pathway, which is a major signaling pathway essential for

cell survival and function. Deletion of JAK2 in mice is embryonic lethal and upregulation of its

activity has been reported in mice and humans with DKD. Several studies highlighted the role of

JAK2 in kidney cells; however, the fundamental role of JAK2 in podocytes remains unknown.

This study (Chapter 2) aimed to characterize the effect of JAK2 deletion in podocytes under

physiological conditions using podocyte-specific JAK2 knockout mice.

Hypothesis:

JAK2 is an essential regulator of podocyte homeostasis.

45

Study 2

Rationale:

Having described the homeostatic action of JAK2 in podocytes in the normal setting in Study 1

(Chapter 2), and recognizing that JAK2 inhibition is being trialed for the treatment of DKD, this

study aimed to explore the effect of both systemic JAK2 inhibition and JAK2 deletion from

podocytes in mouse models of diabetes.

Hypotheses:

1. Systemic JAK2 inhibition will attenuate kidney dysfunction in diabetes

2. JAK2 deletion in podocytes will exacerbate kidney dysfunction in diabetes

Study 3

Rationale:

Paracrine communication between podocytes and glomerular endothelial cells is critical for

preserving the permselectivity of the GFB. In diabetes, the diabetic milieu induces the release of

inflammatory cytokines and chemokines by resident cells in the kidney. Having identified that

the chemokine CCL2 is upregulated in cultured podocytes under high glucose conditions in

Study 2 (Chapter 3), in this study (Chapter 4), we set out to determine the effect of podocyte-

secreted CCL2 on glomerular endothelial cell activation focusing on VCAM-1 as a marker for

endothelial activation.

Hypothesis:

Podocyte-secreted CCL2 contributes to endothelial activation in the kidney glomerulus in

diabetes.

46

CHAPTER 2: Janus Kinase 2 Regulates Transcription

Factor EB Expression and Autophagy Completion in

Glomerular Podocytes

Sections have been adapted with permission from Alghamdi, T.A., Majumder, S., Thieme, K.,

Batchu, S.N., White, K., Liu,Y., Brijmohan, A.S., Bowskill, B. Advani, S.L., Woo, M., Advani,

A. (2017). JAK2 regulates transcription factor EB expression and autophagy completion in

glomerular podocytes. Journal of American Society of Nephrology. 28(9):2641-2653.

Contribution of authors:

T.A.A. designed and performed the experiments, analyzed the data, and wrote the manuscript.

S.M., K.T., and S.N.B. contributed to the experiments and generation of data (specifically, Figure

2.4B and C, Figure 2.6C and E, Figure 2.8, Table 2.2, Table 2.3, Figure 2.9G, Figure 2.10, Figure

2.11A and E). K.W. contributed to the transmission electron microscopic data. Y.L. assisted with

the in vitro experiments. A.S.B. contributed to the immunofluorescence staining data presented in

Figure 2.9F. B.B.B assisted with the animal studies. S.L.A. contributed to the

immunohistological data presented in Figure 2.5. M.W. contributed to the in vivo data and

revised the manuscript. A.A. designed the experiments, supervised the study, and wrote the

manuscript.

47

2.1. INTRODUCTION

Podocytes are in a unique situation. As terminally differentiated epithelial cells with

interdigitating feet that encompass the capillary walls within the glomerular tuft, they are

uniquely exposed to metabolic shifts and hemodynamic pressures that render them vulnerable to

injury in glomerular disease. Where the potential for regeneration and replacement is limited,

podocytes depend heavily on their use of homeostatic pathways to mitigate the pressures that

they face. For instance, they possess a high basal rate of macroautophagy (henceforth referred to

as autophagy), a self-degradative process that removes protein aggregates and damaged

organelles (Hartleben, Gödel et al. 2010). They also depend on intrinsic survival signals, among

them signals that are mediated by the nonreceptor kinase, JAK2 (Logar, Brinkkoetter et al. 2007).

The JAK/STAT pathway is an intracellular signaling cascade that regulates cell growth,

proliferation, and differentiation (reviewed in Chuang and He 2010). Of the four JAK family

members (JAK1, JAK2, JAK3, and TYK2), the JAK2 isoform has become a focus of accelerated

drug discovery attentions since 2005, when activating mutations of its encoding gene were first

shown to underlie the development of certain myeloproliferative neoplasias (Kralovics,

Passamonti et al. 2005). In kidney disease, evidence of JAK/STAT pathway activation in human

diabetic nephropathy (Berthier, Zhang et al. 2009, Hodgin, Nair et al. 2013) encouraged the

repurposing of the JAK1/2 inhibitor baricitinib, and this was recently shown to reduce

albuminuria and markers of renal inflammation in a phase 2 study (Tuttle, Brosius et al. 2018).

Although current advances have shone the spotlight on JAK/STAT signaling as a promising

treatment target for kidney disease (reviewed in Brosius Iii and He 2015), this is not itself a new

concept. It has been a decade and a half since JAK2-mediated signaling was first implicated in

the development of kidney inflammation and fibrosis, an inference that came about with the

publication of a collection of reports describing its actions in glomerular mesangial cells (Amiri,

Shaw et al. 2002, Wang, Shaw et al. 2002, Banes, Shaw et al. 2004). Since then, podocyte

preservation has gained increasing traction for its importance in preventing both the initiation and

propagation of glomerular disease (reviewed in Wolf, Chen et al. 2005, reviewed in Shankland

2006), and in contrast to the studies in replicating mesangial cells, the few reports that have

examined the actions of JAK2 in podocytes have cited the kinase as being a mediator of cell

survival (Logar, Brinkkoetter et al. 2007, Schiffer, Park et al. 2008). Cognizant of the growing

48

interest in therapeutic applications that alter JAK/STAT signaling in kidney disease and the

dearth of literature espousing the homeostatic actions of the pathway in podocytes, in this study,

we set out to examine the phenotypic effects of JAK2 absence. To our surprise, we found that

JAK2 deficiency in mice led to an impairment in autophagy in podocytes, and in exploring the

means by which this occurred, we identified a hitherto unrecognized action of JAK2 in

controlling the expression of the master regulator of autophagy (Settembre, Di Malta et al. 2011)

and lysosome function (Sardiello, Palmieri et al. 2009), the transcription factor TFEB.

2.2. RESEARCH DESIGN AND METHODS

2.2.1. Animal studies

2.2.1.1. Generation of Podocin-cre+R26Rfl/fl mice

Podocin-cre+ mice, transgenic mice that express Cre recombinase specifically in podocytes

controlled by the human podocin (NPHS2) promoter [B6.Cg-Tg(NPHS2-cre)295Lbh/J] (Moeller,

Sanden et al. 2003), and R26Rfl/fl mice, reporter mice that have a loxP-flanked DNA STOP

sequence to prevent β-galactosidase expression [B6;129S4-Gt(ROSA)26Sortm1Sor/J](Soriano

1999), were obtained from the Jackson Laboratory (Bar Harbor, ME). Mice were bred in the St.

Michael’s Research Vivarium.

2.2.1.2. Generation of podocyte-specific JAK2 knockout mice

Jak2fl/fl mice were provided by Dr. Kay-Uwe Wagner (Nebraska Medical Center) (Krempler, Qi

et al. 2004). Podocin-cre+ mice were bred with Jak2fl/fl mice to generate podocyte-specific JAK2

knockout mice Podocin-cre+Jak2fl/fl (JAK2podKO) and their Cre expressing littermates (JAK2Ctrl).

Male JAK2Ctrl (n=10) and JAK2podKO mice (n=12) were studied at 10 weeks of age, and

albuminuria was determined in an additional four mice per group at age 6 months old. Systolic

BP was measured using a CODA Noninvasive BP System (Kent Scientific, Torrington, CA)

(Yuen, Stead et al. 2012). Urine albumin excretion was determined by ELISA (Assaypro, St.

Charles, MO) after housing mice individually in metabolic cages for 24 hours. After harvesting,

49

mouse kidneys were immersed in 10% neutral buffered formalin, routinely processed, and

embedded in paraffin; cryoembedded in Tissue-Tek optimum cutting temperature formulation

compound (VWR International, Mississauga, ON, Canada); flash frozen in liquid nitrogen and

stored at -80°C; or fixed in 2.5% gluteraldehyde for later analysis by transmission electron

microscopy. All experimental procedures adhered to the guidelines of the Canadian Council on

Animal Care and were approved by the St. Michael’s Hospital Animal Care Committee.

2.2.2. β-Galactosidase expression

Kidney cryosections were obtained from Podocin-cre+R26Rfl/fl mice and their control group

Podocin-cre- mice. X-gal staining of kidney cryosections was performed using an X-Gal

Staining Kit (Oz Biosciences, San Diego, CA) according to the manufacturer’s instructions.

Briefly, tissue section slides were fixed with the provided fixing solution and incubated for 10-15

minutes at room temperature. The fixing solution was discarded and the slides were carefully

washed twice with 1X phosphate-buffered saline (PBS). After washing, freshly prepared 1X

staining solution of X-Gal was added to each slide. The slides were then incubated at 37 ºC

overnight. The following day, the X-Gal staining solution was removed and slides were washed

once with 1X PBS. Mounting media was added to each slide. The slides were left to dry and the

tissue sections were examined under a light microscope for blue stained cells.

2.2.3. Primary culture of podocytes

Glomeruli were isolated from JAK2Ctrl and JAK2podKO mice using Dynabeads. After isoflurane

anesthesia, the abdominal aorta was cannulated with a 24-gauge angiocath, and the mouse was

perfused with 1×105 Dynabeads (ThermoFisher Scientific, Rockford, IL) in 5 ml Hank’s

Balanced Salt solution (HBSS) (ThermoFisher Scientific). Podocytes were isolated using

previously reported methods (Shankland, Pippin et al. 1999, Stitt-Cavanagh, Faour et al. 2010).

Briefly, for each animal, both kidneys were minced into 1 mm3 and digested at 37 °C for 30 min

with gentle agitation in 5 ml of Collagenase type I (Thermofisher Scientific) freshly prepared at a

50

concentration of 2 mg/ml. The digested kidney tissues were then gently pressed through a 100

µm sterile cell strainer (Thermofisher Scientific) using a flattened pestle. The filtered cells were

passed through a new 100 µm sterile cell strainer without pressing and the cell strainer washed

with 5 ml HBSS. The cell suspension was then centrifuged at 200 g for 5 min. The supernatant

was then discarded and the cell pellet was resuspended in 2 ml of HBSS. Glomeruli containing

Dynabeads were gathered using MagRack 6 (VWR International, Mississauga, ON, Canada).

Isolated glomeruli were visualized under light microscope (Figure 2.1). Glomeruli were then

seeded on collagen 1–coated plates in a 1:1 mixture of F-12 Kaighn’s Modification media

(HyClone Laboratories, Logan, UT) with media harvested from NIH/3T3 cells (American Type

Culture Collection, Manassas, VA). Cell cultures were maintained for approximately 4–6 days

and were not passaged (Katsuya, Yaoita et al. 2006). For flow cytometry, cells were stained with

anti-nephrin antibody (1:100; R&D Systems, Minneapolis, MN) and Alexa Fluor 488 donkey

anti-goat antibody (1:100; ThermoFisher Scientific) before analysis using a Fortessa X-20 (BD

Biosciences, San Jose, CA). Data analysis was with FlowJo software version 10.2 (FlowJo LLC,

Ashland, OR).

Figure 2.1: An isolated Dynabeads-perfused glomerulus. Original magnification ×400.

51

2.2.4. Immunoblotting

Immunoblotting was performed on cultured cell extracts with antibodies in the following

concentrations: nephrin (1:1000; R&D Systems), JAK2 (1:1000; Cell Signaling Technology,

Danvers, MA), -tubulin (1:1000; Sigma-Aldrich, Oakville, ON, Canada), LC3 (1:1000; Cell

Signaling Technology), p62 (1:1000; BD Biosciences), LAMP2 (1:1000; Abcam, Cambridge,

MA), ß-actin (1:10,000; Sigma-Aldrich), TFEB (1:500; Abcam), and GFP (1:1000; Santa Cruz

Biotechnology, Dallas, TX). Densitometry was performed using ImageJ 1.46r software (National

Institutes of Health, Bethesda, MD).

2.2.5. Immunofluorescence staining

Immunofluorescence microscopy was performed on formalin-fixed, paraffin-embedded kidney

sections and cultured cells with antibodies in the following concentrations: JAK2 (1:50; Cell

Signaling Technology), secondary antibody Alexa Fluor 488 donkey anti-rabbit (1:100;

ThermoFisher Scientific), p62 (1:100; Cell Signaling Technology), secondary antibody Alexa

Fluor 555 donkey anti-rabbit (1:100; ThermoFisher Scientific), LAMP2 (1:100; Abcam),

secondary antibody Alexa Fluor 488 donkey anti-rat (1:100; ThermoFisher Scientific), TFEB

(1:100; Abcam), nephrin (1:100; R&D Systems), and secondary antibody Alexa Fluor 647

donkey anti-goat (1:100; ThermoFisher Scientific). DAPI was from Cell Signaling Technology

and used at a concentration of 1:10,000. Slides were visualized on a Zeiss LSM 700 confocal

microscope (Carl Zeiss Canada, Toronto, ON, Canada). For p62, p62-positive puncta were

counted in six glomeruli from six mice per group. For LAMP2, mean fluorescence intensity was

determined in six glomeruli from six mice per group using ImageJ and represented as the fold

change relative to control. In cultured cells, LAMP2 was calculated as the mean fluorescence

intensity from four samples per condition, and nuclear TFEB was calculated as the proportion of

positively immunostaining nuclear pixels (red) in five fields (x6300 magnification) from nine

samples per condition using Adobe Photoshop 7.0 (San Jose, CA), with both represented as the

fold change relative to control (scramble).

52

2.2.6. Transmission electron microscopy

Transmission electron microscopy was performed with a Philips CM100 transmission electron

microscope (Electron Microscope Research Services, Newcastle University, Newcastle upon

Tyne, United Kingdom). Kidney cortical tissue was examined in each mouse as well as JAK2

siRNA and scramble-transfected podocytes (n=6 per condition). The volume fraction of

autophagosomes (or lysosomes) was calculated on 10–20 representative electron micrographs

(x7900 magnification) from each mouse or each experimental replicate with a masked

quantitative point counting method using ImageJ (Advani, Huang et al. 2011).

2.2.7. Conditionally immortalized mouse podocytes

Differentiated conditionally immortalized mouse podocytes were cultured as previously

described (Endlich, Kress et al. 2001). For knockdown of JAK2, cells were transfected with

sequence-specific siRNA or scrambled siRNA (ThermoFisher Scientific) at a concentration of 75

nM for 24 hours. For experiments with EBSS, RPMI medium (Sigma-Aldrich) was replaced by

EBSS (Sigma-Aldrich) 5 hours after the addition of siRNA (or scrambled siRNA), and cells were

maintained for another 19 hours. Bafilomycin A1 (Sigma-Aldrich) was used at a concentration of

100 nM for 4 hours (Lenoir, Jasiek et al. 2015). TFEB overexpression was achieved by

transfecting cells with a p-EGFP-N1-TFEB construct (Roczniak-Ferguson, Petit et al. 2012) (gift

from Shawn Ferguson; Addgene plasmid 38119; Addgene, Cambridge, MA) for 24 hours.

Cathepsin D activity was determined with a commercial kit (Abcam).

2.2.8. Real-Time PCR

RNA was isolated from cell extracts using TRIzol Reagent (ThermoFisher Scientific), and cDNA

was reverse transcribed from 1 g RNA using SuperScript III Reverse Transcriptase

(ThermoFisher Scientific). Primers were designed and validated using Primer-BLAST

(http://www.ncbi.nlm.nih.gov/tools/primer-blast/), and they were synthesized by Integrated DNA

Technologies (Coralville, IA). Primer sequences are provided in the appendix. Measurement of

gene expression was performed using SYBR green on a ViiA 7 Real-Time PCR System

53

(ThermoFisher Scientific). For experiments in primary cells, mRNA levels were determined in

podocytes from four JAK2Ctrl mice and four JAK2podKO mice. Experiments were performed in

triplicate, and data analyses were conducted using the Applied Biosystems Comparative CT

method.

2.2.9. Promoter Reporter Assay

Podocytes were transfected with a luciferase reporter under the control of the TFEB promoter

(Tsunemi, Ashe et al. 2012) (gift from Albert La Spada; Addgene plasmid 66801; Addgene).

Cells were transfected with JAK2 siRNA or scramble for 24 hours before determination of

luciferase activity with a reporter assay system (Promega, Madison, MA).

2.2.10. Chromatin Immunoprecipitation

Chromatin immunoprecipitation was performed using the Magna ChIP Kit (EMD Millipore,

Etobicoke, ON, Canada). Briefly, mouse podocytes were transfected with scramble or JAK2

siRNA for 24 hours. After crosslinking and sonication, sheared chromatin was

immunoprecipitated with an antibody directed against STAT1 (1:100; Cell Signaling

Technology) or an equal concentration of normal rabbit IgG (Santa Cruz Biotechnology).

Samples were then washed, reverse crosslinked, and proteinase K treated to obtain purified DNA

fragments. Quantitative real-time PCR was performed using primers specific for a sequence of

the mouse TFEB promoter. Primer sequences are provided in the appendix. The promoter region

of TFEB and the putative binding sites for STAT1 within the mouse TFEB promoter (Figure

2.10) were determined by Ensembl genome browser (https://useast.ensembl.org/) and ALGGEN

PROMO (http://alggen.lsi.upc.es) online tools.

2.2.11. Albumin Permeability Assay

An albumin permeability assay was adapted from a previously described method (Nooteboom,

Hendriks et al. 2000). Mouse podocytes were grown to confluent monolayers on transwell plates

54

and transfected with p-EGFP-N1-TFEB, JAK2 siRNA, or scramble for 24 hours. A tracer

solution of 250 g/ml FITC-albumin (Sigma-Aldrich) in RPMI medium was applied to the upper

compartment, and the ratio of fluorescence of samples drawn from the lower compartment at 2

and 24 hours (excitation/emission wavelengths, 495/520 nm) was determined using a SpectraMax

M5 Microplate Reader (Molecular Devices, Sunnyvale, CA).

2.2.12. Statistical Analyses

Data are expressed as means ± SEMs. Statistical significance was determined by one-way

ANOVA with a Fisher least significant difference test for comparison of multiple groups and

unpaired t test for comparison between two groups (or Mann–Whitney test for nonparametric

data). Skew distributed data were log transformed before statistical comparison. Statistical

analyses were performed using GraphPad Prism 6 for Mac OS X (GraphPad Software Inc., San

Diego, CA).

2.3. RESULTS

2.3.1. Knockout of JAK2 from podocytes impairs autophagy completion in mice

To examine the normal actions of JAK2-dependent signaling in podocytes, we generated

podocyte-specific JAK2 knockout mice. First, to confirm that Cre recombinase expression was

limited to the glomerulus, we bred Podocin-cre+ mice (Moeller, Sanden et al. 2003) with

ROSA26 reporter mice (R26Rfl/fl) (Soriano 1999). Histologic staining of kidney sections from

Podocin-cre- mice showed no expression of -galactosidase, whereas -galactosidase was

strongly expressed in the kidneys of Podocin-cre+R26Rfl/fl mice, where it was constrained to the

glomeruli (Figure 2.3A). To examine whether the presence of the cre transgene affects podocyte

permselectivity, we followed Podocin-cre- and Podocin-cre+ mice for 6 months, observing no

difference in the rate of urinary albumin excretion between the two groups (Figure 2.3B).

55

Figure 2.2: Characterization of Podocin-cre+ R26Rfl/fl mice. (A) Enzymatic X-gal staining of

kidney sections from a Podocin-cre− mouse and a Podocin-cre+R26Rfl/fl mouse showing

glomerular β-galactosidase expression in the Podocin-cre+R26Rfl/fl mouse. Original

magnification, ×400. (B) Urine albumin excretion in Podocin-cre- (n=11) and Podocin-cre+

(n=6) mice aged six months. Data are mean ± SEMs.

Second, to generate podocyte-specific JAK2 knockout animals, we bred Podocin-cre+ mice with

Jak2fl/fl mice in which loxP sites had been placed around the promoter and first coding exon of

Jak2 (Krempler, Qi et al. 2004). We studied two groups of mice: Podocin-cre+Jak2+/+ mice and

Podocin-cre+Jak2fl/fl mice, henceforth referred to as JAK2Ctrl and JAK2podKO, respectively. Both

groups of mice were born in the expected Mendelian frequency. To determine the efficiency of

JAK2 deletion, we isolated primary cultured podocytes from JAK2Ctrl and JAK2podKO mice.

Primary cultured podocytes were recognizable by their arborized morphology and the expression

of the podocyte protein nephrin on immunoblotting (Figure 2.4A). JAK2 deletion from

podocytes in JAK2podKO mice was confirmed by (1) immunoblotting (Figure 2.4B) and (2)

immunofluorescence microscopy (Figure 2.4C). In adult mice (age 10 weeks old), the magnitude

of urine albumin excretion in JAK2podKO mice was almost double that of their littermate controls

(Figure 2.4D, Table 2.2). Albuminuria in Podocin-cre+Jak2fl/+ heterozygous mice fell midway

between the levels seen in JAK2Ctrl and JAK2podKO mice (urine albumin excretion, 22±4 µg/day;

56

n=13; P=0.83 vs. JAKCtrl). By 6 months of age, urine albumin excretion was increased threefold

in JAK2podKO mice (Figure 2.4D).

Figure 2.3: Characterization of JAK2 deletion from podocytes in mice. (A) Phase-contrast

microscopy (original magnification, ×100) and immunoblotting for nephrin in primary cultured

mouse podocytes. Lysates from 3T3 cells are provided as a comparator. (B) Immunoblotting for

JAK2 in lysates of primary podocytes isolated from JAK2Ctrl and JAK2podKO mice. (C)

Immunofluorescence dual staining for nephrin and JAK2 in glomerular sections from JAK2Ctrl

and JAK2podKO mice. The merged image shows colocalization of JAK2 and nephrin (yellow-

orange color) in JAK2Ctrl but not in JAK2podKO. Blue is 4',6-diamidino-2-phenylindole (DAPI).

(D) Urine albumin excretion in JAK2Ctrl and JAK2podKO mice ages 10 weeks old (n=10-12 per

group) and 6 months old (n=4 per group). AU, arbitrary units. Values are mean ± SEMs. *P<0.05

by unpaired t test.

57

Table 2.1: Body weight, kidney weight and systolic blood pressure (SBP) in JAK2Ctrl and

JAK2podKO mice.

Body weight (g) Kidney weight

(g)

Kidney weight:

body weight (%)

SBP (mmHg)

JAK2Ctrl (n=10) 23.50.4 0.190.01 0.820.03 892

JAK2podK (n=12) 23.70.4 0.180.01 0.790.02 883

Values are mean ± SEMs. No statistically significant difference observed between all groups.

58

In subsequent experiments, we focused our analyses on the structural changes that occurred in

mice at the earlier (10 weeks) time point, which we speculated were more likely to be causatively

implicated in the development of albuminuria. At this stage, glomerular morphology in

JAK2podKO mice was unremarkable when assessed by light microscopy (Figure 2.5).

Figure 2.4: Representative periodic acid-Schiff (A and B, original magnification ×400) and

hematoxylin and eosin (C and D, original magnification ×100) stained kidney sections from

JAK2Ctrl (A and C) and JAK2podKO mice (B and D) aged 10 weeks.

59

In contrast, when we examined the ultrastructure of podocytes by transmission electron

microscopy, we observed an approximately 80% increase in autophagosome fractional volume in

JAK2podKO mice (Figure 2.6A). Similarly, in primary podocytes from JAK2podKO mice, there was

an increase in abundance of LC3-II, the autophagosome-associated phosphatidylethanolamine-

conjugated form of the protein microtubule-associated protein 1A/1B–light chain 3 (LC3)

(Kabeya, Mizushima et al. 2000) (Figure 2.6B). We considered that increased autophagosome

fractional volume and LC3-II levels could be due to either enhanced induction of autophagy or

impaired completion of autophagy. To help us distinguish between these two scenarios, we

probed for the autophagy substrate, p62 (also called sequestosome 1), that accumulates in the

cytosol when autophagy is impaired (Bjørkøy, Lamark et al. 2005). In comparison with JAK2Ctrl

mice and suggestive of impaired autophagy completion, there was an increase in podocyte p62 in

JAK2podKO mice (Figure 2.6, C and D). This impairment in autophagy completion was

accompanied by an increase in lysosome accumulation as assessed by immunostaining and

immunoblotting for the lysosome marker lysosome-associated membrane protein 2 (LAMP2)

(Figure 2.6, E and F).

60

Figure 2.5: JAK2 deletion impairs podocyte autophagy completion in vivo. (A) Transmission

electron micrographs of podocytes from JAK2Ctrl and JAK2podKO mice and autophagosome

volume fraction (n=10-12 per group). The transmission electron micrographs illustrate

autophagosomes (thick black arrows) and lysosomes (thin black arrows) in the podocyte from the

JAK2podKO mouse. Insets are a higher magnification. Original magnification, ×25,000. (B)

Immunoblotting primary cultured podocytes from JAK2Ctrl (n=4) and JAK2podKO mice (n=4) for

LC3. (C) Immunofluorescence dual staining for nephrin and p62 in glomerular sections of

JAK2Ctrl (n=6) and JAK2podKO (n=6) mice. Insets represent zoomed-in images of the dashed

61

areas. The white arrows point to p62 puncta in podocytes (nephrin positive) from the JAK2podKO

mouse. (D) Immunoblotting primary cultured podocytes from JAK2Ctrl (n=5) and JAK2podKO

mice (n=4) for p62. (E) Immunofluorescence staining for nephrin and LAMP2 in glomerular

sections of JAK2Ctrl (n=6) and JAK2podKO (n=6) mice. (F) Immunoblotting primary cultured

podocytes from JAK2Ctrl (n=4) and JAK2podKO mice (n=4) for LAMP2. AU, arbitrary units.

Values are mean ± SEMs. *P<0.05; †P<0.01 by unpaired t test (or Mann-Whitney test or unpaired

t test of log transformed values for Figure 2.6A).

2.3.2. JAK2 knockdown impairs autophagy completion in differentiated immortalized podocytes

To better understand the causes of autophagosome-lysosome accumulation in JAK2-deficient

podocytes, we turned to an immortalized cell culture system and transfected conditionally

immortalized differentiated mouse podocytes (Endlich, Kress et al. 2001) with either sequence-

specific short interference RNA (siRNA) directed against JAK2 or scramble control (Figure

2.7A). Immunoblotting cell lysates revealed that JAK2 knockdown in these cells similarly led to

an increase in the abundance of LC3-II and p62 (Figure 2.7B), suggestive of impaired autophagy

completion. The increase in LC3-II after JAK2 knockdown was comparable with that observed

when autophagic flux was blocked with Earle’s Balanced Salt Solution (EBSS; autophagy

induction) and bafilomycin A1 (an inhibitor of autophagy completion), with no additive effect of

the combination of JAK2 siRNA, EBSS, and bafilomycin A1 (Figure 2.7C). In contrast, LC3-I

levels appeared lower in podocytes exposed to EBSS and bafilomycin A1 in the presence or

absence of JAK2 siRNA, likely indicative of autophagy induction with the former conditions that

was unaffected by JAK2 knockdown (Figure 2.7C). Stereometric evaluation of transmission

electron micrographs revealed an increase in autophagosome and lysosome volume fraction in

JAK2 siRNA-transfected podocytes compared with scramble-transfected cells (Figure 2.7D).

Likewise, LAMP2 expression was increased in the setting of JAK2 knockdown when assessed by

either immunoblotting (Figure 2.7E) or immunostaining (Figure 2.7F).

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Figure 2.6: JAK2 knockdown with siRNA causes autophagosome and lysosome

accumulation in cultured immortalized mouse podocytes. (A) JAK2 knockdown with siRNA.

(B) Immunoblotting for LC3 (n=6 per condition) and p62 (n=5 per condition). (C)

Immunoblotting for LC3 in JAK2 siRNA-transfected podocytes (or scramble-transfected cells)

incubated in EBSS for 19 hours (5 hours post-transfection), with bafilomycin A1 (100 nM) added

for the final 4 hours ( n=7-10 per condition). (D) Transmission electron micrographs of mouse

63

podocytes transfected with scramble or JAK2 siRNA and autophagosome and lysosome volume

fraction (n=6 per condition). Insets are higher magnification (original magnification, ×25,000).

The thick arrow labels an autophagosome, and the thin arrow labels a lysosome. (E)

Immunoblotting for LAMP2 (n=8 per condition). (F) Immunofluorescence staining for LAMP2

(red) and 4',6-diamidino-2-phenylindole (DAPI) (blue) (n=4 per condition). GAPDH,

glyceraldehyde 3-phosphate dehydrogenase; AU, arbitrary units. Values are mean ± SEMs.

*P<0.05 versus scramble; †P<0.01 versus scramble by one-way ANOVA with a Fisher least

significant difference test for comparison of multiple groups and unpaired t test for comparison

between two groups.

Although the regulation of autophagic processes can differ between primary cells and cell lines

(Puleston, Phadwal et al. 2015) and although the primary culture was an enriched but not pure

podocyte cell population (>85% nephrin positive) (Figure 2.8), JAK2 knockout/knockdown

consistently impaired late-phase autophagy. We speculated that this impairment could be due to

either improper fusion of autophagosomes with lysosomes or impairment of lysosome function

itself.

Figure 2.7: Representative flow cytometry histograms from primary cultured cells (n=4) stained

for nephrin.

64

Because the JAK/STAT pathway is a major regulator of gene transcription, we focused our next

discovery experiments on mRNA changes of genes linked to autophagy pathways in podocytes

transfected with JAK2 siRNA. To explore the regulation of autophagosome-lysosome fusion, we

reviewed the biomedical literature and compiled a list of 16 genes previously linked to this

process. Using RT-qPCR, we found little change in the expression of any of these genes with

JAK2 knockdown (Table 2.2). A difference in mRNA levels encoding four proteins achieved

statistical significance (histone deacetylase 6, Huntingtin associated protein 1, sorting nexin 14,

and vesicle-associated membrane protein 8). However, whereas each was increased in its

expression, none were upregulated >1.25-fold (Table 2.2).

65

Table 2.2: Relative mRNA levels of genes involved in the fusion of autophagosomes with

lysosomes (n=4 per condition).

Scramble

(AU)

JAK2 siRNA

(AU) ATP6AP2 1.000.04 1.050.02

Autophagy related 14 1.000.05 1.080.05

Caveolin-1 1.000.02 0.960.01

CD38 1.000.05 1.060.10

DNA damage regulated autophagy modulator 1 1.020.10 0.910.10

FAM176A 1.090.07 0.950.04

Histone deacetylase 6 1.010.07 1.220.04*

Huntingtin-associated protein 1 1.000.03 1.190.07*

Niemann-Pick C1 1.000.02 1.080.03

Pleckstrin homology domain-containing family M

member 1

1.010.06 1.020.05

SNAP-associated protein 1.000.05 1.120.01

Sorting nexin 14 1.000.04 1.130.02*

Syntaxin 17 1.000.05 1.060.01

Tectonin ß-propeller repeat containing 1 1.010.08 1.010.04

Vesicle-associated membrane protein 7 1.000.05 1.110.06

Vesicle-associated membrane protein 8 1.000.02 1.150.03†

Values are normalized to RPL13a. AU = arbitrary units. Values are mean ± SEMs. *P<0.05,

†P<0.01 by unpaired t test.

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2.3.3. JAK2 knockdown downregulates the transcription factor TFEB

In the context of minimal change in expression of genes involved in autophagosome-lysosome

fusion, we hypothesized that the impairment in autophagy completion in JAK2-deficient

podocytes was a consequence of lysosome dysfunction. Consistent with the presence of

lysosome dysfunction, JAK2 knockdown caused a decrease in the activity of cathepsin D (Figure

2.9A), a lysosomal aspartic proteinase, the deficiency of which was recently implicated in

impaired podocyte autophagy (Yamamoto-Nonaka, Koike et al. 2016). Because the transcription

factor TFEB has been linked to lysosome function (Sardiello, Palmieri et al. 2009), autophagy

(Settembre, Di Malta et al. 2011), and cathepsin D activity (Ivankovic, Chau et al. 2016), we

performed a second RT-qPCR–based screen for mRNA changes of 13 genes drawn from a list of

the most likely lysosomal direct targets of TFEB (Palmieri, Impey et al. 2011). Six of the 13

likely TFEB targets were significantly downregulated with JAK2 siRNA (including cathepsin D)

(Table 2.3). Of these six transcripts, five were also downregulated in podocytes from JAK2podKO

mice, with statistically significant reductions seen in mRNA levels of beclin-1, cathepsin D, and

cystinosin (Figure 2.9B). Having discovered a downregulation in the expression of several

putatively TFEB-regulated genes with JAK2 knockout or knockdown, we queried whether TFEB

itself is affected by JAK2 knockdown. Supportive of this assertion, TFEB promoter activity

(Figure 2.9C), mRNA levels (Figure 2.9D), protein levels (Figure 2.9E), and nuclear localization

(Figure 2.9F) were each reduced in mouse podocytes transfected with JAK2 siRNA compared

with scramble-transfected cells. In determining how JAK2 may regulate the expression of TFEB,

we performed in silico analysis of the mouse TFEB promoter and identified six putative binding

sites for the JAK2-dependent transcription factor, STAT1 (Figure 2.10). By chromatin

immunoprecipitation, we found that STAT1 was enriched at the TFEB promoter and that its

enrichment was negated with JAK2 siRNA (Figure 2.9G). We immunoblotted podocytes

isolated from JAK2podKO mice, and in doing this, we also observed a reduction in TFEB

expression with JAK2 knockout (Figure 2.9H).

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Table 2.3: Relative mRNA levels of likely direct targets of TFEB with a known role in

lysosome function (Palmieri, Impey et al. 2011) in mouse podocytes transfected with JAK2

siRNA or scramble (n=4 per condition).

Scramble (AU) JAK2 siRNA (AU)

-Galactosidase 1.030.15 0.860.05

ATPase H+ transporting accessory protein 1 1.030.15 0.830.01

ATPase H+ transporting lysosomal V0 subunit C 1.060.23 1.060.08

Beclin 1 1.040.18 0.720.03*

Cathepsin B 1.040.19 1.420.13

Cathepsin D 1.030.15 0.680.04*

Cystinosin 1.060.22 0.720.02*

Lysosomal -glucosidase 1.050.21 1.010.10

Mucopilin-1 1.040.17 0.700.03*

Nuclear receptor binding factor-2 1.060.20 1.010.08

Ras-related GTP binding C 1.040.18 0.610.03*

Serine/threonine kinase 4 1.040.19 0.720.04*

Vacuolar protein sorting-associated protein 18 1.060.22 0.840.02

Values normalized to RPL13a. AU = arbitrary units; RPL13a, ribosomal protein L13a. Values

are mean ± SEMs. *P<0.05 by unpaired t test.

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Figure 2.8: JAK2 knockdown or knockout impairs lysosome function and decreases TFEB

expression in mouse podocytes. (A) Cathepsin D activity in immortalized podocytes transfected

with scramble or JAK2 siRNA for 24 hours (n=9 per condition). (B) Relative mRNA levels of

TFEB targets in primary podocytes from JAK2Ctrl (n=4) and JAK2podKO (n=4) mice. BECN1,

beclin 1; CTSD, cathepsin D; CTNS, cystinosin; MCOLN1, mucopilin-1; RRGAC, Ras-related

GTP binding C; STK4, serine/threonine kinase 4. (C–G) Regulation of TFEB expression by

JAK2 in immortalized podocytes transfected with scramble or JAK2 siRNA for 24 hours. (C)

TFEB promoter activity (n=5-6 per condition). (D) TFEB mRNA levels (n=4 per condition). (E)

TFEB protein levels. (F) TFEB nuclear levels (n=9 per condition). (G) Chromatin

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immunoprecipitation of the TFEB promoter after STAT1 enrichment (n=3-4 per condition). (H)

TFEB protein levels in primary podocytes from JAK2Ctrl (n=6) and JAK2podKO (n=5) mice. AU,

arbitrary units. Values are mean ± SEMs. *P<0.05 versus scramble; †P<0.05 versus JAK2Ctrl;

‡P<0.01 versus scramble; §P<0.01 versus IgG by one-way ANOVA with a Fisher least significant

difference test for comparison of multiple groups and unpaired t test for comparison between two

groups.

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Figure 2.9: Putative binding sites for STAT1 within the mouse TFEB promoter.

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2.3.4. TFEB overexpression restores podocyte function after JAK2 knockdown

In our final series of experiments, we investigated whether the podocyte dysfunction, induced by

JAK2 knockdown, could be reversed by TFEB overexpression. We transfected cells with a

plasmid encoding EGFP-tagged TFEB (Roczniak-Ferguson, Petit et al. 2012) (Figure 2.11A) that

negated both the downregulation in cathepsin D gene expression (Figure 2.11B) and the

reduction in cathepsin D activity (Figure 2.11C) with JAK2 siRNA. By immunoblotting, we

observed an increase in LC3-II with TFEB overexpression and an augmentation in this increase

with the inhibitor of late-phase autophagy bafilomycin A1 (Figure 2.11D), indicative of increased

autophagic flux with TFEB overexpression that was blocked by bafilomycin A1. Unlike

bafilomycin A1, however, JAK2 siRNA did not augment the increase in LC3-II with TFEB

overexpression (Figure 10D), suggesting that JAK2 is upstream of TFEB in autophagy

regulation. Lastly, to assess whether the enhancement of autophagic flux with TFEB

overexpression improved podocyte function, we assessed the passage of fluorescently labeled

albumin across podocyte monolayers. Whereas JAK2 knockdown increased albumin transport

across monolayers, this increase was negated by TFEB overexpression (Figure 2.11E).

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Figure 2.10: TFEB overexpression restores lysosome function and albumin permselectivity

in JAK2-deficient mouse podocytes. (A) Immunoblotting for GFP in control mouse podocytes

or podocytes transfected with EGFP-tagged TFEB. (B) Cathepsin D mRNA levels under control

conditions (scramble) or transfected with JAK2 siRNA, EGFP-tagged TFEB, or JAK2 siRNA

and EGFP-tagged TFEB (n= 4-6 per condition). (C) Cathepsin D activity in podocytes under

control conditions (scramble) or transfected with JAK2 siRNA, EGFP-tagged TFEB, or JAK2

siRNA and EGFP-tagged TFEB (n=3-8 per condition). (D) Immunoblotting for LC3 in podocytes

transfected with EGFP-tagged TFEB in the presence or absence of 100 nM bafilomycin A1 for 4

hours or JAK2 siRNA for 24 hours (n=3-6 per condition). (E) Albumin permeability in podocytes

under control conditions (scramble) or transfected with JAK2 siRNA, EGFP-tagged TFEB, or

JAK2 siRNA and EGFP-tagged TFEB (n=3-5 per condition). EGFP, enhanced green fluorescent

protein; GFP, green fluorescent protein; RPLP0, large ribosomal protein P0; AU, arbitrary units.

Values are mean ± SEMs. *P<0.05 versus control; †P<0.05 versus all other groups; ‡P<0.001

versus all other groups by one-way ANOVA with a Fisher least significant difference test.

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2.4. DISCUSSION

The autophagy-lysosome pathway is a highly regulated and evolutionarily conserved catabolic

process that enables cells to remove and recycle intracytoplasmic material during times of stress

or starvation. It seems to be particularly important to the maintenance of the health of nonmitotic

cells, such as the neurons of the central nervous system (reviewed in Rubinsztein, DiFiglia et al.

2005) and the podocytes of the renal glomerulus (Hartleben, Gödel et al. 2010). Here, we found

that genetic removal of the kinase JAK2 impairs autophagy completion and podocyte function.

JAK/STAT signaling facilitates podocyte autophagy by promoting expression of the transcription

factor TFEB that coordinates a network of genes that regulate autophagic-lysosomal function.

Collectively, these findings (1) highlight the importance of JAK2-dependent autophagic

processes to podocyte homeostasis, (2) uncover the significance of TFEB to the maintenance of

podocyte function, and (3) show that TFEB is itself transcriptionally regulated by JAK2/STAT1

in podocytes.

Since an original report described the importance of autophagy to podocyte homeostasis in aging

mice just years ago (Hartleben, Gödel et al. 2010), there has been a rapid recognition that

autophagic disturbance causes podocyte dysfunction in a range of disease settings (Yamahara,

Kume et al. 2013, Kawakami, Gomez et al. 2015, Lenoir, Jasiek et al. 2015, Tagawa, Yasuda et

al. 2015). There are three forms of autophagy: microautophagy (the direct sequestration of

cytoplasmic material into lysosomes), chaperone-mediated autophagy (the transport of cargo

proteins to lysosomes for degradation), and macroautophagy (the best studied form; herein

termed autophagy) (reviewed in Lapierre, Kumsta et al. 2015). (Macro)autophagy can be

conceptualized as taking place through two consecutive phases: (1) the induction of autophagy,

formation of double-membraned autophagosomes, and sequestration of cytoplasmic debris; and

(2) the fusion of autophagosomes with lysosomes and the degradation of the sequestered debris

(reviewed in Shen and Mizushima 2014, reviewed in Lapierre, Kumsta et al. 2015). Historically,

efforts to understand the mechanisms by which autophagic processes are regulated have tended to

focus on its induction. Indeed, the factors that promote autophagy induction (e.g., nutrient

deprivation, 5’ AMP-activated protein kinase, and inhibition of the mammalian target of

rapamycin complex 1) are generally well understood. It is only in the past few years that

attentions have shifted to the strategies used by the cell to ensure autophagy completion. These

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attentions have been focused (at least in part) by the discovery of TFEB, initially as a master

regulator of lysosomal biogenesis and function (Sardiello, Palmieri et al. 2009) and subsequently

as a regulator of broader autophagic-lysosomal processes (Settembre, Di Malta et al. 2011). In

this study, we examined the effects of knockout of JAK2 in podocytes of otherwise healthy mice

and knockdown of JAK2 with siRNA in cultured podocytes under conditions of serum starvation.

In each case, JAK2 deficiency resulted in an increase in autophagosome volume fraction and the

accumulation of the autophagy cargo receptor of ubiquitinated proteins p62, which are together

indicative of autophagy initiation but failed completion. Impairment in podocyte function was

accompanied by an increase in urine albumin excretion in mice and an increase in albumin

passage across podocyte monolayers. These findings are generally congruent with the previous

descriptions of the phenotype of mice in which autophagy-related genes were selectively

removed from podocytes (Hartleben, Gödel et al. 2010, Riediger, Quack et al. 2011) and the

phenotype of mice when the lysosomal protein cathepsin D was deleted (Yamamoto-Nonaka,

Koike et al. 2016). Whereas both basal autophagy and autophagy induction in response to

nutrient deprivation are of use for cellular survival, under certain circumstances, autophagy can

be detrimental, both initiating and executing cell death (reviewed in Eskelinen 2005). To help us

distinguish between cause and consequence, we elected to study JAK2podKO mice at a young,

albeit adult, age (10 weeks). The largely unremarkable glomerular appearance under light

microscopy at this age suggests that the impairment in autophagy completion with JAK2

knockdown was a de novo event and was not a response to generalized cellular injury.

We considered two possibilities for the impairment of autophagy completion with JAK2

knockdown: (1) a block in the fusion of autophagosomes and lysosomes and (2) impairment in

lysosome function itself. We found that few genes encoding proteins involved in

autophagosome-lysosome fusion were altered in their expression with JAK2 knockdown and that

those that were altered were all marginally increased in their expression. We speculate that this

increase reflects a compensatory response to a downstream impediment. Reflective of lysosome

enzymatic dysfunction, we found that JAK2 deficiency was accompanied by an increase in

lysosome number, a decrease in the expression of lysosomal genes, and a reduction in the activity

of the lysosomal aspartic proteinase, cathepsin D. We went on to discover that this dysfunction

was due to the downregulation of the transcriptional regulator of lysosomal biogenesis and

function, TFEB. TFEB is a member of the basic helix-loop-helix leucine zipper family of

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transcription factors that was first identified as a regulator of coordinated lysosomal biogenesis

and function in 2009 (Sardiello, Palmieri et al. 2009). In its phosphorylated, inactive form, TFEB

resides in the cytoplasm (reviewed in Shen and Mizushima 2014). On activation, it shuttles to

the nucleus, where it binds to specific E-box sites at the promoters of several lysosomal genes

that have been collectively termed the Coordinated Lysosomal Expression And Regulation gene

network (Sardiello, Palmieri et al. 2009). Subsequent to the initial discovery of the role of TFEB

in the coordinated regulation of lysosomal genes, it has now become apparent that the

transcription factor also drives the expression of a network of autophagy-related genes (Palmieri,

Impey et al. 2011, Settembre, Di Malta et al. 2011). Although TFEB is known to be regulated

post-translationally (reviewed in Shen and Mizushima 2014), this study also highlights the

importance of its transcriptional regulation. Specifically, the JAK2-activated transcription factor

STAT1 binds to the TFEB promoter, and knockdown of JAK2 decreases TFEB promoter

activity, mRNA and protein levels, and nuclear localization. A functional role for TFEB

downregulation in impaired autophagy completion with JAK2 knockdown is implied by the

coincident downregulation in TFEB-regulated genes and a restoration of autophagic flux and

podocyte permselectivity by TFEB overexpression.

The autophagosomal-lysosomal clearance of accumulated proteins and damaged organelles is a

complex process. One of the nuances of this complexity is its temporal regulation. As an

illustration, the LC3-phosphatidylethanolamine conjugate, LC3-II, is recruited to

autophagosomal membranes and degraded in the autolysosomal lumen during autophagy. In

HeLa cells, TFEB overexpression caused an increase in LC3-II abundance, and siRNA-mediated

knockdown of TFEB downregulated LC3-II (Settembre, Di Malta et al. 2011). In podocytes, we

similarly observed an increase in LC3-II with TFEB overexpression, and we observed an

augmentation of this increase with the inhibitor of late-phase autophagy, bafilomycin A1,

indicative of heightened autophagic flux. In contrast, downregulation of TFEB with JAK2

knockdown also caused LC3-II accumulation. This is likely to be a consequence of lysosomal

dysfunction. Indeed, specific knockdown of the lysosomal enzyme and TFEB target cathepsin D

was recently shown to lead to LC3-II accumulation in podocytes (Yamamoto-Nonaka, Koike et

al. 2016). In this respect, it is noteworthy that, whereas TFEB expression was decreased with

JAK2 knockout/knockdown in podocytes, it was not abolished; also, TFEB-dependent

autophagosomal-lysosomal genes were not uniformly reduced in their expression. Thus, with

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persistent, albeit reduced, TFEB expression, autophagy completion was impaired but was not

negated, causing a phenotype characterized by the accumulation of autophagosomes and

lysosomes and an increase in albuminuria without florid glomerular damage. The discovery that,

under normal circumstances, JAK2 preserves podocyte functionality by promoting autophagy

completion warrants consideration in the context of JAK/STAT pathway activation in human

diabetic kidney disease (Berthier, Zhang et al. 2009, Hodgin, Nair et al. 2013) and the

preliminary benefits of the JAK1/2 inhibitor baricitinib in a 24-week, phase 2 study of

participants with type 2 diabetes and kidney disease (Tuttle, Brosius et al. 2018). Although the

findings herein described would seem to sound a cautionary note as to the possibility of adverse

renal effects of JAK2 inhibition, several distinctions should be considered. First, in an effort to

unravel the normal actions of JAK2, we examined the effects of the kinase in one particular cell

type (the podocyte), whereas systemic JAK inhibition affects multiple cell types, not even those

limited to the kidney. Second, whereas we examined the consequences of JAK2

knockout/knockdown, baricitinib is an enzyme inhibitor and equally efficacious in blocking the

activity of both JAK1 and JAK2 (IC50=5.9 and 5.7 nM, respectively)(Fridman, Scherle et al.

2010). Third, although JAK2 functions in a homeostatic capacity in normal podocytes, the

JAK/STAT signaling pathway also plays an important role in the development of inflammation

(reviewed in Kaplan 2013), one of the principal drivers of the progression of diabetic kidney

disease (reviewed in Heerspink and De Zeeuw 2016). Thus, the extent to which JAK inhibition

may affect JAK2-regulated podocyte autophagy completion in patients and the extent to which

these effects may temper the potentially renoprotective anti-inflammatory properties of JAK

inhibitors remain to be determined.

In summary, JAK2 functions in a homeostatic capacity in podocytes by facilitating autophagy. It

does this by regulating the expression of the transcription factor TFEB that is necessary for

normal autophagic-lysosomal function (Figure 2.12). These actions should be borne in mind in

considering the long-term implications of therapies that interfere with the JAK/STAT signaling

pathway. They also raise the intriguing possibility that therapeutically modulating TFEB activity

(reviewed in Rubinsztein, Codogno et al. 2012) may improve podocyte health in glomerular

disease.

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Figure 2.11: JAK2 regulates autophagy completion in podocytes. (A) Under normal

conditions (wildtype), signaling through JAK2 induces translocation of STAT1 to the nucleus,

where STAT1 binds to the promoter region of the gene encoding the transcription factor TFEB.

TFEB, in turn, facilitates the transcription of genes involved in lysosome and autophagosome

function, including cathepsin D. Autophagosomes are recognized by the presence of LC3-II and

contain proteins bound to p62 and targeted for degradation. Autophagy completion involves the

fusion of double-membrane–bound autophagosomes with lysosomes (recognized by the presence

of LAMP2) and subsequent degradation of the contents of the resultant autolysosome. (B) When

JAK2 is absent (JAK2podKO), TFEB expression is diminished, leading to decreased expression of

lysosomal genes (including cathepsin D) and lysosomal dysfunction, impairing autophagy

completion, and leading to podocyte dysfunction, diminished podocyte permselectivity, and

consequent albuminuria.

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CHAPTER 3: Podocyte-specific JAK2 deletion and JAK inhibition

Have an Anti-inflammatory Effect in the Diabetic Kidney

A portion of this work (Table 3.2) has been adapted with permission from Alghamdi, T.A.,

Batchu, S.N., Hadden, M.J., Yerra, V.G., Liu, Y., Bowskill, B.B., Advani, S.L., Geldenhuys, L.,

Siddiqi, F.S., Majumder, S., Advani, A. (2018). Histone H3 serine 10 phosphorylation facilitates

endothelial activation in diabetic kidney disease. Diabetes. 67(12):2668–2681.

Contribution of authors:

T.A.A. designed and performed the experiments, analyzed the data, and wrote this chapter.

S.N.B. contributed to the data presented in Table 3.2, B.B.B. assisted with the animal studies,

S.L.A. assisted with the immunohistological experiments. A.A. designed the experiments,

supervised the study, and revised and edited this chapter.

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3.1. INTRODUCTION

Global deletion of JAK2 in mice leads to embryonic lethality due to impaired hematopoiesis

(Neubauer, Cumano et al. 1998) and in my studies presented in Chapter 2, its deletion from

podocytes resulted in impaired autophagy completion and a 3-fold increase in albuminuria in

mice (Alghamdi, Majumder et al. 2017). However, it is worth noting that while gene ablation of

JAK2 under normal conditions may have detrimental effects, modulation of JAK2 activity under

abnormal conditions may be advantageous. As reviewed in Chapter 1, the discovery of the

activating JAK2 mutation (JAK2V617F) in certain hematopoietic stem-cell disorders raised a

strong interest amongst the pharmaceutical industry in developing selective JAK2 inhibitors

(Kralovics, Passamonti et al. 2005). The first JAK inhibitor ruxolitinib (INCB018424, Jakafi,

Incyte Corporation) received FDA approval in 2011 for the treatment of polycythemia vera and

myelofibrosis (Verstovsek, Kantarjian et al. 2010), and development of other JAK inhibitors has

evolved apace (reviewed in Moran 2012). For instance, Eli Lilly and Incyte Corporation have

developed an orally administrated JAK1/2 inhibitor, baricitinib (INCB028050), which has been

shown to be effective in the treatment of rheumatoid arthritis (Keystone, Taylor et al. 2013,

Genovese, Kremer et al. 2016). At the time of conducting my experiments, baricitinib was being

evaluated in a phase 2 clinical trial in patients with type 2 diabetes at high-risk for progressive

diabetic kidney disease (NCT01683409) (Tuttle, Brosius et al. 2018). The data from the clinical

trial were recently published and they demonstrated that baricitinib reduced albuminuria by 41%

in these patients in comparison to placebo treated individuals and this reduction was associated

with a decrease in renal inflammation markers with no change in glomerular filtration rate

(Tuttle, Brosius et al. 2018). Elsewhere, cumulative evidence demonstrates that JAK/STAT

activation plays a role in the pathogenetic response of resident renal cells including mesangial

cells and fibroblasts (Nahman, Leonhart et al. 1992, Han, Isono et al. 1999). However,

comparatively, little has been known about the role of the JAK/STAT pathway in glomerular

podocytes in the diabetic kidney.

Having identified the homeostatic actions of JAK2 in podocytes in the normal setting and given

that JAK inhibition has been proposed as a potential therapeutic approach for the treatment of

DKD, we set out to: i) investigate the effect of JAK inhibition in an experimental model of DKD,

and ii) examine the effects of JAK2 absence in podocytes under diabetic conditions. We

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hypothesized that systemic JAK inhibition would attenuate kidney injury in an experimental

model of diabetes and, based upon our results shown in Chapter 2, that deletion of JAK2 from

podocytes may exacerbate the increase in albuminuria in a mouse model of DKD.

3.2. RESEARCH DESIGN AND METHODS

3.2.1. Animal studies

3.2.1.1. JAK inhibition study in streptozotocin (STZ)-diabetic eNOS-/- mice

The effects of AZD1480 (MedChemExpress, Monmouth Junction, NJ), an ATP-competitive JAK

inhibitor (IC50, JAK2 0.26 nM, JAK1 1.3nM) (Derenzini, Lemoine et al. 2011), on kidney

function were assessed in streptozotocin (STZ)-diabetic endothelial nitric oxide synthase

knockout (eNOS-/-) mice. Male nondiabetic and diabetic, C57BL/6 wildtype (WT) and eNOS-/-

mice were studied at eight weeks of age (n=7-12/group) (The Jackson Laboratory, Bar Harbor,

ME). Diabetes was induced in WT and eNOS-/- mice by five daily intraperitoneal injections of

STZ (55mg/kg) in 0.1M citrate buffer, pH 4.5, for five days (or citrate buffer alone for controls)

after a 4-hour fast. STZ-diabetic eNOS-/- mice were treated with either AZD1480 (50 mg/kg) in

0.5% hypromellose, 0.1% Tween 80 (Xin, Herrmann et al. 2011) or vehicle by once daily gavage,

beginning with the first STZ injection for three weeks.

3.2.1.2. Generation of STZ-diabetic podocyte-specific JAK2 knockout mice

JAK2podKO mice were generated and characterized as previously described in Chapter 2

(Alghamdi, Majumder et al. 2017). Male JAK2Ctrl or JAK2podKO mice aged eight weeks were

randomized to receive a daily intraperitoneal injection of STZ (55 mg/kg) in 0.1M citrate buffer,

pH 4.5, for five days (or citrate buffer alone for controls) after a 4-hour fast. We studied four

groups of mice: JAK2Ctrl (n=9), JAK2podKO (n=7), STZ-diabetic JAK2Ctrl (n=8), and STZ-diabetic

JAK2podKO (n=6). Two weeks after the first STZ injection, diabetes was confirmed by fasting

blood glucose testing (One Touch UltraMini, LifeScan Canada Ltd., Burnaby, BC, Canada) and

mice were followed for a total of 14 weeks from the first STZ injection.

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Urine samples were collected after animals were housed individually in metabolic cages for 24

hours. Urine albumin or CCL2 excretion was determined by mouse albumin ELISA (Assaypro,

Charles, MO) and Mouse/Rat CCL2/JE/MCP-1 Quantikine ELISA Kit (R & D Systems,

Minneapolis, MN), respectively. At sacrifice, kidney tissues were immersed in 10% neutral

buffered formalin, routinely processed, and embedded in paraffin. All experimental procedures

adhered to the guidelines of the Canadian Council on Animal Care and were approved by the St.

Michael’s Hospital Animal Care Committee.

3.2.2. Mesangial matrix index

Paraffin-embedded kidney sections were stained with periodic acid-Schiff (PAS). Briefly, slides

were de-waxed twice in xylene for 3 minutes each, followed by twice immersion in 100% ethanol

for 3 minutes each, one time in 70% ethanol for 3 minutes, and then washed thrice with distilled

water for 5 minutes each. Kidney tissue sections were then oxidized by adding 2-4 drops of

periodic acid and incubated at room temperature for 30 mins. After washing the slides three times

with distilled water for 5 minutes each, 2-4 drops of Shiff’s reagent were placed on the tissue

sections, followed by incubation at room temperature for 30 minutes. The slides were then

washed under warm tap water for a minimum of 10 minutes. For counterstain and dehydration,

slides were dipped twice in haematoxylin, and washed with running tap water until clear. Slides

were then dipped in Scott’s tap water, washed with running tap water for 2 minutes, immersed

sequentially in 70% ethanol for 1 minute, twice in 100% ethanol for 1 minute each, once in 100%

ethanol for 2 minutes each, and twice in xylene for 2 minutes each. Finally, mounting media and

coverslips were placed on tissue sections and the slides were left to dry. For each mouse from the

STZ-diabetic eNOS-/- study, 30 glomeruli per PAS-stained kidney section were assessed for

mesangial matrix accumulation using a semi-quantitative scoring method (Advani, Connelly et

al. 2011, Batchu, Majumder et al. 2016). Briefly, depending on the magnitude of mesangial

matrix deposition, each glomerulus was assigned a score using the following scale: (0= normal

appearance; 1= mesangial matrix deposition up to 25% of the glomerulus; 2= 25 to 50% of the

glomerulus; 3= 50 to 75%; and 4= 75 to 100% of the glomerulus). The total number of glomeruli

was multiplied by the assigned score. Mesangial matrix index was calculated using the following

formula:

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Where Fi is the per cent of glomeruli in the mouse with a given score (i) (Kelly, Hepper et al.

2003).

3.2.3. Cell culture studies

Conditionally immortalized human podocytes were provided by Dr. Moin Saleem, University of

Bristol, UK (Saleem, O'Hare et al. 2002). Cells were seeded on type I collagen-coated culture

plates in RPMI-1640 medium with L-glutamine and sodium bicarbonate (Sigma Aldrich, St.

Louis, MO, USA) supplemented with 10% fetal bovine serum (FBS) (Wisent Inc., St. Bruno,

QC, Canada), recombinant mouse interferon-γ (IFN-γ, final concentration 0.02 µg/ml) (Sigma

Aldrich, St. Louis, MO, USA), 100 U/ml penicillin, and 0.1 mg/ml streptomycin (ThermoFisher

Scientific, Rockford, IL, USA). The cells were grown at 33°C (permissive conditions) to reach

80-90% confluence, and then cultured without IFN-γ at 37°C (non-permissive conditions) for 14

days to differentiate. Cultured differentiated human podocytes were treated with 19.4 mM

glucose (final concentration 25 mM, high glucose) or mannitol (final concentration 25 mM,

osmotic control), or maintained under normal (5.6 mM) glucose conditions for 48 hours. After 48

hours, the conditioned media were collected for an array of 41 cytokines and chemokines using

the Human Cytokine/Chemokine Array 41-Plex performed by Eve Technologies Corp. (Calgary,

Alberta, Canada).

3.2.4. Statistical analysis

Data are expressed as mean ± S.E.M. Statistical significance was determined by 1-way ANOVA

followed by Fisher least significant difference post hoc test for more than two groups and 2-tailed

Student t test for two group comparisons. Statistical analyses were performed using GraphPad

Prism for Mac OS X (GraphPad Software Inc., San Diego, CA).

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3.3. RESULTS

3.3.1. JAK2 inhibition attenuates albuminuria in STZ-diabetic eNOS knockout mice

In our first series of experiments, we set out to examine the effects of systemic JAK inhibition

using the JAK inhibitor AZD1480 in STZ-diabetic eNOS-/- mice, a model of DKD that has been

previously characterized in our lab (Yuen, Stead et al. 2012). We selected these mice as a model

of DKD because the kidney injury in STZ-diabetic eNOS-/- mice is characterized by glomerular

endothelial dysfunction and podocyte injury, and because these mice develop massive

albuminuria soon after the induction of diabetes (Yuen, Stead et al. 2012). This allows for a

relatively short-term assessment of compounds with potential antialbuminuric effect (Batchu,

Majumder et al. 2016, Thieme, Majumder et al. 2017). To investigate the effects of JAK

inhibition on renal function in DKD, STZ-diabetic eNOS-/- mice were treated with either vehicle

or AZD1480 for three weeks. Age-matched WT, eNOS-/-, STZ-diabetic WT, and STZ-diabetic

eNOS-/- mice were studied as controls. As expected, body weight was reduced and kidney:body

weight ratio was increased in STZ-diabetic mice in comparison to their non-diabetic counterparts.

Blood glucose was marginally higher in STZ-diabetic eNOS-/- mice in comparison to STZ-

diabetic WT mice, whereas urine albumin excretion was increased approximately 10-fold (Table

3.1). Treatment with the JAK inhibitor AZD1480 was associated with a small but statistically

significant reduction in blood glucose in STZ-diabetic eNOS-/- mice in comparison to vehicle

treated animals, whereas urine albumin excretion was reduced by approximately 50% (Table 3.1).

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Table 3.1: Functional characteristics of control and streptozotocin-diabetic (STZ) wildtype

(WT) and endothelial nitric oxide synthase knockout (eNOS-/-) mice treated with vehicle or

AZD1480 (50 mg/kg).

WT STZ-WT eNOS-/- STZ-eNOS-/- STZ-eNOS-/-

+AZD1480

N 12 14 11 9 7

Body weight (g) 250 210a 240b 191acd 201ad

Kidney weight (g) 0.160.01 0.160.00 0.130.00e 0.150.00g 0.140.00cf

Kidney weight:body

weight (%) 0.650.02 0.760.04df 0.540.01h 0.800.02de 0.700.04ij

Blood glucose

(mmol/L) 9.00.6 22.61.6ad 9.90.6 27.61.7acd 24.21.9ad

Urine albumin

excretion (µg/24h) 121 6616 4512 66563k 30069k

Values are mean S.E.Ms. aP< 0.0001 vs. WT, bP<0.001 vs. STZ-WT, cP<0.05 vs. STZ-WT,

dP< 0.0001 vs. eNOS-/-, eP<0.001 vs. WT, fP<0.01 vs. WT, gP<0.05 vs. eNOS-/-, hP<0.05 vs.

WT, iP< 0.01 vs. eNOS-/-, jP< 0.05 vs. STZ-eNOS-/-, kP<0.0001 vs. all other groups, by one-

way ANOVA with a Fisher least significant difference test.

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3.3.2. JAK inhibition attenuates urine CCL2 excretion and mesangial matrix accumulation in STZ-diabetic eNOS knockout mice

Given the established role of JAK2 in inflammation (reviewed in Hanada and Yoshimura 2002,

reviewed in O'shea and Plenge 2012) and that its activation has been reported in kidney biopsies

from patients with diabetic kidney disease (Berthier, Zhang et al. 2009, Woroniecka, Park et al.

2011), we queried whether systemic JAK inhibition affects mediators of inflammation in the

diabetic kidney. To do this, we looked at urine excretion of the chemokine CCL2 (also known

MCP-1), a pro-inflammatory chemokine that mediates leukocyte infiltration and that has been

extensively studied in the context of DKD (Saitoh, Sekizuka et al. 1998, Matsukawa, Hogaboam

et al. 1999, Tashiro, Koyanagi et al. 2002, Nam, Paeng et al. 2012). Elevated levels of urine

CCL2 excretion have been shown to be associated with renal decline in diabetic mice (Chow,

Nikolic-Paterson et al. 2006), in microalbuminuric patients with type 1 diabetes (Wolkow,

Niewczas et al. 2008), and in patients with type 2 diabetes (Takebayashi, Matsumoto et al. 2006).

In this study, we observed a marked increase in urine CCL2 excretion in STZ-diabetic eNOS-/-

mice in comparison to non-diabetic control groups (Figure 3.1A). After three weeks, AZD1480

treatment was associated with a significant reduction in urine CCL2 excretion in STZ-diabetic

eNOS-/- mice (Figure 3.1A). To examine whether JAK inhibition affects glomerular injury in

STZ-diabetic eNOS-/- mice, we evaluated mesangial matrix accumulation in periodic acid-Schiff-

stained glomerular kidney sections obtained from the studied mice. Whereas the extent of

mesangial matrix was increased in the glomeruli of STZ-diabetic eNOS-/- mice in comparison to

control groups, this was significantly reduced with AZD1480 treatment (Figure 3.2B-G).

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Figure 3.1: Effect of JAK2 inhibition with AZD1480 on urine CCL2 excretion and

mesangial matrix accumulation in the glomeruli of STZ-diabetic eNOS-/- mice. (A) Urine

CCL2 excretion (WT, n=6; STZ-WT, n=7; eNOS-/-, n=5; STZ-eNOS-/-, n=5, STZ-eNOS-/- +

AZD1480, n=6). (B-G) Representative periodic acid-Schiff-stained kidney sections from WT

(B), STZ-WT (C), eNOS-/- (D), STZ-eNOS-/- (E), and STZ-eNOS-/- + AZD1480 (F). Original

magnification ×400. (G) Mesangial matrix index (WT, n=7; STZ-WT, n=10; eNOS-/-, n=8; STZ-

eNOS-/-, n=9, STZ-eNOS-/- + AZD1480, n=8). AU, arbitrary units. Values are mean S.E.Ms. *P

< 0.001 vs. nondiabetic groups, †P<0.05 vs. diabetic groups, ‡P < 0.001 vs. all other groups, by

one-way ANOVA with a Fisher least significant difference test.

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3.3.3. Podocyte-specific JAK2 deletion does not influence urine albumin excretion in STZ-diabetic mice

Having found that JAK inhibition attenuated albuminuria in STZ-diabetic eNOS-/- mice, whereas

deletion of JAK2 from podocytes under non-diabetic conditions conversely contributes to the

development of albuminuria, we went on to examine the effect of JAK2 deletion from podocytes

in diabetic mice. To do this, JAK2Ctrl and JAK2podKO mice were made diabetic with STZ and

were followed for 14 weeks. High blood glucose levels were confirmed in STZ-diabetic animals

(Figure 3.2A). Although no change was observed in kidney weight (Figure 3.2B), STZ-diabetic

mice exhibited significantly lower body weight and increased kidney weight:body weight ratio

compared to their respective non-diabetic control groups (Figure 3.2 C and D). Consistent with

our earlier findings, non-diabetic JAK2podKO mice exhibited almost a 3-fold increase in

albuminuria in comparison to JAK2Ctrl mice and this increase was augmented with STZ-induced

diabetes (Figure 3.2E). Whereas albuminuria was increased in STZ-diabetic mice, there was no

difference in 24-hour urine albumin excretion between STZ-diabetic JAKCtrl and STZ-diabetic

JAK2podKO animals (Figure 3.2E).

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Figure 3.2: Effect of podocyte-specific JAK2 deletion on kidney function in

streptozotocin (STZ)-diabetic mice followed for 14 weeks. A) Blood glucose. B) Body

weight. C) Kidney weight. D) Kidney weight:body weight ratio. E) Urine albumin excretion.

Values are mean S.E.Ms. *P<0.0001 vs. nondiabetic groups, †P<0.001 vs. nondiabetic

groups, ‡P<0.05 vs. nondiabetic groups, §P<0.01 vs. nondiabetic groups, ¶P< 0.05 vs.

JAK2Ctrl, by one-way ANOVA with a Fisher least significant difference test.

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3.3.4. Podocyte-specific JAK2 deletion attenuates urine CCL2 excretion

Next, because we had found that JAK inhibition attenuates urine CCL2 excretion in STZ-diabetic

eNOS-/- mice, and because CCL2 expression has been shown to be under the regulatory control of

JAK2 in other cell-types (Tanimoto, Murata et al. 2008), we queried whether deletion of JAK2

from podocytes would attenuate urine CCL2 excretion. As expected, there was a marked increase

in urine CCL2 excretion in STZ-diabetic mice in comparison to their nondiabetic control groups

(Figure 3.3). In contrast, JAK2 deletion from podocytes resulted in a marked diminution in urine

CCL2 excretion under diabetic conditions with no change under non-diabetic conditions (Figure

3.3). Collectively, these data suggest that although podocyte-specific JAK2 deletion does not

alter urine albumin excretion, its absence in podocytes does attenuate urine CCL2 excretion.

Figure 3.3: Effect of JAK2 knockout from podocytes on urine CCL2 excretion in STZ-

diabetic mice. Urine CCL2 excretion in JAK2Ctrl (n=6), JAK2podKO (n=3), STZ-diabetic JAK2Ctrl

(n=4), and STZ-diabetic JAK2podKO (n=5). Values are mean S.E.Ms. *P<0.0001 vs. nondiabetic

control groups, †P<0.001 vs. nondiabetic control groups, ‡P<0.0001 vs. STZ-diabetic JAK2Ctrl,

by one-way ANOVA with a Fisher least significant difference test.

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3.3.5. The chemokine CCL2 is enriched in culture media conditioned by podocytes exposed to high glucose

Increased urine CCL2 excretion in STZ-diabetic mice and diminished urine CCL2 excretion by

deletion of JAK2 from podocytes led us to conclude that podocytes are a major source of CCL2

in the setting of diabetes. To explore this possibility further, we exposed cultured human

podocytes to high glucose concentration for 48 hours and we used a multiplex array to measure

the concentration of 41 chemokines and cytokines in the culture media (Table 3.1). The most

abundant cytokines/chemokines present in the culture media of podocytes under normal

conditions were C-X-C motif ligand 1 (CXCL1)/CXCL2/CXCL3 (pan-GRO), interleukin-6 (IL-

6), IL-8, CCL2, and vascular endothelial growth factor A. Interestingly, out of all 41

cytokines/chemokines surveyed, CCL2 was the only one to be significantly upregulated with the

addition of high glucose to the culture medium (Table 3.2). In Chapter 4, I will discuss how we

built on these initial observations to explore the role of CCL2 in controlling the glomerular cell

phenotype in diabetes.

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Table 3.2: Chemokine and cytokine content of culture medium of human podocytes under

control conditions or after incubation with high (25 mM) glucose or mannitol for 48 h.

Data are mean ± SD and expressed in pg/mL. Boldface type highlights CCL2 levels. CSF,

colony-stimulating factor; EGF, epidermal growth factor; FGF, fibroblast growth factor; IFN,

interferon; Pan-GRO, CXCL1/CXCL2/CXCL3; PDGF, platelet-derived growth factor; TGF,

transforming growth factor; TNF, tumor necrosis factor; VEGF, vascular endothelial growth

factor. aP , 0.01 vs. control; bP , 0.001 vs. control; cP , 0.05 vs. control by one-way ANOVA

followed by Fisher least significant difference post hoc test.

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3.4. DISCUSSION

Anti-inflammatory agents represent some of the most promising future therapies for the treatment

of DKD, with inhibitors of both JAK1/2 (reviewed in Brosius, Tuttle et al. 2016, Tuttle, Brosius

et al. 2018) and the CCL2 receptor (CCR2) (de Zeeuw, Bekker et al. 2015), recently reporting

favorable results in phase 2 study. These agents may confer their benefits through actions on

leukocytes and/or on resident renal cells. In the present study, we found that systemic inhibition

of JAK with the pharmacological JAK inhibitor AZD1480 attenuated albuminuria, urine CCL2

excretion, and mesangial matrix accumulation in a mouse model of DKD. Without affecting

albuminuria, removal of the kinase JAK2 from podocytes reduced excretion of the inflammatory

protein CCL2 in the urine of STZ-diabetic mice. In cultured human podocytes, we observed a

significant enrichment of the chemokine CCL2 in the culture media of podocytes exposed to high

glucose conditions.

The results of these experiments emphasize the importance of urine CCL2 excretion as a

biomarker for kidney injury in diabetes and they demonstrate the limited value of the

measurement of albuminuria in detecting inflammatory renal changes in experimental diabetes.

High levels of urine CCL2 excretion have been shown to be a predictor of early decline in kidney

function independent of or before the development of albuminuria in some cases (Verhave,

Bouchard et al. 2013, Fufaa, Weil et al. 2015). This is not surprising considering that relying

solely on albuminuria as a central measure of renal function has been questioned for more than a

decade, especially given that several studies have reported the absence of albuminuria in many

patients with DKD (Kramer, Nguyen et al. 2003, Perkins, Ficociello et al. 2003). These studies

have led to a search for additional biomarkers such as measures of inflammation, which have

emerged as new diagnostic and prognostic tools in DKD studies (reviewed in Winter, Wong et al.

2018).

Our findings also highlight the multifaceted function of JAK2 in health and disease. JAK2 is a

ubiquitously expressed cytoplasmic tyrosine kinase that mediates cytokine-dependent signal

transduction. Of the four members of the JAK family, disruption of JAK2 gene is the only one

that causes embryonic death (Neubauer, Cumano et al. 1998, Parganas, Wang et al. 1998,

reviewed in Sandberg, Wallace et al. 2004), and its deletion from podocytes resulted in impaired

autophagy and lysosomal dysfunction under non-diabetic conditions (Chapter 2) (Alghamdi,

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Majumder et al. 2017). However, under pathological conditions, activation of JAK2 has been

implicated in inflammatory diseases and it has been reported to be upregulated in patients with

early stage DKD (Berthier, Zhang et al. 2009, Hodgin, Nair et al. 2013). In this study, we

observed a decrease in urine CCL2 excretion with JAK inhibition in STZ-diabetic eNOS-/- mice

and podocyte-specific JAK2 deletion in diabetic mice, suggesting that podocyte JAK2 may

regulate inflammatory processes and that its modulation may attenuate kidney dysfunction in

diabetes. These findings are in line with data from a recent phase 2 clinical trail of the JAK1/2

inhibitor baricitinib in patients with DKD (Tuttle, Brosius et al. 2018). Treatment with baricitinib

in these patients not only reduced albuminuria, but it also resulted in a dose-dependent decrease

in inflammatory biomarkers implicated in DKD including plasma soluble tumor necrosis factor

receptors 1 and 2 (sTNFR1 and sTNFR2), serum amyloid A (SAA), VCAM1 and ICAM1.

Moreover, there was a reduction in urinary CCL2 and CXCL10 in patients treated with

baricitinib, indicative of their correlation with local inflammation in the kidney rather than

systemic inflammation (Wolkow, Niewczas et al. 2008). Although urine CXCL10 excretion was

not assessed in our rodent models of DKD, we observed no change in the levels of CXCL10 in

cultured human podocytes exposed to high glucose. In contrast, CCL2 was the only chemokine

that was significantly upregulated. The observation that deletion of JAK2 from podocytes

attenuated urine CCL2 excretion in diabetic mice suggests that podocyte JAK2 may in part

contribute to the elevated levels of urine CCL2 excretion in experimental models of diabetes.

The critical role of the chemokine CCL2 and its receptor CCR2 in DKD has been described in

animal models of diabetes. For instance, the CCL2/CCR2 axis has been suggested to exacerbate

the progression of DKD by increasing podocyte motility and albumin permeability (Lee, Chung

et al. 2009). Moreover, blockade of CCL2 and its receptor CCR2 was shown to prevent the

development of DKD in experimental models of type 1 and type 2 diabetes (Kanamori,

Matsubara et al. 2007, Sayyed, Hägele et al. 2009). Indeed, clinical trials have already been

initiated to examine the efficacy of CCL2 and CCR2 inhibitors for the treatment of DKD

(NCT01547897, NCT01447147, NCT01109212). Although these agents have shown promising

results in patients with DKD, the precise pathomechanisms of how the CCL2/CCR2 signaling

pathway contributes to the development of DKD remain to be fully explored.

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This study has several limitations that need to be acknowledged. First, the discordance of the

phenotype between STZ-diabetic JAK2podKO mice (no change in albuminuria) and STZ-diabetic

eNOS-/- mice treated with AZD1480 (reduction in albuminuria) could be the confounding effect

of eNOS absence. Indeed, several studies have shown that reduced expression of eNOS in

glomerular endothelial cells results in glomerular dysfunction and accelerates DKD in

experimental models of diabetes, demonstrating its protective role in the glomerulus (Zhao,

Wang et al. 2006, Kanetsuna, Takahashi et al. 2007, Mohan, Reddick et al. 2008, Yuen, Stead et

al. 2012). Second, the in vivo experiments were conducted in STZ-induced diabetic mouse

models; therefore, the toxic effect of STZ cannot be ruled out. Third, the effects of systemic JAK

inhibition are not limited to those on podocytes and actions on other resident renal cells may be

implicated. For instance, mesangial cells are likely to be implicated in the reduction of mesangial

matrix accumulation observed in the glomeruli of STZ-diabetic eNOS-/- mice treated with

AZD1480. Further discussion and expansion on these limitations is covered in Chapter 5. Finally,

I chose to study AZD1480 as a JAK inhibitor because of its preferential selectivity for JAK2

versus JAK1 (5-fold). However, the IC50 of AZD1480 for JAK1 is still in the low nanomolar

range (1.3 nM) and thus, a role for JAK1 in regulating urine albumin excretion in diabetes cannot

be excluded in these studies.

In summary, this study was undertaken to determine the effects of JAK2 absence in glomerular

podocytes in the diabetes setting. Whereas JAK2 absence in podocytes did not attenuate urine

albumin excretion in the diabetic kidney, its deletion from podocytes was accompanied by a

reduction in urine excretion of the pro-inflammatory chemokine CCL2. Although inhibition of

JAK2 has proven benefits in a number of diseases ranging from cancer (reviewed in LaFave and

Levine 2012) to inflammatory diseases including DKD (reviewed in Brosius, Tuttle et al. 2016),

JAK inhibition has been shown to be associated with adverse effects including anemia,

hypoglycemia, and a small increase in serum creatinine (Tuttle, Brosius et al. 2018). Owing to

the multifaceted actions of podocyte JAK2 in the kidney and given that JAK inhibitors are

regarded as promising treatment of DKD, further studies are required to fully understand the

impact of JAK2 modulation in the kidney and whether other candidates implicated in activation

of inflammatory pathways could be more suitable therapeutic targets for DKD.

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CHAPTER 4: Histone H3 Serine 10 Phosphorylation Facilitates

Endothelial Activation in Diabetic Kidney Disease

Adapted with permission from Alghamdi, T.A., Batchu, S.N., Hadden, M.J., Yerra, V.G., Liu,

Y., Bowskill, B.B., Advani, S.L., Geldenhuys, L., Siddiqi, F.S., Majumder, S., Advani, A.

(2018). Histone H3 serine 10 phosphorylation facilitates endothelial activation in diabetic kidney

disease. Diabetes. 67(12):2668–2681.

Contribution of authors:

T.A.A. designed and performed the experiments, analyzed the data, and wrote the manuscript.

S.N.B. contributed to the experiments, generation and analysis of the data presented in Figure

4.1B-D, Figure 4.3, and Figure 4.7. M.J.H. contributed to the immunohistochemical image

analysis presented in Figure 4.4B. V.G.Y. contributed to the experiments, generation and analysis

of the data presented in Figure 4.2. Y.L. assisted with in vitro experiments. B.B.B. assisted with

animal studies, S.L.A. contributed to the experiments and generation of data presented in Figure

4.5, 4.10D, and 4.11. L.G. and F.S.S. contributed to the human data presented in Figure 4.11.

S.M. contributed to data analysis and revised the manuscript. A.A. designed the experiments,

supervised the study, and wrote the manuscript.

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4.1. INTRODUCTION

Post-translational histone modifications have emerged as pivotal mediators of diabetes

complications, either permitting or preventing cellular injury. Most of the evidence associating

histone modifications with the development and progression of diabetes complications comes

from the study of histone (de)methylation or histone (de)acetylation (reviewed in Keating, van

Diepen et al. 2018). However, several other modifications can also affect histone proteins

including phosphorylation, ubiquitination, O-Glc-NAcylation, ADP-ribosylation and sumoylation

(reviewed in Keating, van Diepen et al. 2018). Whereas these alternative modifications have

important biological functions, their potential contribution to the development of diabetes

complications has largely been overlooked.

Diabetes is an inflammatory disease. Release of inflammatory cytokines by resident cells within

the diabetic kidney, for instance, facilitates the recruitment of leukocytes that in turn contribute to

the progressive fibrosis that characterizes later stage nephropathy. Diabetes is also an endothelial

disease and the enhanced expression of endothelial adhesion molecules that facilitate leukocyte

recruitment has long been linked to the development of diabetes complications (reviewed in

Navarro-Gonzalez, Mora-Fernandez et al. 2011). The endothelial expression of cell-surface

adhesion molecules that facilitate leukocyte recruitment is termed endothelial activation

(reviewed in Liao 2013). One of the archetypical endothelial adhesion molecules indicative of

endothelial activation is vascular cell adhesion molecule-1 (VCAM-1) (reviewed in Liao 2013).

VCAM-1 primarily functions as the ligand for the ß1-integrin sub-family member very late

antigen-4 (VLA-4, 41) present on the leukocyte plasma membrane and its upregulation has

been reported to occur in the kidneys of both diabetic mice (Ina, Kitamura et al. 1999) and

humans with diabetes (Seron, Cameron et al. 1991).

In the present study, we set out to explore the mechanisms that control endothelial activation

within the kidney glomerulus in diabetes. We started from the premise that the ordinary

functioning of the kidney glomerulus depends upon the orchestrated interaction of its cellular

constituents. In particular, paracrine communication between podocytes lining the urinary space

and endothelial cells lining the glomerular capillary walls maintains the permselective integrity of

the glomerular filtration barrier (reviewed in Siddiqi and Advani 2013). Having found that the

chemokine CCL2 is significantly enriched in the media of cultured human podocytes under high

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glucose conditions (Chapter 3), in this study, we set out to determine the paracrine effect of

podocyte-derived CCL2 on glomerular endothelial cell activation under high glucose conditions.

We hypothesized that CCL2 secreted by glomerular podocytes under conditions of high glucose

may promote glomerular endothelial cell activation characterized by VCAM-1 upregulation.

Beginning by testing this hypothesis, we discovered a pivotal role for the phosphorylation of

histone protein H3 on serine residue 10 (phospho-histone H3Ser10) in facilitating glomerular

endothelial activation in diabetic kidney disease.

4.2. RESEARCH DESIGN AND METHODS

4.2.1. Cell culture

Experiments were conducted in conditionally immortalized human podocytes (provided by Dr.

Moin Saleem, University of Bristol, UK) (Saleem, O'Hare et al. 2002) and in primary cultured

human renal glomerular endothelial cells (hGECs) (ScienCell Research Laboratories, Carlsbad,

CA) (Yuen, Stead et al. 2012, Batchu, Majumder et al. 2016). hGECs were cultured under

control conditions (5.6mM glucose) or with the addition of 19.4mM glucose (final concentration

25mM, high glucose, HG) or 19.4mM mannitol for 16h. To generate human podocyte

conditioned medium, differentiated human podocytes were incubated under control conditions

(5.6mM glucose, hpod_CM) or high (25mM) glucose conditions (hpod_HGCM) for 48h.

Neutralizing antibody experiments were performed by incubating hGECs for 16h in high glucose

or hpod_HGCM that had been pre-incubated with an anti-CCL2 neutralizing antibody (Thermo

Fisher Scientific, Rockford, IL) at a concentration of 20µg/ml (Shah, Hinkle et al. 2011) for 1h.

Recombinant angiopoietin-1, angiopoietin-2 or endothelin-1 were applied to hGECs for 16h at

the following concentrations: angiopoietin-1 100ng/ml (Satchell, Anderson et al. 2004) (R & D

Systems, Minneapolis, MN); angiopoietin-2 100ng/ml (R & D Systems) and endothelin-1 10nM

(Collino, Bussolati et al. 2008) (Tocris Bioscience, Bristol, UK). Recombinant human CCL2

(Cloud-Clone Corp., Katy, TX) was applied to hGECs at a concentration of 0.5ng/ml (Salcedo,

Ponce et al. 2000, Gibson, Greaves et al. 2015) for 16h. For CCR2 antagonism, hGECs were

incubated with RS504393 (IC50 <100nM (Mirzadegan, Diehl et al. 2000); Tocris Bioscience) at a

concentration of 10µM (Simonson and Ismail-Beigi 2011). For inhibition of p38 mitogen-

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activated protein kinase (MAPK), hGECs were incubated with SB203580 (IC50 0.6µM (Cuenda,

Rouse et al. 1995); Tocris Bioscience) at a concentration of 10µM (Clerk, Michael et al. 1998).

For inhibition of mitogen- and stress-activated protein kinase 1/2 (MSK1/2), hGECs were

incubated with SB-747651A (IC50 11nM (Naqvi, Macdonald et al. 2012); Tocris Bioscience) at a

concentration of 5µM (Naqvi, Macdonald et al. 2012).

4.2.2. Immunoblotting

Immunoblotting was performed with antibodies in the following concentrations: VCAM-1

1:1000 (Santa Cruz Biotechnology, Dallas, TX), -actin 1:10,000 (Sigma-Aldrich, Oakville,

Ontario, Canada), CCL2 1:1000 (Novus Biologicals, Littleton, CO), CCR2 1:1000 (Novus

Biologicals), ICAM-1 1:1000 (Cell Signaling Technology, Danvers, MA), E-selectin 1:1000

(Abcam, Cambridge, MA), P-selectin 1:1000 (Abcam), phospho-p38 MAPK (Thr180/Tyr182)

1:1000 (Cell Signaling Technology), total p38 MAPK 1:1000 (Cell Signaling Technology),

phospho-histone H3 serine 10 (phospho-histone H3Ser10) 1:1000 (Abcam), total histone H3

1:1000 (Cell Signaling Technology).

4.2.3. Animal Studies

In study one, male C57BL/6 mice (wildtype (WT); The Jackson Laboratory, Bar Harbor, ME)

and CCR2 knockout mice (CCR2-/-; The Jackson Laboratory) aged eight weeks were made

diabetic by administration of a daily intraperitoneal injection of streptozotocin (STZ) (55mg/kg)

in 0.1mol/L citrate buffer (pH 4.5) (or citrate buffer control) after a 4h fast for five consecutive

days. Mice were followed for 14 weeks from the first intraperitoneal injection of STZ (WT n=9;

CCR2-/-, n=6; STZ-WT, n=8; STZ-CCR2-/-, n=7). Blood glucose was determined using One

Touch UltraMini (LifeScan Canada Ltd., Burnaby, BC, Canada). Glomerular VCAM-1 was

determined in frozen kidney sections after immunostaining with a VCAM-1 antibody 1:50

dilution (BD Biosciences, San Jose, CA) and HRP-conjugated donkey anti-rat IgG (H&L) 1:100

dilution (Cedarlane, Burlington, ON, Canada). Glomerular VCAM-1 immunostaining was

quantified using ImageScope 11.1 software (Leica Microsystems, Concord, Ontario, Canada) in

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an average of 7 glomerular profiles per mouse kidney and is represented as fold change relative

to WT. In study two, diabetes was induced in male WT and endothelial nitric oxide synthase

knockout (eNOS-/-) mice (The Jackson Laboratory) aged eight weeks, by five daily

intraperitoneal injections of STZ (55mg/kg) (or citrate buffer) as described in Chapter 3. Mice

were followed for three weeks from the first injection of STZ (WT, n=12; STZ-WT, n=14;

eNOS-/-, n=11, STZ-eNOS-/-, n=9). Urine CCL2 excretion was determined by ELISA (R & D

Systems) after 24h metabolic caging. All experimental procedures adhered to the guidelines of

the Canadian Council on Animal Care and were approved by the St. Michael’s Hospital Animal

Care Committee.

4.2.4. Chromatin Immunoprecipitation

For chromatin immunoprecipitation (ChIP), hGECs were incubated in the presence or absence of

5µM SB-747651A for 1h. ChIP was performed using a Magna ChIP kit (EMD Millipore,

Etobicoke, Ontario, Canada) with an antibody against phospho-histone H3Ser10 (1:50 dilution;

Abcam) or an equal concentration of normal rabbit IgG (Santa Cruz Biotechnology), as

previously described in Chapter 2 (see section 2.2.10). Quantitative real-time PCR was

performed using primers specific for the human VCAM-1 promoter in hGECs or for the mouse

Vcam-1 promoter in the kidneys of male WT and CCR2-/- mice aged 22 weeks (n=4/group).

Primer sequences are provided in the appendix.

4.2.5. Quantitative reverse transcriptase PCR

RNA was isolated from snap frozen kidney tissue or cell lysates using TRIzol Reagent (Thermo

Fisher Scientific) and cDNA was reverse transcribed from 1µg RNA using SuperScript III

Reverse Transcriptase (Thermo Fisher Scientific). Primer sequences are provided in the

appendix and were obtained from Integrated DNA Technologies (Coralville, IA). For

determination of miR-93 levels, RNA isolation was performed using TRIzol Reagent, poly(A)

tailing was performed using Poly(A) Polymerase, Yeast (Applied Biological Materials, Inc.,

Richmond, BC) and cDNA was synthesized using a miRNA cDNA Synthesis Kit (Applied

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Biological Materials Inc.). Primers for has-miR-93 and U6 snRNA were from Applied

Biological Materials Inc. SYBR green based quantitative reverse transcriptase PCR (qRT-PCR)

was conducted using a ViiA7 Real-Time PCR System (Thermo Fisher Scientific) and data

analysis was performed using the Applied Biosystems Comparative CT method.

4.2.6. Human tissue study

Archived kidney tissue was examined from 8 individuals without diabetes (controls) and 9

individuals with diabetic kidney disease (Majumder, Thieme et al. 2018). Tissue had been

obtained at the time of nephrectomy for conventional renal carcinoma and was examined from

regions of the kidney unaffected by tumor. Immunohistochemistry was performed with an

antibody against phospho-histone H3Ser10 (1:200 dilution; Abcam) and the ratio of positively

immunostaining glomerular nuclei to total glomerular nuclei was calculated in 10 glomeruli per

kidney section. All histological analyses were performed by an investigator masked to the study

groups. The study was approved by the Nova Scotia Health Authority Research Ethics Board

and the Research Ethics Board of St. Michael’s Hospital, and was conducted in accordance with

the Declaration of Helsinki. A waiver of consent was provided by the Nova Scotia Health

Authority Research Ethics Board based on impracticability criteria.

4.2.7. In situ hybridization

In situ hybridization for VCAM-1 was performed with RNAscope (Advanced Cell Diagnostics,

Hayward, CA) according to the manufacturer’s instructions and using custom software as

previously described (Wang, Flanagan et al. 2012). Briefly, sections of formalin-fixed paraffin-

embedded mouse or human kidney tissue were baked for 1h at 60oC prior to deparaffinization,

dehydration and air drying. Slides were treated with a peroxidase blocker before boiling in target

retrieval solution for 15min. Protease plus was applied for 30min at 40oC and target probes were

hybridized for 2h at 40oC before signal amplification and washing. Hybridization signals were

detected using Fast Red and RNA staining was identified as red puncta on light microscopy. For

immunofluorescence microscopy, in situ hybridization was followed by immunostaining for

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nephrin, CD31 or phospho-histone H3Ser10 using the following antibodies: mouse nephrin 1:200

(R & D Systems), secondary antibody Alexa Fluor 647 donkey anti-goat 1:100 (Thermo Fisher

Scientific); mouse CD31 1:100 (Abcam), secondary antibody Alexa Fluor 488 donkey anti-rabbit

1:100 (Thermo Fisher Scientific); human nephrin 1:100 (Abcam), secondary antibody Alexa

Fluor 488 donkey anti-rabbit 1:100 (Thermo Fisher Scientific); human CD31 1:100 (Cell

Signaling Technology), secondary antibody Alexa Fluor 647 donkey anti-mouse 1:100 (Thermo

Fisher Scientific); human phospho-histone H3Ser10 1:200 (Abcam), secondary antibody Alexa

Fluor 488 donkey anti-rabbit 1:100 (Thermo Fisher Scientific). DAPI was from Cell Signaling

and was used at a concentration of 1:10,000. Slides were viewed using a Zeiss LSM700 confocal

microscope (Carl Zeiss Canada, Toronto, ON, Canada) with a x63 optic.

4.2.8. Statistical Analysis

Data are expressed as mean ± S.D.. Statistical significance was determined by 1-way ANOVA

followed by Fisher least significant difference post hoc test for more than two groups and 2-tailed

Student t test for two group comparisons. Statistical analyses were performed using GraphPad

Prism for Mac OS X (GraphPad Software Inc., San Diego, CA).

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4.3. RESULTS

4.3.1. Podocyte-derived CCL2 promotes VCAM-1 upregulation in human glomerular endothelial cells and knockout of the CCL2 receptor, CCR2 decreases glomerular VCAM-1 upregulation in diabetic mice

In our first series of experiments, we set out to determine which, if any, podocyte-derived

cytokines or chemokines promote the expression of VCAM-1 by glomerular endothelial cells

under high glucose conditions. By immunoblotting, we observed that VCAM-1 is expressed by

cultured human glomerular endothelial cells (hGECs) and that the magnitude of VCAM-1

expression is unaffected by exposure of hGECs to high (25mM) glucose or mannitol (osmotic

control) alone (Figure 4.1A). Likewise, when we exposed hGECs to culture medium that had

been conditioned by differentiated human podocytes (hpod_CM), we similarly observed no

change in hGEC VCAM-1 expression (Figures 4.2B). In contrast, VCAM-1 expression was

significantly increased when hGECs were incubated in the presence of culture medium that had

been conditioned by human podocytes that themselves had been exposed to high (25mM) glucose

(Figures 14B). Based on the 41 cytokines/chemokines we surveyed in Chapter 3 (Table 3.2), we

queried whether CCL2 was the causative factor responsible for VCAM-1 upregulation.

Confirming that CCL2 contributes to VCAM-1 upregulation, incubation of hGECs in

hpod_HGCM together with an anti-CCL2 neutralizing antibody resulted in a significant lowering

of VCAM-1 mRNA (Figure 4.1C) and protein (Figure 4.1D) levels.

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Figure 4.1: Anti-CCL2 neutralizing antibody diminishes VCAM-1 upregulation induced by

exposure of human glomerular endothelial cells (hGECs) to culture media conditioned by

high glucose-exposed podocytes. (A) Immunoblotting for VCAM-1 in hGECs incubated for 16h

under control conditions (5.6mM glucose) or in the presence of high glucose (25mM, HG) or

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mannitol (osmotic control) (n=3/condition). (B) Immunoblotting for VCAM-1 in hGECs

incubated for 16h under control or HG conditions or in the presence of culture medium

conditioned by human podocytes (hpod_CM) or culture medium conditioned by human

podocytes exposed to high glucose (25mM) for 48h (hpod_HGCM) (control, n=5; HG, n=5;

hpod_CM, n=6; hpod_HGCM, n=7). (C) qRT-PCR for VCAM-1 in hGECs incubated for 16h

with high glucose or hpod_HGCM that had been pre-incubated with an anti-CCL2 neutralizing

antibody (20µg/ml) for 1h (control, n=5; HG, n=6; hpod_HGCM, n=6; hpod_HGCM + anti-

CCL2 antibody (Ab), n=6). (D) Immunoblotting for VCAM-1 in hGECs under control

conditions or incubated for 16h with HG or hpod_HGCM preincubated with an anti-CCL2

neutralizing antibody (20µg/ml) for 1h (n=5/condition). AU = arbitrary units. Values are mean ±

S.D.. *p<0.05, **p<0.01, ****p<0.0001 by 1-way ANOVA followed by Fisher least significant

difference post hoc test.

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We recognized that podocytes secrete other factors that were not included in our

cytokine/chemokine multiplex array (e.g. angiopoietin-1, angiopoietin-2 and endothelin-1) and

that some of these factors have been implicated in podocyte-endothelial communication

(reviewed in Siddiqi and Advani 2013, Daehn, Casalena et al. 2014). However, when we

exposed hGECs to recombinant angiopoietin-1, angiopoietin-2 or endothelin-1 we observed that

each of these recombinant proteins actually downregulated VCAM-1 expression (Figure 4.2).

Figure 4.2: Immunoblotting hGECs for VCAM-1 under control conditions or following

incubation with recombinant angiopoietin-1 (Ang-1; 100ng/ml), angiopoietin-2 (Ang-2;

100ng/ml) or endothelin-1 10nM for 16h (ET-1; n=5/condition). AU = arbitrary units. Values

are mean ± S.D.. **p<0.01, ***p<0.001 by 1-way ANOVA followed by Fisher least significant

difference post hoc test.

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By immunoblotting we observed that hGECs express the principal receptor for CCL2, CCR2 (as

well as CCL2 itself) and that neither CCR2 nor CCL2 were altered in their expression by high

glucose in hGECs (Figures 4.3A and B).

Figure 4.3. Effect of high glucose on CCR2 and CCL2 expression in cultured hGECs. (A

and B) Immunoblotting hGECs for CCR2 (A) or CCL2 (B) under control conditions or following

incubation with HG or mannitol (osmotic control) for 48h (n=4/condition). AU = arbitrary units.

Values are mean ± S.D.

To determine whether CCR2 regulates glomerular VCAM-1 expression in vivo, we examined the

kidneys of non-diabetic and diabetic wildtype (WT) and CCR2-/- mice 14 weeks after the initial

induction of diabetes with streptozotocin (STZ). Whereas elevated blood glucose levels were

unaffected by CCR2 knockout (Figure 4.4A), glomerular VCAM-1 upregulation was

significantly attenuated in diabetic CCR2-/- mice (Figure 4.4B).

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Figure 4.4: Knockout of the CCL2 receptor, CCR2 decreases glomerular VCAM-1

upregulation in diabetic mice. (A and B) Wildtype (WT) and CCR2 knockout (CCR2-/-) mice

14 weeks after diabetes induction with STZ. (A) Blood glucose and (B) immunohistochemistry

for VCAM-1 and quantification of glomerular VCAM-1 immunostaining (WT, n=9; CCR2-/-,

n=6; STZ-WT, n=8; STZ-CCR2-/-, n=7). Original magnification x400. AU = arbitrary units.

Values are mean ± S.D.. **p<0.01, ***p<0.001, ****p<0.0001 by 1-way ANOVA followed by

Fisher least significant difference post hoc test.

By immunofluorescence microscopy we observed VCAM-1 to be expressed by CD31-positive

glomerular endothelial cells in the kidneys of both mice and humans (Figure 4.5). However,

glomerular endothelial cells were not the only cells to express the adhesion molecule, VCAM-1

transcript levels also being detectable in nephrin-positive podocytes (Figure 4.5).

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Figure 4.5: In situ hybridization for VCAM-1 (blue) and immunostaining for nephrin (red) and

CD31 (green) in mouse (A) and human (B) kidneys. Original images taken with a x63 optic.

The zoomed images are enlargements of the boxed areas. The arrows label VCAM-1 transcript

signals (blue puncta) in CD31-positive cells (thick arrows) and nephrin-positive cells (thin

arrows).

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4.3.2. CCL2/CCR2 signaling controls glomerular endothelial cell VCAM-1 expression through p38 MAPK and MSK1/2 dependent pathways

Having discovered that CCL2 regulates VCAM-1 expression in cultured hGECs and that

knockout of the CCL2 receptor, CCR2 diminishes glomerular VCAM-1 upregulation in diabetic

mice, we next set out to determine the pathways through which CCL2/CCR2 signaling control

VCAM-1. We observed that exposing hGECs to recombinant CCL2 caused a greater than

doubling in VCAM-1 protein levels and that this increase was negated by antagonism of CCR2

(Figure 4.6A). We recognized the importance of p38 MAPK as a downstream regulator of CCR2

signaling (Werle, Schmal et al. 2002) and we found that recombinant CCL2 increased hGEC p38

MAPK threonine 180/tyrosine 182 (Thr180/Tyr182) phosphorylation (Figure 4.6B), indicative of

p38 MAPK activation. As expected, pre-treatment of hGECs with the CCR2 antagonist

RS504393 negated the increase in p38 MAPK phosphorylation induced by CCL2 (Figure 4.6C).

Confirming that p38 MAPK activation is required for hGEC VCAM-1 expression, we observed

that the p38 MAPK inhibitor, SB203580 (Cuenda, Rouse et al. 1995) prevented hGEC VCAM-1

upregulation induced by CCL2 (Figure 4.6D). Next, we considered how p38 MAPK induces

VCAM-1 upregulation. Two downstream kinases that are activated by p38 MAPK are MSK1

and MSK2. We pre-incubated cells with the MSK1/2 inhibitor, SB-747651A (Naqvi, Macdonald

et al. 2012) and we observed that, like p38 MAPK inhibition, MSK1/2 inhibition also prevented

the upregulation in hGEC VCAM-1 induced by CCL2 (Figure 4.6E).

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Figure 4.6: CCL2 increases human glomerular endothelial cell (hGEC) VCAM-1 levels

through CCR2, p38 MAPK, MSK1/2 regulated mechanisms. (A) Immunoblotting for

VCAM-1 in hGECs incubated with or without the CCR2 antagonist RS504393 (10µM) for 1h

before exposure to recombinant CCL2 (0.5ng/ml) for 16h (control, n=5; RS504393, n=5; CCL2,

n=3; CCL2 + RS504393, n=3). (B) Immunoblotting for p38 MAPK threonine 180/tyrosine 182

(Thr180/Tyr182) phosphorylation (phospho-p38 MAPK) in hGECs incubated in the presence or

absence of CCL2 (0.5ng/ml) for 16h (n=7/condition). (C) Immunoblotting for phospho-p38

MAPK in hGECs incubated in the presence or absence of the CCR2 antagonist RS504393

(10µM) for 1h before exposure to recombinant CCL2 (0.5ng/ml) for 16h (n=4/condition). (D)

Immunoblotting for VCAM-1 in hGECs incubated with or without the p38 MAPK inhibitor

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SB203580 (10µM) for 1h before exposure to recombinant CCL2 (0.5ng/ml) for 16h (control,

n=7; SB203580, n=6; CCL2, n=7; CCL2 + SB203580, n=6). (E) Immunoblotting for VCAM-1

in hGECs incubated with or without the MSK1/2 inhibitor SB-747651A (5µM) for 1h before

exposure to recombinant CCL2 (0.5ng/ml) for 16h (control, n=5; SB-747651A, n=4; CCL2, n=5;

CCL2 + SB-747651A, n=5). AU = arbitrary units. Values are mean ± S.D.. *p<0.05, **p<0.01,

****p<0.0001 by 1-way ANOVA followed by Fisher least significant difference post hoc test (A,

C, D, E) and 2-tailed Student t test (B).

Supporting a relative specificity for the regulation in the expression of VCAM-1 by CCL2, we

found that the expression of other adhesion molecules (i.e. ICAM-1, E-selectin and P-selectin)

was unaffected by treatment of hGECs with recombinant CCL2 (Figure 4.7).

Figure 4.7: Immunoblotting for ICAM-1, E-selectin and P-selectin in hGECs under control

conditions or following incubation with recombinant CCL2 (0.5ng/ml) for 16h (ICAM-1 and E-

selectin, n=6/condition; P-selectin, n=4/condition). AU = arbitrary units. Values are mean ±

S.D..

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4.3.3. CCL2 induces histone H3 serine 10 phosphorylation, which is enriched at the VCAM-1 promoter in human glomerular endothelial cells and the Vcam-1 promoter in mouse kidneys

MSK1/2 is known to regulate gene expression by directly phosphorylating histone protein H3,

including phosphorylating histone H3 on serine residue 10, which is a mark of active gene

transcription. Accordingly, we next probed to see whether phospho-histone H3Ser10 levels are

altered by CCL2 in hGECs. Aligned with this hypothesis, CCL2 induced an increase in H3Ser10

phosphorylation levels in hGECs and this effect was negated by antagonism of CCR2 (Figure

4.8A) or inhibition of either p38 MAPK (Figure 4.8B) or MSK1/2 (Figure 4.8C). Furthermore,

using chromatin immunoprecipitation (ChIP), we observed enrichment of H3Ser10

phosphorylation at the promoter region of VCAM-1 in hGECs, whereas this enrichment was

diminished (although not negated) by MSK1/2 inhibition (Figure 4.8D). To determine whether

H3Ser10 phosphorylation is also enriched at the Vcam-1 promoter in vivo and whether this is

affected by upstream CCR2-regulated signaling, we performed ChIP experiments in the kidneys

of WT and CCR2-/- mice. Whereas H3Ser10 phosphorylation was enriched at the Vcam-1

promoter in WT mouse kidneys, enrichment was approximately two-thirds lower in the kidneys

of CCR2-/- mice (Figure 4.8E).

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Figure 4.8: CCL2 increases hGEC histone H3 serine 10 (H3Ser10) phosphorylation and

phospho-histone H3Ser10 is enriched at the VCAM-1 promoter in hGECs and mouse

kidneys. (A) Immunoblotting hGECs for histone H3Ser10 phosphorylation (phospho-histone

H3Ser10) incubated with or without the CCR2 antagonist RS504393 (10µM) for 1h before

exposure to recombinant CCL2 (0.5ng/ml) for 16h (n=5/condition). (B) Immunoblotting hGECs

for phospho-histone H3Ser10 incubated with or without the p38 MAPK inhibitor SB203580

(10µM) for 1h before exposure to recombinant CCL2 (0.5ng/ml) for 16h (n=5/condition). (C)

Immunoblotting hGECs for phospho-histone H3Ser10 incubated with or without the MSK1/2

inhibitor SB-747651A (5µM) for 1h before exposure to recombinant CCL2 (0.5ng/ml) for 16h

(control, n=6; SB-747651A, n=5; CCL2, n=6; CCL2 + SB=747651A, n=5). (D) Chromatin

immunoprecipitation (ChIP) for the presence of phospho-histone H3Ser10 at the VCAM-1

promoter in hGECs in the presence or absence of SB-747651A (5µM) for 1h (n=7/condition).

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(E) ChIP for phospho-histone H3Ser10 at the Vcam-1 promoter in wildtype (WT) and CCR2

knockout (CCR2-/-) mouse kidneys (n=4/group). ChIP data were determined by quantitative real-

time PCR. AU = arbitrary units. Values are mean ± S.D.. *p<0.05, **p<0.01, ***p<0.001,

****p<0.0001 by 1-way ANOVA followed by Fisher least significant difference post hoc test.

miR-93 has recently been implicated in regulating podocyte MSK mediated H3Ser10

phosphorylation in diabetic kidney disease (Badal, Wang et al. 2016). However, we saw no

change in miR-93 levels in hGECs following CCL2 treatment (Figure 4.9).

Figure 4.9: qRT-PCR for miR-93 in hGECs under control conditions or following incubation

with recombinant CCL2 (0.5ng/ml) for 16h (control, n=6; CCL2, n=5).

4.3.4. Histone H3 serine 10 phosphorylation is increased in murine and human diabetic kidney disease

Having identified a role for H3Ser10 phosphorylation in facilitating CCL2/CCR2 mediated

VCAM-1 upregulation, we set out to determine whether H3Ser10 phosphorylation levels are

altered in diabetic kidney disease. For these experiments, we chose to study both a mouse model

of diabetic kidney disease that is characterized by endothelial dysfunction and podocytopathy

(STZ-diabetic eNOS-/- mice) (Yuen, Stead et al. 2012) and the glomeruli of humans with diabetic

kidney disease (Majumder, Thieme et al. 2018). In comparison to non-diabetic mice, three weeks

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after the first intraperitoneal STZ injection, STZ-eNOS-/- mice exhibited renal enlargement and

heavy albuminuria (functional data presented in Table 3.1, Chapter 3) that were accompanied by

increased urinary excretion of CCL2 (Figure 4.10A,), increased renal H3Ser10 phosphorylation

(Figure 4.10B) and increased renal VCAM-1 mRNA (Figure 4.10C and D) and protein (Figure

4.10E) levels.

Figure 4.10: Urine CCL2 excretion and renal histone H3 serine 10 phosphorylation and

VCAM-1 expression are increased in streptozotocin (STZ)-diabetic endothelial nitric oxide

synthase (eNOS) knockout (eNOS-/-) mice. Wildtype (WT) and eNOS-/- mice three weeks after

the initiation of diabetes induction with STZ. (A) Urine CCL2 excretion (these data are re-

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presented from from Table 3.1 in Chapter 3 and they are shown again here to aid the

interpretability of the findings). (WT, n=6; STZ-WT, n=7; eNOS-/-, n=5; STZ-eNOS-/-, n=5). (B)

Renal histone H3Ser10 phosphorylation (phospho-histone H3Ser10) (WT, n=7; STZ-WT, n=7;

eNOS-/-, n=6; STZ-eNOS-/-, n=6). (C) Renal VCAM-1 mRNA levels (WT, n=10; STZ-WT,

n=11; eNOS-/-, n=9; STZ-eNOS-/-, n=9). (D) In situ hybridization for VCAM-1. Original

magnification x400. (E) Immunoblotting kidney homogenates for VCAM-1 (n=4/group). AU =

arbitrary units. Values are mean ± S.D.. *p<0.05, **p<0.01, by 1-way ANOVA followed by

Fisher least significant difference post hoc test.

To explore the relationship between H3Ser10 phosphorylation and VCAM-1 expression in

human diabetic kidney disease, we studied kidney tissue from individuals with

histopathologically confirmed diabetic glomerulosclerosis and we compared it to kidney tissue

from individuals without diabetes. The clinical characteristics of the individuals from whom

kidney tissue was obtained have been reported before (Majumder, Thieme et al. 2018). In brief,

we examined kidney tissue from 8 controls (5 male, 3 female; age 69±11 years, serum creatinine

85±11 µmol/L, eGFR 74±11 ml/min/1.73m2) and 9 individuals with diabetic kidney disease (5

male, 4 female; age 67±10 years, serum creatinine 107±39 µmol/L, eGFR 61±25

ml/min/1.73m2). Five of the individuals with diabetic kidney disease had stage 3 chronic kidney

disease or worse. We observed that in the kidney sections from humans with diabetic

glomerulosclerosis there was an approximate 3-fold increase in the proportion of glomerular

nuclei positively immunostaining for histone H3Ser10 phosphorylation (Figure 4.11A) including

H3Ser10 phosphorylation in VCAM-1 expressing glomerular cells (Fiure 4.11B).

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Figure 4.11: Histone H3 serine 10 phosphorylation is increased in human diabetic kidney

disease. (A) Immunohistochemistry for histone H3Ser10 phosphorylation (phospho-histone

H3Ser10) in kidney sections from controls (h_Control; n=8) and individuals with diabetic kidney

disease (h_Diabetes; n=9) and quantification of the proportion of phospho-histone H3Ser10

positive glomerular nuclei. Original magnification x400. (B) In situ hybridization for VCAM-1

(blue puncta) and immunostaining for phospho-histone H3Ser10 (green) in kidney sections from

a control and from an individual with diabetic glomerulosclerosis. Original images taken with a

x63 optic. The zoomed images are enlargements of the boxed areas. Values are mean ± S.D..

****p<0.0001 by 2-tailed Student t test.

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4.4. DISCUSSION

Every cell that lies within the kidney glomerulus is affected by diabetes and every cell that lies

within the kidney glomerulus is affected by the actions of its neighbours. In the present study,

we unearthed a signaling cascade that regulates expression of the adhesion molecule VCAM-1 by

glomerular endothelial cells. Specifically, ligand-binding by the receptor, CCR2 expressed by

glomerular endothelial cells induces VCAM-1 upregulation through a pathway that is regulated

by the MSK1/2-dependent phosphorylation of histone protein H3 on serine residue 10.

Heightened phospho-histone H3Ser10 levels in experimental and human diabetic kidney disease

and recent improvements in MSK1/2 inhibitor specificity (Naqvi, Macdonald et al. 2012) should

galvanize efforts to explore the modulation of histone phosphorylation as a means of attenuating

kidney disease in diabetes.

As a marker of endothelial activation, we focused on the regulation of expression of VCAM-1, an

immunoglobulin superfamily member that is expressed on the surface of endothelial cells in

response to pro-inflammatory cytokines. VCAM-1 promotes the firm adhesion and spreading of

leukocytes on the endothelium enabling their transmigration across the endothelial barrier.

Several studies have linked circulating VCAM-1 levels to diabetic kidney disease or mortality

risk (Stehouwer, Gall et al. 2002, Rubio-Guerra, Vargas-Robles et al. 2009, Liu, Yeoh et al.

2015) and likewise a number of reports have described an association between renal expression

or urinary excretion of the CCR2 ligand, CCL2 and the extent of diabetic kidney disease (Wada,

Furuichi et al. 2000, Tashiro, Koyanagi et al. 2002, Har, Scholey et al. 2013). However, even

though CCL2, CCR2 and VCAM-1 are often considered together in the same context of

inflammation, this is to our knowledge the first description that CCL2/CCR2 binding can directly

trigger glomerular endothelial VCAM-1 upregulation.

CCL2 (also called monocyte chemoattractant protein-1, MCP-1) is a member of the CC

chemokine family. Although CCL2 is best known for its function as the ligand for the receptor

CCR2 which is expressed on the surface of monocytes and macrophages, the actions of CCL2

and CCR2 are not limited to inflammatory cells and the relationship between CCL2 and CCR2 is

not monogamous. For instance, podocytes themselves are known to express both CCL2 and

CCR2 (Lee, Chung et al. 2009, Tarabra, Giunti et al. 2009) and we observed that hGECs also

express both ligand and receptor. In terms of ligand-receptor specificity, CCL2 also binds to

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CCR4 (Power, Meyer et al. 1995) and CCR2 may also be bound by CCL7, CCL8, CCL12

(mouse only), CCL13 and CCL16 (human only) (reviewed in Chu, Arumugam et al. 2014). In a

similar non-reductionist context, although we focused on VCAM-1 upregulation as a marker of

endothelial activation (reviewed in Liao 2013), it is noteworthy that other glomerular cells,

including both podocytes (Visweswaran, Gholizadeh et al. 2015) and mesangial cells (Ishibashi,

Matsui et al. 2014) are also capable of expressing VCAM-1. In the present study, we observed

that: i) VCAM-1 levels were increased in hGECs incubated in culture medium that had been

conditioned by podocytes exposed to high glucose; ii) that secretion of CCL2 by podocytes into

the culture medium was upregulated by high glucose; iii) that an anti-CCL2 neutralizing antibody

diminished hGEC VCAM-1 expression; and iv) that recombinant CCL2 induced hGEC VCAM-1

upregulation in a CCR2-dependent manner. Thus, whereas CCL2/CCR2 signaling to hGECs

could be paracrine in origin, autocrine in origin or both and whereas the relationship between

CCL2 and CCR2 is not exclusive, the evidence herein presented demonstrates that CCR2

signaling regulates glomerular VCAM-1 expression, including CCL2-induced VCAM-1

upregulation by human glomerular endothelial cells.

In unravelling the cascade by which signaling through CCR2 induces VCAM-1 upregulation in

hGECs, we discovered important roles for p38 MAPK and MSK1/2 and an associated enrichment

of the histone H3Ser10 phosphorylation mark at the VCAM-1 promoter. Chromatin

modifications, such as histone H3Ser10 phosphorylation rarely control gene activation or

repression in isolation. Rather an interplay exists whereby histone marks function alongside

other epigenetic regulators, alongside other histone marks and alongside canonical transcription

factors to coordinate gene expression in an integrated manner (reviewed in Yerra and Advani

2018). For instance, H3Ser10 phosphorylation (like histone acetylation) can facilitate gene

activation by affecting the electrostatic charge relationship between histone proteins and DNA,

associating with open chromatin during interphase and allowing access to DNA by the

transcriptional machinery. Separately, H3Ser10 phosphorylation may also promote gene

transcription by virtue of its proximity to other histone marks. For instance, the histone

acetyltransferase Gcn5 can acetylate lysine residue 14 (K14) on histone H3 more effectively

when H3Ser10 is phosphorylated, H3K14ac being found at actively transcribed promoters (Lo,

Trievel et al. 2000). A number of kinases have been reported to phosphorylate histone H3 on

serine residue 10, but the best characterized of these is MSK1/2 which is a substrate for p38

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MAPK (Thomson, Clayton et al. 1999), itself activated by CCR2 (Werle, Schmal et al. 2002).

The observation that MSK1/2 inhibition reduced but did not negate H3Ser10 phosphorylation at

the VCAM-1 promoter may suggest an additional role for other kinases (e.g. calcium/calmodulin-

dependent protein kinase II (CaMKII) (Smedlund, Tano et al. 2010, Awad, Kunhi et al. 2013).

Similarly, H3Ser10 is not the only substrate of MSK1/2, the transcription factor, cAMP response-

element binding protein (CREB) also being phosphorylated by the kinase (Arthur and Cohen

2000). Indeed, VCAM-1 expression induced by tumor necrosis factor- in endothelial cells has

been reported to involve p38 MAPK-mediated CREB phosphorylation (Ono, Ichiki et al. 2006).

Moreover, transcription factor binding at specific sites on the genome is itself dependent on

histone modifications and is both histone modification-specific and protein family-specific (Xin

and Rohs 2018). Thus, aligned with the current perspective of coordinated interplay between

epigenetic modifications and canonical transcription factors, CCR2-regulated VCAM-1

expression by the glomerular endothelium likely involves both effects that are mediated through

histone protein post-translational modifications and effects that are regulated by associated

transcription factor responses. Nonetheless, a role for H3Ser10 phosphorylation in regulating

endothelial activation in diabetes is supported by increased H3Ser10 phosphorylation at the

VCAM-1 promoter and a reduction with MSK1/2 inhibition that coincided with a decrease in

VCAM-1 protein levels in hGECs. H3Ser10 phosphorylation could regulate VCAM-1

expression by directly affecting CCR2 mediated signaling or it could have parallel effects,

decreased H3Ser10 phosphorylation functioning as an epigenetic brake to canonical transcription

factor mediated gene transcription (Figure 4.12).

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Figure 4.12: Schematic illustration of the role that histone H3 serine 10 (H3Ser10)

phosphorylation plays in regulating glomerular endothelial VCAM-1 expression and

endothelial activation in diabetes. High glucose causes increased secretion of the chemokine,

CCL2 by podocytes. CCL2 may function in a paracrine fashion (e.g. arising from podocytes) or

autocrine fashion (arising from the glomerular endothelium) and binds to its cognate receptor,

CCR2 on glomerular endothelial cells. CCR2 can induce signaling that leads to canonical

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transcription factor effects and it can induce signaling that results in epigenetic effects, each of

which may promote VCAM-1 expression. CCR2 signaling can induce epigenetic effects through

a pathway that involves the sequential activation of p38 MAPK, the nuclear kinases mitogen- and

stress-activated protein kinases 1/2 (MSK1/2) and histone H3Ser10 phosphorylation.

Antagonizing CCR2 or inhibiting p38 MAPK or MSK1/2 (numbered circles) limits both

H3Ser10 phosphorylation and VCAM-1 expression by glomerular endothelial cells. H3Ser10

may also be phosphorylated by other kinases and MSK1/2 can also phosphorylate other

transcription factors.

Consistent with its contributory role to the development of diabetic kidney disease, we observed

increased levels of H3Ser10 phosphorylation both in the kidneys of STZ-eNOS-/- mice (a model

considered to more closely mimic human disease (Fu, Wei et al. 2018) and in the glomeruli of

humans with diabetic kidney disease. We studied STZ-eNOS-/- mice soon after the induction of

diabetes because we have previously found that the heavy albuminuria that these mice develops

coincides with the onset of hyperglycemia (Yuen, Stead et al. 2012). Even at this early

timepoint, we observed increased urine CCL2 excretion in STZ-eNOS-/- mice that coincided with

increases in both renal H3Ser10 phosphorylation and VCAM-1 expression. It should be noted

however that, distinct from its role in transcriptional activation, H3Ser10 phosphorylation also

marks highly condensed chromatin during mitosis. Thus, it is unclear whether the increased

kidney cell H3Ser10 phosphorylation in diabetes is indicative of mitotic cell division, a

generalized shift in the epigenomic landscape that supports transcriptional activation, or a

combination of the two. Interestingly though, the findings are aligned with a recent study that

reported increased global H3Ser10 phosphorylation levels in podocytes exposed to high glucose

and in glomerular cells of Type 2 diabetic db/db mice (Badal, Wang et al. 2016).

As already highlighted, our study has limitations. Notably paracrine podocyte-derived CCL2

may not be the only activator of hGEC CCR2 signaling; H3Ser10 phosphorylation by MSK1/2

may not be the sole means through which CCR2 signaling regulates VCAM-1 expression; and

increases in kidney cell H3Ser10 phosphorylation in experimental and human diabetic kidney

disease will not solely reflect the changes occurring at the VCAM-1 promoter. Looking back at

our initial experiments, it is also noteworthy that despite containing appreciable levels of CCL2,

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media of podocytes grown under normal glucose conditions did not induce hGEC VCAM-1

upregulation. This suggests the presence of other non-quantified factor(s) in the culture media.

For instance, we observed a reduction in VCAM-1 expression by exposure of hGECs to

recombinant angiopoietin-1, which is constitutively expressed by podocytes and which is

downregulated in diabetes (reviewed in Gnudi 2016). Thus, overall effects of podocyte

conditioned medium likely reflect the overall balance of its constituents, which are not limited to

proteins but may also involve bioactive lipids, nucleic acids and microparticles (reviewed in

Siddiqi and Advani 2013).

Despite their limitations, the experiments herein reported do provide important new insights.

Firstly, they demonstrate how pro-inflammatory cytokines/chemokines can have direct effects on

the glomerular endothelium. This could have implications for the interpretation of the

mechanism of action of anti-inflammatory therapies recently trialed in the treatment of diabetic

kidney disease (de Zeeuw, Bekker et al. 2015, Tuttle, Brosius et al. 2018). Secondly, they

highlight the emerging role for H3Ser10 phosphorylation and its regulatory kinases, MSK1/2 in

facilitating the activation of genes important to the development of kidney disease in diabetes,

specifically here the expression of VCAM-1 by glomerular endothelial cells. Moreover, the

elucidation of these actions in cultured cells of human origin and the observation of heightened

glomerular cell H3Ser10 phosphorylation in human diabetic kidney disease lend weight to the

significance of the findings in an era when the value of rodent models is under scrutiny.

In summary, ligand-binding by CCR2 initiates an intracellular signalling cascade in glomerular

endothelial cells that involves the p38 MAPK, MSK1/2 regulated phosphorylation of serine

residue 10 on histone H3 facilitating the expression of the inducible pro-inflammatory adhesion

molecule VCAM-1, a marker of endothelial activation. Histone protein phosphorylation should

be placed alongside previously better studied histone modifications when considering potentially

druggable candidates suitable for targeted intervention in diabetic kidney disease.

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CHAPTER 5: SUMMARY AND LIMITATIONS

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5.1. Summary of results

CKD is a serious complication of diabetes that is expected to increase in the prevalence over the

next decade (reviewed in Webster, Nagler et al. 2017). Current treatments include intensive

glycemic control, blood pressure control, blockade of the RAAS, and in some patients inhibition

of SGLT2. Although these therapeutic interventions have shown significant benefits, progression

to ESKD still occurs in many patients, creating a substantial burden on patients, their families,

and health care systems. The work described in this doctoral dissertation seeks to advance our

understanding of glomerular cell (patho)biology at the fundamental level as a means of paving

the way for the development of new treatments for CKD.

In the first study described in Chapter 2, we described the homeostatic effects of JAK2 in

glomerular podocytes under normal conditions. Deletion of JAK2 from podocytes in mice

contributed to the development of albuminuria, which was accompanied by lysosomal

dysfunction and impaired autophagy completion. Likewise, JAK2 knockdown in cultured mouse

podocytes resulted in downregulation of lysosomal genes including the aspartic proteinase

cathepsin D, and it impaired autophagy completion. Having found that JAK2 knockdown caused

downregulation of several lysosomal genes at the transcriptional level, we examined whether this

was mediated by dysregulation of the master regulator of lysosomal biogenesis and autophagy,

TFEB. We found that JAK2 knockdown in cultured mouse podocytes caused a significant

reduction in TFEB promoter activity, mRNA levels, and protein levels, suggesting that JAK2 acts

upstream of TFEB. We went on to discover that the transcription factor STAT1 that acts

downstream of JAK2, was enriched at the TFEB promoter, and this enrichment was diminished

by JAK2 knockdown. In a rescue experiment, we examined whether TFEB overexpression could

restore podocyte dysfunction in a cell culture system. TFEB overexpression in cultured mouse

podocytes improved autophagic flux, increased the expression and the activity of cathepsin D,

and reduced albumin permeability induced by JAK2 knockdown. Taken together, these data

demonstrate that JAK2 plays an important role in podocyte autophagy through regulation of the

transcription factor, TFEB. The study also hints at the possibility of enhancing TFEB activity as a

potential therapeutic strategy to maintain podocyte health.

The second study presented in Chapter 3 unraveled the effects of systemic JAK2 inhibition and

of JAK2 deletion from podocytes on kidney function in the disease setting. We selected diabetes

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as the disease setting as it is the leading cause of CKD. Systemic inhibition of JAK2 with the

pharmacological inhibitor AZD1480 reduced albuminuria in a mouse model of DKD. Although

JAK2 deletion from podocytes under normal conditions led to the development of albuminuria,

JAK2 absence in podocytes neither increased nor decreased albuminuria in diabetic mice.

Recognizing that the JAK/STAT pathway is implicated in inflammation, we queried whether

JAK2 inhibition has an anti-inflammatory effect in diabetic mice. By assessing urine excretion of

the proinflammatory chemokine CCL2, we found that JAK2 inhibition by AZD1480 treatment

resulted in a significant decrease in urine CCL2 excretion in diabetic mice. Because JAK2 acts

upstream of CCL2 and because podocytes are the major source of glomerular CCL2

(Prodjosudjadi, Gerritsma et al. 1995, Chow, Ozols et al. 2004, Hartner, Veelken et al. 2005), we

examined whether deletion of JAK2 from podocytes would decrease urine CCL2 excretion. We

discovered that podocyte-specific JAK2 knockout attenuated urine CCL2 excretion in diabetic

mice, suggesting that podocyte JAK2 play different roles in the context of normoglycemia and of

diabetes. By performing an array for 41 inflammatory cytokines and chemokines, we identified

that CCL2 was significantly enriched in the culture media derived from podocytes under high

glucose conditions. Without undermining the homeostatic action of podocyte JAK2 under normal

conditions, these data highlight the inflammatory effect of podocyte JAK2 in diabetes, and they

demonstrate that modulation of JAK2 activity may have a protective role in the kidney in

diabetes. The findings emphasize the importance of the metabolic milieu in influencing the

beneficial and the detrimental effects of JAK2 in podocytes.

Having found that CCL2 is enriched in the culture media derived from podocytes in the presence

of high glucose, in the third study described in Chapter 4, we built on these observations and

unraveled the effects of CCL2 signaling on glomerular endothelial cells. By exploring the actions

of podocyte-secreted CCL2, we discovered a role for CCL2 in glomerular endothelial activation,

characterized by VCAM-1 upregulation. Incubation of cultured human glomerular endothelial

cells with culture media derived from podocytes exposed to high glucose conditions caused a

marked increase in VCAM-1 mRNA and protein levels, which was prevented by blocking CCL2

signaling. Moreover, recombinant CCL2 alone was sufficient to upregulate VCAM-1 in cultured

human glomerular endothelial cells and this effect was negated with an antagonist of the CCL2

receptor, CCR2. Similarly, CCR2 knockout attenuated glomerular VCAM-1 upregulation in

STZ-diabetic mice. By performing a series of pharmacological inhibition studies, we discovered

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that CCL2 signals through its cognate receptor CCR2 to induce an intracellular signaling cascade

that involves p38 MAPK, MSK1/2, and histone H3Ser10 phosphorylation resulting in VCAM-1

upregulation in glomerular endothelial cells. In STZ-diabetic eNOS-/- mice, we observed a

significant upregulation in renal VCAM-1 mRNA levels and protein levels and this upregulation

was associated with an increase in phospho-histone H3Ser10 protein levels, and urine CCL2

excretion. Likewise, in humans with DKD, glomerular phospho-histone H3Ser10 levels were

increased and this increase was associated with an increase in glomerular VCAM-1 transcript

levels. Collectively, the data from this study identified a new molecular mechanism that controls

glomerular endothelial activation in diabetes characterized by VCAM-1 expression. The findings

also point to the importance of histone phosphorylation in facilitating gene expression in DKD.

Figure 5.1. Summary of key findings. (Created by BioRender).

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5.2. Limitations

Although each of the studies described in this dissertation provides new mechanistic insights into

glomerular cell (patho)biology in health and in diabetes, there are several limitations to the

findings that warrant discussion.

The study described in Chapter 2 reported a fundamental role of JAK2 in autophagy completion

and lysosomal function in podocytes through regulation of TFEB expression. We showed that

dysregulation of TFEB induced by JAK2 knockdown caused downregulation of multiple genes

essential for lysosomal function. However, these genes were compiled from the literature

according to their identified roles in the lysosome and their direct interaction with TFEB. A more

comprehensive approach could be achieved by performing transcriptome analysis using a

powerful tool of transcriptome profiling such as RNA sequencing technology to identify

dysregulated gene expression profiles implicated in the autophagy-lysosomal pathway with JAK2

knockdown. Moreover, we showed that six out of the 13 TFEB targets were downregulated with

JAK2 knockdown i.e. beclin 1, cathepsin D, cystinosin, mucolipin-1, ras-related GTP binding C,

and serine/threonine kinase 4. We speculated that the expression of these genes was not

uniformly reduced because TFEB expression, although significantly reduced with JAK2

knockdown, was not abolished. However, it is still not clear why these six transcripts were

exclusively downregulated out of all the TFEB targets we studied. Moreover, although each of

the downregulated TFEB targets plays an important role in the autophagy-lysosomal pathway and

five of the six TFEB targets were also downregulated in cultured primary podocytes isolated

from JAK2podKO mice, we only focused on cathepsin D in our rescue experiments. For instance,

serine/threonine kinase 4 (STK4) regulates autophagy by phosphorylation of the autophagic

membrane-specific protein LC3 at threonine 50, and loss of phosphorylation at this site in STK4

deficient cells has been reported to block autophagy by impairing fusion of autophagosomes with

lysosomes (Wilkinson and Hansen 2015, Wilkinson, Jariwala et al. 2015). Accordingly, whereas

JAK2 knockdown in cultured mouse podocytes did not alter the expression of most of the

surveyed genes involved in fusion of autophagosomes with lysosomes, reduction of STK4

expression with JAK2 knockdown may suggest otherwise. It remains possible that the reduction

in STK4 expression caused a defect in fusion of autophagosomes with lysosomes and this may

partly explain the impaired autophagy completion in JAK2 deficient podocytes and the improved

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autophagic flux observed with TFEB overexpression. Furthermore, although cathepsin D was

previously shown to play a central role in autophagy and podocyte homeostasis (Yamamoto-

Nonaka, Koike et al. 2016), the effects of JAK2 knockdown and TFEB overexpression on

cathepsin D expression and activity in cultured podocytes were marginal albeit statistically

significant (Figure 2.11B and C). Nonetheless, the observation that cathepsin D mRNA levels

were also significantly reduced in primary podocytes isolated from JAK2podKO mice lends further

weight to the supposition that JAK2 regulates cathepsin D expression. Of note, whereas our

findings demonstrated that regulation of JAK2 by TFEB is STAT1-dependant, we did not

demonstrate a direct interaction between the TFEB promoter region and STAT1. To support our

findings, a mutated version for STAT1 predicted binding sites could have been included in our

ChIP experiments.

Dysregulation of the autophagy-lysosomal pathway has been shown to contribute to the

development of albuminuria in a range of kidney diseases (reviewed in Hartleben, Wanner et al.

2014). In our study, JAK2podKO mice developed albuminuria with dysregulated autophagy

completion and lysosomal dysfunction. Despite the development of albuminuria in JAK2podKO

mice at 10 weeks of age, we observed neither overt morphological defects in the glomeruli of

these mice (Figure 2.5) nor overt changes in podocyte morphology other than accumulation of

autophagosomes and lysosomes (Figure 2.6). Several studies have demonstrated that albuminuria

can occur without apparent morphological changes in podocytes and/or without classical

pathologic glomerular lesions (Branten, Van Den Born et al. 2001, Good, O'Brien et al. 2004, van

den Bergh Weerman, Assmann et al. 2004). Moreover, the unremarkable glomerular morphology

by light microscopy was observed in JAK2podKO mice at 10 weeks of age, which may explain the

benign glomerular phenotype. However, as explained in the Discussion (section 2.4), we

explicitly elected to study these mice at a young age (10 weeks) to demonstrate that the

impairment in autophagy completion was a consequence of podocyte-specific JAK2 knockout

rather than a response to generalized cellular injury. Because the mild increase in albuminuria

observed in JAK2podKO mice at 10 weeks of age progressed to almost 3-fold at 6 months of age,

and because the implication of podocyte autophagy in glomerular deterioration has been shown to

be age-dependent (Hartleben, Gödel et al. 2010), these mice could be followed up for longer (e.g.

up to two years) to further examine the impact of JAK2 deletion from podocytes on glomerular

structure and function. More importantly, TFEB overexpression was shown to rescue impaired

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autophagy completion and lysosomal dysfunction, and restore albumin permselectivity in

cultured mouse podocytes with JAK2 knockdown. While we tried to mimic podocyte barrier

function in a cell culture system, these findings do not necessarily reflect what may occur in vivo.

A key question that therefore remains to be explored is whether TFEB overexpression would

restore albumin permeability in JAK2podKO mice. In addition, it is not clear how TFEB

overexpression improved podocyte function. To identify the protective mechanism of action of

TFEB in podocytes, key proteins essential for podocyte structure and function (e.g. nephrin)

could be assessed with TFEB overexpression in JAK2 deficient podocytes. Furthermore, while

our findings hinted at the possibility of modulation of TFEB as a therapeutic target, our studies

focused only on TFEB expression and the impact of JAK2 knockdown on TFEB activity remains

to be investigated. Lastly, because JAK2 inhibition has been evaluated as a treatment for DKD,

questions thus remain about the long-term effects of JAK2 inhibitors on the autophagy-lysosomal

pathway in podocytes and other resident cells, and whether TFEB modulation would be an

effective therapeutic strategy to maintain podocyte health and glomerular function.

The studies presented in Chapter 3 focused on the effect of systemic JAK2 inhibition and of

JAK2 deletion from podocytes in experimental models of DKD. Our data showed that JAK2

inhibition by AZD1480 reduced albuminuria, urine CCL2 excretion, and mesangial expansion in

STZ-diabetic eNOS-/- mice. We demonstrated that urine CCL2 excretion was also reduced in

STZ-diabetic JAK2podKO mice whereas albuminuria was unaffected. Our array data of 41

cytokines and chemokines further revealed that CCL2 was significantly increased in the culture

media of podocytes exposed to high glucose. Although these findings support the notion that

lowering JAK2 activity plays a protective role in DKD and that podocyte JAK2 is implicated in

renal inflammation, they are rather descriptive. Firstly, we focused only on urine CCL2 excretion

as a pro-inflammatory biomarker and the effects of both JAK2 inhibition and podocyte-specific

JAK2 deletion on other inflammatory markers were not explored. Second, because CCL2 is a key

mediator in macrophage infiltration and having observed a marked diminution in urine CCL2

excretion, it would be reasonable to perform histological examination of inflammatory cell

infiltration in the kidneys of our experimental models of DKD. This could be achieved by

immunohistological staining of kidney sections obtained from these mice with a macrophage

marker (e.g. F4/80) followed by a quantitative image analysis of macrophage-positive cells.

Another limitation worth emphasizing is that treatment of STZ-diabetic eNOS-/- mice with

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AZD1480 was initiated on the first day of inducing diabetes prior to the onset of albuminuria.

Recognizing that previous studies of STZ-diabetic eNOS-/- mice have reported that these mice

develop massive albuminuria soon after inducing diabetes (Kanetsuna, Takahashi et al. 2007,

Yuen, Stead et al. 2012), we elected to start the treatment with the beginning of the first STZ

injection. Although we demonstrated that JAK2 inhibition with AZD1480 reduced albuminuria

and urine CCL2 excretion in STZ-diabetic eNOS-/- mice, these observations were based on a

short-term study and they do not demonstrate whether JAK2 inhibition could reverse kidney

damage in DKD. To assess the reversibility of kidney damage with JAK2 inhibition, STZ-

diabetic eNOS-/- mice could be followed for a longer period of time and AZD1480 treatment

could be initiated after the establishment of DKD. While STZ-diabetic mice have been

extensively used as experimental models in DKD research, the potential nephrotoxic effects of

STZ in our mouse models cannot be excluded (reviewed in Rerup 1970, reviewed in Weiss

1982). To exclude the off target effects of STZ, our in vivo experiments could be recapitulated in

other experimental models of diabetes such as Ins2Akita, a mouse model of type 1 diabetes caused

by a spontaneous mutation in the insulin 2 (Ins2) gene (Yoshioka, Kayo et al. 1997).

The neutral effect of podocyte-specific JAK2 deletion under diabetic conditions on albuminuria

with a decrease in urine CCL2 excretion points to the functional plurality of podocyte JAK2. In

other words, the deleterious effects of podocyte JAK2 absence may have been counterbalanced

by attenuation in inflammatory processes in diabetic JAK2podKO mice, collectively resulting in

neither a decrease nor an increase in albuminuria. Nonetheless, urine CCL2 excretion was

consistently reduced with JAK2 inhibition and podocyte-specific JAK2 deletion under diabetic

conditions, supporting the assertion that albuminuria may not be the best surrogate marker of

kidney injury in diabetes. Whereas we demonstrated that podocyte-specific JAK2 deletion

attenuated urine CCL2 excretion in vivo, how podocyte JAK2 dysregulated CCL2 and whether

podocyte JAK2 is implicated in dysregulation of other inflammatory factors under high glucose

conditions were not investigated. To further explore the role of podocyte JAK2 in inflammatory

processes, the multiplex array of 41 cytokines and chemokines could be performed after

knocking down JAK2 in cultured human podocytes exposed to either high glucose or control

conditions.

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The lack of florid phenotype in diabetic JAK2podKO mice and the insights we gained from our

findings in Chapter 3 prompted us to pursue an additional line of investigation in which we

explored the effect of podocyte-secreted CCL2 on glomerular endothelial cells in diabetes

(Chapter 4). Beginning by exploring the role of podocyte-secreted CCL2 in abnormal podocyte-

endothelial crosstalk under high glucose conditions, we identified a critical role for CCL2/CCR2

signaling in glomerular endothelial activation characterized by VCAM-1 upregulation. Through

our work described in Chapter 4, we discovered that CCL2/CCR2 signaling initiates an

intracellular signaling cascade that involves p38-MAPK and MSK1/2, which results in an

increase in H3Ser10 phosphorylation levels and VCAM-1 upregulation in glomerular endothelial

cells. Although our findings focused on H3Ser10 phosphorylation, histone protein

phosphorylation can occur on a number of different serine, threonine, and tyrosine residues

(reviewed in Rossetto, Avvakumov et al. 2012). However, the best-studied modification is

phosphorylation of histone H3 on serine residue 10, which facilitates gene transcriptional

activation and marks highly condensed chromatin during mitosis, indicative of its dual

functionality (reviewed in Sawicka and Seiser 2012). Therefore, while we showed that increased

levels of H3Ser10 phosphorylation were associated with an increase in glomerular VCAM-1

transcript levels in diabetic mice and humans with DKD, H3Ser10 phosphorylation levels could

also reflect an increase in glomerular cell proliferation. Moreover, we showed that CCL2

signaling through CCR2 increased the levels of H3Ser10 phosphorylation in glomerular

endothelial cells through its downstream mediators p38-MAPK and MSK1/2. However, this may

not be the sole means by which H3Ser10 phosphorylation, induced by CCL2/CCR2 signaling,

regulates glomerular endothelial activation, and other histone marks may be implicated in

transcriptional VCAM-1 upregulation. For instance, phosphorylation of histone H3 has been

shown to facilitate acetylation of histone H3 at lysine 14 (H3K14), which has been shown to

promote oxidative stress in diabetes (Bock, Shahzad et al. 2013). Moreover, there remains the

question of which regions of the genome are enriched by phospho-histone H3Ser10 in response

to CCL2/CCR2 binding in glomerular endothelial cells as the VCAM-1 promoter will not be the

sole region affected. This could be probed for by ChIP-sequencing for H3Ser10 phosphorylation

enriched genomic regions.

Although CCR2 knockout attenuated glomerular VCAM-1 upregulation in diabetic mice, the

renoprotective effect of CCR2 deletion in diabetic mice may extend beyond glomerular

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endothelial cells and VCAM-1 upregulation. For instance, impaired monocyte migration is one of

the first reported characteristic features of CCR2 knockout mice (Boring, Gosling et al. 1997).

However, because blockade of CCR2 either pharmacologically or genetically has been previously

reported to reduce leukocyte infiltration in the kidney of experimental models of diabetes

(Kanamori, Matsubara et al. 2007, Seok, Lee et al. 2013) and recognizing that VCAM-1 is also

implicated in leukocyte recruitment (reviewed in Liao 2013), we chose VCAM-1 upregulation as

the end-point of our study. Whereas our study focused on the delineation of a novel epigenetic

signalling pathway whereby ligand-binding by CCR2 induces VCAM-1 expression by

glomerular endothelial cells, it is worth noting that VCAM-1 has previously been reported to be

expressed in mesangial cells (Ishibashi, Matsui et al. 2014), tubule epithelial cells (Seron,

Cameron et al. 1991), and we reported its expression in podocytes in mice and humans (Figure

4.5). Therefore, it is unclear whether CCL2/CCR2 signalling has similar effects on other VCAM-

1-expressing cells in the kidney. Furthermore, in cultured glomerular endothelial cells, we

showed that recombinant CCL2 does not affect other adhesion molecules such as P-selectin, E-

selectin and ICAM-1 (Figure 4.7). However, these findings were based on in vitro studies and

upregulation of these adhesion molecules has been reported in DKD (Hirata, Shikata et al. 1998,

Gu, Ma et al. 2013). Thus, the effect of CCR2 knockout on other adhesion molecules could have

been examined in diabetic mice.

One limitation of our in vivo studies is the lack of GFR measurement. GFR is a key metric of

kidney function and important readout of translational drug discovery in experimental models of

kidney diseases. In our animal studies, GFR measurement was not performed for several reasons.

First, GFR is commonly measured in humans based on endogenous tracers commonly creatinine,

a byproduct of muscle metabolism produced and filtered by the kidney glomerulus at a relatively

constant rate (reviewed in Breyer and Qi, 2010). However, creatinine-based measurements of

GFR is not recommended in mice due to increased urinary secretion of creatinine attributable to

the renal tubule (Eisner, Faulhaber-Walter et al., 2010) and high concentrations of non-creatinine

chromagens in plasma and urine, resulting in an overestimation of GFR with commercially

available creatinine assays (Meyer, Meyer et al., 1985; Dunn, Qi, 2004; Palm and Lunblad,

2005). Moreover, in comparison to humans, the handling of creatinine by the mouse kidney is

poorly characterized (reviewed in Breyer and Qi, 2010). Therefore, in mouse models, the gold

standard for GFR measurement is based on clearance of exogenous tracers such as inulin, a

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fructose polysaccharide that is freely filtered by the glomerulus and neither reabsorbed nor

secreted by the renal tubule (reviewed in Breyer and Qi, 2010). Whereas inulin-based GFR

measurement in our mouse models may provide more accurate assessment of kidney function,

based on previous experience in our lab, this method is technically demanding and performed as

an end study procedure requiring additional animals. Because our in vivo studies were designed

to explore the molecular and cellular causes of kidney dysfunction in diabetes, to adhere to the

Russell and Burch principle of reduction, refinement, and replacement, we chose not to measure

GFR. Accordingly, in the absence of experimental evidence, no inference on effects on kidney

function in mice or humans should be made.

Another fundamental limitation is the lack of female mice in our animal studies. In 1993, the

National Institutes of Health (NIH) Revitalization Act mandated to account for the role of sex-

specific factors in health and disease, which has led to a requirement to include females in

clinical studies (reviewed in Clayton and Collins 2014). However, preclinical studies that involve

both male and female animals remain low in number (reviewed in Zucker and Beery 2010),

compromising the translational success of these studies to the female population. Between 1997

and 2000, eight out of ten withdrawn drugs from the market by the US Food and Drug

Administration due to severe adverse events had higher health risks for women than men

(available at https://www.gao.gov/new.items/d01286r.pdf), and this was mainly attributed to

male biases in basic, preclinical, and clinical research. Although several challenges may have

hindered the integration of both sexes in preclinical studies including hormonal variability

(reviewed in Wald and Wu 2010), cost and practicality (reviewed in Fields 2014), recent efforts

by funding organizations and scientific journals have been made to ensure reporting and

accounting for sex as a critical biological variable in biomedical research to improve

experimental outcomes and the likelihood of translating these studies in clinical practice

(reviewed in Lee 2018). A focus of our studies was on diabetes and one of the features of female

mice is that they are relatively resistant to the development of diabetes by chemical induction or

genetic means (Maclaren, Neufeld et al. 1980, Haseyama, Fujita et al. 2002). Thus, as with most

preclinical studies of diabetic kidney disease, we restricted ourselves to the study of male mice.

Accordingly, caution should be taken in extrapolating our in vivo findings to the female

population.

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Finally, as the reader may have noted, the statistical parameters and the display of the datasets in

Chapter 2 and 3 (bar graphs with SEM) differ from Chapter 4 (scatter graphs with SD). This

difference reflects an evolution of journal data reporting requirements during the course of my

doctoral studies. I have elected to present the data in this way to recapitulate the manner in which

they were published.

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CHAPTER 6: GENERAL DISCUSSION AND FUTURE

DIRECTIONS

137

6.1. TFEB and the autophagy-lysosomal pathway as potential therapeutic

targets in kidney disease

Autophagy has gained attention over the past few years as a crucial cellular process necessary for

maintaining cellular homeostasis. This self-repair mechanism is particularly important for

terminally differentiated cells and, being terminally differentiated, podocytes have high basal

levels of autophagy (Sato, Kitamura et al. 2006, Hartleben, Gödel et al. 2010). Under

physiological conditions, podocyte-specific knockout of the autophagy gene ATG5 has been

shown to sensitize aged mice to glomerular disease and result in podocyte loss, proteinuria, and

glomerulosclerosis (Hartleben, Gödel et al. 2010). Lysosomes, being the final destination for

degraded proteins and damaged organelles in the autophagy process, also play crucial roles in

podocyte homeostasis.

Lysosomal dysfunction has been shown to cause a defect in autophagy completion, and

contribute to the development of proteinuria and severe glomerulosclerosis (Oshima, Kinouchi et

al. 2011, Chen, Chen et al. 2013, Yamamoto-Nonaka, Koike et al. 2016). Deletion of the

lysosomal enzyme cathepsin D from podocytes in mice contributed to impaired autophagy

completion, and the development of proteinuria in mice at 5 months of age that progressed to

ESKD by 20-22 months of age (Yamamoto-Nonaka, Koike et al. 2016). Dysregulated autophagy

has been implicated in the pathogenesis of DKD in several cell types in the kidney including

mesangial cells (Fiorentino, Cavalera et al. 2013, Lu, Fan et al. 2015), glomerular endothelial

cells (Lenoir, Jasiek et al. 2015), proximal tubule epithelial cells (Liu, Shen et al. 2015,

Brijmohan, Batchu et al. 2018), and podocytes (Fang, Zhou et al. 2013, Wang, Liu et al. 2014,

Tagawa, Yasuda et al. 2015). In line with our findings from Chapter 2, in each of these studies,

autophagy was reported as a protective process and its dysregulation in these cells contributed to

kidney dysfunction. However, out of all these cells, podocytes are the only cell type that is

postmitotic in nature. Podocytes lack the capacity to regenerate, and thus, they rely on autophagy

to maintain their health. Because podocyte loss contributes to the development and progression of

CKD, protecting podocyte health has emerged as an attractive therapeutic strategy to preserve

glomerular function (reviewed in Lal and Patrakka 2018). One of the promising therapeutic

strategies aimed at protecting podocyte health is through the enhancement of homeostatic

mechanisms such as autophagy (reviewed in Liu, Xu et al. 2017).

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Several studies have investigated the effect of inducing autophagy as a therapeutic strategy in

kidney diseases, and efforts have been made to test the effects of pharmacological drugs that

enhance autophagic activity in experimental models of CKD. For instance, the nutrient-sensing

signal mTORC1, which is known to inhibit autophagy, has been investigated as a therapeutic

target for CKD (Kim, Kundu et al. 2011). The mTORC1 inhibitor rapamycin was shown to

suppress podocyte apoptosis in adriamycin-induced nephropathy (Yi, Zhang et al. 2017), a

classic model of CKD characterized by podocyte injury followed by glomerulosclerosis,

tubulointerstitial inflammation and fibrosis (reviewed in Lee and Harris 2011). Moreover,

inducing autophagy by rapamycin was also shown to protect against proximal tubule epithelial

cell damage in transgenic mice with nephron-specific overexpression of kidney injury molecule 1

(KIM-1), a mouse model of CKD characterized by tubular damage, reduced nephron number, and

fibrosis (Yin, Naini et al. 2016). Separately, several studies have shown that mTORC1 inhibition

attenuates cyst growth in rodent models of polycystic kidney disease (PKD), a genetic disorder

characterized by the presence of cysts in the kidney that can lead to ESKD (Tao, Kim et al. 2005,

Shillingford, Murcia et al. 2006, Wu, Wahl et al. 2007, Shillingford, Piontek et al. 2010, Zafar,

Ravichandran et al. 2010, Ravichandran, Zafar et al. 2014). However, the findings from

preclinical studies in models of PKD have failed to be recapitulated in humans. For instance, in a

phase 3 clinical trial, treatment with the mTORC1 inhibitor rapamycin for 18 months in patients

with autosomal dominant PKD showed no effects on renal volume or eGFR (Serra, Poster et al.

2010). The investigators speculated that the absence of effect may be due to the suboptimal dose

of rapamycin used in the study intended to limit the side effects such as proteinuria. Indeed, in a

separate study in which higher doses of rapamycin were found to halt cyst growth in patients with

autosomal dominant PKD, there was also a significant increase in albuminuria and proteinuria

(Perico, Antiga et al. 2010). Moreover, a subsequent study showed that treatment with low or

high doses of rapamycin in patients with autosomal dominant PKD had no effects on cyst

volume, or kidney function across treatment groups (Stallone, Infante et al. 2012).

Although mTORC1 inhibition by rapamycin or its derivatives is clinically approved as an

immunosuppressant following organ transplantation (Lim, Eris et al. 2014), and as a treatment for

specific types of cancer (reviewed in Benjamin, Colombi et al. 2011), it has been shown to be

associated with serious adverse effects, notably proteinuria (Straathof Galema, Wetzels et al.

2006, Perico, Antiga et al. 2010). In the context of podocyte health, although genetic reduction of

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podocyte-specific mTORC1 prevented the development of DKD in diabetic animals, complete

inhibition of mTORC1 in podocytes under normal conditions was shown to worsen podocyte

dysfunction and lead to glomerulosclerosis (Inoki, Mori et al. 2011). These findings may in part

explain the lack of current clinical trials for mTORC1 inhibitors as a treatment for CKD.

Moreover, rapamycin has been shown to result in partial activation of autophagy (reviewed in

Thoreen and Sabatini 2009) and is unable to directly induce autophagy at the transcription level,

which is mainly controlled by the transcription factor TFEB (Settembre, Di Malta et al. 2011).

The discovery of the transcription factor TFEB as a master regulator of lysosomal biogenesis

(Sardiello, Palmieri et al. 2009), lysosomal exocytosis (Medina, Fraldi et al. 2011), and

autophagy (Settembre, Di Malta et al. 2011) provided new insights into the regulatory processes

that control autophagy and lysosomal function. TFEB promotes autophagy by directly binding to

a network of genes that contains the CLEAR motif in the promoter region of lysosomal and

autophagy genes to facilitate their expression (Sardiello, Palmieri et al. 2009, Palmieri, Impey et

al. 2011, Settembre, Di Malta et al. 2011). Complete knockout of TFEB in mice is embryonic

lethal (Steingrímsson, Tessarollo et al. 1998), and gain- and loss-of-function studies in mice

identified its important role in liver metabolism (Settembre, De Cegli et al. 2013), immunity

(Huan, Kelly et al. 2006, Visvikis, Ihuegbu et al. 2014, Samie and Cresswell 2015), bone

resorption (Ferron, Settembre et al. 2013), glucose homeostasis and skeletal muscle energy

balance (Mansueto, Armani et al. 2017). The activity of TFEB is tightly regulated by post-

translational modifications. Under basal conditions, phosphorylated TFEB is bound to the 14-3-3

protein complex and retained in the cytosol in its inactive state. However, under starvation or

stress conditions, activated (dephosphorylated) TFEB translocates to the nucleus to facilitate the

transcription of its target genes. Phosphorylation of TFEB is mediated by at least two kinases,

including mTORC1 (Peña Llopis, Vega Rubin de Celis et al. 2011, Martina, Chen et al. 2012,

Roczniak-Ferguson, Petit et al. 2012, Settembre, Zoncu et al. 2012), and extracellular signal-

regulated kinase 2 (ERK2) (Settembre, Di Malta et al. 2011). TFEB nuclear translocation is

regulated by the phosphatase calcineurin, which binds and dephosphorylates TFEB and is itself

activated by lysosomal Ca2+ release through mucolipin 1 (MCOLN1) (Medina, Di Paola et al.

2015). In addition to (de)phosphorylation, (de)acetylation of TFEB also regulates its nuclear-

cytoplasmic shuttling (Bao, Zheng et al. 2016).

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Dysregulation of TFEB has been shown to contribute to impaired autophagy and lysosomal

dysfunction in neurodegenerative diseases (Decressac, Mattsson et al. 2013, reviewed in Martini-

Stoica, Xu et al. 2016), and enhancing the expression and the activity of TFEB has shown

benefits in several disease models of neurodegenerative diseases. For instance, TFEB activation

in a mouse model of Alzheimer’s disease (AD) was shown to increase lysosomal uptake of

accumulated amyloid β peptides in astrocytes, one of the underlying mechanisms causing

neuronal damage in AD (Xiao, Yan et al. 2014). Several studies have highlighted similarities

between podocytes and neurons, both cell types being postmitotic and the importance of

autophagy in neuronal homeostasis (Rastaldi, Armelloni et al. 2003, Rastaldi, Armelloni et al.

2006, Saito, Miyauchi et al. 2010, reviewed in Wong and Cuervo 2010, Soda, Balkin et al. 2012,

Sun, Zhang et al. 2014), supporting the potential role of TFEB as a promising therapeutic target

to maintain podocyte health in kidney diseases. This assertion has been supported by a few

published studies including the ones conducted in our lab examining the role of TFEB in the

kidney. In proximal tubule epithelial cells, Rega et al. showed that either activation or

overexpression of TFEB rescued cystinosis, a lysosomal storage disease caused by accumulation

of cysteine (Rega, Polishchuk et al. 2016). Consistent with these findings, a study from our lab

also reported that enhancing TFEB activity by inhibition of the cytosolic histone deacetylase 6

(HDAC6) in a rat model of CKD reduced proteinuria, prevented the accumulation of misfolded

protein aggregates in tubule epithelial cells, limited tubule cell death, and diminished

tubulointerstitial collagenous matrix deposition (Brijmohan, Batchu et al. 2018). In podocytes,

we demonstrated that TFEB overexpression restored podocyte dysfunction and impaired

autophagy completion induced by JAK2 knockdown in vitro as described in Chapter 2

(Alghamdi, Majumder et al. 2017). Although these data have identified a hitherto unrecognized

role for JAK2 in regulating TFEB and podocyte autophagy, recapitulating these findings in vivo

would strengthen the interpretability of their importance. Moreover, it would be interesting to

explore the direct role of TFEB in podocytes by generation and characterization of podocyte-

specific TFEB knockout mice. Furthermore, it would be intriguing to test the effect of podocyte-

specific TFEB overexpression and TFEB activation in models of DKD. Small molecule TFEB

activators have recently been developed and shown to ameliorate metabolic syndrome in mice

and extend lifespan in C. elegans (Wang, Niederstrasser et al. 2017). Although it is generally

acknowledged that autophagy plays a protective role in kidney diseases, the potential long-term

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effects of enhancing autophagy by increasing TFEB activity need further investigation, especially

given that increased TFEB activity has been shown to drive tumorigenesis in the kidney and

other tissues (Argani, Laé et al. 2005, Argani 2015, Giatromanolaki, Kalamida et al. 2015).

6.2. Targeting inflammatory mediators for treatment of diabetic kidney disease

The number of successful clinical trials for treatment of DKD has not kept pace with the growing

prevalence of DKD. This is in part due to the lack of animal models that precisely recapitulate the

DKD manifestations observed in humans, which remains an ongoing challenge in DKD research

(reviewed in Azushima, Gurley et al. 2018). However, major advances in scientific research have

provided mounting evidence demonstrating the critical role of inflammatory pathways in the

pathogenesis and progression of DKD (reviewed in Tuttle 2005). Among these inflammatory

pathways are the JAK/STAT pathway and the CCL2/CCR2 pathway, which are among the

promising therapeutic targets for treatment of DKD (reviewed in Brosius, Tuttle et al. 2016,

reviewed in Alicic, Johnson et al. 2018). In this section, I will discuss the findings from my thesis

work in the context of the translational progress of developed agents targeting these pathways,

and future challenges that may impede these agents from reaching the clinic.

6.2.1. JAK2 as a therapeutic target for DKD

The role of JAK/STAT activation in the development of DKD was demonstrated in several cell

types in the kidney (Marrero, Schieffer et al. 1995, Amiri, Shaw et al. 2002, Wang, Shaw et al.

2002, Banes-Berceli, Shaw et al. 2006, reviewed in Marrero, Banes-Berceli et al. 2006).

Moreover, transcriptome analysis of kidney samples from patients with early and progressive

DKD revealed a substantial increase in the expression of members of the JAK/STAT pathway

(Berthier, Zhang et al. 2009, Hodgin, Nair et al. 2013). These studies have shed light on the role

of the JAK/STAT pathway in the development of DKD (Berthier, Zhang et al. 2009). Of note,

JAK1 and JAK2 expression were observed to be upregulated in the glomeruli of patients with

early stage DKD (Berthier, Zhang et al. 2009). Based on findings in cultured cells, experimental

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animals, and human biopsies, modulation of the JAK/STAT activity has been proposed as a new

therapeutic approach for the treatment of DKD (reviewed in Brosius, Tuttle et al. 2016). Indeed,

the JAK inhibitor baricitinib, which has been effective in treatment of rheumatoid arthritis

(Keystone, Taylor et al. 2013, Genovese, Kremer et al. 2016), was recently repurposed for

treatment of DKD. A year before I started my PhD studies, a phase 2 clinical trial was initiated to

test the efficacy of the JAK1/2 inhibitor baricitinib in patients with type 2 diabetes with

progressive kidney disease (ClinicalTrials.gov identifier NCT01683409).

Cognizant of the growing interest in modulating JAK2 activity as a treatment for DKD and the

lack of studies demonstrating the fundamental role of JAK2 in podocytes, in my thesis work, we

examined the effect of podocyte-specific JAK2 deletion in podocytes in the normal setting

(Chapter 2), and the effect of systemic JAK2 inhibition and its deletion from podocytes in the

diabetes setting (Chapter 3). We published our findings on the role of JAK2 in regulating

podocyte autophagy a month after Zhang et al. reported that podocyte-specific overexpression of

JAK2 in podocytes in mice resulted in a modest increase in albuminuria in the normal setting

based on UACR (Zhang, Nair et al. 2017). However, under normal conditions, JAK2

overexpression in podocytes did not have any effects on podocyte structure, glomerular volume,

and glomerular fibronectin levels with only modest effect on mesangial expansion in nondiabetic

mice (Zhang, Nair et al. 2017). In contrast, in the diabetes setting, the investigators showed that

podocyte-specific JAK2 overexpression worsened kidney function, whereas lowering JAK2

activity using the JAK1/2 inhibitor baricitinib caused a significant reduction in UACR (Zhang,

Nair et al. 2017). However, it is not clear whether the renoprotective effect of baricitinib in

diabetic mice was JAK1- or JAK2- specific. By using the selective JAK2 inhibitor AZD1480

(Chapter 3), we found that JAK2 inhibition resulted in a marked reduction in albuminuria,

mesangial expansion, and urine CCL2 excretion in STZ-diabetic eNOS-/- mice. Likewise, urine

CCL2 excretion was significantly reduced in diabetic podocyte-specific JAK2 knockout mice

although albuminuria was not affected. The data from these studies support the notion that

podocyte JAK2 plays different roles under physiological and pathological conditions. In the

normal setting, deletion of JAK2 from podocytes contributes to the development of albuminuria

and podocyte dysfunction (Alghamdi, Majumder et al. 2017) and its overexpression does not

seem to worsen kidney function (Zhang, Nair et al. 2017). In the diabetes setting, however,

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podocyte-specific JAK2 deletion has an anti-inflammatory effect and its overexpression in

podocytes exacerbates kidney damage (Zhang, Nair et al. 2017).

The baricitinib phase 2 trial in patients at high risk for DKD progression defined by persistent

macroalbuminuria showed significant benefits of JAK1/2 inhibition on the primary outcome of

albuminuria in these patients (Tuttle, Brosius et al. 2018). Although the study met its primary

endpoint, baricitinib seems to influence creatinine-derived eGFR measurement, which was

among the secondary outcomes in this trial. There was a small albeit statistically significant

reduction in creatinine-based eGFR in two baricitinib treatment groups (1.5 mg and 4 mg daily

doses) at Week 24 compared to placebo. Although baricitinib did not affect eGFR derived by

cystatin C, creatinine-derived eGFR has been traditionally regarded as the standard surrogate end

point for assessing kidney function in clinical practice and in trials (ref). Moreover, the

observation that there was a decrease in creatinine-derived eGFR in the baricitinib treatment

group even at the middle-range dose (1.5 mg daily), which was recommended as an optimal dose

by the investigators, raises safety concerns for patients with advanced stages of kidney disease in

future clinical trials. In fact, the recent Briefing Document by the FDA Advisory Committee

explicitly stated that “baricitinib is not recommended for use in patients with severe renal

impairment or end-stage renal disease”

(https://www.fda.gov/downloads/AdvisoryCommittees/CommitteesMeetingMaterials/Drugs/Arth

ritisAdvisoryCommittee/UCM605062).

However, thus far, a phase 3 clinical trial for baricitinib has not been initiated and several

challenges may hinder the approval of JAK inhibitors for use in DKD. First, most early clinical

trials focus on albuminuria as a primary outcome. Choosing albuminuria as a primary endpoint in

renal trials especially in patients already receiving ARBs or ACEis limits the determination as to

whether the drug may have benefits in a wider range of patients with DKD. For instance, GFR

has been shown to severely decline in some patients with type 2 diabetes in the absence of

albuminuria (Kramer, Nguyen et al. 2003, Ekinci, Jerums et al. 2013). Classical hard renal

endpoints are death, dialysis, and doubling of serum creatinine in clinical trials of CKD

(reviewed in Weldegiorgis, de Zeeuw et al. 2015). However, phase 3 studies are costly and

sponsors will typically look at surrogate renal endpoints such as albuminuria before committing

resources to later phase clinical evaluation. In our experiments discussed in Chapter 3, we saw

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that JAK2 knockout from podocytes or systemic JAK2 inhibition decreased urine CCL2

excretion under diabetic conditions without affecting albuminuria in the case of podocyte-specific

JAK2 knockout. Concerted efforts are being made to look for alternative biomarkers or

biomarkers that could enrich a study population at higher risk of renal events. For instance, one

recent study showed measuring a combination of serum KIM-1 and β2-microglobulin predicted

renal decline in individuals with type 2 diabetes similar to that shown by a larger and more

expansive panel of biomarkers (Colombo, Looker et al. 2019). KIM-1 is a transmembrane protein

expressed in proximal tubule cells, and has been identified as a biomarker of kidney injury in

mice, rats, and humans (Sabbisetti, Walkar et al., 2014). Elevated levels of serum KIM-1 have

been shown to be associated with acute and chronic kidney injury and to predict progression to

ESKD in type 1 diabetes (Sabbisetti, Walkar et al., 2014). Moreover, upregulation of glomerular

KIM-1 has been reported in animal models of diabetes (Zhao, Zhang et al., 2011). B2M is a low

molecular weight protein that plays a role in antigen presentation by interacting with major

histocompatibility complex class I (MHC-1) (Güssow, Rein et al., 1987). B2M is mainly filtered

by the glomerulus followed by complete reabsorption by the proximal tubule (Peterson, Evrin et

al., 1969). Several studies have identified the role of B2M as a potential biomarker for DKD

(Kim, Yun et al., 2014), ESKD (Astor, Shafi et al., 2012), CVD (Kim, Yun et al., 2014; Astor,

Shafi et al., 2012), and mortality (Foster, Inker et al., 2015). Using a biomarker for glomerular

filtration (i.e. B2M) in combination with a tubular biomarker (i.e. KIM-1), which has been shown

to predict progression of kidney dysfunction in type 2 diabetes from three different clinical

studies (Colombo, Looker et al. 2019), is a novel and feasible approach to enrich clinical trials

and identify patients at high risk of kidney disease progression. However, given that DKD is a

multifactorial disease with complex pathophysiology, it is important to validate whether this

approach will reflect kidney disease progression or drug efficacy in large clinical trials and

whether it can be generalized to a larger patient population. Therefore, continuing to explore

appropriate endpoints suited for prediction of rapid renal decline and the risk of progression to

ESKD in early clinical trials is imperative, especially for a complex and heterogeneous disease

such as DKD. Second, relying on single biomarker such as albuminuria in early clinical trials is

unlikely to circumvent the recruitment challenge of patients with DKD. For instance, in the

baricitinib trial, out of 376 patients assessed for eligibility, only 129 participants were ultimately

enrolled in the study because of lower than anticipated rate of macroalbuminuria, which was an

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inclusions criteria for the study (Tuttle, Brosius et al. 2018). In recent years, an increasing

proportion of DKD is being observed in patients who have a low eGFR with minimal or low

levels of albuminuria (Afkarian, Zelnick et al. 2016). This represents an evolution in our

understanding of the natural history of DKD. Historically, phase 2 clinical studies have focused

on albuminuria as a surrogate endpoint, but if albuminuria becomes less prevalent, these trials

will continue to be harder to conduct. Third, early clinical trials for DKD including the baricitinib

trial are mostly in patients with type 2 diabetes, overlooking the potential effects of JAK

inhibitors on kidney dysfunction in patients with type 1 diabetes. In addition, although baricitinib

was approved for other indications and despite the short duration of the baricitinib trial for DKD,

adverse effects were reported including a slight increase in serum creatinine levels,

hypoglycemia, and anemia (Tuttle, Brosius et al. 2018). Whereas the tolerability profile of JAK

inhibitors may be acceptable in the setting of malignancies or chronic inflammatory

arthropathies, it may be unacceptable for the treatment of complex CKD such as DKD, in which

patients may be otherwise asymptomatic.

6.2.2. CCL2/CCR2 signaling as a therapeutic target for DKD

Cytokines and adhesion molecules play crucial roles in orchestrating inflammatory responses,

and are known to be upregulated in diabetes (reviewed in Navarro-González, Mora-Fernández et

al. 2011). The chemokine CCL2 signals through its major receptor CCR2 to promote recruitment

of monocytes into sites of inflammation (Banba, Nakamura et al. 2000). High levels of urinary

CCL2 (Banba, Nakamura et al. 2000, Tesch 2008, Verhave, Bouchard et al. 2013) and CCR2

overexpression was reported in glomerular podocytes of patients with diabetes and overt

nephropathy (Tarabra, Giunti et al. 2009). Moreover, loss of CCL2 was found to prevent

downregulation of nephrin and albuminuria in diabetic mice, suggesting that CCL2 signaling in

the kidney contributes to the development of albuminuria in DKD and leukocyte recruitment

does not appear to be the sole mechanism by which CCL2 contributes to kidney damage in

diabetes (Tarabra, Giunti et al. 2009). In experimental models of DKD, modulation of the

CCL2/CCR2 axis either by genetic manipulation or using pharmacological compounds that block

CCL2 signaling or its receptor CCR2 have shown benefits in preclinical studies (Chow, Ozols et

al. 2004, Chow, Nikolic-Paterson et al. 2006, Chow, Nikolic-Paterson et al. 2007, Lee, Chung et

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al. 2009). Currently, some of the pharmacological compounds targeting CCL2 and its receptor

CCR2 have shown promising effects in early clinical trials for the treatment of DKD (de Zeeuw,

Bekker et al. 2015, Menne, Eulberg et al. 2016). Treatment with CCX140-B, a selective CCR2

inhibitor, in 332 patients with DKD for over a year reduced UACR (de Zeeuw, Bekker et al.

2015). Likewise, in a phase 2 trial, three month treatment with emapticap pegol (NOX-E36), an

L-RNA optamer that specifically binds and inhibits CCL2, showed favorable effects on UACR

and glycemia in type 2 diabetes patients with albuminuria, persisting for two months after

cessation of therapy (Menne, Eulberg et al. 2016). However, in both of these trials, no changes

were observed on eGFR or blood pressure, suggesting that the renoprotective effects of

CCL2/CCR2 blockade could be independent of hemodynamic changes. Although delineation of

the mechanisms mediating the renoprotective effects of these agents remains under investigation,

several studies in rodent models provided mechanistic insights into their anti-inflammatory mode

of action. For instance, blockade of CCL2 in db/db mice, an experimental model of type 2

diabetes, reduced glomerular macrophage infiltration, which was associated with improvement in

GFR and glomerulosclerosis (Ninichuk, Clauss et al., 2008). In another recent study by Boels and

colleagues, CCL2 inhibition by emapticap pegol treatment for four weeks in STZ-diabetic

apolipoprotein E (ApoE) knockout mice attenuated albuminuria and restored glomerular

endothelial glyocalyx without any effect on absolute number of kidney macrophages or systemic

hemodynamics (Boels, Koudijs et al. 2017). These data are in line with the findings presented in

Chapter 4 in which we provided insights into the role of CCL2/CCR2 signaling in DKD

development beyond macrophage infiltration. In my thesis work (Chapter 4), we showed that in

experimental models of DKD, CCL2 contributes to glomerular VCAM-1 upregulation, indicative

of glomerular endothelial activation, and this increase was attenuated in diabetic CCR2 knockout

mice (Alghamdi, Batchu et al. 2018). Moreover, we showed that signaling through CCR2

induced an epigenetic change, specifically phosphorylation of histone protein H3 on serine

residue 10 (H3Ser10), through p38-MAPK and MSK1/2, which resulted in VCAM-1

upregulation in glomerular endothelial cells. These findings unraveled a previously unrecognized

pathogenetic function for CCL2/CCR2 signaling in glomerular endothelial activation in diabetes,

further underscoring the detrimental effects of CCL2/CCR2 signaling in the context of DKD.

From a therapeutic perspective, our studies shed light on the renoprotective mechanisms of

CCL2/CCR2 blockade, specifically through modulation of glomerular VCAM-1 expression.

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VCAM-1 promotes endothelial activation and its interaction with VLA-4 mediates inflammatory

leukocyte recruitment induced by cytokine activation (Alon, Kassner et al. 1995, reviewed in

Pober 2002). Elevated levels of circulating VCAM-1 have been implicated in DKD and shown to

correlate with albuminuria (Clausen, Jacobsen et al. 2000, Nelson, Karschimkus et al. 2005,

Rubio-Guerra, Vargas-Robles et al. 2009). In a separate study, high levels of circulating VCAM-

1 and albuminuria in patients with type 2 diabetes followed for nine years, were associated with

increased risk of death, which was independent of high blood pressure and poor glycemic control

(Stehouwer, Gall et al. 2002). Despite the accumulating evidence implicating VCAM-1 in the

development of DKD, thus far, no clinical trial has investigated targeting VCAM-1 as a

therapeutic intervention for patients with DKD. This is partly due to the lack of humanized

antibodies that specifically block VCAM-1 (reviewed in Kong, Kim et al. 2018). However,

blocking VCAM-1 by neutralizing antibodies has shown benefits in experimental models of

inflammatory diseases such as rheumatoid arthritis (Carter, Campbell et al. 2002, Silverman,

Haas et al. 2007), and asthma (Nakajima, Sano et al. 1994, Fukuda, Fukushima et al. 1996). In

contrast, a few studies explored the effect of modulation of glomerular VCAM-1 in animal

models of kidney diseases (Allen, McHale et al. 1999, Khan, Allen et al. 2003). In an

experimental model of glomerulonephritis, treatment with an anti-VL4 antibody, but not with an

anti-VCAM-1 antibody, attenuated albuminuria and renal injury with a paradoxical increase in

markers of macrophage activation and no effect on glomerular leukocyte number (Allen, McHale

et al. 1999, Khan, Allen et al. 2003). Although modulation of VCAM-1 has not been explored in

DKD, targeting other adhesion molecules has been evaluated in early clinical trials for treatment

of DKD including vascular adhesion protein 1 (VAP-1) (de Zeeuw, Renfurm et al. 2018),

galectin-3 (Kikuchi, Kobayashi et al. 2004, Dang, MacKinnon et al. 2012, Calvier, Martinez-

Martinez et al. 2015), and αVβ3 integrin (Yoon, Gingras et al. 2001, Maile, Busby et al. 2014).

Out of these therapeutic targets, inhibition of VAP-1 by ASP8232 proved to be safe and effective

when added to the current standard of care for patients with DKD (de Zeeuw, Renfurm et al.

2018).

Although numerous excellent preclinical and early clinical studies point to the potential utility of

agents targeting inflammatory pathways, specifically the CCL2/CCR2 pathway and the

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JAK/STAT pathway in DKD, the safety and the efficacy of these agents for the treatment of

DKD in patients are still under investigation. From a mechanistic perspective, there remain

several unresolved questions that require additional studies. For instance, most of the studies in

kidney diseases focused on the roles of JAK2 and its downstream mediator STAT3 (reviewed in

Brosius Iii and He 2015). However, the cell-specific role of other members of the JAK/STAT

pathway in the kidney is not completely understood. Second, although targeting the CCL2/CCR2

pathway and the JAK/STAT pathway in early clinical trials for treatment of DKD seem

promising, systemic inhibition of these pathways may have opposing effects. For instance, low

pancreatic islet expression of CCL2 may actually contribute to the development of type 1

diabetes in nonobese diabetic mice (Kriegel, Rathinam et al. 2012), and low levels of CCL2 have

been reported in humans with type 1 diabetes in comparison to healthy individuals (Guan,

Purohit et al. 2011). Similarly, several studies reported that activation of the JAK/STAT pathway

plays a protective role in experimental models of acute kidney injury (Nechemia-Arbely, Barkan

et al. 2008, Arany, Reed et al. 2011, Correa-Costa, Azevedo et al. 2012, Susnik, Sörensen-Zender

et al. 2014), suggesting that the role of JAK/STAT pathway in the kidney is context-dependent.

Thus, while the developed agents targeting the CCL2/CCR2 pathway and the JAK/STAT

pathway are being evaluated, elucidating the mechanisms of actions and the tissue-specific role

of these pathways will be crucial in informing the interpretation of any future trial results.

6.3. Histone phosphorylation in DKD

Posttranslational histone modifications play important roles in controlling transcriptional gene

activation generally by modification of chromatin compaction activity and recruitment of effector

complexes (reviewed in Kouzarides 2007, reviewed in Bannister and Kouzarides 2011, reviewed

in Lawrence, Daujat et al. 2016). Among these modifications, histone (de)acetylation and

(de)methylation have been extensively studied in DKD, and only recently have studies begun to

explore the actions of other histone modifications in DKD pathogenesis, particularly histone

phosphorylation (Badal, Wang et al. 2016). Through our work described in Chapter 4, we

discovered that CCL2/CCR2 signaling initiates an intracellular signaling cascade that involves

p38-MAPK and MSK1/2, which results in upregulation of histone H3Ser10 phosphorylation and

glomerular endothelial activation. Several kinases have been identified to phosphorylate histone

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H3 on serine 10 including IκB kinase α (IKK-α), c-Jun N-terminal kinase (JNK), protein kinase

A, Akt, Cancer Osaka Thyroid (Cot) kinase, proto-oncogene serine/threonine-protein kinase 1

(PIM1), cyclin-dependent kinase 8 (CDK8), calcium/calmodulin-dependent protein kinase IIδ

(CaMKIIδ) and MSK1/2 (reviewed in Sawicka and Seiser 2012). However, MSK1/2 is the best-

characterized kinase (reviewed in Arthur 2008), which has been recently implicated in chromatin

remodeling in DKD (Badal, Wang et al. 2016). In our in vitro experiments described in Chapter

4, we reported that MSK1/2 inhibition reduced the expression of VCAM-1 and H3Ser10

phosphorylation induced by CCL2 signalling, and attenuated the enrichment of phospho-histone

H3Ser10 at the VCAM-1 promoter in glomerular endothelial cells. These observations raise the

question of whether inhibition of MSK1/2 may exert renoprotective effects in DKD.

MSK1 and MSK2 are members of the Ribosomal S6 Kinase (RSK) family of serine/threonine

kinases that have overlapping function (Wiggin, Soloaga et al. 2002, Soloaga, Thomson et al.

2003). A number of MSK substrates have been identified, which include transcription factors

cAMP-responsive element binding protein (CREB), activating transcription factor (ATF) 1 and

NF-κB, as well as histone H3 (reviewed in Arthur 2008). While MSK1/2 has been best studied in

the brain and in innate immunity, its role in the kidney remains unexplored. A recent study by

Badal et. al. showed that in vivo depletion of MSK2 prevented podocyte loss and ameliorated

kidney dysfunction in diabetic mice, and this was linked to modulation of its substrate histone

H3Ser10, first implicating MSK2/H3Ser10 in DKD pathogenesis. Although MSK1/2 double

knockout mice lack an overt phenotype under physiological conditions (Wiggin, Soloaga et al.

2002), the investigators showed that MSK2 knockout caused a significant reduction in

albuminuria in mice when challenged with diabetes (Badal, Wang et al. 2016). With the

availability of the highly selective pharmacological MSK1/2 inhibitor SB-747651A employed in

our studies in Chapter 4, it would be particularly interesting to examine the effects of MSK1/2

inhibition as well as MSK1/2 knockout in experimental models of DKD. Although inhibition of

MSK1/2 has not been explored in DKD, a recent study demonstrated the effects of the

pharmacological MSK1/2 inhibitor SB-747651A and MSK1/2 knockout in the context of

pancreatic development (Bhat, Park et al. 2016). The investigators showed that MSK1/2

inhibition, using SB-747651A, in embryonic mouse pancreatic explants caused induction of

endocrine fates including the beta cells lineage, and suppression of acinar differentiation (Bhat,

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Park et al. 2016). Interestingly, they observed similar effects in germline knockout of MSK1 and

MSK2, which resulted in enhanced production of pancreatic alpha cells and suppressed

differentiation towards the acinar lineage. The investigators went on to determine that the effect

of MSK proteins on pancreatic development was mediated by phospho-histone H3Ser28, another

phosphorylation site on histone H3 controlled by MSK1/2 (Bhat, Park et al. 2016). These data

support the potential beneficial effect of MSK1/2 inhibition/knockout and highlight the role of

MSK1/2 in controlling gene expression by means independent of histone H3Ser10

phosphorylation. Because the double knockout of MSK1/2 in mice did not cause an overt

phenotype (Wiggin, Soloaga et al. 2002), modulation of MSK1/2 activity will unlikely have

serious adverse consequences. Recognizing that drug safety is one of the major challenges that

prevent progression of clinical trials of new developed compounds, MSK1/2 serves as an

attractive therapeutic target for treatment of CKD that is worth investigating in preclinical

studies.

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6.4. Conclusion

The research studies described in my doctoral dissertation present new findings that provide

mechanistic insights into the (patho)biology of glomerular cells in health and in diabetes. In

health, we discovered a homeostatic role for podocyte JAK2 in autophagy completion by

regulating TFEB, which itself may serve as a therapeutic target to maintain podocyte

homeostasis. In diabetes, podocyte JAK2 plays a separate role in inflammation and JAK2

inhibition attenuates kidney dysfunction in an experimental model of diabetic kidney disease. By

exploring how podocytes communicate with glomerular endothelial cells under diabetic

conditions, we identified a role for CCL2/CCR2 signaling in epigenetically promoting glomerular

endothelial cell activation through histone H3 phosphorylation. Delineating the molecular

mechanisms implicated in glomerular cell biology in health and disease will continue to provide

new avenues for discovering biological targets and could be crucial in informing future

therapeutic development.

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Appendices

List of primer sequences used in the studies.

Sequences (5’ 3’)

Forward mouse -galactosidase TGGGATCAAACACCTCGCAA

Reverse mouse -galactosidase CCAGTCAGCAAATGTCTGCG

Forward mouse ATP6AP2 TCTCTCCGAACTGCAAGTGCAACA

Reverse mouse ATP6AP2 CCAAACCTGCCAGCTCCAATGAAT

Forward mouse ATPase H+ transporting accessory protein 1 TACACCGCAGCTCTTACTGC

Reverse mouse ATPase H+ transporting accessory protein 1 AGGAGATGCCACCTGAGTCT

Forward mouse ATPase H+ transporting lysosomal VO subunit C TGCTGGTATTTAGAGCGCAG

Reverse mouse ATPase H+ transporting lysosomal VO subunit C GCCTCATGACTGACATGGCT

Forward mouse Autophagy related 14 GTGGCGAAAACCTCAGCAAG

Reverse mouse Autophagy related 14 GAACCAAGAGGTCACCGAGG

Forward mouse Beclin 1 AGGCATGGAGGGGTCTAAGG

Reverse mouse Beclin 1 GCCTGGGCTGTGGTAAGTAAT

Forward mouse ß-actin AGAGGGAAATCGTGCGTGAC

Reverse mouse ß-actin CAATAGTGATGACCTGGCCGT

Forward mouse Cathepsin B ATGTGGTGGTCCTTGATCCTT

Reverse mouse Cathepsin B CTTCCTGGCAGTTTGGGTCC

Forward mouse Cathepsin D CTATAAGCCGGCGACCTCTG

Reverse mouse Cathepsin D TGAACTTGCGCAGAGGGATT

Forward mouse Caveolin-1 AAAAGTTGTAGCGCCAGGCT

Reverse mouse Caveolin-1 GACCACGTCGTCGTTGAGAT

Forward mouse CD38 GATGCTCAATGGGTCCCTCC

Reverse mouse CD38 GGAAGCTCCTTCGATGTCGT

Forward mouse Cystinosin CAAGTCCTGGGGGCTTAGAG

Reverse mouse Cystinosin GGCTGGGTAGGCATCTTGAA

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Forward mouse DNA damage regulated autophagy modulator 1 GCTTCTTGGTCCGACGAG

Reverse mouse DNA damage regulated autophagy modulator 1 AGTGTCGTTGGTGCTATCCA

Forward mouse FAM176A GAAGTACGCGCCAGTCGT

Reverse mouse FAM176A TCAGCACCTTTCCAAGGC

Forward mouse Histone deacetylase 6 AGCCTGGTTAAACGGTAGGC

Reverse mouse Histone deacetylase 6 AAGGCTCTCTAATCTGCGCC

Forward mouse Huntingtin-associated protein 1 TCCCTCTGAGGAGCTGTCTG

Reverse mouse Huntingtin-associated protein 1 GGGGCATCAGAACGACTGAA

Forward mouse Lysosomal -glucosidase AGCGAGTTCCTGCTTTGGAG

Reverse mouse Lysosomal -glucosidase CCGAAGCATGAGATGACCCA

Forward mouse Mucopilin-1 GGCGCCTATGACACCATCAA

Reverse mouse Mucopilin-1 CAGTTCACCAGCAGCGAATG

Forward mouse Niemann-Pick C1 CCTACCCCACATGCTGTCTC

Reverse mouse Niemann-Pick C1 CTGTCTTCCCGGGCCATAAC

Forward mouse Nuclear receptor binding factor-2 TGTCGCTCTTGGGCTCTCA

Reverse mouse Nuclear receptor binding factor-2 CCAGCAGCTAACAAACGGTC

Forward mouse Pleckstrin homology domain-containing family M member 1 TCGAAGTCCAACACTCAGGC

Reverse mouse Pleckstrin homology domain-containing family M member 1 CTCAAAGTGCAGGTGTGTGC

Forward mouse Ras-related GTP binding C AAGTTTTTGTGCGGCATCGG

Reverse mouse Ras-related GTP binding C GGTCATGATCAGGCGAGGAG

Forward mouse Ribosomal protein large p0 GCGTCCTGGCATTGTCTGT

Reverse mouse Ribosomal protein large p0 GAAGGCCTTGACCTTTTCAGTAAG

Forward mouse Ribosomal protein L13a GCTCTCAAGGTTGTTCGGCTGA

Reverse mouse Ribosomal protein L13a AGATCTGCTTCTTCTTCCGATA

Forward human Ribosomal protein L13a AGCTCATGAGGCTACGGAAA

Reverse human Ribosomal protein L13a CTTGCTCCCAGCTTCCTATG

Forward mouse Serine/threonine kinase 4 TGTGTGGCAGACATCTGGTC

154

Reverse mouse Serine/threonine kinase 4 ACAAACGGGTGCTGTAGGAG

Forward mouse SNAP-associated protein GCTACAGAACTGTGCCGGAT

Reverse mouse SNAP-associated protein AACCGCCTTAGTCGTTCCTG

Forward mouse Sorting nexin 14 CCAAATTCAACAGAAGCACACA

Reverse mouse Sorting nexin 14 TGTCCAACTGCTCGTCTGTC

Forward mouse Syntaxin 17 CTAGGCGGGAGGTGTTTCTG

Reverse mouse Syntaxin 17 AGCCTGCGTAACTTCACCTT

Forward mouse Tectonin ß-propeller repeat containing 1 GAATTTTGGAGGGGAGCCCA

Reverse mouse Tectonin ß-propeller repeat containing 1 TGGCTGACATCCTCTCGGTA

Forward mouse Transcription factor EB CTCTTGCAGAAGACCCCTCT

Reverse mouse Transcription factor EB AGGGTGGTGGGATAGTGCAA

Forward mouse Transcription factor EB promoter GCTACACCCCAGGAAACGTC

Reverse mouse Transcription factor EB promoter TTGTTTTGGTGAGTCCCGCA

Forward mouse Vacuolar protein sorting 18 TGGGCGAGGTTGTGATTACC

Reverse mouse Vacuolar protein sorting 18 AAGGACGAGACGATCGAGGA

Forward human Vascular cell adhesion molecule 1 ATTTCACTCCGCGGTATCTG

Reverse human Vascular cell adhesion molecule 1 CCAAGGATCACGACCATCTT

Forward mouse Vascular cell adhesion molecule 1 CCCAAGGATCCAGAGATTCA

Reverse mouse Vascular cell adhesion molecule 1 TAAGGTGAGGGTGGCATTTC

Reverse human Vascular cell adhesion molecule 1 promoter CCTTCAAGGGGAAACCCAGG

Forward mouse Vascular cell adhesion molecule 1 promoter ATCTCTGTCTTTGCTGTCAC

Reverse mouse Vascular cell adhesion molecule 1 promoter CTCTCCTGAAAAGATGATTG

Forward mouse Vesicle-associated membrane protein 7 CAGACGGTACTCGGTCAGATT

Reverse mouse Vesicle-associated membrane protein 7 CTTAGCCAGAATCTGCTCTGTC

Forward mouse Vesicle-associated membrane protein 8 AACCTGCAGTTACGTGTGTG

Reverse mouse Vesicle-associated membrane protein 8 TGTTCAGACGTGGCTTCCAA

155

Copyright Acknowledgments

Chapter 1

Figure 1.1: The prevalence rate of chronic kidney disease (CKD) per 100,000 of the global

population across age groups and by sociodemographic index (SDI) quintiles. Adapted from

(Xie, Bowe et al. 2018) with no copyrights permission required under the terms of the Creative

Commons Attribution-NonCommercial-No Derivatives License (CC BY NC ND). [original

article link: https://doi.org/10.1016/j.kint.2018.04.011]

Figure 1.2: Chronic kidney disease classification based on glomerular filtration rate (GFR) and

albuminuria. Permission for the reuse of this figure was obtained from Springer Nature and

Copyright Clearance Center. The license number for the permission is 4497241332400.

Figure 1.5: JAK2 structure. Permission for the reuse of this figure was obtained from Springer

Nature and Copyright Clearance Center. The license number for the permission is

4497230979056.

Figure 1.6: The intricate beauty of podocytes. Permission for the reuse of this figure was obtained

from Spring Nature and Copyright Clearance Center. The license number for the permission is

4476890749834

Chapter 2

Permission for the reuse of the published manuscript was obtained from the American Society of

Nephrology and Copyright Clearance Center. The license number for the permission is

4278341363568.

Chapter 3 and 4

Permission for the reuse of the published manuscript was obtained from the American Diabetes

Association and Copyright Clearance Center. The license number for the permission is

4491451306362

156

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