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CHARACTERIZATION OF GUARD CELL PROTEOME AND STRESS HORMONE SIGNAL TRANSDUCTION

By

MENGMENG ZHU

A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT

OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

2011

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© 2011 Mengmeng Zhu

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In memory of my beloved grandpa

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ACKNOWLEDGMENTS

My special thanks and appreciation must go to my academic committee

throughout the time that took me to complete the dissertation research. Dr. Sixue Chen,

as my supervisor and committee chair, has inspired me to work hard and make

progress in research and to keep improving myself as a scientist. His care and

understanding of me being an international student have facilitated my study and living

in the U.S.A. The other members, Dr. Alice C. Harmon, Dr. Julie A. Maupin-Furlow and

Dr. David G. Oppenheimer have generously given their expertise and encouragement in

different aspects of my research. I thank them for their great contribution and support.

Dr. Brigitte L. Simons from AB Sciex Inc., Drs. Sarah M. Assmann and Xiaofen Jin

from Pennsylvania State University, and Drs. Wen-yuan Song and Qiang Chen in Plant

Pathogen Department are acknowledged for their help and collaboration in this project.

Technical support was provided by Divisions of Proteomics, Sanger Sequencing and

Hybridoma at the Interdisciplinary Center for Biotechnology Research, University of

Florida.

I am grateful to many people who have provided help during my Ph.D. training,

especially Ning Zhu, Dr. Shaojun Dai, Marjorie Chow, Dr. Cecilia Silva-Sanchez, Dr.

Yan He, Jennifer Parker, Yazhou Chen, Carolyn Diaz, and other lab members and all of

my friends. My parents, Guohua Zhu and Mei Feng, and my roommate Dr. Qiang Chen

are specially thanked for their encouragement and emotional support.

This work was funded by a faculty start up fund from University of Florida, the

National Science Foundation (MCB 0818051) and the National Institute of Health

(1S10RR025418-01) to Sixue Chen. My thanks also go to the Ph.D. program of Botany

in Biology Department, University of Florida, for providing financial support.

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TABLE OF CONTENTS page

ACKNOWLEDGMENTS .................................................................................................. 4

LIST OF TABLES ............................................................................................................ 8

LIST OF FIGURES .......................................................................................................... 9

LIST OF ABBREVIATIONS ........................................................................................... 11

ABSTRACT ................................................................................................................... 13

CHAPTER

1 INTRODUCTION AND LITERATURE REVIEW ..................................................... 15

Stomata: the First Line of Plant Interaction with the Environment ........................... 15

Hormone Interactions in Guard Cells ...................................................................... 17 Abscisic Acid (ABA) Signaling Pathway in Guard Cells .................................... 17 Methyl Jasmonate (MeJA) Signaling Pathway in Guard Cells .......................... 23

Other Hormones in Stomatal Function ............................................................. 27 Regulative Mechanisms Underlying Stomatal Movement ....................................... 29

Phosphorylation/Dephosphorylation ................................................................. 29 Thiol-based Redox Regulation ......................................................................... 37

Conclusions and Project Objectives ....................................................................... 41

2 COMPARATIVE PROTEOMICS PROVIDES EVIDENCE FOR CROSSTALK BETWEEN ABA AND MEJA SIGNAL TRANSDUCTION IN GUARD CELLS ......... 50

Introduction ............................................................................................................. 50 Material and Methods ............................................................................................. 54

Plant Growth ..................................................................................................... 54 Preparation of Guard Cell Protoplasts and Mesophyll Cell Protoplasts ............ 54 Stomatal Bioassays .......................................................................................... 55

Protein Extraction, Digestion, 8-plex iTRAQ Labeling and Fractionation .......... 56 Reverse Phase HPLC and Tandem Mass Spectrometry.................................. 56

Protein Identification and Relative Quantitation ................................................ 57 Promoter Analysis and Interactive Network Assessment ................................. 58

Results .................................................................................................................... 58 Proteins Preferentially Expressed in Guard Cells Imply Functional

Differentiation of Leaf Cell Types .................................................................. 58 Guard cell isolation for proteomics ............................................................. 58 Protein identification by off-line 2D HPLC-MS/MS ..................................... 59

Identification of proteins preferentially expressed in guard cells and mesophyll cells ....................................................................................... 61

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ABA and MeJA both Induce Stomatal Closure in Canola Associated with ROS Production ............................................................................................ 63

Identification of ABA Responsive Proteins Improves Understanding of the Signal Transduction in Guard Cells ............................................................... 64

Up-regulated proteins in guard cells under ABA treatment ........................ 65 Down-regulated proteins in guard cells under ABA treatment.................... 67 Promoter analysis of the gene homologs in Arabidopsis ........................... 69

Identification of MeJA Responsive Proteins in Guard Cells Reveals Crosstalk in Plant Hormone Signaling Pathways .......................................... 71

Identification of MeJA responsive proteins in Brassica napus guard cells . 72

Promoter and functional network analysis of the homologous genes in Arabidopsis ............................................................................................. 77

Discussion and Conclusion ..................................................................................... 78

3 REDOX REGULATORY MECHANISMS IN GUARD CELL ABA AND MEJA SIGNALING PATHWAYS ..................................................................................... 119

Introduction ........................................................................................................... 119

Material and Methods ........................................................................................... 121 Plant Growth, Guard Cell Protoplast Preparation, and Hormone Treatment .. 121 Stomatal Aperture Measurement .................................................................... 122

Reactive Oxygen Species Detection in Guard Cells ....................................... 122 Protein Extraction and ICAT Labeling ............................................................ 123

Saturation DIGE Labeling, 2DE and Protein Digestion ................................... 123 Reverse Phase Nanoflow HPLC, Tandem Mass Spectrometry and Protein

Identification ................................................................................................ 125 Data Analysis ................................................................................................. 126

Results and Discussion......................................................................................... 126 B. napus Guard Cells for Redox Proteomics .................................................. 126

Guard Cell Redox Responsive Proteins in ABA Signaling ............................. 127

Redox Responsive Proteins in MeJA Signaling .............................................. 133 Common Components and Mechanisms in ABA and MeJA Signaling

Pathways..................................................................................................... 135

Complementary ICAT and Saturation DIGE Approaches for Redox Proteomics .................................................................................................. 137

Conclusion ............................................................................................................ 138

4 FUNCTIONAL CHARACTERIZATION OF A BRASSICA NAPUS SNRK2 ........... 156

Introduction ........................................................................................................... 156 Materials and Methods.......................................................................................... 158

RNA Extraction, Reverse Transcription and PCR .......................................... 158 Recombinant Protein Expression and Purification .......................................... 159 In vitro In-solution Kinase Assay .................................................................... 160

Results .................................................................................................................. 160 The Serine/Threonine Protein Kinase Belongs to SnRK2 Subfamily .............. 160

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Recombinant BnSnRK2 Requires Mn2+ for in vitro Autophosphorylation Activity with Multiple Phosphorylation Sites................................................. 161

BnSnRK2 Preferentially Phosphorylates Myelin Basic Protein and Casein in vitro ............................................................................................................. 163

In vitro BnSnRK2 Kinase Activity is Redox Regulated ................................... 164

Cysteines of BnSnRK2 Contribute to the Redox Regulation .......................... 167 Conclusions and Future Work ............................................................................... 167

5 SUMMARY AND PERSPECTIVES ...................................................................... 187

LIST OF REFERENCES ............................................................................................. 191

BIOGRAPHICAL SKETCH .......................................................................................... 222

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LIST OF TABLES

Table page 1-1 Protein components of ABA and MeJA signaling pathways in Arabidopsis

guard cells .......................................................................................................... 44

2-1 Proteins predominantly expressed in guard cells ............................................... 85

2-2 Proteins predominantly expressed in mesophyll cells ........................................ 88

2-3 List of proteins significantly up-regulated in guard cells by ABA. ........................ 94

2-4 List of proteins significantly down-regulated in guard cells by ABA. ................... 97

2-5 Sequence enriched in upstream regions of the genes encoding proteins with more than 1.5-fold change in response to ABA .................................................. 99

2-6 List of proteins significantly up-regulated in guard cells by MeJA ..................... 100

2-7 List of proteins significantly down-regulated in guard cells by MeJA ................ 104

2-8 Motif analysis of genes encoding the MeJA responsive proteins (upstream 500bp) .............................................................................................................. 107

3-1 Redox responsitive proteins identified in B. napus guard cells under ABA treatment .......................................................................................................... 140

3-2 Redox sensitive proteins identified in B. napus guard cells under MeJA treatment .......................................................................................................... 144

4-1 Primers used in this study. ............................................................................... 171

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LIST OF FIGURES

Figure page 1-1 Updated ABA signaling pathways in guard cells................................................. 46

1-2 Double negative regulatory module in the ABA signal transduction in guard cells (Umezawa et al., 2010) .............................................................................. 47

1-3 A simple model of the signaling interaction between ABA and MeJA in Arabidopsis guard cells ...................................................................................... 48

1-4 Redox-active cysteines are sensitive to oxidation .............................................. 49

2-1 Isolation of guard cell protoplasts from B. napus leaves ................................... 110

2-2 Classification of the 1458 identified proteins into molecular functions .............. 111

2-3 Representative MS/MS spectra showing protein identification and relative quantification in guard cells (iTRAQ tag 114) and mesophyll cells (iTRAQ tag 116) .................................................................................................................. 112

2-4 Scatter plot of the ratio of GC/MC at the mRNA level and protein level ............ 113

2-5 Effect of diphenyleneiodonium (DPI), catalase (CAT) and ascorbic acid (ASC) on ABA/MeJA-induced stomatal closure and H2O2 production .............. 114

2-6 Classification of ABA increased and decreased proteins into biological functions ........................................................................................................... 115

2-7 Total protein identification from complementary mass spectrometry platforms 116

2-8 Classification of MeJA increased and decreased proteins into biological functions ........................................................................................................... 117

2-9 The involvement of the MeJA responsive components in response to other stress factors .................................................................................................... 118

3-1 Complimentary approaches of saturation DIGE and ICAT used to identify redox sensitive proteins in response to the ABA or MeJA treatment. ............... 151

3-2 Functional classification of redox sensitive proteins in guard cells under ABA (A) and MeJA (B) treatment .............................................................................. 152

3-3 Example of redox protein identification using DIGE approach .......................... 153

3-4 Example of redox protein identification and cysteine mapping using ICAT approach .......................................................................................................... 154

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3-5 Venn diagram of guard cell thiol proteins responsive to ABA and MeJA identified by ICAT and saturation DIGE ............................................................ 155

4-1 Phylogenetic tree of BnSnRK2 and related kinases in green plants ................. 173

4-2 Comparison of the amino acid sequence of BnSnRK2 with sequences of other protein kinases ........................................................................................ 174

4-3 Effect of cation on SnRK2 autophosphorylation and phosphorylation activities. ........................................................................................................... 175

4-4 Optimization of Mn2+ concentrations in SnRK activity assay ............................ 176

4-5 Phosphorylation of Ser158 is required for BnSnRK2 kinase activity ................. 177

4-6 Ser154 and Ser172 are phosphorylated to maintain the BnSnRK2 activity ...... 178

4-7 SnRK2 specifically phosphorylates myelin basic protein (MBP) and β-casein in vitro ............................................................................................................... 179

4-8 Effects of H2O2, S-nitrosoglutathione (GSNO), and oxidized glutathione (GSSG) on the autophosphorylation activity of BnSnRK2 in vitro..................... 180

4-9 Effect of DTT on the autophosphorylation activity of SnRK2 treated with H2O2, GSNO (S-nitrosoglutathione), and GSSG (oxidized glutathione)............ 181

4-10 Effect of thioredoxin on the autophosphorylation activity of SnRK2 treated with GSNO and H2O2 ........................................................................................ 182

4-11 Effect of thoredoxin f, h and m on the autophosphorylation activity of SnRK2 treated with GSSG. ........................................................................................... 183

4-12 Redox titration of autophosphorylation activity of SnRK2 with DTT .................. 184

4-13 The autophosphorylation activity of SnRK2 is sensitive to the redox status ..... 185

4-14 Effect of oxidants on autophosphorylation activity of BnSnRK2 C142A mutant 186

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LIST OF ABBREVIATIONS

ABA Abscisic acid

ATP Adenosine triphosphate

bp Base pair

BSA Bovine serum albumin

cDNA Complementary DNA

DIGE Differential gel electrophoresis

DNA Deoxyribonucleic acid

DTT Dithiothreitol

EDTA Ethylenediaminetetraacetic acid

GAPDH Glyceraldehyde 3-phosphate dehydrogenase

GSNO S-nitrosoglutathione

GSSG Oxidized glutathione

h Hour

HILIC Hydrophilic interaction liquid chromatography

HPLC High performance liquid chromatography

IAM Iodoacetamide

ICAT Isotope coded affinity tag

iTRAQ isobaric tag for relative and absolute quantitation

kD KiloDalton

LB Lysogeny broth

LC Liquid chromatography

M Molarity

MeJA Methyl jasmonate

min Minute

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MS Mass spectrometry

m/z Mass to charge

NADPH Nicotinamide adenine dinucleotide phosphate hydrate

NO Nitric oxide

PAGE Polyacrylamide gel electrophoresis

PBS Phosphate buffered saline

PCR Polymerase chain reaction

ppm Parts per million

qRT-PCR Quantitative reverse transcription-polymerase chain reaction

RNA Ribonucleic acid

RNase Ribonuclease

ROS Reactive oxygen species

rpm Revolutions per minute

s Second

SCX Strong cation exchange

SDS Sodium dodecyl sulfate

SNP Sodium nitroprusside

Tm Melting temperature

TCEP Tris-2-carboxyethyl-phosphine

UV Ultraviolet

var. Variety

2D Two dimensional

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Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy

CHARACTERIZATION OF GUARD CELL PROTEOME AND

STRESS HORMONE SIGNAL TRANSDUCTION

By

Mengmeng Zhu

December 2011 Chair: Sixue Chen Major: Botany

Plants are sessile organisms on earth. During millions of years of evolution, plants

have developed elaborate mechanisms to perceive and integrate signals from various

environmental conditions. On the leaf surface, especially the lower epidermis, a

structure called stoma is formed by a pair of guard cells, which controls gas exchange

and transpiration as well as functions as the first line of defense against abiotic and

biotic stresses. It has been observed that stomatal closure can be induced by drought,

pathogens, wounding and other stresses. This is an instant defense mechanism

employed by plants to prevent further damage by exogenous factors. Abscisic acid

(ABA) is a major plant hormone that regulates leaf desiccation, seed dormancy and

germination, and it plays a role in plant stress responses. ABA synthesis is activated

upon water deficiency, and the elevated ABA level causes stomatal closure and

prevents stomatal opening to reduce water loss and cell dehydration. The key

regulatory receptor complex and other important components in the ABA signaling

pathway, such as reactive oxygen species (ROS) and cytosolic calcium ([Ca2+]cyt)

oscillation have been identified in the past decades. However, our knowledge of ABA

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signal transduction in guard cells is still far from complete. Another group of

phytohormones, jasmonates, was firstly characterized through the purification of methyl

jasmonate (MeJA) from the jasmine flower. Besides participating in the reproductive

process, jasmonates are generally believed to be important for plant defense against

insects and necrotrophic pathogens. The increased levels of MeJA induced by herbivory

and pathogen invasion have a similar effect on stomatal movement associated with

ROS production as ABA. Due to the presence of ROS as a messenger in the ABA and

MeJA signaling pathways in guard cells, crosstalk between them has been proposed,

and a signaling network involving the two phytohormones in guard cells is intriguing.

Information about protein and metabolite components in the network is largely unknown.

To address this important knowledge gap, proteomic analyses have been conducted

using canola (Brassica napus cultivar Global) guard cells to identify the protein

components responsive to the two hormones and characterize the underlying regulatory

mechanism. The proteomics data presented here not only support the crosstalk

hypothesis but also set up an stage of potential candidates for bioengineering towards

enhanced stress tolerance. Furthermore, a hormone-responsive serine/threonine

protein kinase was characterized from a biochemical perspective. The

autophosphorylation activity of the recombinant kinase is under redox regulation in vitro.

This finding highlights the phosphorylation switches in guard cell signal transduction and

a novel link between the two regulatory mechanisms, i.e., phosphorylation/dephosphory

-lation and redox regulation.

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CHAPTER 1

INTRODUCTION AND LITERATURE REVIEW

Stomata: the First Line of Plant Interaction with the Environment

The importance of water to terrestrial plants can never be over emphasized just by

simply looking at the molecular composition of a typical plant cell. Water makes up a

large portion of the cell volume, and directly participates in essential biochemical

reactions and physiological processes. However, land plants are constantly challenged

by dehydration, which led to the evolution of vascular plant structures including an

extensive root system to extract water from the soil, a low resistance pathway through

the xylem for water transport, a hydrophobic cuticle covering the leaf surface to reduce

evaporation, and microscopic stomatal structure to control gas exchange and

transpiration (Taiz and Zeiger, 2006). The need for water conservation and carbon

dioxide (CO2) uptake poses a dilemma for plants, especially when the two processes

are controlled by the same structure, stomata on leaf surface. On one hand, plants need

ready access to the atmosphere to obtain CO2 for photosynthesis, a process of organic

carbon production for growth, development and yield. On the other hand, the large leaf

surface area aggravates the problem of water loss and dehydration through stomatal

transpiration. To survive, plants must delicately modulate stomatal movement to

balance water conservation and carbon sequestration, especially under the current

challenges of climate change and global warming.

Stomata are microscopic pores located in greater numbers on the lower side of the

leaf, serving as the outward water gate and inward CO2 valve. Stomata first appeared in

terrestrial land plants over 400 million years ago (Hetherington and Woodward, 2003).

Considering the change of atmospheric components, i.e., CO2 concentration increase

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and emergence of new plant groups such as ferns and angiosperms, guard cells are

showing considerable morphological diversity. The two major distinctive types include

dumbbell-shaped guard cells typically found in grasses and a few monocots, whereas

the kidney-shaped guard cells are commonly seen in dicotyledonous plants and non-

grass monocots. It is noteworthy that the subsidiary cells are often absent in the species

with kidney-shaped guard cells, in which case the guard cells are surrounded by

ordinary epidermal cells. One of the guard cell structural features includes the

specialized alignment of cellulose microfibrils, which contributes to its function. The

microfibrils are arranged radially from the pore, making the cell girth reinforced like a

steel-belted radial tire. This organization of microfibrils offers the least resistance when

guard cells curve outward during stomatal opening (Taiz and Zeiger, 2006). In addition,

multiple ion channels, such as K+ inward- and outward-rectifying channels, Ca2+

channels and anion channels distributed on the plasma membrane and vacuole

membrane are coordinated to regulate the ion influx and efflux, thus the „turgidity‟ of

guard cells (Assmann, 1993). Furthermore, previous studies that focused on guard cells

metabolism and response to environmental signals have revealed important features of

functional differentiation of guard cells (Assmann, 1993; Vavasseur and Raghavendra,

2005). Compared to mesophyll cells, guard cells contain fewer chloroplasts with limited

structures and thus possess very low photosynthetic capability. The Calvin cycle in

guard cells only assimilates 2-4% of CO2 fixed in mesophyll cells (Outlaw and De

Vlieghere-He, 2001). In contrast, guard cells contain abundant mitochondria and display

a high respiratory rate, suggesting that oxidative phosphorylation is an important source

of ATP to fuel the guard cell machinery (Parvathi and Raghavendra, 1997). Such

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distinguished features, e.g., high activities of energy metabolism and solute transport

are consistent with the guard cell specific functions. Guard cells clearly possess a

robust machinery to perceive and transduce environmental signals and regulate

stomatal movement.

Given the fact that the guard cells play an essential role in plant terrestrial

adaptation, it is obviously important for us to understand the mechanisms within the tiny

cells for improving agricultural productivity, especifically considering our current grand

challenges of water shortage, global warming and climate change. Since guard cells do

not have plasmadesmata, the adaptive responses to the environment are thus cell-

autonomous (Sirichandra et al., 2009). These properties, together with the correlation

between stomatal closure and many environmental conditions, such as water

availability, make the stomatal guard cells an ideal system for investigating molecular

mechanisms underlying plant responses to environmental factors.

Hormone Interactions in Guard Cells

Abscisic Acid (ABA) Signaling Pathway in Guard Cells

Great effort has been made in the last decades to identify the molecular

components in abscisic acid (ABA) signal transduction in guard cells because ABA is a

well documented stress hormone in plants that regulates water conservation through

promoting stomatal closure and readjustment of cellular osmotic pressure to cope with

prolonged dehydration (Shinozaki and Yamaguchi-Shinozaki, 2007; Sirichandra et al.,

2009). ABA is a terpenoid synthesized from carotenoid precursors and is inducible by

drought, salinity and cold. ABA was first isolated from cotton and sycamore in the 1950s

but the phytohormone is now known to be conserved in all plant species (Wasilewska et

al., 2008). Besides functioning as a key player in response to drought, ABA plays

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important roles in plant developmental processes, including cell division, seed

maturation, seed dormancy and germination, and post-germination seedling growth

(Leung and Giraudat, 1998; Finkelstein and Gibson, 2002).

Water deficiency triggers ABA synthesis, accumulation, and redistribution in the

plant body, including transport from roots to shoots in xylem. In addition, drought-

induced pH increases in the apoplast favor the extracellular retention of the anionic form

of ABA, which may facilitate ABA delivery to guard cells through the efficient apoplast

pathway (Wilkinson and Davies, 2002). ABA reduces transpirational water loss by

triggering stomatal closure and preventing stomatal opening, and this modulation of

stomatal movement is associated with multiple cascades of cellular events (Figure 1-1).

Briefly, ABA is perceived by ABA receptors (Razem et al., 2006; Shen et al., 2006; Liu

et al., 2007; Ma et al., 2009; Park et al., 2009) and induces stomatal closure via

messengers that include reactive oxygen species (ROS), cytosolic Ca2+ ([Ca2+]cyt) and

pH increases (Irving et al., 1992; Allen et al., 2000; Pei et al., 2000; Murata et al., 2001).

[Ca2+]cyt increase is due to Ca2+ influx from outside of guard cells and its release from

internal stores such as endoplasmic reticulum (ER). Ca2+ influx is mediated by Ca2+-

permeable channels and prompted by ROS (Pei et al., 2000; Zhang et al., 2001). ABA-

induced ROS production relies on NADPH oxidases (nicotinamide adenine dinucleotide

phosphate-oxidase) downstream of the ABA-activated protein kinase, OPEN STOMATA

1 (OST1) (Mustilli et al., 2002; Kwak et al., 2003). ROS also promotes the synthesis of

nitric oxide (NO), which in turn elicits Ca2+ release from internal stores (Desikan et al.,

2002; Neill et al., 2002; Garcia-Mata et al., 2003; Sokolovski et al., 2005; Bright et al.,

2006). Downstream components responding to cytosolic Ca2+ increase include vacuolar

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K+-permeable channels, plasma membrane K+-influx channels and anion efflux

channels, e.g., malate, chloride and nitrate. An increase in cytosolic pH promotes the

opening of anion and K+ efflux channels in the plasma membrane (Colcombet et al.,

2005; Li et al., 2006). Guard cell volume reduction and stomatal closure occur upon

water efflux induced by K+ and anion efflux, sucrose removal, and conversion of malate

to osmotically inactive starch (Schroeder and Hedrich, 1989; MacRobbie, 1998).

Phosphatidic acid (PA) and ROS negatively regulate a protein phosphatase 2C (PP2C),

which plays a role in inhibiting anion efflux and ROS production (Leung et al., 1997;

Gosti et al. 1999; Merlot et al., 2001).

Recent advancement has revealed more ABA signaling components in guard cells

including ABA receptors. Hormone signaling must be initiated by the specific recognition

of the hormone molecules by receptors. Although the search for the ABA receptors in

plants was launched over 27 years ago since the report of ABA-binding proteins in the

plasma membrane of Vicia faba guard cells (Hornberg and Weiler, 1984), almost all the

early reported receptors are controversial. For example, the Mg-chelatase H subunit

(CHLH) was identified to be an ABA receptor in 2006 (Shen et al., 2006), but recently it

was disputed that the Mg-chelatase complex only affects ABA signaling, but not serving

the role of being a receptor (Tsuzuki et al., 2011). Nevertheless, the year 2009 marked

a real breakthrough in guard cell ABA signal transduction due to the identification of the

soluble ABA receptor, PYRABACTIN (4-Bromo-N-[pyridin-2-ylmethyl] naphthalene-1-

sulfonamide) RESISTANCE (PYR)/PYRABACTIN RESISTANCE-LIKE

(PYL)/REGULATORY COMPONENT OF ABA RECEPTOR (RCAR) family and the

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elucidation of their biochemical mode of action, so called double negative regulatory

core (Park et al., 2009; Ma et al., 2009).

One of the strategies used to isolate novel components of early ABA signaling was

to identify proteins interacting with PP2C because the PP2C ABA-INSENSITIVE 1

(ABI1) is known to function upstream of all known rapid signaling events. The dominant

negative mutant abi1-1 shows ABA-insensitive stomatal conductance (Koornneef et al.,

1989; Leung et al., 1994), whereas loss-of-function recessive mutants of ABI1 show

hypersensitivity in ABA-mediated stomatal response, leading to the conclusion that

ABI1 is a negative regulator of ABA signaling. In response to ABA, dominant abi1-1

mutants lost the ability to generate ROS, but the dominant ABA-insensitive abi2-1

mutant could generate ROS. Thus it has been proposed that ABI1 acts upstream of

ROS production and ABI2 downstream of ROS production in ABA signaling (Murata et

al., 2001). RCAR1/PYR1-LIKE9 (PYL9) was identified in a yeast two-hybrid screen

using the PP2C ABI2 as a bait (Ma et al., 2009), and a similar strategy using

HOMOLOGY TO ABI1 (HAB1) as a bait identified PYL5, PYL6, and PYL8 (Santiago et

al., 2009). With an alternative strategy, PYR1 gene was identified using chemical

genetics based on insensitivity to the synthetic ABA agonist pyrabactin (Park et al.,

2009). Purification of in vivo ABI1 complex from Arabidopsis led to the identification of

nine of the 14 PYR/PYL/RCARs as the major interactors of ABI1 in planta (Nishimura et

al., 2010). And the pyr1/pyl1/pyl2/pyl4 quadruple mutants showed a strong ABA

insensitive phenotype in double-blinded ABA-induced stomatal closing and ABA

inhibition of stomatal opening analyses (Nishimura et al., 2010). These multiple

independent lines of evidence indicated that the previously uncharacterized

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PYR/PYL/RCAR proteins are major early ABA signaling components. PYR/PYL/RCARs

are small soluble proteins belonging to the START/Bet v I superfamily and they contain

a central hydrophobic ligand-binding pocket (Iyer et al., 2001). The Arabidopsis thaliana

genome encodes 14 PYR/PYL/RCAR proteins that are highly conserved at the protein

sequence level. The identification of this new class of ABA signaling proteins has shed

light in the plant hormone signaling field, providing new avenues of research into ABA

signal transduction. For example, after the crystallization of the ABA receptor, the action

mechanism has started to emerge. Direct ABA binding to PYR/PYL/RCARs was

subsequently established through the elucidation of PYR1, PYL1, and PYL2 crystal

structures in the presence of ABA (Melcher et al., 2009; Miyazono et al., 2009; Santiago

et al., 2009; Yin et al., 2009; Nishimura et al., 2010). It was established that

PYR/PYL/RCARs consist of homodimers with each subunit binding to ABA. The binding

of ABA results in the dissociation of the dimer, introducing conformational changes of

PYR/PYL/RCARs. This creates a new surface for PP2Cs to interact with the receptor,

and consequently the interaction inhibits the phosphatase activity of PP2Cs by blocking

the access of their substrates to the catalytic center since the acting interface between

ABA-bound PYR/PYL/RCARs and PP2Cs is located at the PP2C active site.

As we understand how PYR/PYL/RCARs function through ABA-dependent

inhibition of PP2C activity, the targets of PP2Cs in the signaling pathway become

intriguing. To date, one of the best characterized PP2C target is the OPEN STOMATA 1

(OST1), a serine/threonine kinase with high homology to ABA-activated protein kinases

(AAPKs) found in V. faba (Li and Assmann, 1996). OST1 is a positive regulator in the

ABA signaling pathway under the regulation of the complex formed by ABA receptor

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and phosphatase PP2C (Lee et al., 2009). With the presence of the hormone molecule

binding to the receptor PYR/PYL/RCAR, the phosphatase is deactivated, which in

consequence keeps the phosphorylated status of OST1 in an active form (Figure 1-2).

The substrates of OST1 identified so far include NADPH oxidase located on plasma

membrane, S-type anion channel (SLAC1), inward-rectifying potassium channel (KAT1)

and transcription factors such as ABSCISIC ACID RESPONSIVE ELEMENTS-BINDING

FACTOR 3 (ABF3) although the regulatory mechanisms may vary (Geiger et al., 2009;

Sato et al., 2009; Sirichandra et al., 2009; Sirichandra et al., 2010). Overall, the

receptor, PP2C and OST1 form a double negative regulatory complex at the initial stage

of ABA signaling pathway in guard cells to convey the signal to the downstream

components, leading to the physiological output of stomatal movement.

Although key regulatory events in the ABA signaling pathway have been unraveled

(Table 1-1), the complete molecular networks, including nodes, edges and the

regulatory mechanisms remain to be determined. For example, the structural details of

the receptors imply the formation of homodimer without binding to ABA but the

interaction with PP2C occurs on the receptor monomer with an ABA molecule, which

implies the correlation of the complex formation with the dimer dissociation. However, it

is not clear whether the receptor-PP2C complex formation precedes the homodimer

dissociation or vice versa. The protein/hormone ratio or concentration in vivo could be

balanced to tune the equilibrium for homodimer association/dissociation, thus

appropriately respond to the environmental stimulus (Hubbard et al., 2010). In addition,

the in vitro interaction of PYR/PYL/RCARs-PP2C has been intensively investigated and

the interactions observed, for instance, ABI1 forms complexes with PYR1, PYL1, PYL8

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and PYL9 (Ma et al., 2009; Miyazono et al., 2009; Park et al., 2009; Yin et al., 2009),

may not represent those in vivo. The specificity of PYR/PYL/RCAR and PP2C

complexes need to be determined in relation to different biochemical/physiological

processes since many different homologs exist in the genome. Additionally, PP2C is

known to target OST1 to regulate the activity of the kinase for downstream activation.

However, other targets of PP2C other than OST1 need to be explored. And the

observation that OST1 can be activated by osmotic stress in the PP2C dominant

negative mutants indicates the inhibition of the dephosphorylation activity is not the only

strategy to activate OST1 (Yoshida et al., 2006). Other models, e.g., the existence of

upstream kinases should be further tested. Other questions to be addressed include,

but not exclusively, the relationships between the central regulatory module and other

signaling intermediates, such as ion channels, ROS/NO production, Ca2+ oscillation and

transcriptional responses. Recently Wang and his colleagues applied “omics” approach

to discover common and unique elements of the ABA-regulated transcriptome of

Arabidopsis guard cells and found 1173 ABA responsive genes (696 ABA-induced and

441 ABA-repressed) out of around 24,000 profiled genes (Wang et al., 2011). This work

set the stage for targeted gene functional characterization and further biotechnological

manipulation to improve plant water use efficiency.

Methyl Jasmonate (MeJA) Signaling Pathway in Guard Cells

ABA is often categorized as a phytohormone closely related to abiotic stresses,

while jasmonate (JA) is often recognized more as a biotic stress hormone since this

group of plant hormones mediate plant defense responses against necrotrophic

pathogen and insects (Liechti and Farmer, 2002; Fujita et al., 2006). Besides the roles

in biotic stress, the lipid-derived plant hormone also participates in the regulation of

24

vegetative and reproductive growth, and defense responses against abiotic stresses,

e.g., UV light and ozone (Katsir et al., 2008). Since the first report of MeJA-induced

stomatal closure (Gehring et al., 1997) and the observation of JA accumulation during

drought (Creelman and Mullet, 1997), JA has been proposed to play an important role in

stomatal movement under stress conditions.

Although both ABA and MeJA are positive regulators of stomatal closure,

knowledge on how MeJA and ABA signaling pathways interact and function in guard

cells is lacking. The function of the jasmonate coreceptor CORONATINE INSENSITIVE

1 (COI1), encoding an F-box protein, together with JASMONATE ZIM-DOMAIN (JAZ)

co-receptor were known for efficient ligand binding (Xie et al., 1998; Thines et al., 2007;

Katsir et al., 2008; Sheard et al., 2010). Due to the receptor specificity of each hormone,

the divergence between the ABA and MeJA signal pathways can be reasonably

predicated. However, the MeJA-mediated stomatal closure has been found to involve

guard cell cytoplasmic alkalinization, ROS production via NADPH oxidase subunits

AtrbohD/F (Suhita et al., 2004), NO production (Munemasa et al., 2007; Saito et al.,

2009), and activation of K+ efflux channels (Evans, 2003) and slow anion channels

(Gehring et al., 1997; Suhita et al., 2003), which are processes common to ABA

signaling. In detail, NADPH oxidase-mediated ROS production is necessary for

activation of calcium permeable non-selective cation channels (ICa channels) by ABA

and MeJA. Cytosolic Ca2+ elevation is involved in ABA- and MeJA-induced stomatal

closure via S-type anion channel activation of guard cell plasma membrane and a

regulatory subunit of protein phosphatase 2A, RCN1(ROOT CURLING IN N-

NAPHTHYLPHTHALAMIC ACID 1) regulates both MeJA signaling and ABA signaling in

25

guard cells (Murata et al., 2001). These lines of evidence suggest crosstalks between

ABA and MeJA signaling pathways in guard cells (Figure 1-3 and Table 1-1). This

hypothesis is further supported by observation of MeJA hyposensitivity of stomatal

closure in the ost1 (ABA hyposensitive) mutant, and reduced ABA-mediated stomatal

closure in the jar1 (jasmonate resistant 1, MeJA insensitive) mutant (Suhita et al.,

2004). MeJA-induced stomatal closure was also studied in the ABA-insensitive PP2C

mutant, abi2-1. In this mutant, no stomatal closure was observed in response to either

MeJA or ABA, but production of ROS and NO were retained (Munemasa et al., 2007).

All together, COI1 functions upstream of ROS and NO in MeJA but not ABA signaling,

while ABI2 functions downstream of ROS and NO after the MeJA- and ABA-signaling

pathways have converged. The activation of transcription factors are known to be the

downstream events in the ABA signal transduction (Abe et al., 2003). Thus one more

evidence came from the demonstration that the basic helix-loop-helix (bHLH)

transcription factor AtMYC2, which was originally identified as a transcriptional activator

in the ABA-mediated drought stress pathway, is involved in the JA signal transduction

(Abe et al., 2003; Lorenzo et al., 2004).

Interestingly, myrosinase-glucosinolate system has recently been demonstrated to

be a novel component in ABA signaling in guard cells (Zhao et al., 2008). TGG1

encodes a myrosinase that is highly expressed in guard cells (Husebye et al., 2002;

Zhao et al., 2008). TGG1 was found to be involved in inhibition of light-induced stomatal

opening by ABA, but not in ABA-induced stomatal closure (Zhao et al., 2008). Two

functional myrosinase genes, TGG1 (At5g26000) and TGG2 (At5g25980), have been

found to express at high levels in Arabidopsis shoots and they have redundant function

26

in glucosinolate hydrolysis (Barth and Jander, 2006). Recent work by Murata group

suggests that the two myrosinases function downstream of ROS production and

upstream of cytosolic Ca2+ elevation in ABA and MeJA signaling in guard cells (Islam et

al., 2009). They have also provided evidence showing one of the glucosionlate

degradation products, isothiocyanate can induce stomatal closure, which requires MeJA

priming, but not ABA priming (Khokon et al., 2011a). Additionally, Lackman and

colleagues have identified a tobacco gene, NtPYL4 encoding a protein with high

homology to the PYR/PYL/RCAR family ABA receptors in Arabidopsis and it is involved

in JA signaling (Lackman et al., 2011). Furthermore, recent transcriptomic analysis of

ABA responsive genes in Arabidopsis guard cells has also provided evidence for the

crosstalks at transcriptional level between ABA and MeJA (Wang et al., 2011).

The evidence for the signaling crosstalk between ABA and MeJA is not limited on

the molecular basis but also found in genetic and physiological experiments. Drought is

known to alter the balance of different hormones (Dodd and Davies, 2010). To address

the role of ABA in JA-mediated stomatal regulation, the JA-mediated stomatal response

has been studied in ABA-biosynthetic tomato mutant sitiens. When the petioles of the

sitiens leaves were incubated in JA, no stomatal movement was observed; however,

stomatal closure is triggered by JA when the petioles were pretreated with ABA (Herde

et al., 1997). This suggests that ABA is required by the JA-mediated stomatal response

in tomato. In soybean, exogenous application of MeJA did not affect endogenous ABA

levels, but water-stressed barley seedlings pretreated with JA showed more than 4-fold

accumulation of ABA in comparison to water stressed-barley seedlings without

pretreatment with JA. This indicates a role for JA in ABA biosynthesis under water

27

stress conditions (Bandurska et al., 2003). Many drought-responsive genes are

regulated by MeJA and several MeJA-regulated, drought-responsive genes are also

regulated by ABA with similar expression dynamics (Nemhauser et al., 2006; Huang et

al., 2008). These data support that common signaling components are employed by

ABA and MeJA. However, unique components and regulatory mechanisms underlying

each pathway of hormone signaling need to be further explored.

Other Hormones in Stomatal Function

Several other hormones, including salicylic acid (SA), auxins, cytokinins, ethylene

and brassinosteroids (BRs) are also involved in the regulation of stomatal movement

but the modes of action vary. Generally, BRs and SA are positive regulators triggering

stomatal closure like ABA and JA, whereas cytokinins and auxins are positive regulators

for stomatal opening (Lohse and Hedrich, 1992; Manthe et al., 1992; Lee, 1998; Mori et

al., 2001; Wilkinson and Davies, 2002; Haubrick et al., 2006). Interestingly, ethylene

alone promotes stomatal closure, whereas ethylene in concert with other hormones

opposes stomatal closure. This dual regulatory role of ethylene on stomatal movement

can be observed in a species and/or condition dependent manner (Jackson, 2002; Dat

et al., 2004; Acharya and Assmann, 2009). Although gibberellins (GAs) modulate

expression levels of drought-related genes like ABA, JA, auxins, cytokinins, ethylene

and BRs, little or no effect was observed on the stomatal movement in Arabidopsis

when GA was applied exogenously (Nemhauser et al., 2006; Tanaka et al., 2006;

Huang et al., 2008). Additional evidence also suggests GAs may not play critical roles in

controlling stomatal aperture during water stress (Cramer et al., 1995).

Although the effect of each hormone on stomatal biology was often studied

independently, it is believed that different hormones regulate plant responses to biotic

28

and abiotic stresses via synergistic and antagonistic mechanisms (Fujita et al., 2006).

For instance, interaction of auxin, cytokinins, or ethylene with ABA inhibits ABA-induced

stomatal closure (Tanaka et al., 2006). Additionally, interaction of ABA and SA positively

regulates stomatal closure to impede invasion of bacterial pathogens (Melotto et al.,

2006). However, such observations using exogenous hormone treatment may not

reflect the effects of changes in endogenous hormone levels. In addition, despite recent

progress on hormonal control of stomatal function, many questions remain unanswered.

Many plant hormonal responses are developmental in nature, whereas hormonal

regulation of stomatal movement is a reversible, non-developmental process. Whether

the subcellular targets of hormones discovered in guard cells (e.g., ion channels) are

also cellular targets of hormonal regulation in the developmental processes and whether

they are cell type specific are not known. The molecular switches in regulation that allow

quick response of guard cells to changes in the environment remain to be a key

question. Additional questions include whether stomatal regulatory mechanisms, which

to date have been explored primarily in dicot species, prevail in other species as well,

and in particular whether they occur in the graminaceous species with their unique

guard cell morphology and dominance in agroecosystems. The concerted application of

molecular, genetic, cell biology and biochemical approaches including modern “omics”

technologies is anticipated to significantly advance our knowledge of guard cell signal

transduction and system biology. The improved knowledge will contribute positively

toward future biotechnology of enhanced plant yield and bioenergy.

29

Regulative Mechanisms Underlying Stomatal Movement

Phosphorylation/Dephosphorylation

Although plant hormones have been discovered for a long time, relatively little is

known about their mechanisms of action at the protein level. The evolution of protein

kinases/phosphatases indicates the phosphorylation/dephosphorylation switch

dominates signal transduction processes in higher plants (Stone and Walker, 1995;

Luan, 2003). The reaction of transferring phosphate groups from high-energy donor

molecules, such as ATP, to specific substrates is referred as phosphorylation and

catalyzed by a kinase, alternatively known as a phosphotransferase. The reverse

process, i.e., the removal of the phosphate group, known as dephosphorylation is

catalyzed by another group of enzymes named phosphatases (Burnett and Kennedy,

1954). Such reactions occur on certain amino acid residues, such as histidine and

aspartic acid in the two-component phosphotransfer system more commonly seen in

bacteria, as well as serine, threonine and tyrosine typical for eukaryotes (Hanks and

Hunter, 1995; West and Stock, 2001). Undoubtedly such reversible protein

modifications play a significant role since it could activate or deactivate target proteins

with diverse functions, in a way similar to “on or off switches” (Mundy and Schneitz,

2002).

Prior to molecular identification of any kinases or phosphatases with functions in

guard cells, early evidence has already suggested ion channels and H+ pump are

targets of phosphorylation/dephosphorylation regulation in guard cells. For example, it

has been reported the plasma membrane H+ pump in Vicia faba guard cells, which was

activated by blue light, was inhibited by an inhibitor of myosin light-chain kinase

(Shimazaki et al., 1992). The activities of inward- and outward-rectifying K+ channels

30

were affected by protein phosphatase inhibitors (Li et al., 1994; Thiel and Blatt, 1994;

Armstrong et al., 1995). In late 1990s, direct evidence of the presence of protein

kinases and protein phosphatases in guard cells was obtained through identification of

an ABA-activated protein kinase (AAPK) in V. faba guard cells (Li and Assmann, 1996;

Mori and Muto, 1997). The 48 kD ABA-activated and Ca2+-independent protein kinase

was discovered using in-gel kinase assay and the peptide information was obtained

using mass spectrometry (Li et al., 2000). The functional characterization of AAPK

suggests that the kinase is activated by ABA in vivo and it regulates the anion channels

to induce stomatal closure (Li et al., 2000). It is noteworthy that a study by Mori and

Muto (1997), a 53 kD ABA-activated and Ca2+-dependent protein kinase was proposed

to be the activator of AAPK (Mori and Muto, 1997). Ever since, more kinases have been

found to function in guard cell physiology largely due to the advances in modern

technologies. The discovery of an Arabidopsis serine/threonine kinase, known as OST1,

acting upstream of ROS production in ABA signaling is a landmark of such progress

(Mustilli et al., 2002). OST1 belongs to the sucrose non-fermenting 1 (SNF1) related

kinase 2 (SnRK2) subfamily and the members in the SnRK2 family are mainly involved

in plant stress response and tolerance (Harmon, 2003; Halford and Hey, 2009).

Intensive studies have been conducted to characterize OST1 function, including its

upstream activating kinase, downstream phosphorylation targets and interacting

partners. To date, the upstream kinase remains elusive. However, the 53 kD ABA-

activated and Ca2+-dependent protein kinase identified from V. faba guard cells is a

likely candidate since the AAPK is highly homologous to OST1 (Mori and Muto, 1997;

Assmann, 2003). In contrast, studies on the OST1 targets have been fruitful. To date,

31

the identified OST1 substrates include NADPH oxidase, S-type anion channel (SLAC1),

inward-rectifying potassium channel (KAT1) and transcription factors such as ABF3

(Geiger et al., 2009; Sato et al., 2009; Sirichandra et al., 2009; Sirichandra et al., 2010).

The regulatory domain of OST1 was found to interact with phosphatase ABI1 and

integrate ABA and osmotic stress signals to regulate stomatal closure in Arabidopsis

(Yoshida et al., 2006; Vlad et al., 2009). When ABA binds its receptor PYR/PYL/RCAR,

the phosphatase is deactivated, thus maintain the phosphorylated status of OST1 in an

active form (Lee et al., 2009). In addition, the involvement of OST1 in JA, ROS and CO2

signaling pathways has been unraveled (Suhita et al., 2004; Vahisalu et al., 2010; Xue

et al., 2011). All current results suggest the central role of OST1 in hormone signaling

and stress response is mediated by protein phosphorylation/dephosphorylation

molecular switches.

S-type anion channels contribute to chloride and nitrate export from guard cells,

which in turn initiates stomatal closure. The first identified component of the guard cell

S-type anion channel SLAC1 is a target of OST1 in a Ca2+-independent manner (Geiger

et al., 2009). However, since ABA-induced stomatal closure involves increases of

cytosolic Ca2+ levels, it is not known whether S-type anion channels are also regulated

by an Ca2+-dependent mechanism (Li et al., 2006). Impairment of ABA activation of S-

type anion channels in cpk3cpk6 mutants implies the role of calcium-dependent protein

kinase (CDPK) CPK3 and CPK6 function in ABA regulation of guard cells S-type anion

channels and Ca2+-permeable channels in stomatal closure (Mori et al., 2006). Recently

in vitro evidence of direct interaction between CPK21 and SLAC1 homolog 3 (SLAH3)

and between CPK21 and ABI1/2 suggests a Ca2+-dependent activation of S-type anion

32

channels in ABA signal transduction in Arabidopsis through the receptor RCAR1-PP2C

complex, which might parallel to the Ca2+-independent activation by OST1(Geiger et al.,

2011). The identification of the two types of kinases, SnRK2 and CDPK in the guard cell

function demonstrates the existence of both Ca2+-dependent and Ca2+-independent

ABA activation. However, the specificity and redundancy of the kinases in regulating

downstream targets is worthy of further investigation considering there are 34 CDPK

and 10 SnRK2 genes in Arabidopsis genome.

Another important signaling cascade is mediated by mitogen-activated protein

kinases (MAPKs), including MAP4K, MAP3K, MAP2K, MAPK that are sequentially

activated in the cascade (Taj et al., 2010). MAP kinases MAPK9 and MAPK12 were

found to express preferentially in guard cells and positively regulate ROS-mediated ABA

signaling (Jammes et al., 2009). Additionally, stomatal closure caused by increased

levels of ABA under drought involves MKK1, MAPK3 and MAPK6 (Hamel et al., 2006;

Gudesblat et al., 2007). Pathogen-induced stomatal closure restricts the invasion of

bacteria and thus constitutes an important part of the plant innate immune response.

The stomata of guard cell specific MAPK3 antisense plants act normally upon ABA

treatment, but are not responsive to bacteria, indicating the unique function of MAPK3 in

the stomatal innate immunity response (Gudesblat et al., 2007). It is interesting to

investigate whether pathogen-induced stomatal closure and ABA-induced stomatal

closure are mediated via a common MAPK cascade or other MAPKs are involved in the

stomatal movement.

Besides the three common kinase groups mentioned above, other types of

kinases have been shown to function in guard cell signal transduction. A mutant (ahk5)

33

of Arabidopsis histidine kinase AHK5 localized in cytosol and on plasma membrane has

shown reduced stomatal closure in response to abiotic stimuli, pathogen treatment, as

well as exogenous application of H2O2 (Desikan et al., 2008). However, ABA-induced

stomatal closure, H2O2 production induced by dark adaptation and H2O2 induced NO

synthesis were preserved in the mutant. This observation suggests that AHK5

integrates multiple signaling pathways via H2O2 homeostasis and may be independent

of ABA signaling in guard cells. In addition, a calcineurin B-like-interacting protein

kinase (CIPK) belonging to the SnRK3 subfamily was isolated from V. faba guard cells

and found to be negatively regulated by cytosolic Ca2+ through calcineurin B-like

calcium-binding protein (CBL). The VfCIPK1 may be related to the mitochondrial

functions in guard cells but the detailed mechanisms await further analysis (Tominaga

et al., 2010). In summary, all the identified guard cell protein kinases participate in the

signaling processes that regulate proper stomatal movement in response to

environmental stimuli. Future work needs to map their functions in the sophisticated

guard cell molecular networks to achieve an ultimate understanding of stomatal

movement in response to internal and external stimuli.

The opposite direction of phosphorylation is dephosphorylation catalyzed by

protein phosphatases. Similar to kinases, phosphatases are ubiquitous enzymes in all

eukaryotes and could be classified based on their substrate specificity into

serine/threonine phosphatases, tyrosine phosphatases, dual specificity phosphatases,

histidine phosphatases and lipid phosphatases (Barford, 1996; Camps et al., 2000;

Bäumer et al., 2007). To date, the first two groups, especially the serine/threonine

phosphatases have been found to function in guard cells. The serine/threonine

34

phosphatases can be classified into four major subgroups, protein phosphatase (PP)

type 1, PP2A, PP2B and PP2C based on their substrate specificity, divalent cation

requirement and inhibitor sensitivity (Cohen et al., 1989). The PP1 group phosphatases,

utilizing the β subunits of phosphorylase kinases as substrate, are potently inhibited by

okadaic acid and independent on divalent cations for activity. The PP2 groups generally

use the subunits of phosphorylase kinases as substrate, but their inhibitor and cation

dependence vary. For example, PP2As are okadaic acid sensitive but not dependent on

divalent ions; PP2Bs (calcineurin) are dependent on Ca2+ and stimulated by calmodulin,

but not inhibited by okadaic acid; PP2Cs are dependent on Mg2+ and not sensitive to

okadaic acid (Cohen et al., 1989).

With the knowledge of the known inhibitors to each subgroup of the

serine/threonine phosphatases, early pharmacological studies suggested the

involvement of all the groups in guard cell signal transduction. The PP1/PP2A inhibitor

okadaic acid can partially impair activation of anion channels and stomatal closure in

Arabidopsis (Ler) (Schmidt et al., 1995). The inhibitor disruption of the PP2A regulatory

subunit RCN1 confers ABA insensitivity in Arabidopsis (WS), suggesting a role of RCN1

as a positive transducer of ABA-elicited [Ca2+]cyt transients in guard cells (Kwak et al.,

2002). In Arabidopsis rcn1 mutants, MeJA failed to induce stomatal closure. ROS

production and suppression of inward-rectifying K+ channel activities were not observed

in rcn1 when treated with ABA or MeJA, suggesting RCN1is a shared component

between the two hormone pathways and is functioning upstream of ROS production and

downstream of the branching point of hormone signal reception (Saito et al., 2008).

These results suggest that PP1s/PP2As act as positive regulators of MeJA or ABA

35

signal transduction in Ler and WS guard cells. Inconsistently, however, the application

of okadaic acid promotes anion channel activation and ABA-induced stomatal closure in

Vicia and Commelina, and activates ABA-responsive promoters in tomato hypocotyls

(Pei et al., 1997; Wu et al., 1997). Therefore, PP1s and PP2As can be either positive or

negative regulators in guard cell signaling, dependent upon plant species.

Ca2+ oscillation is an essential process in the guard cell ABA signaling pathway (Li

et al., 2006). The Ca2+-dependent PP2B (calcineurin) was found to deactivate the

plasma membrane inward-rectifying K+ channels in fava bean guard cells and the effect

was blocked by PP2B specific inhibitor (Luan et al., 1993). This observation links the

increase of cytosolic Ca2+ to the inhibition of inward-rectifying K+ channels in guard cells,

and in consequence, stomatal closure by changing the phosphorylation status of

plasma membrane inward K+ channels. Additionally, ABA responses in pea epidermal

peels, including mRNA accumulation of ABA-induced dehydrin and stomatal closure

were reduced by an inhibitor of PP2B (Hey et al., 1997). Furthermore, a Ca2+-

permeable slow vacuolar channel in guard cells was shown to be modulated by

calcineurin (protein phosphatase 2B) (Allen and Sanders, 1995). Since no catalytic

PP2B subunits are found in the Arabidopsis thaliana genome, whether the participation

of PP2B in the guard cells signal transduction is universal in plants is not known (Kerk

et al., 2002).

Due to the unavailability of pharmacological inhibitors to PP2Cs, initial discovery of

PP2Cs in the ABA pathway came from genetic studies of the ABA deficient mutant abi1

(Leung et al., 1994; Meyer et al., 1994). To date, it has been demonstrated that at least

four Arabidopsis PP2Cs (ABI1, ABI2, AtP2C-HAB1 and PP2CA) are negative regulators

36

of the ABA signaling pathway in guard cells (Rodriguez et al., 1998; Gosti et al., 1999;

Merlot et al., 2001; Tahtiharju and Palva, 2001). Armstrong and colleagues reported that

ABI1 (ABA INSENSITIVE 1), a putative protein phosphatase 2C, regulates inward- and

outward-rectifying K+ channels (Armstrong et al., 1995). In response to ABA, dominant

abi1-1 mutants lost the ability to generate ROS, but the dominant ABA-insensitive abi2-

1 mutant could generate ROS. Thus, it has been proposed that ABI1 acts upstream of

ROS production and ABI2 downstream of ROS in guard cell ABA signaling (Murata et

al., 2001). Particularly, the activity of ABI1 is inhibited when interacting with ABA bound

receptor PYR/PYL/RCAR, leading to OST1 activation to initiate downstream signaling

processes (Hubbard et al., 2010). The double negative regulatory core, composed of

the three key elements, the receptor, the phosphatase and the kinase, highlights the

phosphorylation switch in the guard cell signaling transduction. In addition, AtP2C-HAB1

is one of the closest relatives of ABI1 and ABI2 and over-expression of AtP2C-HAB1

impaired stomatal closure (Rodriguez et al., 1998). Similar to the kinases identified in

the stomatal response, ion channels are targets of PP2Cs. For example, PP2CAs bind

to ARABIDOPSIS POTASSIUM TRANSPORT 2 (AKT2), a K+ channel in vitro and

regulate the AKT2 to control K+ channel activity and membrane polarization under

stress conditions (Chérel et al., 2002). Compared to other subgroups of serine/threonine

phosphatases, 76 Arabidopsis genes are identified as PP2C-type phosphatase

candidates, much more than the 26 PP1s and PP2As and there is no representatives of

PP2Bs (Schweighofer et al., 2004; Farkas et al., 2007). Apparently, PP2Cs form a

major class of phosphatases with important functions in plant stress signal transduction.

37

Another class of phosphatases, protein tyrosine phosphatase (PTPase) has also

been shown to control ion efflux from guard cell vacuoles during stomatal closure.

PTPase specific inhibitor prevents stomatal closure caused by ABA, high external Ca2+,

H2O2 and dark, but promotes reopening of the closed stomata, implying that protein

tyrosine dephosphorylation must occur at or downstream of the Ca2+ signal responsible

for ion efflux from the vacuoles (MacRobbie, 2002). However, this conclusion is based

on pharmacological studies, without genetic or other evidence.

The recurrent theme is that protein phosphatases negatively regulate signaling

pathways activated by the action of particular protein kinases. The diversity of plant

phosphatases suggests that individual phosphatase may have specificity in substrate

recognition, as the case of kinases described in the previous section. The coordination

between specific protein kinases and phosphatases, as well as the interaction with their

diverse targets highlight sophisticated and orchestrated signaling networks. It has

become clear that the regulatory mechanism of phosphorylation/dephosphorylation,

best exemplified by research on ABA signaling in guard cells, plays a pivotal role in

plant stomatal function.

Thiol-based Redox Regulation

Plants are subjected to constant challenges in their environment, and they have to

adjust metabolism in real time to maintain a steady state balance between energy

generation and consumption (Foyer and Noctor, 2009). Metabolic imbalance can induce

oxidative stress in cells, as often indicated by the generation and accumulation of

reactive oxygen species (ROS), including H2O2, superoxide ion (O2•-) and hydroxyl

radical (OH•) (Valko et al., 2007). A common property of ROS is that they can cause

oxidative damage to proteins, DNA, and lipids. Oxidized biomolecules have been

38

traditionally recognized as markers for oxidative stress (Suzuki et al., 2011). However,

more and more evidence indicates that ROS can also serve as signaling molecules for

regulating various physiological responses to environmental challenges (Buchanan and

Balmer, 2005). For example, Arabidopsis MAPK4 and MAPK6 are activated in vivo by

oxidative stress such as H2O2 treatment and a MAP kinase responsible for tobacco

sensitivity to ozone is also redox-activated (Desikan et al., 2001; Samuel and Ellis,

2002). However, it remains unclear whether cysteines are involved and whether the

redox regulation is a direct effect of sensing cellular redox state (Figure 1-4).

The role of ROS in plant cell signal transduction is best exemplified in stomatal

movement process, using guard cells as a premium signaling model system. ROS burst

was characterized to be the second messenger in the ABA signaling in guard cells

(Allan and Fluhr, 1997; Lee et al., 1999; Pei et al., 2000). However, ROS production

does not represent a unique mechanism in this pathway since JA-, SA-, CO2- and

ozone-triggered stomatal closure is also associated with the elevation of ROS (Suhita et

al., 2004; Kolla et al., 2007; Vahisalu et al., 2010; Khokon et al., 2011b). ROS

accumulation in guard cells was shown to be a biphasic event, in which the production

was initiated from chloroplasts, followed by ROS production through NADPH oxidases

in plasma membrane (Joo et al., 2005; Vahisalu et al., 2010). Due to the dual function of

ROS, a tight control is essential to balance the oxidative damage to proteins and

signaling activity, including reversible redox regulation of proteins, regulation of

phosphoproteins, activation of ROS-responsive regulatory genes and buffering of ROS

by ROS-scavenging enzymes and antioxidant molecules (Suzuki et al., 2011). There

are a few key examples of guard cell protein redox regulation. The activities of protein

39

phosphatase ABI1 and ABI2 in guard cells are sensitive to redox state (Meinhard and

Grill, 2001; Meinhard et al., 2002). However, direct evidence for thiol-based redox

regulation and a link between protein redox change and stomatal closure remain to be

demonstrated. Great effort has been made to investigate the molecular mechanisms of

ROS production and identification of ROS-regulated molecular components in guard cell

signaling. Plasma membrane NADPH oxidase is important in ROS production in guard

cells (Kwak et al., 2003). The evidence came from the observation that disruption of two

partially redundant Arabidopsis guard cell NADPH oxidase catalytic subunit genes,

AtrbohD and AtrbohF, impairs ABA-induced ROS production and stomatal closure

(Kwak et al., 2003). Recently, the activity of the NADPH oxidase has been shown to be

regulated by the upstream kinase OST1 through phosphorylation, linking the

phosphorylation event with ROS production and redox control of guard cells

(Sirichandra et al., 2009). Exogenous H2O2 can rescue both Ca2+ channel activation and

stomatal closure in the ABA-insensitive mutant gca2 (growth controlled by abscisic acid

2), indicating the correlation between the ROS production and Ca2+ channel activation

(Pei et al, 2000). This was further confirmed by the observation that the ABA-induced

cytosolic Ca2+ increase and activation of plasma membrane Ca2+-permeable channels

were impaired in the atrbohD/F guard cells (Kwak et al., 2003).

Reactive nitrogen species (RNS), e.g., NO, has been recognized to be another

important signaling messenger in plant cell physiology. NO participates in many key

physiological processes such as pathogen defense, development, programmed cell

death, and stress tolerance in plants (Foissner et al., 2000; Pedroso et al., 2000; Beligni

and Lamattina, 2001). As a downstream element of ABA signaling pathway in guard

40

cells, NO was shown to selectively regulate Ca2+- sensitive ion channels of Vicia guard

cells by promoting Ca2+ release from intracellular stores to raise cytosolic-free [Ca2+]

(Garcia-Mata et al., 2003). Together with RNS, ROS could alter the cellular redox

environment. Two groups of ROS scavengers, non-enzymatic (e.g., ascorbate and

glutathione) and enzymatic (e.g., superoxide dismutase, glutathione peroxidase and

ascorbate peroxidase), function together to adjust and balance the redox state within

the cells. ROS, RNS and the scavenging system maintain the cellular redox

homeostasis (Pitzschke et al., 2006). The redox status of guard cells is important in

stomatal movement. Chen and Gallie observed that the levels of H2O2 and ascorbate

redox in guard cells are diurnally regulated, i.e., the former increases in the afternoon

whereas the latter decreases in the course of stomatal closure (Chen and Gallie, 2004).

It is reasonable to predict the existence of signaling components in guard cells are

under redox regulation or interact with ROS and RNS.

Besides the interaction between Ca2+ channels and ROS, only a few redox

regulated components in guard cell signaling are known. For example, one of the

Arabidopsis annexins, known as the target of calcium signaling in eukaryotic cells, has

been shown to be susceptible to oxidation-driven S-glutathionylation on the two

cysteines in the calcium reactive S3 cluster (Konopka-Postupolska et al., 2009). The S-

glutathionylation occurs in planta after ABA treatment, indicating the annexin could be

regulated by the ABA induced ROS production. Recently, the activity of oxidized β-

amylase (BAM1) was reported to be restored by thioredoxin isoform f1 and partially by

NADPH-thioredoxin reductase. This redox-regulated BAM1 plays a role in diurnal starch

degradation important for stomatal opening (Valerio et al., 2011).

41

As described above, phosphorylation/dephosphorylation and redox control are

major regulatory mechanisms in the guard cell signaling networks, where more

components and interactions need to be discovered. In mammals, many signaling

proteins have been shown to be redox regulated, including Ca2+-ATPase, Ras-related

GTPase Rac1 EGF growth factor, phosphorylase β kinase and voltage-dependent anion

channel protein (Suzakawa et al., 2000; Adachi et al., 2004; Sethuraman et al., 2004).

In guard cells, little is known about the interaction between the redox regulation and

kinase/phosphatase signaling cascades. Recently, it was found that stomata of the

ethylene receptor mutant etr1 did not close in response to H2O2, and mutation of a

cysteine residue in ETR1 disrupted H2O2-induced stomatal closure (Desikan et al.,

2005). These findings indicate that redox regulation is an important component of

signaling in guard cells. In maize, the ABA-induced H2O2 production activates a 46kD

mitogen-activated protein kinase (p46MAPK) and the activation of p46MAPK regulates

the production of H2O2, suggesting a positive feedback loop involving NADPH oxidase,

H2O2, and the p46MAPK in ABA signaling (Lin et al., 2009). However, direct evidence

for thiol modification and a link between protein redox change in guard cells and

stomatal closure remains to be demonstrated.

Conclusions and Project Objectives

Although great progress has been made to elucidate hormone (e.g., ABA and

MeJA) signal transduction pathways in guard cells, our knowledge of the pathways and

the molecular networks detailing the interactions between different signaling and

metabolic components as well as pathways are far from complete. Recent years have

seen great progress in plant proteomics (Chen and Harmon, 2006). However, only a

few “whole proteome” analyses of guard cell signaling have been done. High throughput

42

proteomic approaches have been applied in our laboratory to identify hormone

responsive proteins and protein post-translational modifications including

phosphorylation and thiol redox using highly purified guard cells, in order to discover

more novel nodes and edges in guard cell molecular networks.

Due to the presence of ROS as an important signaling messenger, it is our central

hypothesis that protein redox modification and the dynamic changes are critical

regulatory mechanisms in ABA and MeJA signal transduction. The first objective of this

project is to characterize guard cell proteome and its functional specification in ABA and

MeJA signaling. The oxidization and reduction of the sulfhydryl group of cysteine are

known to be an essential regulatory switch in a spectrum of physiological processes

including photosynthesis in plants. However, thiol-based redox switches remain

unknown in the stomatal opening and closing processes. The second objective of this

project is to identify and characterize the redox-sensitive proteins in ABA and MeJA

signaling pathway of guard cells. Two complementary proteomics approaches, Isotope

Coded Affinity Tag (ICAT) and saturation Differential In Gel Electrophoresis (DIGE),

were utilized to identify guard cell thiol-based redox-regulated proteins in response to

ABA or MeJA. Accomplishing these objectives will reveal novel components of ABA

signaling networks and provide knowledge of regulatory mechanisms underlying

stomatal movements.

The third objective is to conduct detailed characterization of the interesting and

novel components using molecular biology, biochemistry and reverse genetics

approaches. Functional characterization of the selected protein components will put

43

them into the ABA and/or MeJA signaling networks and reveal the underlying

mechanisms of important hormone signaling and stomatal movement.

44

Table 1-1. Protein components of ABA and MeJA signaling pathways in Arabidopsis guard cells. The numbers in the parenthesis indicate the number of protein homologs, some of which have been characterized and are listed here with references.

Protein Gene locus Gene

Reference

ABA signaling MeJA signaling

PYR/PYL/RCAR (14) Bet v I domain protein

At4g17870 PYR1 Ma et al., 2009

At5g46790 PYL1 Park et al., 2009

At2g26040 PYL2 Santiago et al., 2009

At2g38310 PYL4 Nishimura et al., 2010 Lackman et al., 2011

At5g53160 PYL8/RCAR3

At1g01360 PYL9/RCAR1

PP2C Group A (9) Mg

2+-dependent Ser/Thr protein

phosphatase

At4g26080 ABI1 Leung et al., 1994 Munemasa et al., 2007

At5g57050 ABI2 Saez et al., 2004 Islam et al., 2010

At1g72770 HAB1 Saez et al., 2004

At1g17550 HAB2 Leonhardt et al., 2004

At3g11410 AtPP2CA Yoshida et al., 2006

At5g51760 AHG1 Nishimura et al., 2007

SnRK2 (10) Ser/Thr protein kinase

At3g50500 SnRK2.2 Merlot et al., 2002

At5g66880 SnRK2.3 Fujii et al., 2007

At4g33950 SnRK2.6/OST1 Mustilli et al., 2002 Suhita et al., 2004

CaM/CML (57) Calmodulin (-like)

At3g51920 CML9 Delk et al., 2005

At5g37770 CML24 Magnan et al., 2008

CDPK (34) Ca

2+-dependent Ser/Thr kinase

At4g23650 CPK3 Choi et al., 2005

At4g09570 CPK4 Mori et al., 2006

At2g17290 CPK6 Ma and Wu, 2007

At1g35670 CPK11 Zhu et al, 2007

At4g04720 CPK21 Geiger et al., 2011

At4g07470 CPK23

At3g57530 CPK32

45

Table 1-1. Continued.

Protein Gene locus Gene

Reference

ABA signaling MeJA signaling

F-box protein (>568) At2g39940 COI1 Xie et al., 1998

Katsir et al., 2008

Jasmonate-ZIM domain protein (12) At1g19180 JAZ1 Sheard et al., 2008

Thines et al., 2007

CBL (10) Calcineurin-B like

At4g17615 CBL1/SCABP5 Cheong et al., 2003

At5g47100 CBL9 Pandey et al., 2008

CIPK/SnRK3 (25) Ser/Thr protein kinase

At5g01810 CIPK15/PKS3 Cheong et al., 2007

At1g30270 CIPK23 Pandey et al., 2008

Rboh (10) NADPH oxidase

At5g47910 AtRbohD Kwak et al., 2003 Suhita et al., 2004

At1g64060 AtRbohF Suhita et al., 2004

PP2A (26) Protein Phosphatase regulatory subunit

At1g25490 RCN1 Kwak et al., 2002 Saito et al., 2008

Murata et al., 2001

Myrosinase (6) At5g26000 TGG1 Zhao et al., 2008 Islam et al., 2009

At5g25980 TGG2 Islam et al., 2009

Transcription factors (>1500) At1g32640 MYC2/JAI1/JIN1 Abe et al., 2003 Lorenzo et al., 2004

At2g47190 MYB2

46

Figure 1-1. Updated ABA signaling pathways in guard cells. [Ca2+]cyt, cytosolic free Ca2+ concentration; ABA, abscisic acid; ABC, ATP-binding cassette; ABI1, ABA insensitive 1; ABI2, ABA insensitive 2; ABI5, ABA insensitive 5; AREB 2, ABA responsive element binding protein 2; Asc, ascorbic acid; ATGPX3, Arabidopsis glutathione peroxidase 3; CDPK, calcium-dependent protein kinase; CHLH, magnesium chelatase H subunit; CP, carotenoid precursor; ETR1, ethylene response 1; G, glucosinolate; GCA2, growth controlled by abscisic acid 2; GCR2, G protein-coupled receptor; GPA1, Arabidopsis α-subunit of the trimeric G protein; GRX, glutaredoxin; HAB1&2, homology to ABI1 1&2; IP3, inositol trisphosphate; ITC, isothiocyanate; KAT1, potassium channel 1; M, myrosinase; MAPK, mitogen-activated protein kinase; OST1, open stomata 1; PA, phosphatidic acid; PI3K, phosphatidylinositol-3-kinase; PI4K, phosphatidylinositol-4-kinase; PIP2, phosphatidylinositol-4,5-bisphosphate; PLC, phospholipase C; PLD, phospholipase D; POX, peroxidase; PP2A, protein phosphatase 2A; PP2C, protein phosphatase 2C; PYL, pyrabactin resistance-like; PYR, pyrabactin resistance; RCAR, regulatory component of ABA receptor; SLAC1, slow anion channel 1; SnRK2, sucrose non-fermenting 1-related protein kinase 2; TF, transcription factor; TRX, thioredoxin.

47

Figure 1-2. Double negative regulatory module in the ABA signal transduction in guard cells (Umezawa et al., 2010). PYR/PYL/RCAR, PP2C and SnRK2 form a signaling complex referred to as the „ABA signalosome‟. A) Under normal conditions, PP2C negatively regulates SnRK2 by direct interactions and dephosphorylation of multiple residues of SnRK2. Once abiotic stresses or developmental cues up-regulate endogenous ABA, PYR/PYL/RCAR binds ABA and interacts with PP2C to inhibit protein phosphatase activity. In turn, SnRK2 is released from PP2C-dependent regulation and activated to phosphorylate downstream factors, such as the AREB/ABF bZIP-type transcription factor or membrane proteins involving ion channels. B) In contrast, the abi1-1-type mutated protein lacks PYR/PYL/RCAR binding, resulting in the constitutive inactivation of SnRK2, even in the presence of ABA, and strong insensitivity to ABA in the abi1-1 mutant.

48

Figure 1-3. A simple model of the signaling interaction between ABA and MeJA in Arabidopsis guard cells. Similar to ABA, MeJA also induces ROS production and NO production and activates ICa channels and S-type anion channels.

49

Figure 1-4. Redox-active cysteines are sensitive to oxidation. Modifications of cysteine induced by oxidative stresses include, but not exclusively, sulfenic acid, sulfinic acid (−SO2H), sulfonic acid (−SO3H), S-glutathionylation, S-nitrosylation, and disulfide bond.

SH H+

S-

H2O2

SOH

H2O2

SO2H

H2O2

SO3H

Irreversible

Thiol

Thiolate

Sulfenic acid

Sulfinic acid

Sulfonic acid

S

SH

S

SG

GSH

NO

Disulfide S-glutathionylation

S

NO

S-nitrosylation

Sulfenamide

N H

H2C

N H

O

N H

H2C

N

S

O

:

:

:

G :

another protein

glutathione

S

50

CHAPTER 2

COMPARATIVE PROTEOMICS PROVIDES EVIDENCE FOR CROSSTALK BETWEEN ABA AND MEJA SIGNAL TRANSDUCTION IN GUARD CELLS1

Introduction

The structure stomata on leaf epidermis are responsible for the gas exchange,

allowing plants to have ready access to carbon dioxide (CO2) and control the rate of

transpiration (Taiz and Zeiger, 2006). The major structural components for stomata are

one pair of guard cells, known for their ability to change shape due to ion influx and

efflux under certain conditions and consequently to control the stomatal aperture. Such

feature provides a highly responsive system for plants to respond to a variety of stress

factors, such as drought, heat, and pathogen invasion (Assmann, 1993).

Compared to mesophyll cells in leaves, guard cells contain fewer chloroplasts with

limited structure; thereby possess very low photosynthetic capability. The Calvin cycle in

guard cells only assimilates 2-4% of CO2 fixed in mesophyll cells (Outlaw and De

Vlieghere-He, 2001). In contrast, guard cells contain abundant mitochondria and display

a high respiratory rate, suggesting that oxidative phosphorylation is an important source

of ATP to fuel the guard cell machinery (Parvathi and Raghavendra, 1997). Such

distinguished features (i.e., high activities of energy metabolism and solute transport)

are consistent with the specific functions of guard cells. It is clear that guard cells

possess a robust machinery to perceive and transduce environmental signals and

regulate stomatal movement.

1 Partial content in this chapter has been published in Molecular & Cellular Proteomics 2009; 8(4):752-766 (PMID: 19106087) and Journal of Proteomics 2010; 73(4):790-805 (PMID: 19913118).

51

Using microarrays covering just one-third of the Arabidopsis genome, the large

scale transcriptomics study identified 1309 guard cell expressed genes of which 64

transcripts mainly involved in transcription, signaling, and cytoskeleton were

preferentially expressed in guard cells compared with mesophyll cells (Leonhardt et al.,

2004). However, functional grouping of the genes revealed only a 1.9% higher

representation of photosynthesis genes in mesophyll cells than in guard cells. The

percentages of genes in all other categories such as protein turnover, defense,

signaling, channels and transporters, and metabolism are similar between the two

distinct cell types (Leonhardt et al., 2004). However, these proteins are known to play

specific roles in guard cell functions (Li et al., 2006). The very recent global

transcriptomic analysis on ABA treated Arabidopsis guard cells identified 1173 ABA-

regulated genes, which set the stage for targeted biotechnological manipulations to

improve the plant tolerance against the water shortage (Wang et al., 2011). However,

responsiveness of several genes might be resulted from the change of upstream

transcription factors at the initial stage of ABA signaling. It will be inefficient and aimless

to select targets from the large candidate pool. All the shortcomings within the

transcriptomics necessitate of the studying guard cell functions at the translational level.

Due to the important roles in plant adaption, the signaling networks within guard

cells have been of great interest for decades. As a phytohormone related to

dehydration, both endogenous and exogenous abscisic acid (ABA) can trigger stomatal

closure in a dose-dependent manner (Wang and Song, 2008). Many key components in

this process have been discovered (Li et al., 2006). Recent work has suggested other

hormones also participate in the regulation of stomatal function; and interestingly, the

52

hormone interaction exists during the regulation (Acharya and Assmann, 2009). Methyl

jasmonate (MeJA) and its free-acid jasmonic acid (JA) regulate a spectrum of

developmental processes and activate plant defense mechanisms under stress

conditions (Alvarez et al., 2009). Since the first report of MeJA-induced stomatal

closure, MeJA signal transduction has become a new area of guard cell signaling

(Gehring et al., 1997). Both ABA and MeJA elicit stomatal movement, but it is not clear

whether the two hormones use similar or divergent signaling mechanisms. Overlapping

components have been identified in both ABA-induced and MeJA-induced stomatal

closure, e.g., production of reactive oxygen species (ROS) via AtrbohD/F and nitric

oxide (NO), activation of K+ efflux channels and slow anion channels, as well as

myrosinases (Gehring et al., 1997; Suhita et al., 2003; Munemasa et al., 2007; Saito et

al., 2009; Islam et al., 2009). Therefore a crosstalk hypothesis was proposed between

ABA and MeJA pathways in guard cells and supported by observations of MeJA

hyposensitivity of stomatal closure in the ost1 (ABA hyposensitive) mutant, reduced

ABA-mediated stomatal closure in the jar1 (MeJA insensitive) mutant, and the

involvement of ABA receptor PYL4 in the JA signaling (Suhita et al., 2004; Munemasa

et al., 2007; Lackman et al., 2011). The common responsive elements are not only seen

between the two pathways mentioned above but also existing between other stress

responses, which is known as cross-tolerance allowing plants to acclimate to a range of

different stresses after exposure to one specific stress. However, the molecular details

still remain scanty even the phenomenon has been recognized for long time.

Proteomics, the large scale analysis of cellular proteins, has become one of the

most important tools in biology and biomedical areas during the past 15 years,

53

especially fueled by the ever-growing DNA sequence information. It provides several

high-throughput platforms for characterizing gene function, building functional linkages

between pathways, and providing insights into the molecular mechanisms underlying

biological processes (Yanagida, 2002; Zhu et al., 2003). Mass spectrometry (MS)

together with multiple-dimensional liquid chromatography (LC) have evolved into a

versatile tool for examining the simultaneous expression of the total proteome as well as

the identification and mapping of post-translational modifications (Templin et al., 2002).

Furthermore, facilitated by recent advances in quantitative MS, shotgun proteomic

methods involving isobaric tagging of peptides enable simultaneous identification and

quantification of peptides using tandem MS and permit simultaneous proteome analysis

of many samples (Thompson et al., 2003). One such method is isobaric tags for relative

and absolute quantitation (iTRAQ), which uses four (4plex: reporter ions 114.1, 115.1,

116.1 and 117.1 m/z) or eight (8plex: reporter ions 113.1-119.1, and 121.1 m/z) amine

specific isobaric reagents to label the primary amines of peptides from four or eight

different biological samples (Ross et al., 2004). The labeled peptides from each sample

are mixed, separated using two-dimensional LC and analyzed using tandem mass

spectrometry (MS/MS). Because of the isobaric nature of these reagents, the same

peptide from each sample appears as a single peak in the MS spectrum. Upon collision

induced dissociation, the iTRAQ-tagged peptides fragment to release reporter ions and

b- and y-ion series among other fragments. The peak area of the reporter ions are used

to determine the relative abundance of the proteins from which they are derived. The

advantages of this technology are that it allows multiple samples to be analyzed

54

simultaneously and it is unbiased toward membrane proteins, very basic or acidic

proteins.

In this study iTRAQ followed by MS identification was employed to discover the

preferentially expressed proteins in Brassica napus guard cells. The data reveal

functional differentiation between mesophyll cells and guard cells at protein level.

Furthermore, the responsive proteins to ABA and MeJA in guard cells were identified

using the same technology, providing new evidence for the cross-tolerance

phenomenon in plants and setting up a stage for further functional characterization of

genes involved in the signaling pathways. The discovery and mapping of these

responsive components will facilitate the elucidation of the molecular mechanisms

underlying stomatal function.

Material and Methods

Plant Growth

Seeds of the B. napus var. Global were obtained from the United States

Department of Agriculture National Plant Germplasm System. Seeds were germinated

in Metro-Mix 500 potting mixture (The Scotts Co., USA), and plants were grown in a

growth chamber under a photosynthetic flux of 160 µmol of photons m-2s-1 with a

photoperiod of 10 h at 24°C in light and 20°C in dark. Fully expanded leaves from 2-

month-old plants were used for preparation of guard cell protoplasts and mesophyll cell

protoplasts.

Preparation of Guard Cell Protoplasts and Mesophyll Cell Protoplasts

Guard cell protoplasts from B. napus leaves were isolated and purified mainly as

described in the protocol developed for Arabidopsis (Pandey et al., 2002) with the

55

following modifications. Eight grams of fully expanded leaves with main veins removed

were blended three times for 30 s each in cold tap water using a 14-speed Osterizer®

blender (Oster Inc., USA). The first enzyme digestion of epidermal peels was 1 h at a

shaking speed of 140 rpm. The second enzyme digestion was 40 min at a speed of 50

rpm. The pore size of the nylon mesh used after the first and the second digestions was

100 and 30 µm, respectively. After Histopaque®-1077 (Sigma-Aldrich Co., USA)

purification, the cells were resuspended in 1 mL of basic solution. Ten microliters of the

suspension was then taken, and the number of protoplasts was estimated with a

hemocytometer. The cells were pelleted at 1000 rpm at 4C, frozen in liquid nitrogen

immediately, and stored in - 80°C freezer. Mesophyll cell protoplasts were isolated as

described previously (Chen et al., 2000) except the sucrose concentration for

purification was 0.7 M instead of 0.5 M.

Stomatal Bioassays

Aperture and H2O2 measurements were carried out as previously described

(Zhang et al., 2001; Desikan et al., 2004) with slight modifications. A couple of leaves

from a plant were blended and the epidermal strips were washed with cold tap water

(Pandey et al., 2002). The freshly prepared epidermal strips were incubated in

degassed medium (50 μM CaCl2, 10 mM KCl and 10 mM MES-KOH, pH 6.2) for 3 h

under light to promote stomata opening. After checking the stomatal aperture, the

following chemicals were added: diphenyleneiodonium (DPI) 20 μM, catalase 200 U/ml,

and ascorbic acid 10 mM, respectively. Tissues were incubated for 20 min before

addition of ABA or MeJA. Images of stomata were captured using a Zeiss Axiostar Plus

56

microscope (Carl Zeiss Inc., USA). At least 60 stomata were analyzed in each

experiment and three replicate experiments were conducted.

Protein Extraction, Digestion, 8-plex iTRAQ Labeling and Fractionation

Three independent guard cell preparations were pooled to yield one biological

replicate, which contained 80 µg total protein as measured by a CB-XTM protein assay

kit (Genotech, USA). Four control replicates and four ABA/or MeJA-treated replicates

were used for overnight acetone precipitation. After protein precipitation, the pellet was

dissolved in 1% SDS, 100 mM triethylammonium bicarbonate, pH 8.5. The samples

were reduced, alkylated, trypsin digested and labeled using the 8-plex iTRAQ® reagent

kit according to manufacturer's instructions (Applied Biosystems Inc., USA). The control

samples were labeled with iTRAQ tags 113, 114, 115 and 116 and ABA/or MeJA-

treated samples were labeled with tags 117, 118, 119 and 121. After labeling, the

samples were combined and lyophilized. The peptide mixture was dissolved in strong

cation exchange (SCX) solvent A (25% v/v acetonitrile, 10 mM ammonium formate, pH

2.8). The peptides were fractionated using SCX chromatography on an Agilent HPLC

system 1100 using a polysulfoethyl A column (2.1×100 mm, 5 µm, 300 Å, PolyLC,

Columbia, USA). Peptides were eluted at a flow rate of 200 µL/min with a linear gradient

of 0–20% solvent B (25% v/v acetonitrile, 500 mM ammonium formate) over 50 min,

followed by ramping up to 100% solvent B in 5 min and holding for 10 min. The

absorbance at 214 nm was monitored and a total of 19 fractions were collected.

Reverse Phase HPLC and Tandem Mass Spectrometry

Each SCX fraction was lyophilized and dissolved in Solvent A (3% acetonitrile v/v,

0.1% acetic acid v/v). The peptides were loaded onto a C18 capillary trap cartridge (LC

Packings, USA) and then separated on a 15 cm nanoflow analytical C18 column

57

(PepMapTM 75 µm id, 3 µm, 100 A) (LC Packings, USA) at a flow rate of 200 nL/min on

a TempoTM nanoflow multidimensional LC system (Applied Biosystems/ MDS Analytical

Technologies, USA). Peptides were eluted from the HPLC column by application of a

linear gradient from 3% solvent B (96.9% acetonitrile v/v, 0.1% acetic acid v/v) to 40%

solvent B for 2 h, followed by ramping up to 90% solvent B in 10 min. Peptides were

sprayed into the orifice of a quadrupole time-of-flight mass spectrometer (QSTAR® Elite

MS/MS system, Applied Biosystems Inc., USA), which was operated in an information-

dependent data acquisition mode where a TOF MS scan (m/z 300-1800, 0.25 s)

followed by three MS/MS scans (m/z 50-2000, 30-2000 ms) of three highest abundance

peptide ions (with charge states 2-5) were acquired in each cycle. Former target ions

were excluded for 60 s. Information dependant acquisition features of Analyst® QS

software, such as automatic collision energy (smart CE), automatic MS/MS

accumulation (smart exit) and dynamic exclusion were selected. The source nebulizing

gas and curtain gas were set at 12 and 20, respectively. Ion spray voltage was 2200V

and the temperature was 80°C.

Protein Identification and Relative Quantitation

The MS/MS data were analyzed for protein identification and quantification by

ProteinPilot™ software (Applied Biosystems Inc., USA). Proteins with one significant

quantitative ratio were included in the report. Bias correction function was used to

correct for potential labeling variation. False discovery rate was estimated by the

integrated PSPEP tool in the ProteinPilot™ Software by performing the search against a

target-decoy concatenated NCBI FASTA database for green plants (5,222,402 entries,

July 2, 2007). If one replicate showed a ratio with a p-value less than 0.05, it is

considered as significant. Only the significant ratios from the replicates were used to

58

calculate the average ratio for the protein. It should be noted that each p-value was

generated based on quantitative information derived from at least three independent

peptides (Pierce et al., 2008).

Promoter Analysis and Interactive Network Assessment

Homologous genes encoding the ABA/or MeJA responsive proteins were identified

in the NCBI Arabidopsis genome database (http://www.ncbi.nlm.nih.gov/). The motif

analysis tool (http://www.arabidopsis.org/tools/bulk/motiffinder/index.jsp) compares the

frequencies of 6 bp elements in the query set with the frequencies of the elements in the

current genomic set of 33,602 sequences. The percentage of the motif occurrence and

p-value was calculated. The p value is the probability of the occurrence of specific

nucleotide combination in the selected genes by chance. In addition, a probabilistic

functional gene network was generated by submitting all the gene loci to AraNet

(http://www.functionalnet.org/aranet/) (Lee et al., 2010).

Results

Proteins Preferentially Expressed in Guard Cells Imply Functional Differentiation of Leaf Cell Types

Guard cell isolation for proteomics

Very few analyses of single cell proteome have been reported in plants. Analysis

of trichome and root hair proteomes identified less than 100 proteins (Amme et al.,

2005; Wan et al., 2005). The pollen proteome has been more widely studied, but pollen

is not a single cell (Dai et al., 2007). Guard cells represent only a tiny percentage of the

total cells in a leaf. It is essential to isolate guard cells with high purity and adequate

quantity. The large-scale protocol for isolating Arabidopsis guard cell protoplasts was

59

established (Pandey et al., 2002). More than 1800 Arabidopsis guard cell proteins have

been identified using 2D gel and shotgun proteomic techniques (Zhao et al., 2008).

We have adapted the Arabidopsis protocol to isolate B. napus guard cells. B.

napus, the most important oilseed crop, is genetically related to Arabidopsis. The two

species share 87% sequence identity in their protein coding regions (Love et al., 2005).

The rich source of genomic sequences available for both organisms, as well as the

success in isolating high quality guard cells dramatically enhances our ability to apply

proteomics tools. The yield and purity of guard cells from B. napus are superior to those

obtained from Arabidopsis leaves. From 8 g of fully expanded leaves, the yield of guard

cell protoplasts was on average 5×105 /mL, which corresponds to ~20 µg of protein.

The purity of final guard cell preparation was above 99.6% on a cell basis with little

contamination originating from mesophyll cells and epidermal cells (Figure 2-1). Three

preparations were pooled to make one “biological” replicate, and three or four

independent experiments were conducted for proteomics analysis.

Protein identification by off-line 2D HPLC-MS/MS

After iTRAQ labeling and combination of guard cell (GC) and mesophyll cell (MC)

samples, the peptides were fractionated by SCX chromatography. A total of 19 SCX

fractions were collected. Each fraction was further separated by nanoflow reverse

phase HPLC-MS/MS. Compared with on-line 2D LC-MS, the off-line 2D LC-MS work

flow has been shown to display superior overall outcome in protein identification and

sequence coverage (Nägele et al., 2004; Qian et al., 2005). After merging the data

obtained from different experiments, a total of 1116 unique proteins were identified to be

present in both guard cells and mesophyll cells. A second set of iTRAQ LC-MS

60

experiments using purified GC identified an additional 342 guard cell proteins. So

altogether 1458 proteins from GC were identified (Figure 2-2). The 1458 proteins were

all confidently identified in guard cells because the signals for iTRAQ 114 and 115 tags

that had been used to label specifically guard cell proteins were clearly present in the

MS/MS spectra of all 1458 proteins. Searching against a reversed database allowed

calculation of false discovery rates for these experiments as 4% at the protein level. A

complete annotated sequence of the B. napus genome is not yet available. Thus other

plant species were included in our database searching to enhance the success rate of

protein identification. For cross-species identification, the mass spectra and

identification quality were carefully inspected. The identified proteins were functionally

assigned according to 1) their homology with other proteins based on protein-protein

basic local alignment search tool (BLAST) searches with an enabled conserved domain

option (Finn et al., 2006), 2) protein family database information, and/or 3) available

literature information. The proteins were classified with reference to the functional

categories established by Bevan et al. (1998). A Venn diagram for the functional

classification is shown in Figure 2-2. The identified proteins cover a wide range of

molecular functions, including photosynthesis (8%), energy (respiration) (9%),

metabolism (26%), transcription (5%), protein synthesis (9%), protein destination (11%),

signaling (7%), membrane and transport (9%), stress and defense (8%), cell structure

(2%), cell division and fate (1%), miscellaneous (3%), and unknown (3%). It should be

noted that the percentages of proteins identified in different functional categories do not

imply their representation in GC because GC and MC were combined for identification

61

in the iTRAQ experiments. Those proteins that are of low abundance in GC would

probably not be identified if only GC were used.

Identification of proteins preferentially expressed in guard cells and mesophyll cells

Of the proteins identified, 427 proteins could be quantified with at least three

different peptide MS/MS spectra and a p value smaller than 0.05 in at least one of the

experiments, and 311 proteins could be quantified in at least two of the three

independent experiments. To determine the significance threshold, ratios of replicate

samples were plotted against p values of the ratios. Repetition of the same sample type,

i.e., identical iTRAQ experiment, showed very similar overall quantification results,

whereas comparison between GC and MC revealed differentially expressed proteins.

Based on this analysis, only proteins with calculated p values (based on multiple

peptide measurements) smaller than 0.05 and a -fold change of at least 2 are included

as guard cell or mesophyll cell preferentially expressed proteins (Tables 2-1, 2-2 and

Figure 2-2). Although most published results are based on a -fold change threshold of

1.2-1.5, our criterion of 2-fold is stringent (Drummelsmith et al., 2007; Duthie et al.,

2007; Guo et al., 2007; Sui et al., 2008). There are 74 proteins and 143 proteins

differentially expressed in GC and MC, respectively. Proteins involved in energy

(respiration), signaling, transport, and transcription account for the majority of proteins

that show preferential expression in GC. In addition, four proteins involved in

nucleosome and three involved in cell structure were highly expressed in GC (Table 2-1

and Figure 2-2). On the contrary, in MC the majority of proteins (~50%) are involved in

photosynthesis followed by 23 proteins involved in metabolism and 17

disease/defense/stress proteins (Table 2-2 and Figure 2-2). Representative MS/MS

62

spectra for peptides identified from a photosystem II protein and plasma membrane H+-

ATPase AHA1 are shown in Figure 2-3. The peaks of iTRAQ signature ions (114.1for

guard cells and 116.1 for mesophyll cells) are shown as insets, representing the relative

abundance of the proteins in MC and GC, respectively. It is important to note that we

identified proteins known to specifically function in GC (most of low abundance) but

were not able to obtain reproducible quantitative information. These proteins include G

protein (Fairley-Grenot and Assmann, 1991; Wang et al., 2001b), Rac GTPase

(Lemichez et al., 2001; Mishra et al., 2006), phospholipase D 1 (Lee and Assmann,

1991), protein kinase C (Sokolovski et al., 2005), OPEN STOMATA 1 kinase (Mustilli et

al., 2002), Atrboh NADPH oxidase (Kwak et al., 2003), potassium channel (Pandey et

al., 2007), chloride channel (Pandey et al., 2007), lipid transfer protein (Smart et al.,

2000), calreticulin (Chen et al., 1994), and profilin (Kim et al., 1995).

The only available transcriptomics analysis of guard cell and mesophyll cell genes

was carried out in Arabidopsis using a microarray covering one-third of the Arabidopsis

genome (Leonhardt et al., 2004). Although 1309 genes were identified to be guard cell-

expressed, the study did not identify functional specialization of guard cells. Our

comparative proteomics of GC and MC revealed specific functions associated with the

two types of cells. When comparing proteome data with transcriptome data, 85 genes of

the 1309 genes could be matched to 110 proteins by identity (proteins identified in

Arabidopsis database) or by high homology (proteins identified in Brassica or other

species database). When the relative protein expression levels were compared with

mRNA levels, 80 displayed a similar expression trend, and 30 showed an opposite trend

of expression. For those that follow a similar expression trend at the mRNA and protein

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levels, the -fold changes at the two levels were mostly different. The correlation

coefficient is only 0.37 (Figure 2-4). Among the 74 proteins enriched in GC described in

the previous section, 15 are represented on the microarray, and nine transcripts were

identified as enriched in GC. These results confirm the general observation that mRNA

levels are not always consistent with protein levels because of post-transcriptional,

translational, or post-translational regulations (Gygi et al., 1999; Li et al., 2003;

Washburn et al., 2003), and also highlight the importance of proteomics analysis.

ABA and MeJA both Induce Stomatal Closure in Canola Associated with ROS Production

ABA has been shown to induce stomatal closure in Arabidopsis, Vicia faba and

Pisum sativum (Zhang et al., 2001; Desikan et al., 2004; Israelsson et al., 2006). MeJA

can also trigger stomatal closure in a similar pattern to ABA (Gehring et al., 1997). To

test whether this effect can be extended to B. napus, epidermal peels were treated with

different concentrations of ABA or MeJA and stomatal movement was examined. It has

been observed that 20 µM ABA or MeJA caused significant stomatal closure within an

hour. As the concentration increased, the treatment became more effective (Figure 2-5).

ROS are known to play an important role in both ABA and MeJA induced stomatal

closure (Suhita et al., 2004; Li et al., 2006). Here we confirmed ROS production in ABA-

and MeJA-treated epidermal tissues of B. napus. The oxidatively sensitive fluorophore

dichlorofluorescein was used to assay intracellular H2O2 levels (Zhang et al., 2001;

Desikan et al., 2004). Under ABA or MeJA treatment, ROS level increased dramatically.

ABA- and MeJA-induced stomatal closure and ROS production were inhibited by

diphenylene iodonium (DPI), catalase (CAT) and ascorbic acid (ASC). Catalase

converts H2O2 to water and oxygen, DPI reduces the generation of superoxide and

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H2O2 through inhibiting NAD(P)H oxidase (Chen and Schopfer, 1999), and ascorbate is

an important reducing compound for H2O2 removal (Noctor and Foyer, 1998). Its

function depends on ascorbate peroxidase and dehydroascorbate reductase, which

regulate the cellular redox state (Chen and Gallie, 2004). These results suggest that

ROS and/or the guard cell redox state are important in the ABA and MeJA signaling

processes leading to stomatal closure.

Identification of ABA Responsive Proteins Improves Understanding of the Signal Transduction in Guard Cells

The identical strategy (i.e., iTRAQ and offline 2D LC-MS) were employed for

protein identification and quantification in this study. A total of 431 unique proteins were

successfully identified based on homology searching with a common protein confidence

cutoff of 95% and with relative quantitative information in control and ABA-treated

samples. Approximately 23% and 66% of the identification matched to proteins in

Brassica and Arabidopsis accessions, respectively. When the concatenated database

was searched, the false discovery rate at protein level was estimated to be 1%. To

determine ABA-responsive guard cell proteins, the relative levels of different proteins

(indicated by the peak areas of the different iTRAQ tags) were compared between

control samples and ABA-treated samples. A threshold of 1.5-fold change together with

p-value smaller than 0.05 were set as stringent criteria for significant difference between

control and treatment. A total of 66 proteins were observed with increased expression

and 38 showed substantial decreases in abundance (Tables 2-3 and 2-4). The ABA-

responsive proteins were grouped into different functional categories (Figure 2-6) with

reference to Bevan et al. (Bevan et al., 1998).

65

Up-regulated proteins in guard cells under ABA treatment

Proteins involved in photosynthesis and stress/defense are the two large groups of

proteins whose levels were increased by ABA. Although photosynthesis is not a

dominant process in guard cells, it is supposed to provide energy and reductants to

maintain the redox state through the ferredoxin/thioredoxin (TRX) system (Vavasseur

and Raghavendra, 2005; Fujino et al., 2006). In this study, several proteins in the two

photosystems, ATP synthase CF1 subunit, ribulose-1,5-bisphosphate

carboxylase/oxygenase (Rubisco) activase, and cytochrome C oxidase and enolase

involved in respiration were found to be increased in response to ABA (Table 2-3).

These results are consistent with the function of energy-providing and redox state

maintenance in guard cells.

Stress and defense related proteins constitute another large group of proteins

increased in abundance by ABA (Table 2-3). Among them are stress-induced protein

KIN2 and lipoxygenase (LOX). The expression of their genes has already been shown

to be ABA inducible. KIN2 expression was initially reported to be cold-inducible, but

later shown to be elevated by ABA, drought and salinity (Acevedo-Hernández et al.,

2005). Rapid induction of LOX gene expression was observed as a result of water

deficit (Erin and Mullet, 1991). Transcriptional changes of these genes correlate well

with the protein level changes observed here. In addition, an enhancer of SOS3-1,

ENH1 was found to be induced by ABA. ENH1 encodes a chloroplast-localized

rubredoxin-like protein, which plays an important role in the detoxification of ROS under

salt stress (Zhu, 2004). Interestingly, proteins such as myrosinase, myrosinase-

associated protein (MyAP) and thiol methyl-transferase were also found with increased

levels by ABA (Table 2-3). Myrosinases, which degrade glucosinolates, belong to a

66

family of enzymes involved in plant defense against pathogens and herbivores (Yan and

Chen, 2007). Recently, the glucosinolate-myrosinase system has been reported to be a

key element in ABA signaling in guard cells (Zhao et al., 2008). Myrosinase is a

thioredoxin (TRX) target and is subjected to thiol-base redox regulation in Arabidopsis

(Marchand et al., 2004). MyAP has been purified from seeds of B. napus both in

complex with myrosinase and in a free form (Taipalensuu et al., 1996). It contains at

least one intramolecular disulfide bond and was observed to respond to wounding and

methyl jasmonate (Taipalensuu et al., 1996). Thiol methyltransferase was found to be

involved in the detoxification of glucosinolate hydrolysis products in B. oleracea (Attieh

et al., 2000). Our data together with the previous reports suggest that guard cell ABA

networks involve plant stress and defense components, some of which such as

myrosinases are potentially redox regulated.

It is interesting to note that while ABA-induced ROS production (Figure 2-5), it may

also activate ROS/oxidative stress removal systems. The proteins in this category

include ascorbate peroxidase (APX) (a key enzyme for H2O2 removal in plants),

phospholipid hydroperoxide glutathione peroxidase (PHGP) (an important enzyme for

removing lipid hydroperoxides from cell membranes), glutathione S-transferase 8

(GST8) (essential for detoxification of xenobiotic compounds), and cyclophilins (CYP)

(important for peroxiredoxin (PRX) regeneration) (Chatfield and Dalton, 1993; Marrs,

1996; Neuefeind et al., 1997; Wang et al., 2001a; Motohashi et al., 2003). Surprisingly,

PRX and TRX were actually decreased in abundance by ABA (Table 2-4). This finding

implies that additional complexity exists in the redox signaling network in guard cells. In

addition, different isozymes may be regulated differently and thus exhibit different

67

functions. For example, the increased GST8 was found to be induced by drought-

associated oxidative stress and counteract ROS production (Bianchi et al., 2002). In

contrast, GST6 was decreased in levels by ABA (Table 2-4). These two GSTs share

very low amino acid sequence identity and their functions in ABA signaling remain to be

characterized.

Other interesting proteins increased by ABA include protein disulfide isomerase

(PDI), Rab GDP dissociation inhibitor and ALTERED RESPONSE TO GRAVITY 1

(ARG1). PDI is known to assist in the folding of proteins through disulfide bond

formation. Its active site closely resembles that of TRX and it is regulated by TRX

(Freedman et al., 1997; Marchand et al., 2004). Rab GDP dissociation inhibitor plays an

essential role in regulating the nucleotide state and subcellular localization of small

guanosine triphosphatases Rab/Ypt proteins. It controls the GTPase cycle of Rab/Ypt

proteins to ensure their proper functions in membrane trafficking, which might be related

to ABA signal reception (Ueda et al., 1998). ARG1 was hypothesized to function in

gravitropic signaling and affects the localization and activity of the auxin transporter,

PIN1 (Boonsirichai et al., 2003). ARG1 is a peripheral membrane protein that modulates

gravity-induced cytoplasmic alkalization. Since ABA also triggers cytosolic alkalization

to enhance K+ out-rectifying channel activity in guard cells, ARG1 may be a common

node shared between ABA and gravity signaling pathways (Ilan et al., 1994).

Down-regulated proteins in guard cells under ABA treatment

Distinct from the functions of the proteins with increased abundance, the 38

proteins decreased in abundance occupy a wide variety of functional categories

including metabolism, protein synthesis, energy, protein folding/transport/degradation,

and membrane and transport (Table 2-4 and Figure 2-6). Metabolism, protein synthesis

68

and energy constitute the three largest groups. In the metabolism group, proteins

decreased in abundance belong to a variety of pathways including spermidine

synthesis, rhamnose biosynthesis, jasmonic acid biosynthesis, fatty acid beta-oxidation,

purine metabolism and alkaloid biosynthesis. Some of the pathways are important to

plant stress and defense. Spermidine synthase was found to be essential for

Arabidopsis growth (Imai et al., 2004). Overexpression of this enzyme enhanced plant

tolerance to multiple environmental stresses (Kasukabe et al., 2004). Spermidine was

suggested to function as a regulator in stress signaling pathways that led to the build-up

of stress tolerance mechanisms in plants (Kasukabe et al., 2004). The enzyme 12-

oxophytodienoate-10,11-reductase (OPR) catalyzes the reduction of 12-

oxophytodienoic acid to produce jasmonic acid (JA) (Turner et al., 2002). The reduced

expression of OPR induced by ABA suggests that there is crosstalk between the ABA

and JA signaling pathways in guard cells. ABA regulation of these metabolic enzymes

has not been reported and deserves further investigation.

Several enzymes involved in cellular respiration were found to be repressed

following ABA treatment, including glyceraldehyde-3-phosphatedehydrogenase

(GAPDH), putative malate dehydrogenase (MD), galactose kinase, succinic

semialdehyde dehydrogenase (ALDH5F1), and fructose-1,6-bisphosphate aldolase

(F1,6BP). Several of these enzymes are known to be redox regulated. For example,

cysteine 149 of GAPDH is critical because it can be S-nitrosylated and thereby

regulates enzyme activity (Giustarini et al., 2005). MD also contains thiols with potential

to be oxidized. Both GAPDH and MD have been identified as TRX targets (Hara et al.,

2006; Fermani et al., 2007). How the redox regulation and activity changes relate to

69

their protein levels is not known. It is worth noting that the expression of ALDH5F1 was

decreased by ABA. This enzyme is part of a metabolic pathway that bypasses two steps

of the tricarboxylic acid cycle. It was reported to be rapidly increased in response to

stress conditions in order to prevent ROS accumulation and cell death (Bouché et al.,

2003).

It should be noted that some membrane and transport proteins were reduced in

abundance by ABA (Table 2-4). Coatomer is a cytosolic heterooligomeric protein

complexed with dilysine motifs typically found in the cytoplasmic domains of ER

membrane proteins. It might function in the signal perception and transduction process

(Harter et al., 1996). Ca2+-dependent membrane-binding annexins are implicated in the

cellular response to cytosolic acidification (Gorecka et al., 2007). An Arabidopsis

annexin mutant displayed hypersensitivity to osmotic stress and ABA. It was suggested

that annexins play important roles in osmotic stress and ABA signaling (Lee et al.,

2004). Furthermore, Rubisco was the only protein in photosynthesis found to be

decreased by ABA. In embryogenesis, exposure of cotyledons to ABA led to decreased

Rubisco levels in Phaseolus vulgaris, but the underlying mechanism remains unknown

(Medford and Sussex, 1989).

Promoter analysis of the gene homologs in Arabidopsis

Previous studies of ABA-inducible promoters identified the cis-acting sequences,

including the G-box-containing elements designated ABA-regulated elements (ABREs),

the functionally equivalent coupling element 3 (CE3) like sequences and the Myb/Myc

binding sequences (Busk and Pages, 1998). Here we used the classical ABREs

available in the PLACE database to evaluate our data set. In this study, 66 and 38

guard cell proteins were increased and decreased in abundance by ABA, respectively.

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The upstream 500 bp of the genes encoding these ABA-regulated proteins were

examined for the common cis-regulatory elements. Table 2-5 lists all motifs containing

an ACGT core sequence and occurrence in each group. Most of these genes (76 out of

104, 73.1%) contain an ACGT sequence, which has been reported to be the core of

ABA-responsive elements (ABREs) (Skriver et al., 1991; Simpson et al., 2003).

Derivative elements include ACGTG, ACGTGKC, YACGTGGC and CCACGTGG. The

ACGTG sequence is required for etiolation-induced expression of ERD1 (EARLY

RESPONSE TO DEHYDRATION 1) (Simpson et al., 2003). It is the most abundant

element of ABREs in our analysis (40 out of 76, 52.6%). ACGTGKC was experimentally

determined to be an ABRE of a rice gene OSEM and an Arabidopsis dehydration and

high-salinity inducible gene RD29A (Hattori et al., 2002; Narusaka et al., 2003).

YACGTGGC and CCACGTGG have also been found to be ABREs in the promoters of

ABA and/or stress-regulated genes in Arabidopsis, maize and Populus spp (Choi et al.,

2000; Guan et al., 2000; Kang et al., 2002; Benedict et al., 2006). Interestingly, the

occurrence of ACGT core sequence in the increased group (52 out of 66, 78.8%) is

higher than that in the decreased group (24 out of 38, 63.2%). This finding is consistent

with the result of microarray data analysis, in which the occurrence of ACGT-containing

sequences in the up-regulated genes is much higher than that of the down-regulated

ones in Arabidopsis guard cells (Leonhardt et al., 2004). Table 2-5 B to D lists the most

abundant ACGT-containing 6 bp sequences in each group. ACGTGG, CCACGT,

ACACGT and ACGTGT are the most abundant elements in increased group. It was

noted that a G or C next to the core sequence occurs much more frequently. However,

the forms of such core-containing elements vary in the decreased group. T or A occurs

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more frequently adjacent to the ACGT core in the motifs within this group. Among all

regulated groups, the ACGTG and CACGT motifs show the highest occurrence, which

is consistent with the PLACE analysis. The result of ABRE analysis provides strong

support to the hypothesis that these genes are potentially regulated at transcriptional

level.

Identification of MeJA Responsive Proteins in Guard Cells Reveals Crosstalk in Plant Hormone Signaling Pathways

Two complementary ionization methods - electrospray ionization (ESI) and matrix-

assisted laser desorption/ionization (MALDI) with tandem MS were utilized to identify

and quantify iTRAQ samples. Each iTRAQ labeled fraction was divided into three

aliquots and submitted onto three different mass spectrometry platforms, i.e., AB SCIEX

QSTAR® XL, AB SCIEX TOF/TOF™ 5800 and AB SCIEX TripleTOF™ 5600 (Applied

Biosystems Inc., USA) separately. Figure 2-7 A shows 491, 892 and 1137 proteins were

identified with a threshold 1.3 of the unused score by the three MS platforms,

respectively. Based on the sequence, the three platforms profiled 1220 non-redundant

proteins in total for the Brassica napus guard cell proteome. Figure 2-7 B shows the

Venn diagram of the guard cell proteins for the three parts of results. Within the

overlapping IDs from different mass spectrometers, TOF/TOF™ 5800 and Triple TOF

5600 usually give higher unused scores, indicating better significance for the

identification. This could be either due to the higher sensitivity of the new generation

mass spectrometry or the advantages of the MALDI method. All these results support

that the two ionization methods and different analyzers will generate better coverage of

the proteome components in a certain material.

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Identification of MeJA responsive proteins in Brassica napus guard cells

Based on the data collected from the three mass spectrometry platforms, a total of

76 and 47 proteins were identified to be up- and down- regulated under MeJA treatment

in Brassica napus guard cells using threshold with at least 1.5-fold change and p value

smaller than 0.05 (Table 2-6 and Table 2-7). Figure 2-8 shows the functional

classification of the responsive proteins. The majority groups among these responsive

proteins include metabolism, stress and defense, energy and photosynthesis.

Compared to the data of guard cell ABA responsive proteins, the profile of MeJA

responsive proteins are similar, indicating convergence of signaling cascades and

analogous metabolic changes under different treatments.

Among the up-regulated proteins, it is interesting, but not surprising to note several

proteins related to ROS scavenging (Table 2-6), e.g., two different superoxide

dismutases and ascorbate peroxidase. Superoxide dismutases (SOD) catalyze the

dismutation of superoxide into oxygen and hydrogen peroxide and thus constitute the

first line of the antioxidant defense for plants. SODs are classified by the metal

cofactors, the copper/zinc (Cu/Zn SOD), manganese (Mn SOD), and iron (Fe SOD)

forms. In plants, Fe SOD has been inferred to locate in chloroplasts while Mn SOD is

only present in mitochondria and peroxisomes (Alscher et al., 2002). The expression

level and enzyme activity of two types SOD are sensitive to various stresses, like

chilling, drought and salinity. However, the regulative mechanism may differ due to their

different subcellular locations (Tsang et al., 1991; Bowler et al., 1992). The large

distribution of responsive proteins identified in the photosynthesis and energy groups

(Table 2-6, Table 2-7 and Figure 2-8) indicate significant changes of the physiological

processes occurring in chloroplast and mitochondria. Therefore, Fe SOD and Mn SOD

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might be involved in separate antioxidant pathways under MeJA treatment and have

specific targets in each compartment. Some other proteins were also activated to

remove the ROS/oxidative stress induced by MeJA, including lipoxygenase (LOX),

ascorbate peroxidase (APX), 2-cysteine peroxiredoxin (PRX) and two glutathione-S-

transferases (GST). Rapid induction of LOX gene expression was observed as a result

of water deficit, wounding and MeJA (Erin and Mullet, 1991). Thus, the transcriptional

level change correlates well with the protein level observed here. APXs are key

regulators of intracellular levels of H2O2 in plants and APX1 has been found to

accumulate during the acclimation to drought and heat stress (Chatfield and Dalton,

1993; Koussevitzky et al., 2003). The 2-cysteine peroxiredoxin was identified as a

thioredoxin target protein and involved in the protection of the photosynthetic apparatus

against oxidative damage (Broin et al., 2002). GSTs are glutathione-dependent

detoxifying enzymes with diverse functions in plants. These antioxidant proteins may

interact with each other to modulate the redox status in guard cells, which is important

in the MeJA signal transduction.

Not only is the ROS scavenging system activated in response to MeJA, but also a

group of stress protein called heat shock proteins (HSPs). HSPs protect cells from injury

and facilitate recovery and survival from stress conditions. HSP70-1 is a molecular

chaperone responsive to various environmental stresses. The tobacco NtHSP70-1 was

found to be a drought-/ABA-inducible gene and the over-expression contributes to plant

drought-stress tolerance (Cho and Hong, 2006). The protective role of the chaperone

HSP70 against stress may be associated with preservation of protein structure and

membrane integrity as well as with the maintenance of high secretory activity mediated

74

by stress adaptive cellular response (Finka et al., 2011). HSP81-3 and HSP81-4 are

members of HSP90 gene family in Arabidopsis, which are highly conserved and

essential for cell survival. HSP81-3 is constitutively expressed and only moderately

induced by heat treatment. Unexpectedly, over-expression of HSP81-3 could impair

plant tolerance to heat stress (Xu et al., 2010). HSP81-4 has high DNA sequence

identity (97%) to HSP81-3 and they locate closely on the same chromosome,

suggesting that they arise from a recent gene duplication event. In general, the

homeostasis of HSP90 is critical for cellular stress response and/or tolerance in plants

(Takahashi et al., 2003). Although HSP-ubiquitin conjugates were not detected, one of

the 26S proteasome regulatory subunit RPT5a was up-regulated. In addition, the

increase of other 26S proteasome subunits RPN6a and RPN1a were detected with low

significance. All the data indicate HSPs and the ubiquitin/26S proteasome system are

important to control the activities and levels of cellular proteins in plant stress response

and tolerance (Smalle and Vierstra, 2004).

Other defensive mechanisms might include gene silencing based on the

proteomics data. The WD-40 repeat protein MSI4 has been reported to express in

guard cells and epigenetically regulate various developmental processes via forming

ubiquitin ligase complex (Zhao et al., 2008; Pazhouhandeh et al., 2011). An

aminomethyltransferase-like precursor protein was found to be MeJA responsive,

suggesting the epigenetic regulation in the MeJA signaling in guard cells. Other proteins

involved in the small interfering RNA (siRNA)-mediated gene silencing, e.g., argonaute

4 (AGO4) were detected to be down-regulated. The same observation was reported in

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the ABA guard cell proteomics studies, revealing another common node between the

two pathways (Zhu et al., 2010).

Among all the stress related proteins, Arabidopsis NONHOST1 (NHO1,

AT1G80460) encodes a protein similar to glycerol kinase, which converts glycerol to

glycerol 3-phosphate. It is required for limiting the in-planta growth of nonhost

Pseudomonas bacteria but completely ineffective against the virulent bacterium

Pseudomonas syringae pv. tomato DC3000 (Lu et al., 2001). Most of the stress induced

proteins identified here have been reported to be responsive to abiotic stimuli. The

NHO1 is an interesting component considering MeJA induction by pathogen invasion

(Liechti and Farmer, 2002). Remarkably, several other interesting proteins were also

increased in abundance under MeJA treatment. Protein phosphatase 2A (PP2A)

regulatory subunit was found to interact with chaperone co-factors CHIP (Carboxyl

terminus of Hsc70-Interacting Protein) and plays a role in temperature and dark stress

responses (Luo et al., 2006; Blakeslee et al., 2007). The data indicate a potential

phosphorylation switch, which is regulated by phosphatase and protein kinase, is

involved in MeJA signaling. In addition, a serine-threonine protein kinase SRK2E was

identified to be responsive to MeJA, the homolog of which in Arabidopsis is OPEN

STOMATA 1 (OST1). OST1 is known to mediate the ABA induced stomatal movement

and act upstream of ROS production (Mustilli et al., 2002). Recently the OST1 kinase

has been reported to function in bicarbonate activation of S-type anion currents in guard

cells and in CO2-induced stomatal closure (Xue et al., 2011). The observation of OST1

as responsive protein to MeJA implies the central role of OST1 kinase and the

convergence of the ABA, MeJA, and CO2 signal transduction pathways in stomatal

76

guard cells (Munemasa et al., 2007). Together with other identified proteins related to

phosphorylation, including a mitogen-activated protein kinase and phospholipase D, it is

obvious that phosphorylation and dephosphorylation play pivotal roles in MeJA signal

transduction in guard cells. Furthermore, the increase of cytosolic-free calcium

concentration ([Ca2+]cyt) was suggested to be a common event in the course of stomatal

closure, e.g., induced by ABA (Li et al., 2006; Acharya and Assmann, 2009). Here we

found calmodulin, calcium binding proteins, and an extracellular calcium sensing

receptor were responsive to MeJA, which indicates the calcium plays a key role in MeJA

signal transduction.

The four major groups of proteins (metabolism, energy, photosynthesis, stress and

defense) dominate the 47 down-regulated proteins, but not the up-regulated proteins.

Other functional categories include membrane and transport, transcriptional related and

signaling (Table 2-7 and Figure 2-3). The levels of several membrane proteins

decreased after MeJA treatment, for example, aquaporin, a vacuolar membrane proton

pump (AVP1), and two subunits of coatomer. The aquaporin contributes to hydrostatic

pressure-induced water transport in Arabidopsis roots and leaves, and facilitates the

transport of CO2 (Postaire et al., 2010; Heckwolf et al., 2011). AVP1 belonging to the V-

PPase (H+ translocating pyrophosphatases) family was also decreased after MeJA

treatment. The enzyme exists in homodimeric form and utilizes energy from

pyrophosphate (PP) hydrolysis to drive H+ uptake into vacuoles. The expression of

AVP1 in cotton was reported to enhance drought- and salt-tolerance and to increase

fiber yield (Pasapula et al., 2011). In contrast, DET3, representing a V-ATPase

(vacuolar-type H+-ATPase) subunit was found to be up-regulated. Here the role of

77

vacuole as a proton sink is highlighted since the accumulation of H+ into vacuole

depends on the activity of V-ATPase and V-PPase (Assmann, 1993). The H+ pumping

activity in vacuolar membranes may energize the dynamic changes of vacuoles.

Coatomer, with the clathrin binding capacity, functions in the vesicle-mediated transport.

The abundance decrease of coatomer was also observed in the ABA treated guard cells

(Table 2-4). All these membrane transport proteins might coordinate to establish and

maintain the transmembrane electrochemical gradient, especially in vacuoles, to control

stomatal movement. Myrosinase TGG2 has been reported to be highly abundant in the

vacuoles (Catter et al., 2004). The identification of TGG2, although the changes are

different between the ABA and MeJA treatments, supports the notion that ABA and

MeJA signaling pathways share common components.

Promoter and functional network analysis of the homologous genes in Arabidopsis

To correlate protein changes with transcriptional control, the upstream 500bp of

homologous genes in Arabidopsis encoding the identified MeJA-responsive proteins

were examined for the common cis-acting elements. Different (Me)JA-responsive

elements (JREs) have been identified in several plant species, including potato,

soybean, tobacco and Arabidopsis. The most common JREs include a GCC motif or a

G box CACGTG (Rouster et al., 1997; Menke et al., 1999; Vom Endt et al., 2007; Brown

et al., 2003).Table 2-8 lists all 6bp elements containing the GCC core sequence and the

G box with the occurrence in all the genes. The majority of the genes (114 out of 123)

contain either the GCC motif or a G box sequence in the upstream 500bp region. Our

result of JRE analysis provides strong support to the hypothesis that these genes are

potentially regulated at transcriptional level. Additionally, all the MeJA responsive genes

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were submitted to AraNet (http://www.functionalnet.org/aranet/) for probabilistic

functional network analysis (Lee et al., 2010). Among the 123 genes, 105 are connected

to one another, which provides hints for potential protein-protein interactions and

coexpression at transcriptional levels. The responsive genes not only form a functional

network, but also show high overlapping with other stress responsive genes. Functional

annotation clustering shows the MeJA responsive genes were also involved in abiotic

stress response, such as heat, cold and metal and biotic stress defense, e.g., bacteria

(Figure 2-9). This provides further molecular evidence for plant cross-tolerance to stress

conditions.

Discussion and Conclusion

Here the guard cell isolation procedure from Arabidopsis was adapted to isolate

guard cells from B. napus, one of the most important oil crops in the world and a close

relative to Arabidopsis. A recently developed iTRAQ proteomics technology was

employed to profile the B. napus guard cell proteome and identify ABA/MeJA

responsive proteins in guard cells. More than 1450 non-redundant proteins were

identified from guard cell and mesophyll cell samples, of which 74 are preferentially

expressed in guard cells. The results have not only revealed the functional

differentiation between guard cells and mesophyll cells but also provide molecular

evidence correlating the proteins to the guard cell functions.

Although most proteomics studies tend to use intact organs and tissues that

contain many different cells, proteomics of individual cell types or organelles has

become increasingly important because it allows fine dissection of cellular or organelle

functions (Majeran et al., 2005; Dunkley et al., 2006; Sarry et al., 2007). Although the

guard cell isolation procedure is tedious and the yield is relatively low, obtaining

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proteomics quality and quantity material is not limiting. The advantages of working with

a crop plant closely related to Arabidopsis are severalfold. First, B. napus guard cells

are larger and have higher protein contents than Arabidopsis guard cells. Second, the

knowledge gained in Arabidopsis and B. napus may be transferrable based on the

conservation of the two plant species (Love et al., 2005). Third, the genomics resources

and functional genomics tools developed in Arabidopsis can be harnessed to address

fundamental questions of guard cell functions. Last and not the least, results obtained in

B. napus can be applied to the enhancement of stress tolerance and production of

oilseeds and biofuels.

iTRAQ labeling technology has been developed for relative and absolute

quantification of proteins. It has immense potential to improve the sensitivity and quality

of mass spectrometric analysis of the proteome (Gan et al., 2006; Pierce et al., 2008).

We demonstrated the usefulness of the technology to label peptide mixtures derived

from proteins extracted from GC and MC and, using LC-MS/MS, to identify and quantify

the relative levels of the peptides emanating from the two types of samples. In the

iTRAQ approach, the peptides from different samples are combined and appear as one

peak in MS, thus increasing the total ion current for that peptide. This is advantageous

for obtaining good quality MS/MS spectra for identification of low abundance proteins. In

this study, we identified 1458 unique proteins, many of which are of low abundance and

would otherwise have escaped identification if the samples had not been combined. For

quantification, because it is based on individual iTRAQ tags associated with different

samples, the combination of different samples has little effect on quantitative results.

For almost every identified protein, relative quantitative information was obtained from

80

at least one of the three different experiments. However, the relative expression ratios

of over half of the proteins either have high p values (>0.05) or no p values. This

generally seems to be the case when iTRAQ experiments are done and analyzed using

the current version of ProteinPilot software. ProteinPilot software only uses MS/MS

spectra unique to a particular protein and peak pairs with a sum of the signal-to-noise

ratio over 9 for quantification (default software settings). In addition, at least three

spectra are needed to determine the statistical significance of a change in protein levels

(Shilov et al., 2007). This software algorithm aiming at high quality and high accuracy

quantitation may compromise the end results of the total number of proteins with

confident changes.

Comparative proteomics using iTRAQ technology and LC-MS/MS has revealed

the functional differences between MC and GC. Proteins involved in respiration were

much more abundant in GC than in MC. Proteins associated with transport and signal

transduction, including channels, ATP synthase, protein kinases, 14-3-3 protein,

calmodulin, and phosphatases, were also more abundant in GC. In contrast, proteins

associated with photosystems, the Calvin cycle, and starch synthesis were more

abundant in MC than in GC. A higher proportion of proteins for respiration, signal

transduction, and transport and a lower proportion of the photosynthetic proteins

indicate that GC devote more cellular activities to processing environmental or

endogenous stimuli than to metabolic activities. Several signaling proteins were found to

be highly expressed in B. napus GC, including calmodulin, 14-3-3 proteins, mitogen-

activated protein kinases (MAPKs), protein phosphatase 2A protein and a glycine-rich

RNA-binding protein (Table 2-1). This is consistent with the expected roles of guard

81

cells in processing diverse signals to regulate stomatal movement. The lower proportion

of photosynthetic activity, in particular, is consistent with the previously known

physiological data (Parvathi and Raghavendra, 1997; Outlaw and De Vlieghere-He,

2001). In the protein turnover category, several proteins preferentially expressed in GC

are involved in ubiquitination and proteasome degradation (Table 2-1). Protein

degradation activity has rarely been studied in GC. This finding highlights the potential

significance of protein turnover in guard cell function. Consistent with the possibly high

protein turnover rate, GC may have high gene transcriptional activities or regulations,

facilitating efficient responses to environmental factors.

Despite advances in transcriptomics, global analysis of protein components is

important. Comparison of the iTRAQ proteomics data set with the Arabidopsis cDNA

microarray data set allows estimation of the correlation between transcripts and proteins.

Although many proteins shown to be highly abundant in guard cells displayed a similar

trend at the transcriptional level, the exact -fold changes were mostly of a low degree of

consistency (Figure 2-4). This is not surprising because post-transcriptional,

translational, and post-translational mechanisms regulate protein isoforms and their

quantities. iTRAQ proteomics is important to identify quantitative changes of different

protein species for which little can be reflected at the mRNA levels. The iTRAQ

proteomics approach allows the analysis of relative abundance of all proteins in a

sample including both membrane and soluble proteins, whereas the traditional 2D gel

electrophoresis-based proteomics tends to focus on identifying soluble proteins and to

quantify gel spots, each often containing more than one protein (Chen and Harmon,

2006). With the development of 8-plex iTRAQ reagents, protein identification and

82

quantification technology will be greatly advanced, especially the possibility of including

more replicates within the same sample preparation, and mass spectrometry analysis

will greatly improve reliability and accuracy of protein quantification (Gan et al., 2006;

Pierce et al., 2008). In conclusion, we have shown the utility of iTRAQ proteomics

technology in identifying and quantifying proteins in GC and MC. This study has

unveiled many differentially expressed proteins, indicating functional specialization of

the two types of cells in B. napus. Although the homologs of some of the proteins have

been studied in other species, rarely any has been functionally characterized in B.

napus GC.

With the successful application of iTRAQ technology in characterization of B.

napus guard cell and mesophyll cell proteomes, another two sets of experiments were

designed to investigate ABA and MeJA responsive protein in guard cells. Physiological

analysis has confirmed that both ABA and MeJA could promote stomatal closure in

association with enhanced ROS generation in B. napus epidermal peels. In total 66

proteins were found with abundance increase whereas 38 were found to be decreased

in response in ABA (Table 2-3, Table 2-4 and Figure 2-6). The functional distribution of

increased and decreased proteins is distinct. Many of the genes encoding these

proteins contained ABREs in their upstream regions, suggesting direct ABA regulation

at the transcriptional level. In MeJA experiments, 76 and 47 proteins were identified to

be up- and down-regulated (Table 2-6, Table 2-7 and Figure 2-8). Functional

classification of the MeJA responsive proteins shows a similar distribution pattern as

ABA. The identification of redox proteins in both cases together with the physiological

observation of ROS levels highlights redox regulation as a potential mechanism in the

83

guard cell ABA and MeJA signaling. Our results established a comprehensive inventory

of ABA- and MeJA-responsive proteins, providing clues to identify new proteins that are

potential components of ABA and MeJA signaling networks in guard cells. For example,

a Bet v I allergen family protein was identified from our ABA treated guard cells and

later proven to be a soluble ABA receptor PYL2 (Melcher et al., 2009).

Recently more and more reports on the identification of stress responsive proteins

in plants using robust proteomic tools have been published (Chen et al., 2009; Pastori

and Foyer, 2009; Chen et al., 2011). The high throughput workflow has facilitated the

discovery of stress biomarkers, either universal or unique in certain process. Here we

observed common components in MeJA treated guard cells with samples of other

stress treatment. Although it is not surprising since plants make use of common

pathways and elements in the stress-response relationship, known as cross-tolerance,

the molecular details are still largely unknown (Sabehat et al., 1998; Capiati et al.,

2006). The interaction between ABA and MeJA signaling pathways in guard cells is of

our great interest because both phytohormones are stress inducible and associated with

stomatal closure. Our data have provided strong evidence for the crosstalk hypothesis

in which the key regulative elements, e.g., phosphorylation/dephosphorylation, ROS

production and calcium dependent signaling events, together with other shared

components, such as myrosinase are known to be involved in both pathways

(Munemasa et al., 2007; Islam et al., 2009). The activation of ROS scavenging system

might serve as an important mechanism towards quenching the ROS burst as the

consequence of ABA and MeJA application. Considering proteins related to other

stresses, especially proteins participating in redox regulation, common sets of proteins

84

are often observed, indicating that similar stress responsive mechanisms are used. This

explains the cross-tolerance phenomenon, i.e., plant response to one type of stress

condition will generate tolerance to another stress condition (Pastori and Foyer, 2002).

The cross-tolerance is a very important protective mechanism to plants‟ survival and

productivity since plants could be simultaneously subject to various environmental

stresses. Additionally, the identification of common components such as AGO4 between

the ABA and MeJA data highlights that gene silencing mediated by small RNA could be

employed as another protective mechanism in the two pathways. It will be interesting to

investigate the role of coatomer and the function of its corresponding subcellular

vesicles in guard cell signaling networks. Although the comparison was conducted from

protein level to transcriptional level and usually the two don‟t correlate well, it still

provides new information on the interaction of responses to different stresses, and most

importantly, the components regulating these responses. Future research focusing on

functional characterization using multidisciplinary tools including reverse genetics,

biochemistry and physiology will detail involvement of the proteins and improve

understanding of ABA and MeJA signaling networks in guard cells. This knowledge can

be applied via modeling to predict routes for rational engineering of important crops for

improving water usage, better yield and enhanced stress tolerance.

85

Table 2-1. Proteins predominantly expressed in guard cells. 2

Accession Protein Experiment 1 Experiment 2 Experiment 3 Average

GC/MC P-value GC/MC P-value GC/MC P-value GC/MC

Energy (16)

gi|15226479 Triose-phosphate isomerase (TIM ) 1.781 0.000 2.044 0.000 2.226 0.001 2.000

gi|15229231 Glyceraldehyde-3-phosphate dehydrogenase C subunit 5.087 0.070 2.777 0.004 5.453 0.020 3.680

gi|15233272 Cytosolic triose phosphate isomerase 1.920 0.000 2.018 0.000 4.702 0.007 2.441

gi|15236591 Aldose 1-epimerase family protein 2.370 0.001 2.603 0.001 4.070 0.063 2.481

gi|15238151 6-phosphogluconate dehydrogenase 2.051 0.012 2.582 0.009 2.286

gi|15240075 Succinate dehydrogenase 1-1(SDH1-1 ) 2.248 0.023 2.041 0.026 1.001 0.998 2.139

gi|21536853 Putative phosphoglycerate kinase 2.166 0.026 2.467 0.020 2.779 0.043 2.445

gi|21592878 Inorganic pyrophosphatase-like protein 2.132 0.003 2.027 0.001 2.078

gi|30689081 Phosphoenolpyruvate carboxylase 2(ATPPC2) 7.017 0.000 4.701 0.001 3.180 0.232 5.630

gi|30696904 Xylose isomerase family protein 2.252 0.043 2.169 0.019 1.939 0.381 2.210

gi|3676296 Mitochondrial ATPase beta subunit 3.088 0.003 2.567 0.003 2.121 0.009 2.532

gi|79314806 Mithochondrial ATP synthase D chain(ATPQ) 2.171 0.017 1.919 0.011 2.037

gi|51102306 Putative glyceraldehyde 3-phosphate dehydrogenase 2.142 0.014 2.089 0.021 2.115

gi|34597332 Enolase 1.807 0.003 1.516 0.206 2.525 0.003 2.106

gi|4874272* Putative protein with PEP/pyruvate binding domain. 2.223 0.045 1.870 0.219 2.223

gi|68426 Triose-phosphate isomerase 2.021 0.000 2.043 0.000 2.276 0.135 2.032

Metabolism(13)

gi|15222072 UDP-D-glucose/UDP-D-galactose 4-epimerase 1 (UGE1) 1.923 0.004 2.187 0.001 2.046

gi|147742770 Hypothetical protein,containing PRK10675 UDP-galactose-4-epimerase domain

1.902 0.018 2.190 0.008 2.036

gi|15242351* Reversibly glycosylated polypeptide-3 0.181 0.635 3.872 0.013 3.872

gi|15241721* Putative protein,containing pfam02719 domain 3.630 0.383 3.064 2.055 0.025 2.055

gi|15239735* Thiazole biosynthetic enzyme precursor (ARA6) 2.438 0.005 2.438

gi|15239772 Aspartate aminotransferase 2 (ASP2) 2.293 0.005 2.127 0.045 2.207

gi|599625* Aconitase 1.132 0.749 1.135 0.589 3.311 0.020 3.311

gi|3334244 S-D-lactoylglutathione methylglyoxal lyase 2.464 0.043 1.994 0.005 1.338 0.338 2.205

2 Proteins with p value smaller than 0.05 in only one of the independent replicates are highlighted with asterisk.

86

Table 2-1. Continued.

Accession Protein Experiment 1 Experiment 2 Experiment 3 Average

GC/MC P-value GC/MC P-value GC/MC P-value GC/MC

gi|7385217* Beta-ketoacyl-ACP synthetase 1 1.406 0.161 2.113 0.036 1.375 0.526 2.113

gi|15226618* Putative fumarase 2.467 0.006 1.860 0.052 2.467

gi|116077986 Pterocarpan reductase 2.479 0.021 3.614 0.021 2.941

gi|157890952* Putative lactoylglutathione lyase 3.311 0.254 2.559 0.320 3.114 0.011 3.114

gi|15241492 Formate dehydrogenase (FDH) 2.419 0.007 2.347 0.007 1.491 0.566 2.383

Protein synthesis (3)

gi|15228111* 40S ribosomal protein S5 1.019 0.909 1.080 0.744 2.085 0.049 2.085

gi|7489746* Golgi associated protein se-wap41 0.229 0.462 3.535 0.015 3.535

gi|79322680 40S ribosomal protein S25 (RPS25E) 2.109 0.006 2.621 0.015 2.338

Protein folding, tansporting and Degradation (7)

gi|15234781* Peptidylprolyl isomerase ROC1 1.191 0.097 1.021 0.886 13.072 0.004 13.072

gi|15229559* Mitochondrial chaperonin hsp60 1.019 0.909 1.080 0.744 2.085 0.049 2.085

gi|15232760 Polyubiquitin (UBQ8) 3.297 0.001 3.373 0.001 1.449 0.010 2.326

gi|40060485 Heat shock protein HSP101 2.315 0.007 1.867 0.008 2.067

gi|15229559 Mitochondrial chaperonin hsp60 2.364 0.024 2.132 0.028 1.600 0.083 2.242

gi|15224993* 20S proteasome subunit (PAA2) 1.149 0.790 1.189 0.810 3.018 0.004 3.018

gi|5921735* 10 kDa chaperonin (Protein CPN10) 2.335 0.026 2.249 0.285 2.335

Membrane and transport (9)

gi|124360090 Plasma-membrane proton-efflux P-type ATPase 4.576 0.007 4.317 0.016 5.797 0.065 4.443

gi|1352830 Vacuolar ATP synthase catalytic subunit A 3.352 0.004 2.785 0.036 2.184 0.003 2.690

gi|15224264 Plasma membrane proton ATPase (PMA), AHA1 1.977 0.005 2.333 0.003 3.674 0.008 2.486

gi|15232300* Plasma membrane H+-ATPase, AHA7 7.210 0.083 6.631 0.035 2.181 6.631

gi|15234666 Plasma membrane H+-transporting ATPase type 2, AHA2 3.209 0.038 2.171 0.763 5.012 0.070 3.209

gi|18844793 Putative H+-exporting ATPase 2.316 0.010 2.546 0.003 2.580 0.067 2.426

gi|2493131 Vacuolar ATP synthase subunit B 1 1.932 3.050 0.004 1.905 0.005 2.345

gi|15231937 Adenylate translocator 2.163 0.000 2.150 0.002 1.766 0.246 2.157

gi|758355* H+-transporting ATPase 1.590 0.099 1.565 0.627 2.694 0.015 2.694

Stress and Defense (9)

gi|15222163* Putative GSH-dependent dehydroascorbate reductase 1 3.586 0.017 1.750 0.070 1.903 3.586

87

Table 2-1. Continued.

Accession Protein Experiment 1 Experiment 2 Experiment 3 Average

GC/MC P-value GC/MC P-value GC/MC P-value GC/MC

gi|15225245* Bet v I allergen family protein 3.134 0.064 2.572 0.031 2.572

gi|15231718 Putative peroxiredoxin type 2 5.085 0.010 4.522 0.006 9.075 0.148 4.787

gi|15239697 Resistant to agrobacterium transformation 5 2.372 0.015 4.025 0.032 4.783 0.003 3.412

gi|157849770 Early-responsive to dehydration 12 (ERD12 protein) 2.039 0.039 2.058 0.040 1.454 0.272 2.048

gi|18397457 Peroxiredoxin IIF (ATPRXIIF/PRXIIF) 2.038 0.000 1.999 0.002 1.935 2.018

gi|18404709 Unknown protein,containing pfam00407 domain 2.532 0.019 3.279 0.041 11.657 2.857

gi|21555213* Vegetative storage protein-like 2.030 0.023 1.019 0.911 4.052 2.030

gi|9795585* Putative GSH-dependent dehydroascorbate reductase 2.255 0.011 2.046 0.068 2.275 0.113 2.255

Signal transduction(8)

gi|15219510 14-3-3 protein, putative 2.428 0.006 1.995 0.014 2.099 0.051 2.190

gi|21553354 Glycine-rich RNA binding protein 7 2.161 0.002 2.280 0.004 1.766 0.158 2.219

gi|3702349 Putative mitogen-activated protein kinase 3.134 0.000 3.250 0.002 3.191

gi|78102508 Cytokinin-binding protein CBP57 2.791 0.034 3.798 0.031 1.770 3.217

gi|79317272 Calmodulin binding/translation elongation factor 3.253 0.013 3.799 0.001 1.459 0.044 2.389

gi|81248479* Mitogen-activated protein kinase 4 2.140 0.138 2.609 0.077 5.013 0.034 5.013

gi|899058 Calmodulin 2.340 0.002 3.475 0.002 2.025 0.000 2.482

gi|9958062* Putative protein phosphotase 2a 65kd regulatory subunit 2.063 0.045 2.075 0.155 2.063

Transcription related (4)

gi|145323776 Histone H4 1.988 0.000 2.621 0.000 4.369 0.014 2.695

gi|15224536 Histone H1 6.491 0.000 8.080 0.002 6.445 0.090 7.199

gi|15241858 Histone H2B, putative 1.877 0.001 2.299 0.000 5.443 0.000 2.605

gi|5777792* Histone H2A 2.282 0.223 2.173 0.182 4.860 0.001 4.860

Cell structure(3)

gi|34733239* Putative tubulin alpha-2/alpha-4 chain 1.650 0.184 1.639 0.397 2.697 0.034 2.697

gi|4139264* Actin 1.181 0.073 1.210 0.059 2.238 0.010 2.238

gi|77549556* Tubulin alpha-3 chain 3.413 0.016 3.413

Unknown (2)

gi|30681554 Unknown protein 1.696 0.000 1.855 0.000 2.994 0.048 2.051

gi|30690673* CP12 domain-containing protein 1 (CP12-1) 1.095 0.800 2.112 0.014 2.112

88

Table 2-2. Proteins predominantly expressed in mesophyll cells. 3

Accession Protein Experiment 1 Experiment 2 Experiment 3 Average

MC/GC P-value MC/GC P-value MC/GC P-value MC/GC

Photosynthesis (71)

gi|108796808 Photosystem I subunit VII 2.759 0.000 3.149 0.000 2.397 0.004 2.768

gi|109389998 Chloroplast chlorophyll a/b binding protein 3.072 0.000 4.745 0.000 8.345 0.000 5.387

gi|110377793 Chloroplast pigment-binding protein CP26 2.427 0.000 3.157 0.000 8.325 0.000 4.636

gi|121582119 Photosystem I P700 apoprotein A1 2.568 0.000 3.643 0.000 7.325 0.000 4.512

gi|125656346 Chloroplast PSI type III chlorophyll a/b-binding protein 3.966 0.000 3.969 0.000 6.431 0.006 4.789

gi|12805303 Putative chlorophyll A-B binding protein.. 3.877 0.000 5.377 0.000 4.627

gi|145688411 LhCa2 protein 3.576 0.000 4.421 0.000 8.994 0.000 5.664

gi|147864470 Hypothetical protein 2.848 0.001 3.886 0.002 3.367

gi|15219418 Photosystem II 22kDa protein, putative 2.464 0.000 3.370 0.000 5.037 0.000 3.624

gi|15221681 Putative photosystem I subunit III precursor 2.388 0.000 2.777 0.000 6.347 0.000 3.837

gi|15222551 Phosphoribulokinase precursor 2.382 0.000 2.562 0.000 2.958 0.000 2.634

gi|15222956 Plastocyanin 2.261 0.000 1.918 0.000 2.504 0.025 2.228

gi|15223331 Starch synthase, putative 2.894 0.000 5.181 0.000 7.577 0.000 5.217

gi|15225630 LHCB4.3 (light harvesting complex PSII) 2.896 0.000 3.081 0.000 3.356 0.025 3.111

gi|15230324 Photosystem II subunit O-2 (PSBO-2/PSBO2) 3.155 0.000 3.520 0.000 4.605 0.005 3.760

gi|15232815 Chlorophyll A-B biding protein 4 percursor homolog 2.989 0.000 3.937 0.000 7.748 0.000 4.891

gi|15234637 Photosystem II subunit Q-2; calcium ion binding 2.198 0.000 2.053 0.000 5.744 0.016 3.332

gi|15235490 Putative photosystem I chain XI precursor 2.316 0.000 3.125 0.000 6.426 0.006 3.956

gi|15235503 Putative photosystem I reaction center subunit II 3.541 0.000 3.855 0.000 3.259 0.000 3.552

gi|15236722 H+-transporting ATP synthase chain 9 - like protein 2.222 0.000 1.949 0.000 5.552 0.005 3.241

gi|15237225 Photosystem II stability/assembly factor HCF136 1.688 0.000 1.532 0.001 3.280 0.032 2.167

gi|15240013 33 kDa polypeptide of oxygen-evolving complex 4.216 0.000 4.515 0.000 8.552 0.001 5.761

gi|15241005 Chlorophyll A-B binding protein CP29 (LHCB4) 2.668 0.000 3.712 0.000 7.691 0.000 4.690

gi|1644289 Chlorophyll a/b-binding protein CP26 in PS II 3.098 0.000 4.077 0.000 3.554 0.000 3.576

gi|17852 Rubisco small subunit 2.018 0.001 2.742 0.000 3.667 0.000 2.809

gi|18405061 Thylakoid lumen 18.3 kDa protein 1.961 0.000 2.821 0.000 4.095 0.000 2.959

3 Proteins with p value smaller than 0.05 in only one of the independent replicates are highlighted with asterisk.

89

Table 2-2. Continued.

Accession Protein Experiment 1 Experiment 2 Experiment 3 Average

MC/GC P-value MC/GC P-value MC/GC P-value MC/GC

gi|21554335 PSI type III chlorophyll a/b-binding protein, putative 3.194 0.000 3.684 0.000 5.179 0.002 4.019

gi|28141361 Granule bound starch synthase 1.469 0.007 3.509 0.001 8.831 0.020 4.603

gi|29470191 Photosystem II protein D1 2.009 0.000 2.897 0.000 6.049 0.000 3.651

gi|3914442 Photosystem I reaction center subunit VI, PSI-H 2.514 0.032 2.847 0.011 2.170 2.681

gi|401249 Cytochrome b6-f complex iron-sulfur subunit 2 4.364 0.000 2.852 0.000 4.349 0.002 3.855

gi|407769 PSI-D1 precursor 3.536 0.001 3.996 0.012 9.398 0.043 5.644

gi|42571761 Nonphotochemical quenching (NPQ4) 1.916 0.000 2.760 0.000 4.849 0.002 3.175

gi|49359169 Photosystem II protein 3.717 0.000 4.621 0.001 6.645 0.003 4.994

gi|50313237 Lhcb6 protein 2.760 0.000 3.545 0.000 7.888 0.043 4.731

gi|515616 LHC II Type III chlorophyll a /b binding protein 2.591 0.000 3.611 0.000 3.215 0.058 3.101

gi|56784285 Chloroplast photosystem I P700 apoprotein A2 1.977 0.010 3.737 0.198 7.440 0.034 4.709

gi|58700507 Chloroplast oxygen-evolving protein 16 KDa subunit 2.135 0.000 2.103 0.000 4.720 0.008 2.986

gi|6006283 Photosystem I subunit PSI-L 2.856 0.001 3.849 0.001 3.353

gi|62318781 Protochlorophyllide reductase precursor like protein 2.633 0.026 2.716 0.019 2.675

gi|75107089 Photosystem I reaction center subunit N (PSI-N) 1.741 0.012 2.528 0.009 2.135

gi|7525059 photosystem II 47 kDa protein 1.777 0.000 2.711 0.000 6.051 0.005 3.513

gi|79013990 Chloroplast Rubisco small subunit precursor 1.738 0.000 2.227 0.000 4.068 0.000 2.678

gi|81176267 Photosystem II protein V 1.889 0.001 2.299 0.001 4.801 0.118 2.094

gi|83641952 PSII cytochrome b559 8kDa subunit 2.381 0.056 3.952 0.001 3.971 0.003 3.962

gi|8745521 Ribulose-1,5-bisphosphate carboxylase/oxygenase 2.008 0.000 2.079 0.000 3.706 0.000 2.598

gi|902201 PSII 32 KDa protein 3.543 0.001 6.049 0.000 4.796

gi|902207 PSII 43 KDa protein 6.378 0.000 6.886 0.000 7.120 0.000 6.795

gi|91983987 Photosystem II protein D2 2.271 0.000 3.056 0.000 5.407 0.001 3.578

gi|91983988 Photosystem II 44 KDa protein 1.900 0.000 2.476 0.000 8.091 0.000 4.155

gi|92884121 4Fe-4S ferredoxin, iron-sulfur binding 2.147 0.098 2.158 0.035 6.393 0.000 4.275

gi|9843639 Rieske FeS protein 2.690 0.000 3.375 0.000 3.033

gi|967968 Photosystem II 10kDa polypeptide 2.206 0.018 1.942 0.145 6.386 0.009 4.296

gi|110377772 Chloroplast pigment-binding protein CP24 3.143 0.000 4.320 0.000 7.529 0.004 4.997

gi|116309995 Chlorophyll A-B binding protein, containing pfam00504 3.495 0.024 4.319 0.007 3.689 0.077 3.907

90

Table 2-2. Continued.

Accession Protein Experiment 1 Experiment 2 Experiment 3 Average

MC/GC P-value MC/GC P-value MC/GC P-value MC/GC

gi|126633416 Unnamed protein product, containing pfam00504 2.981 0.000 4.176 0.000 5.965 0.001 4.374

gi|15222757* putative photosystem I subunit V precursor 5.941 0.011 5.941

gi|15231990 Light harvesting complex PSII (LHCB4.2) 4.652 0.000 6.258 0.000 8.524 0.001 6.478

gi|15233115 LHCA1; chlorophyll binding 3.008 0.000 3.606 0.000 4.962 0.000 3.859

gi|15237593 Photosystem I reaction center subunit PSI-N 2.102 0.000 1.987 0.000 4.536 0.000 2.875

gi|1620920 23kD protein of oxygen evolving system 1.717 0.000 1.850 0.000 3.043 0.005 2.203

gi|24210533 Chlorophyllase 1 2.121 0.022 3.635 0.002 2.878

gi|29839389 Ferritin-1, chloroplast precursor 1.557 0.018 3.280 0.001 3.540 0.185 2.418

gi|34393511 Putative photosystem I antenna protein 3.388 0.000 4.382 0.000 9.827 0.000 5.865

gi|3885892 Photosystem-1 F subunit precursor 2.056 0.001 2.550 0.002 3.757 0.009 2.788

gi|458797* Cytochrome b 1.264 2.175 3.970 0.012 3.970

gi|54043095 Glycolate oxidase 1.990 0.002 1.784 0.018 6.224 0.000 3.333

gi|544122 Apocytochrome f precursor 2.174 0.000 2.641 0.000 6.393 0.000 3.736

gi|67463833* Plastocyanin with cytochrome f 7.934 0.000 7.934

gi|81301580* Cytochrome f 1.265 0.845 1.372 0.773 4.468 0.005 4.468

gi|15229349 Putative ribose 5-phosphate isomerase 2.198 0.000 2.381 0.002 4.961 0.016 3.180

Energy (7)

gi|1480014 Putative delta subunit of ATP synthase 3.540 0.000 2.721 0.000 4.664 0.000 3.641

gi|15234900 Putative fructose-bisphosphate aldolase 1.811 0.000 1.619 0.000 4.383 0.000 2.604

gi|20339362 Ribulose-5-phosphate-3-epimerase 1.743 0.009 2.295 0.011 2.899 0.018 2.312

gi|27530932 Cytosolic NADP-malic enzyme 2.388 0.024 2.327 0.005 2.357

gi|15233597 Unknown protein containing F0F1-ATP synthase gamma domain

1.957 0.000 2.091 0.000 5.336 0.000 3.128

gi|4995091 Malate dehydrogenase 2 2.392 0.001 2.322 0.008 4.982 0.051 2.357

gi|75336517 ATP synthase subunit beta 1.772 0.000 1.775 0.000 3.254 0.000 2.267

Metabolism (23)

gi|114324489 Geranylgeranyl reductase 2.582 0.000 1.613 0.005 1.835 2.097

gi|15217485 Unknown protein containing UDP-galactose-4-epimerase domain

2.619 0.000 2.426 0.000 2.523

gi|15221892 Protein containing methanol dehydrogenase domain 2.103 0.000 2.989 0.000 4.391 0.000 3.161

91

Table 2-2. Continued.

Accession Protein Experiment 1 Experiment 2 Experiment 3 Average

MC/GC P-value MC/GC P-value MC/GC P-value MC/GC

gi|15225026 Alanine-glyoxylate aminotransferase 2.071 0.000 2.099 0.000 3.575 0.021 2.582

gi|15232133 Carbonic anhydrase, chloroplast precursor 2.907 0.000 3.599 0.001 7.765 0.001 4.757

gi|1711296 Myrosinase binding protein 2.916 0.000 4.833 0.000 6.517 0.000 4.755

gi|1769968 Myrosinase-associated protein 2.110 0.003 3.561 0.000 4.843 0.027 3.505

gi|18410661 Unknown protein 3.384 0.035 2.543 0.008 2.963

gi|28192642 Cysteine lyase BOCL-3 1.737 0.013 2.714 0.005 3.658 0.027 2.703

gi|42408130 Putative aminotransferase 2.063 0.007 2.003 0.001 2.793 0.025 2.286

gi|50508805 Putative (S)-2-hydroxy-acid oxidase 2.087 0.000 2.299 0.000 4.892 0.020 3.093

gi|79313265 Jacalin lectin family protein (JR1) 4.524 0.014 4.677 0.007 4.600

gi|15220620 Hydroxypyruvate reductase 1.813 0.027 1.482 0.161 3.574 0.033 2.693

gi|15221119 Aminomethyltransferase-like precursor protein 1.707 0.002 1.819 0.003 4.426 0.021 2.650

gi|15225449 Putative transketolase precursor 2.424 0.013 2.195 0.327 2.369 0.044 2.396

gi|15239032* Allene oxide synthase 3.500 0.054 4.163 0.049 4.163

gi|15239406 P-nitrophenylphosphatase-like protein 2.126 0.001 2.017 0.004 2.634 0.006 2.259

gi|157849706 Catalytic/coenzyme binding protein 1.746 0.067 2.301 0.043 2.301

gi|1617272* AMP-binding protein 1.502 0.091 2.404 0.017 2.404

gi|296223 Glutamate--ammonia ligase precursor 2.353 0.000 2.249 0.000 5.250 0.002 3.284

gi|30692947 Putative phosphoglycolate phosphatase 1.956 0.000 1.826 0.005 2.569 0.006 2.117

gi|5281016* Hydroperoxide lyase (HPOL) like protein, containing

pfam00067 Cytochrome P450 domain 2.933 0.215 7.273 0.011 7.273

gi|6966930* Glutamine synthetase 1.173 0.395 1.301 0.317 5.327 0.000 5.327

Protein synthesis (2)

gi|15232276* 50S ribosomal protein L12-C 2.399 0.002 0.958 0.764 0.982 0.962 2.399

gi|30692346* RPS1 (ribosomal protein S1); RNA binding 2.148 0.040 1.323 0.326 0.975 2.148

Protein folding, transporting and Degradation(11)

gi|15241314 ATP-dependent Clp protease, ATP-binding subunit 2.283 0.014 2.597 0.002 2.167 0.148 2.440

gi|167117 60-kDa beta-polypeptide of plastid chaperonin-60 precursor

2.155 0.013 2.945 0.013 1.693 0.059 2.550

gi|18399551 Complex 1 family protein / LVR family protein 1.412 0.038 2.675 0.014 2.044

gi|42565672 Plastid transcriptionally active 18 (PTAC16 ) 1.924 0.000 2.218 0.001 2.071

92

Table 2-2. Continued.

Accession Protein Experiment 1 Experiment 2 Experiment 3 Average

MC/GC P-value MC/GC P-value MC/GC P-value MC/GC

gi|75321947 DEAD-box ATP-dependent RNA helicase 35B 6.686 0.001 12.884 0.000 12.754 0.007 10.775

gi|15225545 Hypothetical protein, containing COG1222 ATP-

dependent 26S proteasome regulatory subunit domain 2.303 0.000 1.600 0.000 3.433 0.000 2.446

gi|15238369* Ribosomal protein L29 family protein 2.135 0.019 1.127 0.216 2.135

gi|2565436 DEGP protease precursor 1.481 0.007 2.053 0.003 4.659 0.040 2.731

gi|30684767* ATP-dependent peptidase/ATPase/ metallopeptidase 1.597 0.170 1.592 0.186 5.722 0.031 5.722

gi|77554415 Stromal 70 kDa heat shock-related protein, chloroplast 2.745 0.008 3.427 0.001 3.086

gi|841208 Trypsin inhibitor propeptide 1.907 0.005 2.707 0.016 4.022 0.024 2.879

Membrane and transport (5)

gi|124360831 H+-transporting two-sector ATPase, alpha/beta subunit 1.693 0.000 1.587 0.001 5.066 0.004 2.782

gi|15224625 Translocon at the inner envelope membrane of chloroplast 55

2.460 0.004 1.934 0.005 2.197

gi|15228268* Apolipoprotein D-related 2.077 0.082 2.246 0.013 1.529 2.246

gi|2199574* Aquaporin PIP1b2 2.809 0.086 3.693 0.000 3.693

gi|5081423 Plasma membrane intrinsic protein 2 3.546 0.030 5.095 0.013 7.000 0.013 5.214

Stress and Defence (17)

gi|15227359

Unknown protein containing cd01958 and pfam00234

domain, putative seed storage proteins and lipid

transfer proteins

7.321 0.000 6.978 0.002 11.961 0.008 8.754

gi|1755154 Germin-like protein 3.626 0.000 4.533 0.000 8.589 0.000 5.583

gi|17813 BnD22 drought induced protein 2.490 0.000 2.913 0.000 9.806 0.000 5.070

gi|27372775 Lipoxygenase 2 2.180 0.001 3.319 0.000 9.880 0.000 5.126

gi|336422 Triazine-resistance 2.444 0.000 3.408 0.000 5.522 0.000 3.791

gi|5487875 Catalase 2.816 0.000 3.485 0.000 5.072 0.000 3.791

gi|15229440 Unknown protein, containingg pfam04755 PAP-fibrillin domain

2.011 0.000 3.419 0.000 4.592 0.005 3.341

gi|158523427 Myrosinase 3.835 0.002 4.232 0.001 4.544 0.022 4.204

gi|18405273* Kelch repeat-containing protein 4.795 9.490 13.694 0.032 13.694

gi|18423233 Early responsive to dehydration 1 2.670 0.003 1.837 0.008 2.253

gi|1883008* Jasmonate inducible protein containing pfam01419

Jacalin-like lectin domain 1.390 1.902 7.666 0.000 7.666

93

Table 2-2. Continued.

Accession Protein Experiment 1 Experiment 2 Experiment 2 Average

MC/GC P-value MC/GC P-value MC/GC P-value MC/GC

gi|21554102 Putative chloroplast drought-induced stress protein 2.094 0.001 2.036 0.006 2.494 2.065

gi|30688146 Plastid-lipid associated protein PAP 2.093 0.000 2.967 0.000 3.739 2.530

gi|33285912* Putative myrosinase-binding protein 3 2.068 0.079 4.370 0.040 3.839 4.370

gi|62900701 Plastid lipid-associated protein 1, chloroplast precursor 1.638 0.000 2.574 0.000 2.811 2.106

gi|6522943 Myrosinase-associated protein 1.956 0.033 4.132 0.016 3.044

gi|66734182 Epithiospecifier protein 2.099 0.001 2.909 0.001 8.182 0.002 4.397

Signal transduction (2)

gi|15220216 Ca2+

-dependent membrane-binding protein annexin 1.447 0.029 2.911 0.018 5.720 0.085 2.179

gi|89513072* Annexin 1 3.404 0.003 3.404

Transcription (1)

gi|15229384 Putative mRNA-binding protein 1.861 0.006 1.447 0.228 3.902 0.023 2.882

unknown (2)

gi|15232724 Unknown protein 2.832 0.001 2.670 0.015 2.751

gi|18394322* Unknown protein 2.073 0.030 2.258 0.365 2.073

Miscellaneous (2)

gi|15237201 Unknown protein, containing RHOD domain 2.037 0.007 2.271 0.015 3.465 2.154

gi|18418200* Rubredoxin family protein 2.141 0.047 2.783 0.089 1.976 0.474 2.141

94

Table 2-3. List of proteins significantly up-regulated in guard cells by ABA.

Accession Name 117:113 P Val

117:113 118:114

P Val 118:114

119:115 P Val

119:115 121:116

P Val 121:116

Average

Photosynthesis (14)

gi|15231990 Light harvesting complex PSII (LHCB4.2) 2.23 0.02 2.13 0.40 3.30 0.02 2.06 0.10 2.77

gi|81301629 Photosystem I subunit VII 1.70 0.00 1.72 0.00 4.21 0.00 1.74 0.00 2.34

gi|8918361 Rubisco activase small isoform precursor 1.61 0.00 1.66 0.01 3.91 0.00 1.59 0.01 2.19

gi|18402859 Photosystem II subunit 1.26 0.16 1.26 0.25 1.91 0.00 1.29 0.04 1.60

gi|15232249 Putative chlorophyll A-B binding protein 1.64 0.00 1.99 0.00 1.91 0.00 1.68 0.00 1.80

gi|18266039 Chlorophyll a/b binding protein 1.53 0.00 1.81 0.00 2.18 0.00 1.58 0.00 1.77

gi|49359169 Photosystem II protein 1.52 0.00 1.83 0.00 1.20 0.32 1.40 0.00 1.58

gi|15230324 Photosystem II subunit O-2 1.75 0.01 1.67 0.00 1.52 0.07 1.45 0.00 1.62

gi|15224572 Photosystem II subunit P-2 1.72 0.00 1.52 0.03 1.77 0.03 1.41 0.03 1.61

gi|153012221 Photosystem I P700 apoprotein A1 1.59 0.00 1.06 0.84 1.98 0.01 1.35 0.05 1.64

gi|515616 LHC II Type III chlorophyll a /b binding protein

1.58 0.00 1.42 0.06 1.18 0.13 1.43 0.00 1.50

gi|29839389 Ferritin-1, chloroplast precursor 1.53 0.02 1.54 0.14 1.71 0.13 1.68 0.01 1.60

gi|126633416 Unnamed protein product, containing pfam00504 chlorophyll A-B binding protein domain

1.82 0.01 2.31 0.01 2.80 0.03 1.67 0.04 2.15

gi|15234637 Photosystem II subunit Q-2 1.26 0.01 1.62 0.02 1.83 0.00 1.36 0.02 1.52

Energy (7)

gi|7431171 Cytosolic malate dehydrogenase 2.03 0.01 3.10 0.00 2.13 0.01 2.35 0.01 2.40

gi|153012206 ATP synthase CF1 alpha subunit 1.61 0.00 1.64 0.00 2.37 0.00 1.62 0.00 1.81

gi|30684540 DNA-directed DNA polymerase 1.12 0.16 1.70 0.01 1.77 0.00 1.14 0.12 1.74

gi|4218951 Fructose-1,6-bisphosphatase precursor 0.96 0.70 1.58 0.00 1.75 0.00 1.02 0.68 1.67

gi|90194338 LOS, containing cd03313 enolase domain 2.01 0.00 2.30 0.00 2.00 0.07 1.35 0.21 2.15

gi|30684197 Putative glycosyl hydrolase of unknown function

1.09 0.20 0.93 0.66 2.10 0.00 1.79 0.03 1.95

gi|15235720 Cytochrome c oxidase-related 1.06 0.09 1.88 0.00 1.06 0.48 0.99 0.90 1.88

Metabolism (10)

gi|15229530 Putative glutamine synthetase 1.40 0.00 1.83 0.00 2.19 0.00 1.22 0.01 1.66

gi|51091903 Sterol carrier protein 2-like 1.43 0.01 1.74 0.24 1.81 0.00 1.32 0.01 1.52

95

Table 2-3. Continued.

Accession Name 117:113 P Val

117:113 118:114

P Val 118:114

119:115 P Val

119:115 121:116

P Val 121:116

Average

gi|79327530 Asparagine synthase 3 1.00 0.98 1.59 0.00 1.44 0.01 1.10 0.12 1.51

gi|15230338 Aspartate/glutamate/uridylate kinase family protein

1.43 0.03 1.84 0.00 1.82 0.00 1.50 0.02 1.65

gi|79328724 Uridylate kinase 1.04 0.64 1.68 0.00 1.53 0.04 1.17 0.11 1.60

gi|121550795 Nitrilase 1 1.78 0.02 1.87 0.06 3.90 0.02 1.57 0.10 2.84

gi|42566190 Phospholipid/glycerol acyltransferase family protein

1.23 0.12 1.80 0.02 2.33 0.02 1.17 0.37 2.07

gi|14388188 Biotin carboxylase 1.37 0.03 1.22 0.13 2.04 0.01 1.30 0.03 1.57

gi|15229529 Dihydroorotate dehydrogenase/oxidase family protein

1.14 0.14 1.47 0.22 1.54 0.03 1.19 0.09 1.54

gi|1777375 Aspartate kinase-homoserine dehydrogenase

1.10 0.56 0.71 0.49 1.53 0.01 0.86 0.22 1.53

Transcription (5)

gi|18410283 SC35-like splicing factor 30 1.14 0.07 1.29 0.25 1.89 0.04 1.29 0.07 1.89

gi|147224051 Unnamed protein product,containing cd01732 LSm5 domain

1.64 0.03 1.04 0.80 3.77 0.02 1.40 0.04 2.27

gi|124360159 Histone H2A; Histone-fold 1.23 0.16 3.07 0.01 2.22 0.00 1.94 0.01 2.41

gi|15226943 Putative histone H2B 1.47 0.04 1.68 0.03 2.26 0.03 1.50 0.13 1.80

gi|15223948 HTA5; DNA binding 1.16 0.43 1.48 0.04 1.86 0.00 1.35 0.14 1.67

Protein synthesis (3)

gi|15234970 40S ribosomal protein S25 1.41 0.00 1.47 0.04 1.88 0.00 1.43 0.00 1.55

gi|15229706 60S acidic ribosomal protein 1.27 0.00 2.14 0.00 1.56 0.00 1.41 0.00 1.60

gi|72384424 4D11_26,containing histone H3 domain and ribosomal protein S6e domain

1.47 0.01 2.22 0.03 2.54 0.00 1.53 0.00 1.94

Signaling (1)

gi|15232210 Rab GDP-dissociation inhibitor 1.11 0.35 1.55 0.01 1.58 0.00 1.13 0.11 1.56

Membrane and transport (3)

gi|15232110 Vacuolar membrane ATPase subunit G 1.32 0.19 1.66 0.00 3.15 0.00 1.37 0.00 2.06

gi|15225796 Synaptobrevin-related protein 1 1.32 0.07 2.06 0.00 1.61 0.01 1.55 0.00 1.74

gi|157849742 Altered response to gravity 1 1.66 0.06 2.06 0.02 2.69 0.01 1.66 0.04 2.14

96

Table 2-3. Continued.

Accession Name 117:113 P Val

117:113 118:114

P Val 118:114

119:115 P Val

119:115 121:116

P Val 121:116

Average

Protein folding and degradation (4)

gi|15226467 Cyclophilin 2.23 0.00 2.06 0.01 8.25 0.00 2.08 0.00 3.66

gi|22331378 DEGP protease 1 1.39 0.00 1.69 0.00 1.96 0.00 1.35 0.00 1.60

gi|18391078 Xylem bark cysteine peptidase 3 1.26 0.46 1.86 0.09 1.65 0.02 1.46 0.14 1.65

gi|18416749 COP9 signalosome subunit 6B 1.22 0.10 1.53 0.00 1.70 0.01 1.20 0.20 1.61

Stress and defense (14)

gi|157849658 Stress-induced protein KIN2 1.17 0.22 1.35 0.02 1.92 0.02 1.15 0.05 1.64

gi|18418200 Enhancer of SOS3-1 (ENH1) 1.45 0.00 1.55 0.04 1.68 0.00 1.37 0.06 1.56

gi|130845790 Lipoxygenases (LOX) 1.21 0.52 1.85 0.05 1.37 0.27 1.40 0.01 1.63

gi|40388501 Glutathione peroxidase (GPX) 1.01 0.86 1.62 0.04 0.86 0.36 0.96 0.65 1.62

gi|119655911 Thiol methyltransferase 1.33 0.03 1.68 0.00 1.97 0.00 1.29 0.06 1.66

gi|2204102 Glutathione-S-transferase 8 (GST8) 1.24 0.00 1.96 0.01 2.27 0.00 1.19 0.04 1.67

gi|1890354 L-ascorbate peroxidase (APX) 0.94 0.72 1.61 0.00 0.80 0.37 1.06 0.74 1.61

gi|45593261 Putative protein disulphide isomerase 1.56 0.01 1.71 0.04 3.09 0.00 1.49 0.00 1.96

gi|18418013 Glutamine synthetase 1;4 1.43 0.01 1.65 0.00 0.93 0.70 1.20 0.16 1.54

gi|146150661 Resistance-gene-interacting protein RIN4 1.18 0.13 1.45 0.05 1.96 0.00 1.20 0.11 1.70

gi|15234243 Phospholipid hydroperoxide glutathione peroxidase

1.47 0.07 1.97 0.02 2.08 0.03 1.69 0.05 1.91

gi|15225245 Bet v I allergen family protein 1.04 0.59 1.45 0.01 1.56 0.00 1.07 0.36 1.51

gi|15239559 Myrosinase TGG2 1.72 0.04 1.19 0.26 1.29 0.01 1.14 0.54 1.50

gi|1769968 Myrosinase-associated protein 1.63 0.02 1.57 0.03 1.50 0.03 1.36 0.04 1.52

Cell structure (1)

gi|15241179 Tubulin alpha-5 1.00 0.93 2.06 0.00 1.40 0.01 0.99 0.70 1.73

Cell division and fate (1)

gi|15238333 Cell division protein FtsH 1.06 0.53 1.57 0.00 1.46 0.00 1.10 0.17 1.51

Unknown (3)

gi|15222996 Unknown protein 1.17 0.28 1.13 0.39 1.84 0.01 1.26 0.03 1.55

gi|18405887 Unknown protein 1.20 0.01 1.44 0.28 2.55 0.01 1.18 0.13 1.87

gi|30681554 Unknown protein 1.10 0.10 1.73 0.00 0.91 0.43 1.10 0.10 1.73

97

Table 2-4. List of proteins significantly down-regulated in guard cells by ABA.

Accession Name 117:113 P Val

117:113 118:114

P Val 118:114

119:115 P Val

119:115 121:116

P Val 121:116

Average

Photosynthesis (2)

gi|406727 Rubisco small subunit 0.86 0.09 0.64 0.03 0.52 0.00 0.63 0.00 0.60

gi|552959 Rubisco large subunit 0.91 0.18 0.52 0.02 0.42 0.01 0.66 0.18 0.47

Energy (6)

gi|15219721 Putative malate dehydrogenase 0.99 0.60 1.03 0.40 0.66 0.00 0.98 0.24 0.66

gi|15222848 Glyceraldehyde-3-phosphate dehydrogenase 0.75 0.04 0.44 0.00 0.32 0.00 0.55 0.01 0.51

gi|15230749 Galactose kinase 0.86 0.22 0.95 0.62 0.49 0.04 0.75 0.22 0.49

gi|15219379 Succinic semialdehyde dehydrogenase 0.95 0.10 0.63 0.01 0.63 0.00 0.87 0.28 0.63

gi|1096966 ORF B, containing plant ATP synthase F0 domain

0.91 0.28 0.53 0.00 0.67 0.00 0.74 0.02 0.64

gi|125524180 Hypothetical protein,containing fructose-1,6-bisphosphate aldolase domain

0.84 0.09 0.66 0.00 0.60 0.02 0.87 0.23 0.63

Metabolism (8)

gi|15231926 Rhamnose biosynthesis 3 1.00 0.97 0.51 0.00 0.68 0.01 0.80 0.04 0.66

gi|15220885 Spermidine synthase 1 0.80 0.19 0.67 0.02 0.74 0.26 0.64 0.03 0.65

gi|15225045 12-oxophytodienoate-10,11-reductase 0.93 0.24 0.54 0.00 0.70 0.01 0.84 0.42 0.62

gi|15220946 Acyl-CoA oxidase 3 0.89 0.28 0.69 0.05 0.54 0.01 1.01 0.95 0.62

gi|145337526 Phosphoribosylformylglycinamidine synthase 0.60 0.01 1.08 0.53 1.31 0.65 0.64 0.02 0.62

gi|18390900 Strictosidine synthase family protein 1.02 0.92 0.75 0.00 0.57 0.01 0.84 0.06 0.66

gi|15240774 Tudor domain-containing protein 0.67 0.01 0.99 0.88 0.61 0.01 0.91 0.45 0.64

gi|15228345 Diadenosine 5',5'''-P1,P4-tetraphosphate hydrolase

1.03 0.88 1.00 0.97 0.58 0.05 0.93 0.20 0.58

Transcription (2)

gi|15232536 HTA11 0.83 0.06 0.62 0.00 0.70 0.01 0.70 0.15 0.66

gi|18401305 Argonaute 4 (AGO4) 0.78 0.09 0.73 0.02 0.53 0.01 0.82 0.11 0.63

Protein synthesis (7)

gi|20140684 Translationally-controlled tumor protein homolog

0.66 0.00 0.91 0.44 0.45 0.03 0.73 0.01 0.62

gi|23928437 Putative 40S ribosomal protein 1.01 0.95 0.46 0.02 0.70 0.18 0.74 0.05 0.60

gi|15226755 60S ribosomal protein L18A 0.88 0.15 0.53 0.00 0.67 0.01 0.90 0.42 0.60

98

Table 2-4. Continued.

Accession Name 117:113 P Val

117:113 118:114

P Val 118:114

119:115 P Val

119:115 121:116

P Val 121:116

Average

gi|15218274 U2 small nuclear ribonucleoprotein A 0.88 0.42 0.61 0.01 0.66 0.02 0.93 0.53 0.64

gi|118197456 Putative elongation factor 1-beta 1.04 0.82 0.50 0.04 0.97 0.91 0.88 0.61 0.50

gi|15223829 ATP binding / aminoacyl-tRNA ligase 0.92 0.10 0.65 0.00 0.76 0.12 0.99 0.88 0.65

gi|15241519 Small nuclear ribonucleoprotein associated protein

0.80 0.10 0.65 0.02 0.74 0.32 0.90 0.18 0.65

Protein folding and degradation (4)

gi|15240578 Heat shock protein 70-7 (cpHSC70-2) 0.59 0.00 0.69 0.01 0.35 0.00 0.55 0.01 0.55

gi|15233268 20S proteasome subunit C1 (PAC1) 1.02 0.91 1.34 0.63 0.51 0.04 0.90 0.77 0.51

gi|78059506 26S proteasome subunit alpha 4 (PAD1) 0.90 0.79 0.68 0.02 0.64 0.41 0.56 0.04 0.62

gi|15222913 Putative chloroplast FtsH protease 0.79 0.15 0.66 0.04 0.82 0.13 0.79 0.46 0.66

Signaling (1)

gi|44917165 14-3-3 i-2 protein 1.54 0.09 0.23 0.00 0.74 0.01 0.79 0.21 0.48

Membrane and transport (4)

gi|15235964 Putative coatomer beta subunit 0.76 0.14 0.60 0.00 0.66 0.10 0.73 0.01 0.66

gi|15229430 Chloroplast inner membrane methyltransferase

0.93 0.44 0.61 0.00 0.59 0.01 0.75 0.02 0.65

gi|55274626 Plasma membrane proton ATPase 5 0.76 0.29 0.58 0.05 0.61 0.02 0.71 0.07 0.60

gi|15220216 Ca

2+-dependent membrane-binding

protein annexin 0.99 0.96 0.49 0.05 0.88 0.68 1.00 0.99 0.49

Stress and defense (3)

gi|15231718 Peroxiredoxin type 2 0.67 0.01 0.66 0.03 0.69 0.36 0.63 0.02 0.65

gi|15227119 Glutathione S-transferase 6 1.02 0.95 0.86 0.57 0.57 0.03 0.96 0.79 0.57

gi|3062793 Thioredoxin 0.78 0.06 0.58 0.01 0.43 0.02 0.71 0.02 0.57

Unknown (1)

gi|15224568 Unknown protein 1.07 0.64 0.63 0.02 0.70 0.05 0.92 0.20 0.67

99

Table 2-5. Sequence enriched in upstream regions of the genes encoding proteins with more than 1.5-fold change in response to ABA.

(A) PLACE analysis

Group ACGT ACGTG ACGTGKC YACGTGGC CCACGTGG

Up- 66IDs 52/66(78.8%) 30/52(57.7%) 0/52(0.0%) 2/52(3.8%) 3/52(5.8%) Down- 38IDs 24/38(63.2%) 10/24(41.7%) 1/24(4.2%) 3/24(12.5%) 0/24(0.0%)

All 76/104(73.1%) 40/76(52.6%) 1/76(1.3%) 5/76(6.6%) 3/76(3.9%)

(B) Motif analysis of up-regulated group (66 IDs)

Sequence Absolute number in the selected genes

Observed in selected genes

Absolute number in genomic set

Observed in genomic set

P value

ACGTGG 36 24/66(36.4%) 5420 4361/33282 1.12e-06 CCACGT 36 24/66(36.4%) 5420 4361/33282 1.12e-06 CACGTG 46 18/66(27.3%) 7678 3212/33282 2.77e-05 ACACGT 36 24/66(36.4%) 7331 5565/33282 6.55e-05 ACGTGT 36 24/66(36.4%) 7331 5565/33282 6.55e-05

(C) Motif analysis of down-regulated group (38 IDs)

Sequence Absolute number in the selected genes

Observed in selected genes

Absolute number in genomic set

Observed in genomic set

P value

ACGTAG 8 8/38(21.1%) 3121 2850/33282 9.64e-03 CTACGT 8 8/38(21.1%) 3121 2850/33282 9.64e-03 ACGTAC 9 8/38(21.1%) 3740 2855/33282 9.73e-03 GTACGT 9 8/38(21.1%) 3740 2855/33282 9.73e-03 CACGTA 10 9/38(23.7%) 4165 3781/33282 1.56e-02 TACGTG 10 9/38(23.7%) 4165 3781/33282 1.56e-02

(D) Motif analysis of total ABA-responsive group (104 IDs)

Sequence Absolute number in the selected genes

Observed in selected genes

Absolute number in genomic set

Observed in genomic set

P value

ACGTGG 44 30/104(28.8%) 5420 4361/33282 1.19e-05 CCACGT 44 30/104(28.8%) 5420 4361/33282 1.19e-05 CACGTG 54 22/104(21.2%) 7678 3212/33282 2.14e-04 ACACGT 48 31/104(29.8%) 7331 5565/33282 3.69e-04 ACGTGT 48 31/104(29.8%) 7331 5565/33282 3.69e-04

100

Table 2-6. List of proteins significantly up-regulated in guard cells by MeJA.

Accession Name 117:113 P Val

117:113 118:114

P Val 118:114

119:115 P Val

119:115 121:116

P Val 121:116

Average

Photosynthesis (8)

gi|15232249 Putative chlorophyll A-B binding protein 2.3

2.88 0.03 3.19 0.03 2.07 0.08 8.09 0.01 4.72

gi|18266039 Chlorophyll a/b binding protein 3.94 0.01 6.37 0.01 3.63 0.01 3.31 0.03 4.31

gi|405617 LHCII Type III chlorophyll a/b binding protein

3.63 0.01 2.94 0.02 4.53 0.04 3.84 0.19 3.70

gi|7267731 Chlorophyll a/b-binding protein-like 3.22 0.03 2.86 0.05 1.87 0.08 3.70 0.18 3.04

gi|15222551 Phosphoribulokinase precursor 1.42 0.21 0.95 0.87 2.15 0.03 0.81 0.65 2.15

gi|79013990 Chloroplast Rubisco small subunit precursor

2.03 0.03 1.17 0.53 1.34 0.52 0.97 0.88 2.03

gi|262400776 Photosystem I subunit VII 0.95 0.50 1.00 0.75 1.00 0.87 2.00 0.03 2.00

gi|75250014 Photosystem II subunit S 2.27 0.01 2.25 0.02 2.40 0.02 2.75 0.02 2.42

Energy (14)

gi|75325224 Cytochrome c oxidase subunit 2 0.93 0.81 0.95 0.90 0.95 0.92 2.27 0.03 2.27

gi|75311627 NADP-dependent malate dehydrogenase

1.84 0.01 1.71 0.01 1.72 0.01 1.15 0.07 1.75

gi|743641 Phosphoenolpyruvate carboxylase 2.47 0.01 1.28 0.22 1.58 0.04 0.69 0.19 2.03

gi|12643432 V-type proton ATPase subunit E1 2.05 0.01 1.87 0.02 1.94 0.01 1.50 0.13 1.95

gi|12644156 ATPase 1, plasma membrane-type 1.87 0.00 1.07 0.64 1.38 0.03 1.53 0.01 1.59

gi|262400757 ATP synthase subunit beta 1.64 0.00 1.58 0.00 1.57 0.00 1.45 0.01 1.56

gi|75333362 ATP synthase subunit beta-3, mitochondrial

2.33 0.00 2.23 0.00 2.03 0.00 1.27 0.04 1.97

gi|262400756 ATP synthase subunit alpha 1.19 0.09 1.15 0.11 0.98 0.14 4.06 0.00 4.06

gi|75218880 ATP synthase gamma chain 1.53 0.10 1.45 0.20 1.60 0.03 1.00 0.79 1.60

gi|75246084 Phosphoglycerate kinase 1.67 0.00 1.56 0.01 1.56 0.00 1.85 0.00 1.66

gi|119720766 Hydrogen-transporting ATP synthase 4.17 0.05 4.09 0.06 4.33 0.05 1.15 0.79 4.25

gi|25089786 ATP synthase subunit d, mitochondrial

2.54 0.03 3.66 0.01 1.98 0.05 1.38 0.22 3.10

gi|461550 ATP synthase gamma chain 1 3.80 0.00 2.73 0.01 2.68 0.02 1.60 0.14 3.07

gi|18391442 Subunit C of the vacuolar H+-ATPase 2.05 0.02 1.89 0.03 1.82 0.04 1.12 0.88 1.92

101

Table 2-6. Continued.

Accession Name 117:113 P Val

117:113 118:114

P Val 118:114

119:115 P Val

119:115 121:116

P Val 121:116

Average

Metabolism (21)

gi|15241189 Embryo defective 2734 (EMB2734) 1.34 0.09 1.36 0.09 1.69 0.00 1.13 0.28 1.69

gi|122178786 Gamma-glutamylcysteine synthetase 2.44 0.02 2.27 0.03 2.33 0.02 1.46 0.26 2.35

gi|122236395 Cysteine synthase 1.46 0.59 1.33 0.45 1.28 0.41 2.19 0.04 2.19

gi|75265389 Alpha-xylosidase (XYL1) 1.54 0.12 1.57 0.45 1.37 0.56 2.33 0.02 2.33

gi|30696904 Xylose isomerase family protein 2.65 0.04 1.50 0.33 2.05 0.07 0.60 0.09 2.65

gi|17827 3-isopropylmalate dehydrogenase 2.40 0.04 2.29 0.04 2.44 0.04 2.31 0.05 2.38

gi|134273558 Unnamed protein product, containing serine-glycine hydroxymethyltransferase domain

1.12 0.43 2.05 0.00 1.09 0.82 0.74 0.06 2.05

gi|15237853 dTDP-glucose 4-6-dehydratase - like protein

2.03 0.04 1.61 0.11 1.50 0.15 0.86 0.57 2.03

gi|75315930 UDP-d-apiose/UDP-d-xylose synthase

1.84 0.00 1.49 0.01 1.63 0.02 1.54 0.01 1.62

gi|15236129 Aspartate aminotransferase 5 1.77 0.04 1.91 0.04 1.77 0.03 1.36 0.11 1.82

gi|15241486 Carbonic anhydrase 2 1.66 0.09 1.98 0.04 1.21 0.66 1.02 0.60 1.98

gi|21263610 Formate dehydrogenase, mitochondrial

1.69 0.08 1.82 0.02 1.50 0.04 0.69 0.64 1.66

gi|122216331 Glycolate oxidase 2.40 0.00 2.07 0.00 2.01 0.00 1.92 0.00 2.10

gi|54043095 Glycolate oxidase 1.61 0.04 1.57 0.03 1.25 0.16 1.58 0.03 1.59

gi|75103951 Oxalic acid oxidase 1.32 0.28 1.34 0.20 1.84 0.05 18.54 0.01 18.54

gi|75249348 Enoyl-[acyl-carrier protein] reductase 1.67 0.03 1.56 0.10 1.82 0.02 1.64 0.19 1.75

gi|12585448 UTP-glucose-1-phosphate uridylyltransferase 1

1.54 0.01 1.57 0.01 1.49 0.01 1.42 0.03 1.50

gi|17865468 Glucose-1-phosphate adenylyltransferase small subunit, chloroplastic (GLGS)

2.29 0.00 2.33 0.00 2.11 0.00 1.24 0.61 2.24

gi|187936039 Putative ADP-ribosylation factor 4.74 0.05 2.44 0.05 1.67 0.78 2.42 0.18 2.44

gi|118595573 Aldehyde dehydrogenase family 2 member B7, mitochondrial (AL2B7)

2.23 0.02 2.36 0.02 2.15 0.04 2.70 0.02 2.36

gi|13432260 Triosephosphate isomerase, cytosolic 3.05 0.08 2.31 0.13 2.36 0.04 0.53 0.39 2.36

102

Table 2-6. Continued.

Accession Name 117:113 P Val

117:113 118:114

P Val 118:114

119:115 P Val

119:115 121:116

P Val 121:116

Average

Protein synthesis (2)

gi|15238142 40S ribsomal protein S6 6.14 0.03 3.10 0.03 3.16 0.17 0.30 0.48 4.62

gi|72384424 4D11_26, containing histone H3 and ribosomal protein S6e domain

2.88 0.03 2.25 0.06 2.40 0.05 0.99 0.79 2.88

Protein synthesis and degradation (6)

gi|167117 60-kDa beta-polypeptide of plastid chaperonin-60 precursor

1.66 0.03 1.37 0.11 1.53 0.03 1.36 0.11 1.59

gi|1351030 RuBisCO large subunit-binding protein subunit alpha, chloroplastic

1.94 0.00 1.92 0.00 1.96 0.00 1.85 0.00 1.92

gi|85700445 Probable mitochondrial-processing peptidase subunit beta (MPPB)

3.05 0.00 3.13 0.00 2.40 0.00 1.36 0.88 2.86

gi|75337114 26S protease regulatory subunit 6A homolog

1.89 0.05 2.29 0.01 1.56 0.20 1.47 0.37 2.29

gi|99676 Chaperonin hsp60 precursor 1.92 0.05 1.53 0.14 1.20 0.50 1.74 0.15 1.92

gi|75283326 Protein disulfide isomerase (PDI)-like protein

1.91 0.03 1.63 0.07 1.92 0.03 1.21 0.35 1.91

Signaling (4)

gi|15222248 Protein phosphatase 2A regulatory subunit

8.02 0.03 12.59 0.00 5.75 0.01 4.25 0.08 8.79

gi|75332066 Probable calcium-binding protein CML13

1.71 0.04 1.80 0.03 2.01 0.01 1.56 0.05 1.77

gi|75331830 Serine/threonine-protein kinase SRK2E

1.50 0.05 1.53 0.04 1.34 0.13 1.29 0.21 1.51

gi|122215093 Calmodulin 5 2.05 0.01 2.11 0.03 1.79 0.06 2.94 0.01 2.37

Membrane and transport (1)

gi|125557716 Hypothetical protein OsI_024484, containing Arf1-Arf5-like subfamily domain

1.50 0.03 1.53 0.00 1.80 0.00 1.27 0.00 1.53

Stress and defense (18)

gi|914911 Germin-like protein 2.01 0.04 1.09 0.11 1.45 0.12 11.48 0.02 6.75

gi|157849698 Superoxide dismutase 2.81 0.00 2.47 0.00 3.05 0.00 1.89 0.03 2.55

103

Table 2-6. Continued.

Accession Name 117:113 P Val

117:113 118:114

P Val 118:114

119:115 P Val

119:115 121:116

P Val 121:116

Average

gi|15218518 Putative glutathione S-transferase 3.25 0.05 3.31 0.06 2.61 0.06 2.44 0.08 3.25

gi|83032224 Type 2 peroxiredoxin 1.34 0.44 1.27 0.55 3.16 0.04 1.37 0.56 3.16

gi|15229806 Putative 2-cys peroxiredoxin BAS1 precursor

2.56 0.03 2.81 0.02 2.31 0.04 1.32 0.67 2.56

gi|75248680 Ascorbate peroxidase 3.22 0.02 2.83 0.02 2.65 0.02 1.14 0.64 2.90

gi|15241113 Heat shock protein 81-3 (HSP81-3) 1.22 0.10 1.33 0.08 1.57 0.01 1.01 0.53 1.57

gi|75099813 Late embryogenesis abundant family protein

2.31 0.00 2.31 0.00 2.61 0.00 1.60 0.00 2.21

gi|169244541 Superoxide dismutase 1.91 0.02 2.01 0.02 1.94 0.02 1.32 0.07 1.95

gi|2204102 Glutathione-S-transferase 1.61 0.11 1.82 0.05 1.89 0.07 1.20 0.56 1.82

gi|15240578 Heat shock protein 70-7 1.42 0.18 1.38 0.15 1.77 0.02 0.55 0.43 1.77

gi|15237159 Root phototropism 3 (RPT3); ATPase 1.20 0.50 1.75 0.05 1.49 0.12 1.22 0.31 1.75

gi|15241849 Heat shock cognate 70 kDa protein 1 1.63 0.03 1.14 0.40 1.26 0.41 0.65 0.10 1.63

gi|157849720 Heat shock protein 81-4 1.56 0.04 1.61 0.04 1.26 0.23 1.67 0.02 1.62

gi|75312290 Glycerol kinase NHO1 1.63 0.02 1.49 0.03 1.53 0.01 1.61 0.01 1.56

gi|75299507 Lipoxygenase 1.77 0.02 1.98 0.03 1.67 0.04 2.44 0.54 1.81

gi|75263009 Early-responsive to dehydration 9 2.11 0.04 1.92 0.05 2.13 0.04 1.66 0.07 2.05

gi|75274048 Polygalacturonase inhibitor-like protein

1.69 0.05 1.75 0.06 1.94 0.05 2.00 0.04 1.97

Cell division, differentiation and fate (1)

gi|2499441 Proliferating cell nuclear antigen 1.61 0.13 1.56 0.11 1.80 0.08 2.86 0.02 2.86

Cell structure (1)

gi|75216938 Curculin-like lectin family protein 1.53 0.21 1.67 0.10 1.56 0.19 2.51 0.04 2.51

104

Table 2-7. List of proteins significantly down-regulated in guard cells by MeJA.

Accession Name 117:113 P Val

117:113 118:114

P Val 118:114

119:115 P Val

119:115 121:116

P Val 121:116

Average

Photosynthesis (9)

gi|262400730 Photosystem II CP43 chlorophyll apoprotein 0.31 0.00 0.28 0.00 0.39 0.01 1.22 0.50 0.33

gi|262400729 Photosystem II protein D2 0.54 0.10 0.47 0.04 0.56 0.07 1.31 0.50 0.47

gi|262400775 Photosystem I P700 chlorophyll a apoprotein 0.41 0.01 0.41 0.01 0.34 0.01 0.36 0.16 0.38

gi|75294948 Rubisco large chain 0.53 0.01 0.44 0.01 0.43 0.18 0.42 0.00 0.46

gi|4033349 Phosphoenolpyrovate carboxylase 0.74 0.28 0.36 0.02 0.42 0.01 0.49 0.02 0.43

gi|81301541 Photosystem II protein D1 0.31 0.01 0.37 0.00 0.45 0.03 1.47 0.29 0.38

gi|262400743 Photosystem II CP47 chlorophyll apoprotein 0.28 0.00 0.21 0.00 0.27 0.00 0.34 0.01 0.28

gi|22329337 Sucrose-phosphate synthase/ transferase 0.34 0.01 0.28 0.03 0.60 0.19 1.32 0.63 0.31

gi|262400774 Photosystem I P700 apoprotein A1 0.14 0.00 0.12 0.00 0.15 0.00 0.20 0.00 0.15

Energy (5)

gi|15235730 Putative phosphoenolpyruvate carboxykinase 0.66 0.13 0.19 0.00 0.54 0.08 0.11 0.03 0.15

gi|15219234 ATPase 70 kDa subunit, putative 0.63 0.06 0.52 0.02 0.55 0.04 0.67 0.34 0.54

gi|15239128 2-oxoglutarate dehydrogenase, E1 component

0.28 0.00 0.36 0.00 0.36 0.01 0.35 0.01 0.34

gi|75183214 2-oxoglutarate dehydrogenase, E1 -like protein

0.58 0.22 0.53 0.14 0.63 0.24 0.23 0.03 0.23

gi|30693102 NADH-ubiquinone oxidoreductase 75 kDa subunit

0.72 0.20 0.66 0.05 0.86 0.44 0.77 0.14 0.66

Metabolism (6)

gi|75707983 2-isopropylmalate synthase 1 0.44 0.01 0.57 0.02 0.42 0.00 0.52 0.01 0.49

gi|121550795 Nitrilase 1 0.29 0.02 0.61 0.02 0.43 0.02 1.57 0.85 0.44

gi|15240075 Succinate dehydrogenase flavoprotein subunit

0.28 0.00 0.30 0.02 0.48 0.01 0.57 0.03 0.41

gi|15226055 Putative fatty acid elongase 0.29 0.02 0.39 0.03 0.33 0.02 0.52 0.09 0.34

gi|15221119 Aminomethyltransferase-like precursor protein 0.20 0.00 0.50 0.03 0.31 0.02 0.32 0.04 0.33

gi|75180270 Alanine-2-oxoglutarate aminotransferase 0.47 0.05 0.61 0.16 0.91 0.83 0.37 0.02 0.42

Transcription related (5)

gi|18401305 Argonaute 4 (AGO4) 0.34 0.05 0.31 0.03 0.41 0.09 0.30 0.03 0.32

105

Table 2-7. Continued.

Accession Name 117:113 P Val

117:113 118:114

P Val 118:114

119:115 P Val

119:115 121:116

P Val 121:116

Average

gi|15218011 High mobility group protein (HMG1), putative 0.24 0.02 0.13 0.31 0.20 0.05 0.12 0.11 0.22

gi|15238563 Histone H2B-like protein 1.19 0.78 1.24 0.87 1.07 0.91 0.21 0.05 0.21

gi|121907 Histone H1.2 0.61 0.09 0.69 0.18 0.75 0.42 0.46 0.00 0.46

gi|22326646 Tudor domain-containing protein 0.22 0.05 0.14 0.02 0.35 0.00 0.31 0.04 0.26

Protein synthesis (2)

gi|15241316 40S ribosomal protein S8 (RPS8A) 0.59 0.17 0.74 0.33 0.43 0.03 1.12 0.89 0.43

gi|75328787 Elongation factor 1-alpha 0.75 0.18 0.46 0.00 0.90 0.63 0.50 0.00 0.48

Signaling (4)

gi|15222111 Putative calcium-binding protein, calreticulin 0.64 0.01 0.63 0.01 0.66 0.01 0.52 0.03 0.61

gi|15225924 Putative mitogen-activated protein kinase 0.57 0.05 0.44 0.01 0.51 0.02 0.34 0.00 0.46

gi|4324971 Phospholipase D2 0.44 0.02 0.60 0.07 0.38 0.01 0.65 0.15 0.41

gi|75262749 Extracellular calcium sensing receptor 0.88 0.38 0.70 0.29 1.00 0.75 0.44 0.04 0.44

Membrane and transport (6)

gi|15218215 Coatomer protein complex subunit beta 2 0.40 0.01 0.44 0.02 0.43 0.01 0.65 0.16 0.43

gi|15220684 Coatomer protein complex subunit alpha 0.39 0.00 0.40 0.01 0.34 0.00 0.28 0.00 0.35

gi|157849652 Pollen coat protein 0.94 0.98 0.79 0.27 1.05 0.72 0.38 0.00 0.38

gi|42563757 Clathrin heavy chain, putative 0.34 0.08 0.33 0.05 0.50 0.16 0.51 0.14 0.33

gi|1199503 Transmembrane channel protein 0.39 0.05 0.19 0.01 0.47 0.07 0.95 0.93 0.29

gi|399091 Vacuolar membrane proton pump 1 (AVP1) 0.26 0.05 0.17 0.02 0.22 0.04 0.70 0.55 0.22

Stress and defense (8)

gi|15224796 Putative WD-40 repeat protein (MSI4) 0.53 0.04 0.47 0.03 0.60 0.14 0.45 0.08 0.50

gi|15234010 Glycine-rich protein 2 (GRP2) 0.47 0.05 1.00 0.99 0.54 0.16 0.82 0.68 0.47

gi|158523427 Myrosinase 0.39 0.02 0.35 0.03 0.36 0.00 0.15 0.04 0.31

gi|15225798 3-ketoacyl-CoA thiolase 0.44 0.01 0.48 0.03 0.62 0.09 0.50 0.11 0.46

gi|157849770 ERD12 protein 0.69 0.02 0.61 0.31 0.50 0.08 0.21 0.01 0.45

gi|75127356 Water stress induced protein 0.03 0.00 0.03 0.00 0.07 0.01 0.04 0.01 0.04

gi|77999357 Protein disulfide isomerase 0.74 0.91 1.03 0.95 1.06 0.65 0.02 0.04 0.02

gi|231995 Dehydrin Rab18 (DHR18) 0.37 0.12 0.48 0.28 0.31 0.02 0.35 0.09 0.31

106

Table 2-7. Continued.

Accession Name 117:113 P Val

117:113 118:114

P Val 118:114

119:115 P Val

119:115 121:116

P Val 121:116

Average

Cell structure (1)

gi|15230191 Actin 2 0.53 0.03 0.65 0.11 0.57 0.04 0.73 0.30 0.55

Unknown (1)

gi|37999993 Unknown protein, containing CBS domain 0.52 0.06 0.35 0.08 0.15 0.04 0.21 0.03 0.18

107

Table 2-8. Motif analysis of genes encoding the MeJA responsive proteins (upstream 500bp).

Motif Sequence Absolute Number in

Selected Genes Observed in

Selected Genes Absolute Number in Genomic Set

Observed in Genomic Set

P Value

TGAGCC 23 23/123 (18.70%) 3032 2805/33602 (8.35%) 1.30E-04

GCCCAT 46 37/123 (30.08%) 7924 5749/33602 (17.11%) 1.52E-04

GCCCAG 15 15/123 (12.20%) 1712 1590/33602 (4.73%) 4.99E-04

TGCCTT 8 6/123 (4.88%) 4957 4518/33602 (13.44%) 1.16E-03

ACGGCC 15 13/123 (10.57%) 1512 1388/33602 (4.13%) 1.21E-03

GGCCGT 15 13/123 (10.57%) 1512 1388/33602 (4.13%) 1.21E-03

GGCCCA 56 34/123 (27.64%) 8914 5930/33602 (17.65%) 1.90E-03

TGGGCC 56 34/123 (27.64%) 8914 5930/33602 (17.65%) 1.90E-03

GCCAAT 33 29/123 (23.58%) 5342 4853/33602 (14.44%) 2.31E-03

AGGCCC 33 26/123 (21.14%) 5238 4180/33602 (12.44%) 2.32E-03

GGGCCT 33 26/123 (21.14%) 5238 4180/33602 (12.44%) 2.32E-03

AGCCGC 14 12/123 (9.76%) 1451 1377/33602 (4.10%) 3.10E-03

TTGCCC 18 18/123 (14.63%) 2748 2576/33602 (7.67%) 3.38E-03

GCCCCA 11 11/123 (8.94%) 1311 1265/33602 (3.76%) 4.51E-03

CGCCAT 17 17/123 (13.82%) 2625 2456/33602 (7.31%) 4.63E-03

GGCCCC 7 7/123 (5.70%) 666 640/33602 (1.90%) 6.94E-03

GGGGCC 7 7/123 (5.70%) 666 640/33602 (1.90%) 6.94E-03

GCCCAA 48 33/123 (26.83%) 8666 6384/33602 (19.00%) 8.63E-03

108

Table 2-8. Continued.

Motif Sequence Absolute Number in

Selected Genes Observed in

Selected Genes Absolute Number in Genomic Set

Observed in Genomic Set

P Value

GGGCCA 19 17/123 (13.82%) 2920 2663/33602 (7.92%) 9.04E-03

TGGCCC 20 17/124 (13.82%) 2921 2663/33602 (7.92%) 9.04E-03

AGCCCA 52 31/123 (25.20%) 8502 6092/33602 (18.13%) 1.24E-02

GCCAAA 23 21/123 (17.07%) 9731 8218/33602 (24.46%) 1.33E-02

CGGCCC 13 12/123 (9.76%) 1931 1736/33602 (5.17%) 1.44E-02

GGGCCG 13 12/123 (9.76%) 1931 1736/33602 (5.17%) 1.44E-02

GAGCCC 12 12/123 (9.76%) 1841 1737/33602 (5.17%) 1.45E-02

GCCTCA 16 15/123 (12.20%) 2709 2529/33602 (7.53%) 2.11E-02

GAGCCG 12 11/123 (8.94%) 1788 1644/33602 (4.89%) 2.15E-02

TTGCCG 4 4/123 (3.25%) 2721 2558/33602 (7.61%) 2.47E-02

GCCCAC 15 14/123 (11.38%) 2650 2381/33602 (7.08%) 2.58E-02

CGCCGT 3 3/123 (2.44%) 2473 2179/33602 (6.48%) 2.65E-02

AAGGCC 26 20/123 (16.26%) 4531 3830/33602 (11.40%) 2.67E-02

GGCCTT 26 20/123 (16.26%) 4531 3830/33602 (11.40%) 2.67E-02

GCCTAA 25 22/123 (17.89%) 4814 4372/33602 (13.01%) 2.88E-02

ATAGCC 19 18/123 (14.63%) 3680 3411/33602 (10.15%) 3.02E-02

TAAGCC 25 22/123 (17.89%) 4911 4426/33602 (13.17%) 3.14E-02

GCCCGA 7 7/123 (5.70%) 968 927/33602 (2.76%) 3.37E-02

109

Table 2-8. Continued.

Motif Sequence Absolute Number in

Selected Genes Observed in

Selected Genes Absolute Number in Genomic Set

Observed in Genomic Set

P Value

GCCCGA 7 7/123 (5.70%) 968 927/33602 (2.76%) 3.37E-02

AAGCCC 35 25/123 (20.32%) 6960 5443/33602 (16.20%) 4.31E-02

TGCCGT 3 3/123 (2.44%) 2099 1949/33602 (5.80%) 4.54E-02

AGGCCG 9 7/123 (5.70%) 1051 1009/33602 (3.00%) 4.55E-02

CGGCCT 9 7/123 (5.70%) 1051 1009/33602 (3.00%) 4.55E-02

CTGGCC 8 8/123 (6.50%) 1314 1235/33602 (3.68%) 4.62E-02

GGCCAG 8 8/123 (6.50%) 1314 1235/33602 (3.68%) 4.62E-02

AGGGCC 8 8/123 (6.50%) 1330 1246/33602 (3.70%) 4.77E-02

GGCCCT 8 8/123 (6.50%) 1330 1246/33602 (3.70%) 4.77E-02

TATGCC 6 6/123 (4.88%) 3030 2871/33602 (8.54%) 4.79E-02

GCCATT 26 24/123 (19.51%) 5888 5280/33602 (15.71%) 4.81E-02

AGCCGT 13 13/123 (10.57%) 2787 2453/33602 (7.30%) 4.91E-02

GCCTTG 14 14/123 (11.38%) 2930 2712/33602 (8.07%) 4.99E-02

CACGTG 32 15/123 (12.20%) 7766 3253/33602 (9.68%) 7.22E-02

110

Figure 2-1. Isolation of guard cell protoplasts from B. napus leaves. A) Stomata and

epidermal cells on a leaf epidermal peel. B) After the second enzyme digestion, guard cells round up and are released from stomata. C) Guard cell protoplasts collected after separating from epidermal peels. Note the contamination by a mesophyll cell. D) Guard cell protoplasts purified by

Histopaque centrifugation (400 ).

A B C DA B C D

111

Figure 2-2. Classification of the 1458 identified proteins into molecular functions. The pie chart shows the distribution of the non-redundant proteins into their functional classes in percentage. The classification was performed with reference to Bevan et al. A) All 1458 proteins. B) Proteins enriched in guard cells. C) Proteins enriched in mesophyll cells.

112

Figure 2-3. Representative MS/MS spectra showing protein identification and relative

quantification in guard cells (iTRAQ tag 114) and mesophyll cells (iTRAQ tag 116). A) An MS/MS spectrum identified the peptide QLDASGKPDNFTGK (confidence 99%) derived from photosystem II protein and its relative abundance in the two types of cells. B) An MS/MS spectrum identified the peptide DSNIASIPVEELIEK (confidence 99%) derived from plasma membrane P-type ATPase AHA1 and its relative abundance in the two types of cells.

113

Figure 2-4. Scatter plot of the ratio of GC/MC at the mRNA level and protein level. The correlation coefficient was estimated to be 0.37.

114

Figure 2-5. Effect of diphenyleneiodonium (DPI), catalase (CAT) and ascorbic acid (ASC) on ABA/MeJA-induced stomatal closure and H2O2 production. A) DPI, CAT and ASC reverse closure induced by ABA/MeJA. B and C) DPI, CAT and ASC reduce the ROS level elevated by ABA/MeJA. The pseudocolor key beside the stomata indicates increase of the fluorescence from bottom to top.

115

Figure 2-6. Classification of ABA increased and decreased proteins into biological

functions. The pie charts show the distribution of the non-redundant proteins into their functional classes in percentage. A) Sixty six proteins increased in abundance in response to ABA treatment. B) Thirty eight proteins decreased in abundance in response to ABA treatment.

116

Figure 2-7. Total protein identification from complementary mass spectrometry platforms. A) Protein identified from three MS platforms with a threshold 1.3 of the unused score. B) Venn diagram of the guard cell proteins for the three parts of results. Based on the sequence, the three platforms profiled 1220 non-redundant proteins in total for the B. napus guard cell proteome.

117

Figure 2-8. Classification of MeJA increased and decreased proteins into biological functions. The pie charts show the distribution of the non-redundant proteins into their functional classes in percentage. A) Seventy three proteins increased in abundance in response to MeJA treatment. B) Forty seven proteins decreased in abundance in response to MeJA treatment.

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Figure 2-9. The involvement of the MeJA responsive components in response to other stress factors. The accessions identified from the MeJA treated guard cells were also responsive to other stress factors. Red color represents reported responsiveness to the corresponding stress whereas black color indicates non-responsiveness.

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CHAPTER 3

REDOX REGULATORY MECHANISMS IN GUARD CELL ABA AND MEJA SIGNALING PATHWAYS

Introduction

Guard cells are highly specialized epidermal cells that border tiny pores called

stomata on plant leaf surfaces. Guard cells rapidly change volume and shape so that

the pores open or close in response to environmental signals, thus regulating CO2

uptake and water transpiration. Hence, stomatal function is essential for plant growth,

development, yield and interaction with the environment. In response to drought, the

phytohormone abscisic acid (ABA) triggers guard cell responses that inhibit stomatal

opening and promote stomatal closure, thus minimizing water loss. ABA signaling

cascade in guard cells is one of the best understood plant signaling processes

(Assmann, 1993; Schroeder et al., 2001; Fedoroff, 2002; Li et al., 2006). Classic genetic

screens, reverse genetics, and cell biological analyses have revealed over 30

components participating in guard cell ABA signaling, and the information has been

synthesized into a network model (Li et al., 2006; Figure 1-1). H2O2 has been

recognized as a central component in this network (Wang and Song, 2008). Recently

nitric oxidize (NO) has been found to function as another second messenger (Saito et

al., 2009). The elevation of H2O2 and NO is also observed in the methyl jasmonate

(MeJA)-triggered stomatal closure (Munemasa et al., 2007; Saito et al., 2009). The

generation of the weak oxidants could lead to mild oxidative stress in guard cells.

Protein cysteines are particularly susceptible to the oxidative insults due to the

nucleophilic property of the sulfhydryl groups (Di Simplicio et al., 2003). Modification of

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the cysteine thiol by redox is an important signaling mechanism for conveying cellular

responses (Finkel, 2003; Tonks, 2005).

In mammals, many signaling proteins have been shown to be redox regulated,

including Ca2+-ATPase, Ras-related GTPase, EGF growth factor, phosphorylase β

kinase and voltage-dependent anion channel protein (Yuan et al., 1994; Matsunaga et

al., 2003; Heo and Campbell, 2005; Aram et al., 2010; Cuddihy et al., 2011). In plants,

reduction of specific cysteine residues activates Calvin cycle enzymes such as fructose-

1, 6-bisphosphatase and phosphoribulokinase (Jacquot et al., 2002). In guard cells, the

activities of protein phosphatase ABI1 and ABI2 are sensitive to redox state (Meinhard

and Grill, 2001; Meinhard et al., 2002). Recently, it was found that stomata of the

ethylene receptor mutant etr1 did not close in response to H2O2, and mutation of a

cysteine residue in ETR1 disrupted H2O2-induced stomatal closure (Radhika et al.,

2005). However, direct evidence for thiol-based redox regulation and a link between

protein redox change and stomatal closure remain to be demonstrated. Proteomics is a

powerful technology that has moved beyond simple protein cataloging towards large

scale analysis of post-translational modifications (PTMs) (Mann and Jensen, 2003).

Two complementary proteomics approaches, saturation differential in-gel

electrophoresis (DIGE) and isotope-coded affinity tag (ICAT) can be employed to

investigate thiol-based protein redox regulation (Fu et al., 2008). The principle

underlying the approaches is that free thiols are irreversibly alkylated by iodoacetamide

(IAM), leading to carbamidomethylation (CAM). When exposed to oxidative conditions,

the sensitive cysteine thiols are oxidized. After reduction, these thiols can be specifically

labeled by fluorescent dyes or ICAT reagents, which can be differentiated by 2D gel

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electrophoresis (2-DE) and mass spectrometry (MS) analysis (Figure 3-1). Here we

demonstrate the first application of the redox proteomics technologies to investigate

thiol-based protein redox switches in guard cell phytohormone signaling. In total, 73 and

130 redox sensitive proteins were identified in ABA and MeJA treated guard cells,

respectively, among which 37 were common. A total of 54 redox sensitive cysteines

were mapped by MS/MS. This study creates an inventory of potential redox switches

and highlights crosstalk between ABA and MeJA signaling pathways in guard cells. The

evidence of phytohormone signaling mediated by novel redox switches has greatly

improved our understanding of the molecular networks underlying stomatal function.

Material and Methods

Plant Growth, Guard Cell Protoplast Preparation, and Hormone Treatment

Brassica napus var. Global seeds were obtained from Svalöv Weibull AB (Svalöv,

Sweden). Seeds were germinated in Metro-Mix 500 potting mixture (The Scotts Co.,

USA) and plants were grown in a growth chamber under photosynthetic flux of 160 µmol

photons m-2s-1 with a photoperiod of 8 hours at 22°C light and 20°C dark. Fully

expanded leaves from eight weeks old plants were used for isolation of guard cell

protoplasts as previously described. For ABA treatment of guard cells, ABA was added

to the second enzyme digestion and the basic solution used in the following steps at a

final concentration of 100 µM. The treatment time lasted for 3 hours. MeJA treatment

was conducted in the same way but its concentration varied at 100 µM in enzyme

digestion followed by 50 µM in the basic solution. The concentration of MeJA in the

basic solution was adjusted because exposure to 100 µM MeJA resulted in the

breakage of the guard cell protoplasts and finally a much lower yield. This concentration

range is effective to promote stomatal closure in Brassica napus epidermal peels and

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has been used by other research groups (Munemasa et al., 2007; Dombrecht et al.,

2007).

Stomatal Aperture Measurement

Stomatal aperture was measured as previously described with slight modifications

(Zhang et al., 2001). A couple of leaves from a plant were blended and the epidermal

strips were washed with cold tap water. The freshly prepared epidermal strips were

incubated in a degassed medium (50 µM CaCl2, 10 mM KCl and 10 mM MES-KOH, pH

6.2) under white light 125 μE, 22°C for 3 h to promote stomatal opening. After checking

the stomatal aperture, the following chemicals were added: diphenyleneiodonium (DPI)

20 µM, catalase 200 U/mL, and ascorbic acid 10 mM, respectively. The epidermal peels

were incubated for 20 min before addition of 20 µM ABA or MeJA. Images of stomata

were captured by a light microscope Zeiss Axiostar Plus (Carl Zeiss Inc., USA) and

apertures were measured by the software Axiovison 4.1. At least 60 stomata were

analyzed in each experiment and three replicate experiments were conducted.

Reactive Oxygen Species Detection in Guard Cells

Epidermal peels were prepared as described above. Fifty micromolar 2', 7'-

dichlorodihydrofluorescein diacetate (H2DCF-DA), a fluorescent dye for detection of

H2O2 level in guard cell, was added to the incubation medium for 30 min of dye loading

(Desikan et al., 2004). The peels were collected using a nylon mesh and washed with

distilled water. Then the following chemicals were added to the incubation medium with

the dye-loaded peels: ABA 20 µM, MeJA 20 µM, DPI 20 µM, catalase 200 U/ml,

ascorbic acid 10 mM, respectively. The peels were treated for 20 min. Stomata were

observed under a fluorescence microscope (Zeiss Axioplan 2, excitation 488 nm,

emission 515 nm, Carl Zeiss Inc., USA), exposure limited to 20 ms and only one image

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captured per sample. The fluorescence emission of stomata was quantified by software

Progenesis PG200 (Nonlinear Dynamics Ltd., USA).

Protein Extraction and ICAT Labeling

A solution of 10% trichloroacetic acid (TCA) in acetone was used to precipitate

protein for 2 hours on ice. Samples were washed with 80% acetone followed by

washing with 100% acetone twice. Pellets were briefly dried and dissolved in the

ReadyPrepTM Sequential Extraction Reagent 3 (Bio-Rad Inc., USA). Samples were

quantified using a CB-XTM protein assay kit (G Biosciences Inc., USA). A protein aliquot

of 100 µg was alkylated by 100 mM iodoacetamide (IAM) at 75°C for 5 min followed by

37°C for 1 hour (Alvarez et al., 2009). The sample was then precipitated in 100% cold

acetone over night. The pellet was briefly dried and dissolved in 80 μL ICAT denaturing

buffer (pH 8.5) provided in an ICAT kit. Reduction, labeling and trypsin digestion were

performed according to the manufacturer‟s manual (Applied Biosystems Inc., USA).

Tryptic peptides were fractionated on an Agilent HPLC system 1100 using a Luna®

HILIC (hydrophilic interaction chromatography) column (150 x 2.00 mm, 3 µm, 200 Å,

Phenomenex, USA). Ten fractions were collected for each replicate. The peptides in

each fraction were purified using an avidin affinity cartridge provided in the kit, and were

dried and suspended in trifluoroacetic acid to release the peptides from the acid-

cleavable linker by incubating at 37°C for 2 h. The peptides were lyophilized and

dissolved in a loading buffer (3% acetonitrile v/v, 0.1% acetic acid v/v) for mass

spectrometry analysis.

Saturation DIGE Labeling, 2DE and Protein Digestion

Procedures for protein sample preparation, quantification and alkylation was

performed as described above for ICAT labeling. Control and treated guard cell protein

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samples were mixed equally to generate an internal standard. The DIGE labeling

procedure was adapted from the manufacturer‟s protocol (GE Healthcare, USA). Cy3

maleimide (Cy3m) was used to label six equal aliquots (10 μg each) of the internal

standard. Cy5 maleimide (Cy5m) was used to label three control or three treated

(ABA/MeJA) samples (10 μg each). The amount of tris-2-carboxyethyl-phosphine

(TCEP) and Cy dye was adjusted to 3 nmol and 6 nmol, respectively. The final volume

of each combined reaction mixture was 183 µL in rehydration buffer (8 M urea, 2%

CHAPS, 1% DTT, and 1% ampholytes 4-7). Samples were loaded onto 24 cm IPG

strips (pH 4-7, GE Healthcare, USA), rehydrated with the sample buffer for 12 h, and

subsequently focused in an EttanTM IPGphorTM 3 IEF system (GE Healthcare, USA) for

80,000 V-hr, at a maximum voltage of 10,000 V and a current limit of 50 mA/strip.

Proteins were then separated in the second dimension on 24 cm 8-16% gradient Tris-

HCl gels (Jule Biotechnologies Inc., USA) using an Ettan TM DALTsix electrophoresis

unit (GE Healthcare, USA). After electrophoresis, gels were rinsed with Milli-Q water

and scanned on a Typhoon TM 9400 imager (GE Healthcare, USA) with 100 µm

resolution and appropriate photomultiplier tube voltages to ensure no spot saturation.

DeCyder TM software (v5.0, GE Healthcare, USA) was used to analyze the gel images.

Protein spots (with 1.5 fold change) with p-values less than 0.05 were matched to the

preparative gel. Spots were excised for identification according to a standard protocol

(Alvarez et al., 2009). Briefly, a 50 mM ammonium bicarbonate/50% acetonitrile (ACN)

solution was used to wash the gel spots prior to digestion by 12 h incubation at 37°C in

30 µL of 6 ng/µL trypsin (Promega Corp., USA). Peptide extraction was performed in

two rounds; first with 2% ACN, 1% formic acid, and then with 60% ACN.

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Reverse Phase Nanoflow HPLC, Tandem Mass Spectrometry and Protein Identification

ICAT fractions or peptides from each spot of DIGE experiment was dissolved in 10

µL solvent A (0.1% v/v acetic acid, 3% v/v acetonitrile) and loaded onto a C18

PepMapTM nanoliter-flow column (75 µm id, 3 µmm, 100 A, LC Packings, USA). The

elution gradient of the column started at 97% solvent A/3% solvent B (0.1% v/v acetic

acid, 96.9% v/v acetonitrile) and finished at 40% solvent A/60% solvent B within 1 h for

ICAT sample and 20 min for DIGE sample, respectively. Tandem MS analysis was

carried out on a hybrid quadrupole-time of flight mass spectrometer (QSTAR® XL,

Applied Biosystems Inc., USA). The focusing potential and ion spray voltages were set

to 275 V and 2,600 V, respectively. The information-dependent data acquisition (IDA)

was employed in which a survey scan from m/z 400–1,500 was acquired followed by

collision induced dissociation of three most intense ions. Survey scan and each MS/MS

spectrum in an IDA cycle were accumulated for 1 s and 3 s, respectively. The analysis

on the MS data for ICAT was performed in the software ProteinPilotTM 2.0.1 (Applied

Biosystems Inc., USA) searching a target-decoy concatenated NCBI FASTA database

for green plants (5,222,402 entries, July 2, 2007). For the DIGE experiment, the MS

spectra for each spot were searched against the same database using Mascot search

engine (http://www.matrixscience.com). The following parameters were selected: tryptic

peptides with no more than 1 missed cleavage site, mass tolerance of precursor ion and

MS/MS ion of 0.3 Da and variable methionine oxidation, and ICAT and DIGE

modifications of cysteines were selected respectively. At least 2 peptides identified or 1

peptide with at least 6 continuous ions in the MS/MS spectrum was accepted as

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threshold for significant IDs. Sequence coverage and Mascot score were also taken into

consideration for unambiguous identification (Chen and Harmon, 2006).

Data Analysis

For ICAT, after the export of all peptides from the .group file generated by the

software ProteinPilot, the following criteria were used for the identification of the redox

sensitive cysteine-containing proteins: 1) contain at least one ICAT modified cysteine; 2)

at least 20% increase or decrease in ICAT MS ion intensity under treatment; 3) peptide

confidence over 95%; 4) the peptide appears in at least two replicates, and 5) each

peptide assigned to only one protein without redundancy. IDs from DIGE experiments

were screened by the proteins sequence and those without cysteines were not

considered. The protein IDs from both ICAT and saturation DIGE are combined to

generate a redox sensitive protein list for each treatment. The protein sequence was

used to determine the overlapping components between the data sets. The redox

sensitive proteins were classified according to the molecular functions. All the protein

sequences were analyzed by the software DiANNA

(http://clavius.bc.edu/~clotelab/DiANNA/) for intra-disulfide bond prediction using a

neural network-based approach (Ferre and Clote, 2005).

Results and Discussion

B. napus Guard Cells for Redox Proteomics

Exogenous ABA and MeJA can induce stomatal closure and elevation of the

stomatal ROS levels in several species (Desikan et al., 2004; Islam et al., 2009). In

Chapter 2 it was shown the application of 20 μM ABA or MeJA have the similar effect on

Brassica napus stomata (Figure 2-5). Additionally, the induced stomatal closure and the

ROS production can be reversed by ROS scavengers such as diphenylene iodonium

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(DPI), catalase and ascorbic acid. These results not only suggest that the guard cell

redox state are important in the ABA and MeJA signaling processes leading to stomatal

closure but also confirm that Brassica napus guard cells have similar responses as

other plant species. Considering the good quality and quantity of guard cells as well as

the proteomics data generated (e.g., Chapters 2), we choose to use B. napus guard

cells to investigate redox responsive proteins in guard cell hormone signaling.

Guard Cell Redox Responsive Proteins in ABA Signaling

Here a reverse strategy was employed in which the proteins were firstly alkylated

by IAM to block free thiols, then reduced by tris(2-carboxyethyl)phosphine (TCEP) to

expose those sulflhydryl groups that had been reversibly oxidized due to hormone

treatment. The reverse labeling strategy was preferred considering cysteines buried

inside the proteins may be easily accessible for the DIGE or ICAT tags (Fu et al., 2008).

Thus the increase of signal intensity in ABA or MeJA treated samples indicates the

presence of more thiol groups after reduction, i.e., more oxidized cysteines in the

original treated protein samples, compared to control samples. Compared to the forward

strategy which labels the sample directly without the initial alkylation and reduction

steps, the reverse strategy has the advantage of exposing the oxidized cysteines buried

in the protein molecules. In addition, the reverse labeling strategy keeps the initial redox

state of the proteins and covers more modifications spatially (Fu et al., 2008).

Table 3-1 lists the 73 redox sensitive proteins in guard cells under ABA treatment,

of which 27 and 54 were identified from ICAT and saturation DIGE, respectively. Eight

proteins were identified in both methods. Functional classification shows these redox

responsive proteins largely fall into the groups of energy, metabolism, cell structure,

photosynthesis, and stress and defense (Figure 3-2). A large number of guard cell

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proteins belonging to the energy function group were found to be changed at expression

levels, mostly up-regulated under ABA treatment (Table 2-3 and Table 2-4). This is

consistent with the high energy consumption related to the guard cell physiology of

stomatal movement (Parvathi and Raghavendra, 1997). The identified redox responsive

proteins in this group include several ATP synthase subunits, fructose-bisphosphate

aldolase, glyceraldehyde-3-phosphate dehydrogenase, malate dehydrogenase,

phosphoglycerate kinase 1 and succinyl-CoA synthetase, most of which have been

established or identified as potential thioredoxin targets using proteomics approaches

(Table 3-1; Buchanan and Balmer, 2005). Identified redox responsive proteins

participating in photosynthesis include Rubisco large and small subunits, photosystem II

44 kD reaction center protein, phosphoribulokinase, ferredoxin and sedoheptulose-

bisphosphatase (Table 3-1). Both phosphoribulokinase and ferredoxin have the

conserved cysteine residues necessary for thioredoxin-dependent regulation (Walters

and Johnson, 2004; Michels et al., 2005). The enzyme sedoheptulose-bisphosphatase

has thiol group in the active site (Raines et al., 1999). Rubisco subunits are newly

reported thioredoxin targets (Motohashi et al., 2001; Lemaire et al., 2004). Cell

respiration and photosynthesis involve an assembly of redox reactions and thus

represents highly redox regulated processes (Jacquot et al., 2002; Rouhier et al., 2002;

Giraud et al., 2011). Hydrogen peroxide produced by electron transport chain in

mitochondria and pseudocyclic phosphorylation (Mehler reaction) in chloroplasts is an

oxidant signal (op den Camp et al., 2003). Thioredoxin is a small protein reduced

enzymatically by NADPH and ferredoxin, and thus active in thiol/disulfide exchange. It

enables chloroplasts and mitochondria to communicate via a network of transportable

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metabolites such as malate and glycolate through redox sensing (Buchanan and

Balmer, 2005). Several proteins in the two processes are reported to be thiol-based

redox regulated, e.g., fructose bisphosphatase, NADP-malate dehydrogenase and

NADP-glyceraldehyde 3-phosphate dehydrogenase (Ocheretina and Scheibe, 1994;

Carr et al., 1999; Chiadmi et al., 1999). Proteomics approaches have facilitated the

identification of potential thioredoxin target proteins in the two important processes and

an updated list of thioredoxin target proteins have been generated (Motohashi et al.,

2001; Lemaire et al., 2004; Buchanan and Balmer, 2005). Our data have provided extra

evidence for those identified thiol-based (thioredoxin) regulated proteins and revealed

new redox responsive components in guard cell chloroplasts and mitochondria after

ABA treatment.

Proteins involved in the metabolism constitute another large group of redox

responsive groups in ABA treated guard cells (Table 3-1). Several proteins have been

reported to be thioredoxin targets, including aspartate aminotransferase, glutamine

synthetase, and threonine synthase (Buchanan and Balmer, 2005). A few of the

enzymes, such as glutamine synthetase and oxalic acid oxidase, have thiol groups in

the active sites (Chiriboga, 1966; Ericson and Brunn, 1985). This finding implies that

amino acid metabolism might adapt to oxidative stress by post-translational modification

to the cysteines in the active sites, and consequently activate or inhibit the enzymes to

alter the metabolism. The underlying mechanisms deserve further investigation.

Other groups of great interest include stress and defense, cell structure and signal

transduction. Unlike the iTRAQ results (Chapter 2), not many redox responsive proteins

were identified in stress and defense group (Table 2-3, Table 2-4 and Table 3-1). The

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senescence-associated cysteine protease, with a cysteine residue at the active center,

have been extensively studied because they appear to play a central role in a wide

range of proteolytic functions from embryo development to programmed cell death

(Tajima et al., 2011). A senescence-associated cysteine protease was reported to be

redox regulated by ascorbate and thiols during pea root nodule senescence (Groten et

al., 2006). An enolase LOS2 is involved in cold-responsive gene transcription (Lee et

al., 2002). Enolase has been identified to be a thioredoxin target protein (Buchanan and

Balmer, 2005). Here our data show that LOS2 is potentially under redox regulation in

the ABA response (Table 3-1). ERD12 encodes allene oxide cyclase, an enzyme

catalyzing an essential step in jasmonic acid biosynthesis. The identification of ERD12

here indicates the crosstalk between the ABA and MeJA signal transduction in guard

cells. Allene oxide cyclase is also a thioredoxin target and has been identified to be S-

nitrosylated in A. thaliana undergoing hypersensitive response (Buchanan and Balmer,

2005; Romero-Puertas et al., 2008). Myrosinase has been found to be a key regulatory

element in both ABA and MeJA signaling pathways in guard cells (Zhao et al., 2008;

Islam et al., 2009; Figure 3-3). Plant myrosinase is not activated by most reducing

agents, e.g., gluthatione and cysteine but is activated by L-ascorbic acid (Nagashima

and Uchiyama, 1959; Ohtsuru and Hata, 1979). The interaction of myrosinase and ROS

production in the ABA signal transduction in guard cells is not clear. Work in our lab is

under way to validate redox regulation of myrosinases. Ascorbate peroxidase (APX) is

an enzyme that detoxifies peroxides such as hydrogen peroxide using ascorbate as a

substrate (Noctor and Foyer, 1998). It has been reported that cysteine oxidation is

involved in the inactivation of APXs, and glutathione protects APX from irreversible

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oxidation of the cysteine thiol and loss of enzyme activity by binding to the cysteine thiol

group (Kitajima et al., 2007). In plants, the monodehydroascorbate reductase (MDAR) is

an enzymatic component of the glutathione-ascorbate cycle that is one of the major

antioxidant systems of plant cells for the protection against ROS damages (Asada,

1997). Previous work suggested that a conserved cysteine residue of the cucumber

MDAR is required for electron transfer between MDAR-FAD and NAD(P)H prior to the

reduction of monodehydroascorbate to ascorbate (Sano et al., 1995).

Cytoskeleton reorganization is one of the distinguished events in stomatal closure

triggered by ABA (Li et al., 2006). Actin and tubulin reorganization in Arabidopsis guard

cells was observed in the process of ABA-induced stomatal closure (Lemichez et al.,

2001). Specifically, ABA induces rapid depolymerization of cortical actin filaments and

the slower formation of a new type of actin that is randomly oriented throughout the cell.

The actin reorganization in guard cells is mediated by cytosolic calcium levels and by

protein kinase and protein phosphatase activities (Hwang and Lee, 2001). Both actin

and tubulin have also been identified to be thioredoxin target proteins in proteomic

studies, indicating the possibility of redox regulation in addition to phosphorylation

events (Buchanan and Balmer, 2005). Here we have identified actin, tubulins, extensin-

like protein, protein containing stomatin domain and plastid-lipid associated proteins

(PAP) as redox responsive proteins in B. napus guard cells under ABA treatment.

Extensins are essential for cell wall assembly and growth through cell extension and

expansion (Everdeen et al., 1988). Stomatin is a 32 kD membrane protein as a partner

of a membrane-bound proteolytic process (Green et al., 2004). But it has been rarely

studied in plants. The accumulation of PAPs in plastids and the biogenesis of structures

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that sequester hydrophobic compounds are enhanced by various stresses (Murphy,

2004). How these proteins contribute to the cytoskeleton reorganization of guard cells in

response to ABA and the redox regulatory mechanisms are worth of investigation.

Very interestingly, a few signaling proteins were found to be redox responsive,

such as 14-3-3 protein, calmodulin-binding protein, an osmotic stress-activated protein

kinase and a serine/threonine phosphatases 2C. Cysteine of the 14-3-3 protein was

found to be S-nitrosylated (Greco et al., 2006). Redox regulation of calmodulin-binding

protein, kinase and phosphatase has rarely been reported but the interaction between

phosphorylation/dephosphorylation and redox regulation deserves more investigation

(Saze et al., 2001; Cabrillac et al., 2001; Gupta and Luan, 2003).

Overall, ABA treatment has been demonstrated to associate with oxidative stress

involving ROS and RNS production. The identification of the redox responsive proteins

in this process highlights the importance of the redox state in guard cell in the stress

response and the redox regulation as an essential regulatory mechanism. It is

noteworthy a great portion of the identified components have been reported to be

thioredoxin target proteins by proteomics. In addition to the ones mentioned above,

elongation factor Tu, eukaryotic initiation factor 4A and GTP-binding nuclear protein

RAN1 are also in the thioredoxin target list (Table 3-1; Buchanan and Balmer, 2005).

This suggests thioredoxin plays an important role in guard cell redox regulation.

However, the existence of six different types of thioredoxin in A. thaliana raises the

question about target specificity (Buchanan and Balmer, 2005).

In addition, the sequence of each protein was submitted for intra-molecular

disulfide prediction (http://clavius.bc.edu/~clotelab/DiANNA/). Forty three out of 73 were

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predicted to form significant intra-molecular disulfide bonds. It should be noted that

dithiol-disulfide exchange only represents one modification on the thiol group of

cysteine. Other types of modifications include S-nitrosylation, sulfinic acid, sulfenic acid

and sulfonic acid (Depuydt et al., 2011; Figure 1-4). Our data have set a stage for

further characterization of the potential redox regulated proteins in guard cell ABA

signaling.

Redox Responsive Proteins in MeJA Signaling

Table 3-2 lists the redox responsive proteins in guard cells under MeJA treatment.

Functional classification of the proteins has revealed a very similar pattern to that of

ABA (Figure 3-2). Proteins related to energy, metabolism, stress and defense, protein

folding, transporting and degradation, and photosynthesis are dominant followed by

minor groups such as protein synthesis and cell structure. Forty proteins belong to the

group of metabolism, constituting the largest group of the redox responsive proteins in

guard cells under MeJA treatment. Except for some overlapping ones with the ABA

redox responsive proteins, leucine aminopeptidase, cysteine synthase, triosephosphate

isomerase, 3-isopropylmalate dehydrogenase, dihydrolipoamide dehydrogenase,

dihydrolipoamide S-acetyltransferase, serine hydroxymethytransferase and aldehyde

dehydrogenase are MeJA redox responsive proteins that have been listed as

thioredoxin target proteins (Table 3-2; Buchanan and Balmer, 2005).

Proteins involved in cell respiration constitute the secondary dominant group.

Nearly half of them (11 out of 23) are common components between the ABA and MeJA

treated guard cells (Table 3-1 and Table 3-2). More ATP synthase subunits or isoforms

have been identified in the MeJA data set. Not surprisingly, the novel ones in the MeJA

list, e.g., NADH-ubiquinone oxidoreductase, isocitrate dehydrogenase, pyruvate

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dehydrogenase E1 and succinyl-CoA ligase are known to be under thioredoxin

regulation (Table 3-2; Buchanan and Balmer, 2005). This is consistent with the previous

knowledge that reactions in mitochondria are highly redox regulated.

More proteins in photosynthesis have been discovered to be redox responsive to

MeJA than to ABA in guard cells. Rubisco activase contains numerous cysteines and it

has been identified to a thioredoxin target protein (Buchanan and Balmer, 2005). It has

been observed that incubation of the Rubisco activase with DTT and thioredoxin f

increased activity, whereas incubations with DTT alone or with thioredoxin m were

ineffective (Zhang et al., 1999). Ferredoxin-NADP(+)-oxidoreductase (FNR) is the last

enzyme for the step from photosystem I to NADPH in the photoelectron transport chain

(Talts et al., 2007). Two cysteines in the spinach FNR are essential for the enzyme

activity in the ferredoxin-dependent reaction (Aliverti et al., 1993). However, the redox

modification of the cysteines needs to be elucidated.

Compared to the ABA data, more proteins involved in stress and defense were

identified in the MeJA treated guard cells. Except for the overlapping ones, some unique

proteins, such as heat shock proteins, have been reported to contain redox-sensitive

cysteines in animals (Nardai et al., 2000). Other proteins, including 2-Cys peroxiredoxin,

germin-like protein, ascorbate peroxidase, manganese superoxide dismutase, heat

shock protein HSC70 and peroxiredoxin type 2 are known to be thioredoxin target

proteins (Table 3-2; Figure 3-4; Buchanan and Balmer, 2005). Since both ABA and

MeJA trigger stomatal closure involving the cytoskeleton reorganization, it is not

surprising to find apparent overlap between the two data sets in the cell structure

functional group, including actin, tubulins and extensin-like protein (Table 3-1 and Table

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3-2). Other redox responsive proteins worth noting include phospholipase D alpha 1

(PLD1), mitogen-activated protein kinase 12 (MPK12) and potassium channel protein.

PLD1, MPK12 and potassium channel are known to function in ABA signal transduction

in guard cells (Zhang et al., 2004; Li et al., 2006; Jammes et al., 2009). The

identification of these proteins as redox responsive proteins to MeJA provides new

evidence to the crosstalk hypothesis between ABA and MeJA pathways in guard cells.

Nevertheless, how these proteins are regulated in a redox dependent manner needs to

be further investigated.

Up to date, the evidence for the crosstalk hypothesis mainly comes from genetic

studies and some transcriptomic studies, which are fragmentary (Wang et al., 2011). No

proteomic analysis has been reported on the MeJA responsive protein in guard cells,

either on the abundance level or thiol-based redox changes. Here 130 proteins in total

were identified to be redox regulated under MeJA treatment in B. napus guard cells, all

of which contain at least one cysteine. The intra-molecular disulfide prediction indicated

over half (70 out of 130) can form significant disulfide bond(s) within the molecule. Due

to the fact that ABA and MeJA treatment can lead to cellular oxidative changes, the

elucidation of redox responsive proteins in the processes are extremely important to the

understanding of initial signaling stage as well as the adaptive responses in the MeJA

signaling transduction and also may provide new insight to the hormone molecular

networks.

Common Components and Mechanisms in ABA and MeJA Signaling Pathways

Based on the sequence comparison, a total of 37 proteins are shared between

ABA and MeJA treatment (labeled with asterisks in Tables 3-1 and Table 3-2; Figure 3-

5). About one third (12/37) of the proteins were identified by ICAT and two thirds (25/37)

136

by saturation DIGE. In our previous study, we employed iTRAQ to identify guard cell

ABA and MeJA responsive proteins at protein levels (Tables 2-3, Table 2-4, Table 2-6

and Table 2-7). It didn‟t reveal as many shared components as here in this study

(Tables 3-1 and Table 3-2). This result indicates not only the abundance change but

also post-translational modifications, i.e., thiol-based redox modification analyzed here,

are pivotal regulatory mechanisms for the ABA/MeJA signal transduction in guard cells.

Among the 37 shared proteins, 11 fall into the energy group. Guard cells contain

abundant mitochondria and display a high respiratory rate. This suggests that oxidative

phosphorylation is an important source of ATP to fuel the guard cell machinery for

stomatal movement, and this process is known to be redox regulated (Parvathi and

Raghavendra, 1997; Giraud et al., 2011). In the metabolism group, 8 overlapped

proteins involved in the amino acid and carbohydrate metabolism indicate the

importance of these processes in ABA/MeJA signaling. Furthermore, a few cell structure

proteins are shared between the two data sets, which implies cytoskeleton

reorganization in ABA and MeJA induced stomatal closure. Moreover, we have also

observed four shared proteins in the stress and defense group, which supports the long-

standing notion of cross-tolerance in plants (Sabehat et al., 1998; Capiati et al., 2006;

Table 3-1). Other overlapping components fall into groups of protein synthesis, folding,

transport and degradation, as well as cell division, differentiation and fate. Our

proteomic results here and those shown in Chapter 2 have greatly enhanced the depth

and scope of previous knowledge obtained from genetics and physiology aspects

(Table 1-1) and global transcriptomic analysis of hormone interactions in guard cells

(Wang et al., 2011).

137

Complementary ICAT and Saturation DIGE Approaches for Redox Proteomics

Recently, gel-based methods employing cysteine-specific fluorochromes or

radioactive tags have been developed to identify redox-sensitive proteins in complex

protein samples (Yano et al., 2001; Kim et al., 2000; Fu et al., 2008). Unlike minimal

DIGE, saturation DIGE has only two dyes (Cy3 and Cy5) available to label cysteines

and thus the experiment design is more complicated due to potential gel-to-gel variation

(Figure 3-1). This is the reason why we used one dye for the normalization standard.

Statistical analysis is very important to ensure that the spots picked for identification

exhibit reproducible significant change (Figure 3-3 G). Although saturation DIGE is

robust in identifying potentially redox-regulated proteins, the effort to locate the specific

CyDye-labeled cysteines has not been successfull (Tables 3-1 and Table 3-2) due to

the loss of the labeled dyes during the fragmentation stage. Another disadvantage of

this method is that more than one protein could be identified from one spot, therefore it

is often impossible to assign the spot volume changes to specific responsive proteins.

In contrast to DIGE results, we didn‟t identify as many redox responsive proteins

using ICAT. This is due to the lower amount of protein was used for ICAT experiments

and only cysteine-containing peptides were retained for mass spectrometry analysis,

leading to fewer peptides for protein identification. However, an advantage of ICAT is

that it enabled mapping of the redox sensitive cysteines because the ICAT tags were

retained on the cysteines during fragmentation and sequencing of the peptides (Table

3-1, Table 3-2 and Figure 3-4). The mapping of responsive cysteines provides detailed

information about the redox regulation of proteins.

In total, 27 and 54 proteins were identified to be potentially redox responsive to

ABA treatment in guard cells by ICAT and DIGE, respectively. Of these, eight proteins

138

were identified using both methods (Figure 3-5). For the MeJA treated guard cells, ICAT

and DIGE identified 18 and 118 potentially redox-responsive proteins, respectively, with

six proteins identified using both methods (Figure 3-5). Such observation indicates a

disadvantage of saturation DIGE is the incapability of locating the exact sites of cysteine

modifications. This finding is consistent with a previous report (Fu et al., 2008).

Compared with ICAT, other disadvantages of saturation DIGE include those associated

with 2D gels, i.e., little coverage of very acidic or basic proteins as well as proteins with

extreme large or small size. Overall, saturation DIGE is a good option when large-scale

screening is conducted. ICAT, on the other hand, does not have the above DIGE

limitations, and it provides detailed information of redox regulated cysteines. Therefore,

the two methods are complementary in analyzing redox responsive proteins.

Conclusion

ABA and MeJA are the most intensively studied phytohormones in guard cells.

The syntheses of both hormones are stress inducible and can promote stomatal

closure. The interaction between the ABA and MeJA signaling pathways in guard cells

have been observed. However, the molecular details are far from complete, not to

mention the regulatory mechanisms. Elevation of ROS and RNS levels is an early event

common to both signaling pathways, where these molecules serve as secondary

messengers. Although redox regulation in plants has been widely studied in the context

of photosynthesis and plastid antioxidant defense systems under stressful

environmental conditions, the interaction between other signaling

components/processes and ROS/RNS, i.e., redox status change of those proteins by

ROS/RNS, is unknown.

139

Here complementary proteomics approaches employing ICAT tags/DIGE dyes

specific for labeling cysteines were applied to investigate the thiol-based redox

regulated proteins in response to ABA and MeJA in guard cells. In total, saturation

DIGE and ICAT experiments led to identification of 73 and 130 redox responsive

proteins to ABA and MeJA, respectively. Many of the identified proteins are predicted to

form intra-molecular disulfide bonds. Additionally, a great percentage of the redox

responsive proteins have been identified to be the targets of thioredoxin, a universal

enzyme with the reducing power in cellular redox homeostasis. Functional classification

of ICAT and DIGE data sets showed very similar patterns. The findings support that

common signaling events exist between the ABA and MeJA signaling pathways in

guard cells. Proteomic analysis using iTRAQ to identify abundance change proteins in

response to ABA and MeJA didn‟t provide strong evidence to the crosstalk hypothesis.

However, the redox proteomic analysis identified 37 overlapping proteins, representing

a large portion of redox responsive proteins to each hormone. This work has revealed a

novel regulatory mechanism in the guard cell signaling networks. This work represents

the most comprehensive redox proteomics analysis of ABA and MeJA treated guard

cells and highlights several interesting nodes and edges for further investigation.

140

Table 3-1. Redox responsitive proteins identified in B. napus guard cells under ABA treatment. 4

4 Overlapping components with MeJA redox responsive proteins are highlighted with asterisks in column “Accession”. MW, molecular weight; pI,

isoelectric point; Asterisk in column “Fold Change (DIGE)”, average of spot intensity change; C U, unique spot in control gel; O and R, oxidation and reduction of cysteine, respectively.

Name MW pI Unused Score (ICAT)

Peptide (ICAT)

Fold Change (ICAT)

Mascot Score

Fold Change (DIGE)

Redox Switch

Photosynthesis (8)

* Chloroplast chlorophyll a/b binding protein 28363 5.48

127 *1.64 O

Photosystem II 44 kDa reaction center protein 52213 6.71

130 -2.81 R

Ribulose-5-phosphate kinase 45406 5.84

135 1.85 O

*Ribulose bisphosphate carboxylase large chain precursor

53436 5.88 27.81

GRPLLGCTIKPK 1.54

220 *-2.60 O/R

CYHIEPVPGEETQFIAY 1.46

VALEACVQAR 1.45

WSPELAAACEVWK 1.29

YGRPLLGCTIKPK 0.77

GHYLNATAGTCEEMMK 0.75

Ferredoxin 10367 3.82 2.03 FITPEGEQEVECDDDVYVLDAAEEAGIDLPYSCR

1.31

O

*33 kDa polypeptide of oxygen-evolving complex (OEC) in photosystem II

35142 5.55 6.62 GTGTANQCPTIDGGSETFSFKPGK 1.36

O

KFCFEPTSFTVK 1.29

*Sedoheptulose-bisphosphatase (SBPASE) 42787 6.17

208 1.75 O

*Rubisco small subunit 20183 8.23 8.55 WIPCVEFELEHGFVYR 1.38 181 -2.81 O/R

Energy (20)

ATP synthase subunit beta, mitochondrial precursor

59181 6.01

139 1.87 O

*F1-ATPase alpha subunit 46684 5.64

220 -3.46 R

ATP synthase gamma chain, chloroplast precursor

33475 6.12

112 C U R

*Fructose-bisphosphate aldolase, putative 38858 6.05

238 *-2.12/*1.97 O/R

*Malate dehydrogenase, cytosolic, putative 35890 6.11

246 *-2.33/2.02 O/R

*De-etiolated 3 (DET3), V-ATPase subunit C 42878 5.40

130 1.85 O

141

Table 3-1. Continued.

Name M.W. pI Unused Score (ICAT)

Peptide (ICAT)

Fold Change (ICAT)

Mascot Score

Fold Change (DIGE)

Redox Switch

*Glyceraldehyde-3-phosphate dehydrogenase B precursor, chloroplast

43168 5.60

220 -2.01 R

*Putative fructose bisphosphate aldolase 43033 6.48

93 C U R

*Phosphoglycerate kinase 1 (PGK1) 50195 5.91

142 *1.86/*-2.10 O/R

*Chloroplast NAD-dependent malate dehydrogenase

42623 8.48

164 1.67 O

Similar to mitochondrial malate dehydrogenase

37197 8.54

86 3.06 O

Adenosine triphosphatase 53930 5.05

130 1.87 O

Putative fructokinase 35405 5.30

123 -2.00 R

*Vacuolar ATP synthase subunit A (VHA-A) 68812 5.11 6.01 YSNSDAVVYVGCGER 11.58 368 7.45/-1.9 O/R

*Glyceraldehyde-3-phosphate dehydrogenase C subunit (GapC)

36914 6.62 8.04 SDLDIVSNASCTTNCLAPLAK 1.29

O

Transitional endoplasmic reticulum ATPase 89393 5.13 4.46 QSAPCVLFFDELDSIATQR 1.24

O

Cytosolic triosephosphatisomerase 27169 5.39 7.72 IIYGGSVNGGNCK 1.46 118 -4.03 O/R

Succinyl-CoA synthetase, alpha subunit 35317 8.84 2.07 LIGPNCPGIIKPGECK 1.31

O

*Malate dehydrogenase, mitochondrial precursor

35711 8.81 10.32 YCPHALVNMISNPVNSTVPIAAEIFK 1.35

66 -2.44 O/R GLNGVPDVVECSYVQSTITELPFFASK 0.80

Succinate dehydrogenase flavoprotein 69656 5.86 4.49 AAIGLSEHGFNTACITK 0.76 192 -1.90 R

Metabolism (13)

*Aspartate aminotransferase 44497 6.80

114 -2.01 R

Glutamine synthetase 47889 6.37

83 -2.81 R

Biotin carboxyl carrier protein 20791 4.60

74 C U R

Cinnamyl alcohol dehydrogenase 36053 8.15

56 1.75 O

*Adenosine kinase 1 (ADK1) 38268 5.29

59 C U R

Dihydrodipicolinate reductase family protein 37754 6.02

70 -2.00 R

Putative lactoylglutathione lyase 31740 5.19

58 2.01 O

*3-ketoacyl-acyl carrier protein synthase I 50890 7.99

52 3.47 O

*Reversibly glycosylated polypeptide-1 40629 5.61 7.31 NLLCPSTPFFFNTLYDPYR 1.40

O

*Glycolate oxidase 28165 9.52

84 C U R

142

Table 3-1. Continued.

Name M.W. pI Unused Score (ICAT)

Peptide (ICAT)

Fold Change (ICAT)

Mascot Score

Fold Change (DIGE)

Redox Switch

*Enoyl-[acyl-carrier-protein] reductase 40633 8.93

67 3.06 O

Threonine synthase 57777 7.11 2.38 HCGISHTGSFK 0.66

R

SVQDFCVANLKR 1.90

*Oxalic acid oxidase 21504 9.06 9.45 SVQDFCVANLK 1.87

O

AETPAGYPCIRPIHVK 1.82

Protein synthesis (5)

*Eukaryotic initiation factor 4A-2 47084 5.38

95 C U R

Hypothetical protein, containing (EF1) domain 59829 6.66

74 -1.50 R

*Initiation factor 5A-4, putative 17140 5.55 2.01 KLEDIVPSSHNCDVPHVNR 1.23

O

Mitochondrial elongation factor Tu 49410 6.25 4.06 QVGVPSLVCFLNK 1.38

O

60S ribosomal protein L2 27859 10.9 2.00 SIPEGAVVCNVEHHVGDR 0.57

R

Protein folding, transporting and degradation (5)

*Mitochondrial processing peptidase alpha subunit

54539 5.94

81 C U R

*Putative aspartic protease 28008 8.34

51 1.67 O

Putative proteasome 20S beta1 subunit 19000 7.71

110 3.09 O

Peptidylprolyl isomerase ROC4 28208 8.83 2.16 HTGPGILSMANAGPNTNGSQFFICTVK 1.24

O

Ubiquitin extension protein (UBQ5) 17797 9.83 1.52 CGLTYVYQK 0.64

R

Stress and defense (6)

*Senescence-associated cysteine protease 49581 5.49

92 2.55 O

*Low expression of osmotically responsive genes 1 (LOS2)

47974 5.54

127 1.87 O

Early response to dehydration (ERD12) 29229 9.34 2.02 NPQQLCIGDLVPFTNK 1.29

O

*Myrosinase, thioglucoside glucohydrolase 62265 6.30 48.95 QIIQDFKDYADLCFKEFGGK 1.29 330 *-2.70/2.80 O/R

Stromal ascorbate peroxidase 38532 7.12 2.80 VDTSGPHECPEEGRLPDAGPPSPANHLR

1.67

O

*Monodehydroascorbate reductase 46462 5.81 2.03 LPGFHCCVGSGGEK 0.70 115 -2.70 R

Signal transduction (4)

14-3-3 protein homolog 29361 4.83

48 2.01 O

Calmodulin-binding protein 20718 4.86

65 2.66 O

143

Table 3-1. Continued.

Name M.W. pI Unused Score (ICAT)

Peptide (ICAT)

Fold Change (ICAT)

Mascot Score

Fold Change (DIGE)

Redox Switch

Osmotic stress-activated protein kinase 41399 5.64

63 C U R

Serine/threonine phosphatases 2C (PP2C) family

40100 5.32

51 2.89 O

Transcription (1)

Retrotransposon protein, putative 92125 7.23

49 7.45 O

Cell structure (7)

*Tubulin beta-4 chain(TUB4) 50361 4.76

217 C U R

*Actin 41888 5.29

298 *2.02/-2.01 O/R

*Plastid-lipid associated protein PAP2 34689 4.79

54 2.55 O

Plastid-lipid associated protein PAP3 39278 4.55

128 1.67 O

Putative protein, containing band 7 stomatin domain

56003 5.17

75 -2.16 R

Tubulin beta-7 chain 50747 4.74 6.90 VNVYYNEASCGR 0.67

R

*Extensin-like protein 82246 6.49 2.00 IPASICQLPK 1.53

O

Cell division, differentiation and fate (3)

*GTP-binding nuclear protein RAN1 25512 6.25

76 2.01 O

Cell division protein FtsH 75232 5.37 3.12 GCLLVGPPGTGK 0.79

R

*Proliferating cell nuclear antigen (PCNA) 29375 4.61

62 C U R

Unknown(1)

Unnamed protein product 51670 6.81 2.19 LLICGGSAYPR 1.26

O

144

Table 3-2. Redox sensitive proteins identified in B. napus guard cells under MeJA treatment. 5

Name M.W. pI Unused Score (ICAT)

Peptide Fold

Change (ICAT)

Mascot Score

Fold Change (DIGE)

Redox Switch

Photosynthesis (11)

Chlorophyll a/b binding protein 28363 5.48 65 1.79 / -1.75 O/R

Light harvesting chlorophyll A/B binding protein

28659 5.29 75 1.51 O

Rubisco activase (RCA) 52347 5.87 342 *1.76/ -1.93 O/R

High chlorophyll fluorescence 136 44133 6.79 118 1.57 O

Thylakoid lumenal 15 kDa protein, chloroplast 24106 7.55 134 -2.84 R

Oxygen-evolving complex of photosystem II 28079 6.84 135 -1.78 R

Precursor of the 33 kDa subunit of the oxygen evolving complex

35226 5.92 158 1.99 O

Ribulose-1,5-bisphosphate carboxylase/oxygenase

52956 5.87 10.86

CYHIEPVPGEETQFIAY 0.66

535 * 2.10/-1.67 O/R GHYLNATAGTCEEMMKR 0.71

GHYLNATAGTCEEMMK 0.74

ELGVPIVMHDYLTGGFTANTSLAHYCR 0.42

Ribulose bisphosphate carboxylase small chain, chloroplast precursor (RuBisCO small subunit)

20183 8.23 8.09 LPLFGCTDSAQVLK 1.32 O

Ferredoxin-NADP(+)-oxidoreductase 2 41484 8.51 66 1.70 O

Sedoheptulose-1,7-bisphosphatase 42787 6.17 310 * 1.58 O

Energy (23)

ATP synthase subunit alpha, mitochondrial 55393 6.23 244 1.57 / * -1.67 O/R

Tonoplast ATPase 70 kDa subunit 69030 5.19 545 1.54 O

Gamma subunit of mitochondrial F1-ATPase 35597 9.01 83 1.81 O

Nucleotide-binding vacuolar ATPase 54819 4.98 725 1.56 / -1.66 O/R

Mitochondrial F1 ATP synthase beta subunit 63560 6.52 694 * 2.29 O

De-etiolated 3 (DET3), V-ATPase subunit C 42878 5.40 195 4.04 O

5 Overlapping components with MeJA redox responsive proteins are highlighted with asterisks in column “Accession”. MW, molecular weight; pI,

isoelectric point; Asterisk in column “Fold Change (DIGE)”, average of spot intensity change; C U, unique spot in control gel; O and R, oxidation and reduction of cysteine, respectively.

145

Table 3-2. Continued.

Name M.W. pI Unused Score (ICAT)

Peptide Fold

Change (ICAT)

Mascot Score

Fold Change (DIGE)

Redox Switch

Glyceraldehyde-3-phosphate dehydrogenase 37015 7.70 360 * 1.65 O

Glyceraldehyde 3-phosphate dehydrogenase A subunit

37937 7.00 99 1.70 O

Glyceraldehyde 3-phosphate dehydrogenase B subunit

43168 5.60 201 -1.39 R

Phosphoglycerate kinase (PGK) 42162 5.49 129 1.52 O

Phosphoglycerate kinase 1 (PGK1) 50195 5.91 282 * 1.99 / -1.78 O/R

Malate dehydrogenase, cytosolic, putative 35890 6.11 338 * 1.82 O

Chloroplast malate dehydrogenase 42520 8.51 186 1.69 O

Fructose-bisphosphate aldolase, putative 38858 6.05 551 1.51 / *-2.04 O/R

Putative fructose bisphosphate aldolase 43033 6.48 77 4.04 O

Enolase 47631 5.46 683 2.41 O

EMB1467 (embryo defective 1467); NADH dehydrogenase

82557 6.24 128 -1.63 R

NADH-ubiquinone oxidoreductase 75 kDa subunit, mitochondrial

80831 5.87 135 -1.62 R

Isocitrate dehydrogenase, putative 46059 6.13 130 * -1.97 R

Pyruvate dehydrogenase E1 beta subunit 39448 5.67 223 1.52 / -1.88 O/R

Succinyl-CoA ligase (GDP-forming) beta-chain, mitochondrial

45602 6.30 314 * 2.49 / -1.52 O/R

ATP synthase beta subunit 53717 5.20 4.00 DTLGQEINVTCEVQQLLGNNR 1.24 1158 * 1.81 O

Malate dehydrogenase, mitochondrial precursor

35711 8.81 8.04

GLNGVPDVVECSYVQSTITELPFFASK 1.24

114 -1.86 O/R AGKGSATLSMAYAGALFADACLK 1.44

YCPHALVNMISNPVNSTVPIAAEIFKK 1.22

Metabolism (40)

Adenosine kinase 1 (ADK1) 38268 5.29 149 * 2.59 / -1.88 O/R

Allene oxide cyclase 4 (AOC4) 27963 9.15 75 -1.66 R

Glutamine synthetase 38722 5.93 99 1.95 O

Thi1 protein 36755 5.82 206 1.74 O

Leucine aminopeptidase 54760 5.66 62 1.65 O

146

Table 3-2. Continued.

Name M.W. pI Unused Score (ICAT)

Peptide Fold

Change (ICAT)

Mascot Score

Fold Change (DIGE)

Redox Switch

Glycolate oxidase 40907 9.38 117 1.66 O

Cysteine synthase 41976 8.13 198 1.78 O

Unnamed protein product with CIMS domain 84728 6.05 238 -2.21 R

Putative triosephosphate isomerase 33553 7.67 200 1.99 O

Aconitate hydratase, cytoplasmic 98570 5.74 79 * -1.94 R

Cytosol aminopeptidase family protein 61667 6.62 212 -1.82 R

Cytokinin-O-glucosyltransferase 1 54361 5.59 47 -1.67 R

3-isopropylmalate dehydrogenase 44305 5.75 88 1.81 O

Dihydrolipoamide dehydrogenase 1, mitochondrial / lipoamide dehydrogenase 1

54239 6.96 141 -1.64 R

Reversibly glycosylated polypeptide-2 41377 5.76 78 -1.88 R

S-adenosyl-L-homocysteine hydrolase 53744 5.69 252 * -1.72 R

Isoflavone reductase, putative 34515 5.44 112 1.74 O

Glutamate-1-semialdehyde-2,1-aminomutase 50737 6.43 211 -2.10 R

Fumarate hydratase (FUM1) 53479 8.01 102 -1.81 R

Enoyl-[acyl-carrier-protein] reductase [NADH], chloroplastic

40625 8.78 191 1.74 O

Dihydrolipoamide S-acetyltransferase 50106 8.33 64 -1.53 R

Transketolase-like protein 81937 5.80 280 * -1.85 R

Beta-ketoacyl-ACP synthetase 1 32334 9.47 168 * -1.84 R

Oligopeptidase A-like protein 81777 5.39 63 -1.69 R

3-ketoacyl-acyl carrier protein synthase I 50890 7.99 379 * -1.69 R

9-cis-epoxycarotenoid dioxygenase 4 64534 7.65 53 -1.81 R

Delta1-pyrroline-5-carboxylate synthetase 78170 6.00 108 -2.30 R

Aldo-keto reductase, putative 36795 5.49 118 1.69 O

Serine hydroxymethytransferase 1 (SHM1); glycine hydroxymethyltransferase/ poly(U) binding

57535 8.13 198 3.03 O

147

Table 3-2. Continued.

Name M.W. pI Unused Score (ICAT)

Peptide Fold

Change (ICAT)

Mascot Score

Fold Change (DIGE)

Redox Switch

Nucleotide-rhamnose synthase/epimerase-reductase (NRS/ER)

33861 5.73 140 -1.86 R

Glucose-1-phosphate adenylyltransferase small subunit, chloroplastic

57294 5.87 222 1.53 O

3-chloroallyl aldehyde dehydrogenase/ aldehyde dehydrogenase (NAD)

54782 5.47 60 -1.64 R

Unnamed protein product, containing chalcone-flavanone isomerase domain

23362 4.91 125 -1.78 R

ADP-glucose pyrophosphorylase small subunit

57294 5.87 3.22 SCISEGAIIEDTLLMGADYYETDADR 1.66 182 1.70 O

Putative aldehyde dehydrogenase 55264 6.09 2.01 LGPALACGNTVVLK 1.53 O

Aspartate aminotransferase Asp2 44267 6.80 1.52 VGALSIVCK 0.72 R

3-isopropylmalate dehydratase-like protein (small subunit)

27208 6.44 1.53 EHAPVCLGAAGAK 1.39 O

Oxalic acid oxidase 21504 9.06 4.77 AETPAGYPCIRPIHVK 1.24 O

5-methyltetrahydropteroyltriglutamate--homocysteine S-methyltransferase

84357 6.09 4.11 CVKPPVIYGDVSRPK 1.20 O

Streptomyces cyclase/dehydrase family protein

21395 5.98 2.00 SELAQSIAEFHTYHLGPGSCSSLHAQR 0.78 90 -2.31 R

Transcription (2)

RNA helicase 51617 5.68 156 1.53 / * -1.97 O/R

KH domain-containing protein NOVA 33857 5.70 91 1.95 O

Protein synthesis (10)

40S ribosomal protein S3 27612 9.57 154 1.99 O

60S ribosomal protein L12-like 18073 9.05 128 -1.64 R

RIbosomal protein L16 21033 9.94 118 1.57 O

Ribosomal protein S1; RNA binding 45310 5.13 272 -1.98 R

Elongation factor 1-alpha 49799 9.19 199 * 1.81 O

Eukaryotic initiation factor 4A 47187 5.29 155 * -1.85 R

Arabidopsis Rab GTPase homolog E1b 51630 5.84 5.00 HYAHVDCPGHADYVK 0.74

106 1.91 O/R IVVELIVPVACEQGMR 1.33

Elongation factor Tu, chloroplastic 52177 6.21 79 1.81 O

148

Table 3-2. Continued.

Name M.W. pI Unused Score (ICAT)

Peptide Fold

Change (ICAT)

Mascot Score

Fold Change (DIGE)

Redox Switch

Eukaryotic translation initiation factor-5A 17315 5.71 210 * -1.98 R

Translation initiation factor 3, subunit g 32865 8.31 142 1.99 O

Protein folding, transporting and degradation (13)

Putative ATP-dependent Clp protease proteolytic subunit ClpP6

29534 9.38 77 -1.76 R

ClpC protease 99588 8.78 97 -1.69 R

Cyclophilin 38 (CYP38); peptidyl-prolyl cis-trans isomerase

48480 5.06 126 1.66 O

Cyclophilin 28532 8.83 116 1.67 O

Mitochondrial processing peptidase alpha subunit, putative

54539 5.94 302 * -1.84 R

Putative aspartic protease 28008 8.34 48 1.50 O

Molecular chaperone Hsp90-2 80430 4.98 145 * -1.89 R

Chaperonin 60 beta (CPN60B) 64169 6.21 185 -1.82 R

20S proteasome beta subunit; multicatalytic endopeptidase

29847 6.66 179 2.66 O

20S proteasome subunit PAE1 26102 4.70 61 -1.75 R

Proteasome 30685 4.99 243 1.87 O

ATPDIL1-3 (PDI-LIKE 1-3); thiol-disulfide exchange intermediate

64400 4.74 135 * -1.61 R

Multicatalytic endopeptidase complex, proteasome precursor, beta subunit

25151 5.31 2.07 ITQLTDNVYVCR 1.29 O

Signal transduction (3)

Phospholipase D alpha 1 (PLD1) 92236 5.52 270 * -1.77 R

Arabidopsis thaliana MAP kinase 12 (ATMPK12); MAP kinase

42904 8.05 131 1.81 O

Predicted protein, containing calcium binding motif

36689 8.61 67 * -1.90 R

Membrane and transport (3)

Potassium channel protein 36596 8.22 62 1.74 O

2-Cys peroxiredoxin 29708 5.81 210 3.28 O

P-Protein - like protein 113852 6.51 69 -1.96 R

149

Table 3-2. Continued.

Name M.W. pI Unused Score (ICAT)

Peptide Fold

Change (ICAT)

Mascot Score

Fold Change (DIGE)

Redox Switch

Unnamed protein product, containing pfam00153 (mitochondrial carrier protein) domain

32398 9.35 122 1.50 O

Stress and defense (14)

Unnamed protein product, containing cd03013 (peroxiredoxin family) domain

21623 8.97 178 -1.60 R

Monodehydroascorbate reductase 46604 5.81 410 * -2.12 R

Low expression of osmotically responsive genes 1 (LOS2)

47974 5.54 344 -1.81 R

Daikon cysteine protease RD21 32085 4.57 218 * 1.60 O

Early-responsive to dehydration 8 80299 4.95 586 * -1.61 R

Heat shock cognate protein HSC70 71129 5.08 459 * -1.92 R

Germin-like protein 22020 6.81 79 1.64 / -1.72 O/R

Ascorbate peroxidase 27726 5.73 142 2.66 O

Putative manganese superoxide dismutase 25499 8.47 83 -1.66 R

Late embryogenesis abundant family protein

36185 4.69 72 * 1.69 O

Myrosinase 62265 6.30 18.20

QIIQDFKDYADLCFK 0.71

O/R QIIQDFKDYADLCFKEFGGK 0.70

CSPMVDTKHRCYGGNSSTEPYIVAHNQLLAHATVVDLYR

1.22

Type 2 peroxiredoxin 17432 5.37 2.00 VILFGVPGAFTPTCSMK 1.27 O

Glycine-rich RNA binding protein 16351 5.56 260 * -2.68 R

Cell Structure (5)

Actin 41888 5.29 547 * -1.60 R

Plastid-lipid associated protein PAP2 34689 4.79 61 1.79 O

TUB4 (tubulin beta-4 chain) 50361 4.76 427 1.55 O

Putative tubulin alpha-2/alpha-4 chain 50089 4.91 250 * 1.56 O

Extensin-like protein 82246 6.49 2.00 IPASICQLPK 1.20 O

Cell divison, differentiation and fate (2)

Proliferating cell nuclear antigen 29375 4.61 226 * 1.75 O

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Table 3-2. Continued.

Name M.W. pI Unused Score (ICAT)

Peptide Fold

Change (ICAT)

Mascot Score

Fold Change (DIGE)

Redox Switch

Guanine nucleotide regulatory protein (RAN2)

25616 6.39 89 1.87 O

Unknown (4)

CBS domain-containing protein 22829 9.10 205 -1.60 R

Hypothetical protein 41562 8.77 55 -1.67 R

Hypothetical protein 49100 7.55 2.02 MCCLFINDLDAGAGR 1.34 O

Unknown protein 29648 9.52 2.00 LGACVDLLGGLVK 0.64 R

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Figure 3-1. Complimentary approaches of saturation DIGE and ICAT used to identify

redox sensitive proteins in response to the ABA or MeJA treatment. Control and treated guard cells were firstly alkylated to block free -SH groups that were not responsive, then the oxidized cysteines in response to the hormone treatment were reduced and labeled by Cy dyes or ICAT reagents.

SH

SH

SH

+IAMSCAM

SCAM

SCAM

+TCEP

Control

SCAM

SCAM

SCAM

SH

S

S

+IAMSCAM

S

S

+TCEP

ABA or MeJA

SCAM

SH

SH+ ICAT

heavy

Alkylation of

free –SHReduction

of S-S

Labeling of the

–SH groups

+ ICAT

light

cy3m

cy5m

SH

SH

SH

+IAMSCAM

SCAM

SCAM

+TCEP

Control

SCAM

SCAM

SCAM

SH

S

S

+IAMSCAM

S

S

+TCEP

ABA or MeJA

SCAM

SH

SH+ ICAT

heavy

Alkylation of

free –SHReduction

of S-S

Labeling of the

–SH groups

+ ICAT

light

cy3m

cy5m

152

Figure 3-2. Functional classification of redox sensitive proteins in guard cells under ABA (A) and MeJA (B) treatment. The pie charts show the distribution of the proteins into their functional classes in percentage.

153

Figure 3-3. Example of redox protein identification using DIGE approach. A) DIGE

image of control guard cell proteins; B) DIGE image of ABA treated guard cell proteins; C) A redox protein spot from control sample; D) The redox protein spot from treated sample; E) 3D view of (C); F) 3D view of (D); G) Quantitative volume changes of the spot across replicate samples. The protein spot was identified as myrosinase.

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Figure 3-4. Example of redox protein identification and cysteine mapping using ICAT

approach. A) Summary of protein identification (germin-like protein) and quantitative change; B) Peptide quantification in the control sample (light) and ABA treated sample (heavy); C) Peptide MS/MS spectrum indicating a heavy ICAT labeled cysteine residue. Control and treated guard cells were firstly alkylated to block free thiol groups of cysteines, then the oxidized cysteines in response to ABA or MeJA treatment were reduced and differentially labeled using ICAT reagents.

A

B

C

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Figure 3-5. Venn diagram of guard cell thiol proteins responsive to ABA and MeJA identified by ICAT and saturation DIGE. The circled area is proportional to the number of proteins identified for each treatment using single method. The overlapping region is labeled with the number of the same proteins identified between the two treatments. A) A total of 27 and 54 proteins were identified to be redox responsive to ABA treatment in guard cells by ICAT and DIGE, respectively. Eight proteins were identified by both methods. B) For the MeJA treated guard cells, a total of 18 and 118 were identified to be redox responsive by ICAT and DIGE, respectively. Six proteins were identified by both methods. C) A total of 12 and 25 proteins were found to be common between ABA treated and MeJA treated guard cells analyzed in ICAT and saturation DIGE experiments, respectively.

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CHAPTER 4

FUNCTIONAL CHARACTERIZATION OF A BRASSICA NAPUS SNRK2

Introduction

Reversible phosphorylation/dephosphorylation is a universal regulatory

mechanism widely found in both prokaryotic and eukaryotic organisms. Protein kinases

and phosphatase catalyze the transferring and removal of a phosphate group,

respectively (Burnett and Kennedy, 1954). Undoubtedly, this reversible modification

plays an important role in cellular processes since it often acts like an on/off switch to

activate or deactivate certain target proteins with different functions (Mundy and

Schneitz, 2002). It also facilitates the responses to ever changing environment and thus

the survival of living organisms. In plants, this regulatory mechanism in signaling

pathways have been extensively studied due to the fact that plants are sessile and

continuously subjected to different environmental stimuli and challenges. Based on the

currently available sequence information, more than 1000 genes in Arabidopsis genome

are found to encode protein kinases, indicating the broad and fundamental functions of

kinases in plant biology (Tchieu et al., 2003).

Plant protein kinases have been classified into several families. Groups such as

mitogen-activated protein kinase (MAPK), calcium-dependent protein kinase (CDPK)

and sucrose non-fermenting 1 related protein kinase (SnRK) play pivotal roles in plant

responses towards a spectrum of environmental factors. SnRK has three subfamilies,

SnRK1, 2 and 3 (Harmon, 2003). SnRK1 subfamily was firstly identified in plants closely

related to the sucrose non-fermenting 1 (SNF1) from yeast and AMP-activated protein

kinase (AMPK) from animals. The members of SnRK1 mainly participate in carbon and

nitrate metabolism in plants (Halford and Hey, 2009). In contrast, SnRK2 and SnRK3

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are unique to plants with dominant roles in stress response (Halford and Hey, 2009).

For instance, ten genes have been classified into SnRK2 subfamily in A. thaliana, nine

of which are activated upon hyperomostic stress such as drought and salinity

(Boudsocq et al., 2004).

One of the best characterized SnRK2 is the OPEN STOMATA 1 (OST1) in the

abscisic acid (ABA) signal transduction in guard cells. OST1 is a positive regulator that

forms a complex with ABA receptor and phosphatase PP2C (Lee et al., 2009). When

ABA binds to the receptor PYR/PYL/RCAR, the phosphatase PP2C is deactivated,

which in turn keeps OST1 in an active phosphorylated form. To date, the identified

substrates of OST1 include NADPH oxidase located on plasma membrane, S-type

anion channel (SLAC1), inward-rectifying potassium channel (KAT1) and transcription

factors such as ABF3 (Sirichandra et al., 2009; Geiger et al., 2009; Sato et al., 2009;

Sirichandra et al., 2010). In addition, the involvement of OST1 in jasmonate (JA),

reactive oxygen species (ROS) and CO2 signaling pathways has been recently

unraveled (Suhita et al., 2004; Vahisalu et al., 2010; Xue et al., 2011). Together with the

discovery of OST1 targets with divergent functions, all the data imply a central role of

OST1 in plant stress response and signal transduction, which is mediated by the

phosphorylation/ dephosphorylation mechanism.

Although several lines of evidence indicate that OST1 acts upstream of ROS

production, a common event in ABA and JA signal transduction in guard cells, the

question of whether OST1 is under redox regulation has been intriguing and remains

untackled. Our knowledge about redox regulation of plant kinases is scarce. It has been

reported that deactivation of PEPC-PK (phosphoenolpyruvate carboxylase protein-

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serine/threonine kinase) by oxidized glutathione (GSSG) was reversed by adding DTT

and the process could be accelerated by thioredoxin (Saze et al., 2001). However,

inhibitory effect of thioredoxin was observed with an S-locus kinase in Brassica stigma

(Cabrillac et al., 2001). Recently an osmotic stress-activated protein kinase from

tobacco (NtOSAK) has been found to form a cellular complex with glyceraldehyde 3-

phosphate dehydrogenase (GAPDH) and both proteins are regulated directly or

indirectly by nitric oxide (NO) (Wawer et al., 2010). These data indicate a complex

orchestrated regulatory mechanism underlying the connection between redox and

phosphorylation events.

In our previous experiments, a serine/threonine protein kinase BnSNRK2 was

identified to be redox responsive in ABA treated B. napus guard cells. To investigate the

function and regulation of this kinase, the gene was cloned from B. napus, expressed in

E. coli and characterized using biochemical approaches. The results demonstrate that

the BnSNRK2 activity is Mn2+-dependent and redox responsive in vitro. Hydrogen

peroxide, NO donor S-nitrosoglutathione (GSNO) and GSSG can inhibit the in vitro

kinase activity and the inhibitory effect could be reversed by DTT. The cysteines

contributing to the redox regulation have been identified. This work has revealed a novel

regulatory mechanism interconnecting phosphorylation and redox switch in plant

hormone signaling under stress conditions.

Materials and Methods

RNA Extraction, Reverse Transcription and PCR

RNA was extracted from different B. napus tissues using an RNeasy® plant mini kit

(Qiagen, USA). Briefly, liquid nitrogen frozen tissues were ground into fine powder.

Powder material of approximately 100 mg was transferred to RNase free tubes with

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RLT buffer. The lysate was transferred to a QIAshredder spin column and the flow-

through was collected. Mix the clear lysate with 0.5 volume of ethanol by pipetting, and

then load the mixture on an RNeasy spin column. The column was centrifuged multiple

times for RNA binding and washing purposes with appropriate buffers supplied in the kit.

Finally, RNA was eluted from the column in 50 µL of RNase free water. The quality and

quantity of the RNA was measured using a NanoDrop® 1000 spectrometer (Thermo

Fisher Scientific, USA). cDNA was synthesized from 1 µg of total RNA using a

SuperScript® II kit (Invitrogen, USA) in a 20 µL reaction with oligo(dT) following the

manufacturer‟s manual. The major steps include synthesis reaction at 42°C for one hour

after denaturing RNA at 70°C for 5 min, inactivation at 80°C for 5 min, and adding

nuclease free water for downstream PCR. Please refer to Table 4-1 for PCR primers in

each experiment.

Recombinant Protein Expression and Purification

The cDNA of BnSnRK2 was cloned into the pET28a expression vector (Novagen,

USA) using primers SnRK2-F1 and SnRK2-R1 (Table 4-1). To generate the cysteine (C)

mutants and serine (S)/threonine (T) mutants of BnSnRK2, the residues were

substituted by alanine (A) or aspartic acid (D) residues using a site-directed

mutagenesis kit (Stratagene, USA) with appropriate primers (Table 4-1). The fidelity of

the mutated sequences in the constructs BnSnRK2 C90A, C114A, C142A, C186A,

C90A/C114A, C142A/C186A, C114A/C142A, C114A/C186A, S158A, S158D, T159A,

T159D, S154A, S154D, S172A and S172D was confirmed by DNA sequencing. The

constructs were expressed in E. coli strain BL21 (DE3) by growing in LB medium (1%

w/v tryptone, 0.5% w/v yeast extract, 1% w/v NaCl) at 37°C to an absorbance of 0.6,

and then the expression was induced with 1 mM isopropyl-beta-D-

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thiogalactopyranoside (IPTG) at 37°C for 4 h. BnSnRK2 and mutant proteins were

purified as His-tagged proteins using a Midi PrepEase® kit (Affymetrix/USB, USA).

Purified protein was dialyzed against 25 mM Tris-HCl pH 7.5 containing 0.5 mM DTT

and a bacterial protease inhibitor cocktail (Sigma-Aldrich Co., USA) at 4°C overnight.

The protein preparations were concentrated by ultra-filtration using a 3 kD cut-off

membrane (Millipore, USA) at 4°C. Protein concentration was determined by the

Bradford protein assay (Bio-Rad Laboratories Inc., USA) with bovine serum albumin

(BSA) as a standard. The homogeneity of the purified protein was determined by SDS-

PAGE, and the identity was confirmed by LC-MS.

In vitro In-solution Kinase Assay

The reaction buffer for phosphorylation of BnSnRK2 with or without substrates

(myelin basic protein, β-casein or histone type III-S) contains 50 mM Tris-HCl pH 7.5, 10

mM MnCl2 (or other divalent ions), 2 µM cold ATP and 2 µCi [γ-32P] ATP. One

microgram BnSnRK2 was added to initiate the reaction unless otherwise stated. After

incubation at 30°C for 30 min, the reaction was stopped by adding SDS-PAGE sample

buffer and denaturing at 100°C for 5 min. Proteins were separated on 12% SDS gels.

Phosphorylated proteins were visualized by autoradiography after the gel was washed

with a buffer containing 5% trichloroacetic acid and 1% sodium pyrophosphate and

dried.

Results

The Serine/Threonine Protein Kinase Belongs to SnRK2 Subfamily

The serine/threonine protein kinase was identified in the previous proteomic

analysis of ABA treated B. napus guard cells. The sequence in the GenBank

(Accession: AAA33004) was used to design primers for cloning from B. napus var.

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Global. The sequence from our variety has one amino acid difference from its homolog

in other varieties and was submitted to the GenBank (Accession: HM563040) after

sequencing. Sequence alignment with other species suggests that the serine/threonine

kinase belongs to the SnRK2 (SNF1-related protein kinase 2) subfamily (Figure 4-1).

This kinase contains all 11 conserved kinase subdomains characteristic of Ser/Thr

kinases (Hanks et al., 1988). The stretch of aspartic acid residues present at the C

terminal classified the kinase to SnRK2b, whereas SnRK2a has dominant glutamic acid

repeat at the C terminal (Figure 4-2). Phylogenetic analysis shows the close homologs

of the BnSnRK2 include SnRK2.4 and SnRK2.10 from Arabidopsis and an osmotic

stress-activated protein kinase from tobacco (NtOSAK) (Figure 4-1). The Arabidopsis

SnRK2.4 and SnRK2.10 have been found to be activated by ionic (salt) and non-ionic

(mannitol) osmotic stress (Boudsocq et al., 2004). NtOSAK is rapidly activated within 1

min after osmotic stress and the activity maintained for about 2 h (Mikołajczyk et al.,

2000). The known functions of the BnSnRK2 homologs imply that this serine/threonine

protein kinase from B. napus may be activated by stress conditions and involved in

stress signal transduction.

Recombinant BnSnRK2 Requires Mn2+ for in vitro Autophosphorylation Activity with Multiple Phosphorylation Sites

To investigate the biochemical characteristics of the kinase, the BnSnRK2 cDNA

was cloned into pET28a vector with an IPTG inducible lac operon. After expression in E.

coli and nickel affinity purification, the protein identity was confirmed by mass

spectrometry. Autophosphorylation is one of the most important features of kinases

(Smith et al., 1993), but it is not uncommon that some recombinant kinases do not

exhibit any activities under in vitro conditions (Mustilli et al., 2002; Kelner et al., 2004).

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Here we tested three different divalent cations, Mg2+, Mn2+, and Ca2+, for in vitro

autophosphorylation of recombinant BnSnRK2. The autophosphorylation activity could

only be observed in presence of Mn2+ (Figure 4-3). The presence of any other divalent

ions did not inhibit the activity (Figure 4-3). Alkaline phosphatase treatment could

completely inhibit the autophosphorylation activity. It is interesting to note that BnSnRK2

and Arabidopsis OST1 share 84% sequence identity at amino acid level, and their

cation preference in vitro is identical (Geiger et al., 2009). The maximum BnSnRK2

activity was achieved with 5 mM of MnCl2 and maintained with 10 mM [Mn2+] (Figure 4-

4). To ensure optimal assay conditions, 10mM MnCl2 was used for all the in vitro kinase

assays.

To determine the phosphorylated amino acid residues, the autophosphorylation

reaction was conducted with non-radioactive ATP and the sample was separated on

SDS gels. Gel band containing BnSnRK2 protein was excised and digested with trypsin.

The peptides were subject to tandem MS analysis to detect phosphorylation sites. The

MS/MS data suggested serine 154 (Ser154), serine 158 (Ser158), threonine 159

(Thr159) and serine 172 (Ser172) are phosphorylated. These residues were mutated to

alanine (A) or aspartic acid (D) to test their significance to the kinase activity. Ser158

and Thr159 are located in the activation loop of the kinase (Figure 4-2). Figure 4-5

shows a slight band could be detected when the serine 158 is mutated to an alanine,

which indicates a critical role of Ser158 in the kinase autophosphorylation activity.

However, the phosphorylation activity of the S158A mutant didn‟t decrease using its

generic substrate. This implies the Ser158 does not contribute to the phosphorylation

activity of BnSnRK2. The mutant S158D, however, appeared to mimic the constitutive

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phosphorylation of the residue and the phosphorylation activity has been retained

(Figure 4-5). In contrast, the mutation of Thr159 to alanine showed no effect on the

kinase activity, demonstrating the phosphorylation of this residue is not required for the

BnSnRK2 activity. This result is consistent with the features identified of OST1 (Belin et

al., 2006). Unexpectedly, no activity was detected for the T159D mutant. The reasons

could be either phosphorylation of this residue inactivates the kinase mutant, or the

T159D mutation results in a misfolded protein when expressed in E. coli, which could

explain the very low activity. At this stage the two hypotheses cannot be discriminated.

Other residues, serine 154 and serine 172 were also tested for their roles in the

autophosphorylation and phosphorylation activities. The mutation of both residues to

alanine decreased the autophosphorylation activity, but the remaining activity suggests

other residues are phosphorylated to keep the kinase activity (Figure 4-6). Unlike the

S154D mutant, the S172D mutant didn‟t show activity comparable to wild type and the

ability to phosphorylate substrate decreased dramatically (Figure 4-6). All together, the

recombinant BnSnRK2 shows in vitro activity with multiple phosphorylation sites, e.g.,

Ser154, Ser158, Thr159 and Ser172. However, the role of each residue in the kinase

activity may be distinct.

BnSnRK2 Preferentially Phosphorylates Myelin Basic Protein and Casein in vitro

To determine the substrate specificity of the kinase, three generic substrates,

myelin basic protein (MBP), histone type III and β-casein were tested. The purchased

substrates incubated without BnSnRK2 showed no autographic signal, confirming no

introduction of phosphate groups to the proteins without BnSnRK2 (data not shown). In

the kinase assay, each reaction contains 0.2 µg recombinant BnSnRK2 and 5 µg

substrate to mimic a general enzyme/substrate ratio (Figure 4-7). Both MBP and β-

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casein showed strong phosphorylation signals but not histone type III (Figure 4-7).

Interestingly, the well-studied Arabidopsis OST1 phosphorylates histone type III in vitro

whereas the naturally purified NtOSAK phosphorylates MBP and β-casein (Kelner et al.,

2004; Belin et al., 2006). The elucidation of the BnSnRK2 substrate specificity is useful

for monitor its activities in vivo using the in-gel kinase assay, which is simple, sensitive

and specific. It may also provide hints about the in vivo phosphorylation targets when

comparing to other known stress-induced protein kinases.

In vitro BnSnRK2 Kinase Activity is Redox Regulated

Since BnSnRK2 was identified in the guard cell ABA redox proteomics (Chapter 3;

Table 3-1), it is intriguing to test whether its activity is indeed under redox regulation and

what the physiological significance is. Recombinant BnSnRK2 (approximately 1 µg) was

pretreated with 0.2 mM H2O2. After the treatment, the kinase activity was significantly

decreased (Figure 4-8). With 5 mM H2O2, the activity was completely abolished (Figure

4-8). This concentration range has been used by other groups in testing protein redox

regulation (Cabrillac et al., 2001; He et al., 2009; Lindermayr et al., 2010). However, the

natural H2O2 concentration in plants is extremely low (10-14 M), thus whether the redox

response occurs in vivo remains to be investigated (Keppler et al., 1989). Reactive

nitrogen species (RNS) also serve as second messengers in guard cell signal

transduction (Li et al., 2006; Saito et al., 2009). The effect of two NO donors were

tested, i.e., sodium nitroprusside (SNP) and S-nitrosoglutathione (GSNO). SNP inhibits

the activity of BnSnRK2 in a dose-independent manner (Figure 4-8). The underlying

mechanism is not clear. However, SNP was not preferred as a nitric oxide donor in

biological experiments due to its side effect in the presence of ferrous ion (Fe2+).

Therefore, another NO donor, S-nitrosoglutathione (GSNO) was tested. GSNO is a

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general physiological transport and storage form of NO in plants and animals (Zhang

and Hogg, 2004). In contrast to SNP, GSNO inhibits the BnSnRK2 activity in a dose-

dependent manner (Figure 4-8). One millimolar GSNO has obvious inhibitory effect

based on the autoradiographic signal (Figure 4-8). The activity of 5 mM GSNO treated

BnSnRK2 was not detectable and a shift of the gel band was observed (Figure 4-8),

which indicates the loss of activity might be resulted from certain modification, e.g., S-

nitrosylation. Another oxidant, GSSG has a similar inhibitory effect on the kinase activity

as H2O2. With the increase of GSSG concentration, the activity of the kinase decreases

dramatically, with no detection at 5 mM (Figure 4-8). Overall, ROS and RNS have

inhibitory effect on the activity of BnSnRK2 in vitro, suggesting the kinase activity is

sensitive to the oxidation state.

The other direction, i.e., whether the reducing reagents or enzymes could reverse

the inhibition caused by the oxidants is very important and of our great interest to

understand the regulatory mechanism. The most commonly used reducing reagent,

DTT was firstly employed to test whether the redox response is reversible. At

concentration of 10 mM, DTT can rescue the kinase activity which was inhibited by

H2O2, GSNO and GSSG (Figure 4-9). Additionally, enzyme with reducing capability was

also tested. Active recombinant thioredoxin isoforms f, h, and m from B. napus var.

Global were added to the pretreated kinase sample and then the activity was assayed.

The inhibition casued by H2O2 could be reversed by thioredoxin h, which is an isoform

from cytosol while the isoforms from from chloroplast, f and m were inefficient (Figure 4-

10). All three isofoms could partially reverse the inhibitory effect from GSNO at low

concentration (Figure 4-10). In animal, thioredoxin is known to catalyze either

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transnitrosylation or denitrosylation of specific proteins, depending on the redox status

of the cysteines within its conserved oxidoreductase CXXC motif (Wu et al., 2011). On

the contrary, none of the thioredoxin isoforms was able to recover the GSSG treated

kinase activity (Figure 4-11). This is consistent with that thioredoxins have generally

been thought to be relatively inefficient in deglutathionylation in many plant and

mammalian species (Greetham et al., 2010). All these evidence demonstates the

divergent and reversible responses of the in vitro BnSnRK2 kinase activity to the redox

status.

To address the question that whether the kinase activity is correlated to the redox

homeostasis, the activity of the kinase samples with different redox states was

analyzed. After treatment by GSSG or H2O2 (5 mM) at room temperature for 15 min,

reducing reagent DTT was added to each sample at different final concentrations,

incubated for another 15 min, and then the activity was assayed. Figure 4-12 shows the

protein level didn‟t exhibit obvious changes for the GSSG pretreated kinase; however,

the kinase activity is greatly enhanced when the kinase is reduced. Thus the in vitro

kinase activity is dynamically responding to the redox state change in a reversible

manner. The observation of the H2O2 pretreated kinase was different. At lower

concentrations of DTT, the kinase at the monomer size (~42 kD) was barely observed

but with visible bands of larger molecular weight on the gel (Figure 4-10). Thus the loss

of activity caused by H2O2 treatment is partially due to the decreased protein level since

the kinase might be cross-linked to other E. coli protein or forming polymers. Not

surprisingly, high concentration of DTT recovered the inhibitory effect on the kinase

activity from H2O2 treatment (Figure 4-13). Considering the different modications from

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the two oxidants, i.e., inter-molecular disulfide bonds by H2O2 treatment and S-

glutathionylation by GSSG treatment, the involvement of cysteine(s) in the redox

response can be reasonably exoected.

Cysteines of BnSnRK2 Contribute to the Redox Regulation

The thiol containing amino acid cysteine plays a very important role in the redox

regulation (Depuydt et al., 2011). The BnSnRK2 protein sequence has six cysteines,

Cys90, Cys114, Cys120, Cys142, Cys186 and Cys233. Based on the intracellular

disulfide prediction (http://clavius.bc.edu/~clotelab/DiANNA/), Cys90, Cys114, Cys142

and Cys186 are potentially involved disulfide formation. Among these residues, Cys142

is located right before the activation loop of the kinase (Figure 4-2). The crystal structure

of a human 5‟-AMP activated kinase sharing 40% identity with BnSnRK2 suggested

Cys142 is spatially close to the ATP binding motif (PDB ID: 2H6D; Littler et al., 2010).

Therefore, kinase activity was tested with BnSnRK2 mutant C142A exposed to H2O2

and GSNO. The mutant did show the kinase activity, although not as potent as the wild

type (Figure 4-14). After treated with 5 mM H2O2, the activity of the mutant was partially

maintained rather than being inhibited (Figures 4-8 and 4-14). No obvious differences

between untreated and GSNO treated BnSnRK2 C142A mutant activity could be

observed (Figure 4-14). These results suggest the contribution of cysteine 142 to the

redox response of BnSnRK2. The involvement of other cysteines in the redox response

and the modification of the redox-responsive cysteines, e.g., disulfide bond, sulfonic

acid and S-nitrosylation etc., deserve further investigation.

Conclusions and Future Work

From the inventory of redox responsive proteins identified in hormone treated

guard cells, a serine/threonine protein kinase BnSnRK2 with potential function in stress

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response was selected for detailed biochemical and functional characterization. Cation

preference and substrate preference are important features of kinases. Recombinant

BnSnRK2 exhibits autophosphorylation activity with a divalent cation preference of

manganese. No activity was detected with presence of magnesium or calcium. Such

cation preference is also seen in other plant kinase, such as the OPEN STOMATA 1

(OST1) in the guard cell ABA signaling pathway (Geiger et al., 2009). However, the

concentration of Mn2+ at millimolar range may not reflect the cellular physiological level.

Plants contain 15-150 ppm free Mn2+ but in some species it can go up to 1000 ppm

(Mukhopadhyay and Sharma, 1991). Considering the natural abundance of kinase is

usually low, the in vitro autoradiography results may not reflect the activity in vivo

because of the high concentrations of both kinase and manganese in the reaction tube.

Similar to the osmotic stress-activated protein kinase from tobacco (NtOSAK),

BnSnRK2 preferentially phosphorylates myelin basic protein and β-casein. Mass

spectrometry analysis revealed multiple phosphorylation sites of BnSnRK2. The

contribution of each serine or threonine to the kinase activity was investigated. The data

suggested that serine 158 located in the activation loop is critical for the kinase activity

but not the threonine 159. Serine 154 and serine 172 both are phosphorylated and

contribute to the kinase activity. All these results laid a foundation for further in vitro and

in vivo studies of BnSnRK2 functions.

A few kinases in animal have been known to be redox regulated. For example,

Janus kinase activity is nitric oxide and thiol redox regulated (Duhé et al., 1998).

However, redox regulated kinase has been rarely reported in plants. An S-locus

receptor kinase from B. oleracea was found to be inhibited by thioredoxin, a class of

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small redox proteins with reducing capability (Cabrillac et al., 2001). In contrast,

thioredoxin-mediated reductive activation of a protein kinase for the regulatory

phosphorylation of C4-form phosphoenolpyruvate carboxylase from maize has been

reported and the activity was inhibited by oxidized glutathione (Saze et al., 2001). These

two may represent the only cases of redox-regulated protein kinases in plants. The work

presented here is the first time that a redox-regulated kinase in guard cell hormone

signaling has ever been studied. The activity of recombinant BnSnRK2 is sensitive to

oxidant treatment, such as hydrogen peroxide and reactive nitrogen species. One of the

cysteines has been shown to contribute to the redox response of the kinase. Whether

other cysteines contribute and what type of modification on the cysteine will be further

investigated. These results suggest a novel regulatory mechanism in guard cell

signaling, i.e., redox regulation of kinase activity.

Since the SnRK2 and SnRK3 subfamilies are mainly involved in plant stress

response (Harmon, 2003; Halford and Hey, 2009). BnSnRK2 may also participate in the

B. napus response to external environmental stimuli, e.g., drought or osmotic stresses.

This hypothesis need to be further tested in vivo. First of all, the expression profiling will

be studied using promoter GUS and qRT-PCR. The cellular and tissue specificities may

provide hints on the function of BnSnRK2. Meanwhile, an antibody against BnSnRK2

has been developed. In-gel kinase assay will be used to investigate the activators of the

natural kinase activity, including drought, salt and mannitol etc. In addition, the

transgenic plants of over-expression and RNA interference (RNAi) are being generated.

The phosphoproteomics as a robust and high-throughput tool will be applied to identify

the upstream kinase and downstream phosphorylation targets of BnSnRK2.

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The BnSnRK2 was originally isolated from guard cells under ABA treatment. This

brings up the question that whether BnSnRK2 functions as the OST1 in Arabidopsis

although the two kinases only share 84% sequence identity. In the ABA signaling

pathway in guard cells, OST1 is known to act upstream of ROS production (Mustilli et

al., 2002). Based on current results, the feedback regulation of BnSnRK2/OST1 activity

can be hypothesized. Our in vitro data support a novel link between the phosphorylation

events and the redox regulation in guard cell signal transduction. Future in vivo

characterization of BnSnRK2 will provide insights to how this kinase regulate B. napus

responses to stress conditions.

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Table 4-1. Primers used in this study.

Primer Sequence Note

BnSnRK2 F-1 CGGATCCATGGAGAAGTACGAGCTGG E.coli expression forward

BnSnRK2 R-1 CAAGCTTTCACACTTCTCCACTTGCG E.coli expression reverse

SRK2E C142 F CCTGCTCCACGTCTCAAAATCGCAGATTTTGGTTATTCCAAGTCC Cys142Ala forward

SRK2E C142 R GGACTTGGAATAACCAAAATCTGCGATTTTGAGACGTGGAGCAGG Cys142Ala reverse

SRK2E C186 F CAAGATGGCTGATGTATGGTCTGCAGGTGTAACTCTTTATGTCATG Cys186Ala forward

SRK2E C186 R CATGACATAAAGAGTTACACCTGCAGACCATACATCAGCCATCTTG Cys186Ala reverse

SnRK2 C90F GTGAATTATTCGAGCGTATAGCAAGTGCTGGAAGATTCAG Cys90Ala forward

SnRK2 C90R CTGAATCTTCCAGCACTTGCTATACGCTCGAATAATTCAC Cys90Ala reverse

SnRK2 C114F CTTATATCAGGTGTTAGCTATGCACATGCTATGCAAATATGC Cys114Ala forward

SnRK2 C114R GCATATTTGCATAGCATGTGCATAGCTAACACCTGATATAAG Cys114Ala reverse

SnRK2-S158A-F CTACTGCACTCGAGGCCCAAAGCAACAGTTGGAACTCCAGC Ser158Ala forward

SnRK2-S158A-R GCTGGAGTTCCAACTGTTGCTTTGGGCCTCGAGTGCAGTAG

Ser158Ala reverse

SnRK2-S158E-F CTACTGCACTCGAGGCCCAAAGATACAGTTGGAACTCCAGC Ser158Asp forward

SnRK2-S158E-R GCTGGAGTTCCAACTGTATCTTTGGGCCTCGAGTGCAGTAG

Ser158Asp reverse

SnRK2-T159A-F CTGCACTCGAGGCCCAAATCCGCAGTTGGAACTCCAGCATA Thr159Ala forward

SnRK2-T159A-R TATGCTGGAGTTCCAACTGCGGATTTGGGCCTCGAGTGCAG Thr159Ala reverse

SnRK2-T159E-F CTGCACTCGAGGCCCAAATCCGATGTTGGAACTCCAGCATA Thr159Asp forward

172

Table 4-1. Continued.

Primer Sequence Note

SnRK2-T159E-R

TATGCTGGAGTTCCAACATCGGATTTGGGCCTCGAGTGCAG Thr159Asp reverse

SnRK2-S172A-F CATATATTGCACCTGAGGTCCTTGCACGGAGAGAGTATGATG Ser172Ala forward

SnRK2-S172A-R CATCATACTCTCTCCGTGCAAGGACCTCAGGTGCAATATATG Ser172Ala reverse

SnRK2-S172E-F CATATATTGCACCTGAGGTCCTTGATCGGAGAGAGTATGATG Ser172Asp forward

SnRK2-S172E-R CATCATACTCTCTCCGATCAAGGACCTCAGGTGCAATATATG

Ser172Asp reverse

SnRK2-S154A-F CAAGTCCTCTCTACTGCACGCAAGGCCCAAATCCACAGTTG Ser154Ala forward

SnRK2-S154A-R CAACTGTGGATTTGGGCCTTGCGTGCAGTAGAGAGGACTTG Ser154Ala reverse

SnRK2-S154E-F CAAGTCCTCTCTACTGCACGATAGGCCCAAATCCACAGTTG Ser154Asp forward

SnRK2-S154E-R

CAACTGTGGATTTGGGCCTATCGTGCAGTAGAGAGGACTTG Ser154Asp reverse

BnEF-1a-F

CCAGATCAACGAGCCAAAG

qRT-PCR control

BnEF-1a-R

GCGAATGTCACAACCATACC

qRT-PCR control

qRT-SnRK2-FWD2

GCTCCACGTCTCAAAATCTG qRT-PCR BnSnRK2

qRT-SnRK2-RVS2 CCATACATCAGCCATCTTGC qRT-PCR BnSnRK2

173

Figure 4-1. Phylogenetic tree of BnSnRK2 and related kinases in green plants.

References for the sequences of the listed kinases are as follows: ZmSAPK6-serine/threonine-protein kinase SAPK6 from Zea mays (GI: 195623946); Os04g0432000-Os04g0432000 from Oryza sativa (GI: 115458454); FsPK-serine/threonine-protein kinase from Fagus sylvatica (GI: 38228677); GmPK3-protein kinase 3 from Glycine max (GI: 310582); AtSnRK2.10-serine/threonine protein kinase SRK2B from Arabidopsis thaliana (GI: 334182444); AtSnRK2.4- serine/threonine protein kinase SRK2A from A. thaliana (GI: 1168529); Al888390-hypothetical protein ARALYDRAFT_888390 from A. lyrata (GI:297849460); CsPK- serine/threonine protein kinase from Camellia sinensis (GI: 110665974); Vv028464-hypothetical protein VITISV_028464 from Vitis vinifera (GI: 147864363); MtSK-stress kinas from Medicago truncatula (GI: 55140609); PtPP-predicted protein from Populus trichocarpa (GI: 224122666); RcASK1-serine/threonine-protein kinase ASK1 from Ricinus communis (GI: 255579673); NtOSAK-osmotic stress-activated protein kinase from Nicotiana tabacum (GI: 19568098).

174

Figure 4-2. Comparison of the amino acid sequence of BnSnRK2 with sequences of other protein kinases. The ATP binding motif, T-loop and the C terminal stretch of aspartic acid residues are highlighted in red, green and purple, respectively. AtSnRK2.4 and AtSnRK2.10 are two members of A. thaliana SnRK2 family (AT1G10940 and AT1G60940). MtSK is a stress responsive kinase from M. truncatula. NtOSAK is an osmotic stress-activated kinase from tobacco (Kelner et al., 2004).

175

Figure 4-3. Effect of cation on SnRK2 autophosphorylation and phosphorylation

activities. Upper panel: autoradiograph of SnRK2 phosphorylation in vitro. Lower panel: Coomassie blue stained gel as loading control. Lane 1: protein molecular marker. The band in lower panel indicates 37kDa. Lane 2: elution sample from pET28a transformed BL21 as negative control. Lane 3: SnRK2 in the reaction buffer containing 10mM MnCl2. Lane 4: SnRK2 and alkaline phosphatase (CIP) in the Mn2+ buffer. Lane 5: SnRK2 and generic substrate histone III (HIS) in the Mn2+ buffer. Lane 6: SnRK2 in reaction buffer containing 10mM MgCl2. Lane 7: SnRK2 in reaction buffer containing 10mM CaCl2. Lane 8: SnRK2 in reaction buffer containing 10mM MnCl2 and 10mM MgCl2. Lane 9: SnRK2 in reaction buffer containing 10mM MnCl2 and 10mM CaCl2. Lane 10: SnRK2 in reaction buffer containing 10mM MgCl2 and 10mM CaCl2.

176

Figure 4-4. Optimization of Mn2+ concentrations in SnRK activity assay. Upper panel: autoradiograph of SnRK2 phosphorylation in vitro. Lower panel: Coomassie blue stained gel as loading control. Phosphorylation buffer contains 50 mM Tris-HCl pH 7.5, different concentrations of MnCl2 as indicated, 2 μM cold ATP and 2 μCi [γ-32P] ATP.

177

Figure 4-5. Phosphorylation of Ser158 is required for BnSnRK2 kinase activity. Upper panel: autoradiograph of SnRK2 and substrate phosphorylation in vitro. Lower panel: Coomassie blue stained gel as loading control. Phosphorylation buffer contains 50 mM Tris-HCl pH 7.5, 10 mM MnCl2, 2 μM cold ATP and 2 μCi [γ-32P] ATP.

178

Figure 4-6. Ser154 and Ser172 are phosphorylated to maintain the BnSnRK2 activity. Upper panel: autoradiograph of SnRK2 and substrate phosphorylation in vitro. Lower panel: Coomassie blue stained gel as loading control. Phosphorylation buffer contains 50 mM Tris-HCl pH 7.5, 10 mM MnCl2, 2 μM cold ATP and 2 μCi [γ-32P] ATP.

179

Figure 4-7. SnRK2 specifically phosphorylates myelin basic protein (MBP) and β-casein in vitro. Left panel: Coomassie blue stained gel as loading control. Right panel: autoradiograph of SnRK2 with different substrates after phosphorylation reaction in vitro. Phosphorylation buffer contains 50 mM Tris-HCl pH 7.5, 10 mM MnCl2, 10 mM MgCl2, 2 μM cold ATP and 2 μCi [γ-32P] ATP. The protein molecular marker is as indicated. Lanes from left to right are 1): eluted SnRK2 sample dialyzed against 25 mM Tris-HCl pH 7.5 and 0.5 mM DTT overnight; 2): SnRK2 sample with myelin basic protein (MBP); 3): SnRK2 with histone type III (HIS III); 4): SnRK2 with β-casein.

180

Figure 4-8. Effects of H2O2, S-nitrosoglutathione (GSNO), and oxidized glutathione (GSSG) on the autophosphorylation activity of BnSnRK2 in vitro. Another type of nitric oxide donor sodium nitroprusside (SNP) inhibits the activity in a dose-independent manner. Protein samples were treated with for 10 min at room temperature. Kinase activity assay was carried out at 30 °C for 30 min. Reaction buffer contains 50mM Tris-HCl pH 7.5, 10 mM MnCl2, 2 μM ATP and 2 μCi [γ-32P] ATP. SDS-PAGE running buffer without DTT was added to stop reaction then mixtures were loaded onto the gel.

181

Figure 4-9. Effect of DTT on the autophosphorylation activity of SnRK2 treated with H2O2, GSNO (S-nitrosoglutathione), and GSSG (oxidized glutathione). Upper panel: autoradiograph of the kinase phosphorylation in vitro. Lower panel: Coomassie blue stained gel as loading control. Protein samples were treated for 15 min for each step at room temperature. Kinase activity assay was carried out at 30 °C for 30 min. Reaction buffer contains 50 mM Tris-HCl pH 7.5, 10 mM MnCl2, 2 μM ATP and 2 μCi [γ-32P] ATP.

182

Figure 4-10. Effect of thioredoxin on the autophosphorylation activity of SnRK2 treated with GSNO and H2O2. Upper panel: autoradiograph of the kinase phosphorylation in vitro. Lower panel: Coomassie blue stained gel as loading control. Protein samples were treated for 15 min for each step at room temperature. Kinase activity assay was carried out at 30 °C for 30 min. Reaction buffer contains 50 mM Tris-HCl pH 7.5, 10 mM MnCl2, 2 μM ATP and 2 μCi [γ-32P] ATP.

183

Figure 4-11. Effect of thoredoxin f, h and m on the autophosphorylation activity of SnRK2 treated with GSSG. Upper panel: autoradiograph of the kinase phosphorylation in vitro. Lower panel: Coomassie blue stained gel as loading control. Protein samples were treated for 15 min for each step at room temperature. Kinase activity assay was carried out at 30 °C for 30 min. Reaction buffer contains 50 mM Tris-HCl pH 7.5, 10 mM MnCl2, 2 μM ATP and 2 μCi [γ-32P] ATP.

184

Figure 4-12. Redox titration of autophosphorylation activity of SnRK2 with DTT. Upper panel: autoradiograph of the kinase phosphorylation in vitro. Lower panel: Coomassie blue stained gel as loading control. Protein samples were treated for 15 min at room temperature for each step. Kinase activity assay was carried out at 30 °C for 30 min. Reaction buffer contains 50mM Tris-HCl pH 7.5, 10 mM MnCl2, 2 μM ATP and 2 μCi [γ-32P] ATP. SDS-PAGE running buffer without DTT was added to stop reaction then mixtures were loaded onto the gel.

185

Figure 4-13. The autophosphorylation activity of SnRK2 is sensitive to the redox status. Upper panel: autoradiograph of the kinase phosphorylation in vitro. Lower panel: Coomassie blue stained gel as loading control. Protein samples were treated for 15 min at room temperature for each step. Kinase activity assay was carried out at 30 °C for 30 min. Reaction buffer contains 50 mM Tris-HCl pH 7.5, 10 mM MnCl2, 2 μM ATP and 2 μCi [γ-32P] ATP. SDS-PAGE running buffer without DTT was added to stop reaction then mixtures were loaded onto the gel.

186

Figure 4-14. Effect of oxidants on autophosphorylation activity of BnSnRK2 C142A mutant. Upper panel: autoradiograph of the kinase phosphorylation in vitro. Lower panel: Coomassie blue stained gel as loading control. Protein samples were treated for 15 min at room temperature. Kinase activity assay was carried out at 30 °C for 30 min. Reaction buffer contains 50 mM Tris-HCl pH 7.5, 10 mM MnCl2, 2 μM ATP and 2 μCi [γ-32P] ATP.

187

CHAPTER 5

SUMMARY AND PERSPECTIVES

Stomata have been recognized as the first line of plants to sense, respond and

adapt to the external environmental changes. Stomatal movement controls the rate of

carbon dioxide intake and water evaporation, as well as pathogen invasion. Thus

stomatal function is extremely important to the plants‟ survival and fitness considering

their sessile nature. The main function of stomatal guard cells is to perceive, integrate

and transduce the external signals. Thus changes in ion/solute influx and efflux of the

guard cells directly regulate the stomatal movement. In contrast to guard cells,

mesophyll cells constitute the major part of the leaf organ with a predominant function of

photosynthesis. Here isotope tagging technology iTRAQ was employed to profile the

Brassica napus guard cell proteome and identify proteins preferentially expressed in

both the guard cell and mesophyll cell. Overall 1458 non-redundant proteins were

identified with 74 proteins highly expressed in guard cells. The majority of these proteins

fall into the functional groups of energy (respiration), signaling, transport, and

transcription. In addition, four proteins involved in nucleosome and three involved in cell

structure were highly expressed in guard cells. On the contrary, in mesophyll cells over

half of the proteins are involved in photosynthesis followed by 23 proteins involved in

metabolism and 17 disease/defense/stress proteins. Our comparative proteomics of the

guard cells and mesophyll cells provides molecular evidence to the functional

differentiation between the two types of cells.

Stomatal closure, as a fast response to environmental stimuli, can be induced by a

spectrum of factors, such as water deficiency, ozone and UV light, flooding and

pathogen invasion. Phytohormones, including abscisic acid (ABA) and jasmonate (JA)

188

are small molecules associated with stress conditions and can also trigger stomatal

closure in some species, including V. faba, A. thaliana and B. napus. Hormone signal

transduction in guard cells has been studied for decades. Only until very recently, the

initial stages of the ABA signaling pathway in guard cells have been elucidated,

including the receptors belonging to the START/Bet v I superfamily, protein

phosphatase 2C as a negative regulator and a kinase OPEN STOMATA 1 (OST1) as

positive regulator composing a double negative regulatory module (Figure 1-2). A few

signaling events in ABA signal transduction in guard cells were found to be involved in

the MeJA signal transduction, e.g., ROS and NO production, cytosolic alkalinization and

cytosolic Ca2+ elevation. Thus, a hormone crosstalk hypothesis was proposed

(Munemasa et al., 2007). The same technology iTRAQ was applied to investigate the

responsive proteins in B. napus guard cells to ABA and MeJA. Each study has

established an inventory of potential components in the hormone signaling pathway.

However, there are only very limited number of proteins shared between the two data

sets. This indicates the crosstalk may occur mostly at post-translational level rather than

the expression (abundance) level.

ROS production was observed in B. napus epidermal peels when treated with ABA

and MeJA, which might change the redox status of the cellular environment. To profile

redox responsive proteins under such treatments, two complementary redox proteomics

approaches were employed, i.e., ICAT and saturation DIGE, which tags or labels

cysteines specifically. Under ABA and MeJA treatment, 73 and 130 proteins were

identified to be redox responsive, respectively. Very interestingly, a large portion of

proteins (37) are shared between the two data sets. Redox regulation of these identified

189

proteins needs to be validated in vitro and in vivo and deserves further investigation.

These results not only provide molecular details to the crosstalk hypothesis between the

ABA and MeJA signaling pathways in guard cells, but also set a stage to explore the

function of each signaling node.

Another universal post-translational modification is phosphorylation/dephosphory

-lation, which also plays an important role in the guard cell physiology. For example, the

kinase OST1 phosphorylates different targets, including NADPH oxidase, potassium

channel, slow anion channel, and transcription factors. Based on the results from the

proteomic analysis of the hormone treated guard cells, a serine/threonine protein kinase

(BnSnRK2) was cloned and heterogeneously expressed. Recombinant BnSnRK2

exhibits autophosphorylation activity in vitro in a Mn2+-dependent manner with preferred

generic substrates myelin basic protein and casein. Hydrogen peroxide, nitric oxide

donor GSNO and oxidized glutathione (GSSG) have inhibitory effects on the in vitro

BnSnRK2 activity. Furthermore, the inhibitory effect by these oxidants could be

reversed and the activity was even enhanced by DTT. Thioredoxin isoform h also shows

the recovery effect on the kinase activity after H2O2 treatment. However, three types of

thioredoxin f, h, and m could only partially reverse the inhibition on activity caused by S-

nitrosylation and show inefficiency to rescue the loss of activity caused by S-

glutathionylation. Mutation of one cysteine (Cys142) resulted in the impairment of

BnSnRK2 ability to respond to the oxidants. All these in vitro data suggest redox

regulation of phosphorylation process in guard cell signal transduction, which set up a

novel link between these two regulatory mechanisms. Detailed functional

characterization is under way, including the expression profiling, BnSnRK2 activity in

190

vivo, as well as the upstream activating kinase and downstream phosphorylation

targets.

Up to date, most of the knowledge about the hormone signal transduction and

interaction is obtained from the model plant Arabidopsis thaliana, of which the economic

value is very limited. In addition, knowledge from the model plant may not be directly

transferable to crop plants. Brassica napus is one of the most important oilseed crops

around the world. Using the highly purified guard cells from B. napus, direct evidence is

collected to improve the understanding of the stomatal function in this economic crop.

Once the regulatory mechanisms are elucidated, the knowledge can be applied to

potentail rational engineering for better yield and enhanced stress tolerance.

191

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BIOGRAPHICAL SKETCH

Mengmeng Zhu was born in April, 1982 in Anhui Province, China. She was

admitted to Xi‟an Jiaotong University in Shaanxi Province, China for undergrad study,

majoring in bioengineering. Upon graduation in July 2004, she was recruited into the

master program of molecular biology and biochemistry in Xi‟an Jiaotong University.

From July 2005 to August 2006, Mengmeng Zhu did her thesis research in Dr. De Ye‟s

laboratory at the State Key Laboratory of Plant Physiology and Biochemistry, China

Agriculture University. Her research focus was on the characterization of a kinase in the

polar growth of pollen tubes during the male gametophyte development. Upon her

completion of the master study in China, Mengmeng Zhu entered the Ph.D. program of

botany in the Biology Department of University of Florida at Gainesville, Florida in July

2007. She has been under the supervision of Dr. Sixue Chen and working on guard cell

proteomics and hormone signaling. Mengmeng Zhu received her Ph.D. degree in

December 2011. She would like to further develop her career in plant biology related

areas.