Faculty of Bioscience Engineering

Academic year 2013 – 2014

The Effect of Low-fluid Shear on Human Gut Bacteria

Ibtisam Ibtisam Promoter: Prof. Dr. ir. Tom Van de Wiele

Master’s dissertation submitted in partial fulfilment of the requirements for the degree of

Master of Science in Nutrition and Rural Development Main Subject: Human Nutrition – Major: Public Health Nutrition

COPYRIGHT

I, Ibtisam, vow that this is the result of my own work conducted under the supervision of Prof. DrTom Van de Wiele. I declare that this master dissertation has not been submitted to any university for a degree that has been made here or elsewhere. All assistance contained herein, which served as sources of information, has been duly acknowledged given for consulting and copying parts of this work for personal use only by the author and proAny other use falls under the limitation of copyrightspecify the source when using results or citing parts from this master’s dissertation after having obtained the written permission.

Gent, Belgium 21st August 2014

Promoter: Prof. Dr. Ir. Tom Van de Wiele

(E-mail: Tom.vandewiele@ugent

I, Ibtisam, vow that this is the result of my own work conducted under the supervision of Prof. Drthat this master dissertation has not been submitted to any university for

a degree that has been made here or elsewhere. All assistance contained herein, which served as sources of information, has been duly acknowledged by references to the authors. Permission is being given for consulting and copying parts of this work for personal use only by the author and pro

der the limitation of copyright laws; in particular it is obligatory to explicitlyspecify the source when using results or citing parts from this master’s dissertation after having

.

r. Tom Van de Wiele Author: Ibtisam Ibtisam

ugent.be) (E-mail: ibtisam.hasandjazuli@gmail.com)

i

I, Ibtisam, vow that this is the result of my own work conducted under the supervision of Prof. Dr. Ir. that this master dissertation has not been submitted to any university for

a degree that has been made here or elsewhere. All assistance contained herein, which served as by references to the authors. Permission is being

given for consulting and copying parts of this work for personal use only by the author and promoter. laws; in particular it is obligatory to explicitly

specify the source when using results or citing parts from this master’s dissertation after having

mail: ibtisam.hasandjazuli@gmail.com)

ii

Acknowledgement

“The mind travels faster than the pen; consequently, writing becomes a question of learning to make occasional wing shots, bringing down the bird of thought as it flashes by. A writer is a gunner, sometimes waiting in the blind for something to come in…” — E.B. White, The Elements of Style

Everything flowEverything flowEverything flowEverything flowssss,,,, nothing standnothing standnothing standnothing standssss stillstillstillstill ---- Heraclitus of EphesusHeraclitus of EphesusHeraclitus of EphesusHeraclitus of Ephesus

First of all, I would like to take this opportunity to express my most sincere gratitude to my promoter Prof. Dr. ir. Tom Van de Wiele, who have helped and supported me with the completion of this master dissertation; without his professional guidance, useful critiques, clear feedbacks and continuous encouragement, this master dissertation would not have been possible. I'm so lucky to have a chance to work directly under his professional guidance.

I would like to thank to Beasiswa Tesis LPDP Keuangan Indonesia for the funding support from Ministry of Finance of Republic Indonesia. I would also like to express my great appreciation to the programme coordinator of Human Nutrition and Rural Development, ir. Anne-Marie Remaut-De Winter for her valuable advice and assistance during my study.

I would like to thank to Laboratory of Microbial Ecology and Technology (LabMET, Ghent University) for the opportunity working on my master dissertation. I would like to thank all LabMET thesis students, all LabMET researchers, including the laboratory manager and the technician for the pleasant working atmosphere. Also for the extra help and explanations they offer when it was needed. Special thanks should be given to Tim Lacoere and Way Cern Khor who have helped me to improve my English and without their assistance during the laboratory works, this master dissertation would not have been completed to the current extent.

I would like to thank my family in Indonesia who has always supported me towards the accomplishment of this master degree, especially my grateful to my Mom for her endless love and her support. For the love of coffee, thank you coffee pot for always be there, through the days and nights boosting my mood during the laboratory works and the writing processes of this master dissertation.

Finally, I’m so grateful for the blast moment I have during my master degree study and during two years of my stay in Gent, Belgium. I have a nice time and will often think to be back here.

Lastly, as Albert Einstein said: “Learn from yesterday, live for today, hope for tomorrow. The important thing is to not stop questioning.” ― Relativity: The Special and the General Theory.

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Abstract

The human gut is colonized by a vast and diverse microbial community that plays an important role in human health. The gut is typically characterized by several micro-environment parameters to which the residing microorganisms are subjected. There are two micro-environment physicochemical factors that determine the mucus-associated microbiota: an oxygen gradient across the epithelium and mucus layer and the low-fluid shear. The latter is thought to play a key role in dictating whether the bacteria can adapt and favour the host or in reverse become more resistant and cause onset of disease. However, the process by which low-fluid shear affects the adhesion capacity of the mucus-associated microbiota is not well known.

Using the Rotating Wall Vessel Bioreactor (RWV) to create a rheological relevant of low-fluid-shear environments, we investigated the effect of low-fluid shear on the beneficial gut bacteria Lactobacillus reuteri ATCC 6475 as compared to the opportunistic pathogen Adherent Invasive Escherichia coli LF 82 (AIEC). By using RWV in different positions we investigated what impact different fluid shear conditions have on the growth, mucin adhesion, metabolites production, and DNA profiles of the colon gut microbial community.

Low-fluid shear was shown to enhance the mucin adhesion capacity of L. reuteri in different growth media. L. reuteri grown in nutrient rich medium under low-fluid-shear environment was found to initiate biofilm formation. Compared to controls and normal shear conditions, low-fluid shear cultured cells have displayed a higher inactivation of L. reuteri in the presence of linoleic acid (1 log difference). Analyzing the production of organic acids, both L. reuteri and AIEC displayed similar trends in metabolic activity patterns with a tendency for slower metabolic activity. L. reuteri has demonstrated a lower lactate production after 1.5 h incubation and a higher lactate production after 5 h incubation. Similarly, AIEC demonstrated a lower production of acetate at 1.5 h incubation and a higher production of acetate at 5 h incubation. When looking at more complex microbial populations, representative for that of the colon, our results suggest that low-fluid shear conditions favor growth, lower the production of SCFAs (acetate, propionate, and butyrate), and increase the production of lactate. These insights may aid in a better understanding of the key factors influencing the divergence between infection and colonization during the initial host-pathogen interaction and the role of gut microbiota in health and diseases.

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Table of Contents

COPYRIGHT ........................................................................................................................................ I

ACKNOWLEDGEMENT ................................................................................................................... II

ABSTRACT ........................................................................................................................................ III

TABLE OF CONTENTS ...................................................................................................................IV

LIST OF ABBREVIATIONS AND UNITS .................................................................................... VII

LIST OF TABLES .......................................................................................................................... VIII

LIST OF FIGURES ............................................................................................................................IX

LIST OF EQUATIONS .................................................................................................................... XII

1 INTRODUCTION ......................................................................................................................... 1

2 LITERATURE REVIEW ............................................................................................................. 3

2.1 MICROBIOTA IN THE GUT ..................................................................................................... 3

2.1.1 The Gut Microbiota ............................................................................................................. 3

2.1.2 The Mucus – Associated Microbiota .................................................................................. 5

2.1.3 Health Aspect of Host – Microbes interaction in the Gut ................................................... 6

2.1.3.1 Function of Gut Microbiota ........................................................................................ 6

2.1.3.2 Diseases Related to Disturbances of Mucus - Associated Gut Microbiota ................. 8

2.2 SHEAR STRESS IN THE GUT ................................................................................................... 9

2.2.1 Definition of Fluid-Shear Stress ......................................................................................... 9

2.2.2 Peristaltic Movement In the Gut ......................................................................................... 9

2.2.3 Gradient of fluid-Shear Stress In the Gut .......................................................................... 10

2.2.4 Pathogenic Behaviour in the Absence of Low-fluid Shear Stress .................................... 10

2.2.5 Rotating Wall Vessel as an in vitro Model to Study Low-fluid Shear Stress ................... 11

2.3 SUMMARY AND OBJECTIVES ............................................................................................... 12

3 MATERIAL AND METHODS.................................................................................................. 13

3.1 MATERIALS (CHEMICALS , GROWTH MEDIUM , AND BACTERIAL STRAINS) ................... 13

3.1.1 Bacterial Strains ................................................................................................................ 13

3.1.2 Chemicals .......................................................................................................................... 13

3.1.3 Growth Medium ................................................................................................................ 14

3.2 ROTATING WALL VESSEL EXPERIMENTAL SET-UP .......................................................... 14

3.2.1 Preparation of Bacterial Culture and Bacterial Growth Suspension ................................. 14

3.2.2 Filling and Mounting the RWV Bioreactor ...................................................................... 15

3.3 EXPERIMENTAL DESIGNS .................................................................................................... 16

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3.3.1 An Optimization of the Growth Medium for L.reuteri Growth and Mucin Adhesion Assay ........................................................................................................................................... 16

3.3.2 Investigation of the Survival of L.reuteri in the Presence of LA under Low-fluid Shear . 17

3.3.3 A comparative Study of the Effect of Low-fluid Shear in Enriched-Intestinal Water ...... 18

3.3.4 An overview of the Effect of a Low-fluid Shear on Complex Microbial Community ..... 19

3.4 GROWTH AND MUCIN AGAR ADHESION ASSAYS ............................................................... 20

3.4.1 Growth Assay .................................................................................................................... 20

3.4.2 Mucin - adhesion assay ..................................................................................................... 20

3.5 BIO-CHEMICAL ANALYSIS ................................................................................................... 21

3.5.1 Short Chain Fatty Acids extraction for Gas Chromatography Analysis ........................... 21

3.5.2 Lactate Analysis Sample Preparation................................................................................ 22

3.6 MOLECULAR TECHNIQUES FOR DENATURING GRADIENT GEL ELECTROPHORESIS

(DGGE) ANALYSIS .......................................................................................................................... 23

3.6.1 DNA Extraction ................................................................................................................ 23

3.6.2 Agarose Gel Electrophoresis to Check the Purity of DNA Extraction ............................. 23

3.6.3 Nanodrop to Check the Concentration of the Extracted DNA .......................................... 24

3.6.4 Polymerase Chain Reaction (PCR) Amplification for DGGE .......................................... 24

3.6.5 Denaturing Gradient Gel Electrophoresis (DGGE) Experiment Set-up ........................... 25

3.7 STATISTICAL TOOLS ............................................................................................................ 26

3.7.1 Statistical Analysis for Growth Assays ............................................................................. 26

3.7.2 Statistical Analysis for Processing DGGE Results ........................................................... 26

4 RESULTS .................................................................................................................................... 27

4.1 INVESTIGATION OF THE EFFECT OF LOW-FLUID SHEAR ON LACTOBACILLUS REUTERI . 27

4.1.1 Optimization of the Growth Medium for the Investigation of Low-fluid Shear in the RWV ........................................................................................................................................... 27

4.1.2 Investigation of the Effect of Low-Fluid Shear on the inactivation of L. reuteri in Linoleic Acid ........................................................................................................................................... 29

4.1.3 Investigation of the Effect of Low-fluid Shear on L. reuteri in Enriched Growth Medium . ........................................................................................................................................... 31

4.2 INVESTIGATION OF THE EFFECT OF LOW-FLUID SHEAR ON ADHERENT-INVASIVE

ESCHERICHIA COLI ........................................................................................................................... 33

4.3 INVESTIGATION OF THE EFFECT OF LOW-FLUID SHEAR ON COMPLEX M ICROBIAL

COMMUNITY .................................................................................................................................... 36

5 DISCUSSION AND CONCLUSION ........................................................................................ 43

5.1 INTRODUCTION .................................................................................................................... 43

5.2 RESULTS INTERPRETATION ................................................................................................ 44

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5.2.1 The effect of low-fluid shear on mucin adhesion and growth proliferation ...................... 44

5.2.2 The effect of low-fluid shear on the inactivation of L. reuteri in the presence of LA ...... 47

5.2.3 The effect of low-fluid shear on the primary metabolic activity production .................... 48

5.2.4 The effect of low-fluid shear on complex microbial community ...................................... 50

5.3 CONCLUSION ........................................................................................................................ 51

5.4 FUTURE EXPERIMENT ......................................................................................................... 52

REFERENCES .................................................................................................................................... 53

APPENDICES ...................................................................................................................................... A

APPENDIX 1. ...................................................................................................................................... A

APPENDIX 2. ...................................................................................................................................... A

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LIST OF ABBREVIATIONS AND UNITS

± Approximately 3-D 3-Dimensional 16S 16-Sequence AIEC Adherent-Invasive Escherichia coli strain LF82 APS Ammonium Persulphate C2H3O2SNa Sodium thio-glycolate CFU Colony Forming Unit DGGE Denaturing Gradient Gel Electrophoresis dyn Dyne EDTA Ethylenediaminetetraacetic acid EtBr Ethium Bromide GC Gas Chromatography GALT Gut- Associated Lymphoid h Hour IgA Immunoglobulin A K 2HPO4 Potassium Phosphate dibasic KH 2PO4 Potassium dihydrogen Phosphate L. reuteri Lactobacillus reuteri strain ATCC 6475 MM4-1a LabMET Laboratory of Microbiology Ecology and Technology of Ghent University LB Luria Bertani medium for growth LSS Low-Fluid Shear Stress MRS de man-Rogosa-Sharpe medium for growth N Number of replicates NASA National Aeronautics and Space Administration, United States Government NG Normal Gravity Shear Stress p Statistical p-value obtained PCR Polymerase Chain Reaction PVDF polyvinylidene difluoride membrane PVP 40 Poly Vinyl Pyrolidone q-PCR Real-time PCR rcf relative centrifugal force rpm Rotations per minute RWV Rotating Wall Vessel SCFAs Short-Chain Fatty Acids SDS Sodium Dodecyl Sulphate SHIME Simulator of the Human Intestinal Microbial Ecosystem® t time T Temperature TAE Tris-Acetate-EDTA TEMED 1-2-[di (dimethylamino) ethane] UV Ultra-Violet w/v weight/volume V Voltage

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LIST OF TABLES

Table 3-1 Different sampling condition of microbial community derived from M-SHIME proximal colon vessels ..................................................................................................................... 19

Table 3-2 Temperature and Time program for general primers 338F-GC and 518R for conventional PCR .................................................................................................................................. 24

Table 3-3 Standard Composition of Master Mix PCR for One Sample (25 µL) ............................... 25

Table 4-1 Plate counts of L. reuteri (mean ± stdev log CFU/mL) scored after 24 h, which are previously grown in a different media (MRS-broth and intestinal water) and exposed to LSS or NG for 1.5 h at 15 rpm. The start inoculum at t = 0 h was maintained at OD 610 nm ≈ 0.6. The control experiments were conducted without the addition of MAB. IW = intestinal water, MAB = mucin agar beads. ..................................................................... 28

Table 4-2 Acetate proportion (mean ± stdev in mg/L) in intestinal water medium after L. reuteri was subjected under LSS or NG condition for 1.5 h at 15 rpm. The start inoculum at t = 0 h was conditioned at OD 610 nm ≈ 0.6 ............................................................................ 30

Table 4-3 SCFAs production of L. reuteri (mean ± stdev in mg/L) in the medium containing IW+SF, after subjected under LSS or NG condition for 1.5 h and 5 h at 15 rpm. The start inoculum at 0 h was maintained at OD 610 nm ≈ 0.6. IW = intestinal water, SF = M-SHIME feed ...................................................................................................................... 32

Table 4-4 Lactate production of L. reuteri (mean ± stdev in mg/L) in the medium containing IW+SF, after subjected under LSS or NG condition for 1.5 h and 5 h at 15 rpm. The start inoculum at 0 h was maintained at OD 610 nm ≈ 0.6. IW = intestinal water, SF = M-SHIME feed ...................................................................................................................... 33

Table 4-5 SCFAs production of AIEC (mean ± stdev in mg/L) in the medium containing IW+SF, after subjected under LSS or NG condition for 1.5 h and 5 h at 15 rpm. The start inoculum at 0 h was maintained at OD 610 nm ≈ 0.7. IW = intestinal water, SF = M-SHIME feed ...................................................................................................................... 35

Table 4-6 Lactate production of AIEC (mean ± stdev in mg/L) in the medium containing IW+SF after subjected under LSS or NG condition for 1.5 h and 5 h at 15 rpm. The start inoculum at 0 h was maintained at OD 610 nm ≈ 0.7. IW = intestinal water, SF = M-SHIME feed ...................................................................................................................... 35

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LIST OF FIGURES

Figure 2-1 Variation in distribution and composition of human gut microbiota associated with age (Adapted from Sekirov et al., 2010) ................................................................................... 4

Figure 2-2 Variation in distribution and composition of the human gut microbiota. A) Longitudinal variation of microbial composition in density and diversity of the human gut. B) Latitudinal variation of microbial composition in density and diversity of the human gut (Modified from O’Hara and Shanahan, 2006; Sekirov et al., 2010) .................................. 5

Figure 2-3 Mechanism of diseases related to disturbances of mucus - associated gut Microbiota. A) Mechanism of diseases occurs due to impaired microvilli predisposed translocation of mucus-associated microbiota and pathogenic bacteria into systemic organs. B) Mechanism of diseases occurs due to a stress conditions enhanced by injury, infection, and high dense dietary food. These stresses inducer lead to changes in intestinal permeability and permit the translocation of mucus-associated microbiota and pathogenic bacteria into systemic organs (Modified from Sekirov et al., 2010) .................................. 9

Figure 2-4 The RWV vessel operating orientation to mimic A. LSS microgravity condition B. Normal gravity condition (adapted from Nickerson et al., 2003) .................................... 11

Figure 3-1 The RWV experiment was conducted in a horizontal position at 15 rpm speed to mimic the low-fluid shear condition. ........................................................................................... 15

Figure 3-2 The RWV experiment was conducted in a vertical position at 15 rpm speed to mimic the normal gravity condition. ................................................................................................. 16

Figure 3-3 Experimental design of an optimization of the growth medium for growth and mucin adhesion assay in which L. reuteri was subjected to LSS or NG for 1.5 h at 15 rpm, 37°C in different medium: MRS-broth and intestinal water. IW = intestinal water, MAB = mucin agar beads .............................................................................................................. 17

Figure 3-4 Experimental design of the investigation of the survival of L. reuteri after exposed to linoleic acid for 1.5h at 15 rpm, 37°C under LSS or NG in Intestinal water growth medium. IW = intestinal water, LA = linoleic acid .......................................................... 17

Figure 3-5 Experimental design of the investigation of the effect of LSS as compared to NG of beneficial bacteria L. reuteri and pathogen bacteria AIEC after 1.5 h and 5 h incubation at 15 rpm, 37°C in enriched-intestinal water. IW = intestinal water, SF = M-SHIME feed, MAB = mucin agar beads ........................................................................................ 18

Figure 3-6 Experimental design to investigate the effect of LSS as compared to NG on microbial community and was measured at different time point at 15 rpm, 37°C. MC = microbial community, SF = M-SHIME feed, APB = anaerobic phosphate buffer ........................... 19

Figure 3-7 Lactate standard Curve of dilution series of Lactate ranging from 2.5 mg/L to 1 g/L ...... 22

Figure 4-1 Biofilm-like formation of L. reuteri after incubated horizontally in the RWV for t20 at 15 rpm in MRS-broth medium .............................................................................................. 28

Figure 4-2 Histogram of mucin adhesion capacity (% of mean ± stdev CFU/mL) of L. reuteri to mucin-agar beads after t1.5 incubation at 15 rpm in LSS and NG condition in MRS-broth (left) and intestinal water (right). The start inoculum at 0 h was maintained at OD 610 nm ≈ 0.6. IW= intestinal water, MAB = mucin agar beads. Bars indicates the standard errors (n =3) ................................................................................................................................ 29

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Figure 4-3 Plate counts of L. reuteri (mean ± stdev log CFU/mL) scored after 24h in which L. reuteri in intestinal water medium were exposed to 10 µg/mL or 100 µg/mL linoleic acid under LSS or NG condition for 1.5 h at 15 rpm. The start inoculum at t = 0 h was conditioned at OD 610 nm ≈ 0.6. The control experiments were conducted without the addition of linoleic acid. IW = intestinal water, LA = linoleic acid ................................. 30

Figure 4-4 Histogram of (1) Mucin adhesion capacity (% of mean ± stdev CFU/mL) of L. reuteri to mucin-agar beads (2) Flow Cytometry counts of L. reuteri (mean ± stdev log CFU/mL) after t1.5 and t5 incubation time at 15 rpm in LSS and NG condition in the medium containing IW+SF. The start inoculum at 0 h was maintained at OD 610 nm ≈ 0.6. IW = intestinal water, SF = M-SHIME feed, Bars indicates the standard errors. Data represent the mean of three replicates (n = 3). ................................................................................. 31

Figure 4-5 Histogram of (1) Mucin adhesion capacity (% of mean ± stdev CFU/mL) of AIEC to mucin-agar beads (2) Flow Cytometry counts of AIEC (mean ± stdev log CFU/mL) in the medium containing IW+SF after subjected to LSS or NG condition for t1.5 and t5 at 15 rpm. The start inoculum at 0 h was maintained at OD 610 nm ≈ 0.7. IW = intestinal water, SF = M-SHIME feed, Bars indicates the standard errors. Data represent the mean of three replicates (n = 3). ................................................................................................ 34

Figure 4-6 Line Charts of (1) Flow Cytometry counts of microbial community (mean ± stdev log CFU/mL) after subjected to LSS or NG condition at 15 rpm for different time point t0 – t1.5 – t5 – t10 –t15 – t24. (2) SCFAs and Lactate production of microbial community (mean ± stdev in mg/L) after subjected to LSS or NG condition at 15 rpm for different time point t0 – t1.5 – t5 – t10 –t15 – t24. Data represent the mean of three replicates. Bars indicates the standard errors (n = 3). ........................................................................ 37

Figure 4-7 Line Charts of Flow Cytometry total bacterial counts of microbial community (mean ± stdev log CFU/mL) after subjected to LSS or NG condition at 15 rpm for different time point t0 – t1.5 – t5 – t8 from different sample condition (1) experiment 1, (2) experiment 2, (3) experiment 3, (4) average total bacterial counts of microbial community (mean ± stdev log CFU/mL) from 3 experiments. Data represent the mean of three replicates. Bars indicates the standard errors (n = 3). ................................................................................ 38

Figure 4-8 Line Charts of SCFAs production of microbial community (mean ± stdev in mg/L) after subjected to LSS or NG condition at 15 rpm for different time point t0 – t1.5 – t5 –t8 from different sample condition (1) experiment 1, (2) experiment 2, (3) experiment 3, (4) average SCFAs production of microbial community (mean ± stdev log CFU/mL) from 3 experiments. Data represent the mean of three replicates. Bars indicates the standard errors (n = 3). .................................................................................................................... 39

Figure 4-9 Line Charts of Lactate production of microbial community (mean ± stdev in mg/L) after subjected to LSS or NG condition at 15 rpm for different time point t0 – t1.5 – t5 –t8 from different sample condition (1) experiment 1, (2) experiment 2, (3) experiment 3, (4) average Lactate production of microbial community (mean ± stdev log CFU/ml) from 3 experiments. Data represent the mean of three replicates. Bars indicates the standard errors (n = 3). .................................................................................................................... 40

Figure 4-10 Bionumerics cluster analysis using Pearson correlation coefficients and UPGMA clustering algorithm (3.5% - 84.4%) of DGGE Ingeny 338-518 results of microbial community extracted DNA (16s rrna primer) after subjected to Normal Gravity experiment rotated for 8 h at 15 rpm from different sample condition namely (1)

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experiment 1, (2) experiment 2, (3) experiment 3. % = represent percentage of dendogram similarity of microbes lineages cluster. ......................................................... 41

Figure 4-11 Bionumerics cluster analysis using Pearson correlation coefficients and UPGMA clustering algorithm (3.5% - 84.4%) of DGGE Ingeny 338-518 results of microbial community extracted DNA (16s rrna primer) after subjected to Low- fluid Shear experiment rotated for 8 h at 15 rpm from different sample condition namely (1) experiment 1, (2) experiment 2, (3) experiment 3. % = represent percentage of dendogram similarity of microbes lineages cluster. ......................................................... 42

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LIST OF EQUATIONS

Equation 1 Formulation for calculation shear stress in the rotating wall vessel ................................. 12

Equation 2 Formulation for calculation of terminal velocity in the rotating wall vessel .................... 12

Equation 3 Calculation for CFU/mL in inoculum and lumen ............................................................. 20

Equation 4 Calculation for CFU/mL in mucin .................................................................................... 21

Equation 5 Calculation for % mucin adhesion .................................................................................... 21

Equation 6 Calculation for internal standard Gas Chromatography analysis ...................................... 22

Equation 7 Lactate standard calculation for the analyte that was started from solid chemicals and further dissolved in milliq-H2O: ....................................................................................... 22

Equation 8 Lactate standard calculation for the analyte that was started from liquid solution and further back-diluted in milliq- H2O: ................................................................................. 22

1

1 Introduction

The human body has long been known as a host to a various microbial life. These microbes, generally termed as “human-associated microbiota” or the “microbiome” closely associates with the human tissue (Robinson et al., 2010). The microbial community that inhabits the human body has been estimated to contain 1014 bacterial cells. Most of the microbiota reside within the gastrointestinal tract, the colon itself is estimated to be colonized by more than 70% of all the microbes in the human body and outnumber human cells by 10-fold (Gerritsen et al., 2011; Sekirov et al., 2010; Ley et al., 2006; Dethlefsen et al., 2006; Whitman et al., 1998; Savage, 1977).

In recent years, a vast number of studies of gut microbiota have increasingly revealed the role of gut microbiota for human health; yet many questions remain unanswered. This is due to differences in bacterial species composition of the gut microbiota, which significantly changes and varies among individuals (Gerritsen et al., 2011; Zoetendal et al., 1998). The composition itself can undergo rapid changes due to variation in dietary habit, life style, hygiene, and antibiotics (Sommer and Backhed, 2013), the capacity to compete for the nutrients, and the ability to adhere on the food particles or on the colonic mucosa (Suskovic et al., 2001). The latter has been proposed to contribute to the colonization of the mucus layer and shape the mucus-associated microbiota (De Weirdt et al., 2013; Schreiber, 2010; Zoetendal et al., 2002).

Furthermore, evidence suggests that the microbes are able to sense and adapt to several micro-environment factors. In particular, cells associated with the gut epithelium exhibit changes in development, number, physiology and gene expression under low-fluid shear exposure, a specific reologic condition that prevails near the gut epithelium (Foster et al., 2013). Comparable to changing oxygen gradients over the gut epithelium, also low-fluid shear can create changes in the microbial gene expression and mucosal behavior (Foster et al., 2013; Arunasri et al., 2013, Marteyn et al., 2011, Vukanti et al., 2008; Nickerson et al., 2000; Nickerson et al., 2003; Nickerson et al., 2004). Properties that can be affected by low-fluid shear are growth rates in liquid cultures (Foster et al., 2013; Klaus et al., 1997) and adherence properties to mucosal and epithelial surfaces (Thomas et al., 2002; Nickerson et al., 2003). Additionally, some pathogenic microbes also display an increase in virulence, resistance to environmental stress, and higher numbers of survival in the host which have been correlated with changes in gene expression (Foster et al., 2013; Nickerson et al., 2004; Wilson et al., 2002a; Nickerson et al., 2000). Together, the result of previous studies demonstrate that low-fluid stress environment is more favourable for growth (Nickerson et al., 2003). However, it must be noted that the majority of the studies conducted to comprehend the effects of microgravity specifically in low-fluid shear environment has only focused on pathogenic microbes. While information about the effects of low-fluid shear on the beneficial gut microbiota are not known, the subsequent impact on host physiology still needs to be explored.

Most of the research done to investigate the effects of microgravity on host cell physiology has relied on model systems, where epithelial cells are grown under conventional 2-D conditions. This conventional approach has had a big contribution to understanding the role of microbiota in the process of infectious diseases, its impact on host immunity and the host response to infections. But, a drawback for such model is that several parameters of the in vivo environment are still lacking and are not mimicked enough. Hence, it’s not entirely predictive for the in vivo tissue response. A reason for this is because of the lack of complexity, in vitro cell differentiation becomes an issue, as well as mechanical damage due to fluid-shear and turbulence (Barrila et al., 2010; Hammond and Hammond,

2

2001). Thus, to minimize the mechanical damages and for bridging the gaps, 3-D suspension cultures using a rotating wall vessel bioreactor have been used (Barrila et al., 2010; Hammond and Hammond, 2001).

The principle of growing cells in rotating vall vessel (RWV) bioreactor is based on the fact that organs and tissues function in a 3-D environment. This optimized model of suspension culture is used to produce laminar flow for growing cells, yet enabling maintenance of several functions of in vivo tissues and minimize the mechanical damages in the cultures (Barrila et al., 2010; Hammond and Hammond, 2001). The low-fluid shear from the RWV provides a growth environment, which is similar to those encountered in the placenta and other fluid shear areas of the body such as between brush border microvilli of the epithelial cells (Guo et al., 2000; Nauman et al., 2006).

The objective of such RWV studies is to have a better view on intestinal microbial processes in vitro to investigate the effect of low-fluid shear on the gut bacteria and the impact on the interaction with host cells. This master dissertation will study the microbial side of this model. In order to know the significant effect of low-fluid shear on the growth, adhesion capacity to the mucin agar, and metabolism of gut bacteria, a well-designed mechanistic in vitro study using RWV bioreactor was performed.

Recently, there has been an increasing interest in the consumption of probiotics and functional foods in Western diets (o’sullivan, 1996) and probiotic bacteria are known to be able to suppress pathogenic bacteria in the gastrointestinal tract and enhance the population of beneficial microbes (Yaeshima et al., 1997). In this study we investigated the effect of low-fluid shear on beneficial bacteria and potentially probiotic Lactobacillus reuteri as a model organism that has been shown to protect epithelial cells against invasion of entero-pathogens (De Weirdt et al., 2012). Lactobacillus reuteri has been classified as one of the mucus-associated microbiota inhabitant that is strongly adhering to the mucosal surfaces via mucus binding protein, mubs (Mackenzie et al., 2010). Secondly, we investigated the effect of low-fluid shear on Adherent Invasive Escherichia coli (AIEC), which is known to adhere and invade intestinal epithelial cells and which has been brought in relationship with the etiology of in Crohn disease (Keita and Soderholm, 2012). Finally, to get a better view of the effect of low-fluid shear on gut bacteria, we performed experiments using the simulated colon suspension derived from a dynamic gut model called SHIME.

3

2 Literature Review

2.1 Microbiota in the Gut

2.1.1 The Gut Microbiota

The gut microbiota can be described as a diverse microbial community that is composed mainly of bacteria but also includes archaea, viruses, fungi and protozoa (Sommer and Backhed, 2013).

The gut microbiota contains various bacterial species, which significantly change with age and considerably vary among individuals (Gerritsen et al., 2011; Zoetendal et al., 1998). The composition of microbiota consists of resident microbial members and those microbes, which are introduced due to regular intake of particular foods (Gerritsen et al., 2011). The composition itself can undergo rapid changes due to variation in dietary habit, lifestyle, hygiene, and antibiotics (Fig. 2-1) (Sommer and Backhed, 2013; Sekirov et al., 2010) and is mostly determined by the capacity to compete for limiting nutrients and possibly for adhesion sites on food particles or on the colonic mucosa (Sekirov et al., 2010; Suskovic et al., 2001). Moreover, the fact that each site of the gut is characterized by its own physiological and physicochemical parameters, such as intestinal motility, ph, redox potential, diverse concentrations of oxygen, nutrient supplies, and the host secretions (including HCl, digestive enzymes, and mucus), has driven a selective pressure in the variety of the gut microbiota composition (Gerritsen et al., 2011; Marteyn et al., 2011; Booijink et al., 2007).

The colonization of microbes in the gut takes place immediately after birth upon mother’s passage and the diversity increases henceforward (Fig. 2-1) (Sekirov et al., 2010; Redondo-Lopez, 1990). During the first year of life, the gut microbiota composition undergoes fluctuations due to decreasing oxygen concentrations concomitant to increases of the age. Hence, it allows a successive colonization by anaerobic microbes such as members of the genus Bacteroides and members of the phylum Actinobacteria and Firmicutes (Sommer and Backhed, 2013) and also includes all major pathogens of the lower part of human gut (Marteyn et al., 2011).

The primary colonizers of the newborn infants gut are facultative anaerobic bacteria such as proteobacteria; these are presumed to be involved in shaping the composition of the adult gut microbiota (Sommer and Backhed, 2013; Sekirov et al., 2010). The gut microbiota composition stabilizes and resembles the ‘adult state’ when the infant reaches 1–2 years of age (Sommer and Backhed, 2013; Sekirov et al., 2010). In contrast, during adulthood the gut microbiota exhibits minor changes and this is marked by decreases in the Bifidobacterial population compared to that of the infant gut microbiome (Robinson et al., 2010). In addition to being modulated by the way of delivery (vaginal or C-section) the gut microbiota composition is also influenced by dietary factors and host genetics. However, the effect of host genetic on the gut microbiota composition is most likely indirect through host metabolisms (Sekirov et al., 2010).

Figure 2-1 Variation in distribution and composition of human gut microbiota with age (Adapted from Sekirov

The majority of ‘normal’ gut microbiota is composed phyla of Bacteroidetes and Firmicutes100 - 1000 folds (Sommer and Backhed, 2013Mariat et al., 2009; Savage, 1977phyla of Proteobacteria, Verrucomicrobia, Actinobacteria, Fusobacteria(Sommer and Backhed, 2013; Sekirov2005). Over the length of the gastrointestinal tract, tsmall intestine is enriched with with Bacteroidetes and the Lachnospiraceae al., 2007). The gut microbiota is not homogeneous gradients. First, the microbial density increases from the proximal to the distal gut (duodenum contains 101 to 103 bacteria per gramileum and increasing to 1011 to 10Sekirov et al., 2010; O’Hara and Shanahansame axis as microbial density along the mucus layer and a large number (Sekirov et al., 2010). The intestinalwith the ratios of anaerobes to aerobes being lower at mucosal surfaces as compared with the lumen or feces (Gerritsen et al., 2011; of the gut microbiota reside inProteobacteria, Clostridium, Lactobacillus, have been found to adhere and reside within the mucus layer close to the Backhed, 2013; Sekirov et al., 2010range of biochemical and metabolic activities to complement provides protection against pathogand Backhed, 2013).

Variation in distribution and composition of human gut microbiota Sekirov et al., 2010)

‘normal’ gut microbiota is composed of 90% of anaerobic bacteria specificallFirmicutes, which outnumber aerobic and facultative anaerobic bacteria by and Backhed, 2013; Sekirov et al., 2010; Hooper and Macpherson, 2010

Savage, 1977). Other phyla, which are present to a minor Proteobacteria, Verrucomicrobia, Actinobacteria, Fusobacteria, and

Sekirov et al., 2010; Hooper and Macpherson, 2010e gastrointestinal tract, the composition of microbiota

with the Bacilli class of the Firmicutes, while the colon Lachnospiraceae family of the Firmicutes (Sekirov, et al

gut microbiota is not homogeneous and their distribution can be distinguised microbial density increases from the proximal to the distal gut (

bacteria per gram, 104 to 107 bacteria per gram in the jejto 1012 cells/ gram in the colon (Fig. 2-2A) (Sommer

O’Hara and Shanahan, 2006). Second, the bacterial diversity increalong the mucus layer–lumen axis (with a few bacteria adher

a large number inhabit the lumen) (Fig. 2-2B) (Sommer and Backhed, 2013he intestinal lumen microbiota is significantly different from the mucus layer

with the ratios of anaerobes to aerobes being lower at mucosal surfaces as compared with the lumen ; Sekirov et al., 2010; Swidsinski et al., 2005; Shanahan, 2004

gut microbiota reside in the lumen, whereas fewer microbes includingLactobacillus, and Enterococcus and also Akkermansia muciniphila

adhere and reside within the mucus layer close to the epithelium , 2010; Swidsinski et al., 2005). This difference provides

range of biochemical and metabolic activities to complement to the host physiologyprotection against pathogens and play a key role in maintaining tissue homeosta

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Variation in distribution and composition of human gut microbiota associated

anaerobic bacteria specifically by outnumber aerobic and facultative anaerobic bacteria by

Hooper and Macpherson, 2010; minor extent belong to the

, and Cyanobacteria Hooper and Macpherson, 2010; Eckburg et al.,

of microbiota also differs. The colon is more enriched

et al., 2010; Frank et distribution can be distinguised into two

microbial density increases from the proximal to the distal gut (the stomach and bacteria per gram in the jejunum and

(Sommer and Backhed, 2013; bacterial diversity increases in the

few bacteria adhering the and Backhed, 2013;

significantly different from the mucus layer with the ratios of anaerobes to aerobes being lower at mucosal surfaces as compared with the lumen

Shanahan, 2004). Most ing some members of

Akkermansia muciniphila helium (Sommer and

is difference provides a diverse physiology. Besides, it is also

ens and play a key role in maintaining tissue homeostasis (Sommer

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Figure 2-2 Variation in distribution and composition of the human gut microbiota. A) Longitudinal variation of microbial composition in density and diversity of the human gut. B) Latitudinal variation of microbial composition in d ensity and diversity of the human gut (Modified from O’Hara and Shanahan, 2006; Sekirov et al., 2010)

2.1.2 The Mucus – Associated Microbiota

One of the largest interfaces in human gut in which the host–microbes interactions primarily occur is the gut mucosa (O’Hara and Shanahan, 2006). The gut mucosa is the first line that provides a protective barrier against the pathogens (Navabi et al., 2013) as well as against harmful agents from the lumen, destructive enzymes, and luminal microbiota (Atuma et al., 2001). It also helps to maintain the concentrations of secreted iga and antimicrobial peptides on the surface of the epithelium enabling the host to avert direct microbial contact with the underlying epithelium (Van den Abbeele et al., 2011). At the same time, it promotes attachment sites for bacterial adhesion and provides an essential environment for establishment of gut microbiota in the colon (Atuma et al., 2001).

The gut mucosa is a thick gel-like layer that extends, depending on the gut site, from 150 μm to 1 mm from the surface of intestinal epithelial cells (Hooper and Macpherson, 2010; Johansson et al., 2008). Study by Atuma et al. (2001) revealed that the gut mucosa was translucent, continuous, and can be separated into two layers: a loosely adherent gel and an underlying solid adherent gel which remains attached to the mucosa. Based on the attachment site of the gut microbiota, the gut mucosa can also be divided into two layers: the inner layer is devoid of bacteria and the outer layer is inhabited by members of gut microbiota (Navabi et al., 2013; Sekirov et al., 2010; Johansson et al., 2008).

The outer part of mucus layer represents a selective habitat of microbiota and express specific microbial community characterized through microbial adhesion (strong mucus binding capacity), ability to compete for nutrients and utilize mucin glycan, as well as resistance to host defence molecules (Sommer and Backhed, 2013, Vignaes et al., 2013; Van den Abbeele et al., 2011). The specific microbial community that is found to colonize the mucus layer is typically termed as mucus-associated microbiota (Hooper and Macpherson, 2010). As previously described, the adhesion capacity had shaped the composition of mucus-associated microbiota in the gut and differentiate from

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the luminal microbiota (i.e the strong adhesion capacity of Lactobacillus sp to the mucus layer) (De Weirdt et al., 2013; Van den Abbeele et al., 2011; Schreiber, 2010; Zoetendal et al., 2002).

Due to closer contact to the epithelial cells, the mucus- associated microbiota has been proposed to have a better entanglement with the epithelial and immune cells rather than luminal microbiota. Furthermore, they might be able to prevent invasion of pathogens to the epithelium by secreting antimicrobial compounds or via their adhesion properties (Vignaes et al., 2013; Van den Abbeele et al., 2011). Hence, disruption of this mucosal microbial community is believed to lead to dysregulation of the immune responses, given an example observed from the recent study in ulcerative colitis patients (Vignaes et al., 2013). The results showed significant lower proportion of Lactobacillus sp and Bifidobacterium sp residing in the mucus layer as compared to the lumen, in contrast to healthy microbiota (Vignaes et al., 2013).

2.1.3 Health Aspect of Host – Microbes interaction in the Gut

The gut microbiota is an essential component of human health and diseases. The symbiotic relationships between Host – microbes in the gut can be described as ‘Homeostasis’, in which the presence of diverse commensal microbiota in the gut has been contributed beneficially in several host metabolism and maintenance of the host intestinal immune system as well as affect the host intestinal epithelium development and physiology (Sommer and Backhed, 2013; Hooper and Macpherson, 2010). While, in return they occupied a protected nutrient-rich environment (Hooper and Macpherson, 2010). However, in spite of the symbiotic relationship of the host – microbe’s interaction, the dynamic fluctuation of the gut microbiota and the presence of invading pathogens also pose serious health challenges. This constant threat is further sharpened by the sheer number of microbial load and their close contact to a single-cell epithelial layer and large intestinal surface area (± 200 m2 in humans) (Sommer and Backhed, 2013; Hooper and Macpherson, 2010).

2.1.3.1 Function of Gut Microbiota

The human gut harbors a complex microbial community which has essential roles in human health and physiology. Amongst these roles, the primary function of the gut microbiota is to enhance the host digestive metabolism. For instance, by facilitating the degradation of dietary fiber to short chain fatty acids, synthesize essential vitamins and amino acids, and modulates the uptake and deposition of dietary lipids (Sommer and Backhed, 2013; Hooper and Macpherson, 2010; Martens et al., 2008, Backhed et al., 2004).

The human digestive system has been known to lack enzymes to degrade the dietary fibers (Hooper and Macpherson, 2010; Martens et al., 2008). This lack of enzymes was complemented by a complex and dynamic anaerobic microbiota in the colon, which harbours a diversity of saccharolytic enzymes and assist the fermentation process (Hooper and Macpherson, 2010). Therefore, in the colon, the dietary fibers are fermented to metabolites end-products of which the short-chain fatty acids (SCFAs) are the major group (den Besten et al., 2013; Roy et al., 2006). SCFAs have been shown to yield beneficial effects in host energy metabolism and play an important role in the prevention and treatment of the metabolic syndrome, bowel disorders, and certain types of cancer. Moreover, some of the SCFAs such as butyrate are engaged in the prevention of potentially toxic metabolic end-products (Sekirov et al., 2010; Duncan et al., 2004; Bourriaud et al., 2002). At the level of the gut microbiota, dietary fibers are important for bacterial growth and the SCFAs required to balance the end-product metabolites in the anaerobic environment of the gut by inducing the production of antimicrobial peptides (den Besten et al., 2013).

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The second function of gut microbiota is to maintain the host intestinal immune system as a deterrent to pathogen colonization by means of a barrier to pathogens via competitive exclusion, such as occupation of attachment sites, consumption of nutrient sources, and stimulation of various antimicrobial substances (Sekirov et al., 2010; Hooper and Macpherson, 2010; Sanz et al., 2007).

Given the fact that the gut mucosal surface represents the surface area where the microbes attach to and account for the formation of antigens that trigger the intestinal immune response, the gut microbiota plays an important role in the development of the intestinal immune system, specifically along the mucus layer (Sekirov et al., 2010). The gut microbiota is intricately involved in two conflicting functions of the mucosal immune system. On the one hand, the immune system has to be tolerant towards the overlying microbiota to prevent excessive induction and detrimental systemic immune response. At the same time, it has to be able to respond to invading pathogens and control overgrowth of gut microbiota as well as their translocation to systemic sites (Sekirov et al., 2010; Hooper and Macpherson, 2010). These adaptations by mucosal immune system include effective mechanisms that limit the contact of gut microbiota to the epithelial cells surface and their exposure to the systemic immune system (Hooper and Macpherson, 2010).

Previous studies have revealed that exposure to the structural parts of gut microbiota is enough to drive host immune maturation both locally and systemically, at the molecular, cellular, and organ levels respectively (Sekirov et al., 2010; Mazmanian et al., 2005). Control towards the gut microbiota is carried out by the mucosal immune system. This is achieved by improving physical barrier integrity through the production of mucus, antigens secretory iga and antimicrobial peptides (Sekirov et al., 2010; Hooper and Macpherson, 2010; Tsuji et al., 2008; Meyert-Hoffert et al., 2007; Machperson and Uhr, 2004).

Mucus production generates a diffusion barrier that concentrates the antimicrobial peptides and restricts the contact of luminal microbiota with epithelium (Hooper and Macpherson, 2010). The secreted iga allowing the control of gut microbiota growth and restricts their penetration across the epithelium by coating the gut microbiota at the intestinal mucosa (Sekirov et al., 2010; Machperson and Uhr, 2004; Tsuji et al., 2008; Peterson et al., 2007). Concurrently, the presence of various bacteria species and the end-products of metabolism induces the production of different antimicrobial peptides (Sekirov et al., 2010). These antimicrobial peptides strengthen the host protection against pathogen invasion and overgrowth of the gut microbiota through enzymatic attack of bacterial cell walls that further help to eliminate the gut microbiota from breaching the epithelium (Sekirov et al., 2010; Hooper and Macpherson, 2010). The optimum antimicrobial activity was observed in the intestinal crypts and in the mucus layer overlying mucosa (Sekirov et al., 2010; Meyert-Hoffert et al., 2007). Reduced antimicrobial activity in the lumen allows the gut microbiota growth with limited contact to the host epithelium (Sekirov et al., 2010).

The third function of the gut microbiota is contribution to the development and maturation of the intestinal epithelium (Sekirov et al., 2010; Wagner et al., 2008; Salminen and Isolauri, 2006). It is well documented that in newborns, the structure and functionality of the gut is still immature, and the maturation process is partially stimulated by the initial gut microbiota (Sommer and Backhed, 2013). Sekirov et al. (2010) demonstrated that in order for the gut to reach maturity, the gut needs to maintain its homeostasis and should be able to regenerate after injury by developing an efficient peristaltic motility as well as sufficient surface area for attachment sites and blood supply for nutrient acquisition. The gut microbiota itself accompanies these functions by getting involved in the maintenance of intestinal epithelium barrier integrity through maintenance of cell-to-cell junctions and supports the intestinal epithelium healing after injury (Sekirov et al., 2010). Furthermore, a

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review by Sommer and Backhed (2013) summarized the role of gut microbiota in several aspects on host physiology processes. The gut microbiota has been demonstrated to modulate gut-associated lymphoid (GALT) maturation, brush border differentiation and tissue regeneration (microvilli), and peristaltic motility. The gut microbiota also contributes in vascularization process surrounding the gut and reduces the permeability of the epithelial cells lining the gut. For instance, various probiotic strains of Lactobacillus sp have shown protection against pathogen assault or intestinal injury by contributing in the maintenance of tight junctions of intestinal epithelia (Sommer and Backhed, 2013; Sekirov et al., 2010; Lutgendorff et al., 2008).

2.1.3.2 Diseases Related to Disturbances of Mucus - Associated Gut Microbiota

In contrast to a healthy gut microbiota that appears to promote the host growth and development, an overgrowth or reduction can generate several detrimental conditions and adversely affect the functionality of the gut. As the gut microbiota is the key of mucosal homeostasis, there are consequences that dysregulation of gut mucosa homeostasis tend to induce an excessive host immune system and predispose a multitude intestinal diseases, such as inflammatory bowel disease (Sekirov et al., 2010; Honda and Takeda, 2009; Sartor, 2008).

The dysregulation of gut mucosa homeostasis can occur by two mechanisms. The first mechanism is due to an ‘internal’ factor such as impaired microvilli function. This in turn leads to a loss of barrier integrity. These predispose the gut microbiota to migrate beyond their tightly regulated borders to systemic organs. Which in turn, promote an excessive host immune system and subsequently more diseases (Fig. 2-3A) (Sekirov et al., 2010; Othman et al., 2008). The second mechanism is due to ‘external’ factors such as infection, injury, or unhealthy diet. It also leads to changes in intestinal permeability that permit translocation of gut microbiota or pathogens to systemic sites and further promotes host immune system to aggravate the diseases onset (Fig. 2-3B) (Sekirov et al., 2010).

Most of the intestinal diseases caused by bacterial pathogens occur through secondary mechanisms. Colonization of the intestinal mucosa by bacterial enteric pathogens induces a strong inflammatory response aimed to counteract the invading pathogens. However, this protective mechanism response has also shown counterintuitive effects leading to a decrease in the viability of mucosal microbiota, particularly anaerobic. Hence, induces alteration in their compositions and further allows the pathogens to penetrate directly through mucosal microbiota overlying the gut mucosa. Furthermore, these pathogens are succeed in competing with commensal microbes and occupies the vacated niches (Sekirov et al., 2010; Sekirov and Finlay, 2009; Pedron and Sansonetti, 2008; Srikanth and McCormick, 2008; Stecher and Hardt, 2008b). For instance, a number of pathogens from the Enterobacteriaceae family, such as pathogenic Escherichia coli and Salmonella enterica serovar Typhimurium, have been described to reduce the total numbers of gut microbiota, mainly anaerobic bacteria through inflammation-mediated processes. At the same time, inflammations at the intestinal mucosa likewise drive an overgrowth of Enterobacteriaceae (Sekirov et al., 2010; Lupp et al., 2007; Stecher et al., 2007) by better utilization of nutrients in the inflamed intestines as compared to the gut microbiota (Sekirov et al., 2010; Stecher et al., 2008a). Another study done by Stecher et al. (2008a) indicates that Salmonella enterica serovar Typhimurium taking benefits from mucins released during inflammation. Additionally, previous study in patients with Crohn’s diseases highlight that a disturbed mucosal barrier function is an important factor in pathogenesis. Besides, it also exhibits an increase in the number of AIEC in the mucosal layer and the concentration significantly increases with the severity of the disease (Keita and Soderholm, 2012).

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Figure 2-3 Mechanism of diseases related to disturbances of mucus - associated gut Microbiota. A) Mechanism of diseases occurs due to impaired microvilli predisposed translocation of mucus-associated microbiota and pathogenic bacteria into systemic organs. B) Mechanism of diseases occurs due to a stress conditions enhanced by injury, infection, and high dense dietary food. These stresses inducer lead to changes in intestinal permeability and permit the translocation of mucus-associated microbiota and pathogenic bacteria into systemic organs (Modified from Sekirov et al., 2010)

2.2 Shear Stress in the Gut

2.2.1 Definition of Fluid-Shear Stress

Fluid shear stress can be defined as distribution of frictional forces due to hydrodynamic flow against the surface of the cells (Mammoto and Ingber, 2010; Papaioannou and Stefanadis, 2005). At the level of host cells, several studies indicate that these biomechanical forces are involved in cell differentiation and development in mammals (Barilla et al., 2010) as well as inducing changes in cell metabolism and function (Hammond and Hammond, 2001).

The effects of fluid shear stress on the activity of endothelial cells are well documented. The fluid shear stress generated by blood flow on the inner layer of vascular endothelial cells are found to be critical in the maintainance of the normal cell structure and fuction. Besides, this fluid shear stress is also found to be involved in the regulation of certain protein activity and modulation of gene expression (Avvisato et al., 2007, Papaioannou and Stefanadis, 2005; Hammond and Hammond, 2001). Likewise, in spite of vast differences in the function, the underlying epithelium in each tissues are also exposed to shear stress due to the movement of gut contents (Polacheck et al., 2013; Avvisato et al., 2007; Hammond and Hammond, 2001).

2.2.2 Peristaltic Movement In the Gut

Epithelial cells of the gut are continuously subjected to a myriad of mechanical forces including peristalsis and shear forces as an impact of gut contents movement, luminal pressure gradients, and the movement along the crypt-villus unit during normal gut motility (Gayer and Basson, 2009; Avvisato et al., 2007; Jeffrey et al., 2003). These forces lead to several changes in the biology of intestinal epithelial cells and the responses is vary depending on the cells interaction, with various

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effects on proliferation (cell growth and survival), differentiation, and functionality (Gayer and Basson, 2009; Avvisato et al., 2007).

As described previously, peristaltic movement is one of the essential factors which sustain the normal function of the gut. Peristalsis in the gut is defined as a slow wave-like movements pattern which entangle partial or total occlusion of the lumen towards rectal direction (Huizinga and Lammers, 2009) due to coordinated contractions and relaxations of circular and longitudinal smooth muscle layers (Gayer and Basson, 2009). This slow wave is actively dispersed to the gut cell walls and create a force to the cell walls to oscillate at a same frequency (Huizinga and Lammers, 2009).

2.2.3 Gradient of fluid-Shear Stress In the Gut

During normal gut function, within the colon exists a wide range of micro environments in attendance due to the luminal flow rates, variations in the viscosity of the mucus layer, interactions with epithelial surfaces, and constant changes in the levels of nutrients (Macfarlane and Dillon, 2007). The mucus layer covering the epithelial cell are also exposed to forces due to pressure and shear stress from interaction with luminal content, cyclic strain associated with villous motility rhythmically at the mucosal level, and further deformation induced by repeated peristaltic muscular contraction and relaxation within the gut epithelial wall (Gayer and Basson, 2009).

The interaction between luminal contents and the contracting muscle of the epithelial layers result in mucosal compression in which the mucosa squeezed in between (Gayer and Basson, 2009, Alizadeh et al., 1989). Thus, leading to further physical contact with the opposing mucosa during the contraction and generating shear stress, compression, or other forces (Gayer and Basson, 2009). On the other hand, rhythmic contraction of the intestinal villi within the mucosa also result in a gradient of shear stress which is varied in magnitude and a frequency of distribution gradient that decreases progressively from duodenum to ileum or depends on the specific site in the gut (Gayer and Basson, 2009).

The flow of a bolus through the center of the lumen creates the highest fluid-shear that must be traversed by the microbes prior to colonization (Pearson and Brownlee, 2010). Thereafter, the successfull colonizer encounters the intestinal epithelial cells in which the level of fluid shear decreases with increasing proximity to the intestinal walls (Guo et al., 2000; Pearson and Brownlee, 2010). The presence of microvilli in the epithelial cell walls reduced the fluid shear from 1 – 5 dynes/ cm2 to less than 1 dyne/cm2 (Guo et al., 2000). Moreover, the viscoelastic properties of the mucus layer further reduces the fluid shear and provides protection for living cells within the mucus from high-fluid shear (Atuma et al., 2001).

2.2.4 Pathogenic Behaviour in the Absence of Low-fluid Shear Stress

Microbes have the ability to sense and adapt to the environmental changes and constantly grow in various environment conditions. There is a lot of evidence that during the onset of infection, pathogenic bacteria encounter wide fluctuations of fluid shear micro-environment, which is ranging from 4 to 50 dynes/cm2 along blood vessel walls to less than 1 dyne/cm2 in uterus and between the brush border microvilli of epithelial cells (Nauman et al., 2007; Guo et al., 2000). The latter provide low-fluid shear conditions, which are favorable by most of the enteric pathogens such as pathogenic bacteria Salmonella enterica serovar Typhimurium (Nauman et al., 2007). Several studies conducted in pathogenic bacteria have shown to increase virulence, stress resistance, change gene expression and obtain higher numbers of survival under low-fluid shear culture

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environment as compared to increased-fluid shear (Nickerson et al., 2000; Wilson et al., 2002a; Wilson et al., 2002b; Nickerson et al., 2003). These can be explained by the fact that microbes are able to respond to environment changes including mechanical stimuli and undergo alteration of adherence properties in response to modulated shear stress (Nickerson et al., 2003). Furthermore, numerous studies have indicated that these changing in shear stress conditions also modulate the expression of genes related to starvation response, acid stress, osmotic stress, oxidative stress, bio-film formation, and lipid biosynthesis (Arunasri et al., 2013; Vukanti et al., 2008; Nickerson et al., 2000). Yet, it also reveals that the impacts are limited to certain stress resistance and end-product metabolisms (Nickerson et al., 2003). However, in the absence of low-fluid shear micro-environment, it was clearly observed that the pathogenic bacteria are most likely to demonstrate decreases in survival rate rather than in low-fluid shear environment (Nauman et al., 2007).

2.2.5 Rotating Wall Vessel as an in vitro Model to Study Low-fluid Shear Stress

The rotating wall vessel bioreactor (RWV) (size 55 mL) from Synthecon Inc. Is a rotating bioreactor

developed by NASA and designed to mimic microgravity state (weightlessness), in which cells are maintained in suspension with constant free fall gravity. These micro-gravity conditions also produce a sustained low-fluid shear (less than 1 dyne/cm2) (Nauman et al., 2007; Nickerson et al., 2004; Hammond and Hammond, 2001).

In line with the assumption of microbes are behaving in almost the same manner as spherical particles, their size and density would prefer a minimal shear. Thus, It was further assumed that low-fluid shear is a result of a combination of a reological and gravitational vector (Nickerson et al., 2003). This condition is provided by the RWV: hydrodynamic forces offset the gravitational movement of the culture enabling the microbes to be suspended at a constant terminal velocity. This further provides a ‘laminar flow’condition with minimum shears and low turbulences within the vessel based upon stokes law for a flow around spherical objects (Nauman et al., 2007; Hammond & Hammond, 2001; Gao et al., 1997). Hence, the growth environment achieved through optimized suspension culture in the RWV serves low-fluid shear growth motions relevant to those encountered in particular low-fluid shear areas of the host such as between the brush border microvilli of epithelial cells (Nickerson et al., 2003). Moreover, low-fluid shear/ low turbulence in the RWV has shown some advantage over either dynamic or static cultures, The RWV enable cells to aggregate, grow in a 3-D and differentiate. Besides, it also provides an adequate nutrition and oxygenation in a homogenized way. At the same time it prevents mechanical cell damage (Nickerson et al., 2003). Moreover, besides of being used to grow bacteria in a low-fluid shear manner (against the gravitational vector), the RWV can also be used to mimic the normal gravity condition by changing the position of the RWV vessel alligned with the gravitational vector (Fig. 2-4) (Nickerson et al., 2003).

Figure 2-4 The RWV vessel operating orientation to mimic A. LSS microgravity condition B. Normal gravity condition (adapted from Nickerson et al., 2003)

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In order to minimize the mechanical damage and optimized differentiation of the cells culture, the suspension culture must experience a solid body rotation flow and zero head space. Therefore, there are two basic principal design of the RWV needs to be fulfilled: (1) based upon a solid body rotation of culture medium within a cylinder vessel around horizontal axis (zero headspace between atmosphere and culture medium) yields in low-fluid shear and randomization of gravitational vector; (2) an optimal diffusion of dissolved gasses inside the vessel which is obtained by hydrophobic membrane in the core (i.e. the vessel completely filled with the medium devoid gas bubbles) and which allows constant gas exchange during growth or oxygenation by diffusion (Nauman et al., 2007; Nickerson et al., 2003; Hammond and Hammond, 2001; Unsworth and Lelkes, 1998; Gao et al., 1997, Tsao et al., 1994).

Shear stress in the rotating wall vessel suspension culture can be defined as the function of terminal velocity and fluid viscosity over the radius of the particle (Eq. 1) (Hammond and Hammond, 2001; Gao et al., 1997). At which, the terminal velocity is determined by gravity, radius of particle, differences in density between culture particle and culture medium, as well as fluid viscosity (Eq. 2) (Hammond and Hammond, 2001).

Equation 1 Formulation for calculation shear stress in the rotating wall vessel

���� = ��

Equation 2 Formulation for calculation of terminal velocity in the rotating wall vessel

= �������– ������μ���

Where, Tmax is the maximum shear stress, Vs is the terminal velocity, g is gravity, r is the radius of the particle, ρr is the density of the culture particles, ρf is the density of culture medium (fluid), ρr - ρf is the difference in density between culture particles and medium, and µ is the viscosity of cell culture medium.

2.3 Summary and Objectives

Given the above information, it is of particular interest to conduct a study to evaluate the effect of low-fluid shear on the gut bacteria, particularly bacteria which inhabiting the mucus layer overlying the epithelial cell of the colon. Therefore, by utilizing the rotating wall vessel bioreactor that provides relevant rheological conditions that prevail near the brush border in vivo, this study is aimed to investigate the effect of low-fluid shear on the gut bacteria with respect to their mucin-adhesion properties, growth kinetics, primary metabolic activity, and community structure.

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3 Material and Methods

3.1 Materials (Chemicals, Growth Medium, and Bacterial Strains)

3.1.1 Bacterial Strains

This study was conducted using two pure cultures and suspension of microbial community. The pure cultures of two bacterial strains were obtained from -80°C freezer collection of labmet (Ghent University, Belgium). Lactobacillus reuteri strain ATCC 6475 (MM4-1a), which is known as a beneficial bacterium, was obtained as an isolate from Finnish mother’s milk (Biogaia, AB, Rayleigh, USA) (De Weirdt et al., 2013). In contrast, Adherent-Invasive Escherichia coli strain LF82 (AIEC) was selected as a model pathogen and was obtained as an isolate from an ileal Crohn’s disease patient (Darfeuille-Michaud et al., 2004).

For microbial community experiment, the microbial community suspension was collected from the suspension culture of M-SHIME control colon vessels. The fecal samples were derived from two donors, namely a 32-year-old healthy volunteer (donor J) and a 25-year-old healthy volunteer (donor C) who had no history of antibiotic treatment for 6 months prior to the study.

3.1.2 Chemicals

Unless otherwise mentioned, the chemicals used throughout the experiments were obtained from Sigma (Bornem, Belgium). Linoleic acid was obtained from Larodan (Malmo, Sweden). De Man Rogosa Sharpe (MRS) and Technical agar were obtained from Oxoid (Hampshire, UK). Arachide oil was obtained from Vita d’ore (LIDL, Nederland). Phosphate Buffer Saline without ions (-) Ca2+ and (-) Mg2+ were obtained from (Dulbecco’s). General bacterial primers 338F-GC and 518R PCR products were obtained from Thermo-scientific. 40% Acrylamide (2-Propenamide), 2% Bis AA (Methylenediacrylamide) and Ammonium Persulfate 10% w/v (APS) were obtained from biorad (Hercules, CA, USA). TAE buffer 50 X, Formamide 24% (Methanamide) and TEMED (1-2-di-dimethylamino-ethane) were obtained from Applichem (Darmstadt, Germany). Urea was obtained from Aldrich (Steinheim, Germany). SYBR Green I Nucleic Acid gel stain was obtained from Eugene (Oregon, VS).

The anaerobic phospate buffer (0.1 M, pH 7) was prepared by autoclaving a mixed solution of 1 L of de-mineralized H20, K2HPO4 8.8 g/L, KH2PO4 6.8 g/L, and C2H3O2SNa 1.0 g/L. Physiological solution was prepared by autoclaving the dissolved solution of 8.5 g NaCl in 1 L of distilled H2O.

Lysis buffer for a DNA extraction was prepared by mixing 5 mL of 1 M Tris pH 8, 10 mL of 0.5 M Na-EDTA pH 8, 1 mL of 5 M NaCl, 5 mL of 10% Polyvinylpyrolidone (PVP 40 w/v), 10 mL of 10% Sodium Dodecyl Sulphate (SDS w/v) and adjusted with distilled H2O to 50 mL.

60 % denaturation buffer for DGGE analysis was freshly prepared for 50 mL dissolved solution in milli-Q H2O containing 10 mL of Acrylamide 40%, 2.5 mL of Bis AA 2%, 1 mL of TAE 50X, 12 mL of Formamide 24%, and 12.5 g of Urea. Meanwhile, 0 % denaturation buffer was freshly prepared in the same procedure without the addition of Formamide 24% and Urea. The denaturation buffer was stored at 4°C prior to use. On the other hand, a 10% w/v APS for DGGE was freshly prepared by dissolving 0.1 g APS in 1 mL of milli-Q H2O and stored at 4°C prior to use.

A filter sterilized solution of 0.5% (v/v) Triton X-100 was prepared by diluting an approximate volume of Triton X-100 viscous solution in physiological solution, Thus, its formed a concentration

14

of 0.5% (v/v). Subsequently, the solution was filtered using a PVDF membrane filter 33mm (0.22 µm cut-off) and stored in a place protected from the light.

Freshly prepared mucin agar was made by boiling (approximately 3 times) an aqueous solution containing 5% mucin porcine stomach type II and 1% technical agar. The pH was adjusted to 6.8 by the addition of 10 M NaOH. Freshly prepared mucin agar beads were made by dropping 5 mL of the boiled-mucin agar into the surface of arachide oil using 0.5 mm needle of syringe. The mucin agar beads were left to sink in the arachide oil and form a perfect sphere with the same size. Then the beads were carefully washed two times with 30 mL and 50 mL of physiological solution, separately. Furthermore, the mucin agar beads were resuspended in 50 mL of physiological solution and stored in the fridge prior to use. The final volume of the mucin agar beads should reach 7.5 mL of the falcon tube. Prior to transferring the mucin agar beads to the inoculum, the mucin agar beads were washed carefully by using 50 mL of preferential medium or phosphate buffer saline.

3.1.3 Growth Medium

Pure Cultures of L. reuteri were grown in their preferential medium de man Sharpe Rogosa (MRS). Similarly, AIEC were grown in Luria Bertani (LB). For this purpose, MRS agar and LB agar were prepared by autoclaving a mixed solution of 1 L of distilled H2O containing 15 g Technical agar and 52 g MRS or 20 g LB, respectively.

The intestinal water was prepared according to De Weirdt et al., (2013) by collecting the suspension from proximal colon vessels (ph 5.6 – 5.9) of the Simulator of the Human Intestinal Microbial Ecosystem (SHIME®, prodigest – Ghent University, Ghent, Belgium; Molly et al., 1993; Van den Abbeele et al., 2010) followed by centrifugation (10 min, 1500 rcf) and autoclaving the supernatant. The supernatant was further preserved in 50 mL aliquots at 4°C.

The M-SHIME feed was prepared by autoclaving the mixed solution contained with 1 L of distilled H2O, 1.0 g/L arabinogalactan, 2.0 g/L pectin, 1.0 g/L xylan, 3.0 g/L starch, 0.4 g/L glucose, 3.0 g/L yeast extract, 1.0 g/L peptone, 4.0 g/L mucin, and 0.5 g/L cystein (Vigsnaes et al., 2013; Van den Abbeele et al., 2011).

Unless otherwise mentioned, all procedures were performed under laminar flow or around bunzen burner to maintain the axenic conditions. All equipments were previously sterilized and autoclaved at 1210C for 20 min.

3.2 Rotating Wall Vessel Experimental Set-up

3.2.1 Preparation of Bacterial Culture and Bacterial Growth Suspension

Isolates of two bacterial strains previously stored at -80°C freezer were grown in their preferential media at 37°C for overnight (± 24h) under aerobic condition. Subsequently, a colony was picked and statically grown aerobically in 10 mL of their preferential suspension for overnight (± 16h). Then, 1 mL of the Overnight-grown culture were back-diluted in 100 mL of their preferential medium (MRS-broth and LB broth) and were grown with constant agitation at 37°C, 110 rpm until reaching a mid log-phase growth (± 4h). This was marked at an optical density 610 nm) of 0.6 for L. reuteri and 0.7 for AIEC. These back-diluted cultures were directly used as inoculum (t = 0h) in the RWV bioreactor in nutrient-rich growth medium experiments. On the other hand, for limited-nutrient growth medium experiment, these back-diluted cultures were further centrifuged for 10 min at 20°C, 9000 rpm. The bacterial pellets were washed with 100 mL of physiological solution and centrifuged again for 10 min

15

at 20°C, 9000 rpm. The existing pellets were resuspended in 100 mL of intestinal water medium (IW) and further used as inoculum (t = 0h) in the RWV bioreactor.

The turbidity was determined spectrophotometrically at an optical density of 610 nm according to the standard operating procedure LabMET (Ghent University, Belgium) based on the principle by Beer-Lambert law which is stated that the absorbance of a solution at a certain wavelength is directly linked to the concentration of the absorbing species in the solution and the wavelength.

3.2.2 Filling and Mounting the RWV Bioreactor

This study was aimed to evaluate the effect of low-fluid shear by means of the Rotating Wall Vessel Bioreactor (Synthecon, Houston, TX). The cells are maintained in a gentle fluid orbit and sustained low-fluid shear (< 1 dyne/cm2). The autoclaved RWV bioreactor cylinder was reassembled prior to use. Two of the sampling ports mounted with the stopcocks. One stopcock was connected with the 5 mL luerlock-syringe (with the plunger) and the other stopcock with the 10 mL luerlock-syringe (without the plunger). Subsequently, the inoculum was fully filled in the RWV and the sampling port was immediately closed afterwards. The 10 mL syringe was filled with the inoculum and closed with the plunger. Then, both of the syringes were played in such a way to remove all the air bubbles inside the RWV. Before it was rotated, the RWV was incubated at 37°C for 10 min in a position statically and horizontally. Subsequently, the RWV was mounted to the rotation base and was rotated horizontally at 37 °C, 15 rpm for different time points to mimic the low-fluid shear conditions (Fig. 3-1). These treatments are further referred to as “LSS”. Biological replicates were conducted three times by growing the bacterial cultures independently from the same strain.

Figure 3-1 The RWV experiment was conducted in a horizontal position at 15 rpm speed to mimic the low-fluid shear condition.

The same experiment procedure was conducted three times with the RWV in the vertical position to mimic the normal fluid shear conditions. As this coincides with normal-fluid shear condition these experiments are further reffered to as NG (Fig. 3-2).

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Figure 3-2 The RWV experiment was conducted in a vertical position at 15 rpm speed to mimic the normal gravity condition.

3.3 Experimental Designs

This study was designed by using pure cultures of two different bacterial strains and suspension of the microbial community from M-SHIME colon vessels with an objective to observe the effect of low-fluid shear environments (microgravity) as compared to normal gravity in different growth mediums and at different incubations time. The observations were conducted in terms of growth, adhesion capacity to mucin agar as well as their metabolic activity. In addition, molecular techniques to assess the possibility of microbial community shift after subjected to LSS or NG were performed by means of DGGE analysis.

3.3.1 An Optimization of the Growth Medium for L. reuteri Growth and Mucin Adhesion Assay

This experiment was aimed to determine the appropriate medium which will be used for LSS in the RWV for better optimization of L. reuteri growth and mucin adhesion assay as described in Fig. 3-3. To this end, an experiment was designed for different nutrient conditions of the growth medium namely, MRS-broth (nutrient rich growth medium) and intestinal water (limited nutrient growth medium). For the nutrient-rich growth medium experiments, the samples were obtained directly from back-diluted cultures which were previously grown on their preferential medium and were further used as inoculum (t = 0h) in the RWV bioreactor. On the other hand, for the limited-nutrient growth medium experiments, these back-diluted cultures were further centrifuged for 10 min at 20°C, 9000 rpm. The bacterial pellets were washed with 100 mL of physiological solution and centrifuged again for 10 min at 20°C, 9000 rpm. The existing pellets were resuspended in 100 mL of intestinal water medium and further used as inoculum (t = 0h) in the RWV bioreactor. With respect to mucin adhesion assay, the mucin agar beads were added to the inoculum prior to transferring the inoculum in the RWV. Subsequently, the inoculum was subjected to a fluid shear conditions in the RWV for 1.5 h at 37°C, 15 rpm under LSS or NG. Then, a growth and mucin adhesion assays were carried out for further analysis. To confirm the results, control experiments were performed in both medium for LSS and NG without the addition of mucin agar beads and the observation were done at time point 0 h, 1.5 h, and 20 h; respectively.

17

Figure 3-3 Experimental design of an optimization of the growth medium for growth and mucin adhesion assay in which L. reuteri was subjected to LSS or NG for 1.5 h at 15 rpm, 37°C in different medium: MRS-broth and intestinal water. IW = intestinal water, MAB = mucin agar beads

3.3.2 Investigation of the Inactivation of L. reuteri in the Presence of LA under Low-fluid Shear

The second part of the study was designed (Fig. 3-4) to examine whether there is an effect of a LSS as compared to NG after exposed with the additional stress condition factor namely, Linoleic acid (LA). For this purpose, a growth assay was carried out on L. reuteri to assess the survival of L. reuteri under a given stress condition LSS or NG for 1.5 h at 37°C, 15 rpm. The experiments were performed in limited-nutrients growth medium with the addition of linoleic acid and in the absence of mucin agar beads. Here, a modification in filling the RWV was conducted when the inoculum was half-filled into the RWV cylinder in order to allow the LA were mixed homogeneously with the inoculum.

Figure 3-4 Experimental design of the investigation of the survival of L. reuteri after exposed to linoleic acid for 1.5h at 15 rpm, 37°C under LSS or NG in Intestinal water growth medium. IW = intestinal water, LA = linoleic acid

According to a recent study conducted by De Weirdt and colleagues (2013), the relevant concentration of linoleic acid for monoculture experiment should be 10 times lower than the amount used in the M-SHIME experiment, in line with the total bacteria counts which is generally 10 times lower (108 – 109 flow cytometer counts/ml as compared to 109 – 1010 16S rDNA qPCR counts/mL in the M-SHIME). Gradient concentration of LA was prepared with the addition of LA (density 0.9 g/mL) to the RWV bioreactor (Volume: 55 mL) as follow: 100 µg/mL (122 µL of LA), and 10 µg/mL

18

(0.611 µL of LA). The linoleic acid concentrations correspond to the calculation which was previously diluted in ethanol 96% and the total concentration of the linoleic acid/ethanol added to the RWV bioreactor was maintained at 122 µL. Moreover, based on previous study by De Weirdt et al. (2013), in this study, the effect of ethanol was neglected in the control experiment. Both control of LSS or NG experiment was done without the addition of linoleic acid and was measured for growth assay and SCFAs analysis. Each treatment was only conducted for one biological replicate.

3.3.3 A comparative Study of the Effect of Low-fluid Shear in Enriched-Intestinal Water

These experiments were designed as described in Fig. 3-5 aimed to investigate the effect of LSS as compared to NG in the optimized growth medium by the use of intestinal water enriched with the addition of M-SHIME feed. These experiment were also designed to assess the effect of different incubation time of a given stress conditions. Moreover, these experiments were aimed as a comparative study between a beneficial bacteria L. reuteri as compared to a pathogen bacteria AIEC. For all these purposes, the back-diluted cultures were prepared as previously described and the existing pellets were re-suspended in a mix of suspension containing 50 mL of intestinal water and 50 mL of M-SHIME feed. These mixed-suspension cultures were further used as inoculum (t = 0 h) in the RWV bioreactor. Furthermore, with respect to the mucin adhesion assay, the mucin agar beads were brought into the inoculum and together were exposed to LSS or NG for 1.5 h and 5 h at 15 rpm, 37°C. Further analysis was carried out in terms of growth and mucin adhesion assay as well as SCFAs and Lactate analysis. Both experiments of LSS and NG were performed for incubation time 1.5 h and 5 h using bacterial cultures which was grown-independently from the same strain. Each treatment was only conducted for one biological replicate.

Figure 3-5 Experimental design of the investigation of the effect of LSS as compared to NG of beneficial bacteria L. reuteri and pathogen bacteria AIEC after 1.5 h and 5 h incubation at 15 rpm, 37°C in enriched-intestinal water. IW = intestinal water, SF = M-SHIME feed, MAB = mucin agar beads

19

3.3.4 An overview of the Effect of a Low-fluid Shear on Complex Microbial Community

The last part of this study was designed with an objective to get a better insight on how a complex microbial community behaves in LSS environments (microgravity) as compared to NG. To this end, sample of microbial community were derived from 4 different conditions of M-SHIME proximal colon vessels as shown in Table. 3-1.

Table 3-1 Different sampling condition of microbial community derived from M-SHIME proximal colon vessels

M-SHIME Donors Age Experiment Time of RWV experiment conducted

Start-up (years old)

15/4/2014 Donor J (32) LSS 24 H ± 7 days after the SHIME established

(1) LSS & NG 8 H ± 10 days after the SHIME established

(2) LSS & NG 8 H ± 25 days after the SHIME established

7/5/2014 Donor C (25) (3) LSS & NG 8 H ± 10 days after the SHIME established

Sample of microbial community was freshly harvested 35 mL quantitatively from the M-SHIME proximal colon vessel and was aliquoted in two falcon tubes. Each falcon tubes were added quantitatively with 17.5 mL of M-SHIME feed and 15 mL of anaerobic phosphate buffer. This mixed suspension was further used as inoculum in the RWV (t = 0h). The RWV was fully filled again with M-SHIME feed immediately thereafter each of the sampling time and was continuously checked for gas bubbles formation for every hour. The experiment of LSS and NG as described in Fig 3-6 for 8 h incubation time was conducted for at least three biological replicates. While the experiment of LSS for 24 h incubation time was only performed for one biological replicate. During all of the experiments, the microbial community was monitored by means of culture-based quantification (Flow Cytometer) and metabolic activity in terms of SCFAs and lactate at different time point. Additional DNA-based finger printing analysis (DGGE) was carried out to observe the microbial community before and after 8 h incubation at 15 rpm, 37°C under LSS or NG in order to demonstrate the possibilities of microbiota composition that might be shifted in a given fluid shear conditions.

Figure 3-6 Experimental design to investigate the effect of LSS as compared to NG on microbial community and was measured at different time point at 15 rpm, 37°C. MC = microbial community, SF = M-SHIME feed, APB = anaerobic phosphate buffer

20

3.4 Growth and Mucin Agar Adhesion assay

3.4.1 Growth Assay

All growth assays was conducted in 3 technical replicates from one biological replicates. Viability (CFU/mL) was quantified in the inoculum and after exposed to the LSS or NG condition (further termed as lumen). Growth assay was conducted by means of quantification of total bacterial counts using two methods namely, plates counting and Flow cytometer.

In respect to plates counting methods, 20 µL of inoculum and lumen subsamples were serially diluted

in 96 well-plates containing 180µL of physiological solution (100 – 10-7 micro-dilution series). Then, 10 µL of the micro-dilution series were grown in a preferential growth medium aerobically at 37°C for at least 24 h. The calculation for CFU/mL was conducted using the following equation, in which the plated volume is equal to 10-2 mL:

Equation 3 Calculation for CFU/mL in inoculum and lumen

���/�� = ��������� �!��" ���#�$������$%!�#%���� #�� × '�!���(!�#�$�

Meanwhile, the Flow Cytometry measurement was done according to standard operating procedure of Flow Cytometer (BD C6 Accuri, BD csampler Software). Based on the principle that cell which is stained with fluorescent stains gets excitated by a specific wavelength and radiates a light that can be detected by the appropriate detector. For this purpose, a dilution series of 100 µL of inoculum and lumen subsamples in 900 µL physiological solution (100 – 10-4 dilution series) was prepared. Prior to the dilution process, the autoclaved physiological solution was filter-sterilized using a PVDF membrane filter 33mm (0.22 µm cut-off). Based on the trial, the dilution series that visible to be counted were 10-2 – 10-4 serial dilutions. Of these vortexed dilution series, 198 µL was pipetted to 96 well-plates and was spiked with 2 µL of SYBR Green (the emission light of SYBR Green is used as the excitation source) and followed by incubation aerobically for 13 min at 37°C in the dark. Prior to analysis, the flow cytometer was set at 96-well plates flat bottom (plate type), fast speed with flow rate 66 µL/min core size 22 µm (flow rate), FL1-H less than 500 (threshold), and 25 µL (sample volume). A filter-sterilized physiological solution was subsequently used as a blanco to set the gate. The calculation of CFU/ml was conducted using (eq.3), in which the volume is equal 2.5 x 10-2 mL.

3.4.2 Mucin - adhesion assay

After subjected to a given fluid shear conditions at different time, all the content inside the RWV bioreactor (the lumen and mucin agar beads) were transferred to the falcon tubes carefully to avoid more turbulences of the content. The lumen was then separated from the mucin agar beads to different falcon tubes. The mucin agar beads were washed two times with 10 mL of physiological solution before further applied with mucin-agar adhesion assay. The remaining adhered bacteria were detached using Triton X-100 by means the mucin agar beads were treated with 5 mL of Triton X-100 0.5% (v/v) for 10 min at 37°C, 110 rpm. All the detached in triton-X 100 solution (further termed as mucin) was quantitatively transferred to another falcon tubes. Followed by, the mucin agar beads were washed two times with 5 mL of physiological solution and the remaining solution was incorporated to the mucin. The Final volume of mucin should be approximately 15 mL. Furthermore, the quantification of the attached bacteria in the mucin was done by means of plates counting and flow cytometer methods as previously described. With respect to the trial experiment of Flow Cytometer quantification method in mucin, the dilution series that visible to be counted were 10-1 – 10-2 dilutions.

21

Thus, the sample was only measured for 10-1– 10-2 dilution series. All mucin agar-adhesion assays was performed in three technical replicates.

The calculation for CFU (mg/mL) was conducted using the following equation, in which correction factors were obtained from 15 mL divided to 55 mL (volume of RWV):

Equation 4 Calculation for CFU/ml in mucin

���/�� = � ���� #%���� #�� × �������� �!��" ���#�$������$%!�#%���� #�� × '�!���(!�#�$�

The percentage of mucin adhesion was calculated based on the following equation:

Equation 5 Calculation for % mucin adhesion

%*$+�%�� =,����� -�$+���$%��� %�

,����� - %�!����+ ,����� -�$+���$%��� %��× /00%

3.5 Bio-chemical Analysis

3.5.1 Short Chain Fatty Acids extraction for Gas Chromatography Analysis

Samples preparation for SCFAs analysis was determined according to Gas Chromatography GC-2014 (Shimadzu,'s-Hertogenbosch, The Netherlands) standard operating procedure. The principle of the analysis is a quantitative determination of a capillary gas chromatography which is coupled with a flame ionization detector. It was fitted with a fatty acid-free capillary EC-100 Econo-Cap column (dimensions: 25 mm x 0.55 mm, film thickness 1.2 µm, Altech, Laarne, Belgium). The injection volume was 1 µL, and the temperature rose to 6°C/min, ranging from 110°C to 160°C. The carrier gas was N2 and the temperature of the injector and detector was 100°C and 220°C, respectively. Briefly, the separation of SCFAs was conducted by liquid-liquid extraction as follow: 2 mL samples of inoculum, lumen and mucin supernatant were collected in 10 mL tubes for SCFAs extraction. Followed by addition of 500 µL H2SO4 50% to enhance the protonated form, ±400 mg NaCl was added to assist the separation, 400 µL Internal Standard was added constantly in the same amount to the samples and blanco as well as to the calibration standard, and finally was merged with 2 mL of diethyl ether. The latter was added quantitatively because it would determine the amount of SCFAs extracted from the samples. After the addition of diethyl ether, the tubes were immediately closed to avoid evaporation. Subsequently, the mixture was rotated in the rotary equipment for exactly 2 min in order to homogenize the samples. The tubes were centrifuged for 3 min at 3000 rpm. The upper phase containing SCFAs in ether was transferred to GC vial tubes and was kept in the fridge prior to analysis. Microbial activity in terms of SCFAs: Acetate, propionate, and butyrate were measured using GC. Distilled H2O was used as a blanco. All sample of each treatment was consisted out of three technical replicates.

The internal standard that was used for normalization for SCFAs analysis, was prepared by dilution of a volume of 1.5 ml 2-methyl hexanoic acid in a quantitative flask of 100 mL and adjusted to 100 mL with a 0.1 N NaOH (in milli-Q H2O) solution according to the standard operating procedure of LabMET (Ghent University, Belgium). Subsequently, the dilution was transferred to a Scott bottle and was mixed with 100 mL of milli-Q H2O. The extraction of the external standard was prepared by dilution series 1:2 of pure external standard which was obtained from Supelco Volatile Free Acid Mix in de-ionized water. The internal standard was prepared using the following calculation:

Equation 6 Calculation for internal standard Gas Chromatography analysis

3.5.2 Lactate Analysis Sample Preparation

Samples of inoculum, lumen and mucin supernatant were filter0.22 µm cut-off) to HPLC vials for approximately 500 performed in three technical replicates. The samples were stored at 4°C prior to analysis using Ion Chromatography-Dionex AS 50technical replicates.

With respect to external lactate standard preparation, regression plot of different concentrations (ranging from 2.5 mg to 1000 mg) of dstandard solutions (Fig. 3-7). To this end, lactate external standard was prepared by quantitative serial dilutions of pure lactate standard or from prepared sodium lactate operating procedure of LabMETout by dividing the obtained peak area with the gradient of lactate standard curve. Prior to that, the sample peaks were checked whether it was positioned in the range area of lactate standard and whether the sample peaks was obtained at the retention time of lactate standard

The calculation of lactate standard done the following equation:Equation 7 Lactate standard calculation for tchemicals and further dissolved in

Equation 8 Lactate standard calculation for tsolution and further back-diluted in

Concentration Ret.Time (min) Area (

Lactate (mg/L) Lactate

1000 9.2400

100 8.8800

10 8.6630

750 9.1200

75 8.7530

7.5 8.6670

500 9.0070

50 8.7270

5 8.6230

250 8.9170

25 8.6670

2.5 8.6400

Figure 3-7 Lactate standard Curve of dilution series of Lactate ranging g/L

Calculation for internal standard Gas Chromatography analysis

Lactate Analysis Sample Preparation

Samples of inoculum, lumen and mucin supernatant were filter-sterilized (PVDF membto HPLC vials for approximately 500 µL. All sample of each treatment technical replicates. The samples were stored at 4°C prior to analysis using Ion

Dionex AS 50. All of each treatment of the experiment was conducted for three

With respect to external lactate standard preparation, lactate standard curve was obtained from linear regression plot of different concentrations (ranging from 2.5 mg to 1000 mg) of d

). To this end, lactate external standard was prepared by quantitative serial of pure lactate standard or from prepared sodium lactate according to the standard

MET (Ghent University, Belgium). Lactate analysis was carried out by dividing the obtained peak area with the gradient of lactate standard curve. Prior to that, the sample peaks were checked whether it was positioned in the range area of lactate standard and

sample peaks was obtained at the retention time of lactate standard.

The calculation of lactate standard done the following equation: Lactate standard calculation for the analyte that was started from solid

further dissolved in milli-Q H 2O:

Lactate standard calculation for the analyte that was started from liquid diluted in milli-Q H 2O:

Area (µs*min)

Lactate

15.6027

1.4223

0.0820

11.6874

1.0023

0.0566

7.6529

0.6174

0.0318

3.7728

0.2526

0.0101

Lactate standard Curve of dilution series of Lactate ranging

-

2.0000

4.0000

6.0000

8.0000

10.0000

12.0000

14.0000

16.0000

18.0000

0 200 400

Are

a µ

S*

min

La

cta

te

Lactate Concentration (mg/L)

Lactate Standard Curve

22

Calculation for internal standard Gas Chromatography analysis

PVDF membrane, 33 mm, of each treatment was

technical replicates. The samples were stored at 4°C prior to analysis using Ion atment of the experiment was conducted for three

actate standard curve was obtained from linear regression plot of different concentrations (ranging from 2.5 mg to 1000 mg) of different lactate

). To this end, lactate external standard was prepared by quantitative serial according to the standard

Lactate analysis was carried out by dividing the obtained peak area with the gradient of lactate standard curve. Prior to that, the sample peaks were checked whether it was positioned in the range area of lactate standard and

was started from solid

was started from liquid

Lactate standard Curve of dilution series of Lactate ranging from 2.5 mg/L to 1

y = 0.0155x

R² = 0.9996

600 800 1000

Lactate Concentration (mg/L)

Lactate Standard Curve

23

3.6 Molecular Techniques for Denaturing Gradient Gel Electrophoresis (DGGE) Analysis

DGGE was carried out as a qualitative observation to monitor the shifts within the complex microbial community before and after subjected to simulated LSS or NG environment (further termed as inoculum 8 h and lumen 8 h).

3.6.1 DNA Extraction

DNA extraction was performed according to LabMET standard operating procedure (Ghent University, Belgium) based on the basic principle step of mechanical and chemical lyses to obtain DNA and purification of DNA (precipitation). Briefly, 0.5 mL of samples of inoculum and lumen 8 h which was previously stored at -20°C were centrifuged for 10 min at 5000 rpm. The obtained pellets were transferred to fastprep compatible tubes (2 mL). The pellets were incorporated with ± 200 mg of glass beads and 1000 µL of lysis buffer. Then the fastprep tubes were disrupted 2 times for 40 seconds at 1600 rpm and followed by centrifugation for 5 min at maximum speed. The obtained supernatant was transferred to 1.5 mL eppendorf tubes and was spiked with 500 µL of mixed solution of phenol: chloroform: iso-propil alcohol (25:24:1) pH 7 - 8. The eppendorf tubes were vortexed, further inverted for 5 times, and centrifuged for 5 min at maximum rpm. Thereafter, the supernatant was transferred to new eppendorf tubes and was spiked with 700 µL of chloroform. Once again, the eppendorf tubes were inverted for 5 times and centrifuged for 1 minute at maximum speed. Subsequently, 450 µL of the upper phase containing DNA in chloroform was transferred to new eppendorf tubes and was incorporated with 45 µL of 3 M Na-acetate and 500 µL of isopropyl alcohol (previously stored at -20°C). In order to get homogenous solution, the tubes were inverted for 5 times and further stored at -20°C for at least 1 hour (preferably stored for overnight). Immediately thereafter from -20°C, the tubes were centrifuged for 30 min at 4°C, maximum speed. The pellet was dried for ± 30 min by inverting the tubes and followed by addition of 50 µL of T10E1 1X to dissolve the pellet. Furthermore, the obtained DNA was checked for their purity in Agarose gel electrophoresis and was measured for concentration using Nanodrop. For each treatment constituted 3 technical replicate samples. The purified DNA was stored at – 20°C prior to use.

3.6.2 Agarose Gel Electrophoresis to Check the Purity of DNA Extraction

The principle of gel electrophoresis separation is based on the migration of DNA molecules which was separated according to the length. The smaller molecules will migrate faster in the gel. The phosphate groups of the DNA which were negatively charged in a neutral to slightly alkaline medium promote the migration towards a positive charge. Thus, the strength of the electric field, the molecules size of the DNA and the porosity further determine the speed of the migration.

Briefly, the gel electrophoresis comb and holder was reassembled prior to use. The agarose gel was prepared by boiling the partially dissolved solution of 1.3% of Agarose ultrapure in 0.5X of TAE buffer until visually clear solution was obtained. The agarose gel solution was allowed to cool before further poured to the gel holder and left to solidify for ± 20 min. After solidified, the agarose gel was taken out from holder and the comb was removed. Thereafter, the solidified gel was placed inside the gel electrophoresis instrument and was immersed in 0.5X TAE buffer. Subsequently, 2 µL of a loading dye was mixed to 3 µL of sample and further spiked to the loading gel. The gel electrophoresis was carried out for 25 min at 20°C and the current was set at 100 V to allow the DNA migrate in the gel. Mass Ruller Mix DNA Ladder was used as a marker. Finally, the stained gel was photographed to visualize the obtained bands. To this end, the gel was developed in Ethium Bromide

24

(Et-Br) and the DNA bands were visualized by UV trans-illuminator at 590 nm using Proxima AQ4 software.

3.6.3 Nanodrop to Check the Concentration of the Extracted DNA

In principle, Nanodrop ND-1000 V3-8.1 Spectrophotometer instrument (Isogen Life Science, Ijsselstein, Netherlands) was performed to determine the amount of DNA (ng/L) at 260 nm. The purity of the samples were obtained from the ratio of 260/280 (DNA/ RNA) and the ratio of 260/230 (DNA/ protein). The DNA/ protein ratio is best situated in between of 1.8 and 2.0. On the other hand, The DNA/RNA ratio is bigger than 1.8. Blanc measurement was done with measuring 1 µL of distilled H2O and 1 µL of T1OE1 buffer. Thereafter, 1 µL of each sample was measured independently

3.6.4 Polymerase Chain Reaction (PCR) Amplification for DGGE

PCR amplification was aimed to amplify the target gene sequences encoding for the marker genes, in this case 16S rRNA genes of the total community obtained with general bacterial primers 338F-GC and 518R PCR products (1: 100) dilution. The basic principle of PCR amplification was a repeated denaturation, annealing, and elongation cycle. The substances that were synthesized from each cycle were used as a substrate for the next cycle, which result in an increasing concentrated of the substances. The first step was initial denaturation process at a temperature 94°C for 5 min to denature a double-stranded DNA to a single-stranded DNA. Thereafter, the second step was continued with 20 – 30 x cycles consisted of denaturation at 94°C, annealing (hybridization) at a temperature started at 53°C - 72°C in which the primers freely moved and ionically bonded with a single-stranded DNA enhance the formation of DNA template and had allowed the Taq-DNA polymerase making copies, and elongation process at 72°C allowing the extension process of the primers. The third step was final elongation occurred at 72°C, which was the optimum temperature for Taq-DNA polymerase. In case of the primers were not exactly matched, they were started separated from the DNA template and stick to each others. The process was ends up with cooling at 4°C. To this end, the PCR instrument (Applied Biosystems, Carlsbad, CA) was programmed for general temperatures as listed below:

Table 3-2 Temperature and Time program for general primers 338F-GC and 518R for conventional PCR

Amplification Process Temperature (°C) and time (minutes)

Initial denaturation 94 ° C, 5 min

Denaturation 94 °C, 1 min

Annealing 53 °C , 1 min

Elongation 72 °C, 2 min

Final elongation 72 °C, 10 min

Cooling 4°C , ~ min

The amplification process was performed in an axenic PCR unit cabinet. The general primers 338F-GC and 518R PCR products were diluted (1: 100) in PCR water. The samples were diluted (1: 100) in PCR water and were vortexed as preparatory to mixing with a master mix solution of which 1 µL of samples were spiked to 24 µL of master mix in PCR tubes. In order to monitor the possibilities of

25

contamination during the preparation of master mix and amplification process in the PCR cabinet, two negative controls and one positive control were prepared. In which, one of the negative control tubes was immediately closed after spiked with 25 µL of master mix, while the other one was closed after all the amplification process is completed. To all this end, a master mix solution of 625 µL was freshly prepared according to standard of master mix composition for 21 samples (exactly 25 µL for each sample) based on standard operating procedure LabMET (Ghent University, Belgium) as listed below:

Table 3-3 Standard Composition of Master Mix PCR for One Sample (25 µL)

Product Volume (µL)

PCR water 14.1875

Taq Buffer 10 X (diluted in KCl) 2.5

Mgcl2 (25 mm) 1.5

Dntps (10 mm) 0.5

Primer F (10 µm) 0.5

Primer R (10 µm) 0.5

BSA (20 mg/mL) 0.0625

SYBR Green 20X (diluted in DMSO) 0.125

Taq-DNA Polymerase 0.125

After the PCR process, agarose gel electrophoresis as described previously was applied to the amplicons to test whether a contamination occurred and to determine whether the amplification process was formed for each sample. The amplicons were thereafter stored at -20°C prior to use for DGGE.

3.6.5 Denaturing Gradient Gel Electrophoresis (DGGE) Experiment Set-up

DGGE was applied to separate the total microbial community of the amplified DNA samples obtained using general bacterial primers 338F-GC and 518R for 16S rRNA genes. In principle, DGGE is a gradient separation process that occurs in the presence of denaturing chemicals (Urea- Formamide) ranging from 45% to 60% and electrophoretic mobility of amplified-DNA in 8% polyacrylamide gel at constant T°C. As a result, an amplified-DNA sample will stop migrating in the polyacrylamide gel when it was denatured.

DGGE was performed using Ingeny DGGE instrument phoru 2x2 system (Ingeny International BV, the Netherlands) according to standard operating procedure of LabMET (Ghent University, Belgium) and refers to protocol of Muyzer et al. (1993). Prior to use, the glass plates and the spacers were cleaned. The glass plates were installed in the cassette and the spacers were placed in between the glass followed by incorporating the comb.

Briefly, DGGE process can be performed in 5 steps. The first step of DGGE was casting the bottom gel, in which a mix of gel solution (containing 1.5 mL of denaturation buffer 60%, 30µL of APS, and 1.5 µL of TEMED) was injected through the spacers and left for 15 min to polymerize. The second step was casting the gradient in which the gradient denaturing gel consisted of 45% and 60% solution were injected through the spacers. For this purpose, 60% of denaturion buffer (consisted of 24 mL of denaturion buffer 60%) and 45% of denaturation buffer (consisted of 18 mL of denaturion buffer 60%

26

and 6 mL of denaturion buffer 0%) were added with 130 µL of APS and 10 µL of TEMED. Both denaturation buffers were gradually mixed in the communicating vessels of tubing device. Consequently, the concentration of the gel gradually decreased from 60% to 45%. It should be noted, at this step must avoid the air bubbles entering the glass plates. Subsequently, milli-Q H2O was added on top of the gel and the glass plate covered with aluminum foil for at least 1 hour so that the gel can be polymerized. The third step was casting the stacking gels, in which a mix of gel solution (containing 5 mL of denaturation buffer 0%, 100µL of APS, and 5 µL of TEMED) was injected approximately 6 mL through the spacers and covered with alumunium foil for 30 min to polymerize. The fourth step constituted of loading and running the gel. After 30 min, the comb was lifted and the gel holder was slowly installed inside the Ingeny tank. The Ingeny instrument was charged at low voltage and submerged in TAE buffer which was pre-heated to 60°C for 1 hour. At this step, together a mix of 8 µL of amplified-DNA samples and 2 µL of loading dye were injected to the gel (10 µL). A mix of the marker genes (16S rRNA) and loading dye were injected at both side and in the middle of the gel. Finally, the electrophoresis gel was run for 16 hours at 120 V, 60°C. After 16 hours, the gel can be developed. To this end, the gel was carefully taken out from the gel holder and submerged in 300 mL of TAE 1X buffer. Subsequently, approximately 14 µL of SYBR Green stain was diluted in the buffer and covered with alumunium foil for 20 min. Last step was visualization of the staining gel in which the gel was subjected to UV-transilluminator via SYBR green filter glass and the amplified-DNA bands were acquired using Proxima AQ4 software.

3.7 Statistical tools

3.7.1 Statistical Analysis for Growth Assay

All statistical analysis for growth assay (log CFU/mL) was performed using TIBCO Spotfire-SPLUS Software (Ghent University, Belgium). The significance level was set at p-value 0.05. However, since the numbers of biological replicates were not sufficient to perform a parametric test, therefore significant differences between LSS and NG was assessed using non-parametric test Wilcoxon Rank Sum Test.

3.7.2 Statistical Analysis for Processing DGGE Results

To process the visualized gel, further analysis was carried out according to Van den Abbeele et al. (2011) and Vigsnaes et al. (2013) in which bionumerics software version 5.10 (Applied Maths, Sint-Martens-Latem, Belgium) was used for identification of visualized bands and normalization of band patterns from DGGE gels. A cluster analysis to calculate the dendrograms of different samples were conducted based on Pearson correlation coefficients and Un-weighted pair group method using arithmetic mean (UPGMA) clustering algorithm, taking into account both band position and band density. As a result, a cluster analysis was presented as a plot in a comparative matrix, where the percentages represent the similarity.

27

4 Results

4.1 Investigation of the Effect of Low-fluid Shear on Lactobacillus reuteri

Investigation of the effect of low-fluid shear on the beneficial microbe L. reuteri was done by three different experiment types. The first experiment was conducted to determine the appropriate medium, which will be used for mimicking low fluid shear stress (LSS) in the RWV in order to obtain optimization of the growth and mucin adhesion assay of L.reuteri. Here, the control experiment was carried out in the absence of Mucin agar beads in both media: MRS and intestinal water. The next experiment was conducted to examine whether there was an effect of LSS as compared to NG in the presence of another stressor linoleic acid. Here, the normal gravity (NG) experiments are corresponds to normal shear conditions. The control experiment was conducted in intestinal water medium without the addition of linoleic acid. The last experiment was performed to investigate the effect of simulated microgravity LSS as compared to NG in optimized growth medium and was carried out for growth assay, mucin adhesion assay and assessing the metabolic activity at throughout the experiment.

4.1.1 Optimization of the Growth Medium for the Investigation of Low-fluid Shear in the RWV

The purpose of this experiment was to determine the appropriate medium for the growth of L. reuteri. This medium will be further used in the investigation of the effects of in vitro low-fluid shear towards growth and mucin adhesion. To this end, a growth and mucin adhesion assay was carried out using medium MRS-broth and intestinal water for t = 1.5h at 15 rpm in different orientation position of the RWV, the low–fluid shear and normal gravity. A control experiment was conducted for both media in the absence of mucin agar beads for t = 1.5h and t = 20h at 15 rpm in LSS and NG position to test the utilization of the medium by L. reuteri. The bacterial concentration in the inoculum and lumen was counted based on eq. 3, while the bacterial concentration in the mucus was obtained based on eq. 4.

Based on the difference in average bacterial concentration between lumen and inoculum, Table 4-1 experimentally indicates that the growth of L. reuteri in MRS-broth was slightly higher in comparison to intestinal water, regardless of the applied shear stress. Furthermore, experimental results of NG have shown slightly higher differences in bacterial concentrations between the lumen samples and inoculum as compared to LSS irrespective of the medium used. In addition, with respect to the control experiment, it can be proposed that the growth of L. reuteri was enhanced with the presence of mucin agar beads without taking into account the type of medium and the type of applied shear stress.

Although all of the results shown in Table 4-1 are not significant different (p-value: 0.1), it was visually observed in the control experiment LSS (in the absence of mucin agar beads, incubated for t20 horizontally in MRS-broth) that a biofilm was formed and that considerable gas formation was taking place (Fig. 4-1). This indicates the tendency to adhere and colonize and a high metabolic activity. Meanwhile, precipitation and gas formation was also observed in the control experiment NG at the veritical position in MRS broth in the absence of mucin agar beads. On the other hand, these visual observations were not found in the control experiment without the addition of mucin agar beads using media intestinal water. On the contrary, complete reduction (below the detection limit) of L. reuteri growth resulted on plates counting (incubated for t20 horizontally and vertically).

28

Table 4-1 Plate counts of L. reuteri (mean ± stdev log CFU/mL) scored after 24 h, which are previously grown in a different media (MRS-broth and intestinal water) and exposed to LSS or NG for 1.5 h at 15 rpm. The start inoculum at t = 0 h was maintained at OD 610 nm ≈ 0.6. The control experiments were conducted without the addition of MAB. IW = intestinal water, MAB = mucin agar beads.

Medium Experimental designs Mean+ stdev Log CFU/mL Mean Log CFU/mL

Shear Stress Treatment Inoculum Lumen t1.5 Mucin t1.5 Difference Lumen - Inoculum

MRS LSS (-) MAB 8.18 ± 0.11 8.06 ± 0.05 - 0.99

LSS (+) MAB 8.98 ± 0.04 9.14 ± 0.05 6.66 ± 0.04 1.02

NG (-) MAB 8.09 ± 0.08 8.20 ± 0.06 - 1.01

NG (+) MAB 8.24 ± 0.06 9.37 ± 0.05 6.53 ± 0.06 1.14

IW LSS (-) MAB 8.28 ± 0.04 7.99 ± 0.05 - 0.96

LSS (+) MAB 7.26 ± 0.04 7.19 ± 0.05 4.73 ± 0.04 0.99 NG (-) MAB 8.10 ± 0.06 7.95 ± 0.05 - 0.98

NG (+) MAB 7.27 ± 0.06 7.25 ± 0.05 4.75 ± 0.06 1.00

Figure 4-1 Biofilm-like formation of L. reuteri after incubated horizontally in the RWV for t20 at 15 rpm in MRS-broth medium

Moreover, an adhesion assay was carried out on the basis to investigate the adhesion capacity of L.

reuteri after being subjected to LSS or NG condition for t1.5 in the RWV. The percentage of L. reuteri adhered to mucin agar beads were calculated based on eq. 5. The presented result in Fig. 4-2 showed that under LSS, L. reuteri has better capacity to adhere to mucin agar beads as compared to NG condition irrespective of the medium used. In contrast with this observation, no significant difference was noticed in the experiment using intestinal water for both condition LSS and NG.

29

Figure 4-2 Histogram of mucin adhesion capacity (% of mean ± stdev CFU/mL) of L. reuteri to mucin-agar beads after t1.5 incubation at 15 rpm in LSS and NG condition in MRS-broth (left) and intestinal water (right). The start inoculum at 0 h was maintained at OD 610 nm ≈ 0.6. IW= intestinal water, MAB = mucin agar beads. Bars indicates the standard errors (n =3)

4.1.2 Investigation of the Effect of Low-Fluid Shear on the inactivation of L. reuteri in Linoleic Acid

As indicated from previous results, L. reuteri has a slightly higher growth in the Lumen under NG condition in comparison to LSS. Further experiments have been carried out to strengthen this finding in order to determine whether or not the applied shear stress has an effect to L. reuteri growth in the presence of a stress factor like linoleic acid. For this purpose, a growth test was conducted to a back-diluted culture of L. reuteri in intestinal water in combination with different concentration of linoleic acid/ethanol, namely 10µg/mL and 100µg/mL under LSS or NG condition for t1.5 at 15 rpm. In the meantime, control experiments were conducted in the absence of linoleic acid. The bacterial concentration in the inoculum and lumen was counted based on eq. 3. The inactivation was expressed as a difference in bacterial concentration between the lumen and inoculum. Additionally, SCFAs analysis was carried out to test whether a metabolic activity occurred in the control experiment and expressed in mg/L.

The observed results of L. reuteri inactivation were shown in Fig. 4-3. A significant decrease in the bacterial concentration of L. reuteri in the presence of linoleic acid at a 100 µg/mL under LSS condition can be seen as compared to NG. However, no significant difference was observed in the difference of bacterial concentration between lumen and inoculum in the presence of linoleic acid 10 µg/mL with respect to the control. Furthermore, SCFAs analysis as presented in Table 4-3 of the control experiments (in the absence of linoleic acid) showed depletions in the concentration of acetate

-0.05%

0.00%

0.05%

0.10%

0.15%

0.20%

0.25%

0.30%

0.35%

0.40%

0.45%

0.50%

LSS 1.5 H NG 1.5 H

Mu

cin

Ad

he

sio

n (

%)

Shear Stress

% Mucin Adhesion

Lactobacillus reuteri

RWV 1.5 H MRS-broth + MAB

-0.05%0.00%0.05%0.10%0.15%0.20%0.25%0.30%0.35%0.40%0.45%0.50%

LSS 1.5 H NG 1.5 H

Mu

cin

Ad

he

sio

n (

%)

Shear Stress

% Mucin adhesion

Lactobacillus reuteri

RWV 1.5 H IW + MAB

Conclusion:

Based on the result of growth assay, it can be deduced that L. reuteri is growing less effectively in the lumen under LSS in comparison to NG conditions. When including mucin agar beads it’s important to note that the growth of L. reuteri was generally enhanced both under LSS as NG conditions. Yet, based on the mucin agar adhesion assay, L. reuteri appeared to have a better adhesion capacity under LSS in comparison to NG.

30

(mg/L) and indicates that the metabolic activity might not taking place. These depletions were slightly higher under LSS in comparison to NG condition.

Experiment Mean + stdev Log

CFU/ml

Shear Stress [LA] µg/mL Inoculum Lumen

LSS (-) LA 8.28 ± 0.04 7.99 ± 0.05

(+) LA 10 8.12 ± 0.04 7.86 ± 0.06

(+) LA 100 8.23 ± 0.02 3.37 ± 0.17

NG (-) LA 8.10 ± 0.06 7.95 ± 0.05

(+) LA 10 8.14 ± 0.07 7.97 ± 0.09

(+) LA 100 8.22 ± 0.04 4.26 ± 0.04

Figure 4-3 Plate counts of L. reuteri (mean ± stdev log CFU/mL) scored after 24h in which L. reuteri in intestinal water medium were exposed to 10 µg/mL or 100 µg/mL linoleic acid under LSS or NG condition for 1.5 h at 15 rpm. The start inoculum at t = 0 h was conditioned at OD 610 nm ≈ 0.6. The control experiments were conducted without the addition of linoleic acid. IW = intestinal water, LA = linoleic acid

Table 4-2 Acetate proportion (mean ± stdev in mg/L) in intestinal water medium after L. reuteri was subjected under LSS or NG condition for 1.5 h at 15 rpm. The start inoculum at t = 0 h was conditioned at OD 610 nm ≈ 0.6

Shear Stress Subgroup Mean [Acetate] ± stdev (mg/L)

Concentration Difference Inoculum -Lumen

LSS Inoculum t0 687.00 ± 10.39 80.33

Lumen t1.5 606.67 ± 19.86

NG Inoculum t0 680.00 ± 5.00 66.00

Lumen t1.5 614.00 ± 9.54

-4.86

-3.96

-0.25

-0.17

-0.29

-0.15

-6.00 -5.00 -4.00 -3.00 -2.00 -1.00 -

log difference CFU/mLLu

me

n -

Ino

culu

m

Log difference CFU/mL

Lumen - Inoculum

RWV 1.5 H, Medium IW + LA

IW NG 1.5 H

IW LSS 1.5 H

IW NG 1.5 H+LA 10 mcg/mL

IW LSS 1.5 H+LA 10 mcg/mL

IW NG 1.5 H+LA 100 mcg/mL

IW LSS 1.5 H+LA 100 mcg/mL

Conclusion:

Based on the results of the growth assay, it was revealed that L. reuteri has better survival (mean ± stdev log CFU/mL) in the lumen under NG in comparison to LSS. This finding suggests that L. reuteri experiences more stress condition (higher toxicity of Linoleic acid) under LSS condition. In addition, the SCFA analysis has shown a slight depletion of metabolic activity (acetate) of L. reuteri under LSS as compared to NG. However, this finding still needs further investigation.

31

4.1.3 Investigation of the Effect of Low-fluid Shear on L.reuteri in Enriched Growth Medium

From the above analysis, it was found that L. reuteri has a better mucin adhesion capacity under LSS as compared to NG. Yet, in terms of growth, L. reuteri showed less growth under LSS as compared to NG. These findings were further examined on the basis to assess the effect of LSS and NG shear stress on growth, mucin adhesion capacity as well as metabolic activity of L. reuteri in the proposed enriched intestinal water medium with the addition of SHIME feed. For this purpose, a growth and mucin adhesion assay was carried out on L. reuteri after exposure to LSS or NG condition in the RWV. The bacterial concentration in the inoculum and lumen was counted based on eq. 3, while the bacterial concentration in the mucin was obtained after corrected based on eq. 4. In addition, SCFAs and lactate analysis was carried out to determine whether there was a different metabolic activity pattern of L. reuteri after subjected to LSS or NG condition for t1.5 and t5 at 15 rpm.

The results presented in Fig. 4-4 shows a similar trend of mucin adhesion capacity of L. reuteri as obtained from the previous results. L. reuteri was found to have better mucin adhesion capacity under LSS as compared to NG. Moreover, this adhesion capacity was further increased as the incubation time increased. However, in terms of growth ability, no significantly different results could be deduced from these experiments.

Figure 4-4 Histogram of (1) Mucin adhesion capacity (% of mean ± stdev CFU/mL) of L. reuteri to mucin-agar beads (2) Flow Cytometry counts of L. reuteri (mean ± stdev log CFU/mL) after t1.5 and t5 incubation time at 15 rpm in LSS and NG condition in the medium containing IW+SF. The start inoculum at 0 h was maintained at OD 610 nm ≈ 0.6. IW = intestinal water, SF = M-SHIME feed, Bars indicates the standard errors. Data represent the mean of three replicates (n = 3).

0.00%

0.20%

0.40%

0.60%

0.80%

NG 1.5 H NG 5 H LSS 1.5 H LSS 5 H

Mu

cin

Ad

he

sio

n

(%)

Shear Stress

% Mucin Adhesion

Lactobacillus reuteri

RWV Medium IW+S

-

2.00

4.00

6.00

8.00

10.00

NG 1.5 H NG 5 H LSS 1.5 H LSS 5 H

Log

CF

U/m

L

Shear Stress

Log CFU/mL Lactobacillus reuteri

RWV Medium IW+SF

Inoculum

Lumen

Mucin

1

2

32

Additionally, with taking into account standard deviations of the results from SCFAs analysis as presented in Table 4-3, L. reuteri has shown redistribution of SCFAs from inoculum (t = 0 h) into lumen and mucin, with a slightly higher production of acetate under LSS as compared to NG. Moreover, the acetate productions have shown an increase in concentration over the time. Detailed observations from SCFAs analysis of L. reuteri are presented in Appendix. 1.

Conversely, data of lactate analysis presented in Table 4-4 have shown lower concentration of lactate under LSS as compared to NG after 1.5 h incubation. This lactate concentration was increased over the time. Yet, the results from 5 h incubation showed a slightly increase in lactate final concentration under LSS as compared to NG.

Table 4-3 SCFAs production of L. reuteri (mean ± stdev in mg/L) in the medium containing IW+SF, after subjected under LSS or NG condition for 1.5 h and 5 h at 15 rpm. The start inoculum at 0 h was maintained at OD 610 nm ≈ 0.6. IW = intestinal water, SF = M-SHIME feed

Shear Stress Subgroup SCFAs Concentration (mean ± stdev in mg/L) Difference of Acetate

Acetate Propionate Butyrate Lumen - Inoculum (mg/L)

NG 1.5 H Inoculum 511.61 ± 8.94 157.09 ± 1.17 658.63 ± 11.98 2.55

Lumen 514.16 ± 4.21 142.07 ± 1.21 606.61 ± 6.93

Mucin - - 62.11 ± 1.07

NG 5 H Inoculum 429.00 ± 6.17 266.65 ± 8.08 571.01 ± 16.12 12.24

Lumen 441.25 ± 20.07 240.92 ± 6.05 513.39 ± 8.17

Mucin - 28.54 ± 0.30 64.18 ± 0.50

LSS 1.5 H Inoculum 506.41 ± 16.41 155.13 ± 3.74 661.71 ± 15.84 18.89

Lumen 525.30 ± 15.89 144.26 ± 5.32 622.30 ± 24.03

Mucin - - 53.49 ± 1.32

LSS 5 H

Inoculum 486.30 ± 39.52 287.98 ± 15.37 607.70 ± 18.77 42.49

Lumen 528.79 ± 21.76 263.01 ± 10.24 546.86 ± 18.06

Mucin - 23.41 ± 0.41 52.76 ± 0.23

33

Table 4-4 Lactate production of L.reuteri (mean ± stdev in mg/L) in the medium containing IW+SF, after subjected under LSS or NG condition for 1.5 h and 5 h at 15 rpm. The start inoculum at 0 h was maintained at OD 610 nm ≈ 0.6. IW = intestinal water, SF = M-SHIME feed

Shear Stress Lactate Concentration (mean ± stdev mg/L) Difference of Lactate (mg/L)

Inoculum Lumen Mucin Lumen - Inoculum

NG 1.5 H 129.47 ± 4.20 180.85 ± 3.30 11.99 ± 0.80 51.37

NG 5 H 87.19 ± 1.59 146.2 ± 6.11 14.72 ± 1.33 59.01

LSS 1.5 H 136.13 ± 1.94 161.8 ± 5.45 9.28 ± 0.56 25.67

LSS 5 H 107.46 ± 2.50 175.88 ± 5.38 14.87 ± 021 68.42

4.2 Investigation of the Effect of Low-fluid Shear on Adherent-Invasive Escherichia coli

These experiments were designed as a comparative study to L. reuteri to investigate the effect of LSS and NG shear stress on growth, mucin adhesion capacity as well as metabolic activity of Adherent-Invasive Escherichia coli in the proposed enriched intestinal water medium with the addition of SHIME feed. To this end, a growth and mucin adhesion assay was carried out on AIEC after exposure to LSS or NG condition for t1.5 and t5 incubation time in the RWV (Fig. 4-5). The bacterial concentration in the inoculum and lumen was counted based on eq. 3, while the bacterial concentration in the mucin was obtained after corrected based on eq. 4. However, unlike the results obtained from L. reuteri experiments, no prominent changes can be distinguished from both tests carried out on AIEC.

Conclusion:

The findings from this experiment have strengthened the previous findings and indicate that L. reuteri has better mucin adhesion capacity under LSS as compared to NG. However, no significant differences were obtained for the growth assay. Interestingly, SCFAs and lactate analysis displayed an increase in acetate and decrease in lactate under LSS as compared to NG at 1.5 h incubation. Yet, after 5 h incubation, a higher concentration of acetate and lactate under LSS was observed. Moreover, the results from SCFAs and lactate have shown that L. reuteri experienced a slower metabolic activity for conversion of sugars to lactate from 0 h to 1.5 h under LSS as compared to NG, but its activity increased in the time frame 1.5 h to 5 h. Meanwhile, L. reuteri has displayed faster metabolic activity for the conversion of sugars to acetate from 0 h to 5 h under LSS. Further observations have suggested that L. reuteri tended to produce more lactate than acetate under NG as compared to LSS.

34

Figure 4-5 Histogram of (1) Mucin adhesion capacity (% of mean ± stdev CFU/mL) of AIEC to mucin-agar beads (2) Flow Cytometry counts of AIEC (mean ± stdev log CFU/mL) in the medium containing IW+SF after subjected to LSS or NG condition for t1.5 and t5 at 15 rpm. The start inoculum at 0 h was maintained at OD 610 nm ≈ 0.7. IW = intestinal water, SF = M-SHIME feed, Bars indicates the standard errors. Data represent the mean of three replicates (n = 3).

In addition, SCFAs and lactate analysis was carried out to determine whether there was a different metabolic activity pattern of AIEC after subjected to LSS or NG condition for t1.5 and t5 at 15 rpm. The results from SCFAs analysis as presented in Table 4-5 of AIEC has shown contrary findings as the SCFAs analysis from L. reuteri incubations. Considering the obtained averages and standard deviations, incubation of AIEC primarily showed a redistribution of SCFAs (derived from the intestinal water medium) from inoculum (t = 0 h) into lumen and mucin with lower proportion of acetate under LSS as compared to NG after 1.5 h incubation. Interestingly, different results were obtained after incubation for 5 h, the SCFAs analysis showed significant depletion of acetate under NG and in contrast showed significant increase in acetate under LSS. Detailed observations from SCFAs analysis of AIEC are presented in Appendix. 2

0.00%

0.20%

0.40%

0.60%

0.80%

LSS 1.5 H LSS 5 H NG 1.5 H NG 5 H

Mu

cin

AD

he

sio

n (

%)

Shear Stress

% Mucin Adhesion

Adherent Invasive Escherichia coli

RWV Medium IW+SF

-

2

4

6

8

10

LSS 1.5 H LSS 5 H NG 1.5 H NG 5 H

Log

CF

U/m

L

Shear Stress

Log CFU/mL

Adherent-Invasive Escherichia coli

RWV Medium IW+SF

Inoculum

Lumen

Mucin

1

2

35

Table 4-5 SCFAs production of AIEC (mean ± stdev in mg/L) in the medium containing IW+SF, after subjected under LSS or NG condition for 1.5 h and 5 h at 15 rpm. The start inoculum at 0 h was maintained at OD 610 nm ≈ 0.7. IW = intestinal water, SF = M-SHIME feed

Shear Stress Subgroup SCFAs Concentration (mean ± stdev in mg/L) Difference of Acetate

Acetate Propionate Butyrate Lumen - Inoculum (mg/L)

NG 1.5 H Inoculum 423.00 ± 55.07 252.33 ± 28.94 546.67 ± 54.28 26.00

Lumen 449.00 ± 7.00 253.67 ± 5.13 546.67 ± 10.97

Mucin - 28.67 ± 1.15 66.00 ± 1.73

NG 5 H Inoculum 435.00 ± 24.58 249.67 ± 9.87 544.33 ± 11.93 2.00

Lumen 437.00 ± 23.07 231.67 ± 10.02 504.67 ± 10.26

Mucin - 25.33 ± 0.58 60.33 ± 1.15

LSS 1.5 H Inoculum 435.67 ± 17.67 259.00 ± 6.08 562.00 ± 9.54 2.33

Lumen 438.00 ± 22.65 243.00 ± 12.29 526.67 ± 26.63

Mucin - 22.33 ± 0.58 54.00 ± 1.00

LSS 5 H

Inoculum 490.67 ± 9.07 277.00 ± 2.00 588.00 ± 13.45 47.00

Lumen 537.67 ± 10.69 268.33 ± 8.39 562.00 ± 24.52

Mucin - 23.41 ± 0.41 58.00 ± 2.00

Similarly, Lactate analysis data presented in Table 4-6 has displayed contrary findings as obtained in the experiment of L.reuteri. No significant difference was observed on lactate produced by AIEC from 0 h to 1.5 h under LSS or NG. However, AIEC has shown lower production of lactate from 1.5 h to 5 h under LSS and sharp increase of lactate proportion under NG.

Table 4-6 Lactate production of AIEC (mean ± stdev in mg/L) in the medium containing IW+SF after subjected under LSS or NG condition for 1.5 h and 5 h at 15 rpm. The start inoculum at 0 h was maintained at OD 610 nm ≈ 0.7. IW = intestinal water, SF = M-SHIME feed

Shear Stress Lactate Concentration (mean ± stdev mg/L) Difference Lactate (mg/L)

Inoculum Lumen Mucin Lumen - Inoculum

NG 1.5 H 81.02 ± 10.06 181.38 ± 25.73 20.10 ± 2.58 100.36

NG 5 H 235.18 ± 30.84 425.52 ± 49.71 34.10 ± 4.57 190.34

LSS 1.5 H 196.44 ± 22.34 297.48 ± 33.92 12.03 ± 1.45 101.05

LSS 5 H 284.87 ± 38.20 405.63 ± 60.13 16.79 ± 3.58 120.76

Conclusion:

In contrast to L. reuteri in terms of SCFAs and Lactate analysis results, AIEC have shown lower production of lactate under LSS from 1.5 h to 5 h. On the other hand, AIEC also have shown lower production of acetate under LSS as compared to NG from 0 h to 1.5 h. Yet, this acetate proportion was increased prominently from 1.5 h to 5 h under LSS in contrast to NG which possessed a depletion of acetate. Further observations have suggested that AIEC tended to produce more lactate than acetate under NG as compared to LSS. Unlike the experiments with L. reuteri, it is however not possible to make a conclusion for AIEC as regards the growth and mucin adhesion potency.

36

4.3 Investigation of the Effect of Low-fluid Shear on Complex Microbial Community

In this chapter, the effect of low-fluid shear to the microbial community was investigated in order to provide a better insight on how the microbial community that has shaped the colon will behave under LSS. To investigate this further, a growth assay was conducted by means quantification of total bacterial counts using flow cytometry after exposed to LSS or NG condition at different time point. The bacterial concentration in the inoculum and lumen was counted based on eq. 3. Furthermore, the microbial community was monitored on the basis of their metabolic activity (SCFAs and Lactate analysis) as well as DNA-based fingerprinting analysis (DGGE).

The first experiment was conducted at 5 point time analysis namely: t0 h, t1.5h, t5h, t10 h, t15 h, and t24 h under LSS to get a better picture at which time point the microbial community shows higher activity visually (in terms of gas production) or based on the analysis results. The results from Flow Cytometer total bacterial counts (Fig. 4-6-1) showed a trend of increases in the total number of bacteria at time point of t1.5 - t5 - t10 and reached a relatively stable growth started at time point of t10 until t24. Similarly, SCFAs and Lactate analysis (Fig. 4-6-2) also showed prominent increases in their concentration at the same time point. These results were also supported by visual observations, in which it was observed an increase of gas formation started at time point of t1.5 - t5 - t10. The observed gas formation was less frequently seen at time point of t10 - t15 - t24. As indicated by concurrent results above, the microbial community showed higher activity in terms of growth and metabolic activity between time point’s t1.5 and t10. These observations were considered to be used in further experimental design and were set at time point of t1.5, t5 and t8 to obtain a more detailed view.

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Figure 4-6 Line Charts of (1) Flow Cytometry counts of microbial community (mean ± stdev log CFU/mL) after subjected to LSS or NG condition at 15 rpm for different time point t0 – t1.5 – t5 – t10 –t15 – t24. (2) SCFAs and Lactate production of microbial community (mean ± stdev in mg/L) after subjected to LSS or NG condition at 15 rpm for different time point t0 – t1.5 – t5 – t10 –t15 – t24. Data represent the mean of three replicates. Bars indicates the standard errors (n = 3).

The next experiments were designed to further investigate the effect of LSS and NG towards microbial community from different sample conditions at time point t0 – t1.5 – t5 – t8 and were termed as experiment (1), (2), and (3) respectively. Similar result to LSS at 24 h experiment was obtained based on the average results of 3 experiments carried out in growth assays (Fig. 4-7). The microbial community showed higher increases in total bacterial counts under LSS as compared to NG.

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Figure 4-7 Line Charts of Flow Cytometry (mean ± stdev log CFU/mL) after subjected to LSS or NG point t0 – t1.5 – t5 – t8 from different sample condition experiment 3, (4) average total bacterial counts CFU/mL) from 3 experiments. standard errors (n = 3).

Interestingly, similar findings were Fig. 4-8. Here, microbial communities were observed producand butyrate) under NG as compared to LSS despite of derived from the samples. On the other hand, observed results from Lactate analysis (shown more lactate produced under LSS as compare

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experiments. Data represent the mean of three replicates. Bars indicates the

similar findings were obtained from SCFAs analysis of 3 experiments as presented in ommunities were observed producing more SCFAs

and butyrate) under NG as compared to LSS despite of the different condition On the other hand, observed results from Lactate analysis (

shown more lactate produced under LSS as compared to NG.

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of microbial community rpm for different time

2) experiment 2, (3) of microbial community (mean ± stdev log

Data represent the mean of three replicates. Bars indicates the

analysis of 3 experiments as presented in s (acetate, propionate,

different condition of sampling time On the other hand, observed results from Lactate analysis (Fig. 4-9) have

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Figure 4-8 Line Charts of SCFAs production of microbial community (mean ± stdev in mg/L) after subjected to LSS or NG condition at 15 rpm for different time point t0 – t1.5 – t5 –t8 from different sample condition (1) experiment 1, (2) experiment 2, (3) experiment 3, (4) average SCFAs production of microbial community (mean ± stdev log CFU/mL) from 3 experiments. Data represent the mean of three replicates. Bars indicates the standard errors (n = 3).

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Figure 4-9 Line Charts of Lactate production of microbial community (mean ± stdev in mg/L) after subjected to LSS or NG condition at 15 rpm for different time point t0 – t1.5 – t5 –t8 from different sample condition (1) experiment 1, (2) experiment 2, (3) experiment 3, (4) average Lactate production of microbial community (mean ± stdev log CFU/ml) from 3 experiments. Data represent the mean of three replicates. Bars indicates the standard errors (n = 3).

To further investigate the behavior of microbial community with respect to their metabolic activity by using DNA profiles comparison, DGGE analysis was carried out to examine whether the microbial community has shifted during the experiment under LSS or NG for 8 H. For this purpose, Comparison of DGGE profiles for total microbial community containing (16S rRNA) Ribosomal Ribonucleic acid genes were amplified from luminal samples after 0 h and 8 h incubation under LSS or NG. The similarity of 3 biological and 3 technical phylogenetic samples was presented in percentages as calculated with a band position and intensity based Pearson correlation. A given data from Bionumerics have shown a shift in microbial community in experiment (1) after 8 h incubation regardless of the type of the shear stress. However, experiment (2) and (3) have shown more similarity (≈ 90%) in their composition before and after 8 h incubation regardless of the condition of a given shear stress. Overall, from the results of LSS and NG experiments, there are slightly decreases

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in percentage of similarity of LSS experiment as compared to NG. However, it is not possible from the provided results (Fig. 4-10) and (Fig. 4-11) to observe a shift in the microbial community profiles due to insufficient time for the microbial community divergence (8 h).

Figure 4-10 Bionumerics cluster analysis using Pearson correlation coefficients and UPGMA clustering algorithm (3.5% - 84.4%) of DGGE Ingeny 338-518 results of microbial community extracted DNA (16s rrna primer) after subjected to Normal Gravity experiment rotated for 8 h at 15 rpm from different sample condition namely (1) experiment 1, (2) experiment 2, (3) experiment 3. % = represent percentage of dendogram similarity of microbes lineages cluster.

1 = 56% similarity

2 = 90.7 % similarity

3 = 95.7 % similarity

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Figure 4-11 Bionumerics cluster analysis using Pearson correlation coefficients and UPGMA clustering algorithm (3.5% - 84.4%) of DGGE Ingeny 338-518 results of microbial community extracted DNA (16s rrna primer) after subjected to Low- fluid Shear experiment rotated for 8 h at 15 rpm from different sample condition namely (1) experiment 1, (2) experiment 2, (3) experiment 3. % = represent percentage of dendogram similarity of microbes lineages cluster.

1 = 35.5% similarity

2 = 83.9 % similarity

3 = 93.9 % similarity

Conclusion:

In contrast to previous findings from L. reuteri and AIEC, the microbial community has shown increases in their total bacterial counts under LSS as compared to NG. Furthermore, with respect to SCFAs and Lactate analysis results, once again microbial community exhibit similar metabolic activity as compared to L. reuteri and AIEC. These microbial communities have shown lower production of SCFAs and higher production of Lactate under LSS as compared to NG.

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5 Discussion and Conclusion

5.1 Introduction

The human gut possesses numerous micro-environment challenges which microbes must be able to withstand. Within the colon itself, various micro-environments are present and act as a physical barrier for bacterial colonization. These barriers include interactions with epithelial cell surfaces, changes in nutrients level, variations in the viscosity of the mucus layer, and the luminal fluid-flow (Macfarlane and Dillon, 2007). The latter are known to significantly contribute in generating a fluid shear stress, which decreases gradually from the lumen to the proximity in the intestinal epithelial cell walls (Pearson and Brownlee, 2010). Moreover, the presence of a mucus layer and microvilli in the vicinity of the epithelial cell provide a ‘low-fluid shear’ environments for the microbes, which is different to those encountered in the lumen (Pearson and Brownlee, 2010; Guo et al., 2000).

On the other hand, bacteria must be able to adapt and proliferate under a variety of environmental conditions in the human body, including low-fluid shear environments (Nickerson et al., 2004; Castro et al., 2011). These environments have shown a correlation with distinctive changes in stress evoked rpos gene expression, which further implement the changes in physiology, virulence, and bacterial growth rate (Nickerson et al., 2003). Several studies have demonstrated that some of the bacteria exhibited modulation of defense against low-fluid shear environments to maintain their normal growth rates (Nickerson et al., 2003; Nickerson et al., 2004; Avvisato et al., 2007; Rosado et al., 2009; Lecuyer et al., 2011; Castro et al., 2011). Based on all the studies mentioned, it is clear that ‘low-fluid shear’ is perceived by the bacteria as a stress factor. However, it must be noted that all the studies conducted to mimic these low-fluid shear environments were only performed on pathogens. Meanwhile, it has been known that most of the bacteria inhabiting the human gut mucosal surfaces are mainly composed of commensal microbes (Zoetendal et al., 2002). This microbial community was found to play an important role in human health and diseases (Sekirov et al., 2010). Consequently, it is of particular interest to conduct a study to evaluate the effect of low-fluid shear on the gut bacteria, particularly on bacteria which inhabit the mucosa overlying the epithelial cells of the colon. Therefore, in this present study, the effect of low-fluid shear was examined by utilizing a rotating wall vessel bioreactor that provides a relevant rheological characteristic of brush border epithelial cell microvilli.

Based on the obtained results, the main findings of this thesis will be discussed. First, the effect of low-fluid shear on Mucin adhesion capacity and growth proliferation of Lactobacillus reuteri and Adherent invasive Escherichia coli (AIEC) are discussed, followed by the effect of low-fluid shear on the survival of L. reuteri in the presence of stress factor linoleic acid. Next, the effect of low-fluid shear on the primary metabolic activity of L. reuteri and AIEC are discussed further with respect to SCFAs and lactate ratios. Finally, the effect of low-fluid shear on the growth kinetics, primary metabolic activity and DNA based profiles in the presence of complex microbial communities are discussed.

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5.2 Results Interpretation

5.2.1 The effect of low-fluid shear on mucin adhesion and growth proliferation

Bacteria are able to encode molecular mechanisms to sense and respond to a mechanical stimulus (Isberg and Barnes, 2002). These mechanisms include their ability to sense changes in membrane deformation and alter adherence properties in response to fluid-shear stress (Poolman et al., 2002; Thomas et al., 2002). As previously mentioned, the flow induced by intestinal peristalsis along the gut surfaces creates a shear stress and tend to remove everything on it, including the bacteria which adhere to the epithelial cell surfaces (Sokurenko et al., 2008). Meanwhile, the bacterial colonization is often facilitated by the ability of bacteria to attach to the surface of epithelial cells and further developed to form a biofilm (Isberg and Barnes, 2002; Thomas et al., 2002; Sonnenburg et al., 2004). Thus, resisting removal by means of adhesion capacity under fluid shear stress is considered as an important characteristic for bacterial colonization (Sokurenko et al., 2008). A study by Thomas et al. (2002) revealed that the surface adhesion capacity of the bacteria is often observed in the presence of shear stress. Meanwhile, a study performed by Thomas (2008) had postulated that the strongest adhesion under flow is expected to occur at the lowest fluid shear stress where the forces reach the weakest point, with the rationale that bigger forces are needed to break the adhesion bonds (Evans and Ritchie, 1997). Also, the dragging forces are generally increased in accordance with increases in flow velocity and viscosity (Thomas et al., 2002). Moreover, the results of Thomas et al. (2002) have shown that some pili promotes efficient adhesion only when they are subjected to a flow-regulated adhesion that induce a shear stress of 0.02 dynes/cm2, or when they are subjected to mucosa overlying the epithelium which maintains a slower flow rates.

A review by Sengupta and colleagues (2013) gave an outline that Lactobacillus sp are known for their characteristic to adhere and interact with the epithelium and mucus layers in order to promote colonization. The results from the current study presented in Fig. 4-2 and Fig. 4-4 (1), provided clear observations that the mucin adhesion capacity of L. reuteri to mucin agar (%) was enhanced under low-fluid shear compared to the normal-fluid shear conditions, regardless of the type of the medium used or the availability of the nutrients. Although no prior study has been done to justify the influence of low-fluid shear on adhesion properties of commensal bacteria, in particular L. reuteri, yet, several study has revealed a direct link of the modification of cell surface structure and its composition of Lactobacillus sp. to their adhesion properties in response to stress factors encountered in the gut (Kravtsov et al., 2008; Buck et al., 2009; Buck et al., 2005; Servin, 2004; Granato et al., 1999). These stress responses of Lactobacillus sp is dependent on the strain, species, and the type of the stress (Sengupta et al., 2013). By considering that the adhesion is generally expressed through two pathways. Specific adhesion occurs via adhesins on the bacterial cell binding to a receptor on the epithelial cells. On the other hand, non-specific adhesion occurs by hydrophobic/polymeric or electrostatic interaction. These non-specific adhesions may not significantly affect the colonization of bacteria overlying the mucus epithelium in vivo, but they may be important in the colonization of the luminal content considering that these adhesions may enhance substrate uptake and alter growth proliferation (Suskovic et al., 2001). Therefore, two explanations can be hypothesized with respect to the observed enhanced adhesion properties of L. reuteri under low-fluid shear.

The First explanation for the observed enhanced adhesion of L. reuteri under low-fluid shear might be due to an activation of adhesion related genes of mucus binding protein (mubs) present in the L. reuteri cell surface. This hypothesis is sustained by several reports that implicate the observed effect of low-fluid shear on pathogenic bacteria in previous studies. Such findings obtained

45

from the study on S. aureus and P. aeruginosa, have revealed that low-fluid shear environments were correlated with decreased hfq global regulator expression which in their turn can be associated to bacterial adherence and biofilm formation (Kim et al., 2013; Castro et al., 2011; Rosado et al., 2009). Similarly, it has been observed that PapG adhesins (Nilsson et al., 2006) and fimH adhesins (Thomas et al., 2002) were also enhanced the bacterial adhesion of E. coli under fluid shear. Furthermore, a second explanation can be proposed that the observed increase in adhesion of L. reuteri under low-fluid shear may also occur by modifying the interactions of cell surface components which subsequently result in a change in the cell surface structures. This hypothesis is might be best suited to explain the obtained results according to the visual observations of biofilm formation as presented in Fig. 4-1 when L. reuteri was grown in nutrient rich medium MRS for 20 hours under low-fluid shear.

Although, the findings from current study could not explain in a metabolic sense, the mechanism by which L. reuteri respond to a low fluid-shear stress and further produces biofilm, yet several suggestions based on previous studies can be considered to explain this biofilm formation . According to a review by Sengupta et al. (2013) the cell surface of Lactobacillus sp consists of peptidoglycan, cell wall teichoic acids, lipoteichoic acids, exo-polysaccharides (EPS), protein filaments (pili), and the remaining proteins which overly the surface of the bacterial cell (S-layer protein or collagen binding protein). All of the mentioned cell surface substrates above have important roles in determining the hydrophobicity of the cell surfaces, provide electrostatic interactions, mediates the interactions with the environment components as well as correlated with the host binding receptor (Danne and Dramsi, 2012; Lebeer et al., 2012; Ciszek-Lenda et al., 2011; Lebeer et al., 2011; Bath et al., 2005; Rosenberg and Kjelleberg, 1986). Nevertheless, based on the literature study, it can be assumed that the collagen binding-layer protein (Cnbp) and EPSs are might be involved in the observed biofilm formation of L. reuteri and mucin adhesion capacity of L. reuteri in different media. These assumptions were undertaken by taking into consideration that: (1) collagen binding protein is L. reuteri strain specific, in which the bacteria itself are embedded in the extracellular polymeric substances matrix (Sengupta et al., 2013; Aleljung et al., 1994). (2) Secretion of EPS were found to be higher in L. reuteri as compared to other Lactobacillus sp strain and these EPS were strongly associated with the polymeric interactions binding strength of the bacteria to the epithelium cell surface as it can promotes surface charge and hydrophobicity (Ciszek-Lenda et al., 2011; Wang et al., 2006; Rickard et al., 2003; Tsuneda et al., 2003). The latter reason was supported by the research of Ramasamy and Zhang (2005) which examined the EPS secretion of a biofilm quantitatively under fluid shear stress and found that the shear stress cause a drastic increase of EPS-polysaccharides in the biofilm. This increase in EPS secretion is correlated to increase in adhesion capacity as a short term occasion (Liu and Tay, 2002). Similarly, a study by Menniti et al. (2009) had examined the relation between the level of shear and extracellular polymeric substances. They revealed that high fluid shear produced lower concentrations of EPS which corresponds to a decrease in soluble EPS production. The finding by Menniti et al. (2009) may be provides an explanation to the visual observation of the biofilm formation in the present study in which the obtained biofilm was less dense and easily breakable.

Additionally, by theory, the mucosal biofilm formation is known to be widely attributed to the presence of micro-aerophilic conditions, the presence of fluid shear stress, the excess of nutrients and its homogeneous distribution, extracellular polymeric substances (EPS), host - microbes interaction, as well as microbes – microbes interaction, or a combination of the parameters (Marzorati et al., 2011). It must be noted that the nutrient availability also plays an important role in changing the expression levels of multiple stress genes under low-fluid shear (Arunasri et al., 2013; Vukanti and

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Leff, 2012; Vukanti et al., 2012; Rosado et al., 2009; Vukanti et al., 2008; Tucker et al., 2007; Nickerson et al., 2004; Baker et al., 2004; Wilson et al., 2002a). In fact, based on the results of the present study, it can be proposed that L. reuteri have a slightly more efficient utilization of nutrients in MRS-broth in comparison to intestinal water with respect to their capacity to adhere to mucin agar beads. Thus, in spite of all the mentioned studies above which have confirmed the changes in adhesion gene expression, additional investigation still needs to be conducted to assess the adhesins gene expression (Mubs) of L. reuteri under low-fluid shear conditions in order to support the above hypothesis. Moreover, further investigation still needs to be performed to assess the expression of EPS associated with biofilm formation of L. reuteri under low-fluid shear.

The shear-enhanced adhesion properties have important implications for pathogens (Nickerson et al., 2004). Unfortunately, based on the obtained results in the present comparative study of pathogenic AIEC as presented in Fig. 4-5 (1), it is not possible to conclude the effect of low-fluid shear on mucin adhesion capacity of AIEC to the mucin agar. Additional test are needed to distinguish the effect of low fluid shear on AIEC adhesion properties as compared to normal-fluid shear conditions. A previous study by Allen et al. (2008) has demonstrated increased adherence when AIEC was grown under low-fluid shear due to an increase in Rpos-regulated proteins expression. With respect to the obtained results, it can be argued that (1) the presence of a functional flagellum influences the rates of detachment similar to those observed by Thomas et al. (2002). (2) Since E. Coli were known to easily proliferate in minimal medium (Arunasri et al., 2013), it can also be reasoned that the variability in adhesion capacity of AIEC could be caused by nutrient rich medium which offset the possibility to distinguish differences between low fluid shear and normal-fluid shear.

Furthermore, a number of studies have demonstrated a range of bacteria grown under batch culture of low-fluid shear conditions yields higher final bacterial concentrations, yet this is not the case in the present study. The observed increase in mucin adhesion capacity and the tendency for biofilm formation of L. reuteri were not followed by similar results with regards to the growth proliferation. No significant difference on growth proliferation was obtained in the present study that can be used to properly distinguish the effect of low-fluid shear as compared to normal-fluid shear. As presented in Table 4-1 and Fig. 4-4 (2) L. reuteri demonstrated a similar final bacterial concentration under low-fluid shear as compared to normal-fluid shear, irrespective of the type of the medium used, namely MRS, intestinal water, and intestinal water enriched with SHIME feed. Similar results were obtained during AIEC experiments using intestinal water media enriched with SHIME feed as presented in Fig. 4-5 (2). No significant difference can be observed in growth proliferation. The obtained result is similar to a study conducted by Allen et al. (2008), which revealed no significant effect on AIEC O83:H1 after being grown for 12 h in minimal medium cultures under low-fluid shear condition, compared to controls. It can be argued that different bacteria exhibit different response to fluid shear conditions and all of the mechanisms of response triggered were to keep their normal bacterial growth. With respect to growth proliferation, the present findings are the same to those in the study by Rosado et al. (2009) on S. aureus and Guadarrama et al. (2005) on P. aeruginosa. Xiao and colleagues (2010) have observed a reduction of Microcystis aeruginosa growth after being subjected to low-fluid shear for 6 days due to lesser utilization of the available nutrient, which implies that the bacteria tends to possess a mechanism of response to maintain their normal growth as long as possible. Moreover, by theory, the growth proliferation under low-fluid shear is strongly influenced by the mobility of the bacteria itself and the reduction of extracellular mass transfer between bacteria. The mobility of the bacteria should be absent under low-fluid shear with the exception to flagellated bacteria (Benoit and Klaus, 2007). This motility offsets the bacterial cell deposition as it disrupts the

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laminar flow conditions (Benoit and Klaus, 2007). The motility of bacteria is thought to be the reason for the lack of significant differences in growth proliferation observed from AIEC LF82 in the present study (Keita and Soderholm, 2012). However, this assumption is still needs further investigation.

Lastly, based on the obtained results from total bacterial counts as presented in Table 4-1 and Fig. 4-4 (2), the growth of L. reuteri appears to be enhanced with the presence of mucin agar beads irrespective of the medium and the applied shear stress. In this respect, the obtained results extend to previous studies that have demonstrated increased expression of mucin genes and thereby induce mucin secretion in the presence of Lactobacillus sp (Lebeer et al., 2008) which further provide additional nutrient substrates for a bacterial growth.

By taking together all these findings, it can be summarized that fluid shear stress has a significant effect on mucin adhesion of L. reuteri but not on growth proliferation. The biofilm formation of L. reuteri could be due to an excessive secretion of EPSs. Although the adhesion capacity of AIEC in the current study is still questionable, literature data mentions that the adhesion of AIEC was enhanced under low-fluid shear (Allen et al., 2008). In respect to growth proliferation of AIEC, both findings from the obtained result and literature data have shown no significant effect between low-fluid shear and normal-fluid shear. Furthermore, it is most likely that a change in growth proliferation in response to low-fluid shear conditions occurs on a strain-specific basis.

5.2.2 The effect of low-fluid shear on the inactivation of L. reuteri in the presence of LA

Several studies have been performed to assess the resistance of different bacteria under low-fluid shear conditions. Findings from these studies indicate that low-fluid shear does not induce general resistance to all environmental stressors and affects resistance differently depending on the species and the strain of the bacteria (Nickerson et al., 2004). Salmonella typhymurium demonstrated decreased resistance to oxidative stress, while also demonstrating increased resistance to acid, osmotic, and thermal stress under low-fluid shear as compared to normal-fluid shear (Nickerson et al., 2000; Wilson et al., 2002a). Growth of E. coli K-12 under LSS has shown an increase in resistance to osmotic and acid stresses (Lynch et al., 2004). Meanwhile, AIEC O83:H1 has shown a significant increase in thermal stress and oxidative stress resistance under Low-fluid shear conditions as compared to normal-fluid shear controls (Allen et al., 2008). Furthermore, low-fluid shear cultures of S. aureus have experienced more resistance to antibiotic stress (Castro et al., 2011). However, no study has been conducted on commensal microbes specifically L. reuteri under low-fluid shear in the presence of other stressors, in order to better clarify the finding in the following obtained results.

In this present study, as presented in Fig. 4-3, the effect of linoleic acid at different concentrations (10 and 100 µg/mL) on the inactivation of L. reuteri has been assessed. Subsequently, this finding has revealed that L. reuteri possessed higher inactivation rates in the presence of linoleic acid at concentration 100 mg/L and generates a 1 log difference in inactivation under low fluid shear as compared to normal-fluid shear. Although, it should be noted that the inactivation of L. reuteri in the presence of linoleic acid at concentration 10 mg/L resulted in similar inactivation as compared to those in controls. It can be assumed that the sensitivity of L. reuteri under low-fluid shear condition may occur due to the substrate availability which is embedded with linoleic acid. This in turn provides better homogeneity in the distribution of the nutrient as well as in the antimicrobial substances of linoleic acid. This assumption is strengthened by the study done by Kacena et al. (1999), which found that the relative densities of the cells does not exist under low-fluid shear, thus enabling better nutrient uptake. Based on the obtained results in the present study it can be further concluded, that L. reuteri

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has experienced a higher sensitivity to linoleic acid under low-fluid shear in comparison to normal-fluid shear and that the effect of linoleic acid on the inactivation of L. reuteri was increased as the concentration was increased. This assumption is in accordance with Jenkins and Courtney (2003), which revealed that lower linoleic acid concentrations resulted in a neutral effect; in contrast with higher concentration of linoleic acid which provides bactericidal effect on different Lactobacillus sp, including L. reuteri.

To summarize the findings, the low-fluid shear was perceived by L. reuteri as a stress factor, in which L. reuteri exhibits higher inactivation in the presence of other stress factors such as linoleic acid. The inactivation towards linoleic acid by L. reuteri was increased in line with increases in the concentrations of linoleic acid.

5.2.3 The effect of low-fluid shear on the primary metabolic activity production

Substantial evidence derived from multiple species of bacteria indicates that microbes undergo changes in metabolic pathways under low-fluid shear in the rotating wall vessel and implies alteration of the primary and secondary metabolites. The accumulation of certain metabolites is believed to be important for the bacteria itself to accommodate the low-fluid shear stress conditions (Nickerson et al., 2004; Brown et al., 2002). After execution of this study some general trends could be observed with regards to the primary metabolic SCFAs and Lactate analysis results. The obtained results from L. reuteri and AIEC has shown a similar trend in the metabolic activity pattern of SCFAs and lactate.

L. reuteri ATCC PTA 6475 belongs to lineage II of the L. reuteri species and it is classified as an obligate heterotrophic fermentative Lactic Acid Bacterium (LAB) which synthesize lactic acid as the major metabolic end-product (Stevens et al., 2011; Oh et al., 2010, Axelsson, 2004; Konings, 2002). In a normal condition such as an excess of sugars and limited oxygen, the glycolysis of the Embden-Meyerhof pathway resulted in one mol of hexoses converted into two mol of lactic acid at pH 5 – 6.2 (den Besten et al., 2013; Flint et al., 2012a; Flint et al., 2012b; Stevens et al., 2011; Axelsson, 2004; Torino et al., 2001). Meanwhile, they also tends to degrade the hexose sugars into ethanol, acetate, CO2, formate and succinate at lower pH 4 – 5 (Suskovic et al., 2001; Torino et al., 2001), and at the same time also converts the pentose sugars to lactate and acetate via phosphoketolase pathway (Axelsson, 2004). The acetate formation can also take a place more directly from pyruvate via pyruvate metabolism - Wood-Ljungdahl pathway, which has been reported to be active in minimum glucoses availability (Reichardt et al., 2014; den Besten et al., 2013; Flint et al., 2012a; Flint et al., 2012b; Axelsson, 2004).

Based on the theory above, L. reuteri is more likely to produce lactate as the major metabolite and acetate as their byproduct. However, contrary results were obtained after 1.5 h incubation from the present study as shown in Table 4-3 and Table 4-4. Interestingly, the SCFAs and lactate analysis has displayed an increase in acetate and decrease in lactate under low-fluid shear than that of normal-fluid shear at 1.5 h incubation. Yet, after 5 h incubation, it was observed a higher concentration of acetate and lactate under low-fluid shear. More precisely, it was observed a slightly increase in lactate final concentration under low-fluid shear. The magnitude of a lower proportion of lactate, together with higher increase in acetate proportion at 1.5 h might be occur due to a slower metabolic activity for the conversion of sugars to lactate or also might be occur due to a shift in metabolic activity pathways under low-fluid shear. As has been observed at 5 h incubation, L. reuteri was presumed to experience other metabolic mechanisms to overcome low-fluid shear conditions and in their turn able to regenerate the lack of lactate proportion. Meanwhile, L. reuteri is also presumed has displayed faster

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metabolic activities for the conversion of sugars to acetate from 0 h to 5 h under low-fluid shear. It can be further assumed that under low-fluid shear, L. reuteri undergo different metabolic pathways and tends to preserve their nutrient to maintain the energy for the normal growth. This proposed reason is in accordance with the observation from the growth assays as shown in Table 4-1 and Fig. 4-4 (2) in which L. reuteri has demonstrated a similar final bacterial concentration under low-fluid shear as compared to normal-fluid shear, irrespective of the type of the medium used. However, additional investigation is still needed in order to clarify the possibility of a shift in metabolic activity pathways under low-fluid shear conditions.

According to the metabolic pathways, Escherichia coli is known to produce excessive acetate via the repression of Acetyl-Coa synthetase activity and produced as a main metabolic activity end-product (Valgepea et al., 2010), while D-lactate was produced via pyruvate metabolism with formate as an intermediate products (Sode et al., 1999). However, with regards to the observed results, the metabolic activity seems to occur conversely. As can be seen from Table 4-5 and Table 4-6, AIEC has shown a lower production of lactate under low-fluid shear from 1.5 h to 5 h, which further implies a lower proportion of lactate after 5 h incubation. On the other hand, AIEC also has shown lower production of acetate under low-fluid shear as compared to normal-fluid shear from 0 h to 1.5 h. Yet, this acetate proportion was increased prominently from 1.5 h to 5 h under low-fluid shear in contrast to normal-fluid shear, which possessed a depletion of acetate. Further observation has suggested a rather slower metabolic activity conversion of sugars to lactate under low-fluid shear as compared to normal-fluid shear, between 1.5 h and 5 h. Most importantly, based on the observation in terms of acetate production, it can be assumed that adherent invasive Escherichia coli also experienced a slower metabolic activity conversion of sugars to acetate from 0 h to 1.5 h incubation under low-fluid shear. Yet at 5 h incubation, AIEC was presumed to experience a shift in metabolic activity pathways to overcome the low-fluid shear conditions and able to regenerate the lack of acetate proportion, in contrast to those experienced under normal-fluid shear. This assumption is supported by several observation as follow; (1) formate production was observed in IC Dionex (data were not shown) between 1.5 h to 5 h, and this formate is known as an intermediate product of the conversion from lactate to acetate. (2) It was observed smaller increases in lactate production under low-fluid shear in contrast to normal-fluid shear. These observations may indicate that the lactate conversion to acetate might be occurs. Furthermore, it can be assumed that the tendency of a slower metabolism that has been demonstrated by AIEC may occur to preserve their nutrients availability as long as possible for their normal growth. This is supported by the observation of acetate production after 5 h, wherein it was clearly observed a depletion of acetate under normal-fluid shear and increases of acetate under low-fluid shear. This proposed assumption is in accordance with the observation from growth assay as shown in Fig. 4-5 (2) in which AIEC has demonstrated a similar final bacterial concentration under low-fluid shear as compared to normal-fluid shear.

Collectively, these findings demonstrate that low-fluid shear can alter metabolic activities to different pathways but these are strain-dependent. Both findings of L. reuteri and AIEC have shown a similar trend in the metabolic activity pattern of SCFAs and Lactate. Both of L. reuteri and AIEC seems to demonstrate a slower metabolic activity from 0 h to 1.5 h incubation time and demonstrate a shift in their metabolic activity from 1.5 h to 5 h under low-fluid shear. However, an extensive study with respect to metabolic activity pathways under low-fluid shear conditions is needed in order to clarify these findings.

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5.2.4 The effect of low-fluid shear on complex microbial community

Previous studies have only focused on the effect of low-fluid shear on pure cultures. Meanwhile, it is well known that the gut microbiota have experienced complex metabolism pathways and cross feeding for the regulation of the host metabolism. The colonic fermentation produces SCFAs and lactic acid, which are important to determine the pH of the colonic lumen and implies the predominant luminal microbes in the colon. The SCFAs are generally consisted of acetate (60%), propionate (20%), and butyrate (18%) (Macfarlane and Cummings, 1991; Suskovic et al., 2001). Disturbance of the gut microbiota can also occur due to stress conditions which may affect the production of mucus and may in turn decrease the number of mucus associated microbiota such as lactobacilli and favor the enterotoxigenic strains such as E. coli (Suskovic et al., 2001). This disturbance is assumed to have an impact in the metabolic activity of the gut microbiota.

During the elaboration of the study, the primary metabolic activity of L. reuteri and AIEC were found to be affected by low-fluid shear. For this reason, it has been attempted to further confirm the effect of low-fluid shear on the primary metabolic activity within the complex microbial community. Interestingly, similar findings were deduced from SCFAs analysis of 3 experiments as presented in Fig. 4-8. In general, the results from microbial community showed a declining trend in all SCFAs proportion (acetate, propionate, and butyrate) following a low-fluid shear, irrespective of the different condition derived from the samples. On the other hand, the observed results from Lactate analysis (Fig. 4-9) have shown more lactate produced under low-fluid shear in contrast to normal-fluid shear.

Theoretically, low-fluid shear environments are known to provide laminar pattern which in turns result in a reduction of extracellular mass transfer between bacteria or less cross-feeding (Klaus et al., 2004; Kacena et al., 1999). Also the exchange of signaling molecules can be lowered. Thus, the quorum sensing of the bacteria are disrupted and the mass transfer are reduced (Klaus et al., 2004). Meanwhile, cross feeding is one of the important factors in the anaerobic fermentation process of carbohydrates within the gut (Flint et al., 2012a). As it was noted above, it can be assumed that a lower production of primary SCFAs might be occur due to less cross feeding within the complex microbial community in the gut under low-fluid shear environments. Yet, it can be also assumed that microbial community may also experience a slower metabolic activity considering higher lactate production and lower acetate production. This slower metabolic activity might be correlated to the tendency of the microbial community to preserve nutrients for their normal growth. Furthermore, it can be also assumed that the trends of metabolic activity may occur due to a shift in metabolic activity pathways within the microbial community. Nevertheless, these assumptions are still need to be clarified by further investigation in order to draw a conclusion. Moreover, it was also observed an increase in the proportion of acetate and a reduction in the proportion of butyrate regardless of the applied shear. Decreases in butyrate proportion might be due to a reduction of butyrate producers within the microbial community. Yet, this assumption could not be proven based on the obtained data.

By taking into consideration the results from SCFAs and Lactate analysis, DGGE analysis was carried out to examine whether the microbial community has shifted during the experiment under low-fluid shear or normal-fluid shear after 8 h in order to assess the behavior of microbial community in relation to their metabolic activity by comparison of DNA profiles. A given data from Bionumerics have shown a shift in microbial communities in experiment (1) after 8 H incubation regardless of the type of the shear stress. However, experiment (2) and (3) have shown more similarity (≈ 90%) in their composition before and after 8 h incubation, regardless of the condition of a given shear stress. It can be argued that the microbial community in the experiment (1) was obtained from newly SHIME experimental set-up and still experiencing a change towards a more stable composition. On the other

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hand, the microbial communities in experiment (2) and (3) were obtained from already stable microbial community. Overall, there are slightly decreases in the percentage of similarity of low-fluid shear experiment as compared to normal-fluid shear. Nevertheless, it is not possible from the provided results (Fig. 4-10) and (Fig. 4-11) to observe a shift in microbial community profiles with an argument that the time for the divergence of the microbial community (8 h) was not yet sufficient.

Lastly, interesting findings in a growth kinetic assay of microbial community (Fig. 4-7) was obtained based on the experiments that were carried out under low-fluid shear for 8 h, in comparison to growth assay results of L. reuteri and AIEC. Here, the microbial community has shown a higher increase of total bacterial concentrations under low-fluid shear as compared to normal-fluid shear. This finding is in accordance with several previous studies conducted in different bacteria species or strain under low-fluid shear, which has revealed that low-fluid shear can cause changes to bacterial growth (Benoit and Klaus, 2007; Nickerson et al., 2004; Wilson et al., 2002a; Kacena et al., 1999; Klaus et al., 1997). As it was reported from previous studies, the general tendency of the bacterial growth under low-fluid shear is a reduced lag phase, a much higher stationary concentration, and an increased in a final bacterial concentration (Benoit and Klaus, 2007; Kacena et al., 1999; Klaus et al., 1997). The changes in bacterial growth might be occured due to a decrease in an extracellular mass transfer between the bacteria (Benoit and Klaus, 2007; Kacena et al., 1999; Klaus et al., 1997). However, as discussed earlier, it is most likely that changes in the growth kinetics in response to low-fluid shear conditions occur on a strain-specific basis.

Overall, these findings suggested that microbial community possess similar behavior with respect to metabolic activity in which they possessed lower production of primary SCFAs under low-fluid shear as compared to the observations made on L. reuteri and AIEC. It appears from the above discussion that in a low-fluid shear condition, microbial community would have to regulate its metabolic activity to maintain a balance with the applied fluid shear force to their surface through utilization of associated energy metabolites.

5.3 Conclusion

To summarize, the findings from the present study has revealed that indeed low-fluid shear is perceived by bacteria as a stress factor. This stress factor is perceived by bacteria with a different response manner. Low-fluid shear conditions have a significant effect on mucin adhesion of L. reuteri but not in the growth proliferation. The mucin adhesion capacity of L. Reuteri was enhanced under low-fluid shear. The biofilm formation of L. reuteri could be due to an excessive secretion of EPS. L. reuteri has demonstrated a higher inactivation in the presence of other stress factor like linoleic acid. The sensitivity of L. reuteri towards linoleic acid was increased in line with increases in concentration of the linoleic acid. On the other hand, the adhesion capacity of AIEC in the current study is still questionable, yet based on the literature data the adhesion of AIEC was enhanced under low-fluid shear. With respect to growth proliferation of AIEC, both findings from the obtained result and literature data have shown no significant effect between low-fluid shear and normal-fluid shear.

The results of L. reuteri and AIEC have shown a similar trend in metabolic activity with respect to SCFAs and lactic acid productions. Both L. reuteri and AIEC seem to demonstrate a slower metabolic activity in the initial phase of incubation (first 1,5 h) and further demonstrate a shift in metabolic activity pathway between 1.5 h to 5 h under low-fluid shear. Microbial community also possessed a similar behavior with respect to metabolic activity in which they demonstrated a lower production of primary SCFAs and a higher production of lactate under low-fluid shear. However, an extensive study

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with respect to the metabolic activity pathways under low-fluid shear conditions is needed in order to clarify these findings.

To conclude based on the overall findings, it is most likely that a change in the growth proliferation in response to low-fluid shear conditions occur on a strain-specific basis. Most importantly, it appears that in a low-fluid shear conditions, bacteria would have to regulate its metabolic pathways to maintain a balance with the applied fluid shear forces to their surfaces through utilization of associated energy metabolites. Under low-fluid shear, bacteria seem to have a similar trend changes in metabolic activity pathways, slower metabolic activity, and lower production of their primary metabolites. This study has provided a new insight for further investigation on the metabolic activity patterns of the bacteria under low-fluid shear conditions.

5.4 Future Experiment

During the elaboration of the study, there is three main finding that has gain an interest for further investigations. The adhesins gene expression (Mubs) and the expression of EPS associated with biofilm formation of L. reuteri still needs further investigation under low-fluid shear. Most importantly, the metabolic activity patterns of the bacteria under low-fluid shear are still not clear yet. Thus, future experiment under low-fluid shear conditions should emphasize on assessing the metabolic activity pathways and the quantification of the metabolites produced by means of the use of specific quantified feed and quantified medium nutrient source. This will further help to forecast the possible risk of physico-chemical changes brought by low-fluid shear conditions and better anticipation towards fluid shear conditions associated with disease.

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A

APPENDICES

Appendix 1. SCFAs production of L. Reuteri (mean ± stdev in mg/L) the medium containing

IW+SF, after subjected under LSS or NG conditions for 1.5 h and 5 h at 15 rpm. The start inoculum at 0 h was conditioned at OD 610 nm ≈ 0.6

Appendix 2. SCFAs production of AIEC (mean ± stdev in mg/L) the medium cotaining IW+SF,

after subjected under LSS or NG conditions for 1.5 h and 5 h at 15 rpm. The start inoculum at 0 h was conditioned at OD 610 nm ≈ 0.7