University of Florida Thesis Or Dissertation Formatting

GUARD CELL MOLECULAR RESPONSES TO ELEVATED AND LOW CO2 REVEALED BY METABOLOMICS AND PROTEOMICS

SISI GENG

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

2016

To my beloved mother, father and husband In memory of my beloved grandfather

ACKNOWLEDGMENTS

My special thanks goes to my graduate committee: Dr. Sixue Chen, Dr. Kevin

Folta, Dr. Julie Maupin-Furlow, and Dr. Harry Klee. Their expertise and achievement inspired and urged me throughout my Ph.D. research. Dr. Sixue Chen, as my supervisor and committee chair was a great role model as a scientist and helped me both in my research project and living.

Dr. Bing Yu from Heilongjiang University (a visiting scholar in the Chen lab), Dr.

Evaldo de Armas and Dr. Craig Dufresne from Thermo Fisher Scientific, Dr. David

Huhman and Dr. Lloyd W. Sumner from Samuel Roberts Noble Foundation, Dr. Hans T.

Alborn from United States Department of Agriculture, Dr. Sarah M. Assmann and Dr.

Mengmeng Zhu from Pennsylvania State University, and Dr. Zhonglin Mou from

Microbiology and Cell Science Department are acknowledged for their help and collaboration in this project. Technical support was provided by the Proteomics and

Mass Spectrometry Core at the Interdisciplinary Center for Biotechnology Research,

University of Florida.

I am also grateful to people who have helped me during my PhD research, especially Dr. Biswapriya Misra, Ning Zhu, Dr. Cecilia Silva-Sanchez, other Chen lab members and all of my friends. My parents, Biao Geng and Wei Zhou, and my husband

Dr. Hongbing Liu are specially thanked for their encouragement and emotional support.

My study here is funded by China Scholarship Council (CSC), Plant Molecular

and Cellular (PMCB) graduate program, and partly by the U.S. National Science

Foundation grants NSF-0818051 and NSF-1158000 (to S. Chen).

TABLE OF CONTENTS

page

ACKNOWLEDGMENTS ...... 4

LIST OF TABLES ...... 7

LIST OF FIGURES ...... 8

LIST OF ABBREVIATIONS ...... 10

ABSTRACT ...... 13

CHAPTER

1 INTRODUCTION ...... 15

Guard cell CO2 Response ...... 15 Short Term Effects of CO2 on Guard Cell Signaling ...... 15 Long Term Effects of CO2 on Plant Physiology ...... 19 CO2 Effects on Guard Cell Development ...... 22 Guard Cell Metabolism ...... 23 Guard Cell Metabolism in General ...... 23 Osmoregulation ...... 26 ROS Homeostasis ...... 27 Signaling Molecules ...... 28

2 JASMONATE-MEDIATED STOMATAL CLOSURE UNDER ELEVATED CO2 REVEALED BY TIME-RESOLVED METABOLOMICS ...... 34

Introduction ...... 34 Materials and Methods...... 37 Plant Materials ...... 37 Preparation of Epidermal Peels for Stomatal Movement and ROS Assays ...... 37 Stomatal ROS Measurement ...... 38 Large Scale Preparation of Stomata for Metabolomics ...... 38 Metabolite Extraction ...... 39 Metabolite Profiling Using Hyphenated Metabolomics Platforms ...... 40 Metabolomics Data Processing and Statistical Analysis ...... 42 Metabolic Pathway Mapping and Enrichment Analyses ...... 43 Results ...... 43 Elevated CO2 Induced Stomatal Closure and ROS Production ...... 43 Overview of Temporal Changes in Guard Cell Metabolome under Elevated CO2 ...... 44 Specific Metabolite Changes in Response to Elevated CO2 ...... 46 Functional Characterization of JA-Mediated CO2 Induced Stomatal Closure ... 48

Discussion ...... 49 Changes in Primary Metabolites and Osmolytes in The Course of Stomatal Closure under Elevated CO2 ...... 49 The Roles of ROS and Flavonoids in CO2-Induced Stomatal Closure ...... 52 Lipids Are Involved in Elevated CO2-Induced Stomatal Movement ...... 53 JA Signaling Mediates High CO2-Induced Stomatal Closure ...... 54

3 LOW CO2 RESPONSIVE METABOLOME AND PROTEOME IN BRASSICA NAPUS GUARD CELLS ...... 111

Introduction ...... 111 Materials and Methods...... 114 Plant Materials ...... 114 Preparation of Epidermal Peels for Stomatal Movement Assay ...... 115 Metabolite Extraction ...... 115 Metabolite Profiling ...... 117 Metabolomics Data Processing and Statistical Analysis ...... 119 Metabolic Pathway Mapping and Enrichment Analyses ...... 119 Protein Extraction and TMT 10-Plex Labeling ...... 119 Strong Cation Exchange Fractionation and LC-MS/MS Analysis ...... 121 Protein Identification and Quantification ...... 123 Results ...... 124 Low CO2 Induced Stomatal Opening and Overview of Low CO2 Responsive Guard Cell Metabolism Protein Identification and Quantification ...... 124 Lipid Metabolism under Low CO2 ...... 125 Phytohormone Changes under Low CO2 ...... 126 Proteomic Changes under Low CO2...... 127 Comparison between High and Low CO2 Responsive Metabolites ...... 129 Discussion ...... 130 Primary Metabolism Changes under Low CO2 ...... 130 Phytohormone Crosstalk in Guard Cells under Low CO2 Induced Stomatal Opening...... 131 Osmoregulations under Low CO2 ...... 133 Redox Regulation under Low CO2 ...... 134

4 SUMMARY AND PERSPECTIVES ...... 165

LIST OF REFERENCES ...... 168

BIOGRAPHICAL SKETCH ...... 188

LIST OF TABLES

Table page

2-1 MRM period method design ...... 57

2-2 Information of metabolite detected in Brassica napus guard cells ...... 67

2-3 Significantly changed metabolites under elevated CO2 ...... 80

2-4 Metabolites significantly changed at 3 or more time points or with a fold change over 10 under elevated CO2 ...... 94

3-1 Fold changes and p values of significantly changed metabolites in low CO2 treated B. napus guard cells ...... 136

3-2 Significantly changed proteins under low CO2 ...... 148

LIST OF FIGURES

Figure page

2-1 Elevated CO2 induced stomatal closure and ROS production in B. napus guard cells ...... 95

2-2 Overview of significantly changed metabolites in response to elevated CO2 treatment ...... 97

2-3 PCA plots of high CO2 treated guard cell metabolomics data ...... 98

2-4 Pathway view of representative metabolite changes at different time points after elevated CO2 treatment ...... 99

2-5 Heat map and hierarchical clustering of significantly changed metabolites ...... 100

2-6 Pathway impact analysis of the elevated CO2 responsive metabolites in the time-course study ...... 104

2-7 Changes in the flavonoid contents during elevated CO2 treatment of enriched guard cells ...... 105

2-8 Metabolite changes in JA pathway in stomata of B. napus guard cells under elevated CO2 treatment ...... 106

2-9 A. thaliana JA mutants as well as stomatal movement in the mutants under elevated CO2 ...... 107

2-10 Metabolite changes in guard cells of Arabidopsis JA and CO2 mutants and in B. napus guard cells ...... 108

2-11 Changes of ABA and ABA catabolism metabolites in B. napus guard cells ..... 109

2-12 Proposed model of JA-mediated CO2 signaling pathway ...... 110

3-1 Stomatal movement and overview of metabolomics changes under low CO2 .. 157

3-2 Venn diagram of significantly changed pathways under low CO2 ...... 158

3-3 Lipid metabolism under low CO2 ...... 159

3-4 Jasmonic aicd biosynthesis under low CO2 ...... 160

3-5 Phytohormone changes in guard cells under low CO2 ...... 161

3-6 Proteomics data overview ...... 162

3-7 Go term enrichment anlaysis for significantly changed proteins under low CO2 ...... 163

LIST OF ABBREVIATIONS

12-OPDA 12-oxophytodienoic Acid

2D Two dimensional dGMP 2-Deoxyguanosine-5-Mono Phosphate

IAA 3-Indole-Acetic Acid

ABA Abscisic acid

ABA-GE Abscisic Acid Glucose Ester

3’-AMP Adenosine-3-Monophosphate

ATP Adenosine triphosphate

CO2 Carbon dioxide

CoA Coenzyme A

G6P D-Glucose-6-Phosphate

DNA Deoxyribonucleic acid

F 1,6-BP Fructose 1,6-Bisphosphate

F6P Fructose 6-Phosphate

GA3P Glyceraldehyde 3-Phosphate

GSNO S-nitrosoglutathione

GSSG Oxidized glutathione h Hour

HILIC Hydrophilic interaction liquid chromatography

HPLC High performance liquid chromatography

IBA Indole Butyric Acid

ICA Indole Carboxylic Acid

JA Jasmonic acid

LC Liquid chromatography

M Molarity m/z Mass to charge

MeJA Methyl jasmonate min Minute

MS Mass spectrometry

NADPH Nicotinamide adenine dinucleotide phosphate hydrate

NO Nitric oxide

PAGE Polyacrylamide gel electrophoresis

PBS Phosphate buffered saline

PCR Polymerase chain reaction

PEP Phosphoenolpyruvic Acid ppm Parts per million qRT-PCR Quantitative reverse transcription-polymerase chain reaction

FMN Riboflavin-5-Mono Phosphate

R5P Ribulose 5-Phosphate

RNA Ribonucleic acid

ROS Reactive oxygen species rpm Revolutions per minute s Second

SA Salicylic acid

SCX Strong cation exchange

TCEP Tris-2-carboxyethyl-phosphine

TMT Tandem mass Tag

UMP Uridine-5-Monophosphate

UV Ultraviolet var. Variety

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

GUARD CELL MOLECULAR RESPONSES TO ELEVATED AND LOW CO2 REVEALED BY METABOLOMICS AND PROTEOMICS

Sisi Geng

August 2016

Chair: Sixue Chen Major: Plant Molecular and Cellular Biology

Foliar stomatal movements are critical for regulating plant water status and gas exchange. Elevated carbon dioxide (CO2) concentrations are known to induce stomatal closure. However, current knowledge on CO2 signal transduction in stomatal guard cells is limited. Here we report the metabolomic responses of Brassica napus guard cells to different CO2 concentrations using hyphenated metabolomics (including gas chromatography (GC)-mass spectrometry (MS), liquid chromatography (LC)-multiple reaction monitoring (MRM)-MS, and ultra-high-performance LC (UHPLC)-quadrupole time-of-flight (QToF)-MS) and tandem mass tag (TMT) nanoflow UHPLC-quadrupole

Exactive Plus proteomics platform. A total of 358 metabolites were quantified in a time- course response of guard cells to elevated CO2 treatment. A total of 411 metabolites and 1397 proteins were identified in the low CO2 experiment. Most metabolites increased under elevated CO2, and the differences were most significant at 10 minutes.

Concomitantly, reactive oxygen species (ROS) production increased and stomatal aperture decreased with time. Major alterations in flavonoid, organic acid, sugar, fatty acid, phenylpropanoid, and amino acid metabolic pathways indicated changes in both primary and specialized metabolic pathways in guard cells. Most interestingly, the

jasmonic acid (JA) biosynthesis pathway was significantly altered in the course of the elevated CO2 treatment. Under low CO2, most metabolites showed decreasing trends towards the end of the one-hour treatment. Multiple phytohormones, including auxins and cytokinins that induce stomatal opening, showed significant increases at early time points. Proteomics data from the low CO2 experiments indicate that proteins involved in cellular redox regulation, energy metabolism as well as ion transportation processes are overrepresented in the significantly changed proteins. At the same time osmolytes such as sucrose, mannitol and malate and other organic acids showed significant changes under both elevated and low CO2. Interestingly, many metabolites showed inverse trends of changes under elevated versus low CO2 conditions. Together with results obtained from JA biosynthesis and signaling mutants as well as CO2 signaling mutants, we discovered that JA biosynthesis and signaling is involved in elevated CO2 induced stomatal closure, but not in low CO2 induced stomatal opening.

CHAPTER 1 INTRODUCTION

Guard cells are specialized pairs of cells that border stomata, which are microscopic pores on leaf surfaces. Stomatal guard cells respond to various biotic and abiotic environmental signals as well as endogenous phytohormones, and control the balance of CO2 uptake for photosynthesis and water loss. Proper stomatal responses can thus be essential for a plant to adapt to the fast changing environment. CO2 concentration is one of the factors that control stomatal movement. Generally, plants close their stomata under elevated CO2 to reduce water loss, and open their stomata under low CO2 to gain enough CO2 for photosynthesis. Atmospheric CO2 concentration has exceeded 400 ppm in May, 2014 (Mauna Loa Observatory, Hawaii), and with an increasing rate of atmospheric CO2, a better understanding of plant CO2 signaling pathway is urgent.

Guard cell CO2 Response

The effect of CO2 on plants can be different depending on whether it’s a temporary exposure or an extended period of exposure. Here we will discuss the effect of changing CO2 concentration on plants grown under different CO2 levels (long-term), and plants grown under atmospheric CO2 but treated temporarily with elevated or low

CO2 (short-term) separately. The short term effect of CO2 concentration changes is mainly on stomatal movement that impacts stomatal conductance and photosynthesis rate. The long term effect can be diverse, including stomatal development, overall photosynthesis rate, susceptibility to pathogens and pest infestation. Here we will discuss the short and long term effects of CO2.

A temporary elevation of CO2 concentration, either intercellular CO2 concentration (Ci) or atmospheric CO2 concentration (Ca) can induce the closure of stomata (Engineer et al., 2015), and vice versa, a decrease of CO2 concentration, will induce the opening of stomata. The intercellular CO2 concentration has long been indicated as a secondary messenger that coordinates stomatal aperture with mesophyll cell photosynthesis rate. The change of Ca is normally not much during the day (10-20 parts per million, ppm, data from Mauna Loa Observatory, Hawaii). Yet Ci can vary greatly due to the photosynthesis rate of mesophyll cell and stomatal opening status.

When stomata are closed, either at night or for some species at noon, Ci could build up quickly due to respiration. In Vicia faba, Ci levels can rise to 700 ppm from around 200 ppm baseline level when light is turned off, and drops quickly back to around 200 ppm

2 2 when illuminated with 300 μE/ (m ·s ) light. The response to CO2 varies under different environmental conditions. Several species are insensitive to high CO2 induced stomatal closure under either saturated light intensities, high leaf water potential, or low endogenous ABA levels. These species include Pinus sylvestris, Picea sichensis and

Gunnera tinctoria (Beadle et al., 1979; Fricker and Willmer, 1996a; Ludlow and Jarvis,

1971; Ng and Jarvis, 1980). In addition, in the dark, the stomata of Commelina communis L. are less sensitive to low CO2 induced stomatal opening (Morison and

Jarvis, 1983).

Short Term Effects of CO2 on Guard Cell Signaling

Short term effects of CO2 are mostly studied in context of guard cell response.

The signaling pathway for elevated CO2 induced stomatal opening shares many nodes with the well-studied ABA signaling pathway, including GROWTH CONTROLED BY

ABSCISIC ACID 2 (GCA2) (Young et al., 2006), the activation of OPEN STOMATA1

(OST1) and its target SLOW-TYPE ANION CHANNEL 1 (SLAC1) (Xue et al., 2011), increased ROS and NO levels (Shi et al., 2015), as well as increased cytosolic Ca2+ concentration (Schwartz et al., 1988; Webb et al., 1996). Studies have shown that the

CO2 signaling pathway is independent from the ABA signaling pathway (Hashimoto et al., 2006; Hu et al., 2010; Merilo et al., 2013; Tian et al., 2015). Though contradictory data have shown that both ABA signaling mutants, pyr1 pyl1 pyl4, and pyr1 pyl1 pyl2 pyl4 and, ABA biosynthesis mutant nced3 nced5 have impaired high CO2 response

(Chater et al., 2015), indicating that a baseline level of ABA may be needed to prime guard cell for high CO2 induced stomatal closure. It has also been shown that the activation of SLAC1 under elevated CO2 is not dependent upon ABA. Several mutants that are exclusive to CO2 signaling have been identified so far, including the carbonic anhydrase double mutant ca1ca4 (carbonic anhydrase 1, 4) (Hu et al., 2010), rhc1

(resistant to high CO2 1) (Tian et al., 2015), and ht1 (high temperature 1) (Hashimoto et al., 2006). A comprehensive review on CO2 signaling in guard cell has been published recently (Engineer et al., 2015). The signaling of CO2 starts with conversion of CO2 to bicarbonate catalyzed by CA1 and CA4, leading to increased bicarbonate concentration in the cytosol. CA1 and CA4 are highly expressed in guard cell, both are beta-family carbonic anhydrases. CA4 localizes to the plasma membrane while CA1 localizes to the chloroplast. The CO2 insensitive phenotype can be restored by expressing CA1, CA4 or a human alpha-CA2 under a guard cell specific promoter (Hu et al., 2010). Further studies on the localization of carbonic anhydrases show that both a plasma membrane localization of CA4 and a chloroplast localized CA1 can restore the insensitive CO2 phenotype of ca1ca4 double mutant. However, mistargeting CA4 to the chloroplast

cannot restore the CO2 insensitive phenotype, indicating different functions of CA1 and

CA4 during high CO2 induced stomatal closure (Hu et al., 2015). CA1 is also known as

SALICYLIC ACID BINDING PROTEIN 3 (AtSABP3). At the whole plant level, the carbonic anhydrase activity is required for resistance to pathogens. The CA1 carbonic anhydrase activity but not salicylic acid binding capacity is regulated by nitrosylation at

C280. A substitution of this cysteine to serine causes impaired resistance to pathogens

(Wang et al., 2009). Chloroplast located carbonic anhydrases are known to play key roles in lipid biosynthesis by condensing inorganic carbon in the chloroplasts (Hoang and Chapman, 2002).

Downstream of the carbonic anhydrases, the increased level of bicarbonate can be sensed by (RESISTANT TO HIGH CO2 1) RHC1. Activation of RHC1 suppresses

HT1, a negative regulator for high CO2 induced stomatal closure. The suppression of

HT1 removes its inhibition on OST1 activity, which is then able to activate SLAC1 and facilitates stomatal closure by transporting anions from cytosol to the intercellular space

(Tian et al., 2015). OST1 can also activate RBOHD/F to promote hydrogen peroxide production which lead to an ROS burst in the cytosol. This increase of ROS in the cytosol causes an increase of NO production, both of which can activate the tonoplast

Ca2+ channel to trigger the release of Ca2+ into the cytosol. Increase in cytosolic Ca2+ is an important step for CO2 induced stomatal closure (Webb et al., 1996; Young et al.,

2006), and it activates the SLAC1 channel (Xue et al., 2011). Atalmt/quac1, a mutant of rapid type anion channel, responsible for malate2- export, has also been identified to have impaired high CO2 induced stomatal closure (Meyer et al., 2010). Another transporter for malate intake from the intercellular space in Arabidopsis, ATP-BINDING

CASSETTE B14 (AtABCB14), which mediates malate import from intercellular space, has been shown to be a negative regulator for high CO2 induced stomatal closure (Lee et al., 2008). Previously we have observed an increase of jasmonic acids in guard cells under high CO2. This increase was not observed in the ca1ca4 mutant, and jasmonic acid biosynthesis and signaling mutants exhibit an impaired high CO2 response. These results indicate a possible role of jasmonic acid in high CO2 induced stomatal closure, but the mechanism of this induction of JA production still needs to be further tested.

Understanding of the mechanism for elevated CO2 induced stomatal closure has seen much progress recently, yet the mechanism for low CO2 induced stomatal opening is still very vague. Mutants that are known to be insensitive to low CO2 induced stomatal opening include ca1ca4, ht1, ost1, slac1, patrol1, rboh, and nr1. Among these mutants, ht1 and patrol1, both screened by a high leaf temperature phenotype, have constant high CO2 responses (Hashimoto-Sugimoto et al., 2013; Hashimoto et al., 2006;

Matrosova et al., 2015; Shi et al., 2015). Tomato plants that are NITRATE

REDUCTASE (NR) repressed have a similar level of conductance as wildtype (WT) (Shi et al., 2015), and all other mutants have either more opened stomata or higher conductance than WT. All these mutants showed impaired low CO2 response, but only ht1 completely lost the low CO2 response. The double mutant of ost1 ht1 has an intermediate level of conductance compared to the single ost1 and ht1 mutants, but does not have a low CO2 response, indicating that HT1 is epistatic to ost1 in low CO2 induced stomatal opening (Matrosova et al., 2015).

Long Term Effects of CO2 on Plant Physiology

A long term exposure to either elevated or low CO2 can affect the plant photosynthesis rate, and thus biomass production. However the effects of low or

elevated CO2 do not limit only photosynthesis. Plant development and physiology also change as an adaptation to different CO2 levels. Under elevated CO2, the carboxylation rate of Rubisco is enhanced and oxygenation inhibited, thus, causing an increase of photosynthesis. This increase is lower in C4 plants than in C3 plants, as C4 plants have a CO2 enrichment ability, which makes them less sensitive to increasing CO2 levels since the current CO2 level may already be close to their CO2 saturation point

(Ainsworth and Long, 2005; Bowes, 1993). Based on a meta-analytical review focusing on studies using Free-air CO2 Erichment (FACE) techniques, C3 plants have a 33% average increase in photosynthesis under elevated CO2, yet C4 plants show either no increase or a small increase of 15 ~ 20% (Ainsworth and Long, 2005). Unlike the difference between C3 and C4 plants in increased photosynthetic rate, stomatal conductance is generally reduced to an average of 20% under elevated CO2 in both types of plants (Ainsworth and Long, 2005). The decreased stomatal conductance can be partially explained by decreased stomatal aperture under elevated CO2 and can be explained by a decrease in stomata number as well. Developmental changes under elevated CO2 will be discussed more in detail later. The increase of assimilation rate at saturated light condition as well as decrease of conductance can both be stimulated under different stress conditions including high temperature (above 25 ˚C compared to below 25 ˚C), ozone, and drought. However, under low nitrogen stress, assimilation rate is not stimulated (Ainsworth and Long, 2005). This result is quite different from those obtained from growth chamber experiments, where stress conditions cause reduction in assimilation under elevated CO2. Photosynthetic acclimation is a phenomenon used to describe a change in photosynthetic parameters in response to different CO2 levels

when plants grow under elevated CO2 (Atwell et al., 1999). Thus changes have been found in Rubisco amount/activity, RuBP regeneration capacity, and phosphate regeneration capacity (Sage, 1990). This acclimation is found to be more significant in

C3 crops than in tress and legumes. Photosynthetic acclimation is often found to be diminished when nutrient limits (such as nitrogen supply) are removed (Isopp et al.,

2000; Stitt and Krapp, 1999b). Interestingly, the effect of photosynthetic acclimation can be removed by nodulation in Glycine max (Ainsworth et al., 2004) and Medicago sativa

(Lüscher et al., 2000). Limited N level is suggested to cause a decrease in total protein amount in plant and, thus, Rubisco amount (Stitt and Krapp, 1999a). A FACE experiment further indicated that this reduction in protein mainly occurs due to Rubisco, not other proteins in the leaf (Ainsworth and Long, 2005).

Besides all the physiological influences of CO2, plant height, stem diameter, branching number, leaf number, leaf-area index (LAI), dry matter production (DMP) and crop yield have all been indicated to increase under elevated CO2, but the degree of changes varies among different plant species. Trees were indicated to have the highest increases in height, stem diameter, LAI, as well as DMP, while C3 crops showed less increases in height and DMP, but showed no significant increase in LAI. Crop yields generally increased under elevated CO2, but the yield increase from the FACE experiment (a 17% average) is much less than what was predicted from the growth chamber experiments (28 to 35%) (Ainsworth and Long, 2005; Cure and Acock, 1986;

Isebrands et al., 2001; Kimball, 1983). The increase in yield caused by elevated CO2 can be more obvious under stress conditions such as drought (Ottman et al., 2001).

Studies have also shown that crops may be less resistant to pests or pathogen infestation when grown under elevated CO2 (Zhang et al., 2015).

CO2 Effects on Guard Cell Development

Elevated CO2 will reduce both stomata density and stomata index (McElwain and

Chaloner, 1995; Woodward, 1987). Thus negative correlation with CO2 concentration and stomata density or index can be observed from fossil evidence dated 400 million years ago (McElwain and Chaloner, 1995). This phenotype is inversed in a putative 3- keto acyl coenzyme A synthase (KSC) mutant high carbon dioxide (hic) (Gray et al.,

2000). HIC encodes an enzyme responsible for very long chain fatty acid biosynthesis, and such enzymes are involved in the synthesis of waxes, glycerolipins, sphingolipins and cutin (Post-Beittenmiller, 1996). This finding indicates that long chain fatty acids may play an important role in leaf patterning. Similarly, two wax accumulation mutants, cer1 and cer6 also shows significant increases of stomatal indices (Jenks et al., 1995;

Post-Beittenmiller, 1996; Post-Beittenmiller, 1998). On the other hand, a wax over- accumulation mutant shine (shn) showed reduced stomatal index (Aharoni et al., 2004).

The carbonic anhydrase mutant ca1ca4 has also been found to have an increased stomatal index under elevated CO2 (Engineer et al., 2014). A transcriptional analysis revealed that EPIDERMAL PATTERNING FACTOR 2 (EPF2) is upregulated in the wild type but not the ca1ca4 mutant growing under elevated CO2. EPF2 belongs to a peptide family of 11 members, which are predicted to be cleaved in order to become the active isoform. Thus a cell-wall proteome analysis was conducted in the same study to find the cell-wall located protease (Engineer et al., 2014). The authors screened and identified that a CO2 responsive secreted protease (CRSP, previously known as SUBTILASE 5.2,

SBT 5.2), which can cleave synthetic peptide covering EPF2 cleavage site in vitro.

Consistent with the above results, epf2 mutant showed an increased stomatal index while crsp showed a decreased stomatal index (Engineer et al., 2014).

Guard Cell Metabolism

Despite numerous physiological and genetics studies, only a handful of studies have reported metabolic changes in guard cells under low CO2. Small molecules play key roles during stomatal movement including osmotic regulation, signaling, as well as antioxidants that regulate guard cell redox status, an important regulation for stomatal movement (Misra et al., 2015a). Sugars, sugar alcohols, and organic acids can contribute to the turgor pressure together with inorganic ions, which leads to guard cell volume change, thus stomatal opening or closure. The most extensively studied organic osmolytes in guard cell are malate and sucrose (Daloso et al., 2015a; Daloso et al.,

2015b; Lawson et al., 2014; Lee et al., 2008; Medeiros et al., 2016). Small molecules that are known to acts as signaling molecules in guard cells include phytohormes

(Daszkowska-Golec and Szarejko, 2013; Misra et al., 2015a; Murata et al., 2015), lipids

(Jung et al., 2002; Sakaki et al., 1995), zeaxanthine (Assmann, 1999; Zeiger and Zhu,

1998; Zhu et al., 1998), as well as cGMP (Pharmawati et al., 1998). The glutathione ascorbate cycle is the best known reactive oxygen species scavenging pathway.

Besides, flavonols has also been shown to play a role in ROS scavenging, and can inhibit ABA induced stomatal closure (Watkins et al., 2014).

Guard Cell Metabolism

The function of photosynthesis in guard cells has been under debate for a long time. In general, guard cells have fewer and smaller chloroplasts than mesophyll cells.

The chlorophyll content in guard cells is about 1 to 4% that of mesophyll cells

(Birkenhead and Willmer, 1986; Reckmann et al., 1990; Song et al., 2014; Zemel and

Gepstein, 1985). In a transgenic line where only guard cells are chlorophyll deficient, many “deflated” thin shame guard cells are observed, indicating an essential role of guard cell chloroplasts in maintaining stomatal turgor pressure (Azoulay-Shemer et al.,

2015). However, the loss of chloroplasts does not affect guard cell response to high

CO2. Normal shaped chlorophyll-less guard cell pairs can still respond to elevated CO2 when compared to wild type, indicating photosynthesis is not essential for high CO2

14 induced stomatal response (Azoulay-Shemer et al., 2015). Study with CO2 as carbon source indicates guard cells can to metabolize CO2 by utilizing the first several initial steps in C4 photosynthesis (Willmer and Dittrich, 1974). Phosphoenolpyruvate (PEP) carboxylase (PEPc) activities are detected in guard cells, and are four times higher in the lower epidermis, which contains most of the guard cells compared to the upper epidermis (Willmer et al., 1973a). Malate dehydrogenase activity is also found in guard cells (Willmer et al., 1973b). A detailed list of enzymes and activities has been reviewed previously (Fricker and Willmer, 1996b). Here we summarized information on individual enzymes from this review and recent literature. The following enzyme activity data were all from studies using guard cell protoplasts or guard cells from dissected freeze-dried leaf tissues as materials, since epidermal peels have been criticized to have too much contamination from epidermal cells and mesophyll cells (Outlaw et al., 1982).

First, CO2 needs to be converted to bicarbonate by the activity of carbonic anhydrases before being further metabolized into organic compounds. The carbonic anhydrase activities are found to be almost equal in the cytosol and chloroplasts

(Fricker and Willmer, 1996b). This correlates well with the localization, activity and functional complementation of CA1 and CA4 (Hu et al., 2015), but activities contributed

by other carbonic anhydrases cannot be excluded. Bicarbonate is then metabolized together with PEP by PEPc to form oxalic acid (OAA), which can be further converted to malate by NAD-dependent malate dehydrogenase. The PEPc from guard cells forms a tetramer (Denecke et al., 1993) and is similar to the PEPc from C4 plant leaves in that it has high activity and is dependent on Mg2+. Guard cell PEPc activity is activated by glucose-6-phosphate (G-6-P) and is inhibited by malate (Tarczynski and Outlaw Jr,

1993). Phosphorylation of PEPc regulates PEPc activity in C4 plants, and this type of regulation is also found in guard cells during light and fuscoccin induced stomatal opening, as well as ABA induced stomatal closure (Du et al., 1997; Zhang et al., 1994).

Phosphorylation of PEPc activates it and reduces the inhibition effect of malate (Jiao and Chollet, 1991). Similar to PEPc, a high level of NAD specific malate dehydrogenase activity can be detected in guard cells (Gotow et al., 1985; Scheibe et al., 1990). Malate dehydrogenase activity is quickly enhanced under light and inhibited under dark conditions. The activation of NAD-malate dehydrogenase under light can be inhibited by

DCMU (3-(3,4-dichlorophenyl)-1,1-dimethylurea), indicating this activation is dependent on the electron transport chain (Gotow et al., 1985).

The activities of enzymes responsible for glycolysis and glucoseneogenesis are all present in guard cells (Fricker and Willmer, 1996b). Fructose-2,6-bisphosphate increases significantly under illumination in Vicia faba guard cells (Hedrich et al., 1985).

This increase in fructose-2,6-bisphosphate is indicated to be a regulatory mechanism that drives the carbon metabolism towards starch degradation by inhibiting gluconeogenesis through the inhibition of cytoplasmic fructose-1,6-bisphosphatase and activating glycolysis through the activation of fructose-6-phosphate transferase (Hedrich

et al., 1985). On the contrary, F-2,6-BP level decreases under dark, which facilitates stomatal closure by releasing its inhibition of gluconeogenesis (Hedrich et al., 1985).

Osmoregulation

Stomatal movement is realized by the change in osmolality which directly leads to the volume change. This osmolality change is contributed mainly by inorganic and organic ions. Studies have shown that inorganic ion contributes part of the osmolarity change during diurnal stomatal aperture changes, and the other part is contributed by organic small molecules such as malate and sucrose. H+, K+, and Cl- are the main inorganic ions that regulate stomatal movement. During ABA induced stomatal closure, cytosolic alkalizaion can be observed, which further induces the activation of K+ outward rectifying channel, as well as activation of quick and slow type anion channels, exporting Cl- from the cytosol to intercellular space (Geiger et al., 2009; Munemasa et

2- al., 2015). During elevated CO2 induced stomatal closure, malate is also exported through AtABCB14. The abcb14 mutant is insensitive to elevated CO2 induced stomatal closure (Lee et al., 2008). Yet, the intercellular malate levels in guard cells have not been measured during elevated CO2 response. During stomatal opening however, increases of malate are usually observed, while starch concentration decreases in the meantime. During stomatal closure, a decrease in malate is usually detected. Excessive malate can be released into the extracellular space, metabolized or synthesized back to starch. In order to be metabolized into starch, the malate needs to be first decarboxylated into pyruvate, then be converted to PEP before entering gluconeogenesis. However, the activities for enzymes synthesizing PEP have not been detected in guard cells, thus this pathway may be questionable. Nevertheless, a recent paper reported that starch biosynthesis in guard cells, but not in mesophyll cells, is

required for high CO2 induced stomatal closure (Azoulay-Shemer et al., 2016). This confirms that the activity of ADGase (ADP-glucose-pyrophosphorylase) is essential for stomatal osmoregulation by starch biosynthesis. ADGase activity is regulated the same way in guard cell as in mesophyll cells. It is activated by 3-PGA and inhibited by inorganic phosphate concentration (Robinson et al., 1983; Outlaw and Tarczynski,

1984). Interestingly, a recent study has found that apoplastic sucrose, glucose and fructose serves as signaling molecules rather than osmotic regulators. These sugars can be sensed by hexokinases (HXK) when transported into guard cells and can stimulate stomatal closure (Daloso et al., 2015a; Kelly et al., 2013).

ROS Homeostasis

ROS are essential secondary signals in multiple signaling pathways in guard cells, including darkness, elevated CO2, ABA, ethylene, jasmonic acid, salicylic acid, as well as ozone. The production of hydrogen peroxide (H2O2) is catalyzed by RBOH D and F in ABA, MeJA and elevated CO2 induced stomatal closure. Loss of AtRBHOD/F causes impaired stomatal responses to the stimuli above (Kolla et al., 2007; Kwak et al.,

2003; Leshem and Levine, 2013). Both H2O2 and NO can induce stomatal closure in a concentration dependent manner. The increases of ROS and NO in the cytosol cause release of Ca2+ from internal stores such as ER, which further induces SLAC1 and

+ inhibits K inward rectifying channels (Pham and Desikan, 2009). Excessive H2O2 is usually scavenged through the ascorbate-glutathione cycle. Major enzymes that have evolved to scavenge peroxides include: superoxide dismutase (which eliminates

2- superoxide radicals and O in a reaction that yields H2O2), catalase (which catalyzes the conversion of H2O2 to oxygen and water), and enzymes involved in the ascorbate- glutathione cycle. The ascorbate-glutathione cycle is the major antioxidant pathway in

plants, where H2O2 is converted to water though the oxidation of ascorbate to monodehydroascorbate radical by ascorbate peroxidase. Ascorbate regeneration is completed in two ways. In plastids, the reduction of monodehydroascorbate is catalyzed by monodehydroascorbate reductase by transferring the election from NADPH to monodehydroascorbate and forming NADP+ and ascorbate. Alternatively, it can spontaneously dismutate to dehydroascorbate, which is reduced by dyhydroascorbate reductase using glutathione (GSH), resulting in the formation of oxidized glutathione

(GSSG) and ascorbate. GSSG is then reduced back to GSH by glutathione reductase through the consumption of NADPH (Buchanan et al., 2000). Flavonols play a role in scavenging ROS to counteract ABA induced stomatal closure (Watkins et al., 2014).

Ethylene together triggers flavonol production in guard cells, and when ethylene and

ABA are used to treat guard cells, ABA induced stomatal closure is impaired (Watkins et al., 2014).

Signaling Molecules

A number of small molecules play a role in signaling in guard cells, such as phytohormones, lipids, and sugars. Phytohormones are the main signaling molecues in regulating stomatal movement in response to various biotic and abiotic stimuli. Known phytohormones that are involved in stomatal aperture regulation include abscisic acid, ethylene, gibberellins, jasmonic acid, salicylic acid, auxins, cytokines, and brassinosteroids. Generally, auxin, cytokinine, ethylene and brassinosteroids induces stomatal opening, but their effects are concentration dependent. Under high concentration when applied exogenously, these small molecules can induce stomatal closure. While JA, SA and ABA generally induce stomatal closure and are mainly responsible for wounding, pathogen infection and drought induced stomatal closure,

respectively. Among all these hormones, ABA is the best studied hormone. ABA is a terpenoid phytohormone synthesized from β-carotenoid in the plastids. Enzymes that are responsible for ABA biosynthesis include β-carotene hydroxylase 2 (BCH2, catalyzing the conversion of β-carotenoid to zeaxanthin), zeaxanthin-epoxidase (ABA1 or ZEP, converting zeaxanthin to antheraxanthin and then to violaxanthin), neoxanthin synthase (ABA4, converting violaxanthin to neoxanthin), an unknown cis-isomerase that converts neoxanthin to 9-cis-violaxanthin,9-cis-epoxycarotenoid-dioxygenase in plastids

(NCED3, converting 9-cis-violaxanthin to xanthoxin), ABA DEFICIENT 2 (ABA2, encoding a short-chain dehydrogenase/reductase to convert xanthoxin to abscisic aldehyde in the cytosol, and ABA DEFICIENT 3 (ABA3 encoding a molybdenum cofactor sulfurase to convert abscisic aldehyde to ABA (Nambara and Marion-Poll,

2005). Interestingly, though a precursor for ABA biosynthesis, zeaxanthin actually induces stomatal opening under blue light and low CO2 (Zeiger and Zhu, 1998; Zhu et al., 1998). All the genes encoding enzymes needed for ABA biosynthesis mentioned above have been found to be expressed in guard cells, and an aba3 mutant is shown to be insensitive to drought induced stomatal closure (Bauer et al., 2013). ABA signaling pathway has been well characterized and shares many components with elevated CO2 induced stomatal closure, as indicated in the CO2 signaling section. ABA is perceived by the ABA receptor complex, PYRABACTIN RESISTANCE 1 (PYR)/PYR1-LIKE

(PYL)/REGULATORY COMPONENT OF ABA RECEPTOR (RCAR). (Ma et al., 2009;

Park et al., 2009) Upon binding of ABA, the receptor complex physically interacts with

PP2Cs (protein phosphatase type 2C), which inhibits the ABA signaling pathway and inactivates the PP2Cs. This inactivation of PP2Cs further allows for activation of the

downstream signaling pathways including autophosphorylation and activation of OST1

(Lee et al., 2009), then the activation of rapid-type anion channel and slow-type anion channel (SLAC1) (Geiger et al., 2009). Further downstream are the activation of K+ outward rectifying channel, the inactivation of inward rectifying K+ channel (KAT1) (Sato et al., 2009), and activation of downstream transcription factors such as ABSCISIC

ACID RESPONSIVE ELEMENTS-BINDING FACTOR 3 (ABF3) (Sirichandra et al.,

2010) and MYC2 (Abe et al., 2003). ROS production is another event downstream of

OST1. The increase of ROS triggers the production of NO, as well as the release of

Ca2+ from the internal stores as well as cytosolic alkalization. Cytosolic alkalization can also be observed during ABA induced stomatal closure, which in turn enhances K+ outward rectifying channel.

Besides ABA, jasmonic acid (JA) is another well-known phytohormone that induces stomatal closure. JA is mainly responsible for wounding and pest infestation induced stomatal closure. JA is a oxilipin synthesized from α-linolenic acid (18:3) in the chloroplasts. α-linolenic acid is first oxidized by lipoxigenases (LOX) to 13S- hydroperoxy-(9Z,11E,15)-octadecatrienoic acid (13-HPOT), then further dehydrated and converted to 12,13-epoxyoctadecatrienoic acid (12,13-EOT) by allene oxide synthase

(AOS) (Laudert et al., 1996). 12,13-EOT is unstable, and can cyclized into 12-oxo- phytodienoic acid (OPDA). In the presence of allene oxide cyclase (AOC) (Stenzel et al., 2003), the main product is 9S,13S/cis (+)-OPDA for the reaction catalyzed by AOC.

The steps above take place in the plastids, and cis (+)-OPDA is transported to the peroxisome and is further converted to cyclopentanone (3-oxo-2-(2’(Z)-pentenyl)- cyclopentane-1-octanoic acid (OPC-8:0) by the acitivity of 12-oxo-phytodienoic acid

reductase (OPR), and undergoes three rounds of beta oxidation utilizing acyl-CoA oxidase (ACX), multifunctional protein (MPF, exhibiting 2-trans-enoyl-CoA hydratase, L-

3-hydroxyacyl-CoA dehydrogenase, D-3-hydroxyacyl-CoA epimerase and Δ3, Δ2-enoyl-

CoA -isomerase activities), and l-3-ketoacyl-CoA thiolase (KAT), producing (+)-7-iso-JA, which is the final product of JA biosynthesis. JA is readily isomerized into (-)-JA, which is more thermodynamically favored (Sembdner and Parthier, 1993). Over 30 distinct modifications for JAs can be found in different cellular components across the plant kingdom (Sembdner and Parthier, 1993), among which free JA, methyl jasmonic acid

(MeJA), and jasmonic acid isoleucine (JA-Ile) are the major active forms (Fonseca et al., 2009). Among these active forms, JA-Ile has been shown to be able to bind to the

JA signaling pathway receptor COI1. Coronatine is a JA-Ile mimic produced by

Pseudomonas syringae, yet it induces stomata opening by suppressing SA accumulation (Zheng et al., 2012). The receptor COI1 is a F-box protein (Katsir et al.,

2008). Upon binding of JA-Ile, COI1 forms a SCF complex together with Skp1 (S-phase kinase-associated protein)-related protein, a cullin, and a RING-box protein which ubiquitinates downstream jasmonate ZIM domain (JAZ) proteins. JAZ proteins repress the transcription of JA responsive genes, thus JA signaling also has a double negative regulation. MeJA induced stomatal closure also shares several components with ABA signaling pathway, including cytosolic alkalization, production of ROS and NO, as well

2+ as increase of [Ca ]cyt (Islam et al., 2010). The convergence point of ABA and JA signaling is predicted to be downstream of OST1 and COI1, but upstream of ROS production, yet the mechanism is still not clear.

Salicylic acid is a phenolic phytohormone produced by plants from cinnamate

(Klambt, 1962) or isochorismate (Wildermuth et al., 2001) mainly during pathogen infection to induce stomatal closure (Melotto et al., 2006). Cinnamate can be synthesized to salicylic acid either through benzoate or o-coumarate depending on whether it is hydroxylated first (Klambt, 1962) or chain-shortened first (Coquoz et al.,

1998). Exogenous application of SA can induce ROS production, which further leads to

2+ + increase of [Ca ]cyt and inhibition of inward rectifying K channel (Khokon et al., 2011).

SA deficient plants or biosynthesis mutants showed hypersensitivity to bacterial pathogens infection (Melotto et al., 2006). ABA has also been shown to play a role in

SA induced stomatal closure, since aba3-1 mutant does not show a proper stomatal closure in response to flg22, which is a Pathogen Associated Molecular Pattern (PAMP) elicitor, and neither does ost1 mutant (Melotto et al., 2006). However, another study using a different ABA biosynthesis mutant, aba2, showed that there’s no difference between the mutant and wildtype in stomatal movement in response to SA (Issak et al.,

2013).

Auxins are a group of phytohormones including 3-indole-acetic acid (IAA) and compounds having similar effects as IAA. The effect of IAA on stomata movement is contradictory between species, tissues, and treatment conditions as mentioned above.

The IAA receptor TIR1 forms a SCF complex and ubiquitinates downstream repressors for auxin responses and leads to their degradation (Gray et al., 2001; Kepinski, 2007;

Tiwari et al., 2004; Zenser et al., 2001). Meanwhile, the Aux/IAA genes are repressors for themselves, forming a negative regulation loop. During auxin induced stomatal opening, activation of H+-ATPases was observed, leading to cytosolic acidification and

activation of K+ influx channel. At the same time, auxin can repress ROS and NO production, but cannot remove ROS and NO already present in the cells (She and Song,

2006; Song et al., 2006).

Cytokinins are adenine-derived phytohormones that also affect stomatal movement 1n a concentration depended manner. Increases of cytokinins in the xylem has been shown to promote stomatal opening, and at the same time reduces ABA sensitivity (Kepinski, 2007). Yet unlike auxins, cytokinins can decrase ROS and NO levels as well as repress further ROS and NO production (She and Song, 2006; Song et al., 2006). Brassinosteroids are steroidal phytohormones. They also have concentration dependent effects on stomatal movement. Under lower concentrations, 24- epibrassinolide (0.1 μm) induces stomatal opening, while under higher concentrations (1 to 5 μm), it induces stomatal closure (Xia et al., 2014b). The ros levels negatively correlate with stomatal aperture when treated with different brassinosteroid concentrations (Xia et al., 2014b). However, application with another brassinosteroid, brassinolide, at the same concentration as epibrassinolide mentioned above (0.1 μm) causes stomatal closure by inhibiting inward rectifying k+ channel in vicia faba

(Haubrick et al., 2006). This indicates that brassinosteroid induced stomatal movement may be specific for different brassinosteroids, as well as for different species.

CHAPTER 2

JASMONATE-MEDIATED STOMATAL CLOSURE UNDER ELEVATED CO2 REVEALED BY TIME-RESOLVED METABOLOMICS1

Introduction

Increase in atmospheric CO2 concentration is of global concern with regards to its long term effects on crop growth and productivity (Guo et al., 2014; Li et al., 2015b;

Noguchi et al., 2015). It is expected that increased CO2 may benefit crop yield by increasing photosynthetic rates in most plant species, especially C3 plants, and by minimizing water loss due to reduced transpiration through stomatal closure (Leakey,

2009). However, elevated CO2 can cause heat stress because of the reduced evaporative cooling accompanying closed stomata (Engineer et al., 2015). In addition, elevated CO2 was shown to reduce the resistance of tomato plants to herbivore infestation by suppressing the jasmonate (JA) signaling pathway (Guo et al., 2012).

Therefore, whether elevated CO2 increases or decreases plant yield depends on the species, growth conditions, and associated effects on stomatal movement (Easterling et al., 2007; Kirschbaum, 2011; Misra et al., 2015a).

Guard cells are specialized cells that border the pores on leaf surfaces called stomata. Opening and closing of stomata control the balance of water loss and CO2 intake for photosynthesis. Proper stomatal responses to different external environmental changes and endogenous phytohormones are essential for plants to adapt to an ever changing environment. It is well-known that increases in CO2 concentration around guard cells, including both intercellular CO2 concentration (Ci) and atmospheric CO2

1 Reprinted with permission from Geng, S., Misra, B.B., Armas, E.d., Huhman, D., Alborn, H.T., Sumner, L.W. and Chen, S. (2016) Jasmonate-mediated stomatal closure under elevated CO2 revealed by time- resolved metabolomics. Plant J.

concentration (Ca), induce the closure of stomata (Engineer et al., 2015). Recent findings on two carbonic anhydrases, CA1 and CA4, revealed their roles in guard cells

- for the conversion of CO2 to bicarbonate (HCO3 ) (Engineer et al., 2015), the first step in

CO2 signaling (Hu et al., 2010). The plasma membrane localization of CA1 and

- chloroplast localized CA4 enables the regulation of HCO3 concentration in the cytosol and chloroplast, and is important for elevated CO2 induced stomatal closure (Hu et al.,

- 2015). Downstream of CA1 and CA4, the increased level of HCO3 in the cytosol activates RESISTANT TO HIGH CO2 1 (RHC1), which physically interacts with HIGH

TEMPERATURE 1 (HT1) kinase and inhibits its activity (Tian et al., 2015). Inhibition of

HT1 relieved its inhibition of the kinase activity of OPEN STOMATA 1 (OST1), leading to stomatal closure (Tian et al., 2015). Although abscisic acid (ABA) signal transduction converges in multiple steps with CO2 signaling, e.g., reactive oxygen species (ROS)

2+ production and [Ca ] oscillations in the cytosol, CO2 signaling appears to be independent of ABA in the upstream steps, which involve CA1, CA4, RHC1, and HT1

(Kim et al., 2010b; Tian et al., 2015). In support of the above, elevated CO2 did not induce ABA production in tomato guard cells during stomatal closure (Li et al., 2015b).

ROS are important players in many signaling pathways that induce stomatal closure, such as ABA, JA, dark, pest infestation, and pathogen infection (Song et al.,

2014). Elevated CO2-induced stomatal closure is known to induce ROS production in both Arabidopsis and tomato (Kolla et al., 2007; Shi et al., 2015). But besides the involvement of NADPH/respiratory burst oxidase homolog (RBOH) D/F, little is known about ROS production in guard cell CO2 signaling (Kolla et al., 2007). Interestingly, low levels of ROS can induce stomatal opening, whereas high levels of ROS leads to stress

responses resulting in stomatal closure (Watkins et al., 2014). Thus, intracellular ROS scavengers (enzymes and metabolites) are important for the regulation of ROS levels and for cellular homeostasis and stomatal movement. Primary and specialized metabolites (e.g., phytohormones, sugars, organic acids, phenylpropanoids, flavonoids, and fatty acids) are known to play important roles in stomatal movement and guard cell physiology (Misra et al., 2015a). While extensive effort has been made in genetic and physiological studies of stomatal responses, little emphasis has been put on the discovery and functional analysis of small molecules in the guard cells. The current status of the guard cell metabolome documenting ~110 metabolites was recently reviewed (Misra et al., 2015a), with the most comprehensive catalog coming from the study on the ABA-responsive Arabidopsis guard cell metabolome (Jin et al., 2013).

Despite the progress in guard cell -omics and CO2 signaling, the understanding of the mechanisms underlying the guard cell response to elevated CO2 is incomplete, and metabolomics studies of the important processes have not been reported.

To discover new players and regulators important for elevated CO2-induced stomatal closure, we applied hyphenated mass spectrometry (MS)-based metabolomics approaches to analyze short-term metabolomic responses in B. napus (canola) guard cells to elevated CO2. A total of 358 metabolites with temporal changes were quantified.

We observed increased accumulation of flavonoids at early time points, increased primary metabolites (e.g., fatty acids, amino acids, and nucleotides), and changes in the levels of osmoregulators and JA-related metabolites under elevated CO2 treatment.

Together, with reverse genetics and functional studies, we report a function of JA signaling in mediating the guard cell CO2 responses. This study also highlights the utility

of single cell-type metabolomics in discovering and testing new nodes and edges in cellular signaling and metabolic networks.

Material and Methods

Plant Material

B. napus var. Global seeds obtained from Svalöv Weibull AB (Svalöv, Sweden) were grown as previously described (Zhu et al., 2010). A. thaliana mutant seeds coi1-

12, jar1, and jin1 were provided by Dr. Zhonglin Mou, Department of Microbiology and

Cell Science, University of Florida, and ca1ca4 mutants were obtained from the

Arabidopsis Biological Resource Center (ABRC, Ohio State University, Columbus,

USA). Seeds were germinated on half strength Murashige and Skoog (MS) (Murashige and Skoog, 1962) media prior to transferring to soil. Arabidopsis plants were grown under a photosynthetic flux of 140 µmol photons m-2 sec-1 and an 8 h light/16 h dark cycle for six weeks until collection of leaves for further analyses.

Preparation of Epidermal Peels for Stomatal Movement and ROS Assays

Small squares (0.5 × 0.5 cm2) of leaf pieces from 8 weeks old B. napus plants were fixed abaxial side down onto coverslips coated with medical adhesive (Hollister,

Libertyville, IL, USA). Abaxial epidermis and mesophyll layers were removed with a scalpel. After washing three times with distilled water to remove cellular debris, the coverslips were incubated with a cell wall digesting enzyme mixture containing 0.1 %

(w/v) PVP-40 (Calbiochem , Billerica, Massachusetts, USA), 0.25 % (w/v) BSA

(Research Products International Corp., Mt Prospect, Illinois, USA), 0.7 % Cellulase R-

10 (Yakult Honsha Co., Ltd, Tokyo, Japan), and 0.025% Macerozyme R-10 (Yakult

Honsha Co., Ltd, Tokyo, Japan) in 55% basic solution (0.55 M sorbitol, 0.5 mM CaCl2,

0.5 mM MgCl2, 0.5 mM ascorbic acid, 10 µM KH2PO4, 5 mM MES-Tris, pH 5.5 adjusted

with 1 M KOH) at 26 °C, 140 excursions per min for 13 min. The coverslips were then incubated with a stomatal opening buffer (10 mM KCl, 50 μM CaCl2, 10 mM MES-KOH, adjusted to pH 6.15 with 1 M KOH) under light (110 µmol m-2 s-1) for an hour. For elevated CO2 treatment, the open stomata were exposed continuously to 800 ppm CO2 for a period of 60 min as previously described (Hu et al., 2010).

Stomatal ROS Measurement

For ROS measurement, 30 μM 2',7'-dichlorodihydrofluorescein diacetate

(H2DCFDA) was added to the opening buffer and incubated with the epidermal peels for

40 min. After washing with the opening buffer to remove excess dye, the stomata were transferred to an infusion chamber, which was pre-equilibrated with 400 ppm (control) or

800 ppm elevated CO2 (treatment). Images of stomatal guard cells were acquired using excitation wave lengths of 450-490 nm and emission wave lengths of 500-550 nm on a

Leica DM 6000 B fluorescence microscope (Leica, Buffalo Grove, IL, USA). Stomatal aperture and ROS fluorescent intensities were measured using ImageJ software

(National Institutes of Health, Bethesda, Maryland, USA).

Large Scale Preparation of Stomata for Metabolomics

Stomata from B. napus were prepared as recently described (Zhu et al., 2012).

A. thaliana stomata were prepared using a Scotch-tape method as previously described

(Svozil et al., 2015; Wu et al., 2009). Briefly, five weeks old A. thaliana leaves were attached to clear Scotch tape (3 M, St. Paul, MN) with the abaxial side facing down.

Another piece of Scotch tape was used to separate the mesophyll cells attached to the adaxial layers from the abaxial side with pavement and guard cells. A total of 25 epidermal peels constituted a biological replicate, and four replicates were collected.

The peels were digested in 70 mL of the cell-wall digesting enzyme solution for 15 min

as described above. All the samples were stabilized in 400 ppm CO2 (control) for 15 min before continuing in control or switching to 800 ppm CO2 (treatment) conditions (Hu et al., 2010). The samples were collected at 0, 5, 10, 30, and 60 min on 100 μm nylon mesh. The samples were quickly frozen (~30 s) in liquid nitrogen and then lyophilized before metabolite extraction.

Metabolite Extraction

Lyophilized B. napus samples (100 mg dry weight each) were homogenized with a metal ball in a screw-capped tube for 20 s at 1900 strokes/min on a GenoGrinder

(Geno/Grinder 2000, SPEX SamplePrep., Metuchen, NJ, USA). An internal standard mixture (10 µL) (100 M each of lidocaine, 10-camphorsulfonic acid, and adonitol) was added to each sample. Metabolites were extracted following a standard method (Fiehn et al., 2008). Briefly, samples were extracted once in 1 mL of extraction solvent I

(acetonitrile: isopropanol: water, 3:3:2), and twice with 0.5 mL of extraction solvent II

(acetonitrile: water, 1:1) on a thermomixer (Thermomixer R, Eppendorf, Hamburg,

Germany) at 4°C and 1100 rpm for 5 min each time, followed by sonication for 15 min on ice and centrifugation at 13000 g for 15 min at 4°C. The supernatants were combined and lyophilized. For LC-MRM-MS and UHPLC-QToF-MS, the extracts were re-constituted in 100 μL distilled water. For GC-MS, the dried extracts were subjected to derivatization procedures using 100 μL each of 25 mg/mL methoxyamine hydrochloride and N,O-bis(trimethylsilyl) trifluoroacetamide (BSTFA) with 1% trimethylchlorosilane

(Supelco, PA, USA) as previously described (Kopka et al., 2005).

For the A. thaliana samples, an additional step of extraction with 80% methanol was conducted for efficient extraction of oxylipins (Glauser and Wolfender, 2013). Thus,

sequential extraction using 3 mL of 80% methanol, 2 mL of extraction solvent I, and 2 mL of extraction solvent II was followed during metabolite extraction. All extracts were lyophilized and were then re-suspended in 100 μL of 80% methanol for JA-related metabolite analysis.

Metabolite Profiling Using Hyphenated Metabolomics Platforms

HPLC-MRM-MS was conducted using an Agilent 1100 HPLC (Agilent, Santa

Clara, CA, USA) coupled with an AB Sciex 4000 QTRAPTM (AB Sciex, Framingham,

MA, USA). Optimized detection conditions including precursor ion, product ion, declustering potential (DP), collision energy (EP) and cell exit potential (CXP) were established for 277 authentic compounds (Table 2-1). A reverse-phase C18 column

(Agilent, Eclipse XDB-C18, 4.6 x 250 mm, 5 µm) was used for metabolite separation with 0.1% formic acid in water as solvent A and 0.1% formic acid in acetonitrile as solvent B. The LC gradient was initially held at 1% solvent B for 5 min, then a linear gradient was imposed from 1% B to 99.5% B over 41.5 min, followed by holding at

99.5% B for 4.5 min, and then a return to 1% B. The flow rate was 0.5 mL/min, and the total analysis time was one hour. The mass spectrometer conditions were: 30 psi curtain gas, 50 psi GS1, 55 psi GS2, ion source voltage at + or - 4500 V, with the Turbo

ElectroSpray Ionization (ESI) interface temperature at 350 °C. A multiple period

(segment) method was followed as previously described (Chen et al., 2013). Details about the period (segment) design are provided in Table 2-1.

GC-MS was performed using a Thermo Scientific ISQTM single-quadrupole system (Thermo Fisher Scientific Inc., Framingham, MA, USA). Extracted metabolic samples were derivatized as previously described (Lisec et al., 2006). Derivatized samples (1 µL) were injected onto an Rtx-5Sil MS, 30 m x 0.25 mm column with 10 m

integrated guard column, 0.25 µm film thickness (Restek GmbH, Bad Homburg,

Germany) in splitless mode. Helium was used as a carrier gas. The oven temperature was held constant at 70°C for 1 min, and then ramped to 76 °C in 6 min followed by a

45 min ramp to 350 °C, and held constant at 350 °C for 1 min, then held constant at 330

°C for 10 min. The obtained data were deconvoluted and quantified using AMDIS software (Automated Mass Spectral Deconvolution and Identification System, National

Institute of Standards and Technology, Gaithersburg, MD, USA) (Stein, 1999) and metabolites were identified by matching against the GOLM spectral database (Kopka et al., 2005).

For UHPLC-QToF MS, lyophilized extracts were reconstituted in 100 μL 80% methanol with 18 µg mL-1 umbelliferone as an internal standard. The mixture was vortexed for 15 min, then sonicated for 5 min, vortexed again for 10 min, and finally centrifuged at 12000 rpm for 15 min. Data were collected on a Waters Acquity UHPLC system (Waters Corporation, Milford, MA, USA) connected to Waters Premium hybrid quadrupole time-of-flight mass spectrometer (QToF) using an electron spray ionization

(ESI) interface. An ACQUITY UHPLC BEH C18 column (1.7-μm, 2.1 x 150 mm, Waters

Corporation, Milford, MA, USA) was used with 0.05% formic acid in water (solvent A), and 0.05% formic acid in acetonitrile (solvent B) as solvents. The UHPLC gradient for solvent B was as follows: 5% to 70% B step gradient over 30 min, then 70% to 95% for

3 min, then holding at 95% for 3 min, and finally back to 5% B over 3 min. The mobile phase flow rate was 560 μL/min, and the column temperature was kept constant at 60

°C.

Metabolomics Data Processing and Statistical Analysis

The UHPLC-MS data were converted to netCDF format and were pre-processed using mzMINE software version 2.1 (Pluskal et al., 2010). The aligned peak lists were gap-filled and filtered to remove duplicated peaks and final peak lists were searched against PlantCyc, KEGG, LipidMaps, and PubChem databases with a mass tolerance set to 5 ppm (Watson et al., 2015). The data from all the three platforms were concatenated and were exported to .csv files. The final peak list from each platform was subjected to missing value imputation, batch effect correction and statistical analysis using R version 3.3.2 (R Development Core Team, 2015). A k-Nearest Neighbor (KNN) method was used for missing value imputation (R package “impute”). Batch effect correction for replicates was performed using the ComBat method (Johnson et al.,

2007) in the “sva” package. Differentially changed metabolites were analyzed using R- based empirical analysis of digital gene expression in R (EDGE) package as previously described (Jin et al., 2013; Storey JD, 2015). Treatment and control samples for each time points were compared separately. The full model took CO2 as the variable of interest, replicate batch, and time as adjustment variables, and a null model only used time and batch as adjustment variables. This allowed for the analyses of metabolites that were significantly different in control and treatment and at the same time excluded batch and time effects. For each comparison, 1000 bootstrap iterations were performed.

Principal component analysis (PCA) analysis was performed using the R base package

“Stats”. The PCA and Volcano plots were generated using the “ggplot2” package

(Wickham, 2009). Heat maps for the significantly changed metabolites were generated using heatmap2 function in R package “gplot” (Marc, 2015).

Metabolic Pathway Mapping and Enrichment Analyses

Metabolic pathway analyses were performed for metabolites at each time point separately using the pathway analysis functionalities in MetaboAnalyst 3.0 (Xia et al.,

2015). Raw data were uploaded to MetaboAnalyst 3.0 webserver and only metabolites that could be mapped to the KEGG pathway database were used. These 275 mapped metabolites out of all the quantified metabolites (combined targeted and untargeted data sets) were uploaded as a reference metabolome for the pathway enrichment and impact analysis, and were searched against an A. thaliana metabolite database.

Results

Elevated CO2 Induced Stomatal Closure and ROS Production

Guard cell protoplasts (GCPs) have been successfully used as a model system for a wide range of studies from patch clamping electrophysiology (Hashimoto et al.,

2006; Hu et al., 2010; Tian et al., 2015; Zhang et al., 2008) to biochemical analyses, as well as systems biology such as proteomics (Zhu et al., 2012; Zhu et al., 2010) and metabolomics (Jin et al., 2013). We prepared stomata that were highly pure (~99 % with little impurities from mesophyll and epidermal cells on a cell basis) and showed > 98% viability based on fluorescein diacetate staining (Zhu et al., 2016). Compared to GCPs, the stomata were preserved in stomatal structure, allowing monitoring of the stomatal movement and direct correlation with metabolomic changes over real time CO2 treatment.

B. napus stomatal movements were recorded at seven different time points across the one hour ambient (400 ppm) or elevated (800 ppm) CO2 conditions. Under control conditions, stomatal aperture did not change significantly over the one hour period. In contrast, elevated CO2 caused stomatal apertures to gradually decrease and

become significantly different from the control samples at 10 min and onwards (Figure

2-1 A, B). Previously, it was shown that ROS production was increased in guard cells

- when high concentrations of HCO3 were used as a source of elevated CO2 (Kolla et al.,

2007). Hence, we quantified ROS levels in stomatal guard cells during the elevated CO2 treatment as a physiological indicator of stomatal behavior. We observed a significant increase in ROS at 5 min of 800 ppm CO2 treatment and an overall 25-40% increase in

ROS at different time points relative to the respective time point controls (Figure 2-1 C,

D). Together, these results indicated that the prepared stomata were responsive to elevated CO2, and their responses were clearly discernible from the ambient control conditions at as early as 5 min after CO2 treatment.

Overview of Temporal Changes in Guard Cell Metabolome under Elevated CO2

In order to capture both early and late metabolome changes in the course of stomatal closure induced by elevated CO2, we collected B. napus guard cell samples at

0, 5, 10, 30, and 60 min after the treatment based on the data shown in Figure 2-1.

Using hyphenated MS-based metabolomics platforms, i.e., HPLC-MRM-MS, GC-MS, and UHPLC-QToF-MS, we identified and quantified a total of 358 unique metabolites, covering both primary and specialized metabolic pathways enriched in fatty acid, flavonoid, phenylpropanoid, amino acid, citric acid, purine, and pyrimidine metabolism among others (Table 2-2). Clearly, the current technologies used here have greatly enhanced our capabilities in analyzing the guard cell metabolome, from 89 metabolites reported in the targeted analysis of A. thaliana guard cells (Jin et al., 2013) to 358 metabolites, an increase of 4-fold.

We first performed univariate statistical analysis to determine metabolome level responses to the elevated CO2 and to identify significantly changed metabolites at each

time point (Figure 2-2 A). The numbers of changed metabolites that were unique or shared between the different time points are shown in a Venn diagram (Figure 2-2 B).

Overall, among the 226 significantly changed metabolites, 179 increased (79.2%) and

47 decreased (20.8%). Interestingly, the number of significantly decreased metabolites was much lower than the increased ones. These significantly changed metabolites alone were sufficient to separate the elevated CO2 treated samples from the ambient control samples, as indicated by PCA plots (Figure 2-3). The unique metabolites, either present or absent in the treatment at different time points, are listed together with other significantly changed metabolites in Table 2-3. The top 20 significantly changed metabolites at each time point are indicated in the volcano plots shown in Figure 2-2 C.

In addition, the metabolites with significant changes in at least three different time points and fold changes of over 10 are listed in Table 2-4. The results indicate that the most significantly changed metabolites were represented by nucleotides, nucleosides, and flavonoids. Other notable metabolites included mannitol, which significantly decreased by over 5-fold at 5 min and more than 10-fold at 10 min after elevated CO2 treatment. In addition, salicin, uridine-5-monophosphate, 1-18:3-2-16:0-phosphatidylglycerol, citramalic acid, and histidine showed more than 10-fold changes at different time-points

(Table 2-4). Figure 2-4 shows the pathway view of many significantly changed metabolites at different time points after the elevated CO2 treatment.

Hierarchical clustering was used to group metabolites with similar trends of changes during the elevated CO2 treatment (Figure 2-5). Cluster 1 was enriched in organic acids, most of which increased at the early time points and decreased at 60 min. Cluster 2 was enriched in amines, several phytohormones, and other basic

compounds that showed increased trends throughout the treatment. Cluster 7 consisted of metabolites decreasing at all the time points during the elevated CO2 treatment, potentially acting as osmoregulators during stomatal closure.

Specific Metabolite Changes in Response to Elevated CO2

Metabolites that significantly changed at one or more time points were subjected to pathway enrichment analysis, where the top 20 affected metabolic pathways based on the ln (p-value) score are shown in Figure 2-6. Metabolites in the TCA cycle showed increases except for citrate. Amino acids generally showed increased trends similar to many other biosynthetic pathways under elevated CO2. In contrast, nucleotides (e.g., purine and pyrimidines) consisted of a large set of metabolites showing decreasing trends (e.g., orate, UMP, adenosine, and 5-methyl-thioadenosine). Other interesting pathways showing functional enrichment included brassinosteroid biosynthesis at 5 min, and glucosinolate biosynthesis at 30 min. The phytohormones quantified in our platforms included ABA, auxins, cytokinins, SA, and brassinosteroids. Most auxins and cytokinins showed increasing trends throughout the time-course study (Figure 2-4).

Kinetin and indole-3-butyric acid showed increases at 5 min. Similarly, metabolites associated with brassinosteroid biosynthetic pathways showed significant changes at 5 min after elevated CO2 treatment (Figure 2-6).

The group of metabolites exhibiting the most dynamic changes belonged to the flavonoid pathway. Flavonoids derived from quercetin showed an increase at 5 min, then dropped sharply at 10 min and 30 min, and increased at 60 min back to control levels (Figure 2-4, 2-7 A). Glycoconjugates of kaempferol decreased at the early time points and rose back to higher than control at 60 min (Figure 2-7 B). Apigenin and its derivatives, as well as metabolites involved in anthocyanin biosynthetic pathways

increased to very high levels at the early time points, but dropped back to levels comparable to control at 30 min, and then either increased again or maintained at levels comparable to control (Figure 2-7 C). This group of metabolites generally showed the highest fold changes. The isoflavonoids generally decreased at 5 min, then fluctuated around control levels at the later time points (Figure 2-7 D).

Lipid-derived metabolites constitute approximately 13% of the total quantified metabolites in our metabolomics datasets. Changes in lipid metabolites included isoprenoids, sterols, alpha-linoleates, and fatty acids (Figure 2-5: Clusters 1: six increased; Clusters 2: 11 increased, while Clusters 7: eight decreased). Among these lipid metabolites, JAs are a very intriguing group since JAs are known to induce stomatal closure in many studies (Khokon et al., 2015; Munemasa et al., 2014; Zhu et al., 2012). The biosynthesis of JA starts with oxidation of alpha-linolenic acid to 13(S)- hydroperoxylinolenic acid in chloroplast membrane. In our data, we observed that

12,13-epoxylinolenic acid (12,13-EOT), which is the precursor of 12-oxo-cis-10,15- phytodienoic acid (12-OPDA), showed decreasing trends at both 10 and 30 min (Figure

2-8), while 3-oxo-2-(cis-2’-pentenyl)-cyclopentane-1-octanoic acid (OPC-8:0) increased significantly at 5 min and then decreased at 10 min. Metabolites at the branch points including 9-oxononanoic and 12-oxo-9(Z)-dodecenoic acids showed decreases at 10 min and 30 min. Unlike these precursors and branching pathway metabolites, the phytoactive forms of JA such as JA, MeJA, and JA-Ile all showed significant increases at different time points (Figure 2-8). The significant changes in guard cell JA related metabolites in response to elevated CO2 are new discoveries, which we assessed further in focused studies.

Functional Characterization of JA-Mediated CO2 Induced Stomatal Closure

To test the hypothesis from our metabolomics analysis that JA signaling mediates elevated CO2 induced stomatal closure, we first measured the stomatal movement output in several well-studied JA biosynthesis and signaling mutants of A. thaliana: the JA-Ile biosynthesis mutant jasmonate resistant 1 (jar1) (Staswick et al.,

1992) and the signaling mutants of CORONATINE-INSENSITIVE1 (coi1) (Xie et al.,

1998) and jasmonate insensitive 1 (jin1) (Berger et al., 1996; Laurie-Berry et al., 2006).

Interestingly, the biosynthesis and signaling mutants showed compromised CO2 response as compared to wild type (WT), e.g., the stomatal aperture of coi1 actually increased under elevated CO2 (Figure 2-9). As a negative control, the CA mutant ca1ca4 directly associated with CO2 signaling was used in this experiment. Consistent with previous reports (Hu et al., 2010), the guard cells of the ca1ca4 were insensitive to elevated CO2 (Figure 2-9). To test whether the insensitivity to elevated CO2 of these mutants can be attributed to JA signaling, we performed targeted profiling of JA related metabolites in the guard cells of the mutants using HPLC-MRM-MS. As shown in Figure

2-10, among all the JA metabolites quantified, four of them (α-linolenic acid, JA, JA-Ile, and 13(S)-HpOTrE) showed significant changes in the stomata of WT plants under elevated CO2, but not in ca1ca4, indicating JA changes downstream of CO2 sensing.

Interestingly, in the coi1 mutant elevated CO2 was able to induce the production of JA-

Ile. coi1 is defective in JA signaling, and coi1 stomata did not close under elevated CO2

(Figure 2-10). JAR1 catalyzes the formation of JA-Ile, and JIN1/MYC2 is a transcription factor that positively regulates JA responsive genes (Berger et al., 1996; Laurie-Berry et al., 2006; Staswick et al., 1992). Compared to WT, jar1 and jin1 mutants exhibited hyposensitivity to elevated CO2 induced stomatal closure (Figure 2-10). These results

highlight the essential role of JA-Ile and JA signaling in guard cell elevated CO2 response. Furthermore, ROS production appeared to be early event in elevated CO2 induced stomatal closure, peaking at 5 and 10 minutes in WT. Since JA induction occurred at later time points (10 and 30 min) (Figures 2-10), elevated CO2 might induce

JA production through ROS signaling, a hypothesis to be tested in the future.

In addition to JA-related metabolites, ABA was quantified to determine its potential involvement in JA production during elevated CO2 induced stomatal closure.

As shown in Figure 2-11, there were no significant changes in ABA levels in either WT or ca1ca4 mutants after the CO2 treatment, indicating the JAs mediated elevated CO2 response was independent of ABA level changes. The absence of significant changes in ABA levels in B. napus guard cells after elevated CO2 treatment (Figure 2-11) further corroborate this finding.

Discussion

Changes in Primary Metabolites and Osmolytes in The Course of Stomatal Closure under Elevated CO2

Our metabolomics datasets revealed significant changes in the levels of sugars, organic acids, amino acids and many other primary metabolites (Figure 2-4). Although elevated CO2-induced stomatal closure may affect photosynthates and related metabolites, the roles of many primary metabolite changes in CO2-induced stomatal closure is not clear. Most of the primary metabolites showed increasing trends under elevated CO2 likely due to an increased photosynthesis rate given the availability of excess CO2 (Lawson, 2009b). It is well-established that guard cell respiration and starch hydrolysis contribute to stomatal movement by providing ATP and osmotically active metabolites (Lawson, 2009a; Raghavendra and Vani, 1989; Tominaga et al., 2001). The

increased amino acids, nucleotides, and intermediates in the TCA cycle indicate increased energy metabolism. The enrichment and impact of TCA cycle metabolites at

5, 10, and 60 min (Figure 2-4) further support the enhanced metabolic rates triggered by elevated CO2.

Organic acids, sugars, and sugar alcohols have been the primary focus in stomatal studies, as their changes regulate the energy levels as well as osmolality in guard cells (Fernie and Martinoia, 2009; Medeiros et al., 2016; Outlaw and Lowry, 1977;

Talbott and Zeiger, 1993). Sugars such as sucrose function as osmolytes that work alongside K+ and Cl- in guard cells to regulate the diurnal stomatal aperture changes

(Munemasa et al., 2015; Talbott and Zeiger, 1998). Generally, an opening signal (e.g.,

+ - light and low CO2) will induce an influx of K , followed by influx of anions such as Cl and malate2- (Sun et al., 2014), leading to an increase in guard cell volume and stomatal opening. Upon perception of closing signals such as high CO2, anion efflux depolarizes the membrane potential which provides a driving force for K+ efflux through outward K+ channels that are voltage-gated and opened by the depolarization, leading to stomatal closure. Besides these ions, other metabolites have been indicated as important osmolytes driving the osmotic changes in guard cells that lead to stomatal movement. Sugars, including sucrose, fructose and glucose, induce stomatal closure as signals (Kelly et al., 2013). Sucrose showed significant decreases at 10 min in our data

(Figure 2-4), consistent with its role as an osmoregulator, rather than a signal, during elevated CO2 induced stomatal closure. In addition, mannitol showed significant decreases at all the time points after elevated CO2 treatment (Table 2-4). Mannitol,

known to play an important role in salinity stress tolerance is also a likely osmoregulator during the elevated CO2 response (Ewert et al., 2000).

Malate showed significant increases during the one hour elevated CO2 treatment

(Figures 2-4). Organic acids such as malate and citrate are known to act as counter ions for K+ (Talbott and Zeiger, 1993). A malate transporter mutant atabcb14 was shown to be insensitive to elevated CO2-induced stomatal closure (Lee et al., 2008), indicating a possible role of malate as the messenger integrating mesophyll cell photosynthesis with stomatal movement. Other organic acids including citrate, isocitrate, and many acidic amino acids have been examined in opened and closed stomata induced by different conditions, and the results support the osmoregulation role of the organic acids (Outlaw and Lowry, 1977; Talbott and Zeiger, 1993). Furthermore, increased malate under blue and red light suggests its role as a counter ion and osmoregulator to induce the opening of stomata (Talbott and Zeiger, 1993). Under most conditions that trigger stomatal closure, malate in guard cells showed decreasing trends

(Araujo et al., 2011). This appears contradictory to our findings reported here. With the increase in CO2 concentration, the increase of phosphoenolpyruvate carboxylase activity may provide a boost to most of the metabolic pathways including the TCA cycle, as shown in Figure 2-4. Another possibility is starch degradation, which may lead to enhanced malate levels. These possibilities are worth testing in the future.

Nevertheless, during stomatal closure under elevated CO2, malate might not play a major function as an osmolyte. Citrate, mannitol, and sucrose could be the dominant players that contribute to stomatal osmotic changes under elevated CO2.

The Roles of ROS and Flavonoids in CO2-Induced Stomatal Closure

We observed increased ROS production accompanying stomatal closure under elevated CO2 (Figure 2-1). This result is consistent with a recent publication showing that the elevated CO2 induced ROS generation was abolished in NADPH respiratory burst oxidase mutants (Chater et al., 2015). ROS appear to be a common signaling component in CO2 and ABA induced stomatal closure. Using metabolomics, we observed perturbations of flavonoid levels in the course of stomatal closure (Figure 2-7).

Guard cells can be distinguished by their high flavonoid content and diversity as compared to other leaf cell-types (Schnabl et al., 1986; Weissenbock et al., 1984).

Flavonoids such as quercetin, apigenin, and kaempferol have been shown to accumulate in Arabidopsis guard cells relative to other cell types (Farag et al., 2008;

Naoumkina et al., 2007; Watkins et al., 2014). Furthermore, the role of flavonoids in plant cellular ROS amelioration is well-known (Agati et al., 2012). The consistently increased levels of several flavonoids (apigenin, luteolin, hesperetin, and ononin) throughout the time-course could be attributed to C-incorporation through pentose phosphate pathway leading to enhanced phenylpropanoid and hence flavonoid biosynthesis (Kunz et al., 2010; Wu et al., 2015). Flavonoid glycosides (mostly quercetin and kaempferol glycosides) could constitute a reservoir for flavonoids to quench the

ROS generated for redox homeostasis during the elevated CO2 treatments (Figure 2-1), thus showing a bell-shaped response along the time course. Recently, enhanced flavonol contents and decreased ROS levels in guard cells were correlated with a reduction of stomatal closure in response to ABA, indicating the role of flavonols in quenching the ABA-dependent ROS burst (Watkins et al., 2014). Moreover, elevated

CO2 progressively promoted the accumulation of flavonoids in both wheat seedlings and

strawberry fruits (Misra et al., 2015a). In this study, the dynamic changes of many flavonoids (and their conjugated derivatives) were measured in guard cells under elevated CO2. The results suggest the potential involvement of flavonoids as ROS scavengers (Watkins et al., 2014) in CO2 induced stomatal closure.

Lipids Are Involved in Elevated CO2-Induced Stomatal Movement

Lipids (especially phospholipids) are known to play critical functions in guard cells (Gilroy et al., 1990; Jung et al., 2002; Misra et al., 2015a; Ng et al., 2001). In our metabolomics data sets, a number of lipid metabolites were quantified, especially by untargeted UHPLC-QToF MS (Table 2-2). As elevated CO2 induces increased photosynthate accumulation, the increased flow of glucose towards acetyl-CoA biosynthesis for de novo fatty acid biosynthesis (unsaturated, very long chain, and long- chain fatty acids) would reasonably be expected. Similarly, associated changes in alpha-linoleates, sterols, fatty acids (unsaturated and long-chain ones), carotenoids and brassinosteroids are expected. While lipids are essential for membrane formation and energy storage, their role in stomatal signaling is also interesting (Misra et al., 2015a).

For example, polyunsaturated fatty acids such as linolenic acid and arachidonic acid enhance stomatal opening and inhibit stomatal closing (Youngsook et al., 1994), and diacylglycerols induce stomatal opening (Lee and Assmann, 1991). Lipid metabolites also act as secondary messengers that positively regulate guard cell ABA signaling and

ABA-induced stomatal closure (Gilroy et al., 1990; Jin et al., 2013; Jung et al., 2002; Ng et al., 2001). We show a clear increase in dodecanoic acid under elevated CO2 conditions in guard cells (Figure 2-5). Previously, straight chain fatty acids, such as decanoic and undecanoic acids, were shown to inhibit stomatal opening and cause

stomatal closure in epidermal strips of Commelina communis (Willmer et al., 1978). This result is consistent with our data on elevated CO2 induced stomatal closure.

Another line of evidence for involvement of lipid biosynthesis in guard cells during elevated CO2 induction is obtained from alpha-linolenic acid metabolites at 10 min, glycerophospholipid, alpha-linolenic acid, pantothenate and CoA, unsaturated fatty acids at 30 min, and glycerophospholipid, and fatty acids/unsaturated fatty acids at 60 min. (Figure 2-6). In fact, brassinolide, the most bioactive brassinosteroid form was shown to promote stomatal closure in Vicia faba (Haubrick et al., 2006), and high concentrations of epibrassinolide promoted stomatal closure in epidermal peels of

Solanum lycopersicon in the light (Xia et al., 2014b). Compared to previous studies (Jin et al., 2013), here we expanded the analysis of guard cell lipid metabolites and intermediates, for most of which functional assignments in guard cells are to be investigated in future studies.

JA Signaling Mediates High CO2-Induced Stomatal Closure

ABA is one of the most extensively studied phytohormones and many studies have focused on ABA signaling in guard cells (Kollist et al., 2014; Merilo et al., 2015;

Munemasa et al., 2015). Clearly, ABA plays an important role in stomatal functions.

However, our findings in B. napus guard cells as well as A. thaliana WT and CO2 signaling mutants showed that ABA levels did not significantly change under elevated

CO2 (Figure 2-10 and 11), thus indicating that ABA changes may not be required for

CO2-induced stomatal closure under elevated CO2. The result is consistent with a recent publication where elevated CO2 did not cause significant changes in ABA levels

(Chater et al., 2015). The role of ABA in elevated CO2 induced stomatal closure is highly controversial. In 2011, WT stomatal response to 800 ppm CO2 in a quadruple

mutant of ABA receptors was reported (Xue et al., 2011). Later, two groups (one used the same quadruple mutant and the other used a sextuple ABA receptor mutant) independently observed reduced stomatal responses to elevated CO2 in the ABA receptor mutants (Chater et al., 2015; Merilo et al., 2013). Interestingly, different ABA deficient mutants showed different CO2 responses, with aba1-1 and aba3-1 showing

WT-like responses (Merilo et al., 2013) versus nced3 nced5 unable to close as WT

(Chater et al., 2015) in response to elevated CO2. Although the conflicting results are enigmatic, together with our data it seems that a basal level of ABA rather than the changes of ABA may be important to potentiate the system for elevated CO2 responses in guard cells.

Our metabolomic data clearly showed significant increases in JA-biosynthesis pathway metabolites in guard cells of B. napus (Figure 2-8) and Arabidopsis WT guard cells under high CO2 conditions (Figure 2-10), and the CO2 signaling mutant ca1ca4 did not show the increase. The results reiterate that the CO2-response is not only JA- mediated but also may be a general mechanism within the Brassicaceae. MeJA treatment induced stomatal closure in epidermal peels possibly by inducing ROS production and cytosolic alkalization (Munemasa et al., 2014; Suhita et al., 2004). Thus, the common signaling nodes for JA and CO2 may include RBOHD/F, ROS production,

ABI2, and Ca2+ spiking (Kolla et al., 2007; Suhita et al., 2004) (Figure 2-12). In general, in plants grown under elevated CO2 SA production is increased, while JA pathway is usually repressed at the whole plant level (Vaughan et al., 2014; Zhang et al., 2015). In this study, JA biosynthesis pathway is shown to be significantly induced in guard cells after 10 min of elevated CO2 treatment (Figure 2-8). The impaired response of elevated

CO2 induced stomatal closure in the JA-Ile biosynthesis and signaling mutants jar1, coi1 and jin1 (Figure 2-9) supports our hypothesis that JA plays an essential role in stomatal closure induced by elevated CO2. Earlier investigations showed that the long-term effect of elevated CO2 caused plants to decrease JA levels (Sun et al., 2013). Yet, no study observed changes in JA levels during the short-term elevated CO2 treatment. Our data indicate the induction of JA production at very early time points of sensing elevated

CO2, unlike the long-term effect of lowered JA production. This discovery can also be attributed to our analysis of a single cell-type of guard cells (Misra et al., 2015a). The underlying molecular mechanisms of the JA induction by elevated CO2 are still unclear.

In fact, a guard cell-specific and ABA-independent oxylipin signaling pathway was recently reported in the context of pathogen infection (Montillet et al., 2013; Montillet and Hirt, 2013). Derived from complex membrane lipids, unesterified fatty acids are catalyzed by lipoxygenases into various oxylipin products, such as JA, fatty acid hydroperoxides, and reactive electrophilic oxylipins, which can also induce stomatal closure (Montillet et al., 2013). This induction of stomatal closure is independent of ABA signaling (Montillet et al., 2013). Based on these data and previous findings (Jin et al.,

2013; Li et al., 2015c), CO2 acts upstream of JA, and JA signaling is essential for guard cell responses and stomatal closure under elevated CO2 (Figure 2-12).

Table 2-1. MRM period method design Precursor Product Dwell Mode Period Metabolite name DP CE CXP ion ion time Positive 1 74.063 57 15 1-Methylguanidine hydrochloride 47 11 5 Positive 1 75.1 58.1 15 1,3,-Diaminopropane 32 14 7 Positive 1 76 59.1 15 Trimethylamine-N-oxide 43 10 5 Positive 1 89.1 72 15 1,4-Diaminobutane 35 11 5 Positive 1 89.9 44.1 15 Sarcosine 50 22 7 Positive 1 90 44 15 Alanine 35 21 6 Positive 1 101.9 56.1 15 1-aminocyclopropane-1-carboxylic acid 35 17 8 Positive 1 102.1 59.1 15 Betaine aldehyde 94 35 9 Positive 1 103 86.1 15 Cadaverine 33 10 5 Positive 1 104 58.1 15 N,N-Dimethylglycine 43 24 8 Positive 1 106 88 15 Diethanolamine 38 14 7 Positive 1 112 95 15 Histamine 38 22 6 Positive 1 112.043 43 15 Cytosine 61 33 12 Positive 1 114.9 69.9 15 5,6-Dihydrouracil 61 28 8 Positive 1 116 70 15 Proline 60 17 8 Positive 1 120 74 15 Threonine 32 13 5 Positive 1 122 104 15 Cysteine 40 15 7 Positive 1 125.8 96.9 15 2-aminoethylphosphonic acid 56 31 15 Positive 1 126 44.2 15 Taurine 58 16 9 Positive 1 126.1 109.1 15 1-Methylhistamine 37 21 8 Positive 1 132 85.9 15 4-Hydroxyl-L-proline 52 24 12 Positive 1 132 86 15 Leucine 40 9 5 Positive 1 132.1 86 15 Isoleucine 25 16 5 Positive 1 132.2 89.9 15 Creatine 27 35 10 Positive 1 133 69.9 15 L-Ornithine 40 28 11 Positive 1 133 70.1 15 N-Alpha-L-ornithine 74 26 11 Positive 1 133 74 15 Asparagine 40 28 5 Positive 1 133.1 87 15 Glutaric acid 47 18 8 Positive 1 138.3 95.1 15 1-Methylnicotinamide 94 36 13

Table 2-1. Continued Precursor Product Dwell Mode Period Metabolite name DP CE CXP ion ion time Positive 1 146.1 72.1 15 Spermidine 41 25 11 Positive 1 147 84 15 Lysine 40 13 17 Positive 1 147.1 84 15 Glutamine 60 25 5 Positive 1 148 84 15 Glutamic acid 35 25 5 Positive 1 148 88 15 O-Acetyl-L-serine 29 28 10 Positive 1 150 132 15 Triethanolamine 59 18 8 Positive 1 156 110 15 Histidine 40 14 8 Positive 1 159.1 116.2 15 Allantoin 26 15 13 Positive 1 169 134.1 15 Pyridoxine 63 31 10 Positive 1 170 107.1 15 Norepinephrine 29 53 12 Positive 1 170.085 96 15 3-Methyl-L-histidine 52 24 7 Positive 1 170.18 124 15 1-Methylhistidine 38 23 6 Positive 1 171.12 153.1 15 Methylthiobutyric acid 23 13 7 Positive 1 175 70 15 Arginine 30 33 11 Positive 1 175.1 88 15 Dehydroascorbic acid 34 28 9 Positive 1 175.11 157 15 cis-Aconitic acid 34 13 9 Positive 1 176.1 70 15 L-Citrulline 35 35 11 Positive 1 180 88 15 Tricine 34 22 7 Positive 1 182 56 15 L-Methionine sulfone 38 30 8 Positive 1 182 136 15 Tyrosine 40 20 8 Positive 1 183.1 147.1 15 D-Mannitol 24 13 7 Positive 1 203.2 112.1 15 Spermine 45 32 13 Positive 1 205 146 15 Tryptophan 43 12 15 Positive 1 223 134 15 Cystathione 40 10 6 Positive 1 223.1 134.1 15 L-Cystathionine 39 44 14 Positive 1 227.1 110.1 15 L-Carnosine 49 39 6 Positive 1 260 126 15 D-Glucosamine-6-phosphate 38 23 7 Positive 1 264.9 122 15 Thiamine 83 24 9 Positive 1 289.25 243 15 Eriodictyol 30 14 8

Table 2-1. Continued Precursor Product Dwell Mode Period Metabolite name DP CE CXP ion ion time Positive 2 110.1 63 40 Hypotaurine 60 30 9 Positive 2 112.92 96 30 Uracil 45 25 8 Positive 2 123 80 30 Niacinamide 55 11 8 Positive 2 124 96 30 Nicotinic acid 60 17 8 Positive 2 125.7 109 30 5-Methylcytosine 69 44 7 Positive 2 132 72.1 30 2-Guanidinopropionic acid 40 24 7 Positive 2 132.2 11 30 6-Amino caproic acid 40 12 9 Positive 2 132.2 89.9 15 Creatine 27 35 10 Positive 2 133 74 15 Asparagine 40 28 5 Positive 2 133.12 115 20 3-Ureidopropionic acid 26 10 8 Positive 2 134 74 30 Aspartic Acid 35 20 6 Positive 2 135 89 30 L-Malic Acid 19 10 7 Positive 2 135.88 119 30 Adenine 25 33 7 Positive 2 136.18 118 30 Homocysteine 41 11 9 Positive 2 136.2 56.1 40 Homocysteine 98 32 10 Positive 2 138.3 95.1 15 1-Methylnicotinamide 94 36 13 Positive 2 138.4 120 30 Anthranilic acid 42 32 7 Positive 2 138.5 93 30 4-Imidazoleacrylic acd 63 31 7 Positive 2 139.1 121.1 20 Salicylic acid 35 21 7 Positive 2 140.195 122 30 Tropinone 37 19 11 Positive 2 146.1 87.1 30 Acetylcholine 38 21 13 Positive 2 150 104 30 Metheonine 40 20 8 Positive 2 150.15 109 30 3-Methyladenine 62 24 10 Positive 2 151.6 135 30 Guanine 85 30 9 Positive 2 157 79 30 Orotic acid 47 36 10 Positive 2 168.12 150 30 2,3-Pyridinedicarboxylic acid 21 16 5 Positive 2 170.18 152 30 Pyridoxine 64 8 16 Positive 2 171.12 153.1 15 Methylthiobutyric acid 23 13 7 Positive 2 180.96 120.96 40 Acetylsalicylic acid 16 13 7

Table 2-1. Continued Precursor Product Dwell Mode Period Metabolite name DP CE CXP ion ion time Positive 2 198.1 107 20 3, 4-Dihydroxy-phenylalanine 52 41 7 Positive 2 220.1 101.9 20 O-Succinyl L-homoserine 72 32 10 Positive 2 244.085 112 20 Cytidine 37 17 8 Positive 2 248.1 150.1 40 Pyridoxal-5-phosphate 50 28 11 Positive 2 257.1 179 30 Melibiose 23 17 7 Positive 2 351.96 220.2 30 Zeatin riboside 22 25 7 Positive 2 387.1 171 30 1-Octacosanol 14 37 12 Positive 2 427.2 247.1 30 Abscisic acid glucose ester 30 17 7 Positive 2 542.04 524.2 30 Cyclic adenosine diphosphate ribose 53 22 7 Nicotinamide adenine dinucleotide Positive 2 766.08 644.04 30 43 23 7 phosphate Positive 3 62 44 40 Ethanolamine 30 8 4 Positive 3 76 30 30 Glycine 30 20 3 Positive 3 95.5 78 20 2-Hydroxypyridine 93 31 9 Positive 3 97.08 69 30 Guanidine 53 69 7 Positive 3 118 59 30 Betaine 56 11 9 Positive 3 127 109.9 30 Thymine 62 25 7 Positive 3 129.8 84 30 Pyroglutamic acid 40 20 7 Positive 3 138 121 30 Tyramine 30 12 8 Positive 3 146.3 114 20 4-Methyl-5-thiazol ethanol 47 50 7 Positive 3 154.14 136 20 3-Hydroxyanthranilic acid 29 10 9 Positive 3 155.04 137.04 30 2,3-Dihydroxybenzoic acid 44 22 7 Positive 3 161 144 30 Tryptamine 34 10 11 Positive 3 164.2 104 20 Homomethionine 35 29 7 Positive 3 166 120 30 Phenylalanine 28 16 7 Positive 3 177.1 115.1 20 Serotonin 27 38 9 Positive 3 178.1 103.9 30 N-formyl-L-methionine 36 24 13 Positive 3 195 138 30 Caffeine 55 10 16 Positive 3 216 81 30 6-Furfurylaminopurine 30 40 7

Table 2-1. Continued Precursor Product Dwell Mode Period Metabolite name DP CE CXP ion ion time Positive 3 216.3 81.1 30 Kinetin 49 32 14 Positive 3 220.08 202.1 30 Zeatin 41 21 7 Positive 3 222.2 126.1 30 N-acetyl-D-mannosamine 34 29 12 Positive 3 229.2 113.1 30 2-Deoxyuridine 32 45 6 Positive 3 245.069 113 20 Uridine 33 22 8 Positive 3 248.1 150.1 40 Pyridoxal-5-phosphate 50 28 11 Positive 3 252.1 136.1 20 2-Deoxyadenosine 43 25 9 Positive 3 268.2 152.1 30 2-Deoxyguanosine 43 36 7 Positive 3 268.24 136 20 Adenosine 56 25 11 Positive 3 269.23 137 30 Inosine 36 21 11 Positive 3 284 152 30 Guanosine 35 14 13 Positive 3 291.2 139.1 30 Catechin 45 27 10 Positive 3 291.1 139.1 30 Epicatechin 54 26 10 Positive 3 298.1 136.1 30 5-Deoxy-5-methylthio-adenosine 62 27 10 Positive 3 307.1 185 20 L-glutathione 73 44 9 Positive 3 308.04 179 30 Glutathione 36 22 7 Positive 3 308.4 179 30 glutathione reduced 21.73 22 7 Positive 3 332.1 136.1 20 2-Deoxyadenosine-5-monophosphate 47 26 10 Positive 3 346.08 152.04 30 Cyclic guanosine monophosphate 39 27 7 Positive 3 348.22 136.1 30 2-Deoxyguanosine-5-monophosphate 44 35 20 Positive 3 348.22 136 30 Adenosine-3-monophosphate 43 33 6 Positive 3 351.96 220.2 30 (6R)-5,6,7,8-Tetrahydrobiopterin 22 25 9 Positive 3 377.4 243 30 Riboflavin 63 24 11 Positive 3 433.3 271 30 Callistephin 14 35 13 Positive 3 442 295 30 Folic acid 41 28 7 Positive 3 613.2 355.1 20 Glutathione oxidized 47 35 7 Positive 4 131.04 113.04 30 Citraconic acid 15 13 7 Positive 4 149.04 131.1 30 Cinnamic acid 24 14 7 Positive 4 153.3 93.1 30 Vanillin 46 36 35

Table 2-1. Continued Precursor Product Dwell Mode Period Metabolite name DP CE CXP ion ion time Positive 4 162 118 30 Indole carboxylic acid 48 20 7 Positive 4 165.1 147 30 Coumaric acid 35 16 7 Positive 4 165.12 147 30 o-Hydroxycinnamic acid 25 16 7 Positive 4 167.2 106.9 40 3,4-Hydroxyphenylpropionic acid 20 47 12 Positive 4 176 129.9 30 3-Indole-acetic acid 53 26 8 Positive 4 179.062 133 40 4-Hydroxy-3-methoxycinnamaldehyde 27 16 3 Positive 4 190.08 130.1 20 Methyl indole acetate 44 16 7 Positive 4 195.12 177 30 Ferulic acid 32 17 7 Positive 4 199.9 141.1 30 Syringic acid 50 24 11 Positive 4 204.12 186.1 30 Indole butyric acid 26 20 7 Positive 4 206.1 189.1 30 Alpha-lipoamide 34 31 9 Positive 4 211.27 193 30 Jasmonic acid 39 12 10 Positive 4 233 174.1 30 Melatonin 42 35 9 Positive 4 235.2 86.1 30 Lidocaine 42 18 7 Positive 4 251.27 233 40 Gamma-Glu-Cys 47 15 5 Positive 4 257.2 137.1 30 Liquiritigenin 67 40 12 Positive 4 271.1 91 30 Genistein 36 49 6 Positive 4 287.1 137 30 Cyanidin 123 48 11 Positive 4 291.2 139.1 30 Catechin 45 27 10 Positive 4 291.1 139.1 30 Epicatechin 54 26 10 Positive 4 303.1 153.2 30 Alpha-lactose 42 39 7 Positive 4 347.28 311.2 40 Gibberellin A3 10.31 24 7 Positive 4 431.1 269.1 30 Ononin 28 32 22 Positive 4 449.38 287 30 Luteolin-7-beta-glucoside 51 21 12 Positive 4 481.2 445.4 30 Epibrassinolide 40 20 7 Positive 4 247.08 31.2 30 Abscisic acid 26 8 7 Positive 5 77.3 45 30 Cysteamine 32 23 10 Positive 5 123.1 79.1 30 Benzoic acid 32 17 7 Positive 5 131.1 42.1 30 Agmantine sulfate 41 23 11

Table 2-1. Continued Precursor Product Dwell Mode Period Metabolite name DP CE CXP ion ion time Positive 5 162.1 58.1 30 Carnitine 49 60 8 Positive 5 163.23 117 20 Nicotine 31 12 4 Positive 5 171.12 153.1 40 Methylthiobutyric acid 23 13 7 Positive 5 190.08 130.1 20 Methyl indole acetate 44 16 7 Positive 5 229.96 122.08 20 Buthionine-sulfoximine 32 22 7 Positive 5 243.09 127.1 30 Thymidine 30 13 7 Positive 5 285.1 267.2 40 Dihydrophaseic acid 32 13 7 Positive 5 285.2 213 30 Biochanin A 94 51 19 Positive 5 288.1 270.3 40 Retinol 47 36 7 Positive 5 300.5 281.9 30 Sphingosine 15 16 7 Positive 5 301.3 153 30 Kaempferide 94 51 12 Positive 5 306 137.1 30 Capsaicin 53 30 11 Positive 5 343.08 325.2 40 Sucrose 28 12 7 Positive 5 345.2 284.2 30 Eupatorin 30 45 9 Positive 5 380.3 264.2 30 Sphingosine-1-phosphate 34 29 7 Negative 1 75 47.1 40 Glycolic acid -27 -16 -15 Negative 1 103 59.2 40 Malonic acid -23 -15 -9 Negative 1 135 92 40 Hypoxanthine -64 -25 -6 Negative 1 173 93 40 Shikimic acid -51 -24 -15 Negative 1 184 78.8 40 O-phospho-L-serine -31 -34 -12 Negative 1 193.1 113.1 40 D-glucuronic acid -29 -28 -7 Negative 1 199.1 79 40 Dodecanoic acid -74 -61 -11 Negative 1 199.8 136 40 L-cysteine-S-sulfate -42 -27 -12 Negative 1 213.1 96.8 40 2-Deoxyribose-5-phosphate -43 -59 -12 Negative 1 228.9 96.9 40 D-ribose-5-phosphate -30 -34 -7 Negative 1 259 96.8 40 D-glucose-6-phosphate -44 -74 -12 Negative 1 259 96.9 40 D-mannose-6-phosphate -49 -40 -12 Negative 1 259.001 96.9 40 Alpha-D-mannose-1-phosphate -45 -25 -14 Negative 1 323.1 78.9 40 Uridine-5-monophosphate -87 -42 -12

Table 2-1. Continued Precursor Product Dwell Mode Period Metabolite name DP CE CXP ion ion time Negative 1 341 59.1 40 Maltose -27 -44 -9 Negative 1 341.1 79.2 40 Galactinol -20 -63 -15 Negative 1 341.2 101 40 Cellobiose -40 -34 -12 Negative 1 351.2 271.1 40 Xanthophyll -33 -11 -6 Negative 1 503 89.1 40 1-Kestose -62 -49 -13 Negative 1 503.4 179.1 40 Raffinose -104 -40 -13 Negative 2 102.9 56.9 40 2-Hydroxyiisobutyric acid -86 -15 -8 Negative 2 115.1 55 40 Sodium-3-methyl-2-oxobutyrate -63 -47 -7 Negative 2 115.1 70.9 40 Fumaric acid -29 -22 -10 Negative 2 116.9 55 40 Methylmalonic acid -34 -41 -9 Negative 2 117 73.1 40 Succinic acid -28 -18 -10 Negative 2 128.9 84.8 40 Mesaconic acid -12 -20 -9 Negative 2 131.1 87.1 40 Ethylmalonic acid -52 -34 -7 Negative 2 135 92 40 Hypoxanthine -64 -25 -6 Negative 2 137.12 93 40 4-Hydroxybenzoic acid -53 -8 -9 Negative 2 146.8 86.9 40 Citramalic acid -37 -21 -7 Negative 2 157.1 112.9 40 Dihydroorotic acid -87 -16 -10 Negative 2 159.1 96.8 40 Pimelic acid -54 -29 -6 Negative 2 165 65.9 40 3-Methyl-xanthine -63 -43 -10 Negative 2 167 121.9 40 Homogentisic acid -31 -33 -6 Negative 2 167.4 107.9 40 Vanillic acid -50 -20 -8 Negative 2 175 114.9 40 2-Isopropylmalic acid -29 -23 -14 Negative 2 179 135 40 Caffeic acid -43 -10 -3 Negative 2 202.1 131.9 40 6-Gamma-dimethylallylamino purine -47 -46 -8 Negative 2 251.1 134.9 44 2-Deoxyinosine -63 -31 -24 Negative 2 271 107.9 40 Arbutin -55 -38 -16 Negative 2 285 120.9 40 Salicin -25 -46 -21 Negative 2 323.1 78.9 40 Uridine-5-monophosphate -87 -42 -12 Negative 2 331.1 135 40 2-Deoxyinosine-5-Triphosphate -47 -45 -12

Table 2-1. Continued Precursor Product Dwell Mode Period Metabolite name DP CE CXP ion ion time Negative 2 353 191 40 Chlorogenic Acid -51 -20 -11 Negative 2 359.3 160.9 40 Rosmarinic acid -62 -25 -10 Negative 2 388.5 195.2 40 8-Nitroguanosine 3,5-cyclic -95 -32 -7 monophosphate Negative 2 427 134.9 40 Inosine-5-diphosphate -61 -36 -7 Negative 2 431.2 311 40 Vitexin -74 -38 -12 Negative 2 440.1 174.8 40 Dihydrofolic acid -76 -54 -10 Negative 2 455.1 255 40 Riboflavin-5-mono-phosphate -46 -43 -10 Negative 2 579.53 271.5 40 Naringin -29 -50 -7 Negative 2 593.3 269.3 40 Pelargonin -85 -43 -17 Negative 2 609 300 40 Rutin -10 -54 -6 Negative 3 108.9 91 40 Pyrocatechol -61 -27 -10 Negative 3 137.9 107.9 40 4-Nitrophenol -58 -33 -17 Negative 3 150.5 107 40 4-Hydroxyphenylacetic acid -31 -33 -6 Negative 3 151 107 40 Adonitol -42 -30 -7 Negative 3 151 107.1 40 2-Hydroxyphenylacetic acid -21 -20 -5 Negative 3 151.1 107 40 Mandelic acid -64 -14 -10 Negative 3 151.1 107.9 40 Xanthine -48 -25 -10 Negative 3 163.1 119.1 40 2-Hydroxycinnamic acid -50 -20 -8 Negative 3 167 122.9 40 3, 4-Dihydroxy-phenylacetic acid -24 -31 -10 Negative 3 176.7 59 40 Gulonic acid gamma lactone -46 -31 -9 Negative 3 177 103 40 6-methoxy cinnamic acid -30 -16 -6 Negative 3 177 133 40 6,7-Dihydrxy coumarin -55 -15 -11 Negative 3 191 175 40 Scopoletin -35 -9 -30 Negative 3 193 133 40 3-Hydroxy-4-methoxycinnamic acid -49 -40 -23 Negative 3 237 208 40 Daidzein -92 -45 -9 Negative 3 237.2 90.9 40 7-Hydroxyflavone -30 -45 -9 Negative 3 237.2 101 40 6-Hydroxyflavone -79 -47 -6 Negative 3 255.1 209.1 40 Isoliquiritigenin -44 -12 -16

Table 2-1. Continued Precursor Product Dwell Mode Period Metabolite name DP CE CXP ion ion time Negative 3 269.1 116.9 40 Apigenin -86 -50 -9 Negative 3 271.1 150.8 40 Naringenin -60 -29 -7 Negative 3 285.2 133 40 Luteolin -73 -48 -7 Negative 3 301.24 273 40 Quercetin -70 -28 -8 Negative 3 301.3 135.9 40 Hesperetin -84 -48 -10 Negative 3 317.23 151 40 Myricetin -65 -10 -3 Negative 3 339.1 182.9 40 Lignoceryl alcohol -39 -63 -10 Negative 3 341.1 182.8 40 Isomaltose -29 -56 -9 Negative 3 367.3 133.9 40 Curcumin -64 -49 -7 Negative 3 431.1 268 40 Apigenin-7-glucoside -66 -48 -17 Negative 3 447.2 300 40 Chlorophyll A -78 -43 -12 Negative 3 447.3 300.1 40 Quercitrin -77 -40 -10 Negative 3 579.53 271.5 40 Naringin -29 -50 -7 Negative 3 593.9 269.9 40 Pelargonin -85 -43 -17 Negative 3 609.4 301.1 40 Neohesperidin -16 -54 -12

Table 2-2. Information of metabolite detected in Brassica napus guard cells Detection KEGG PubChem Molecular Retention Metabolite Name Platform ID ID weight time

UPLC-MS 1-Palmitoylglycerol 3-Phosphate C04036 46173172 408.471 34.37

UPLC-MS (9Z)-12-Oxo-Dodec-9-Enoate C16311 25243932 211.280 12.42

UPLC-MS Traumatin C16309 15388629 211.280 28.34

UPLC-MS 16-Hydroxypalmitate NA 7058075 271.419 28.41

UPLC-MS 18-Hydroxyoleate C19616 86289578 297.457 22.31

UPLC-MS 18-Oxo-Oleate NA 90657874 295.441 22.99

UPLC-MS 2-Oxindole-3-Acetyl-L-Aspartate NA 90659281 304.259 16.34

UPLC-MS 2-Oxo-5-Methylthiopentanoate C17211 25203687 161.195 0.53

UPLC-MS 3-Beta-D-Galactosyl-Sn-Glycerol C05401 16048618 254.236 14.73

UPLC-MS 4-Amino-4-Deoxychorismate C11355 45266632 224.193 14.02

UPLC-MS 5,10-Methenyltetrahydrofolate C00445 46878371 454.421 24.87

UPLC-MS 5-Hydroxy-Coniferaldehyde C12204 5282094 194.187 13.43

UPLC-MS 5-Hydroxyisourate C11821 250388 184.111 0.53

UPLC-MS 9,10-Epoxy-18-Hydroxystearate C19620 25245732 313.456 24.47

UPLC-MS Acryloyl-Coa C00894 45266595 817.551 0.63

UPLC-MS Geranylfarnesyl Diphosphate C04217 25244051 515.542 31.39

UPLC-MS Androstenedione C00280 6128 286.413 33.09

UPLC-MS Arachidate C06425 5461017 311.527 33.89

UPLC-MS Benzaldehyde C00261 240 106.124 4.23

UPLC-MS Chlorophyll B C05307 11593175 907.486 24.78

UPLC-MS 16-Oxo-Palmitate C19614 25202344 269.403 32.32

UPLC-MS (9R,10S)-Dihydroxystearate C19622 25201835 315.472 3.94

UPLC-MS Indole-3-Acetyl-Glycine NA 6921768 231.230 3.37

UPLC-MS (-)-Jasmonoyl-L-Isoleucine C18699 1.24E+08 322.423 31.06

UPLC-MS Salicin C01451 439503 286.281 26.74

UPLC-MS 16-Feruloyloxypalmitate C18217 44237331 447.590 28.65

UPLC-MS Stigmasterol 3-O-Beta-D-Glucoside NA 44237224 574.840 33.14

UPLC-MS 4-Methylumbelliferyl Glucoside NA 2733779 338.313 2.35

UPLC-MS 24-Epicathasterone-22-O-Sulfate NA 45479391 511.736 31.41

Table 2-2. Continued Detection KEGG PubChem Molecular Retention Metabolite Name Platform ID ID weight time

UPLC-MS 13-Hydroxy-Alpha-Tocopherol NA 45479210 446.712 34.36

UPLC-MS 26,27-Dehydrozymosterol NA 46173326 382.628 30.01

UPLC-MS 6-Methylthiohexylhydroximoyl-Glutathione NA 90659350 465.559 11.20 Indole-3-Acetonitrile-Gamma-Glutamylcysteine

UPLC-MS NA 49859671 403.432 13.13 Conjugate

UPLC-MS 2,5-Dihydroxybenzoate 5-O-Beta-D-Glucoside NA 54726827 315.256 3.95

UPLC-MS 1,2-Dipalmitoyl-Phosphatidylglycerol-Phosphate NA 49859597 799.934 33.54

UPLC-MS Phylloquinol C03313 90658882 452.719 13.96

UPLC-MS (9Z)-12,13-Dihydroxyoctadeca-9-Enoate NA 52940209 313.456 22.03

UPLC-MS 22-Oxo-Docosanoate C19624 52940144 353.564 34.96

UPLC-MS Docosanedioate C19625 22173968 368.556 32.31

UPLC-MS 13-Apo-Beta-Carotenone C20696 5363697 258.403 31.73

UPLC-MS (3R, 7S)-12-Hydroxy-Jasmonoyl-L-Isoleucine NA 54758637 338.423 28.57

UPLC-MS 1-Naphthol Glucoside NA 7573796 306.315 13.82

UPLC-MS (+)-5-Deoxystrigol C18037 15102684 330.380 5.48

UPLC-MS 4-Hydroxy-2-Nonenal-[Cys-Gly] Conjugate NA 90659346 334.430 19.70

UPLC-MS Ajmaline C06542 441080 326.438 25.76

UPLC-MS 5,8,11,14-Eicosatetraynoate C00219 18544330 295.400 22.99

UPLC-MS Quercetin-3-Gentiobioside NA 90657242 626.524 4.11

UPLC-MS Quercetin-3-Gentiotrioside NA 5319886 788.666 2.01

UPLC-MS Kaempferol-3-Gentiobioside NA 9960512 610.524 2.33

UPLC-MS 6C-Glucosyl-2-Hydroxynaringenin NA 90657396 450.398 16.88

UPLC-MS 3-Hydroxy-Decanoyl-Coa C05264 7651 933.753 2.96

UPLC-MS Salicyl Alcohol C02323 5146 124.139 0.61

UPLC-MS 1-18:1-2-Trans-16:1-Phosphatidylglycerol NA 90658021 745.992 32.59

UPLC-MS 1-18:2-2-Trans-16:1-Phosphatidylglycerol NA 90657478 743.977 31.74

UPLC-MS 1-18:3-2-Trans-16:1-Phosphatidylglycerol NA 90658485 741.961 28.64

UPLC-MS 1-18:2-2-16:2-Monogalactosyldiacylglycerol NA 86290020 751.052 23.06

UPLC-MS 1-18:3-2-16:3-Monogalactosyldiacylglycerol NA 90659307 747.020 32.57

Table 2-2. Continued Detection KEGG PubChem Molecular Retention Metabolite Name Platform ID ID weight time

UPLC-MS 2-Trans-Hexadecenal C06123 5280541 238.412 15.48

UPLC-MS 17-Beta-Estradiol C00951 5757 272.386 28.40

UPLC-MS Norajmaline C11810 24893138 312.411 24.51

UPLC-MS N-Glucosylnicotinate C03003 439878 285.253 3.51

UPLC-MS 5-Alpha-Cholesta-8,24-Dien-3-One NA 22298942 382.628 30.01

UPLC-MS Prephytoene Diphosphate C03427 25245670 719.897 32.48

UPLC-MS Presqualene Diphosphate C03428 25244634 583.660 30.78

UPLC-MS Mevalonate 5-Phosphate C01107 25244548 225.115 25.78 (9Z,11E,14Z)-(13S)-Hydroperoxyoctadeca-(9,11,14)-

UPLC-MS NA 9548586 309.425 23.76 Trienoate

UPLC-MS (-)-Jasmonic Acid C08491 7251181 209.264 6.77

UPLC-MS 5-Beta-Pregnan-3,20-Dione C05479 92745 316.483 21.44

UPLC-MS Castasterone C15794 25203131 464.684 33.69

UPLC-MS 24-Methylenecycloartanol C08830 90658794 440.751 34.33

UPLC-MS (R)-3-(3,4-Dihydroxyphenyl)Lactate NA 25203144 197.167 0.63

UPLC-MS Delphinidin C05908 25203213 301.232 4.18

UPLC-MS 3-Dehydroteasterone C15792 25202373 446.669 32.12

UPLC-MS Typhasterol C15793 25200584 448.685 28.63

UPLC-MS 8-Apo-Beta-Carotenal C19728 5478003 416.645 30.26 (9Z,11E,15Z)-(13S)-Hydroperoxyoctadeca-9,11,15-

UPLC-MS C04785 45266757 309.425 20.85 Trienoate

UPLC-MS 12,13-(S)-Epoxylinolenate C04672 25244010 291.409 22.04

UPLC-MS 3-Oxo-2-(Cis-2-Pentenyl)-Cyclopentane-1-Octanoate C04780 25244083 293.425 23.88

UPLC-MS Coumarinate C05838 54714352 163.152 4.22

UPLC-MS Malonylshisonin C16299 90657833 841.709 36.49

UPLC-MS Tetradecanoic Acid C06424 4075158 227.366 28.51

UPLC-MS 22-Hydroxydocosanoate C19623 17802799 355.580 25.06

UPLC-MS 1-18:1-2-16:3-Monogalactosyldiacylglycerol NA 90657729 751.052 23.06

UPLC-MS (+)-7-Iso-Jasmonate C16317 7251182 209.264 6.76

Table 2-2. Continued Detection KEGG PubChem Molecular Retention Metabolite Name Platform ID ID weight time

UPLC-MS 1-18:3-2-18:3-Digalactosyldiacylglycerol NA 90658449 937.216 33.59

UPLC-MS 1-18:2-2-18:2-Digalactosyldiacylglycerol NA 90657438 941.247 34.45

UPLC-MS 1-18:2-2-16:0-Phosphatidylglycerol NA 90658491 745.992 32.27

UPLC-MS 1-18:3-2-16:0-Phosphatidylglycerol NA 90657393 743.977 33.35

UPLC-MS 1-18:3-2-16:0-Digalactosyldiacylglycerol NA 90657885 915.209 34.43

UPLC-MS 1-18:2-2-18:2-Monogalactosyldiacylglycerol NA 90657255 779.105 33.78

UPLC-MS Protochlorophyll A NA 25245458 868.190 32.98

UPLC-MS Petroselinate C08363 5461010 281.457 25.48

UPLC-MS Crocetin Dialdehyde C19730 11109238 296.408 25.16

UPLC-MS 9-Oxo-Nonanoate C16322 21270557 171.216 21.11

UPLC-MS 3-Methoxybenzaldehyde NA 11569 136.150 23.05

UPLC-MS Palmitoleate C08362 5461012 253.404 29.73

UPLC-MS 3,5-Dihydroxyanisole NA 71648 140.138 12.03

UPLC-MS Geranyl Acetate C09861 1549026 196.289 0.62

UPLC-MS Alpha-Allenylagmatine NA 19773255 168.241 13.26

UPLC-MS Carboxymethyl-Coa NA 44123415 820.531 2.29

UPLC-MS 1-Monopalmitoylethylene Glycol NA 20201 300.481 31.71

UPLC-MS 2-Monooleoylglycerol NA 5319879 356.545 25.04

UPLC-MS 1,3-Dioctanoylglycerol NA 44237238 330.464 13.61

UPLC-MS 1-Octadecanoyl-Sn-Glycerol 3-Phosphate NA 49859619 436.524 9.41

UPLC-MS Methyl Jasmonate C11512 5367719 224.299 17.70

UPLC-MS Kaempferol-3-O-Gentiobioside-7-O-Rhamnoside NA 25203808 756.667 6.08

UPLC-MS Quercetin 3-O-Glucoside C05623 25203368 463.374 4.18

UPLC-MS Kaempferol-3-Glucoside C12249 25203515 447.374 2.33

UPLC-MS Pregn-5-Ene-3,20-Dione-17-Ol NA 14562950 330.466 13.61

UPLC-MS Pregn-5-Ene-3,20-Dione NA 150901 314.467 22.04

UPLC-MS 2-Oxo-6-Methylthiohexanoate C17216 44237195 175.222 0.54 Phosphatidylglycerophosphate (1-Octadecenoyl(9Z),

UPLC-MS NA 90658639 825.972 34.50 2-Palmitoyl)

Table 2-2. Continued Detection KEGG PubChem Molecular Retention Metabolite Name Platform ID ID weight time

UPLC-MS Castasterone-23-O-Glucoside NA 90657427 626.826 33.53

UPLC-MS Brassinolide-23-O-Glucoside NA 90658531 642.826 33.46

UPLC-MS Enol-Phenylpyruvate C02763 54705603 163.152 2.35

UPLC-MS Flavin Adenine Dinucleotide C00016 46906035 782.533 2.49

UPLC-MS Fecosterol C04525 440371 398.671 30.18

UPLC-MS Formononetin C00858 5280378 268.268 21.39

UPLC-MS Glutathione Reduced C00051 7048684 306.313 13.51

UPLC-MS Glycerophosphoglycerol C03274 25202983 245.146 24.91 (5Z)-(15S)-11-Alpha-Hydroxy-9,15-Dioxoprosta-13-

UPLC-MS C04707 25244714 349.446 21.95 Enoate

UPLC-MS Inosine C00294 6021 268.229 4.55

UPLC-MS L-1-Glycerophosphorylethanolamine C01233 70678815 215.142 3.33

UPLC-MS 1-Oleyl-2-Lyso-Phosphatidate C00416 46173225 434.509 19.69

UPLC-MS Lauroyl-Coa C01832 25113193 945.808 3.73

UPLC-MS Linoleate C01595 5460332 279.442 23.52

UPLC-MS 4-Coumaroylagmatine C04498 25245514 277.345 14.72

UPLC-MS 1-Naphthol C11714 7005 144.173 13.47

UPLC-MS (9Z)-Octadecenoic Acid C00712 5460221 281.457 32.08

UPLC-MS Glutathione Oxidized C00127 40467895 610.610 4.84

UPLC-MS Hexadecanoic Acid C00249 504166 255.420 24.72

UPLC-MS Phenylalanine C00079 6925665 165.191 1.22

UPLC-MS Phenylacetaldehyde C00601 998 120.151 2.24

UPLC-MS Phenylglyoxal NA 14090 134.134 4.23

UPLC-MS Phosphoryl-Ethanolamine C00346 7059434 140.055 24.71

UPLC-MS Phytosphingosine 1-Phosphate NA 57339286 396.483 32.89

UPLC-MS Pristanate NA 20849056 297.500 33.41

UPLC-MS L-Quinate C00296 1560034 191.160 1.65

UPLC-MS R-4-Phosphopantothenoyl-L-Cysteine C04352 25245609 399.332 5.64 UPLC-MS (S)-Coclaurine C06161 46878403 286.350 6.34

Table 2-2. Continued Detection KEGG PubChem Molecular Retention Metabolite Name Platform ID ID weight time

UPLC-MS Sinapyl Alcohol C02325 5280507 210.229 6.76

UPLC-MS Sphingosine C00319 46878424 300.504 33.41

UPLC-MS Octadecanoic Acid C01530 3033836 283.473 33.10

UPLC-MS Strictosidine C03470 44123291 531.581 27.66

UPLC-MS Taxa-4,11-Diene C11894 443484 272.473 32.32

GC-MS Myo-inositol C00137 892 180.157 29.55

GC-MS Beta-Sitosterol C01753 222284 414.713 45.41

GC-MS Stearic Acid C01530 3033836 283.473 32.44

GC-MS Sucrose C00089 5988 342.299 36.94

GC-MS Hexadecanoic Acid C00249 504166 255.420 29.46

GC-MS Xylose C01394 4585 150.130 22.46

GC-MS Ribose C00121 5779 150.130 22.46

GC-MS Sorbose C01452 1101 180.156 26.07

GC-MS Mannitol C00392 6251 182.173 27.03

GC-MS Cellobiose C06422 10712 342.299 37.78

GC-MS Malate C00149 5459792 132.073 19.21

GC-MS Citrate C00158 31348 189.101 25.40

GC-MS Phosphate C00009 3681305 95.979 14.24

GC-MS Threonate C01620 21145021 135.096 20.54

GC-MS Xylitol C00379 6912 152.147 23.47

GC-MS Glycerol C00116 753 92.094 14.20

GC-MS Proline C00148 6971047 115.132 14.83

GC-MS Ethanolamine C00189 444693 62.091 13.75

GC-MS Campesterol C01789 23424736 400.687 44.55

GC-MS Lactose C00243 84571 342.299 37.76

GC-MS Glucose C00031 5793 180.157 26.48

GC-MS Glycine C00037 5257127 75.067 14.95

GC-MS Glucuronate C00191 16740916 194.139 27.27

GC-MS Mannose C00159 18950 180.156 26.79

Table 2-2. Continued Detection KEGG PubChem Molecular Retention Metabolite Name Platform ID ID weight time

GC-MS (9E)-Octadecenoic Acid C00712 5460221 281.457 32.02

GC-MS Threonine C00188 6971019 119.120 16.86

GC-MS Lyxose C00476 65550 150.131 22.46

GC-MS Pyroglutamate C01879 5289118 128.107 20.11

GC-MS Erythronic Acid NA 2781043 136.103 20.54 GC-MS Cholesterol C00187 5997 386.660 43.46

GC-MS Serine C00065 6857581 105.093 16.31

GC-MS Benzoate C00180 242 121.115 13.84

GC-MS Eicosanoic Acid C06425 5461017 311.527 35.14

GC-MS Valine C00183 6971018 117.147 12.65

GC-MS Fructose C00095 439709 180.157 26.24

GC-MS Galactose C00124 439357 180.156 26.46

GC-MS Norvaline C01826 6950514 117.147 12.65

GC-MS Cysteamine C01678 3799953 78.152 13.92

GC-MS Linoleate C01595 5460332 279.442 31.94

GC-MS Phytol C01389 5280435 296.535 31.29

GC-MS Alpha-Linolenate C06427 5461005 277.426 32.05

GC-MS Leucine C00123 7045798 131.174 14.30

GC-MS Glycerol-3-Phosphate C00093 7048686 170.058 24.53

GC-MS Aspartate C00049 5460294 132.096 19.87

HPLC-MRM 1,3-Diaminopropane C00986 4030255 76.141 4.25

HPLC-MRM 1,4-Diaminobutane C00134 3452892 90.168 4.39

HPLC-MRM Sarcosine C00213 7311726 89.094 5.27

HPLC-MRM Alanine C00041 7311724 89.094 4.97

HPLC-MRM Betaine Aldehyde C00576 249 102.156 4.91

HPLC-MRM Cadaverine C01672 3718401 104.195 4.42

HPLC-MRM N,N-Dimethylglycine C01026 6971056 103.121 5.12

HPLC-MRM Histamine C00388 25201573 112.154 4.62

HPLC-MRM Cytosine C00380 597 111.103 4.31

Table 2-2. Continued Detection KEGG PubChem Molecular Retention Metabolite Name Platform ID ID weight time

HPLC-MRM 5,6-Dihydrouracil C00429 649 114.104 5.40

HPLC-MRM Threonine C00188 6971019 119.120 5.04

HPLC-MRM Cysteine C00097 6419722 121.154 4.84

HPLC-MRM Taurine C00245 4068592 125.142 4.92

HPLC-MRM Trans-4-Hydroxyl-L-Proline C01157 6971053 131.131 5.07

HPLC-MRM Leucine C00123 7045798 131.174 4.36

HPLC-MRM Isoleucine C00407 7043901 131.174 5.07

HPLC-MRM L-Ornithine C00077 6992088 133.170 4.47

HPLC-MRM Asparagine C00152 6992089 132.119 4.88

HPLC-MRM 1-Methylnicotinamide C02918 457 137.161 6.06

HPLC-MRM Spermidine C00315 6992097 148.271 4.20

HPLC-MRM Lysine C00047 5460926 147.197 4.47

HPLC-MRM Glutamine C00064 6992086 146.146 5.00

HPLC-MRM Glutamic Acid C00025 5460299 146.122 5.18

HPLC-MRM O-Acetyl-L-Serine C00979 25245438 147.130 5.26

HPLC-MRM Triethanolamine C06771 3777650 150.197 4.98

HPLC-MRM Histidine C00135 6971009 155.156 4.30

HPLC-MRM Allantoin C01551 204 158.116 5.53

HPLC-MRM 3-Methyl-L-Histidine C01152 64969 169.183 4.82

HPLC-MRM Methylthiobutyric Acid C01180 473 148.180 4.30

HPLC-MRM Arginine C00062 1549073 175.210 4.83

HPLC-MRM Dehydroascorbic Acid C05422 15558810 174.110 4.31

HPLC-MRM Cis-Aconitic Acid C00417 5459816 171.086 4.30

HPLC-MRM L-Citrulline C00327 6992098 175.187 5.32

HPLC-MRM L-Methionine Sulfone NA 7020882 182.171 4.37

HPLC-MRM Tyrosine C00082 6942100 181.191 4.33

HPLC-MRM Mannitol C00392 6251 182.173 5.13

HPLC-MRM Spermine C00750 446718 206.374 4.76

HPLC-MRM Tryptophan C00078 6923516 204.228 5.09

Table 2-2. Continued Detection KEGG PubChem Molecular Retention Metabolite Name Platform ID ID weight time

HPLC-MRM L-Cystathionine C02291 25243997 222.259 2.30

HPLC-MRM D-Glucosamine-6-Phosphate C00352 45266742 258.144 4.92

HPLC-MRM Thiamine C00378 1130 265.352 5.51

HPLC-MRM Eriodictyol C05631 90657147 287.248 4.28

HPLC-MRM Oxaloacetic Acid C00036 164550 130.057 4.99

HPLC-MRM Glyceraldehyde 3-Phosphate C00118 24794350 168.043 5.26

HPLC-MRM Fructose 6-Phosphate C00085 21114947 258.121 5.00

HPLC-MRM Fructose 1,6-Bisphosphate C00354 5460765 336.085 5.32

HPLC-MRM Hypotaurine C00519 25244088 109.143 7.68

HPLC-MRM Uracil C00106 1174 112.088 9.95

HPLC-MRM Nicotinamide C00153 936 122.126 11.19

HPLC-MRM Nicotinic Acid C00253 937 122.103 9.60

HPLC-MRM 5-Methylcytosine C02376 65040 125.130 7.06

HPLC-MRM 3-Ureidopropionic Acid C02642 6971254 131.111 9.02

HPLC-MRM Aspartic Acid C00402 5460295 132.096 6.19

HPLC-MRM L-Malic Acid C00149 5459792 132.073 7.34

HPLC-MRM Adenine C00147 190 135.128 9.84

HPLC-MRM Homocysteine C00155 6971015 135.181 7.31

HPLC-MRM Anthranilic Acid C00108 5459842 136.130 6.11

HPLC-MRM Salicylic Acid C00805 54675850 137.115 12.53

HPLC-MRM Tropinone C00783 3551155 140.205 12.47

HPLC-MRM Acetylcholine C01996 187 146.209 7.44

HPLC-MRM Metheonine C00073 6992087 149.207 9.48

HPLC-MRM Guanine C00242 764 151.127 10.24

HPLC-MRM Orotic Acid C00295 1492348 155.090 7.65

HPLC-MRM 2,3-Pyridinedicarboxylic Acid C03722 5460301 165.105 11.25

HPLC-MRM Pyridoxine C00314 1054 169.180 6.40

HPLC-MRM Acetylsalicylic Acid C01405 3434975 179.152 7.57

HPLC-MRM O-Succinyl L-Homoserine C01118 46878420 218.186 8.48

Table 2-2. Continued Detection KEGG PubChem Molecular Retention Metabolite Name Platform ID ID weight time

HPLC-MRM Cytidine C00475 6175 243.219 10.18

HPLC-MRM Pyridoxal-5-Phosphate C00018 644168 245.128 11.76

HPLC-MRM Melibiose C05402 11458 342.299 7.69

HPLC-MRM Abscisic Acid Glucose Ester C15970 46173811 426.463 6.57

HPLC-MRM Phosphoenolpyruvic Acid C00074 3674425 165.019 11.22

HPLC-MRM Ribulose 5-Phosphate C00199 21144996 228.095 13.39

HPLC-MRM Betaine C00719 247 117.147 23.30

HPLC-MRM Thymine C00178 1135 126.115 19.12

HPLC-MRM Pyroglutamic Acid C01879 5289118 128.107 16.97

HPLC-MRM Tyramine C00483 5249538 138.189 17.28

HPLC-MRM 2,3-Dihydroxybenzoic Acid C00196 54675818 153.114 20.13

HPLC-MRM Tryptamine C00398 3985862 161.226 22.46

HPLC-MRM Homomethionine C17213 90659289 163.234 17.22

HPLC-MRM Phenylalanine C00079 6925665 165.191 19.33

HPLC-MRM Serotonin C00780 4048638 177.225 21.49

HPLC-MRM N-Formyl-L-Methionine C03145 5288223 176.210 20.06

HPLC-MRM Caffeine C07481 2519 194.193 23.17

HPLC-MRM 6-Furfurylaminopurine NA 10471 215.211 22.84

HPLC-MRM Kinetin C08272 3830 215.214 22.85

HPLC-MRM Zeatin C00371 449093 219.246 19.64

HPLC-MRM N-Acetyl-D-Mannosamine C00645 11096158 221.210 19.39

HPLC-MRM 2-Deoxy Uridine C00526 13712 228.204 17.64

HPLC-MRM Uridine C00299 6029 244.204 16.90

HPLC-MRM 2-Deoxyadenosine C00559 13730 251.244 17.58

HPLC-MRM 2-Deoxyguanosine C00330 187790 267.244 18.09

HPLC-MRM Adenosine C00212 60961 267.244 17.40

HPLC-MRM Inosine C00294 6021 268.229 17.39

HPLC-MRM Guanosine C00387 6802 283.243 17.80

HPLC-MRM 5-Deoxy-5-Methylthio-Adenosine C00170 439176 297.331 20.72

Table 2-2. Continued Detection KEGG PubChem Molecular Retention Metabolite Name Platform ID ID weight time

HPLC-MRM Glutathione Reduced C00051 7048684 306.313 16.94

HPLC-MRM 2-Deoxyadenosine-5-Monophosphate C00360 22848660 329.208 16.48

HPLC-MRM Cyclic Guanosine Monophosphate C00942 16727415 344.200 17.26

HPLC-MRM 2-Deoxyguanosine-5-Mono Phosphate C00362 6994968 345.208 17.37

HPLC-MRM Adenosine-3-Monophosphate C01367 15938966 345.208 17.37

HPLC-MRM (6R)-5,6,7,8-Tetrahydrobiopterin C00272 1125 241.249 21.49

HPLC-MRM Riboflavin C00255 45480541 375.360 23.07

HPLC-MRM Callistephin C12137 443649 432.383 22.89

HPLC-MRM Folic Acid C00504 1549092 439.387 21.59

HPLC-MRM Glutathione Oxidized C00127 40467895 610.610 16.94

HPLC-MRM Cinnamic Acid C00423 5957728 147.153 32.98

HPLC-MRM Vanillin C00755 1183 152.149 27.55

HPLC-MRM Indole Carboxylic Acid C19837 69867 161.157 28.83

HPLC-MRM Coumaric Acid C00811 54708745 163.152 27.96

HPLC-MRM 3,4-Hydroxyphenylpropionic Acid C01744 10394 181.168 26.79

HPLC-MRM 3-Indole-Acetic Acid C00954 801 174.179 30.20

HPLC-MRM Methyl Indole Acetate C05660 18986 205.213 26.39

HPLC-MRM Ferulic Acid C01494 54691413 193.179 27.55

HPLC-MRM Indole Butyric Acid C11284 3702659 202.232 30.94

HPLC-MRM Alpha-Lipoamide C00248 6992093 205.333 31.14

HPLC-MRM Jasmonic Acid C08491 7251181 209.264 33.68

HPLC-MRM Melatonin C01598 896 232.282 28.94

HPLC-MRM Liquiritigenin C09762 114829 256.257 29.58

HPLC-MRM Genistein C06563 25201420 269.233 35.09

HPLC-MRM Cyanidin C05905 25202542 285.232 24.53

HPLC-MRM Epicatechin C09727 72276 290.272 23.32

HPLC-MRM Alpha-Lactose C00243 84571 342.299 25.66

HPLC-MRM Gibberellin A3 C01699 25200591 345.371 27.10

HPLC-MRM 4-Hydroxy-3-Methoxycinnamaldehyde C02666 5280536 178.187 29.82

Table 2-2. Continued Detection KEGG PubChem Molecular Retention Metabolite Name Platform ID ID weight time

HPLC-MRM Ononin C10509 442813 430.410 28.29

HPLC-MRM Luteolin-7-Beta-Glucoside C03951 5280637 448.382 26.59

HPLC-MRM Glycolic Acid C00160 5460308 75.044 6.04

HPLC-MRM Malonic Acid C00383 9084 102.046 7.92

HPLC-MRM Hypoxanthine C00262 790 136.113 14.63

HPLC-MRM Shikimic Acid C00493 7057976 173.145 7.81

HPLC-MRM O-Phospho Serine C01005 7059387 183.057 4.91

HPLC-MRM Dodecanoic Acid C02679 4149208 199.312 5.80

HPLC-MRM 2-Deoxyribose-5-Phosphate C00673 25245723 212.096 4.16

HPLC-MRM D-Ribose-5-Phosphate C00117 24794349 228.095 5.05

HPLC-MRM D-Glucose-6-Phosphate C01172 21604865 258.121 5.27

HPLC-MRM D-Mannose-6-Phosphate C00275 25244236 258.121 4.98

HPLC-MRM Uridine-5-Monophosphate C00105 1778309 322.168 9.74

HPLC-MRM Maltose C00897 439341 342.299 6.38

HPLC-MRM Galactinol C01235 25202439 342.299 4.74

HPLC-MRM Cellobiose C06422 10712 342.299 5.66

HPLC-MRM 1-Kestose C03661 440080 504.441 8.69

HPLC-MRM Raffinose C00492 439242 504.441 8.11

HPLC-MRM Fumaric Acid C00122 5460307 114.057 18.88

HPLC-MRM Methylmalonic Acid C02170 5459982 116.073 17.29

HPLC-MRM Succinic Acid C00042 160419 116.073 16.45

HPLC-MRM Mesaconic Acid C01732 7257940 128.084 18.35

HPLC-MRM Ethylmalonic Acid NA 11756 132.115 19.03

HPLC-MRM Citramalic Acid C00815 1081 146.099 17.65

HPLC-MRM L-Dihydroorotic Acid C00337 5460289 157.105 24.11

HPLC-MRM Pimelic Acid C02656 5242388 158.154 24.05

HPLC-MRM 3-Methyl Xanthine C16357 70639 166.139 18.98

HPLC-MRM Homogentisic Acid C00544 5460389 167.141 18.58

HPLC-MRM Vanillic Acid C06672 54675858 167.141 24.86

Table 2-2. Continued Detection KEGG PubChem Molecular Retention Metabolite Name Platform ID ID weight time

HPLC-MRM 2-Isopropylmalic Acid C02504 6419726 174.153 23.10

HPLC-MRM 2-Deoxyinosine C05512 65058 252.229 18.21

HPLC-MRM Arbutin C06186 440936 272.254 17.26

HPLC-MRM Salicin C01451 439503 286.281 23.07

HPLC-MRM 2-Deoxy Inosine-5-Triphosphate C01345 25203822 488.137 16.82

HPLC-MRM Chlorogenic Acid C00852 7003561 353.305 21.14

HPLC-MRM Inosine-5-Diphosphate C00104 7156952 425.165 16.70

HPLC-MRM Dihydrofolic Acid C00415 40480038 441.402 21.49

HPLC-MRM Riboflavin-5-Mono Phosphate C00061 44229199 453.324 22.09

HPLC-MRM 4-Nitrophenol C00870 644235 138.102 32.59

HPLC-MRM 4-Hydroxyphenylacetic Acid C00642 4693933 151.141 26.91

HPLC-MRM Adonitol C00474 6912 152.147 26.96

HPLC-MRM 2-Hydroxyphenylacetic Acid C05852 6933325 151.141 26.93

HPLC-MRM Mandelic Acid C01983 5460269 151.141 27.76

HPLC-MRM Xanthine C00385 1188 152.112 27.57

HPLC-MRM 6,7-Dihydroxy Coumarin C09263 5281416 178.142 30.93

HPLC-MRM 3-Hydroxy 4-Methoxy Cinnamic Acid C10470 12653 194.184 27.57

HPLC-MRM Daidzein C10208 5281708 254.242 34.33

HPLC-MRM 7-Hydroxyflavone C11264 5281894 238.242 33.19

HPLC-MRM Isoliquiritigenin C08650 638278 256.257 34.57

HPLC-MRM Apigenin C01477 25200950 269.233 33.26

HPLC-MRM Naringenin C00509 439246 272.257 31.12

HPLC-MRM Luteolin C01514 25201972 285.232 30.98

HPLC-MRM Hesperetin C01709 49859576 301.275 34.02

HPLC-MRM Chlorophyll A C05306 90657767 892.495 26.91

HPLC-MRM Quercitrin C01750 25200492 447.374 26.90

HPLC-MRM Naringin C09789 25244342 580.541 36.15

HPLC-MRM Neohesperidin C09806 25246273 610.568 26.54

Table 2-3. Significantly changed metabolites under elevated CO2 Fold change p-value q-value Metabolite Name 5 10 30 60 5 10 30 60 5 10 30 60 min min min min min min min min min min min min (9Z)-12-Oxo-Dodec-9- 0.96 0.73 0.79 0.84 9.44 2.30 4.11 4.30 3.78 1.21 3.52 4.46 Enoate E-01 E-04 E-03 E-02 E-01 E-02 E-02 E-02 Benzaldehyde 1.03 0.94 0.95 1.05 1.90 3.19 5.31 1.78 1.69 4.01 3.52 2.85 E-01 E-02 E-03 E-02 E-01 E-02 E-02 E-02 Phytosphingosine 1- 0.71 1.85 0.90 2.82 1.33 2.18 7.02 5.68 4.91 1.27 2.51 2.10 Phosphate E-02 E-03 E-01 E-05 E-02 E-02 E-01 E-03 Sarcosine 2.23 2.33 1.82 1.54 5.71 1.90 2.30 1.40 1.56 1.27 5.69 2.69 E-04 E-03 E-02 E-02 E-02 E-02 E-02 E-02 1-Methylnicotinamide 2.57 2.02 2.17 1.71 7.14 3.47 8.34 2.84 3.75 4.12 1.07 1.26 E-03 E-02 E-02 E-03 E-02 E-02 E-01 E-02 Mannitol 0.17 0.07 0.16 0.14 6.34 1.30 4.33 3.66 3.75 2.86 8.33 4.20 E-03 E-02 E-02 E-02 E-02 E-02 E-02 E-02 Orotic Acid 0.48 0.47 0.44 0.82 4.00 8.16 9.83 6.49 3.21 2.21 4.77 2.41 E-03 E-03 E-03 E-01 E-02 E-02 E-02 E-01 Cytidine 1.79 1.68 1.24 1.75 8.00 7.47 1.02 2.39 3.90 2.13 1.12 1.11 E-03 E-03 E-01 E-03 E-02 E-02 E-01 E-02 Pyroglutamic Acid 1.69 2.71 3.27 1.82 3.38 2.13 4.11 1.40 2.24 1.27 3.52 2.69 E-01 E-03 E-03 E-02 E-01 E-02 E-02 E-02 Guanosine 2.11 1.94 1.32 2.02 5.09 1.67 1.62 7.50 3.51 3.33 1.36 2.03 E-03 E-02 E-01 E-03 E-02 E-02 E-01 E-02 5-Deoxy-5-Methylthio- 0.34 0.39 0.51 0.58 9.71 1.80 1.93 3.49 4.14 3.33 1.47 4.05 Adenosine E-03 E-02 E-01 E-02 E-02 E-02 E-01 E-02 Riboflavin 2.10 1.89 1.21 1.91 1.60 9.94 2.15 1.72 2.51 2.39 1.58 2.84 E-03 E-03 E-01 E-02 E-02 E-02 E-01 E-02 Cyanidin 1.73 1.68 0.97 1.60 7.14 5.17 8.02 1.92 3.75 1.75 2.62 2.99 E-03 E-03 E-01 E-02 E-02 E-02 E-01 E-02 Alpha-Lactose 3.78 3.56 0.96 2.85 3.60 1.56 6.93 1.97 3.21 3.25 2.49 2.99 E-03 E-02 E-01 E-02 E-02 E-02 E-01 E-02

Table 2-3. Continued Fold change p-value q-value Metabolite Name 5 10 30 60 5 10 30 60 5 10 30 60 min min min min min min min min min min min min Luteolin-7-Beta-Glucoside 5.69 5.05 1.03 3.63 8.51 2.87 6.76 1.63 4.00 1.38 2.48 2.84 E-03 E-03 E-01 E-02 E-02 E-02 E-01 E-02 4.00 3.91 5.71 2.83 3.21 4.54 1.52 1.39 Uridine-5-Monophosphate 0.38 0.27 0.05 0.12 E-03 E-02 E-05 E-01 E-02 E-02 E-03 E-01 6.23 2.00 1.48 5.11 3.75 3.45 5.44 1.64 Vanillic Acid 1.49 1.46 1.44 1.59 E-03 E-02 E-02 E-03 E-02 E-02 E-02 E-02 3.89 4.11 2.43 5.17 3.21 4.62 1.66 1.64 Xanthine 1.24 1.26 1.13 1.27 E-03 E-02 E-01 E-03 E-02 E-02 E-01 E-02 2.57 8.45 4.57 4.64 3.19 2.23 8.13 1.97 7-Hydroxyflavone 0.43 0.36 0.22 1.77 E-03 E-03 E-04 E-01 E-02 E-02 E-03 E-01 5.71 1.72 3.84 1.44 1.56 3.33 2.05 2.71 Apigenin 2.40 2.42 1.15 2.12 E-04 E-02 E-01 E-02 E-02 E-02 E-01 E-02 2.29 1.56 7.43 4.21 6.13 3.25 3.95 4.46 Naringenin 0.54 0.51 0.47 0.55 E-02 E-02 E-03 E-02 E-02 E-02 E-02 E-02 6.71 3.21 3.63 6.88 3.14 4.01 8.07 2.01 (+)-5-Deoxystrigol 1.04 0.92 0.87 1.19 E-01 E-02 E-02 E-03 E-01 E-02 E-02 E-02 3-Oxo-2-(Cis-2-Pentenyl)- 1.33 2.55 6.54 9.94 4.91 3.64 1.00 3.15 1.19 0.93 0.91 0.98 Cyclopentane-1-Octanoate E-02 E-02 E-02 E-01 E-02 E-02 E-01 E-01 7.88 9.52 1.14 3.35 3.35 2.92 2.44 1.38 3,5-Dihydroxyanisole 1.02 1.02 0.90 1.14 E-01 E-01 E-04 E-03 E-01 E-01 E-03 E-02 7.09 4.28 2.05 1.57 3.75 4.76 5.52 9.81 Enol-Phenylpyruvate 1.23 0.84 0.83 1.09 E-03 E-02 E-02 E-01 E-02 E-02 E-02 E-02 L-1- 1.44 4.38 5.83 1.70 1.42 1.84 3.52 2.71 Glycerophosphorylethanola 0.74 0.96 1.32 1.73 E-01 E-01 E-03 E-04 E-01 E-01 E-02 E-03 mine 9.50 1.90 8.00 2.13 3.78 1.27 1.22 1.20 Salicin 0.51 0.17 0.04 0.82 E-01 E-03 E-04 E-01 E-01 E-02 E-02 E-01 (9Z)-12,13- 3.97 4.14 5.71 5.61 2.39 1.61 1.52 2.18 0.98 0.88 0.84 0.98 Dihydroxyoctadeca-9-Enoate E-01 E-03 E-05 E-01 E-01 E-02 E-03 E-01

Table 2-3. Continued Fold change p-value q-value Metabolite Name 5 10 30 60 5 10 30 60 5 10 30 60 min min min min min min min min min min min min 4.05 1.03 4.23 3.32 2.39 8.03 3.52 3.99 Kaempferol-3-Gentiobioside 0.98 0.92 0.92 1.05 E-01 E-01 E-03 E-02 E-01 E-02 E-02 E-02 1-18:1-2-Trans-16:1- 9.25 2.36 3.29 9.09 3.71 3.63 1.95 6.74 1.12 2.53 1.11 3.68 Phosphatidylglycerol E-01 E-02 E-01 E-04 E-01 E-02 E-01 E-03 1-18:3-2-16:3- 8.87 3.28 2.17 3.98 1.06 1.38 1.58 3.68 1.50 3.28 1.26 1.94 Monogalactosyldiacylglycerol E-02 E-03 E-01 E-04 E-01 E-02 E-01 E-03 5.01 2.41 7.05 9.32 2.65 1.27 2.51 2.24 Prephytoene Diphosphate 0.81 1.74 1.10 1.87 E-01 E-03 E-01 E-03 E-01 E-02 E-01 E-02 2.96 1.26 2.57 7.07 2.13 2.84 3.43 2.51 12,13-(S)-Epoxylinolenate 0.96 0.91 0.86 1.00 E-01 E-02 E-03 E-01 E-01 E-02 E-02 E-01 1-18:2-2-16:0- 3.25 3.91 4.54 4.94 2.21 1.59 8.49 4.99 1.15 2.58 1.34 1.69 Phosphatidylglycerol E-01 E-03 E-02 E-02 E-01 E-02 E-02 E-02 4.51 1.11 5.71 2.67 2.50 2.57 1.52 1.35 9-Oxo-Nonanoate 0.98 0.89 0.85 0.94 E-01 E-02 E-05 E-01 E-01 E-02 E-03 E-01 3.36 1.98 9.45 1.28 2.24 3.45 2.92 2.58 Carboxymethyl-Coa 1.00 0.77 1.02 0.77 E-01 E-02 E-01 E-02 E-01 E-02 E-01 E-02 2.68 9.42 5.94 1.94 2.03 7.71 3.52 2.99 Kaempferol-3-Glucoside 1.01 0.93 0.93 1.04 E-01 E-02 E-03 E-02 E-01 E-02 E-02 E-02 1.03 1.66 2.76 1.30 4.28 1.10 1.75 2.58 1,3-Diaminopropane 1.28 1.14 1.15 1.26 E-02 E-01 E-01 E-02 E-02 E-01 E-01 E-02 2.29 2.48 7.26 1.03 1.88 3.64 1.03 2.33 Alanine 1.49 1.51 1.34 1.68 E-01 E-02 E-02 E-02 E-01 E-02 E-01 E-02 9.54 3.14 1.35 6.89 4.14 4.01 5.44 6.33 N,N-Dimethylglycine 1.22 1.30 1.21 1.19 E-03 E-02 E-02 E-02 E-02 E-02 E-02 E-02 1.21 8.05 1.22 4.66 1.29 2.21 1.26 1.62 Threonine 1.40 1.51 1.22 1.47 E-01 E-03 E-01 E-03 E-01 E-02 E-01 E-02 6.23 2.41 2.27 1.52 9.23 1.27 1.61 2.82 Trans-4-Hydroxyl-L-Proline 1.47 1.82 1.23 1.44 E-02 E-03 E-01 E-02 E-02 E-02 E-01 E-02

Table 2-3. Continued Fold change p-value q-value Metabolite Name 5 10 30 60 5 10 30 60 5 10 30 60 min min min min min min min min min min min min 6.58 3.05 1.74 1.08 9.44 1.38 1.36 2.40 Isoleucine 1.56 1.92 1.33 1.38 E-02 E-03 E-01 E-02 E-02 E-02 E-01 E-02 3.75 2.72 1.66 4.25 7.20 3.74 1.36 4.46 Glutamine 1.31 1.51 1.17 1.40 E-02 E-02 E-01 E-02 E-02 E-02 E-01 E-02 6.99 1.57 4.97 1.70 9.73 3.25 2.21 2.84 L-Malic Acid 2.24 2.32 1.09 2.37 E-02 E-02 E-01 E-02 E-02 E-02 E-01 E-02 3.26 4.43 1.46 8.40 3.21 1.61 5.44 2.81 Betaine 2.68 3.06 1.86 0.82 E-03 E-03 E-02 E-01 E-02 E-02 E-02 E-01 3.05 9.83 3.97 1.70 2.15 2.39 8.14 8.61 Thymine 1.20 1.55 1.33 1.49 E-01 E-03 E-02 E-03 E-01 E-02 E-02 E-03 1.50 2.25 6.39 2.34 1.46 3.59 2.42 3.29 Uridine 1.44 1.89 0.88 2.15 E-01 E-02 E-01 E-02 E-01 E-02 E-01 E-02 3.27 1.12 7.72 3.37 2.22 2.57 2.57 3.99 2-Deoxyguanosine 1.39 1.77 1.03 1.46 E-01 E-02 E-01 E-02 E-01 E-02 E-01 E-02 1.24 3.71 5.94 9.56 4.83 1.71 3.52 7.39 Liquiritigenin 0.40 0.80 0.46 0.62 E-02 E-01 E-03 E-02 E-02 E-01 E-02 E-02 2.18 2.87 6.07 3.14 6.13 1.38 9.98 3.84 Ononin 1.57 1.89 1.42 1.55 E-02 E-03 E-02 E-02 E-02 E-02 E-02 E-02 2.01 1.82 4.07 9.49 5.96 3.33 8.19 2.24 Galactinol 1.45 1.55 1.32 1.39 E-02 E-02 E-02 E-03 E-02 E-02 E-02 E-02 4.51 7.47 2.48 6.98 3.42 2.13 1.68 6.36 Mesaconic Acid 2.21 2.35 1.19 0.47 E-03 E-03 E-01 E-02 E-02 E-02 E-01 E-02 14.9 17.8 4.00 8.05 1.29 2.33 1.56 1.27 1.28 1.27 Citramalic Acid 1.13 0.14 6 2 E-04 E-04 E-01 E-01 E-02 E-02 E-01 E-01 5.71 1.32 2.01 3.23 1.56 1.27 5.52 1.54 L-Dihydroorotic Acid 4.82 4.62 1.75 0.48 E-04 E-03 E-02 E-01 E-02 E-02 E-02 E-01 6.21 6.56 7.77 2.61 3.02 6.08 3.95 3.42 6,7-Dihydroxy Coumarin 1.06 1.65 1.93 1.63 E-01 E-02 E-03 E-02 E-01 E-02 E-02 E-02

Table 2-3. Continued Fold change p-value q-value Metabolite Name 5 10 30 60 5 10 30 60 5 10 30 60 min min min min min min min min min min min min 5.14 9.17 3.70 3.15 3.51 2.82 2.05 3.84 Chlorophyll A 2.64 0.98 0.53 3.07 E-03 E-01 E-01 E-02 E-02 E-01 E-01 E-02 9.26 8.96 6.40 3.11 4.14 2.81 2.42 3.84 Quercitrin 2.07 0.89 0.80 2.52 E-03 E-01 E-01 E-02 E-02 E-01 E-01 E-02 12.2 3.22 3.83 2.09 6.97 2.05 3.06 Histidine NA 1.83 1.83 NA NA 6 E-02 E-01 E-02 E-02 E-01 E-02 4.93 5.57 2.03 3.81 8.31 2.13 5.52 4.32 Homocysteine 1.19 1.05 1.25 1.44 E-02 E-01 E-02 E-02 E-02 E-01 E-02 E-02 8.86 1.70 2.80 2.71 Fructose NA 0.90 NA 2.36 NA NA NA NA E-01 E-04 E-01 E-03 3.28 2.74 4.25 1.57 1.75 4.46 Galactose NA 1.08 0.86 2.10 NA NA E-01 E-01 E-02 E-01 E-01 E-02 8.58 1.15 2.75 2.42 Cysteamine NA 0.90 NA 1.32 NA NA NA NA E-01 E-02 E-01 E-02 7.42 6.14 4.37 5.80 1.00 2.25 2.13 1.79 18-Hydroxyoleate 0.74 0.98 1.16 1.40 E-02 E-01 E-01 E-03 E-01 E-01 E-01 E-02 2-Oxindole-3-Acetyl-L- 7.14 7.53 1.77 7.35 3.75 2.53 5.52 6.58 1.15 1.00 0.88 0.88 Aspartate E-03 E-01 E-02 E-02 E-02 E-01 E-02 E-02 6.50 1.93 3.23 9.88 3.06 3.45 1.93 7.39 4-Amino-4-Deoxychorismate 1.04 0.56 1.27 0.64 E-01 E-02 E-01 E-02 E-01 E-02 E-01 E-02 6.32 5.22 6.26 9.77 3.02 5.22 2.40 2.26 5-Hydroxyisourate 1.07 0.63 1.08 1.75 E-01 E-02 E-01 E-03 E-01 E-02 E-01 E-02 1.06 9.89 5.38 8.84 1.18 2.39 2.27 2.91 Acryloyl-Coa 0.83 0.59 1.03 0.83 E-01 E-03 E-01 E-01 E-01 E-02 E-01 E-01 4.74 8.88 5.38 3.41 2.54 2.80 2.27 3.99 Androstenedione 1.17 0.98 1.08 1.47 E-01 E-01 E-01 E-02 E-01 E-01 E-01 E-02 6.83 3.21 3.00 7.47 3.14 4.01 1.83 2.62 (9R,10S)-Dihydroxystearate 0.92 2.17 1.25 0.95 E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01

Table 2-3. Continued Fold change p-value q-value Metabolite Name 5 10 30 60 5 10 30 60 5 10 30 60 min min min min min min min min min min min min 3.08 7.16 2.81 1.70 2.15 6.52 1.75 2.84 Indole-3-Acetyl-Glycine 1.07 0.94 0.95 1.08 E-01 E-02 E-01 E-02 E-01 E-02 E-01 E-02 4-Methylumbelliferyl 1.11 1.12 1.31 6.45 4.45 8.58 5.44 5.98 1.22 0.89 0.82 1.16 Glucoside E-02 E-01 E-02 E-02 E-02 E-02 E-02 E-02 3.42 4.67 2.32 5.68 6.97 1.92 1.61 2.10 26,27-Dehydrozymosterol 0.68 0.90 0.83 1.87 E-02 E-01 E-01 E-05 E-02 E-01 E-01 E-03 Indole-3-Acetonitrile- 8.40 3.17 9.63 5.21 3.50 4.01 2.95 2.11 Gamma-Glutamylcysteine 0.97 0.91 1.01 1.02 E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 Conjugate 7.75 1.12 6.59 1.73 1.00 8.58 2.47 2.84 22-Oxo-Docosanoate 0.79 0.75 1.04 1.43 E-02 E-01 E-01 E-02 E-01 E-02 E-01 E-02 8.66 2.67 8.83 2.37 1.06 3.73 2.80 1.28 Docosanedioate 1.20 0.62 1.05 1.20 E-02 E-02 E-01 E-01 E-01 E-02 E-01 E-01 (3R, 7S)-12-Hydroxy- 5.07 5.39 2.33 1.70 8.34 2.09 1.61 2.71 0.69 0.92 0.82 1.96 Jasmonoyl-L-Isoleucine E-02 E-01 E-01 E-04 E-02 E-01 E-01 E-03 4.49 1.89 1.85 1.53 2.50 1.19 5.52 8.42 1-Naphthol Glucoside 0.95 0.92 0.84 1.14 E-01 E-01 E-02 E-03 E-01 E-01 E-02 E-03 4-Hydroxy-2-Nonenal-[Cys- 2.34 4.63 2.94 7.67 3.19 1.91 1.81 2.66 1.19 0.91 1.13 0.98 Gly] Conjugate E-03 E-01 E-01 E-01 E-02 E-01 E-01 E-01 2.38 2.35 6.30 1.61 6.13 1.31 9.98 2.84 5,8,11,14-Eicosatetraynoate 1.20 1.08 0.91 1.07 E-02 E-01 E-02 E-02 E-02 E-01 E-02 E-02 7.54 2.51 8.95 1.12 3.30 3.64 1.07 7.89 Quercetin-3-Gentiotrioside 1.07 0.80 0.82 1.15 E-01 E-02 E-02 E-01 E-01 E-02 E-01 E-02 1.60 7.20 6.28 2.76 2.51 2.45 2.40 1.36 Salicyl Alcohol 1.87 1.06 1.08 0.72 E-03 E-01 E-01 E-01 E-02 E-01 E-01 E-01 1-18:2-2-Trans-16:1- 4.03 2.99 4.35 7.50 2.39 4.00 2.13 2.62 1.36 2.61 1.43 0.86 Phosphatidylglycerol E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 1.68 2.09 7.47 2.62 1.58 3.51 2.55 1.35 2-Trans-Hexadecenal 1.08 1.25 0.99 0.94 E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01

Table 2-3. Continued Fold change p-value q-value Metabolite Name 5 10 30 60 5 10 30 60 5 10 30 60 min min min min min min min min min min min min 3.28 5.25 5.74 7.39 6.97 2.07 2.32 2.03 Norajmaline 0.74 0.95 1.12 1.35 E-02 E-01 E-01 E-03 E-02 E-01 E-01 E-02 5-Alpha-Cholesta-8,24-Dien- 3.42 4.68 2.33 5.68 6.97 1.92 1.61 2.10 0.67 0.90 0.83 1.87 3-One E-02 E-01 E-01 E-05 E-02 E-01 E-01 E-03 2.99 5.08 7.14 1.79 2.13 2.05 3.95 1.06 Mevalonate 5-Phosphate 0.90 0.97 0.79 1.15 E-01 E-01 E-03 E-01 E-01 E-01 E-02 E-01 (9Z,11E,14Z)-(13S)- 2.15 4.34 3.77 3.01 1.81 1.84 8.07 1.29 Hydroperoxyoctadeca- 0.73 0.87 0.77 1.31 E-01 E-01 E-02 E-03 E-01 E-01 E-02 E-02 (9,11,14)-Trienoate 1.12 1.75 9.77 3.41 1.23 1.13 2.99 3.68 5-Beta-Pregnan-3,20-Dione 0.90 0.93 1.01 1.25 E-01 E-01 E-01 E-04 E-01 E-01 E-01 E-03 4.24 3.73 4.24 3.77 7.82 4.38 2.13 1.72 Delphinidin 1.16 0.85 0.94 1.04 E-02 E-02 E-01 E-01 E-02 E-02 E-01 E-01 1.66 9.06 7.51 8.98 2.51 2.81 2.55 2.94 3-Dehydroteasterone 0.62 0.88 0.92 0.92 E-03 E-01 E-01 E-01 E-02 E-01 E-01 E-01 7.22 2.08 4.71 3.98 9.85 1.22 2.17 3.68 8-Apo-Beta-Carotenal 0.84 0.91 1.13 1.27 E-02 E-01 E-01 E-04 E-02 E-01 E-01 E-03 1-18:3-2-18:3- 3.54 4.60 6.95 4.09 2.28 1.27 2.49 1.83 0.93 0.69 1.06 1.04 Digalactosyldiacylglycerol E-01 E-04 E-01 E-01 E-01 E-02 E-01 E-01 1-18:2-2-18:2- 9.09 2.39 1.65 9.43 3.66 1.32 1.36 2.24 1.18 0.67 1.35 1.76 Digalactosyldiacylglycerol E-01 E-01 E-01 E-03 E-01 E-01 E-01 E-02 1-18:3-2-16:0- 2.71 1.98 3.63 1.12 2.03 1.21 2.05 2.42 0.77 0.71 1.08 1.83 Digalactosyldiacylglycerol E-01 E-01 E-01 E-02 E-01 E-01 E-01 E-02 2.97 6.56 5.53 2.39 6.87 2.33 2.27 3.30 Crocetin Dialdehyde 1.35 1.03 1.08 0.64 E-02 E-01 E-01 E-02 E-02 E-01 E-01 E-02 4.28 5.87 7.86 2.91 2.42 2.18 2.59 3.68 3-Methoxybenzaldehyde 1.09 1.07 0.98 1.45 E-01 E-01 E-01 E-02 E-01 E-01 E-01 E-02 6.36 5.43 8.58 3.41 3.02 2.09 2.73 3.68 Palmitoleate 0.93 1.08 0.95 1.48 E-01 E-01 E-01 E-04 E-01 E-01 E-01 E-03

Table 2-3. Continued Fold change p-value q-value Metabolite Name 5 10 30 60 5 10 30 60 5 10 30 60 min min min min min min min min min min min min 3.52 2.78 4.77 5.54 2.28 3.77 2.17 2.16 Geranyl Acetate 0.99 0.92 1.10 1.00 E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 Phosphatidylglycerophospha 5.75 4.02 6.85 9.47 8.92 4.62 2.49 3.03 te (1-Octadecenoyl(9Z), 2- 2.15 0.53 1.11 0.92 E-02 E-02 E-01 E-01 E-02 E-02 E-01 E-01 Palmitoyl) 6.15 5.43 3.26 9.98 3.02 5.31 3.52 7.39 Glycerophosphoglycerol 1.00 0.83 0.65 1.24 E-01 E-02 E-03 E-02 E-01 E-02 E-02 E-02 3.19 4.05 5.71 4.16 2.19 1.80 1.52 1.85 4-Coumaroylagmatine 1.08 0.97 0.84 0.95 E-01 E-01 E-05 E-01 E-01 E-01 E-03 E-01 4.11 7.91 2.72 4.33 2.39 2.62 1.75 4.46 (9Z)-Octadecenoic Acid 1.06 1.00 0.95 1.09 E-01 E-01 E-01 E-02 E-01 E-01 E-01 E-02 9.73 7.47 1.35 1.88 3.83 2.13 1.28 1.10 Hexadecanoic Acid 0.98 0.78 0.85 1.12 E-01 E-03 E-01 E-01 E-01 E-02 E-01 E-01 6.54 7.47 7.29 7.99 9.44 2.13 2.54 6.94 Pristanate 0.85 0.74 1.06 1.17 E-02 E-03 E-01 E-02 E-02 E-02 E-01 E-02 3.61 8.43 6.48 3.38 2.28 2.72 2.44 3.99 Sorbose 0.80 0.86 0.86 1.69 E-01 E-01 E-01 E-02 E-01 E-01 E-01 E-02 1.90 5.17 7.34 4.91 1.69 1.75 2.54 2.04 Citrate 0.65 0.46 1.04 1.12 E-01 E-03 E-01 E-01 E-01 E-02 E-01 E-01 7.62 4.29 7.67 2.76 3.30 1.84 2.57 3.53 Tyrosine 1.08 1.12 1.03 1.41 E-01 E-01 E-01 E-02 E-01 E-01 E-01 E-02 1.97 3.47 1.35 1.37 1.71 4.12 1.28 8.80 Tryptophan 1.39 1.73 0.69 1.62 E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-02 6.81 2.68 4.69 9.36 3.14 3.73 2.17 3.01 Thiamine 1.08 1.28 1.16 0.87 E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 1.82 1.67 2.69 4.08 1.65 1.27 1.75 1.83 Oxaloacetic Acid 1.73 3.14 1.26 0.62 E-01 E-03 E-01 E-01 E-01 E-02 E-01 E-01 5.11 6.81 3.76 4.57 2.69 2.39 2.05 4.66 Nicotinamide 1.34 1.13 0.79 2.39 E-01 E-01 E-01 E-02 E-01 E-01 E-01 E-02

Table 2-3. Continued Fold change p-value q-value Metabolite Name 5 10 30 60 5 10 30 60 5 10 30 60 min min min min min min min min min min min min 7.42 9.26 4.12 2.77 3.28 7.65 2.11 3.53 Abscisic Acid Glucose Ester 0.90 1.84 0.80 2.00 E-01 E-02 E-01 E-02 E-01 E-02 E-01 E-02 6.07 2.41 1.23 2.20 3.02 1.27 1.26 1.22 Ribulose 5-Phosphate 1.12 2.13 1.35 0.65 E-01 E-03 E-01 E-01 E-01 E-02 E-01 E-01 4.10 6.20 3.56 6.36 2.39 2.25 2.05 1.91 2,3-Dihydroxybenzoic Acid 0.81 1.08 1.11 1.57 E-01 E-01 E-01 E-03 E-01 E-01 E-01 E-02 3.99 2.02 5.59 2.15 2.39 3.45 2.29 1.20 6-Furfurylaminopurine 0.51 2.28 0.84 0.67 E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 3.59 1.68 5.35 2.61 2.28 3.33 2.27 1.35 Kinetin 0.52 2.20 0.88 0.76 E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 7.08 5.36 6.05 2.16 3.20 2.09 2.36 1.04 3-Indole-Acetic Acid 0.90 1.13 0.90 1.49 E-01 E-01 E-01 E-03 E-01 E-01 E-01 E-02 3.12 4.43 1.67 8.64 2.17 1.61 1.36 2.86 Indole Butyric Acid 0.46 1.73 0.74 1.12 E-01 E-03 E-01 E-01 E-01 E-02 E-01 E-01 2.13 2.54 7.27 2.45 1.80 3.64 2.54 1.31 Alpha-Lipoamide 0.39 2.62 0.95 0.51 E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 7.50 1.44 5.18 9.05 3.29 1.27 2.25 2.94 Jasmonic Acid 0.76 2.80 1.06 1.01 E-01 E-03 E-01 E-01 E-01 E-02 E-01 E-01 9.95 2.98 7.26 4.05 3.88 1.50 2.54 4.46 Hypoxanthine 1.04 0.86 0.95 2.36 E-01 E-01 E-01 E-02 E-01 E-01 E-01 E-02 7.43 1.80 6.87 9.32 3.28 1.15 1.03 2.24 2-Deoxyribose-5-Phosphate 0.94 0.89 0.67 0.39 E-01 E-01 E-02 E-03 E-01 E-01 E-01 E-02 7.86 4.58 6.93 3.69 3.35 1.90 2.49 1.39 Fumaric Acid 0.83 1.14 1.11 1.75 E-01 E-01 E-01 E-03 E-01 E-01 E-01 E-02 1.58 2.14 4.52 3.75 1.53 1.23 2.17 1.39 Succinic Acid 1.15 1.19 0.92 1.38 E-01 E-01 E-01 E-03 E-01 E-01 E-01 E-02 6.29 1.90 4.07 8.27 3.02 1.27 2.10 2.78 Pimelic Acid 0.66 2.15 1.10 1.18 E-01 E-03 E-01 E-01 E-01 E-02 E-01 E-01

Table 2-3. Continued Fold change p-value q-value Metabolite Name 5 10 30 60 5 10 30 60 5 10 30 60 min min min min min min min min min min min min 2-Deoxy Inosine-5- 6.74 8.85 4.87 1.66 3.14 2.80 2.20 2.84 0.95 1.08 1.06 2.28 Triphosphate E-01 E-01 E-01 E-02 E-01 E-01 E-01 E-02 7.71 2.55 6.23 9.34 3.90 1.38 2.40 7.39 Dihydrofolic Acid 0.46 0.60 0.90 1.84 E-03 E-01 E-01 E-02 E-02 E-01 E-01 E-02 6.30 1.72 1.68 5.54 3.02 1.27 1.36 2.16 2-Hydroxyphenylacetic Acid 0.78 4.09 1.38 0.82 E-01 E-03 E-01 E-01 E-01 E-02 E-01 E-01 3-Hydroxy 4-Methoxy 5.76 6.10 1.44 4.19 2.91 2.24 1.34 4.46 0.94 1.06 0.85 1.24 Cinnamic Acid E-01 E-01 E-01 E-02 E-01 E-01 E-01 E-02 6.77 5.46 4.85 1.25 3.14 1.75 2.20 8.48 Isoliquiritigenin 0.95 2.00 0.85 0.57 E-01 E-03 E-01 E-01 E-01 E-02 E-01 E-02 8.56 5.29 4.07 9.44 3.52 1.75 2.10 3.03 Luteolin 0.91 2.78 1.16 0.85 E-01 E-03 E-01 E-01 E-01 E-02 E-01 E-01 1-Palmitoylglycerol 3- 1.72 2.68 4.72 3.98 1.59 1.42 2.17 3.68 0.72 1.49 1.10 2.14 Phosphate E-01 E-01 E-01 E-04 E-01 E-01 E-01 E-03 3.33 7.89 7.72 1.14 6.97 6.95 1.07 2.42 18-Oxo-Oleate 1.31 1.11 0.90 1.10 E-02 E-02 E-02 E-02 E-02 E-02 E-01 E-02 2-Oxo-5- 1.17 2.47 1.11 4.19 1.25 3.64 1.18 1.85 1.07 0.91 0.93 0.98 Methylthiopentanoate E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 3-Beta-D-Galactosyl-Sn- 3.34 9.74 4.51 4.45 2.24 2.97 3.52 1.91 1.08 1.00 0.84 0.99 Glycerol E-01 E-01 E-03 E-01 E-01 E-01 E-02 E-01 5.82 1.15 2.07 2.21 8.92 1.27 5.52 1.22 Chlorophyll B 0.86 0.72 0.77 1.11 E-02 E-03 E-02 E-01 E-02 E-02 E-02 E-01 5.91 1.63 2.08 1.02 2.96 1.10 1.55 7.10 (-)-Jasmonoyl-L-Isoleucine 0.85 1.24 1.15 2.42 E-01 E-01 E-01 E-03 E-01 E-01 E-01 E-03 5.06 2.28 1.83 4.20 8.34 3.59 5.52 1.85 Quercetin 4-O-Glucoside 1.13 0.91 0.87 0.98 E-02 E-02 E-02 E-01 E-02 E-02 E-02 E-01 24-Epicathasterone-22-O- 4.58 1.61 5.43 1.14 2.50 1.09 2.27 2.71 0.94 1.16 0.95 1.51 Sulfate E-01 E-01 E-01 E-04 E-01 E-01 E-01 E-03

Table 2-3. Continued Fold change p-value q-value Metabolite Name 5 10 30 60 5 10 30 60 5 10 30 60 min min min min min min min min min min min min 3.71 8.25 9.10 9.09 7.20 7.09 2.87 2.24 Phylloquinol 0.88 1.19 0.99 1.37 E-02 E-02 E-01 E-03 E-02 E-02 E-01 E-02 4.09 1.28 1.53 9.09 2.39 9.29 1.34 6.74 24-Methylenecycloartanol 0.82 1.34 1.33 3.58 E-01 E-01 E-01 E-04 E-01 E-02 E-01 E-03 2.55 2.69 8.77 1.19 1.98 1.42 1.07 7.37 (+)-7-Iso-Jasmonate 0.94 1.09 1.15 1.39 E-01 E-01 E-02 E-03 E-01 E-01 E-01 E-03 3.69 5.21 2.49 1.18 7.20 5.22 1.68 2.43 Malonylshisonin 0.53 3.22 0.82 2.70 E-02 E-02 E-01 E-02 E-02 E-02 E-01 E-02 2.94 6.91 8.56 8.52 2.13 2.41 2.73 6.74 Tetradecanoic Acid 0.90 1.05 0.98 1.30 E-01 E-01 E-01 E-04 E-01 E-01 E-01 E-03 1-18:3-2-16:0- 28.6 1.59 5.75 4.33 6.07 1.53 6.07 2.13 2.29 1.35 1.08 0.93 Phosphatidylglycerol 4 E-01 E-05 E-01 E-01 E-01 E-03 E-01 E-01 3.61 2.37 1.81 4.13 7.20 3.63 5.52 1.84 Quercetin 3-O-Glucoside 1.14 0.91 0.87 0.98 E-02 E-02 E-02 E-01 E-02 E-02 E-02 E-01 1.91 2.23 1.03 7.87 5.80 3.59 1.12 2.70 Fecosterol 1.36 1.39 1.18 1.06 E-02 E-02 E-01 E-01 E-02 E-02 E-01 E-01 3.72 4.55 6.24 3.98 2.31 5.00 9.98 4.46 Phenylglyoxal 0.99 0.94 0.96 1.03 E-01 E-02 E-02 E-02 E-01 E-02 E-02 E-02 1.05 6.90 9.59 2.72 1.18 1.27 1.11 1.36 Phosphoryl-Ethanolamine 0.89 0.73 0.85 1.09 E-01 E-04 E-02 E-01 E-01 E-02 E-01 E-01 6.93 1.74 7.12 5.19 3.17 3.33 2.52 2.11 (S)-Coclaurine 0.98 0.87 1.00 1.01 E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 2.53 2.81 8.66 1.19 1.97 1.45 1.07 7.37 Sinapyl Alcohol 0.94 1.09 1.15 1.39 E-01 E-01 E-02 E-03 E-01 E-01 E-01 E-03 3.41 4.11 1.51 9.85 2.24 4.62 1.34 7.39 Histamine 0.71 0.64 0.71 0.59 E-01 E-02 E-01 E-02 E-01 E-02 E-01 E-02 4.18 2.04 1.33 1.80 2.40 1.21 1.28 2.85 Cysteine 1.60 6.11 3.27 1.90 E-01 E-01 E-01 E-02 E-01 E-01 E-01 E-02

Table 2-3. Continued Fold change p-value q-value Metabolite Name 5 10 30 60 5 10 30 60 5 10 30 60 min min min min min min min min min min min min 4.09 1.28 3.59 3.75 2.39 9.29 2.05 1.39 Leucine 1.17 1.23 1.12 1.22 E-01 E-01 E-01 E-03 E-01 E-02 E-01 E-02 2.61 4.60 9.62 1.74 2.01 5.01 2.95 2.84 Asparagine 1.23 1.23 1.01 1.31 E-01 E-02 E-01 E-02 E-01 E-02 E-01 E-02 3.02 4.91 8.51 4.30 6.87 5.09 1.07 4.46 Spermidine 1.75 1.96 1.29 1.69 E-02 E-02 E-02 E-02 E-02 E-02 E-01 E-02 1.37 2.03 8.74 7.36 4.92 1.21 1.07 6.58 Lysine 1.62 1.32 1.27 1.38 E-02 E-01 E-02 E-02 E-02 E-01 E-01 E-02 4.34 5.43 8.13 2.30 7.89 5.31 2.64 3.27 Methylthiobutyric Acid 1.89 1.51 0.93 1.73 E-02 E-02 E-01 E-02 E-02 E-02 E-01 E-02 1.47 1.85 2.83 2.01 1.45 1.17 1.75 2.99 Cis-Aconitic Acid 1.62 1.23 1.20 1.54 E-01 E-01 E-01 E-02 E-01 E-01 E-01 E-02 2.39 1.01 9.93 5.06 1.92 7.98 1.11 1.64 L-Methionine Sulfone 1.39 1.46 1.33 1.67 E-01 E-01 E-02 E-03 E-01 E-02 E-01 E-02 6.81 9.37 1.53 2.43 9.58 2.39 1.34 1.30 Anthranilic Acid 1.71 2.04 1.28 0.62 E-02 E-03 E-01 E-01 E-02 E-02 E-01 E-01 1.71 6.20 3.78 4.09 1.58 5.80 2.05 1.47 Guanine 1.23 1.36 1.20 1.47 E-01 E-02 E-01 E-03 E-01 E-02 E-01 E-02 2.46 1.52 4.74 6.70 1.94 1.04 3.52 2.43 Acetylsalicylic Acid 1.40 1.78 2.20 0.80 E-01 E-01 E-03 E-01 E-01 E-01 E-02 E-01 1.51 3.23 2.54 8.06 5.30 4.01 1.68 6.95 Pyridoxal-5-Phosphate 0.40 0.40 0.57 0.60 E-02 E-02 E-01 E-02 E-02 E-02 E-01 E-02 1.30 1.26 1.42 4.68 1.35 1.27 5.44 1.98 N-Formyl-L-Methionine 2.26 9.48 8.09 1.86 E-01 E-03 E-02 E-01 E-01 E-02 E-02 E-01 7.01 1.18 5.76 8.64 3.19 8.90 2.32 2.24 Zeatin 0.93 1.35 1.06 1.62 E-01 E-01 E-01 E-03 E-01 E-02 E-01 E-02 3.90 5.54 4.72 2.47 2.39 5.35 2.17 3.35 2-Deoxyadenosine 1.28 1.61 1.10 1.60 E-01 E-02 E-01 E-02 E-01 E-02 E-01 E-02

Table 2-3. Continued Fold change p-value q-value Metabolite Name 5 10 30 60 5 10 30 60 5 10 30 60 min min min min min min min min min min min min 1.59 3.34 6.68 1.24 5.30 4.08 2.47 8.48 Adenosine 0.50 0.52 1.03 0.65 E-02 E-02 E-01 E-01 E-02 E-02 E-01 E-02 1.59 2.22 5.39 1.31 5.30 3.59 2.27 8.57 Inosine 0.51 0.53 1.06 0.67 E-02 E-02 E-01 E-01 E-02 E-02 E-01 E-02 Cyclic Guanosine 1.81 1.75 4.43 4.15 5.73 1.13 2.14 4.46 1.64 1.47 1.12 2.07 Monophosphate E-02 E-01 E-01 E-02 E-02 E-01 E-01 E-02 2-Deoxyguanosine-5-Mono 6.14 7.40 5.51 2.02 9.21 2.50 2.27 2.99 1.34 0.98 0.84 1.58 Phosphate E-02 E-01 E-01 E-02 E-02 E-01 E-01 E-02 Adenosine-3- 4.12 6.21 4.64 2.40 7.70 2.25 2.17 3.30 1.35 1.02 0.81 1.52 Monophosphate E-02 E-01 E-01 E-02 E-02 E-01 E-01 E-02 (6R)-5,6,7,8- 1.76 7.36 3.17 2.51 5.72 6.65 1.90 3.36 1.50 1.44 1.11 1.48 Tetrahydrobiopterin E-02 E-02 E-01 E-02 E-02 E-02 E-01 E-02 2.04 2.64 9.12 1.48 1.75 1.41 2.87 8.42 Indole Carboxylic Acid 1.09 1.14 1.02 1.29 E-01 E-01 E-01 E-03 E-01 E-01 E-01 E-03 2.34 9.97 1.60 2.61 6.13 7.98 1.36 3.42 Malonic Acid 1.35 1.30 1.20 1.33 E-02 E-02 E-01 E-02 E-02 E-02 E-01 E-02 Shikimic Acid 1.14 3.93 5.89 2.28 1.23 1.77 9.98 3.27 1.25 1.12 1.25 1.28 E-01 E-01 E-02 E-02 E-01 E-01 E-02 E-02 Dodecanoic Acid 1.49 3.60 5.46 9.63 2.51 1.68 2.27 3.08 2.14 1.74 0.92 0.95 E-03 E-01 E-01 E-01 E-02 E-01 E-01 E-01 Methylmalonic Acid 1.41 1.83 1.57 7.81 1.40 3.33 1.35 6.84 1.30 1.54 1.24 1.28 E-01 E-02 E-01 E-02 E-01 E-02 E-01 E-02 Riboflavin-5-Mono 8.59 2.00 3.99 7.39 3.52 1.21 2.09 2.03 0.98 1.24 0.83 1.54 Phosphate E-01 E-01 E-01 E-03 E-01 E-01 E-01 E-02 4-Nitrophenol 5.71 3.16 8.80 5.17 1.56 1.54 1.07 2.11 2.04 1.18 0.73 0.77 E-04 E-01 E-02 E-01 E-02 E-01 E-01 E-01 4-Hydroxyphenylacetic Acid 4.60 1.72 1.57 7.79 2.50 1.27 1.35 2.68 1.12 4.04 1.31 0.88 E-01 E-03 E-01 E-01 E-01 E-02 E-01 E-01

Table 2-3. Continued Fold change p-value q-value Metabolite Name 5 10 30 60 5 10 30 60 5 10 30 60 min min min min min min min min min min min min Mandelic Acid 1.00 3.28 2.69 3.36 1.18 1.38 1.75 1.59 3.09 8.59 1.16 0.33 E-01 E-03 E-01 E-01 E-01 E-02 E-01 E-01 Hesperetin 7.64 1.10 2.35 1.59 3.30 8.56 5.69 8.42 1.07 1.24 1.39 1.42 E-01 E-01 E-02 E-03 E-01 E-02 E-02 E-03

Table 2-4. Metabolites significantly changed at 3 or more time points or with a fold change over 10 under elevated CO2 Metabolite name KEGG ID Chemical group 5 min 10 min 30 min 60 min

Sarcosine C00213 Amino acid and derivatives 2.23** 2.33** 1.81 1.54*

Pyroglutamic Acid C01879 Amino acid and derivatives 1.69 2.71** 3.27** 1.82*

Histidine C00135 Amino acid and derivatives 12.26 NA 1.83 1.83*

Cyanidin C05905 Anthocyanin 1.73** 1.68** 0.97 1.60*

Luteolin-7-Beta-Glucoside C03951 Flavonoids 5.69** 5.05** 1.03 3.63*

7-Hydroxyflavone C11264 Flavonoids 0.43** 0.36** 0.22* 1.77

Apigenin C01477 Flavonoids 2.4** 2.42* 1.15 2.12*

Naringenin C00509 Flavonoids 0.54 0.51* 0.47** 0.55*

Cytidine C00475 Nucleotides / nucleosides 1.79** 1.68** 1.24 1.75**

Guanosine C00387 Nucleotides / nucleosides 2.11** 1.94* 1.32 2.02**

5-Deoxy-5-Methylthio-Adenosine C00170 Nucleotides / nucleosides 0.34** 0.39* 0.51 0.58*

Uridine-5-Monophosphate C00105 Nucleotides / nucleosides 0.38** 0.27* 0.05** 0.12

Xanthine C00385 Nucleotides / nucleosides 1.24** 1.26* 1.13 1.27**

Lactose C00243 Oligosaccharides 3.78** 3.56* 0.96 2.85*

Citramalic Acid C00815 Organic acids 14.96** 17.82** 1.13 0.14

Orotic Acid C00295 Organic acids 0.48* 0.47** 0.44** 0.82

Vanillic Acid C06672 Phenolics 1.49** 1.46* 1.44 1.59** 1-18:3-2-16:0-Phosphatidylglycerol NA Phospholipids 1.35 28.64** 1.08 0.93

Mannitol C00392 Sugar alcohol 0.17** 0.07* 0.16 0.14*

Salicin C01451 Sugar conjugates 0.51 0.17** 0.04** 0.82

1-Methylnicotinamide C02918 Vitamins 2.56** 2.02* 2.17 1.71**

Riboflavin C00255 Vitamins 2.1** 1.89** 1.21 1.91*

A 400 ppm

800 ppm

0 min 5 min 10 min 30 min 60 min

B C 160 6 400 ppm 400 ppm * 140 800 ppm * 800 ppm * 5.5 120 * 100 * 5 * * * * * * 80

4.5 Fluorescence DA

- 60 (% of control) of (% 40 Stomata Aperture(µm) Stomata 4 H2DCF 20

3.5 0 0 20 40 60 0 5 10 30 60 Time (min) Time (min)

Figure 2-1. Elevated CO2 induced stomatal closure and ROS production in B. napus guard cells. A) Representative images of stomatal aperture during 1 h control atmospheric CO2 (400 ppm) and elevated CO2 (800 ppm) treatments. Scale bar indicates 25 μm. B) Time course of stomatal movement under atmospheric and elevated CO2 conditions. Data are mean ± standard error of three independent experiments (n=3) with at least 60 independent stomata counted for each replicate. *p<0.05, Student’s t-test. C) Relative H2DCF-DA fluorescence levels indicating changes of ROS in B. napus guard cells under control and elevated CO2 conditions. Data are mean ± standard error of three independent experiments (n=3) with about 60 independent stomata counted for each replicate. *p<0.05, Student’s t-test. D) Representative images of stomatal ROS production at different time points of control and elevated CO2.

D 400 ppm

800 ppm

0 min 5 min 10 min 30 min 60 min

Figure 2-1. Continued

Figure 2-2. Overview of significantly changed metabolites in response to elevated CO2 treatment. A) Total significantly increased and decreased metabolites at each time point of treatment. B) Venn diagram showing significantly changed metabolites unique to or shared between samples. Red fonts indicate significantly increased metabolites, blue fonts indicate significantly decreased metabolites. C) Volcano plots showing significantly changed metabolites. Red and blue dots indicate significantly increased and decreased metabolites, respectively (p and q value both < 0.05; Fold change cut-off was set to <0.8 or >1.2). Light blue and light red dot indicate metabolites with a p value <0.05 and q value between 0.05 and 0.1. Gray dot indicates metabolites that did not pass the fold change or p, q value threshold. Annotation: 1. Citramalic acid; 2. Mannitol; 3. Luteolin-7-beta-glucoside; 4. L-Dihydroorotic acid; 5. Alpha- lactose; 6. 5-Deoxy-5-methylthio-adenosine; 7. Betaine; 8. Uridine-5- monophosphate; 9. Chlorophyll a; 10. 1-Methylnicotinamide; 11. Liquiritigenin; 12. Apigenin; 13. 7-Hydroxyflavone; 14. Sarcosine; 15. Mesaconic acid; 16. Dihydrofolic acid; 17. Dodecanoic acid; 18. Guanosine; 19. Riboflavin; 20. Quercitrin; 21. 1-18:3-2-16:0-Phosphatidylglycerol; 22. N-Formyl-L- methionine; 23. Mandelic acid; 24. Salicin; 25. 2-Hydroxyphenylacetic acid; 26. 4-Hydroxyphenylacetic acid; 27. 1-18:3-2-16:3- Monogalactosyldiacylglycerol; 28. Oxaloacetic acid; 29. Jasmonic acid; 30. Luteolin; 31. Pyroglutamic acid; 32. Alpha-lipoamide; 33. Orotic acid; 34. Acetylsalicylic acid; 35. Naringenin; 36. 6,7-Dihydroxy coumarin; 37. Glycerophosphoglycerol; 38. L-1-Glycerophosphorylethanolamine; 39. Mevalonate 5-phosphate; 40. (9Z)-12-Oxo-dodec-9-enoate; 41. 1-18:1-2- Trans-16:1-phosphatidylglycerol; 42. 24-Methylenecycloartanol; 43. Phytosphingosine-1-phosphate; 44. Malonylshisonin; 45. 2-Deoxyribose-5- phosphate; 46. (-)-Jasmonoyl-L-isoleucine; 47. Nicotinamide 48. L-Malic Acid 49. Hypoxanthine 50. Fructose 51. 2-Deoxy inosine-5-triphosphate; 52. Uridine; 53. 1-Palmitoylglycerol 3-phosphate; 54. Galactose.

Figure 2-3. PCA plots of high CO2 treated guard cell metabolomics data. A) PCA plots of each time point with all the metabolites. B) PCA plots with only the significantly changed metabolites at each time point. C) PCA plots with random metabolites (same number of significantly changed ones, 52 for 5 min, 21 for 10 min, 25 for 30 min, and 73 for 60 min). The blue and red oval indicate 95% confidence level.

Figure 2-4. Pathway view of representative metabolite changes at different time points after elevated CO2 treatment. Colors indicate the significance levels of the changed metabolites at different time points. Different shadings of the pathways indicate different metabolic pathways. Dashed lines indicate multiple steps. Yellow: amino acids; blue: glycolysis; red: TCA cycle; dark blue: phenylpropanoids; green: phytohormones; brown: nucleotides; purple: flavonoids. Abreviations of metabolites can be found in the abreivation table.

Figure 2-5. Heat map and hierarchical clustering of significantly changed metabolites. The z -scores of ln transformed mean of the significantly changed metabolites are used in the heat map. All metabolites are clustered into six clusters indicated by the color code on the left side of the heat map.

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Figure 2-5. Continued

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Figure 2-5. Continued

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Figure 2-5. Continued

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Figure 2-6. Pathway impact analysis of the elevated CO2 responsive metabolites in the time-course study. Bars showing statistically significant pathways were colored in grey. Numbers inside the bars indicated the number of metabolites that matched to the total metabolites in that pathway in the matched database. Only pathways with four or more metabolites that matched were included in the analysis.

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Figure 2-7. Changes in the flavonoid contents during elevated CO2 treatment of enriched guard cells. A) Quercetin and derivatives; B) Kaempferol and derivatives; C) Apigenin and apigenin derivatives; and D) Isoflavonoids. The log2 normalized fold changes were plotted. The levels of significance between ambient control and elevated CO2 treatments were indicated by open dots for p > 0.1, grey dots for 0.05 < p < 0.1, and solid black dots for p < 0.05.

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Figure 2-8. Metabolite changes in JA pathway in stomata of B. napus guard cells under elevated CO2 treatment. Color codes were the same as described in Fig. 2. 9-(S)-HOTrE, 10E,12Z,15Z)-(9S)-9-Hydroperoxyoctadeca-10,12,15-trienoic acid; 13-HPOT, (9Z,11E,15Z)-(13S)-13-Hydroperoxyoctadeca-9,11,15- trienoic acid; 12, 13-EOT, (9Z,15Z)-(13S)-12,13-Epoxyoctadeca-9,11,15- trienoic acid; cis-(+)-OPDA, (15Z)-12-Oxophyto-10,15-dienoic acid; OPC-8:0, (9S,13S)-10,11-dihydro-12-oxo-15-phytoenoic acid; (+)-7-iso-JA, (+)-7- Isojasmonic acid; (+)-7-isomethyl-JA, (+)-7-Isomethyljasmonic acid; (-)-JA, jasmonic acid; (-)-methyl-JA, methyl jasmonic acid; JA-Ile, jasmonic acid isoleucine; 12-Hydroxyl-JA-Ile, 12-hydroxyl-jasmonic acid isoleucine.

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Figure 2-9. A. thaliana JA mutants as well as stomatal movement in the mutants under elevated CO2. Stomatal movement of JA biosynthesis and signaling mutants after elevated CO2 treatment. Two way ANOVA and Tukey’s test were used for stomatal movement analysis between different time points and different genotypes. Different letters indicates p < 0.05.

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Figure 2-10. Metabolite changes in guard cells of Arabidopsis JA and CO2 mutants and in B. napus guard cells. Metabolite changes in wild type (WT) and different mutants. White bar, ambient CO2 control (400 ppm); gray bar, elevated CO2 treatment (800 ppm). The abundances of different metabolites were presented in their total ion intensity detected by the mass spectrometry. Three biological replicates were measured for metabolite analysis. Error bars indicate standard errors. Student’s t-test was done for different genotypes. Star (*) indicates p < 0.05.

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Figure 2-11. Changes of ABA and ABA catabolism metabolites in B. napus guard cells. Student’s t-test was done for different time points. Star (*) indicates p < 0.05.

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Figure 2-12. Proposed model of JA-mediated CO2 signaling pathway. Elevated CO2 induces JA-Ile biosynthesis in guard cells. JA signaling operates downstream 2+ of CO2 sensing through COI1, ROS and Ca to induce stomatal closure. Flavonoids are induced by elevated CO2 and may act as ROS scavengers. Mannitol and organic acids are repressed by elevated CO2 and act as osmoregulators during the stomatal closure. Dashed lines indicate multiple steps.

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CHAPTER 3 CHARACTERIZATION OF LOW CO2 RESPONSIVE METABOLOME AND PROTEOME IN BRASSICA NAPUS GUARD CELLS

Introduction

Guard cells are specialized pairs of cells that border stomata, which are microscopic pores on leaf surfaces. Stomata movement in response to various environmental signals as well as endogenous phytohormones such as abscisic acid controls the balance of water loss and CO2 intake for photosynthesis, and is thus essential for plants to adapt to their habitats. An elevation of CO2 concentration, either intercellular CO2 concentration (Ci) or atmospheric CO2 concentration (Ca) can induce the closure of stomata (Engineer et al., 2015), and a decrease of CO2 concentration will induce stomatal opening. The atmospheric CO2 concentration has been increasing at a speed of 2 ppm per year since 2005. The signaling pathway for elevated CO2 induced stomatal closure shares many elements and events with the well-studied ABA signaling pathway, including activation of OPEN STOMATA1 (OST1) and its target SLOW-TYPE

ANION CHANNEL 1 (SLAC1) (Xue et al., 2011), increased reactive oxygen species

(ROS) (Shi et al., 2015), increased NO production (Shi et al., 2015), as well as increased cytosolic Ca2+ concentration (Schwartz et al., 1988; Webb et al., 1996).

However, the upstream signaling steps of CO2 diverge from the ABA signaling pathway.

Several mutants that are specifically insensitive to elevated CO2 have been identified, including the carbonic anhydrases mutant ca1ca4 (Hu et al., 2010), rhc1 (resistant to high CO2 1) (Tian et al., 2015), and ht1 (high temperature 1) (Tian et al., 2015). A comprehensive review of CO2 signaling in guard cells has been published recently

(Engineer et al., 2015). Briefly, the signaling of CO2 starts with the conversion of CO2 to bicarbonate by the activity of CA1 and CA4, then the increased bicarbonate

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concentration in cytosol activates RHC1, which further suppresses HT1, a negative regulator of high CO2 induced stomatal closure. The inhibition of HT1 removes its inhibition on OST1 activity, which further activates SLAC1 and facilitates stomatal closure by transporting Cl- from cytosol to the intercellular space (Tian et al., 2015).

OST1 also activates RBOHD/F to promote H2O2 production, which lead to a ROS burst in the cytosol. NO production is known to be downstream of ROS, and both H2O2 and

NO can activate the tonoplast Ca2+ channel to trigger the release of Ca2+ into the

2+ cytosol. The increase in cytosol Ca is an important step for CO2 induced stomatal closure (Webb et al., 1996; Young et al., 2006), and it activates the SLAC1 channel

(Xue et al., 2011). A rapid type anion channel AtALMT/QUAC1, responsible for malate2- export, has also been identified to be involved in high CO2 induced stomatal closure

(Meyer et al., 2010). Another malate transporter, AtABCB14, which mediates malate import from intercellular space, has been shown to be a negative regulator for high CO2 induced stomatal closure (Lee et al., 2008). Previously, we have observed an increase of jasmonic acids in guard cells under elevated CO2 (Chapter 2). This increase was not observed in ca1ca4 mutant, and JA biosynthesis and signaling mutants exhibit an impaired high CO2 response. These results indicate a possible role of jasmonic acids in high CO2 induced stomatal closure.

Despite the progress made recently in understanding elevated CO2 induced stomatal closure (Engineer et al., 2015; Tian et al., 2015; Chapter 2), the mechanism underlying low CO2 induced stomatal opening is not clear. Mutants that are known to be insensitive to low CO2 induced stomatal opening include ca1ca4, ht1, ost1, slac1, patrol1, rboh, and nr. Among these mutants, ht1 and ptrol1, both screened by a high

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leaf temperature phenotype, have constant high CO2 responses (Hashimoto et al.,

2006; Matrosova et al., 2015). Nitrate reductase mutant, nr tomato plants have similar level of stomatal conductance as wild type, and all other mutants have either more opened stomata or higher conductance than wild type. All these mutants showed impaired low CO2 response, but only ht1 has completely lost the low CO2 response. The double mutant of ost1 ht1 has an intermediate level of conductance relative to the single ost1 and ht1 mutants, but does not have a low CO2 response, indicating HT1 is epistatic to ost1 in low CO2 induced stomatal opening (Matrosova et al., 2015).

Despite these physiological and genetic studies, hardly any studies have reported metabolic changes in guard cells under low CO2 (Azoulay-Shemer et al., 2016;

Zeiger and Zhu, 1998). Small molecules play key roles during stomatal movement including osmotic regulation, signaling, as well as antioxidant activities that regulate guard cell redox status (Misra et al., 2015a). Sugars, sugar alcohols, and organic acids can contribute to turgor pressure together with inorganic ions, leading to guard cell volume change, and thus stomatal opening or closure. The most extensively studied organic osmolytes in guard cells are malate and sucrose (Daloso et al., 2015a; Daloso et al., 2015b; Lawson et al., 2014; Lee et al., 2008; Medeiros et al., 2016). Small molecules that are known to act as signaling molecules in guard cells include phytohormones (Daszkowska-Golec and Szarejko, 2013; Misra et al., 2015a; Murata et al., 2015), lipids (Jung et al., 2002; Sakaki et al., 1995), zeaxanthine (Assmann, 1999;

Zeiger and Zhu, 1998; Zhu et al., 1998), as well as cGMP (Pharmawati et al., 1998).

The glutathione ascorbate cycle is the best known ROS scavenging pathway. In

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addition, flavonols have been shown to play a role in ROS scavenging, and can repress

ABA induced stomatal closure (Watkins et al., 2014).

In order to characterize metabolome level changes in the course of low CO2- induced stomatal closure, we applied hyphenated mass spectrometry (MS)-based metabolomics and proteomics approaches to analyze short-term low CO2 responses in

B. napus (canola) guard cells. A total of 411 metabolites were quantified. We observed decreased trends in the biosynthesis of primary metabolites (e.g., most common amino acids, nucleotides, and sugars) and increased levels of osmoregulators, such as sucrose, malate and mannitol, at both early and late time points. In contrast to elevated

CO2 conditions, JA biosynthesis was not altered. Instead, phytohormones that induce stomatal opening, including cytokinins, auxins, as well as GA increased at early time points. This study highlights the utility of single cell-type metabolomics in discovering and testing new nodes and edges in guard cell signaling and metabolic networks regulating the CO2 responses.

Materials and Methods

Plant Materials

B. napus var. Global seeds obtained from Svalöv Weibull AB (Svalöv, Sweden) were grown as previously described (Zhu et al., 2010). Fully expanded leaves from well- watered seven weeks old plants were used for stomatal movement analysis and guard cell purification. A. thaliana mutant seeds coi1-12 was provided by Dr. Zhonglin Mou,

Department of Microbiology and Cell Science, University of Florida, and ca1ca4, lox2 mutants were obtained from the Arabidopsis Biological Resource Center (ABRC, Ohio

State University, Columbus, USA). Seeds were germinated on a half strength

Murashige and Skoog (MS) (Murashige and Skoog, 1962) media prior to transferring to

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soil. Arabidopsis plants were grown under a photosynthetic flux of 140 µmol photons m-2 sec-1 and an 8 h light/16 h dark cycle for six weeks.

Preparation of Epidermal Peels for Stomatal Movement Assay

Small squares (0.5 × 0.5 cm2) of leaf pieces from 8 weeks old B. napus plants were fixed abaxial side down onto coverslips coated with medical adhesive (Hollister,

(w/v) PVP-40 (Calbiochem , Billerica, Massachusetts, USA), 0.25 % (w/v) BSA

(Research Products International Corp., Mt Prospect, Illinois, USA), 0.7 % Cellulase R-

10 (Yakult Honsha Co., Ltd, Tokyo, Japan), and 0.025% Macerozyme R-10 (Yakult

Honsha Co., Ltd, Tokyo, Japan) in 55% basic solution (0.55 M sorbitol, 0.5 mM CaCl2,

0.5 mM MgCl2, 0.5 mM ascorbic acid, 10 µM KH2PO4, 5 mM MES-Tris, pH 5.5 adjusted with 1 M KOH) at 26 °C, 140 excursions per min for 13 min. The coverslips were then incubated with a stomatal incubation buffer (10 mM KCl, 50 μM CaCl2, 10 mM MES-

KOH, adjusted to pH 6.15 with 1 M KOH) under light (110 µmol m-2 s-1) for an hour.

Incubation buffers were bubbled with 400 ppm or 0 ppm CO2 balanced air (Airgas, Inc.,

USA) for at least 1 hour before being used for any treatment. For low CO2 treatment, the stomata were first stabilized in 400 ppm CO2 balanced incubation buffer for 15 min and then exposed continuously to 0 ppm CO2 balanced incubation buffer for a period of

60 min as previously described (Hu et al., 2010).

Metabolite Extraction

Samples of 10 mg dry weight (DW) were analyzed on GC-MS and LC-MS/MS at

Metabolon® Inc. (Durham, NC, USA). Metabolite extraction and derivatization for GC-

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MS was conducted as previous described (Yan et al., 2014) . Briefly, samples were extracted in sequential with four different extraction buffers. The four different extraction buffers are: 400 μL tridecanoic acid (2.5 mg/mL) dissolved in ethyl acetate:ethyl alcohol

(1:1), 200 μL methanol, 200 μL methanol:H2O (3:1), and 200 μL dichloromethane : methanol (1:1). Each extraction was carried out on a Geno/Grinder 2000 homogenizer

(Glen Mills Inc., NJ, USA) for 2 min in the above extraction buffers, and the supernatants of each extraction were collected after centrifugation and pooled together.

Aliquots of the pooled extract were used for LC-MS and GC-MS metabolite detection respectively. GC-MS aliquots were further derivatized using bistrimethylsilyl- trifluoroacetamide and acetonitrile:dichloromethane:cyclohexane (5:4:1) with 5% triethylamine at 60 °C for 1 h.

The above samples of 100 mg DW were used for our in-house targeted analysis on as previously described (Chapter 2). Briefly, samples were homogenized for 20 s at

1900 strokes/min on a GenoGrinder (Geno/Grinder 2000, SPEX SamplePrep.,

Metuchen, NJ, USA) in a screw-capped tube. A metal ball was added to each tube before homogenizing. 10 µL of internal standard mixture (100 M lidocaine and 100 M

10-camphorsulfonic acid) was added to each sample. Metabolites were extracted 1 mL of each extraction solvents, 80% methanol, acetonitrile: isopropanol: water (3:3:2), and acetonitrile: water (1:1) on a thermomixer (Thermomixer R, Eppendorf, Hamburg,

Germany) at 4°C and 1100 rpm for 15 min each time. Samples were then sonicated for

15 min on ice and centrifuged at 13000 g for 15 min at 4 °C. The combined supernatants were lyophilized and re-dissolved in 100 L of 0.1% formic acid in water at

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room temperature for 15 min. Then centrifuged at 13000 g for 15 min at 4 °C.

Supernatants were then subjected for metabolite detection.

Metabolite Profiling

Samples for GC-MS and UPLC-MS analysis were profiled as described previously (Bridgewater Br, 2014; Lawton et al., 2008). Derivatized GC-MS samples were separated on a 5% diphenyl / 95% dimethyl polysiloxane fused silica column (20 m x 0.18 mm ID; 0.18 um film thickness) with helium as carrier gas and a temperature ramp from 60° to 340°C in a 17.5 min period. Samples were analyzed with a Trace DSQ fast-scanning single quadruple mass spectrometer (Thermo Scientific Inc., San Jose,

CA, USA) operated at unit mass resolution with electron impact ionization. The mass range was from 50 – 750 m/z. Samples for LC-MS were reconstituted in water with

0.1% formic acid for reverse phase positive mode, 0.1% formic acid in 6.5mM ammonium bicarbonate for negative mode, and 10mM ammonium formate, for HILIC negative mode detection. The column for reverse phase analysis (both positive and negative mode) is a Waters UPLC BEH C18 (2.1x100 mm, 1.7 μm) column, and the column for HILIC separation is a Waters UPLC BEH Amide (2.1x150 mm, 1.7 μm) column. Solvent used for reverse phase positive mode is 0.1% formic acid in water

(solvent A) and methanol (solvent B), for reverse phase negative mode is 6.5 mM ammonium bicarbonate in water (A) and methanol (B), and for HILIC negative mode is

10 mM ammonium formate in water (A) and acetonitrile (B). The UPLC system is an an

Acquity UPLC (Waters, Millford, MA, USA) system. The gradient of solvent B for reverse phase column was ramped from 0.5% to 70% in 4 min, then from 70% to 98% in 0.5 min, then held at 98% for 0.9 min, then return to 0.5% in 0.2 min, and then finally held at

0.5% for 5.4 min. And the flow rate is 0.35 mL/min. The gradient of solvent B for HILIC

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column was ramped from 5% to 50% in 3.5 min, then to 95% in 2 min, then held at 95% for 1 min, and ramp back to 5% in 0.2 min, with a final hold at 5% for 4.3 min. And the flow rate is 0.5 mL/min. The UPLC was connected to a Thermo Scientific Q-Exactive high resolution/accurate mass spectrometer interfaced with a heated electrospray ionization (HESI-II) source and Orbitrap mass analyzer operated at 35,000 mass resolution. The MS analysis alternated between MS and data-dependent MS2 scans using dynamic exclusion, and the scan range was from 80-1000 m/z. The spray voltage for reverse phase positive mode, negative mode, HILIC negative mode was 4 kV, 2.75 kV, and 3 kV respectively. The source heater temperature for reverse phase positive and negative mode was 400 °C, and for HILIC was 380 °C. The ion transfer tube temperature was 300 °C for the two mode from reverse phase, and 400 °C for HILIC.

The normalized collision energy for reverse phase positive mode, negative mode and

HILIC negative mode was 40, 60, 60 au respectively.

HPLC-MRM-MS was conducted using an Agilent 1100 HPLC (Agilent, Santa

Clara, CA, USA) coupled with an AB Sciex 4000 QTRAPTM (AB Sciex, Framingham,

MA, USA). Optimized detection conditions were as previously described (Chapter 2). An

Agilent Eclipse XDB-C18 column (4.6 x 250 mm, 5 µm) was used for metabolite separation with 0.1% formic acid in water as solvent A and 0.1% formic acid in acetonitrile as solvent B. The LC gradient was initially held at 1% solvent B for 5 min, then a linear gradient was imposed from 1% B to 99.5% B over 41.5 min, followed by holding at 99.5% B for 4.5 min, and then return to 1% B in 0.3 min, with a final hold at

1% B for 8.7 min. The flow rate was 0.5 mL/min. The mass spectrometer conditions were: 30 psi curtain gas, 50 psi GS1, 55 psi GS2, ion source voltage 4500 V, with the

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Turbo ElectroSpray Ionization (ESI) interface temperature at 350 °C. A multiple period method was followed as previously described (Chen et al., 2013). Details about the period (segment) design are provided in (Supporting Information Table S1).

Metabolomics Data Processing and Statistical Analysis

All data were combined to a final peak list (Supplemental Information Table S2) and were processed and analyzed using R version 3.2.5 (R Development Core Team,

2015). Missing values were imputed using a k-Nearest Neighbor (KNN) method (Hastie et al.). Differentially changed metabolites were analyzed using R-based empirical analysis of digital gene expression in R (EDGE) package as previously described (Jin et al., 2013; Storey JD, 2015). Comparisons were made between treatment and control samples for each time point. The full model took CO2 concentration as the variable of interest, replicate batch as adjustment variables, and a null model only replicate batch as adjustment variables. A total of 2000 bootstrap iterations were performed for each comparison. Heat maps for the significantly changed metabolites were generated using heatmap2 function in R package “gplot” (Marc, 2015).

Metabolic Pathway Mapping and Enrichment Analyses

Metabolic pathway analyses were performed for metabolites at each time point separately using the pathway analysis functionality in MetaboAnalyst 3.0 (Xia et al.,

2015). Raw data were uploaded to MetaboAnalyst 3.0 webserver and only metabolites that could be mapped to the KEGG pathway database were used. A log2 transformation was used to normalize and scale the data before further analysis.

Protein Extraction and 10-Plex Tandem Mass Tag (TMT) Labeling

Proteins were extracted using a phenol protein extraction method (Mostafa et al.,

2016). Frozen enriched stomata samples (100 mg fresh weight each) were ground with

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a mortar and a pestle in liquid nitrogen into fine powder. Then 1.25 mL of 10 mM Tris-

HCl, pH 8.0 saturated phenol and 1.25 mL of extraction buffer (0.1M Tris-HCl pH8.8,

10mM EDTA, 0.4%β-Me, 0.9M sucrose) was added to the sample sequentially. The mixture was agitated at room temperature for 2 h. The samples were centrifuged at

5000 g for 10 min at 4 °C. The phenol layer was transferred to a new tube, and another

1.25 mL phenol was added to the bottom layer to back extract at room temperature for

30 min. After centrifugation at 5000 g, 4 °C, the phenol layer was combined with the previous extraction, and protein was precipitated with 5 volumes of pre-cooled 0.1 M ammonium acetate in 100% methanol overnight at -20 °C. The protein was then pelleted by centrifugation at 20000 g for 20 min at 4 °C. The pellet was washed twice with 0.1M ammonium acetate in methanol, twice with 80% acetone and once with 100% acetone (all pre-cooled to -20 °C). The protein pellet from the last wash was lyophilized briefly and re-suspended in a TMT sample buffer (100 mM triethyl ammonium bicarbonate, TEAB). Samples were assayed using an EZQ protein assay kit (Thermo

Fisher Scientific Inc., San Jose, CA, USA) according to manufacture instructions. A total of 30 µg of samples were precipitated in pre-cooled acetone overnight at -20 °C, and centrifuged at 12000 g, 4 °C for 15 min. Protein pellets were briefly dried and then re- desolved in 50 l 100 mM TEAB buffer, then reduced with Tris (2-carboxyethyl) phosphine at a final concentration of 10 mM for 1 h. Iodoacetamide was then added to the sample to a final concentration of 17 mM to alkylate the samples for 30 min at room temperature in dark. Six volumes of pre-chilled (-20 °C) acetone was then added to the sample and samples were precipitated at -20 °C overnight. Samples were then centrifuged at 8000 g for 10 min at 4 °C. The supernatant was carefully removed and

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the pellets were lyophilized briefly, before solubilized in 50 L of 100 mM TEAB. For trypsin digestion, 1.5 g of trypsin was incubated with each sample at 37 °C overnight.

TMT labels were dissolved in 41 l of anhydrous acetonitrile, and half of the label was used for each of the two biological replicates. The label 126, 127N, 127C, 128N, 128C,

129N, 129C, 130N, 130C, and 131 were used to label 0 min, 5 min control, 5 min treatment, 10 min control, 10 min treatment, 30 min control, 30 min treatment, 60 min control, 60 min treatment, and internal standard, respectively. Samples were labeled for

1 hour and then quenched with 4 L of 5% hydroxylamine for 15 min. All samples were combined, lyophilized, and reconstituted in 100 L 0.1% TFA (Trifluoroacetic acid) solution. A Macrospin C-18 reverse phase mini-column with a capacity of 30–300 μg

(The Nestgroup Inc., Southborough, MA, USA) was used to desalt the samples. The column was first equilibrated twice with 500 μL each of 100% acetonitrile, 80% acetonitrile and 0.1% TFA in water. Then sample was loaded twice on to the column.

After washing with 500 μL 0.1% TFA, peptides were eluted with 200 μL 80% acetonitrile, followed by lyophilization to dryness.

Strong Cation Exchange Fractionation and LC-MS/MS Analysis

The TMT labeled peptides were fractionated on a polysulfoethyl A strong cation exchange column (2.1 × 100 mm, 5 µm, 300 Å, PolyLC, Columbia, USA). Solvent A

(25% (v/v) was acetonitrile, 10m Mammonium formate, and 0.1% (v/v) formic acid, pH

2.8) for 10 min, and solvent B was (25% (v/v) acetonitrile and 500 mM ammonium formate, pH 6.8. The gradient for solvent B was as follows: hold at 0% for 10 min, ramp up to 20% in 80 min, then increase to 100% in 5 min and hold for 10 min. Peptide absorbance at 280 nm was monitored and 38 fractions were collected and then

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combined into 12 fractions based on the elution profile. These fractions were lyophilized and re-dissolved in 30 μL 0.1% TFA in water and cleaned up using ZipTipµ-C18 (Millipore,

USA). Each ziptip was equilibrated with 10 μL each of 100% acetonitrile, 50% acetonitrile, and 0.1% TFA trice before sample loading. Fractions were loaded five times and cleaned with 0.1% TFA trice and eluted with 10 μL 80% acetonitrile. Each fraction was lyophilized and solubilized in 15 μL 0.1% FA for LC-MS detection.

The samples were analyzed on an Easy-nLC 1200 system coupled to a Q-

Exactive Orbitrap Plus MS (Thermo Fisher Scientific Inc., Bremen, Germany) system.

The peptides were concentrated on an Acclaim Pepmap 100 pre-column (20 mm × 75

μm; 3 μm-C18) for 20 uL at 1180 bar, then separated on a PepMap RSLC analytical column (250 mm × 75 μm; 2 μm-C18). Water and 80% acetonitrile with 0.1% formic acid were used as solvent A and B. The gradient for solvent B ramped from 2–30% in 100 min, then from 30–98% in 10 min, held at 98% for 10 min. The flow rate was 350 nL/min. Positive ion mode with data dependent scanning higher-energy collision dissociation (HCD) was used as previously described (Jones et al., 2013). The chromatography peak width was 4 s and the default charge state was 3. The full MS resolution was 70,000 with a scan range of 400–2000 m/z, an AGC target of 1e6 and maximum IT of 100 ms. The tandem mass spectrum resolution was 35,000, an AGC target of 2e5, maximum injection time of 117 ms, a loop count of 10, an isolation window of 1.3 m/z, a fixed first mass of 115 m/z and the NCE of 32. A lock mass of polysiloxane ion (445.12003 m/z) was used for real-time mass locking. The spray voltage was set to be 1900 volts, the capillary temperature was 320 °C, and the stacked ring ion guide RF was set to 70.

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Protein Identification and Quantification

Peptides were identified using proteome discover 1.4 software (Thermo Fisher

Scientific Inc., Bremen, Germany), searched against a customized B. napus database.

The database was downloaded from Genescope (Chalhoub et al., 2014). Redundant sequences were removed with patpd program from AB-BLAST 3.0 (Gish, 1996-2009).

The filtered database was then subjected to redundant entry clustering using the perl script nrdb90 with an identity level at 95% (Holm and Sander, 1998). The final database contains 79366 non-redundant proteins. The annotation was done by blasting against the non-redundant green plant database from NCBI using Blast2Go (Conesa and Götz,

2008). The protein quantification was done with the SEQUEST algorithm with the following parameters: 10 ppm tolerance for precursor mass tolerance, and 0.02 Dalton for fragment mass tolerance, allowing two missed cleavage sites, TMT10plex label on the N-terminal, carbamidomethylation (C), oxidation (M), phosphoralation (S, T, Y), and deamidation on the N-terminal as variable modifications. Peptides were filtered using a stringent Xcorr value cut off at 2.31 for 2+, 2.41 for 3+, 2.6 for 4+ and 5+ peptides.

Peptide quantification result was exported for further processing and statistical analysis.

The peptide quantification was first normalized by the mean of each tag, then sum of the same peptide was calculated and used as the quantification for that peptide. Only peptides that were present in both biological replicates and were unique for their corresponding proteins were used for protein quantification. Ratios of 0 ppm CO2 treated sample to 400 ppm CO2 treated control were calculated for each time point

(127C/127N for 5 min, 128C/128N for 10 min, 129C/129N for 30 min, and 130C/120N for 60 min). Fold changes for proteins were the means of all unique peptides identified from that protein filtered from the previous step. Student’s t-tests were performed with

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the log2 transformed fold changes for each time point. A singular enrichment analysis

(SEA) was performed for proteins with a p-value less than 0.05 using agriGO (Du et al.,

2010). Since no B. napus reference database is available, Arabidopsis was used as a reference background.

Results

Low CO2 Induced Stomatal Opening and Overview of Low CO2 Responsive Guard Cell Metabolome

To determine the time points for low CO2 induced stomatal opening, B. napus stomatal apertures were recorded at seven different time points during the one-hour treatment either under ambient (400 ppm) or low (0 ppm) CO2 conditions. Stomatal aperture under low CO2 treatment gradually increased, and became significantly different from the control samples at 5 min and onwards (Figure 3-1 A, B). After one hour, the stomatal aperture became stable. According to the acquired stomatal movement data, we chose to collect our guard cell samples at 0, 5, 10, 30 and 60 min after treatment with elevated CO2 for metabolomics.

Using different hyphenated-MS based metabolomics platforms, we identified 411 unique metabolites (Table 3-1). Numbers of differentially accumulated metabolites at each time point were shown in Figure 3-1C. Unlike under elevated CO2, the number of significantly increased metabolites decreased over the one-hour treatment (Figure 3-

1C). The number of significantly decreased metabolites was the highest at 10 min. At 60 min, the decreased metabolites exceeded the increased metabolites correlating well with the decreased carbon source under low CO2 condition. The initial increase in many metabolites could be caused by catabolism of larger storage molecules. Due to low CO2 induced stomatal opening, osmolytes need to accumulated to provide adequate turgor.

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Therefore, the initial metabolite increase is expected. The significantly accumulated metabolites are specific to each time point (Figure 3-1D) and belong to different metabolic pathways (Figure 3-2). At 5 min, biosynthesis of unsaturated fatty acids, and nicotinate and nicotinamide metabolism are significantly altered. At 5 and 10 min, fatty acid and flavonoid biosynthesis showed significant changes, both of which also responsd to elevated CO2. Interestingly, melatonin, a well-studied animal hormone regulating circadian rhythms and various biological processes and behaviors, was also increased at 10 min.

Lipid Metabolism under Low CO2

Lipid metabolism showed significant changes at 5 and 10 min according to the pathway enrichment analysis (Figure 3-2). Since many of the lipids identified cannot be assigned with a KEGG ID, and thus were not included in the pathway enrichment analysis, we chose to examine all the lipid metabolites (Table 3-1). The lipids detected in our data are mainly short chain free fatty acids and monoacylglycerols since they are less hydrophobic than di- or tri-acylglycerols and long chain fatty acids, and are thus easier detected on a LC system. At 5 min, most lipids and fatty acids increased. Yet from 10 min onwards, most lipids decreased (Figure 3-3). This trend is similar for both saturated and unsaturated lipids, and among short chain, long chain and very long chain lipids (Figure 3-3). This may be an indication of a quick induction of free fatty acids production either from intercellular lipid stores or from de novo biosynthesis under low CO2 induced stomatal opening. After 10 min, as these free fatty acids were incorporated into membrane or utilized for energy generation, the total level of free fatty acids decreased again, presumably due to the lack of carbon source for further fatty acid biosynthesis. Our proteomics data (described below) indicates that under low CO2,

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proteins involved in catabolic processes are enriched (Figure 3-7 A). Thus the initial increase in lipids is more likely due to a breakdown from internal lipid stores such as acylgycerals. Consistent with this assumption, at 5 min, 2 GDSL esterase lipases were significantly increased. Only two lipids showed significant decreases at 5 min, both phospholipids. Consistent with this result, phospholipase A1-IIα showed significant decreases at 5 min. The product of phospholipase Dα has been shown to be a positive player of ABA induced stomatal closure (Zhang et al., 2009). Thus the decreased levels of phospholipids and phospholipase are consistent with the stomatal opening phenotype under low CO2.

Phytohormone Changes under Low CO2

Jasmonic acids were previously shown to be involved in elevated CO2 induced stomatal closure (Chapter 2). Under low CO2, however, we only observed an increase of the intermediate 13(S)-hydroperoxylinolenic acid at 5 min. There were no significant changes in JA, MeJA or 12-oxo-phytodienoic acid. Interestingly, the branch pathway product traumatic acid showed significant increases with a very high fold change (> 7- fold from 10 min onward) (Figure 3-4). This diversion from JA biosynthesis to a branch pathway could potentially facilitate stomatal opening under low CO2. We tested the stomatal movement response of JA biosynthesis mutant lox2 and signaling mutant coi1, and found that both mutants were able to open under low CO2. This result indicates that jasmonic acids are not involved in low CO2 induced stomatal movement. Similar to JA, abscisic acid did not show significant changes under low CO2 either. But the ABA catabolic products, phaseic acid (1.49-fold at 5 min) and dihydrophaseic acid (> 2.4-fold from 10 min onward) showed significant increases (Figure 3-1). On the other hand, hormones that have been shown to induce stomatal opening including auxins,

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cytokinins, brassinosteroids and gibberellins showed increasing trends under low CO2

(Figure 3-5). Except for zeatin riboside, which significantly increased at 60 min, all other hormones listed above increased at early time points (5 or 10 min), suggesting possible crosstalk between low CO2 signaling with the hormone signaling pathways.

Proteomic Changes under Low CO2

In order to investigate proteomic changes and validate the metabolomic data, we performed a proteomics study using the same materials as with metabolomics study.

Proteins with significant changes are listed in Table 3-2. Interestingly, the number of significantly changed proteins showed very similar trends as the metabolite changes.

The number of significantly increased proteins decreased over time, while the number of significantly decreased proteins showed decreasing trend during the time course

(Figure 3-6). Single enrichment analysis was performed for proteins that show significant changes at one or more time points. The biological process enrichment result indicates that these differentially accumulated proteins are enriched in metabolic processes, especially oxidation reduction, carbohydrate catabolism, proteolysis, and cellular nitrogen compound metabolism. In the molecular function GO term enrichment analysis, similar results were obtained, i.e., the proteins were enriched in catalytic activity, protein and nucleotide binding activity and antioxidant activity. Among these significantly changed proteins, several with interesting functions were selected for discussion below.

At 5 and 10 min, two V-type ATPase subunits were found to be significantly increased. These proteins can be responsible for proton transportation to induce cytosolic acidification under low CO2 induced stomatal opening. Guard cell V-type

ATPase activity was found to be insensitive to ABA or fusicoccin treatment in C.

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communis (Willmer et al., 1995); thus, it may be a regulator specific for low CO2 response. In addition, at 5 min a probable aquaporin PIP2;5 was increased (Table 3-2).

Aquaporin is one of the channels for CO2 import into the cytosol. Although a knockout mutant pip2;1 did not show significant differences in high CO2 induced stomatal closure compared to wild type, it has been indicated that PIP2;1 can physically interact with

CA4, located on the plasma membrane, to facilitate activation of the CO2 signal transduction (Wang et al., 2016). Thus, PIP2;5 may have a similar function under low

CO2. Furthermore, at 10 min, a predicted voltage dependent potassium channel beta subunit (KAB1), which can physically interact with KAT1 and is highly expressed in guard cells compared to mesophyll cells (Tang et al., 1996), increased 1.21-fold. K+ channels are important for the stomatal opening process (Kwak et al., 2001; Outlaw and

Lowry, 1977; Sato et al., 2009). A subtilisin-like protease 2 showed an increase at 5 min. Substilisin-like protease SSD1 was shown to be responsible for cleaving

EPIDERMAL PATTERNING FACTOR 2 (EPF2) and producing the active form of EPF2.

The loss of SSD1 will cause a hypersensitive elevated CO2 induced decrease of stomatal index (Engineer et al., 2014). So we would expect a higher SSD protein level under lower CO2 conditions to produce a high stomatal index. However, how SSDs are involved in regulating stomatal movement under low CO2 is not known.

Consistent with the phytohormone changes mentioned in the previous section, auxin transporter 3, and gibberellin-regulated 14 like proteins were significantly increased at 5 and 10 min, respectively, supporting the hypothesis that auxin and gibberellin may play a role in low CO2 induced stomatal opening. At 30 min, an isoflavone reductase homolog P3-like protein showed a significant decrease.

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Isoflavonone reductase has been shown to be down regulated when treated with ROS scavengers such as glutathione and diphenyleneiodonium (DPI) (Kim et al., 2010a).

Thus the decrease of isoflavone reductase may be an indicator of active ROS scavenging process during stomatal low CO2 response.

Comparison between High and Low CO2 Responsive Metabolites

Changes in metabolites under low and elevated CO2 (from our previous study) are compared here to give a better understanding of CO2 regulation of guard cell metabolism and signaling. Interestingly, the changes in many different groups of metabolites, especially phytohormones, sugars, and flavonoids showed opposite trends under elevated and low CO2 treatments. Phytohormones that induce stomatal opening, including auxin, cytokinin, gibberellin showed increases under low CO2 but not under elevated CO2, and phytohormones that induce stomatal closure, such as ABA and JAs showed increases under elevated CO2 but not under low CO2. Sugars, sugar alcohols and organic acids, which are key players for osmoregulation, mostly showed increases under low CO2 and no change or decreases under elevated CO2. Interestingly, malate showed increases both under elevated and low CO2. The source of malate may be different under these two conditions. Since guard cells have a similar way of incorporating CO2 as C4 plants, it is likely that a temporal increase of CO2 under elevated CO2 increases malate through the activity of pyruvate carboxylase and malate dehydrogenase (Daloso et al., 2015a; Gotow et al., 1985; Scheibe et al., 1990) . Under low CO2, since the activity of pyruvate carboxylase will be inhibited by the low availability of CO2, it is possible that malate is channeled to the cytosol through starch degradation (Azoulay-Shemer et al., 2016; Horrer et al., 2016). Nevertheless, the increase of malate under elevated CO2 is contradictory with previous findings related to

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stomatal closure in response to other stimuli such as ABA and darkness. More research is clearly needed to elucidate the roles of malate in guard cell CO2 responses.

Two groups of flavonols, quercetins and luteolins have been shown to increase transiently at 5 and 10 min under elevated CO2 (Chapter 2). Interestingly, under low

CO2, both metabolites showed decreases rather than increases. Since flavonols have been suggested to be ROS scavengers that may regulates ABA response in guard cells, and ROS level decreases under low CO2 (Shi et al., 2015), this decrease of flavonols may better utilize limited carbon under low CO2.

Discussion

Primary Metabolism Changes under Low CO2

In general, the primary metabolism in guard cell under low CO2 tilts towards catabolism instead of anabolism, which may be due to the limited availably of CO2.

Recently, it has been shown that the breakdown of stored triacylglycerols is an essential process for light induced stomatal opening, and the fatty acids generated during this process may be utilized for energy production to promote stomatal opening (McLachlan et al., 2016). Here we showed that initial increases of free fatty acids and monoglyceryl lipids were observed under low CO2 induced stomatal opening, and two GDSL esterase lipases significantly increased at 5 min. This result indicates that the break-down of stored lipids may also provide energy for guard cell low CO2 response. In the meantime, membrane expansion is needed for stomatal opening processes, thus the free fatty acids may also be utilized for new membrane lipid synthesis. Roh family members of the Ras-related G proteins were found to be involved in endocytosis processes during

ABA and elevated CO2 induced stomatal closure. The loss of ROP2 caused impaired stomatal response to light, ABA and elevated CO2 (Hwang et al., 2011). Here we found

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that two Ras-related proteins were increased at 5 and 10 min. The functions of these proteins in low CO2 guard cell response are not known and need to be further investigated.

Stomatal opening is an energy consuming process. The source of guard cell energy can come from either photosynthesis or respiration (Azoulay-Shemer et al.,

2015; Raghavendra and Vani, 1989), and the importance of guard cell photosynthesis has been under debate for a long time (Araujo et al., 2011; Azoulay-Shemer et al.,

2015; L., 2008). Our metabolomics data showed a significant alteration in glycolysis, starch and sucrose metabolism, as well as the pentose phosphate pathway (Figure 3-

2). Consistent with the metabolomics result, the GO term enrichment analysis for significantly changed proteins indicates significant changes in the glycolysis pathway

(Figure 3-2). Proteins involved in glycolysis and the TCA cycle, including glycerol-3- phosphate dehydrogenase, a L-lactate dehydrogenase B-like protein, a predicted fructose-bisphosphate aldolase, enolase/phosphopyruvate hydrease, aconitate hydratase and pyruvate dehydrogenase E1 component subunit alpha, increased at both early and later time points. Meanwhile, ribulose bisphosphate small subunit decreased at 5 min (Table 3-2). A recent study using chlorophyll-less guard cells showed that guard cell CO2 response does not depend on photosynthesis (Azoulay-Shemer et al.,

2015), indicating respiration may be the main source of energy production during CO2 induced stomatal movement.

Phytohormone Crosstalks in Guard Cells under Low CO2 Induced Stomatal Opening

In this study, we found that many phytohormes known to induce stomatal opening may coordinately facilitate the stomatal opening response to low CO2. Auxins

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were found to counteract ABA induced stomatal closure by preventing further ROS and

NO production, but it cannot remove ROS and NO that is already present in the cells

(She and Song, 2006; Song et al., 2006). Cytokinins can help to remove ROS and NO that are already present in the cells, as well as prevent further ROS and NO production

(She and Song, 2006; Song et al., 2006). Brassinosteroids (BR), on the other hand, can induce stomatal opening or closure depending on the concentration. Evidence on BR induced stomatal movement has been controversial. A BR deficient mutant was shown to be hypersensitive to ABA induced stomatal closure (Ephritikhine et al., 1999). But in most studies where BR is exogenously applied to plants, it induces stomatal closure

(Haubrick et al., 2006; Xu et al., 1994a; Xu et al., 1994b). Recently it has been reported that the effects of BR are concentration dependent. Lower concentrations of BR induce stomatal opening, while higher concentrations promote stomatal closure (Xia et al.,

2014a). Here we observed increases in auxins, cytokinins, as well as BR at early time points. Since we were monitoring a stomatal opening process, these hormones may help promote stomatal opening. But absolute quantification for these hormones need to be done in order to confirm this point. Given that these phytohormones can induce stomatal closure when applied exogenously at high concentrations, absolute quantification of these hormones in the cells may be needed to reach conclusive results.

Previously we reported a role of JA signaling in elevated CO2 induced stomatal closure (Geng et al., 2016). Under low CO2 conditions, we did not observe significant changes in JA levels. However, a JA precursor, 13-HPOT, showed a significant increase at 5 min; and a branch pathway product, traumatic acid, which competes with

JA for the common intermediate 13(S)-HOTrE, showed significant increases at the later

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time points (Table 3-1, Figure 3-4). Studies on drought stress in rice showed that the hydroperoxide lyase (HPL) branch which leads to green leaf volatile and traumatic acid production, competes with the AOS branch, which leads to JA production (Liu et al.,

2012). This induction of traumatic acid indicates a diversion from JA biosynthesis.

Similarly, ABA catabolism products phaseic acid and dihydrophaseic acid showed significant increases during low CO2 treatment. However, ABA itself was not significantly changed (Table 3-1).

Osmoregulation in guard cells under Low CO2

Stomatal movement, which is caused by guard cell turgor/volume change, is directly regulated by cellular osmolality mediated by ion and solute fluxes. Both inorganic and organic ions contribute to the osmolality during stomatal movement (Lee et al., 2008; Meyer et al., 2010; Misra et al., 2015a; Munemasa et al., 2015). Sucrose and malate were the most interesting organic osmolytes regulating stomatal movement.

Malate is known to be involved in stomatal closure induced by dark (Penfield et al.,

2012), elevated CO2 (Lee et al., 2008) and ABA (Dittrich and Raschke, 1977). Here we observed significant increases in both sucrose and malate throughout the treatment. In pathway enrichment analysis, significantly changed metabolites were enriched in both starch and sucrose metabolism and glycolysis/gluconeogenesis pathways (Figure 3-2).

Together with the observation that significantly changed proteins were overrepresented by proteins in the glycolysis pathway, we may conclude the production of malate and sucrose from starch breakdown is an important pathway to increase the turgor pressure in guard cell under low CO2. Besides sugars, we previously found that mannitol showed decreases of over 5-fold under elevated CO2 (Chapter 2). Here we found that mannitol showed a much less fold change under low CO2 (1.5- to 1.7-folds), which is much lower

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than sucrose (over 4-fold at 10 30 and 60min) (Table 3-1, Figure 3-3). These results further confirm that sucrose is the major osmoregulator in low CO2 induced stomatal opening. Besides starch, glucan has also been indicated to be a source of sucrose during stomatal opening processes (Fricker and Willmer, 1996b). Here we found that a glucan endo-1,3-beta-glucosidase-like protein increased significantly at 5 min (Table 3-

2), suggesting that glucan may also play a role in guard cell low CO2 response.

Redox Regulation in Guard Cells under Low CO2

Redox status is a key player in guard cell response to many biotic and abiotic stimuli (Neill et al., 2008; Pham and Desikan, 2009; Song et al., 2014). The regulation of

ROS production is stringently regulated by a delicate system to maintain homeostasis.

ROS production is increased under elevated CO2 to promote stomatal closure, and when the ROS level is low under low CO2, stomatal opening is promoted (Shi et al.,

2015). Here we report that the significantly changed proteins are enriched in cell redox homeostasis processes. Identified proteins that belong to this group include four peroxidases, a superoxide dismutase, a peroxisomal ascorbate peroxidase, two NADH- ubiquinone oxidoreductases, a sulfate reductase, a sulfate oxidase, and many others involved in various cellular redox regulation processes (Table 3-2). Most of these proteins showed significant increases. The increased amount of peroxidases at 10 and

30 min is consistent with the decreased level of ROS under low CO2. Metabolites related to the ascorbate-glutathione cycle did not show significant changes when compared to ambient control. But when compared to guard cells treated with elevated

CO2 (Chapter 2), dehydroascorbic acid showed significant increase at 60 min, while both glutathione and glutathione disulfide showed significant increases at 30 min. This result indicates an active ROS scavenging process under low CO2 to remove excessive

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ROS and is also consistent with the observation that a mitochondria glutaredoxin increased significantly at 30 min (Table 3-2). Besides the direct ROS scavengers, the increases of auxin, cytokinin, and melatonin can also indirectly decrease ROS levels in guard cells through their independent signaling pathways (Li et al., 2015a; She and

Song, 2006). Here we also found a significant increase of melatonin at 10 min (Table 3-

1). Melatonin has been found to regulate redox status in plants (Arnao and Hernández-

Ruiz, 2006; Li et al., 2015a). Treatment with melatonin can inhibit plant ABA response by attenuating ROS production, as well as repressing the expression of ABA biosynthesis genes, and inducing the expression of ABA catabolism related genes (Li et al., 2015a). However, there has been no report on the effects of melatonin on stomatal movement. Thus, our finding indicates a potential role of melatonin in low CO2 induced stomatal opening, which can be pursued in future studies.

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Table 3-1. Fold changes and p values of significantly changed metabolites in low CO2 treated B. napus guard cells Fold change p-value q-value Detection Metabolite name 5 10 30 60 5 10 30 60 5 10 30 60 Platform min min min min min min min min min min min min LC/MS 2.11 5.17 9.99 8.88 5.98 2.20 4.03 7.02 17-methylstearate 1.82 1.14 1.07 0.81 Neg E-03 E-01 E-01 E-03 E-02 E-01 E-01 E-02 1- LC/MS 3.55 8.98 2.49 6.24 1.81 3.00 2.92 3.33 palmitoylglycerophosph 1.48 1.00 1.28 1.17 Neg E-02 E-01 E-01 E-01 E-01 E-01 E-01 E-01 oglycerol* LC/MS 2-palmitoylglycerol (2- 5.77 3.01 3.91 1.33 8.28 1.59 2.07 1.72 2.82 1.95 3.09 0.74 Neg monopalmitin) E-03 E-01 E-02 E-01 E-02 E-01 E-01 E-01 LC/MS 3.31 1.05 2.83 1.51 1.78 9.33 2.92 1.74 3-deoxyoctulosonate 1.52 0.70 0.82 0.60 Polar E-02 E-01 E-01 E-01 E-01 E-02 E-01 E-01 LC/MS 3.32 4.68 7.41 8.18 1.78 2.04 3.52 3.66 3-methyl-2-oxovalerate 2.12 0.80 0.97 1.32 Neg E-02 E-01 E-01 E-01 E-01 E-01 E-01 E-01 LC/MS 6-oxopiperidine-2- 2.14 4.75 8.67 1.80 5.98 6.48 2.66 1.83 1.83 1.87 0.73 0.64 Pos carboxylic acid E-03 E-02 E-02 E-01 E-02 E-02 E-01 E-01 LC/MS 5.94 3.08 4.07 7.86 8.28 1.62 3.08 3.59 Benzamide 1.60 1.33 1.22 0.92 Pos E-03 E-01 E-01 E-01 E-02 E-01 E-01 E-01 LC/MS 4.17 3.83 4.16 8.82 6.99 1.83 3.09 3.79 Caproate (6:0) 1.52 0.93 0.94 0.99 Neg E-03 E-01 E-01 E-01 E-02 E-01 E-01 E-01 LC/MS 1.55 6.95 6.61 6.76 1.44 7.26 3.46 3.45 Caprylate (8:0) 1.44 0.59 1.18 1.12 Neg E-02 E-02 E-01 E-01 E-01 E-02 E-01 E-01 LC/MS Docosadienoate 2.43 7.19 1.59 9.42 4.06 2.66 1.48 3.90 2.56 1.22 1.27 1.01 Neg (22:2n6) E-04 E-01 E-02 E-01 E-02 E-01 E-01 E-01 LC/MS Eicosenoate (20:1n9 or 2.00 5.86 1.37 3.76 4.06 2.34 2.66 1.22 2.04 1.17 1.54 0.84 Neg 11) E-04 E-01 E-01 E-02 E-02 E-01 E-01 E-01 Gamma-aminobutyrate 4.99 6.69 4.99 9.21 1.93 2.52 3.29 3.86 GC/MS 1.30 0.92 0.80 0.98 (GABA) E-02 E-01 E-01 E-01 E-01 E-01 E-01 E-01 LC/MS Gentisic acid-5- 1.71 5.92 3.20 4.10 1.44 2.35 2.07 2.70 1.39 0.89 0.58 0.83 Neg glucoside E-02 E-01 E-02 E-01 E-01 E-01 E-01 E-01 LC/MS 2.79 8.91 2.36 2.67 1.69 2.99 2.84 2.19 Hypoxanthine 1.36 1.08 0.73 0.77 Neg E-02 E-01 E-01 E-01 E-01 E-01 E-01 E-01

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Table 3-1. Continued Fold change p-value q-value Detection Metabolite name 5 10 30 60 5 10 30 60 5 10 30 60 Platform min min min min min min min min min min min min LC/MS 1.89 1.52 6.57 2.03 5.98 1.07 7.47 3.55 N-acetylglutamate 4.28 0.80 0.15 0.31 Pos E-03 E-01 E-03 E-03 E-02 E-01 E-02 E-02 LC/MS 3.01 1.44 3.61 5.76 1.71 1.05 3.04 3.30 N-acetylproline 1.35 0.91 0.89 1.16 Pos E-02 E-01 E-01 E-01 E-01 E-01 E-01 E-01 LC/MS 9.40 1.25 1.71 3.81 1.05 9.80 2.66 1.22 Nicotinamide riboside 1.88 1.47 1.93 2.42 Pos E-03 E-01 E-01 E-02 E-01 E-02 E-01 E-01 LC/MS 1.12 2.98 1.18 9.18 5.98 1.59 2.66 3.85 Stachydrine 1.86 0.64 0.37 1.04 Pos E-03 E-01 E-01 E-01 E-02 E-01 E-01 E-01 2.18 3.62 2.68 2.20 1.52 6.14 2.92 1.16 LC-MRM 1,3-diaminopropane 1.53 1.84 1.44 1.35 E-02 E-02 E-01 E-02 E-01 E-02 E-01 E-01 4.82 1.36 4.89 1.67 1.93 1.04 3.29 1.07 LC-MRM Sarcosine 1.87 1.60 1.23 1.44 E-02 E-01 E-01 E-02 E-01 E-01 E-01 E-01 3.85 1.78 8.42 8.35 1.81 1.18 3.67 1.46 LC-MRM Betaine aldehyde 1.34 1.39 1.16 1.25 E-02 E-01 E-01 E-02 E-01 E-01 E-01 E-01 4.61 4.85 6.91 2.23 1.93 6.48 3.47 2.07 LC-MRM N,N-dimethylglycine 1.37 1.48 1.23 1.17 E-02 E-02 E-01 E-01 E-01 E-02 E-01 E-01 2.33 3.67 8.07 9.58 6.01 6.15 3.63 3.94 LC-MRM Allantoin 1.59 1.69 1.01 0.99 E-03 E-02 E-01 E-01 E-02 E-02 E-01 E-01 5.37 1.11 5.26 8.38 8.17 5.13 3.29 3.70 LC-MRM 3-methyl-L-histidine 1.53 1.62 1.33 1.13 E-03 E-02 E-01 E-01 E-02 E-02 E-01 E-01 1.99 1.54 3.62 5.44 1.52 5.36 3.04 3.20 LC-MRM Methylthiobutyric acid 1.54 1.82 1.36 1.08 E-02 E-02 E-01 E-01 E-01 E-02 E-01 E-01 1.52 3.74 8.24 4.02 5.98 3.88 3.65 1.22 LC-MRM Tricine 1.75 1.85 1.11 1.45 E-03 E-03 E-01 E-02 E-02 E-02 E-01 E-01 4.94 7.31 3.08 2.83 1.93 2.68 2.92 2.26 LC-MRM Cystathionine 1.79 1.02 1.41 1.30 E-02 E-01 E-01 E-01 E-01 E-01 E-01 E-01 2.09 1.09 1.30 5.56 1.52 5.13 2.66 1.40 LC-MRM Uracil 1.58 1.43 1.50 1.60 E-02 E-02 E-01 E-02 E-01 E-02 E-01 E-01

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Table 3-1. Continued Fold change p-value q-value Detection Metabolite name 5 10 30 60 5 10 30 60 5 10 30 60 Platform min min min min min min min min min min min min 4.11 1.37 4.07 2.42 1.81 1.04 3.08 2.12 LC-MRM Niacinamide 1.47 1.31 0.88 0.80 E-02 E-01 E-01 E-01 E-01 E-01 E-01 E-01 2-guanidinopropionic 1.72 5.95 2.20 3.06 1.44 6.67 2.80 1.19 LC-MRM 1.47 1.33 1.55 1.88 acid E-02 E-02 E-01 E-02 E-01 E-02 E-01 E-01 7.76 7.93 1.40 5.80 5.98 2.57 2.66 3.30 LC-MRM 3-ureidopropionic acid 1.92 2.03 1.66 1.18 E-04 E-04 E-01 E-01 E-02 E-02 E-01 E-01 2.32 1.25 3.02 8.46 1.52 9.80 5.04 1.46 LC-MRM L-malic acid 1.59 1.46 1.94 1.79 E-02 E-01 E-03 E-02 E-01 E-02 E-02 E-01 1.49 2.13 1.48 1.05 5.98 5.52 9.40 1.52 LC-MRM Homocysteine 2.18 1.94 2.35 1.75 E-03 E-02 E-04 E-01 E-02 E-02 E-03 E-01 2,3-pyridinedicarboxylic 3.40 3.47 4.61 2.72 6.10 1.71 3.26 2.20 LC-MRM 1.63 1.19 0.93 0.98 acid E-03 E-01 E-01 E-01 E-02 E-01 E-01 E-01 Cyclic adenosine 2.09 7.48 3.95 2.08 1.52 4.84 2.07 2.00 LC-MRM 2.52 1.74 1.98 1.40 diphosphate ribose E-02 E-03 E-02 E-01 E-01 E-02 E-01 E-01 4.11 4.59 4.68 1.68 1.81 2.03 3.26 1.82 LC-MRM Zeatin 1.37 1.26 1.28 1.35 E-02 E-01 E-01 E-01 E-01 E-01 E-01 E-01 2.26 5.85 4.40 3.95 1.52 6.67 3.20 2.65 LC-MRM 2-deoxyadenosine 1.44 1.33 1.38 1.28 E-02 E-02 E-01 E-01 E-01 E-02 E-01 E-01 2.16 2.60 6.01 9.48 1.52 5.63 3.41 3.91 LC-MRM Inosine 1.24 1.36 1.25 1.02 E-02 E-02 E-01 E-01 E-01 E-02 E-01 E-01 Cyclic guanosine 3.79 9.64 5.23 2.15 1.81 9.06 3.29 2.03 LC-MRM 1.59 1.29 1.14 1.78 monophosphate E-02 E-02 E-01 E-01 E-01 E-02 E-01 E-01 4.22 1.02 2.88 7.85 1.81 9.16 2.92 3.59 LC-MRM Phaseic acid 1.50 1.45 1.43 1.14 E-02 E-01 E-01 E-01 E-01 E-02 E-01 E-01 1.78 1.86 4.80 8.21 5.98 1.21 3.29 3.66 LC-MRM Syringic acid 2.37 1.38 0.72 1.20 E-03 E-01 E-01 E-01 E-02 E-01 E-01 E-01 3.15 2.15 2.09 9.01 6.10 2.87 2.74 3.81 LC-MRM Indole butyric acid 2.11 2.86 1.76 1.07 E-03 E-03 E-01 E-01 E-02 E-02 E-01 E-01

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Table 3-1. Continued Fold change p-value q-value Detection Metabolite name 5 10 30 60 5 10 30 60 5 10 30 60 Platform min min min min min min min min min min min min 5.36 1.13 2.32 2.65 8.17 2.57 2.83 2.19 LC-MRM Liquiritigenin 1.64 4.75 0.73 0.81 E-03 E-03 E-01 E-01 E-02 E-02 E-01 E-01 2.08 1.88 1.06 7.09 1.52 1.21 2.66 3.53 LC-MRM Alpha-lactose 2.21 0.41 0.35 0.93 E-02 E-01 E-01 E-01 E-01 E-01 E-01 E-01 2.44 1.74 1.71 8.71 1.56 5.41 2.66 3.78 LC-MRM Ononin 1.85 2.56 0.53 0.99 E-02 E-02 E-01 E-01 E-01 E-02 E-01 E-01 13(S)- 4.10 2.49 5.83 7.91 1.81 1.43 3.39 3.59 LC-MRM hydroperoxylinolenic 1.76 1.58 1.27 0.98 E-02 E-01 E-01 E-01 E-01 E-01 E-01 E-01 acid 6.81 3.96 2.77 1.36 8.85 3.88 2.92 1.73 LC-MRM Buthionine-sulfoximine 1.56 1.66 1.46 1.37 E-03 E-03 E-01 E-01 E-02 E-02 E-01 E-01 2.69 9.87 1.91 2.68 6.10 3.19 2.67 1.17 LC-MRM Eupatorin 2.34 1.05 0.73 0.64 E-03 E-01 E-01 E-02 E-02 E-01 E-01 E-01 4.78 4.29 7.57 9.72 1.93 1.95 3.53 3.98 LC-MRM S-sulfocysteine 1.68 0.40 0.91 1.07 E-02 E-01 E-01 E-01 E-01 E-01 E-01 E-01 1.56 8.28 8.56 1.85 1.44 2.86 3.69 1.87 LC-MRM Citramalic acid 1.39 1.07 1.12 0.79 E-02 E-01 E-01 E-01 E-01 E-01 E-01 E-01 2.47 7.54 1.80 4.43 1.56 2.72 2.66 1.26 LC-MRM 2-isopropylmalic acid 1.52 1.14 1.57 0.77 E-02 E-01 E-01 E-02 E-01 E-01 E-01 E-01 2.28 6.30 4.51 6.31 1.52 2.45 3.26 3.34 LC-MRM 2-deoxyinosine 1.69 1.02 1.16 0.95 E-02 E-01 E-01 E-01 E-01 E-01 E-01 E-01 6.91 5.12 3.46 1.18 8.85 2.18 3.04 1.62 LC-MRM Catechol 3.50 0.87 1.27 0.36 E-03 E-01 E-01 E-01 E-02 E-01 E-01 E-01 3,4- 1.66 6.51 1.97 4.26 1.44 2.49 2.68 2.76 LC-MRM dihydroxyphenylacetic 1.92 0.84 1.45 1.23 E-02 E-01 E-01 E-01 E-01 E-01 E-01 E-01 acid 1- LC/MS 3.87 1.83 3.10 3.08 1.81 1.20 2.92 2.36 palmitoylglycerophosph 0.65 0.71 0.64 1.25 Neg E-02 E-01 E-01 E-01 E-01 E-01 E-01 E-01 ocholine (16:0)

139

Table 3-1. Continued Fold change p-value q-value Detection Metabolite name 5 10 30 60 5 10 30 60 5 10 30 60 Platform min min min min min min min min min min min min 1- LC/MS 1.66 1.23 2.67 2.02 1.44 9.80 2.92 1.14 palmitoylglycerophosph 0.61 0.78 0.65 1.38 Neg E-02 E-01 E-01 E-02 E-01 E-02 E-01 E-01 oethanolamine LC/MS 7.14 9.44 1.68 7.93 8.85 3.08 3.96 3.59 Cis-urocanate 0.74 0.97 0.36 0.97 Pos E-03 E-01 E-03 E-01 E-02 E-01 E-02 E-01 3.36 4.37 8.40 6.21 6.10 1.96 3.67 3.33 LC-MRM Naringenin 0.46 0.83 1.02 1.13 E-03 E-01 E-01 E-01 E-02 E-01 E-01 E-01 3.30 3.18 1.05 5.09 1.78 1.64 2.66 3.06 LC-MRM Luteolin 0.51 1.43 1.55 1.51 E-02 E-01 E-01 E-01 E-01 E-01 E-01 E-01 1- LC/MS 8.85 2.37 5.98 3.36 6.82 5.52 3.41 2.47 stearoylglycerophospho 0.99 1.38 0.89 1.12 Neg E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 ethanolamine 6.50 2.25 3.59 1.49 5.90 5.52 2.07 1.74 GC/MS Alpha-tocopherol 1.13 1.52 0.60 0.80 E-01 E-02 E-02 E-01 E-01 E-02 E-01 E-01 LC/MS 5.55 4.14 4.86 2.78 5.58 6.29 3.29 1.18 O-sulfo-L-tyrosine 0.65 2.31 1.15 0.49 Neg E-01 E-02 E-01 E-02 E-01 E-02 E-01 E-01 9.61 1.52 4.76 8.26 6.98 2.57 3.29 3.67 LC-MRM Eriodictyol 0.86 1.54 1.37 0.99 E-01 E-03 E-01 E-01 E-01 E-02 E-01 E-01 8.86 2.02 3.87 3.76 2.49 5.52 3.08 2.56 LC-MRM Fructose-6-phosphate 1.62 1.73 0.84 1.16 E-02 E-02 E-01 E-01 E-01 E-02 E-01 E-01 7.43 8.05 2.29 5.46 6.27 4.84 1.67 1.40 LC-MRM Anthranilic acid 1.06 1.48 1.79 1.58 E-01 E-03 E-02 E-02 E-01 E-02 E-01 E-01 9.63 1.38 1.89 2.65 6.98 2.57 2.67 1.17 LC-MRM Melibiose 0.81 1.70 1.49 3.52 E-01 E-03 E-01 E-02 E-01 E-02 E-01 E-01 5.92 4.34 4.97 7.83 5.73 6.29 3.29 3.59 LC-MRM 2-phosphoglyceric acid 1.04 1.35 1.27 0.97 E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 5.07 1.73 8.82 6.25 1.93 5.41 3.75 3.33 LC-MRM Thymine 1.52 1.44 1.07 1.20 E-02 E-02 E-01 E-01 E-01 E-02 E-01 E-01

140

Table 3-1. Continued Fold change p-value q-value Detection Metabolite name 5 10 30 60 5 10 30 60 5 10 30 60 Platform min min min min min min min min min min min min 3-hydroxyanthranilic 8.70 2.26 7.59 3.38 2.49 2.87 3.53 2.47 LC-MRM 1.36 1.78 1.15 1.35 acid E-02 E-03 E-01 E-01 E-01 E-02 E-01 E-01 N-acetyl-D- 9.73 4.45 2.60 6.18 7.00 6.30 2.92 3.33 LC-MRM 0.94 2.27 1.48 1.72 mannosamine E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 2-deoxyguanosine-5- 3.01 2.29 7.89 1.71 4.15 5.52 3.60 1.82 LC-MRM 1.17 1.50 1.05 3.17 monophosphate E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 Adenosine-3- 2.46 2.34 3.31 1.71 3.93 5.52 3.03 1.82 LC-MRM 1.20 1.58 1.80 3.09 monophosphate E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 3,4- 2.65 3.15 1.67 4.72 4.05 5.79 2.66 2.95 LC-MRM hydroxyphenylpropionic 1.47 1.79 1.46 1.02 E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 acid 6.12 4.62 8.01 1.67 2.14 6.40 3.62 1.82 LC-MRM 3-indole-acetic acid 1.26 1.48 1.18 1.29 E-02 E-02 E-01 E-01 E-01 E-02 E-01 E-01 3.22 4.59 3.77 7.78 4.28 6.40 3.08 3.59 LC-MRM Methyl indole acetate 1.51 3.12 1.16 1.00 E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 9.64 1.43 5.28 1.87 2.56 5.36 3.29 1.87 LC-MRM Melatonin 1.92 3.32 0.75 1.49 E-02 E-02 E-01 E-01 E-01 E-02 E-01 E-01 8.06 1.87 4.03 6.37 6.57 5.52 3.08 3.35 LC-MRM Gibberellin A3 1.05 2.72 1.47 0.91 E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 2.65 1.55 1.80 6.28 4.05 5.36 2.66 3.33 LC-MRM Epibrassinolide 2.96 3.17 1.76 1.21 E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 9.41 1.52 1.06 1.48 6.95 2.57 1.11 1.35 LC-MRM Traumatic acid 0.91 8.25 9.90 7.01 E-01 E-03 E-05 E-05 E-01 E-02 E-03 E-03 7.25 7.95 5.08 6.55 6.22 4.84 6.44 1.57 LC-MRM Dihydrophaseic acid 1.02 2.54 3.88 2.47 E-01 E-03 E-03 E-04 E-01 E-02 E-02 E-02 1.35 3.43 5.88 5.56 2.95 5.93 3.39 3.24 LC-MRM Capsaicin 1.40 3.35 1.32 1.21 E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 9.72 3.81 3.61 5.30 7.00 6.17 5.04 2.54 LC-MRM Sucrose 0.91 4.68 5.59 4.40 E-01 E-02 E-03 E-05 E-01 E-02 E-02 E-03

141

Table 3-1. Continued Fold change p-value q-value Detection Metabolite name 5 10 30 60 5 10 30 60 5 10 30 60 Platform min min min min min min min min min min min min 3.05 1.37 2.69 1.29 4.17 5.36 2.92 1.72 LC-MRM Glycolic acid 1.12 1.36 1.40 0.78 E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 4.95 3.78 5.34 2.63 5.20 6.17 2.47 2.19 LC-MRM Pimelic acid 1.04 1.33 2.01 0.89 E-01 E-02 E-02 E-01 E-01 E-02 E-01 E-01 LC/MS 10-heptadecenoate 4.21 1.98 9.39 4.06 1.81 5.52 3.86 2.69 1.09 0.77 1.03 1.06 Neg (17:1n7) E-02 E-02 E-01 E-01 E-01 E-02 E-01 E-01 LC/MS 1-oleoylglycerol (1- 9.97 4.12 1.49 9.31 7.07 6.29 2.66 3.87 1.01 0.74 0.81 1.05 Neg monoolein) E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 LC/MS 1-palmitoylglycerol (1- 7.61 2.57 1.29 3.91 6.35 5.63 2.66 2.64 1.02 0.76 0.79 0.93 Neg monopalmitin) E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 LC/MS 5.57 2.99 4.81 3.88 5.58 5.75 3.29 1.22 2'-deoxyguanosine 0.94 0.80 0.89 0.80 Neg E-01 E-02 E-01 E-02 E-01 E-02 E-01 E-01 LC/MS 2.99 6.94 1.28 7.86 4.14 4.84 2.66 3.59 2-hydroxypalmitate 0.87 0.69 0.69 0.98 Neg E-01 E-03 E-01 E-01 E-01 E-02 E-01 E-01 LC/MS 2-oleoylglycerol (2- 9.63 1.99 8.81 2.36 6.98 5.52 2.66 2.09 0.95 0.50 0.42 2.31 Neg monoolein) E-01 E-02 E-02 E-01 E-01 E-02 E-01 E-01 LC/MS 4.41 5.45 2.73 5.65 1.87 4.37 1.86 1.55 4-hydroxybenzoate 0.84 0.77 0.87 0.77 Neg E-02 E-03 E-02 E-04 E-01 E-02 E-01 E-02 LC/MS 8.16 5.80 4.07 2.31 6.58 4.42 3.08 2.09 Adenosine 1.02 0.72 0.91 0.92 Pos E-01 E-03 E-01 E-01 E-01 E-02 E-01 E-01 LC/MS 6.75 1.98 1.12 4.14 6.04 5.52 2.66 2.72 Arachidonate (20:4n6) 0.95 0.72 0.81 0.93 Neg E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 LC/MS 1.12 7.57 6.74 4.27 2.67 4.84 3.46 1.26 Asparagine 0.62 0.54 0.96 0.62 Polar E-01 E-03 E-01 E-02 E-01 E-02 E-01 E-01 LC/MS 1.12 3.41 4.69 2.10 2.67 5.93 3.26 2.01 Aspartate 0.54 0.78 0.78 1.23 Pos E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 Cytidine-3'- LC/MS 1.87 1.32 9.51 2.68 3.37 2.57 3.90 1.17 monophosphate (3'- 1.10 0.79 1.06 0.81 Pos E-01 E-03 E-01 E-02 E-01 E-02 E-01 E-01 CMP)

142

Table 3-1. Continued Fold change p-value q-value Detection Metabolite name 5 10 30 60 5 10 30 60 5 10 30 60 Platform min min min min min min min min min min min min LC/MS Cytosine-2',3'-cyclic 4.34 1.31 1.63 1.72 4.99 2.57 2.66 1.07 0.92 0.73 0.88 0.86 Pos monophosphate E-01 E-03 E-01 E-02 E-01 E-02 E-01 E-01 LC/MS Dihomo-linoleate 1.55 1.40 9.62 4.99 3.16 5.36 3.91 3.01 1.11 0.75 1.07 0.95 Neg (20:2n6) E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 LC/MS Dihomo-linolenate 6.38 2.83 9.37 6.59 5.89 5.74 3.86 3.41 1.04 0.71 1.05 0.95 Neg (20:3n3 or n6) E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 LC/MS 3.99 3.20 9.14 6.00 4.79 5.79 3.82 3.32 Erucate (22:1n9) 1.09 0.70 1.17 0.96 Neg E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 4.22 1.87 6.09 1.33 4.92 5.52 3.42 2.54 GC/MS Erythritol 1.12 0.70 0.94 0.44 E-01 E-02 E-01 E-03 E-01 E-02 E-01 E-02 2.44 3.05 5.24 4.65 3.92 5.75 3.29 2.92 GC/MS Fucose 0.85 0.79 0.90 0.90 E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 LC/MS 8.57 2.75 8.30 8.32 6.76 5.66 3.67 1.46 Gluconate 1.02 0.54 0.90 0.63 Polar E-01 E-02 E-01 E-02 E-01 E-02 E-01 E-01 LC/MS 2.04 3.80 6.09 7.87 3.49 6.17 2.57 1.46 Glycylisoleucine 0.87 0.78 0.72 0.78 Pos E-01 E-02 E-02 E-02 E-01 E-02 E-01 E-01 LC/MS 6.29 1.62 1.67 1.05 5.89 5.36 2.66 1.52 Glycylvaline 0.94 0.80 0.85 0.85 Pos E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 LC/MS 3.45 1.58 2.76 6.72 4.41 5.36 2.92 1.42 Guanosine 0.88 0.77 0.88 0.84 Pos E-01 E-02 E-01 E-02 E-01 E-02 E-01 E-01 LC/MS Guanosine-2',3'-cyclic 5.69 2.63 3.61 1.86 5.64 5.63 3.04 1.08 0.94 0.76 0.99 0.83 Pos monophosphate E-01 E-02 E-01 E-02 E-01 E-02 E-01 E-01 LC/MS 5.76 2.21 6.36 4.01 5.69 5.52 3.46 2.66 Linoleate (18:2n6) 1.04 0.78 1.10 0.93 Neg E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 LC/MS 6.00 4.09 2.04 1.11 2.11 6.29 2.72 1.58 Myristoleate (14:1n5) 1.19 0.77 1.13 1.16 Neg E-02 E-02 E-01 E-01 E-01 E-02 E-01 E-01 LC/MS 4.01 1.02 5.45 2.23 4.80 5.03 3.29 2.07 N6-methyladenosine 0.89 0.44 0.60 0.77 Pos E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01

143

Table 3-1. Continued Fold change p-value q-value Detection Metabolite name 5 10 30 60 5 10 30 60 5 10 30 60 Platform min min min min min min min min min min min min LC/MS 4.33 4.07 2.42 5.94 4.99 6.29 2.88 6.32 N-acetylalanine 1.12 0.64 0.84 0.74 Polar E-01 E-02 E-01 E-03 E-01 E-02 E-01 E-02 LC/MS 2.74 4.79 8.46 5.11 4.05 6.48 2.64 1.35 Nicotinate 1.11 0.72 0.70 0.65 Pos E-01 E-02 E-02 E-02 E-01 E-02 E-01 E-01 LC/MS 8.18 1.30 5.39 3.99 6.58 5.36 3.29 2.65 Oleic ethanolamide 0.97 0.49 0.90 0.91 Neg E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 LC/MS 1.22 4.30 8.83 3.05 1.24 6.29 3.75 2.36 Palmitoleate (16:1n7) 1.14 0.80 1.06 1.05 Neg E-02 E-02 E-01 E-01 E-01 E-02 E-01 E-01 LC/MS 4.98 3.42 3.85 3.72 5.20 5.93 3.08 1.22 Phosphate 1.06 0.78 0.90 0.79 Neg E-01 E-02 E-01 E-02 E-01 E-02 E-01 E-01 LC/MS 2.30 8.58 6.85 6.40 3.80 4.84 2.57 1.42 Pseudouridine 0.78 0.70 0.74 0.74 Pos E-01 E-03 E-02 E-02 E-01 E-02 E-01 E-01 LC/MS 7.27 1.49 8.42 5.69 6.22 2.57 3.67 3.30 Spermidine 0.97 0.68 1.09 0.96 Pos E-01 E-03 E-01 E-01 E-01 E-02 E-01 E-01 LC/MS 2.67 3.23 3.10 6.01 4.05 5.79 2.92 3.32 Tryptophylglycine 0.66 0.71 0.71 1.09 Pos E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 5-deoxy-5-methylthio- 4.86 4.45 1.82 2.41 5.20 6.30 2.66 1.16 LC-MRM 1.14 0.34 0.77 0.41 adenosine E-01 E-02 E-01 E-02 E-01 E-02 E-01 E-01 2-hydroxyphenylacetic 2.80 4.17 1.75 7.74 4.05 6.29 2.66 3.59 LC-MRM 1.49 0.73 1.39 0.90 acid E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 8.40 1.38 8.14 1.71 6.70 5.36 3.64 1.82 LC-MRM Quercetin 1.01 0.66 1.16 0.80 E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 4.53 2.03 8.94 2.09 5.11 5.52 3.76 2.00 LC-MRM Hesperetin 1.09 0.59 1.03 0.84 E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01 9.52 1.73 6.09 3.39 2.56 5.41 3.42 2.47 LC-MRM Curcumin 0.50 0.40 1.02 0.89 E-02 E-02 E-01 E-01 E-01 E-02 E-01 E-01 4.63 4.03 5.28 2.64 5.11 6.29 3.29 2.19 LC-MRM Neohesperidin 0.93 0.64 1.21 0.63 E-01 E-02 E-01 E-01 E-01 E-02 E-01 E-01

144

Table 3-1. Continued Fold change p-value q-value Detection Metabolite name 5 10 30 60 5 10 30 60 5 10 30 60 Platform min min min min min min min min min min min min 5.41 7.01 3.74 1.39 5.47 7.26 2.07 1.74 GC/MS Campesterol 0.93 0.87 1.29 0.87 E-01 E-02 E-02 E-01 E-01 E-02 E-01 E-01 LC/MS 4.55 3.48 3.44 2.67 5.11 1.72 2.07 2.19 N-formylphenylalanine 0.75 0.85 2.03 0.82 Neg E-01 E-01 E-02 E-01 E-01 E-01 E-01 E-01 2.68 5.65 2.44 9.50 4.05 2.31 1.72 1.49 LC-MRM Metheonine 1.35 1.14 1.54 1.99 E-01 E-01 E-02 E-02 E-01 E-01 E-01 E-01 1.20 1.17 3.48 2.61 2.78 9.66 2.07 2.19 LC-MRM D-ribose-5-phosphate 1.32 1.41 1.90 0.78 E-01 E-01 E-02 E-01 E-01 E-02 E-01 E-01 LC/MS 5.69 7.14 1.65 8.70 5.64 2.65 3.96 3.78 5-oxoproline 0.93 0.98 0.59 0.99 Neg E-01 E-01 E-03 E-01 E-01 E-01 E-02 E-01 LC/MS 2.92 1.83 2.54 4.14 4.07 1.20 4.83 5.27 Lactate 0.92 0.74 0.51 0.78 Polar E-01 E-01 E-03 E-03 E-01 E-01 E-02 E-02 LC/MS Malonate 7.14 2.13 9.53 6.69 6.22 1.32 3.02 1.42 0.99 0.96 0.76 0.87 Polar (propanedioate) E-01 E-01 E-04 E-02 E-01 E-01 E-02 E-01 LC/MS 6.28 4.85 1.65 5.20 5.89 6.48 1.48 1.35 Pyridoxine (Vitamin B6) 0.97 0.85 0.77 0.78 Pos E-01 E-02 E-02 E-02 E-01 E-02 E-01 E-01 LC/MS 8.12 4.35 1.09 2.72 6.57 1.96 1.09 2.20 Pyruvate 0.91 0.69 0.60 1.32 Neg E-01 E-01 E-02 E-01 E-01 E-01 E-01 E-01 LC/MS 1.90 8.13 6.68 4.50 3.38 2.84 7.47 2.86 Saccharopine 1.25 0.91 0.43 1.21 Neg E-01 E-01 E-03 E-01 E-01 E-01 E-02 E-01 LC/MS 2.71 4.41 7.60 1.88 4.05 1.96 8.03 1.87 Sulfate* 1.08 1.00 0.74 0.93 Neg E-01 E-01 E-03 E-01 E-01 E-01 E-02 E-01 LC/MS 7.97 2.46 6.88 2.12 6.55 1.42 3.47 1.35 Choline phosphate 0.74 1.37 0.90 3.62 Pos E-01 E-01 E-01 E-05 E-01 E-01 E-01 E-03 1.64 5.22 5.87 2.48 3.21 2.20 3.39 1.16 LC-MRM 5,6-dihydrouracil 1.24 1.19 0.84 1.70 E-01 E-01 E-01 E-02 E-01 E-01 E-01 E-01 6.55 2.43 8.05 9.16 2.17 1.42 2.57 7.02 LC-MRM Adenine 1.97 1.38 1.52 2.10 E-02 E-01 E-02 E-03 E-01 E-01 E-01 E-02

145

Table 3-1. Continued Fold change p-value q-value Detection Metabolite name 5 10 30 60 5 10 30 60 5 10 30 60 Platform min min min min min min min min min min min min 7.59 1.63 6.18 3.14 2.42 1.11 2.57 1.19 LC-MRM Cytidine 1.82 1.36 1.58 1.71 E-02 E-01 E-02 E-02 E-01 E-01 E-01 E-01 1.69 9.59 7.04 4.00 3.21 3.12 3.47 1.22 LC-MRM Zeatin riboside 1.29 1.00 1.21 1.53 E-01 E-01 E-01 E-02 E-01 E-01 E-01 E-01 8.68 1.62 2.88 3.26 6.80 1.11 2.92 1.19 LC-MRM Ribulose-5-phosphate 0.83 2.69 7.61 2.87 E-01 E-01 E-01 E-02 E-01 E-01 E-01 E-01 2.55 8.32 4.27 3.30 3.99 2.86 3.15 1.19 LC-MRM 3-methyl xanthine 1.07 0.93 0.84 1.34 E-01 E-01 E-01 E-02 E-01 E-01 E-01 E-01 1.00 LC/MS 2,4,6- 2.59 7.77 1.59 4.03 7.89 4.03 1.07 0.87 0.74 1.06 0.70 E+0 Neg trihydroxybenzoate E-01 E-02 E-02 E-01 E-02 E-01 E-01 0 LC/MS 6.42 3.26 8.66 4.45 5.90 1.66 3.72 1.26 2-hydroxyoctanoate 1.19 0.73 1.04 0.58 Neg E-01 E-01 E-01 E-02 E-01 E-01 E-01 E-01 LC/MS 9.38 1.03 4.13 4.38 6.95 9.20 3.08 1.40 7-methylguanosine 0.89 0.73 0.61 0.30 Pos E-01 E-01 E-01 E-04 E-01 E-02 E-01 E-02 LC/MS 6.03 1.78 6.10 4.08 5.75 1.18 2.57 5.27 Aconitate [cis or trans] 1.06 0.89 0.80 0.77 Neg E-01 E-01 E-02 E-03 E-01 E-01 E-01 E-02 LC/MS 8.64 6.31 8.21 1.53 2.49 6.76 3.65 5.85 Adipate 1.28 0.62 1.10 0.42 Polar E-02 E-02 E-01 E-04 E-01 E-02 E-01 E-03 LC/MS 3.99 1.58 3.55 2.93 4.79 1.11 3.04 1.19 Guanine 1.11 0.86 0.79 0.69 Pos E-01 E-01 E-01 E-02 E-01 E-01 E-01 E-01 LC/MS 1.99 3.29 5.12 6.78 3.44 1.67 3.29 6.50 N1-methyladenosine 1.20 0.77 0.75 0.32 Pos E-01 E-01 E-01 E-03 E-01 E-01 E-01 E-02 LC/MS Suberate 4.83 1.41 9.30 3.16 5.19 1.05 2.66 1.19 1.08 0.89 0.84 0.79 Neg (octanedioate) E-01 E-01 E-02 E-02 E-01 E-01 E-01 E-01 LC/MS 3.84 4.19 1.26 2.85 4.70 6.29 2.66 1.19 Thymidine 0.91 0.80 0.78 0.79 Pos E-01 E-02 E-01 E-02 E-01 E-02 E-01 E-01 LC/MS 2.45 1.48 4.77 3.93 3.92 1.07 3.29 1.22 Uridine 1.15 0.84 0.76 0.65 Pos E-01 E-01 E-01 E-02 E-01 E-01 E-01 E-01

146

Table 3-1. Continued Fold change p-value q-value Detection Metabolite name 5 10 30 60 5 10 30 60 5 10 30 60 Platform min min min min min min min min min min min min LC/MS 1.25 2.86 7.53 2.98 2.83 1.57 3.53 1.19 Valylglutamine 1.23 0.84 0.87 0.59 Pos E-01 E-01 E-01 E-02 E-01 E-01 E-01 E-01 5.99 1.50 5.00 1.67 5.75 1.07 3.29 1.07 LC-MRM 1-methylguanidine 1.03 1.23 1.09 0.78 E-01 E-01 E-01 E-02 E-01 E-01 E-01 E-01 2,3-dihydroxybenzoic 4.78 6.16 1.03 4.28 5.18 2.42 2.66 1.26 LC-MRM 1.17 1.17 0.44 0.63 acid E-01 E-01 E-01 E-02 E-01 E-01 E-01 E-01 1.02 2.51 6.55 1.60 2.65 1.43 3.46 1.07 LC-MRM Shikimic acid 1.25 1.23 1.20 0.62 E-01 E-01 E-01 E-02 E-01 E-01 E-01 E-01 1.39 1.43 6.41 7.19 2.99 1.05 3.46 6.56 LC-MRM Maltose 1.41 1.53 1.12 0.54 E-01 E-01 E-01 E-03 E-01 E-01 E-01 E-02 9.83 7.26 6.80 2.39 7.06 2.68 3.47 1.16 LC-MRM 1-kestose 0.80 0.96 1.05 0.39 E-01 E-01 E-01 E-02 E-01 E-01 E-01 E-01 9.63 7.63 7.75 4.39 6.98 2.73 3.57 1.26 LC-MRM Raffinose 0.77 0.88 1.12 0.43 E-01 E-01 E-01 E-02 E-01 E-01 E-01 E-01 3.83 4.36 4.30 2.09 4.70 1.96 3.15 1.15 LC-MRM Arbutin 0.78 0.97 0.95 0.50 E-01 E-01 E-01 E-02 E-01 E-01 E-01 E-01 Deoxyinosine 1.60 9.42 5.15 1.80 3.20 3.08 3.29 1.08 LC-MRM 0.74 1.04 1.01 0.53 triphosphate E-01 E-01 E-01 E-02 E-01 E-01 E-01 E-01

147

Table 3-2. Significantly changed proteins under low CO2 Fold change p-value Genescope Annotation 10 30 60 10 30 60 ID 5 min 5 min min min min min min min GSBRNA2T0 3.06 2.49 3.23 3.81 V-type proton atpase subunit G1 1.28 1.28 1.33 1.28 0092270001 E-02 E-01 E-01 E-01 GSBRNA2T0 3.21 5.43 7.41 6.23 GDSL esterase lipase At1g29660-like 1.39 1.31 1.04 0.88 0158037001 E-02 E-01 E-01 E-01 GSBRNA2T0 4.22 1.59 1.58 9.87 GDSL esterase lipase At1g29670-like 1.28 1.52 1.33 1.07 0150758001 E-02 E-01 E-01 E-01 GSBRNA2T0 PREDICTED: uncharacterized protein 4.87 3.11 8.36 5.63 1.32 1.12 0.99 0.96 0019083001 LOC106332922 E-02 E-01 E-01 E-01 GSBRNA2T0 Glycerol-3-phosphate dehydrogenase 1.88 3.61 1.10 3.57 1.33 1.25 0.91 0.97 0000403001 mitochondrial-like E-02 E-01 E-01 E-01 GSBRNA2T0 2.63 6.96 3.87 8.22 Beta-glucosidase 44 1.34 0.90 0.80 1.57 0005505001 E-02 E-03 E-01 E-02 GSBRNA2T0 Ethanolamine-phosphate 1.46 1.53 7.61 9.75 1.38 1.17 1.13 1.14 0140053001 cytidylyltransferase-like E-02 E-03 E-01 E-01 GSBRNA2T0 1.64 1.95 7.90 7.76 5-oxoprolinase-like isoform X2 1.43 1.21 0.98 1.20 0036796001 E-03 E-01 E-01 E-01 GSBRNA2T0 3.01 1.70 4.82 6.24 Subtilisin-like protease 1.53 1.18 0.92 1.02 0071521001 E-02 E-01 E-01 E-01 GSBRNA2T0 4.21 2.16 9.86 7.53 Proteasome subunit alpha type-1-A-like 1.31 1.34 1.00 1.10 0100720001 E-02 E-01 E-01 E-01 GSBRNA2T0 PREDICTED: uncharacterized protein 1.59 4.27 6.04 6.37 1.46 1.36 1.20 1.19 0130920001 At2g17340 E-02 E-01 E-01 E-01 GSBRNA2T0 Photosystem I P700 chlorophyll a apo A1 6.79 9.68 3.13 2.11 1.22 1.00 0.87 0.95 0066038001 (chloroplast) E-03 E-01 E-01 E-01 GSBRNA2T0 Eukaryotic translation initiation factor 2 2.40 4.43 7.38 2.08 1.36 1.04 1.04 0.89 0017087001 subunit beta-like E-02 E-01 E-01 E-01 GSBRNA2T0 1.14 4.87 1.07 3.36 Pectin acetylesterase 11 isoform X1 1.22 1.30 0.84 1.56 0035145001 E-02 E-01 E-01 E-01

148

Table 3-2. Continued Fold change p-value Genescope Annotation 10 30 60 10 30 60 ID 5 min 5 min min min min min min min GSBRNA2T0 3.02 4.73 5.26 4.62 Cystine lyase CORI3-like 1.88 1.04 1.05 1.10 0072955001 E-02 E-01 E-01 E-01 GSBRNA2T0 4.61 4.20 1.38 5.90 L-arabinokinase isoform X1 1.63 1.07 1.09 0.91 0056503001 E-02 E-01 E-01 E-01 GSBRNA2T0 1.92 7.21 1.64 3.70 Aconitate hydratase mitochondrial 1.68 0.97 1.29 1.06 0097804001 E-02 E-01 E-01 E-01 GSBRNA2T0 2.90 4.05 7.01 9.45 Aminopeptidase M1 1.37 1.03 0.97 1.00 0121200001 E-02 E-01 E-01 E-01 GSBRNA2T0 PREDICTED: uncharacterized protein 4.60 3.51 9.23 5.19 1.53 0.87 1.02 0.65 0122725001 LOC103862003 E-03 E-01 E-01 E-01 GSBRNA2T0 4.70 2.57 8.22 5.56 50S ribosomal chloroplastic 1.27 0.69 0.98 0.84 0128065001 E-03 E-01 E-01 E-02 GSBRNA2T0 4.72 5.26 1.97 3.96 Phosphomethylpyrimidine chloroplastic 1.46 0.96 0.93 0.84 0082082001 E-03 E-01 E-01 E-01 GSBRNA2T0 3.99 3.53 3.46 1.02 Probable aquaporin PIP2;5 1.36 1.41 0.75 0.73 0098759001 E-02 E-01 E-01 E-01 GSBRNA2T0 ATP-dependent zinc metalloprotease FTSH 4.42 6.69 9.13 7.78 1.32 1.37 1.02 1.03 0102276001 chloroplastic mitochondrial E-02 E-02 E-01 E-01 GSBRNA2T0 4.34 3.15 3.96 4.06 Ras-related RABB1b 1.30 0.77 1.24 0.89 0100097001 E-02 E-01 E-01 E-01 GSBRNA2T0 1.32 6.06 6.81 2.47 Cysteine ase inhibitor 4-like 1.34 1.21 1.12 0.87 0083500001 E-03 E-01 E-01 E-01 GSBRNA2T0 Sulfite reductase [ferredoxin] chloroplastic- 3.12 7.32 7.72 1.83 1.35 1.11 1.00 0.87 0072923001 like E-02 E-01 E-01 E-01 GSBRNA2T0 2.30 3.98 4.04 6.84 Reticulon B5 1.27 1.35 1.10 1.17 0074023001 E-02 E-01 E-01 E-01 GSBRNA2T0 Mitochondrial import inner membrane 2.66 6.34 8.39 5.70 1.42 1.28 1.07 1.24 0082968001 translocase subunit TIM9 E-02 E-01 E-01 E-02

149

Table 3-2. Continued Fold change p-value Genescope Annotation 10 30 60 10 30 60 ID 5 min 5 min min min min min min min GSBRNA2T0 4.24 5.07 8.29 3.48 Dirigent 20 1.36 1.26 0.98 0.90 0125549001 E-03 E-01 E-01 E-01 GSBRNA2T0 4.03 3.19 1.99 3.24 Pathogenesis-related ATOZI1 1.44 1.39 1.19 0.87 0004069001 E-02 E-01 E-01 E-01 GSBRNA2T0 2.30 1.76 4.35 3.61 Glucan endo-1,3-beta-glucosidase-like 1.63 1.40 0.97 1.41 0011248001 E-02 E-01 E-01 E-01 GSBRNA2T0 2.61 5.99 9.97 3.11 Nudix hydrolase 3 1.34 1.44 1.02 1.20 0132018001 E-02 E-01 E-01 E-02 GSBRNA2T0 Photosystem I reaction center subunit 4.37 2.86 2.91 3.17 1.26 0.70 1.43 0.80 0004139001 chloroplastic E-02 E-02 E-01 E-01 GSBRNA2T0 Phosphoserine aminotransferase 4.56 2.13 8.76 2.22 1.85 0.65 0.99 0.71 0073304001 chloroplastic E-02 E-01 E-01 E-01 GSBRNA2T0 2.85 2.94 2.26 7.09 Auxin transporter 3 1.37 1.22 1.29 1.02 0099273001 E-02 E-01 E-01 E-01 GSBRNA2T0 3.62 8.15 3.88 7.88 GDSL esterase lipase At5g03610-like 1.46 1.12 1.12 1.03 0006803001 E-03 E-01 E-01 E-01 GSBRNA2T0 4.19 5.29 2.16 5.69 Endoglucanase 3 1.80 0.81 0.70 0.93 0033145001 E-02 E-01 E-01 E-01 GSBRNA2T0 1.02 5.64 9.70 6.70 Lysosomal Pro-X carboxypeptidase-like 1.41 1.22 1.00 1.23 0083309001 E-02 E-01 E-01 E-01 GSBRNA2T0 2.13 6.02 3.64 9.48 5 -adenylylsulfate reductase chloroplastic 1.26 0.90 1.04 1.00 0157821001 E-03 E-01 E-02 E-01 GSBRNA2T0 2.45 2.49 6.43 9.19 Thioredoxin chloroplastic-like 0.68 1.23 1.30 1.03 0091301001 E-02 E-01 E-01 E-01 GSBRNA2T0 Ribulose bisphosphate carboxylase small 7.12 1.51 2.01 6.24 0.61 0.76 0.88 0.98 0114439001 chloroplastic-like E-03 E-01 E-01 E-01 GSBRNA2T0 6.62 9.05 9.54 4.77 Patellin-1-like 0.72 1.05 1.01 0.89 0116439001 E-03 E-01 E-01 E-01

150

Table 3-2. Continued Fold change p-value Genescope Annotation 10 30 60 10 30 60 ID 5 min 5 min min min min min min min GSBRNA2T0 4.10 8.08 1.44 1.31 ATP synthase subunit chloroplastic-like 0.73 1.08 1.09 0.75 0119832001 E-02 E-01 E-01 E-01 GSBRNA2T0 PREDICTED: uncharacterized protein 4.30 3.63 9.18 8.76 0.75 1.56 1.02 1.03 0039727001 LOC106373019 E-02 E-01 E-01 E-01 GSBRNA2T0 6.75 5.95 4.61 3.70 Glycine-rich RNA-binding RZ1C isoform X1 0.80 1.04 0.85 0.78 0049316001 E-03 E-01 E-01 E-01 GSBRNA2T0 2.21 2.90 1.27 9.99 SUMO-activating enzyme subunit 1A 0.80 1.31 0.74 1.01 0056366001 E-03 E-01 E-01 E-01 GSBRNA2T0 1.88 2.75 8.75 6.70 Formate--tetrahydrofolate ligase 0.72 1.37 0.99 1.08 0021140001 E-02 E-01 E-01 E-01 GSBRNA2T0 1.82 9.38 6.79 1.58 CBS domain-containing chloroplastic-like 0.74 1.01 1.01 0.79 0099963001 E-03 E-01 E-01 E-01 GSBRNA2T0 2.61 4.76 8.75 5.76 PHD finger ALFIN-LIKE 6-like 0.74 0.70 0.99 0.82 0095575001 E-02 E-01 E-01 E-01 GSBRNA2T0 3.58 3.24 2.42 5.19 Peroxiredoxin- mitochondrial 0.56 1.06 0.75 0.74 0038509001 E-02 E-01 E-01 E-01 GSBRNA2T0 4.22 4.46 6.46 2.19 Receptor for activated C kinase 1C 0.68 1.14 1.07 0.96 0101398001 E-02 E-01 E-01 E-01 GSBRNA2T0 1.57 2.87 2.63 8.23 Phospholipase A1-Iidelta 0.65 1.31 1.26 0.98 0084737001 E-03 E-01 E-01 E-01 GSBRNA2T0 2.30 3.66 1.62 8.69 Peptidyl-prolyl cis-trans isomerase CYP18-3 0.43 1.55 0.83 0.98 0061071001 E-02 E-01 E-01 E-01 GSBRNA2T0 PREDICTED: uncharacterized protein 5.79 3.82 3.92 6.92 0.58 1.19 0.84 1.23 0014811001 LOC106382647 E-03 E-01 E-01 E-01 GSBRNA2T0 1.57 3.00 4.76 3.22 Trafficking particle complex subunit 3-like 0.74 0.67 0.76 0.80 0006821001 E-02 E-01 E-02 E-01 GSBRNA2T0 Mitochondrial import receptor subunit 4.32 8.60 6.65 9.80 0.77 0.98 0.96 1.00 0137369001 TOM40-1-like E-03 E-01 E-01 E-01

151

Table 3-2. Continued Fold change p-value Genescope Annotation 10 30 60 10 30 60 ID 5 min 5 min min min min min min min GSBRNA2T0 4.58 3.44 3.07 3.73 Probable calcium-binding CML27 0.35 1.21 0.67 0.87 0006492001 E-02 E-01 E-01 E-01 GSBRNA2T0 7.85 3.62 2.72 4.06 Basic endochitinase CHB4-like 1.16 2.05 1.24 0.78 0036077001 E-01 E-03 E-01 E-01 GSBRNA2T0 Carotenoid 9,10(9 ,10 )-cleavage 1.67 3.72 7.53 5.76 0.89 1.22 1.03 0.96 0156720001 dioxygenase 1 E-01 E-02 E-01 E-01 GSBRNA2T0 6.28 4.18 1.16 8.28 Expansin A8 1.31 1.82 1.25 1.58 0132842001 E-01 E-02 E-01 E-02 GSBRNA2T0 1.08 8.26 5.04 4.39 Heat shock 90-1-like 0.58 1.28 0.88 0.83 0059518001 E-01 E-03 E-02 E-01 GSBRNA2T0 9.41 3.25 5.37 9.75 NRT1 PTR FAMILY -like 1.02 1.20 0.94 1.01 0082679001 E-01 E-02 E-02 E-01 GSBRNA2T0 1.54 1.67 7.13 3.26 Serine carboxypeptidase-like 27 isoform X1 1.22 1.31 0.95 1.32 0059535001 E-01 E-03 E-01 E-01 GSBRNA2T0 6.51 2.89 1.99 9.92 Stem-specific TSJT1 0.95 1.26 1.14 1.02 0053128001 E-01 E-03 E-01 E-01 GSBRNA2T0 Isovaleryl-coa-dehydrogenase precursor 6.21 4.62 1.57 3.60 1.06 1.27 0.93 0.89 0011530001 mitochondrial E-01 E-02 E-01 E-01 GSBRNA2T0 1.58 4.08 8.75 9.33 Probable cytosolic oligopeptidase A 1.26 1.27 1.09 1.11 0000707001 E-01 E-02 E-01 E-02 GSBRNA2T0 8.68 1.52 6.91 3.46 Basic 7S globulin 2-like 1.04 1.35 1.13 1.30 0114689001 E-01 E-02 E-01 E-01 GSBRNA2T0 7.28 3.87 3.88 4.44 V-type proton atpase subunit a2-like 1.16 1.43 0.91 0.90 0108093001 E-01 E-02 E-01 E-01 GSBRNA2T0 3.93 2.56 9.36 1.65 Transcription factor FAMA-like 0.81 1.28 1.00 0.66 0158357001 E-01 E-02 E-01 E-01 GSBRNA2T0 3.57 1.34 9.69 7.13 Elongation factor chloroplastic 1.04 1.24 1.00 1.09 0086390001 E-01 E-02 E-01 E-01

152

Table 3-2. Continued Fold change p-value Genescope Annotation 10 30 60 10 30 60 ID 5 min 5 min min min min min min min GSBRNA2T0 Lysm domain-containing GPI-anchored 2- 1.81 6.29 3.02 3.53 1.45 1.50 1.16 0.86 0147404001 like E-01 E-03 E-01 E-01 GSBRNA2T0 Pyruvate dehydrogenase E1 component 2.97 2.23 5.57 9.16 0.57 1.69 1.16 0.99 0066583001 subunit alpha- mitochondrial-like E-01 E-02 E-01 E-01 GSBRNA2T0 3.87 2.03 4.00 7.34 Alpha-soluble NSF attachment 2 0.92 1.34 0.92 1.01 0050818001 E-01 E-02 E-01 E-01 GSBRNA2T0 5.52 3.14 2.73 4.52 Ribosomal L2 (chloroplast) 1.14 1.21 0.83 0.80 0100794001 E-01 E-03 E-01 E-02 GSBRNA2T0 Probable voltage-gated potassium channel 6.84 1.38 6.47 2.54 0.90 1.26 1.17 0.78 0089688001 subunit beta E-01 E-02 E-01 E-01 GSBRNA2T0 2.31 1.83 1.05 2.82 EG45-like domain containing 2 isoform X2 1.35 1.72 1.13 0.69 0077487001 E-01 E-02 E-01 E-01 GSBRNA2T0 3.33 3.02 3.50 5.51 TRAF-like family 0.82 1.41 1.27 0.92 0123499001 E-01 E-02 E-01 E-01 GSBRNA2T0 2.36 1.51 1.11 1.93 COP9 signalosome complex subunit 7-like 1.11 1.40 1.13 0.84 0110050001 E-02 E-02 E-01 E-01 GSBRNA2T0 PREDICTED: uncharacterized protein 5.17 4.52 1.96 5.45 1.18 1.24 1.36 1.19 0034768001 LOC106298962 E-01 E-02 E-01 E-01 GSBRNA2T0 3.24 4.00 5.62 5.45 Gibberellin-regulated 14-like 1.29 1.27 0.92 0.92 0157892001 E-01 E-02 E-01 E-01 GSBRNA2T0 3-oxoacyl-[acyl-carrier- ] synthase 6.03 4.82 9.32 3.27 0.77 1.22 1.03 0.88 0068613001 chloroplastic-like E-01 E-02 E-01 E-01 GSBRNA2T0 3.34 1.33 8.19 3.98 Peroxidase 34-like 1.18 1.67 1.05 1.29 0125390001 E-01 E-02 E-01 E-01 GSBRNA2T0 Aldehyde dehydrogenase family 3 member 1.72 6.40 9.98 7.35 0.72 1.28 1.07 0.91 0121471001 F1-like E-01 E-03 E-01 E-01 GSBRNA2T0 Plant intracellular Ras-group-related LRR 7- 5.98 3.85 8.23 7.17 1.24 1.32 0.98 1.09 0134520001 like E-01 E-02 E-01 E-01

153

Table 3-2. Continued Fold change p-value Genescope Annotation 10 30 60 10 30 60 ID 5 min 5 min min min min min min min GSBRNA2T0 3-deoxy-manno-octulosonate mitochondrial- 8.94 1.04 9.63 3.37 1.10 1.69 1.06 0.77 0091475001 like E-01 E-02 E-01 E-01 GSBRNA2T0 9.49 4.24 9.53 9.20 T-complex 1 subunit alpha 1.20 1.28 1.01 0.99 0054373001 E-01 E-02 E-01 E-01 GSBRNA2T0 ASPARTIC PROTEASE IN GUARD CELL 8.82 1.83 4.68 6.77 0.99 1.27 0.85 0.89 0077568001 1-like E-01 E-02 E-01 E-01 GSBRNA2T0 Mediator of RNA polymerase II transcription 4.85 1.94 3.86 5.79 0.84 1.25 0.54 0.77 0062288001 subunit 15a-like isoform X1 E-01 E-02 E-01 E-01 GSBRNA2T0 Receptor-like serine threonine- kinase SD1- 3.43 1.87 7.62 6.62 1.25 1.29 1.11 1.33 0076859001 8 E-01 E-02 E-01 E-01 GSBRNA2T0 4.39 1.27 3.08 9.41 Oxygen-evolving enhancer 3- chloroplastic 0.93 0.52 1.07 1.00 0067337001 E-01 E-02 E-02 E-01 GSBRNA2T0 PREDICTED: uncharacterized protein 7.69 4.27 9.04 9.58 1.08 0.73 0.99 0.57 0139011001 LOC103858124 E-01 E-02 E-01 E-02 GSBRNA2T0 1.61 1.06 8.80 7.40 10 kda chaperonin-like 0.61 0.62 1.03 0.94 0089109001 E-01 E-02 E-01 E-01 GSBRNA2T0 Peptidyl-prolyl cis-trans isomerase FKBP16- 6.56 4.72 4.58 6.29 0.94 1.14 1.25 1.10 0021981001 chloroplastic-like E-01 E-01 E-02 E-01 GSBRNA2T0 1.03 3.94 3.27 7.03 Cysteine-rich repeat secretory 55 1.80 1.20 1.29 1.48 0143017001 E-01 E-01 E-02 E-01 GSBRNA2T0 3.43 2.34 7.39 2.38 Peroxidase 66 1.28 1.50 1.22 0.93 0036927001 E-01 E-01 E-03 E-01 GSBRNA2T0 Probable H ACA ribonucleo complex 2.63 4.14 4.76 6.45 1.81 1.35 1.48 1.16 0050940001 subunit 1 E-01 E-01 E-03 E-01 GSBRNA2T0 9.46 7.64 3.74 5.06 Elongation factor chloroplastic-like 1.00 1.05 1.27 0.92 0092231001 E-01 E-01 E-02 E-01 GSBRNA2T0 3.41 1.72 3.68 6.88 BPI LBP family At1g04970 1.08 1.45 1.47 0.90 0002811001 E-01 E-01 E-03 E-01

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Table 3-2. Continued Fold change p-value Genescope Annotation 10 30 60 10 30 60 ID 5 min 5 min min min min min min min GSBRNA2T0 6.33 2.04 2.98 2.92 Glycine-rich 3 short isoform-like isoform X2 0.89 0.87 1.26 0.68 0154994001 E-01 E-01 E-02 E-01 GSBRNA2T0 Gamma-glutamyltranspeptidase 1 isoform 4.81 1.79 1.85 2.71 1.09 1.35 1.20 1.48 0075149001 X2 E-01 E-01 E-02 E-01 GSBRNA2T0 2.25 1.84 8.80 3.06 Topless-related 2 0.81 1.17 1.22 0.70 0067661001 E-01 E-01 E-03 E-01 GSBRNA2T0 External alternative NAD(P)H-ubiquinone 2.34 2.95 4.67 4.41 0.95 1.28 1.25 1.35 0025043001 oxidoreductase mitochondrial E-01 E-01 E-03 E-01 GSBRNA2T0 Peptidyl-prolyl cis-trans isomerase FKBP15- 5.00 6.34 4.89 5.97 0.83 1.03 0.69 0.80 0085258001 1 E-01 E-01 E-04 E-01 GSBRNA2T0 4.34 3.13 1.21 6.44 Isoflavone reductase homolog P3-like 0.82 1.20 0.76 0.91 0067819001 E-01 E-01 E-02 E-01 GSBRNA2T0 PREDICTED: uncharacterized protein 8.07 3.14 4.14 3.29 0.95 1.28 0.68 0.88 0031379001 LOC106306337 E-01 E-01 E-02 E-01 GSBRNA2T0 3.33 1.40 4.50 3.77 Transmembrane 9 superfamily member 11 0.67 0.90 0.67 0.72 0091606001 E-01 E-01 E-02 E-01 GSBRNA2T0 5.32 8.87 4.06 9.42 Galactose oxidase-like 1.14 1.05 0.70 1.05 0025406001 E-01 E-01 E-02 E-01 GSBRNA2T0 DNA-binding DDB_G0278111-like isoform 2.55 3.14 4.74 6.62 0.42 0.95 0.59 0.84 0035012001 X1 E-01 E-01 E-02 E-01 GSBRNA2T0 7.36 5.01 4.87 3.81 DNA damage-binding 1a 1.20 1.06 0.75 0.89 0086122001 E-01 E-02 E-02 E-01 GSBRNA2T0 2.81 7.45 1.00 6.68 Dicarboxylate transporter chloroplastic 1.23 1.04 0.66 0.90 0104207001 E-01 E-01 E-03 E-01 GSBRNA2T0 2.19 1.79 6.69 3.99 Non-specific lipid-transfer A 1.52 1.28 1.12 1.34 0005366001 E-01 E-01 E-01 E-02 GSBRNA2T0 4.81 2.99 3.79 3.94 Aconitate hydratase mitochondrial 1.09 1.22 0.88 1.20 0078888001 E-01 E-01 E-01 E-02

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Table 3-2. Continued Fold change p-value Genescope Annotation 10 30 60 10 30 60 ID 5 min 5 min min min min min min min GSBRNA2T0 Probable inactive serine threonine- kinase 5.11 6.22 4.43 2.01 1.05 0.94 0.80 1.21 0029549001 fnkC E-01 E-01 E-01 E-03 GSBRNA2T0 5.08 8.21 1.73 1.28 Polygalacturonase inhibitor 2-like 1.10 0.97 0.74 1.40 0136156001 E-01 E-01 E-01 E-02 GSBRNA2T0 2.10 3.55 2.69 3.41 Glutamine--tRNA ligase-like 1.19 1.51 1.14 1.25 0142386001 E-01 E-01 E-01 E-02 GSBRNA2T0 Probable LRR receptor-like serine 7.99 4.06 1.76 1.48 1.11 1.29 1.15 1.41 0152613001 threonine- kinase At1g67720 E-01 E-01 E-01 E-02 GSBRNA2T0 2.39 3.20 5.42 1.19 Selenium-binding 2 0.85 0.83 0.80 1.44 0061570001 E-01 E-01 E-02 E-02 GSBRNA2T0 8.45 1.28 6.72 1.04 Thioredoxin chloroplastic 0.98 0.81 0.94 0.79 0121519001 E-01 E-01 E-01 E-02 GSBRNA2T0 3.44 7.09 5.75 2.80 Choline transporter 2 1.50 1.10 0.89 0.72 0137568001 E-01 E-01 E-01 E-02 GSBRNA2T0 PREDICTED: uncharacterized protein 1.42 9.90 3.48 2.68 0.59 1.22 1.12 0.75 0056265001 LOC103834482 E-01 E-02 E-01 E-03 GSBRNA2T0 2.77 7.80 1.99 4.37 40S ribosomal S21-2-like 0.57 1.15 0.84 0.77 0139400001 E-01 E-01 E-01 E-02 GSBRNA2T0 5.44 3.56 2.02 4.29 S-formylglutathione hydrolase 0.84 1.34 0.81 0.78 0019115001 E-01 E-01 E-01 E-02 GSBRNA2T0 1.95 7.44 5.98 2.01 Clathrin light chain 3-like 1.10 1.03 0.98 0.76 0021703001 E-02 E-01 E-01 E-02 GSBRNA2T0 5.40 4.51 8.38 1.45 AP-1 complex subunit mu-2-like 1.36 0.90 0.97 0.76 0008833001 E-01 E-01 E-01 E-02 GSBRNA2T0 7.05 2.16 3.38 2.24 2-oxoglutarate dehydrogenase E2 subunit 0.91 1.42 1.08 0.68 0009710001 E-01 E-01 E-01 E-02 GSBRNA2T0 2.64 5.43 2.86 2.10 Phosphate dikinase chloroplastic-like 2.10 1.39 0.80 0.78 0021277001 E-01 E-01 E-01 E-02

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Figure 3-1. Stomatal movement and overview of metabolomics changes under low CO2. A) Stomatal aperture under low CO2 treatment. Three independent experiments were done for each time point, and at least 60 stomata were measured for each experiment. B) Representative stomatal images for the chosen timepoints. C) Number of significantly changed metabolites at each timepoint. D) Venn diagram of significantly changed metabolites, red indicates significantly increased metabolites, and blue indicates significantly decreased metabolites. Student’s t-test was done between control and treatment for each time point. Stars indicate significant differences (p < 0.05).

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Figure 3-2. Venn diagram of significantly changed pathways under low CO2. Pathways with p < 0.05 are plotted in the graph. Numbers in the parentheses indicate mapped metabolites/total metabolites in the specific pathway.

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Figure 3-3. Lipid metabolism under low CO2. Short/medium chain lipids include lipids of 5C-14C lipids. Long/very-long chain lipids include lipids with a carbon chain longer than 16C. Only lipids that showed significant changes (p<0.05) were included.

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Figure 3-4. Jasmonic aicd biosynthesis under low CO2. A). Changes of jasmonic acids and biosynthesis intermediates under low CO2. Error bars indicate standard errors. Stars indicate significant differences (p <0.05). B). Low CO2 response of jasmonic acid biosynthesis mutant lox2 and signaling mutant coi1. Three independent experiments were performed, and 70 stomatal were measured for each replicates. Error bars indicate standard errors. A two-way ANOVA was conducted, and different letters indicate significant differences as determined by Tukey’s test (p < 0.05). C). Representative stomata for (B).

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Figure 3-5. Phytohormone changes in guard cells under low CO2. Student’s t-test was conducted between low CO2 treatment (0 ppm) and ambient control (400 ppm). Stars indicate significant differences (p < 0.05).

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Figure 3-6. Proteomics data overview. Proteins with significant changes (p<0.05) and fold change of over 1.2 or less than 0.8 were selected.

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Figure 3-7. Go term enrichment anlaysis for significantly changed proteins under low CO2. A) Biological process go term enrichment analysis. B) Molecular function go term enrichment analysis

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Figure 3-7. Continued

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CHAPTER 4 SUMMARY AND PERSPECTIVES

Global climate change and anthropogenic CO2 emissions have posed immense challenges to plant life. A better understanding of how plants react to this environmental challenge can greatly facilitate breeding and biotechnology efforts toward producing crops that can better adapt to climate change. Stomata serve as the first line for plant response to both biotic and abiotic signals, and have independent delicate signaling pathways capable of responding to these signals, making them a perfect system to study complex signaling networks. Although metabolomics studies of plant single cell- types are still rare, the importance of uncovering molecular processes at cellular or subcellular resolution is obvious (Dai and Chen, 2012; Misra et al., 2015b). Using different platforms, we have shown the capabilities of MS-based approaches in capturing guard cell metabolomic and proteomic changes in response to elevated and low CO2 in a time-resolved manner. This dissertation research has led to identification and quantification of 358 metabolites in elevated CO2 experiment, 411 metabolites and

1397 proteins in low CO2 experiment in B. napus guard cells. Interestingly, this study has enabled new discoveries at the metabolome and proteome levels, and generation of testable hypotheses. Under elevated CO2, most primary and secondary metabolites within flavonoid, organic acid, sugar, fatty acid, phenylpropanoid, and amino acid metabolic pathways showed increases, indicating increased carbon assimilation. Under low CO2 however, lipid metabolism, flavonoid metabolism, tryptophan metabolism and ubiquinone and other terpenoid-quinone biosynthesis showed significant changes at early time points, while most of the carbon assimilation/catabolism pathways and amino acid metabolism pathways showed significant changes at later time points. Though

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photosynthesis have been shown to be not essential for elevated CO2 induced stomatal closure (Azoulay-Shemer et al., 2015), an increased level of carbon assimilation cannot be excluded during high CO2 response. We observed a good correlation between stomatal movement and many well-known osmoregulators in guard cells, including sucrose, mannitol, and many organic acids under both elevated and low CO2 conditions. Our proteomics data confirmed an increased level of glycolysis under low

CO2, indicating increased production small sugar molecules such as sucrose, fructose and glucose, which further confirms their osmoregulatory function in during CO2 induced stomatal responses. Our metabolomics and proteomics data together also indicated that free fatty acids significantly increased at 5 min, but dropped quickly from 10 min onward. This response is consistent with the need for membrane expansion during the stomatal opening process.

As for the cellular redox regulation, flavonols such as luteolins and quercetins showed temporary increases at early time points under elevated CO2, but decreases under low CO2, indicating a possible role in ROS scavenging during the early CO2 response. Under low CO2, proteins that showed significant changes were enriched in cellular redox status regulation, indicating an important role of ROS regulation under low

CO2.

Most interestingly, jasmonic acid biosynthesis has been shown to be significantly affected by CO2 treatment. Using reverse genetics, targeted metabolite profiling and stomatal movement assays, we confirmed that CO2 induced stomatal closure was mediated by JA-Ile and JA signaling, but not by ABA. There is a high possibility that this increase in JA biosynthesis is regulated by CA1. The loss of CA1 has been shown to

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decrease chloroplast lipid accumulation in cotton seeds (Hoang and Chapman, 2002), indicating CA1 plays an important role in lipid biosynthesis. During low CO2 induced stomatal opening, multiple phytohormones including auxin, cytokinin, brassinosteroids and gibberellins were found to be significantly increased during early time points. Unlike elevated CO2, JA biosynthesis is diverted to a branch pathway under low CO2, possibly facilitating stomatal opening. Further confirmation of phytohormone functions during low

CO2 response is being tested.

Overall, this study has expanded knowledge of the guard cell metabolome and proteome in response to different concentrations of CO2. We provided strong evidence for a new mechanism of JA-mediated stomatal closure in response to elevated CO2, as well as hormone crosstalk during low CO2 induced stomatal opening. At the same time, most CO2 signaling mechanisms established now is based on the reference plant

Arabidopsis. The knowledge gained may be limited when transferring to other crop species. Our findings from Brassica napus guard cells can be directly applied to this crop for breeding or genetic engineering to improve its yield and/or resistance to diseases.

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LIST OF REFERENCES

Abe, H., Urao, T., Ito, T., Seki, M., Shinozaki, K. and Yamaguchi-Shinozaki, K. (2003) Arabidopsis AtMYC2 (bHLH) and AtMYB2 (MYB) Function as Transcriptional Activators in Abscisic Acid Signaling. The Plant Cell, 15, 63-78.

Agati, G., Azzarello, E., Pollastri, S. and Tattini, M. (2012) Flavonoids as antioxidants in plants: Location and functional significance. Plant Science, 196, 67-76.

Aharoni, A., Dixit, S., Jetter, R., Thoenes, E., van Arkel, G. and Pereira, A. (2004) The SHINE Clade of AP2 Domain Transcription Factors Activates Wax Biosynthesis, Alters Cuticle Properties, and Confers Drought Tolerance when Overexpressed in Arabidopsis. The Plant Cell, 16, 2463-2480.

Ainsworth, E.A. and Long, S.P. (2005) What have we learned from 15 years of free-air CO2 enrichment (FACE)? A meta-analytic review of the responses of photosynthesis, canopy. New Phytologist, 165, 351-371.

Ainsworth, E.A., Rogers, A., Nelson, R. and Long, S.P. (2004) Testing the “source–sink” hypothesis of down-regulation of photosynthesis in elevated [CO2] in the field with single gene substitutions in Glycine max. Agr Forest Meteorol, 122, 85-94.

Araujo, W.L., Nunes-Nesi, A., Osorio, S., Usadel, B., Fuentes, D., Nagy, R., Balbo, I., Lehmann, M., Studart-Witkowski, C., Tohge, T., Martinoia, E., Jordana, X., Damatta, F.M. and Fernie, A.R. (2011) Antisense inhibition of the iron-sulphur subunit of succinate dehydrogenase enhances photosynthesis and growth in tomato via an organic acid-mediated effect on stomatal aperture. Plant Cell, 23, 600-627.

Arnao, M.B. and Hernández-Ruiz, J. (2006) The Physiological Function of Melatonin in Plants. Plant Signaling & Behavior, 1, 89-95.

Assmann, S.M. (1999) The cellular basis of guard cell sensing of rising CO2. Plant Cell and Environment, 22, 629-637.

Atwell, B.J., Kriedemann, P.E. and Turnbull, C.G.N. (1999) Photosynthetic acclimation. In Plants in action : adaptation in nature, performance in cultivation. South Yarra: MacMillan Education Australia.

Azoulay-Shemer, T., Bagheri, A., Wang, C., Palomares, A., Stephan, A., Kunz, H.-H. and Schroeder, J.I. (2016) Starch biosynthesis in guard cells but not in mesophyll cells is involved in CO2-induced stomatal closing. Plant Physiology.

Azoulay-Shemer, T., Palomares, A., Bagheri, A., Israelsson-Nordstrom, M., Engineer, C.B., Bargmann, B.O.R., Stephan, A.B. and Schroeder, J.I. (2015) Guard cell photosynthesis is critical for stomatal turgor production, yet does not directly mediate CO2- and ABA-induced stomatal closing. Plant J., 83, 567-581.

168

Bauer, H., Ache, P., Lautner, S., Fromm, J., Hartung, W., Al-Rasheid, Khaled A.S., Sonnewald, S., Sonnewald, U., Kneitz, S., Lachmann, N., Mendel, Ralf R., Bittner, F., Hetherington, Alistair M. and Hedrich, R. (2013) The Stomatal Response to Reduced Relative Humidity Requires Guard Cell-Autonomous ABA Synthesis. Current Biology, 23, 53-57.

Beadle, C.L., Jarvis, P.G. and Neilson, R.E. (1979) Leaf conductance as related to xylem water potential and carbon-dioxide concentration in Sitka Spruce. Physiologia Plantarum, 45, 158-166.

Berger, S., Bell, E. and Mullet, J.E. (1996) Two methyl jasmonate-insensitive mutants show altered expression of AtVsp in response to methyl jasmonate and wounding. Plant Physiology, 111, 525-531.

Birkenhead, K. and Willmer, C.M. (1986) Some Biochemical Characteristics of Guard Cell and Mesophyll Cell Protoplasts from Commelina communis L. Journal of Experimental Botany, 37, 119-128.

Bowes, G. (1993) Facing the inevitable: Plants and increasing atmospheric CO2. Annual Review of Plant Physiology and Plant Molecular Biology, 44, 309-332.

Bridgewater Br, E.A.M. (2014) High Resolution Mass Spectrometry Improves Data Quantity and Quality as Compared to Unit Mass Resolution Mass Spectrometry in High-Throughput Profiling Metabolomics. Journal of Postgenomics Drug & Biomarker Development, 04.

Buchanan, B.B., Gruissem, W. and Jones, R.L. (2000) Biochemistry & Molecular Biology of Plants. In Biochemistry & Molecular Biology of Plants (Buchanan, B.B. et al. eds): American Society of Plant Physiologists, pp. 1189-1197.

Chalhoub, B., Denoeud, F., Liu, S.Y., Parkin, I.A.P., Tang, H.B., Wang, X.Y., Chiquet, J., Belcram, H., Tong, C.B., Samans, B., Correa, M., Da Silva, C., Just, J., Falentin, C., Koh, C.S., Le Clainche, I., Bernard, M., Bento, P., Noel, B., Labadie, K., Alberti, A., Charles, M., Arnaud, D., Guo, H., Daviaud, C., Alamery, S., Jabbari, K., Zhao, M.X., Edger, P.P., Chelaifa, H., Tack, D., Lassalle, G., Mestiri, I., Schnel, N., Le Paslier, M.C., Fan, G.Y., Renault, V., Bayer, P.E., Golicz, A.A., Manoli, S., Lee, T.H., Thi, V.H.D., Chalabi, S., Hu, Q., Fan, C.C., Tollenaere, R., Lu, Y.H., Battail, C., Shen, J.X., Sidebottom, C.H.D., Wang, X.F., Canaguier, A., Chauveau, A., Berard, A., Deniot, G., Guan, M., Liu, Z.S., Sun, F.M., Lim, Y.P., Lyons, E., Town, C.D., Bancroft, I., Wang, X.W., Meng, J.L., Ma, J.X., Pires, J.C., King, G.J., Brunel, D., Delourme, R., Renard, M., Aury, J.M., Adams, K.L., Batley, J., Snowdon, R.J., Tost, J., Edwards, D., Zhou, Y.M., Hua, W., Sharpe, A.G., Paterson, A.H., Guan, C.Y. and Wincker, P. (2014) Early allopolyploid evolution in the post-Neolithic Brassica napus oilseed genome. Science, 345, 950-953.

169

Chater, C., Peng, K., Movahedi, M., Dunn, Jessica A., Walker, Heather J., Liang, Y.-K., McLachlan, Deirdre H., Casson, S., Isner, Jean C., Wilson, I., Neill, Steven J., Hedrich, R., Gray, Julie E. and Hetherington, Alistair M. (2015) Elevated CO2- induced responses in stomata require ABA and ABA signaling. Current Biology, 25, 2709-2716.

Chen, W., Gong, L., Guo, Z.L., Wang, W.S., Zhang, H.Y., Liu, X.Q., Yu, S.B., Xiong, L.Z. and Luo, J. (2013) A novel integrated method for large-scale detection, identification, and quantification of widely targeted metabolites: application in the study of rice metabolomics. Molecular Plant, 6, 1769-1780.

Conesa, A. and Götz, S. (2008) Blast2GO: A Comprehensive Suite for Functional Analysis in Plant Genomics. International Journal of Plant Genomics, 2008, 619832.

Coquoz, J.-L., Buchala, A. and Métraux, J.-P. (1998) The Biosynthesis of Salicylic Acid in Potato Plants. Plant Physiology, 117, 1095-1101.

Cure, J.D. and Acock, B. (1986) Crop responses to carbon dioxide doubling: a literature survey. Agr Forest Meteorol, 38, 127-145.

Dai, S. and Chen, S. (2012) Single-cell-type proteomics: toward a holistic understanding of plant function. Molecular & Cellular Proteomics, 11, 1622-1630.

Daloso, D.M., Antunes, W.C., Pinheiro, D.P., Waquim, J.P., Araujo, W.L., Loureiro, M.E., Fernie, A.R. and Williams, T.C. (2015a) Tobacco guard cells fix CO2 by both RubisCO and PEPcase whilst sucrose acts as a substrate during light induced stomatal opening. Plant Cell Environ.

Daloso, D.M., Williams, T.C.R., Antunes, W.C., Pinheiro, D.P., Müller, C., Loureiro, M.E. and Fernie, A.R. (2015b) Guard cell-specific upregulation of sucrose synthase 3 reveals that the role of sucrose in stomatal function is primarily energetic. New Phytologist, 209, 1470–1483.

Daszkowska-Golec, A. and Szarejko, I. (2013) Open or close the gate - stomata action under the control of phytohormones in drought stress conditions. Front Plant Sci, 4, 138.

Denecke, M., Schulz, M., Fischer, C. and Schnabl, H. (1993) Partial purification and characterization of stomatal phosphoenolpyruvate carboxylase from Vicia faba. Physiologia Plantarum, 87, 96-102.

Dittrich, P. and Raschke, K. (1977) Malate metabolism in isolated epidermis of Commelina communis L. in relation to stomatal functioning. Planta, 134, 77-81.

170

Du, Z., Aghoram, K. and Outlaw Jr, W.H. (1997) In Vivo phosphorylation of phosphoenolpyruvate carboxylase in guard cells of Vicia faba L. is enhanced by fusicoccin and suppressed by abscisic acid. Archives of Biochemistry and Biophysics, 337, 345-350.

Du, Z., Zhou, X., Ling, Y., Zhang, Z. and Su, Z. (2010) agriGO: a GO analysis toolkit for the agricultural community. Nucleic Acids Research, 38, W64-W70.

Easterling, W., Aggarwal, P., Batima, P., Brander, K., Erda, L., Howden, M., Kirilenko, A., Morton, J., Soussana, J.-F., Schmidhuber, J., Tubiello, F., Antle, J., Baethgen, W., Barlow, C., Chhetri, N., Clers, S.d., Craig, P., Cranage, J., Killmann, W., Mader, T., Mann, S., O’Brien, K., Pfeiffer, C. and Sedjo, R. (2007) Food, fibre, and forest products. In Climate Change 2007: Impacts, Adaptation and Vulnerability. (Parry, M. et al. eds): Cambridge University Press, Cambridge, UK, pp. 273-313.

Engineer, C.B., Ghassemian, M., Anderson, J.C., Peck, S.C., Hu, H. and Schroeder, J.I. (2014) Carbonic anhydrases, EPF2 and a novel protease mediate CO2 control of stomatal development. Nature, 513, 246-250.

Engineer, C.B., Hashimoto-Sugimoto, M., Negi, J., Israelsson-Nordstrom, M., Azoulay- Shemer, T., Rappel, W.J., Iba, K. and Schroeder, J.I. (2015) CO2 sensing and CO2 regulation of stomatal conductance: advances and open questions. Trends in Plant Science.

Ephritikhine, G., Fellner, M., Vannini, C., Lapous, D. and Barbier-Brygoo, H. (1999) The sax1 dwarf mutant of Arabidopsis thaliana shows altered sensitivity of growth responses to abscisic acid, auxin, gibberellins and ethylene and is partially rescued by exogenous brassinosteroid. The Plant Journal, 18, 303-314.

Ewert, M.S., Outlaw, W.H., Zhang, S., Aghoram, K. and Riddle, K.A. (2000) Accumulation of an apoplastic solute in the guard-cell wall is sufficient to exert a significant effect on transpiration in Vicia faba leaflets. Plant Cell and Environment, 23, 195-203.

Farag, M.A., Huhman, D.V., Dixon, R.A. and Sumner, L.W. (2008) Metabolomics reveals novel pathways and differential mechanistic and elicitor-specific responses in phenylpropanoid and isoflavonoid biosynthesis in Medicago truncatula cell cultures. Plant Physiology, 146, 387-402.

Fernie, A.R. and Martinoia, E. (2009) Malate. Jack of all trades or master of a few? Phytochemistry, 70, 828-832.

Fiehn, O., Wohlgemuth, G., Scholz, M., Kind, T., Lee, D.Y., Lu, Y., Moon, S. and Nikolau, B. (2008) Quality control for plant metabolomics: reporting MSI- compliant studies. The Plant Journal, 53, 691-704.

171

Fonseca, S., Chini, A., Hamberg, M., Adie, B., Porzel, A., Kramell, R., Miersch, O., Wasternack, C. and Solano, R. (2009) (+)-7-iso-Jasmonoyl-L-isoleucine is the endogenous bioactive jasmonate. Nat Chem Biol, 5, 344-350.

Fricker, M. and Willmer, C. (1996a) Stomatal responses to environmental factors - carbon dioxide. In Stomata. London: Chapman & Hall.

Fricker, M. and Willmer, C. (1996b) The metabolism of guard cell - Introduction. In Stomata. London: Chapman & Hall.

Geiger, D., Scherzer, S., Mumm, P., Stange, A., Marten, I., Bauer, H., Ache, P., Matschi, S., Liese, A., Al-Rasheid, K.A.S., Romeis, T. and Hedrich, R. (2009) Activity of guard cell anion channel SLAC1 is controlled by drought-stress signaling kinase-phosphatase pair. Proceedings of the National Academy of Sciences, 106, 21425-21430.

Geng, S., Misra, B.B., Armas, E.d., Huhman, D., Alborn, H.T., Sumner, L.W. and Chen, S. (2016) Jasmonate-mediated stomatal closure under elevated CO2 revealed by time-resolved metabolomics. Plant J.

Gilroy, S., Read, N.D. and Trewavas, A.J. (1990) Elevation of cytoplasmic calcium by caged calcium or caged inositol triphosphate initiates stomatal closure. Nature, 346, 769-771.

Gish, W. (1996-2009) AB-BLAST 3.0 Personal Edition. http://blast.advbiocomp.com

Glauser, G. and Wolfender, J.L. (2013) A non-targeted approach for extended liquid chromatography-mass spectrometry profiling of free and esterified jasmonates after wounding. Methods in Molecular Biology, 1011, 123-134.

Gotow, K., Tanaka, K., Kondo, N., Kobayashi, K. and Syōno, K. (1985) Light Activation of NADP-Malate Dehydrogenase in Guard Cell Protoplasts from Vicia faba L. Plant Physiology, 79, 829-832.

Gray, J.E., Holroyd, G.H., van der Lee, F.M., Bahrami, A.R., Sijmons, P.C., Woodward, F.I., Schuch, W. and Hetherington, A.M. (2000) The HIC signalling pathway links CO2 perception to stomatal development. Nature, 408, 713-716.

Gray, W.M., Kepinski, S., Rouse, D., Leyser, O. and Estelle, M. (2001) Auxin regulates SCFTIR1-dependent degradation of AUX/IAA proteins. Nature, 414, 271-276.

Guo, H., Sun, Y., Li, Y., Liu, X., Wang, P., Zhu-Salzman, K. and Ge, F. (2014) Elevated CO2 alters the feeding behaviour of the pea aphid by modifying the physical and chemical resistance of Medicago truncatula. Plant Cell and Environment, 37, 2158-2168.

172

Guo, H., Sun, Y., Ren, Q., Zhu-Salzman, K., Kang, L., Wang, C., Li, C. and Ge, F. (2012) Elevated CO2 reduces the resistance and tolerance of tomato plants to Helicoverpa armigera by suppressing the JA signaling pathway. PLoS One, 7, e41426.

Hashimoto-Sugimoto, M., Higaki, T., Yaeno, T., Nagami, A., Irie, M., Fujimi, M., Miyamoto, M., Akita, K., Negi, J., Shirasu, K., Hasezawa, S. and Iba, K. (2013) A Munc13-like protein in Arabidopsis mediates H+-ATPase translocation that is essential for stomatal responses. Nature Communications, 4.

Hashimoto, M., Negi, J., Young, J., Israelsson, M., Schroeder, J.I. and Iba, K. (2006) Arabidopsis HT1 kinase controls stomatal movements in response to CO2. Nature Cell Biology, 8, 391-397.

Hastie, T., Tibshirani, R., Narasimhan, B. and Chu, G. Impute: Imputation for microarray data.

Haubrick, L.L., Torsethaugen, G. and Assmann, S.M. (2006) Effect of brassinolide, alone and in concert with abscisic acid, on control of stomatal aperture and potassium currents of Vicia faba guard cell protoplasts. Physiologia Plantarum, 128, 134-143.

Hedrich, R., Raschke, K. and Stitt, M. (1985) A Role for Fructose 2,6-Bisphosphate in Regulating Carbohydrate Metabolism in Guard Cells. Plant Physiology, 79, 977- 982.

Hoang, C.V. and Chapman, K.D. (2002) Biochemical and molecular inhibition of plastidial carbonic anhydrase reduces the incorporation of acetate into lipids in cotton embryos and tobacco cell suspensions and leaves. Plant Physiology, 128, 1417-1427.

Holm, L. and Sander, C. (1998) Removing near-neighbour redundancy from large protein sequence collections. Bioinformatics, 14, 423-429.

Horrer, D., Flütsch, S., Pazmino, D., Matthews, Jack S.A., Thalmann, M., Nigro, A., Leonhardt, N., Lawson, T. and Santelia, D. (2016) Blue light induces a distinct starch degradation pathway in guard cells for stomatal opening. Current Biology, 26, 362-370.

Hu, H., Boisson-Dernier, A., Israelsson-Nordstrom, M., Bohmer, M., Xue, S., Ries, A., Godoski, J., Kuhn, J.M. and Schroeder, J.I. (2010) Carbonic anhydrases are upstream regulators of CO2-controlled stomatal movements in guard cells. Nature Cell Biology, 12, 87-93; sup pp 81-18.

Hu, H., Rappel, W.J., Occhipinti, R., Ries, A., Bohmer, M., You, L., Xiao, C., Engineer, C.B., Boron, W.F. and Schroeder, J.I. (2015) Distinct cellular locations of carbonic anhydrases mediate CO2 control of stomatal movements. Plant Physiology.

173

Hwang, J.-U., Jeon, B.W., Hong, D. and Lee, Y. (2011) Active ROP2 GTPase inhibits ABA- and CO2-induced stomatal closure. Plant, Cell & Environment, 34, 2172- 2182.

Isebrands, J.G., McDonald, E.P., Kruger, E., Hendrey, G., Percy, K., Pregitzer, K., Sober, J. and Karnosky, D.F. (2001) Growth responses of Populus tremuloides clones to interacting elevated carbon dioxide and tropospheric ozone. Environmental Pollution, 115, 359-371.

Islam, M.M., Hossain, M.A., Jannat, R., Munemasa, S., Nakamura, Y., Mori, I.C. and Murata, Y. (2010) Cytosolic alkalization and cytosolic calcium oscillation in Arabidopsis guard cells response to ABA and MeJA. Plant and Cell Physiology, 51, 1721-1730.

Isopp, H., Frehner, M., Long, S.P. and Nösberger, J. (2000) Sucrose-phosphate synthase responds differently to source-sink relations and to photosynthetic rates: Lolium perenne L. growing at elevated pCO2 in the field. Plant, Cell & Environment, 23, 597-607.

Issak, M., Okuma, E., Munemasa, S., Nakamura, Y., Mori, I.C. and Murata, Y. (2013) Neither Endogenous Abscisic Acid nor Endogenous Jasmonate Is Involved in Salicylic Acid-, Yeast Elicitor-, or Chitosan-Induced Stomatal Closure in Arabidopsis thaliana. Biosci Biotech Bioch, 77, 1111-1113.

Jenks, M.A., Tuttle, H.A., Eigenbrode, S.D. and Feldmann, K.A. (1995) Leaf Epicuticular Waxes of the Eceriferum Mutants in Arabidopsis. Plant Physiol, 108, 369-377.

Jiao, J.-a. and Chollet, R. (1991) Posttranslational Regulation of Phosphoenolpyruvate Carboxylase in C4 and Crassulacean Acid Metabolism Plants. Plant Physiology, 95, 981-985.

Jin, X., Wang, R.S., Zhu, M., Jeon, B.W., Albert, R., Chen, S. and Assmann, S.M. (2013) Abscisic acid-responsive guard cell metabolomes of Arabidopsis wild-type and gpa1 G-protein mutants. Plant Cell, 25, 4789-4811.

Johnson, W.E., Li, C. and Rabinovic, A. (2007) Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics, 8, 118-127.

Jones, K.A., Kim, P.D., Patel, B.B., Kelsen, S.G., Braverman, A., Swinton, D.J., Gafken, P.R., Jones, L.A., Lane, W.S., Neveu, J.M., Leung, H.C., Shaffer, S.A., Leszyk, J.D., Stanley, B.A., Fox, T.E., Stanley, A., Hall, M.J., Hampel, H., South, C.D., de la Chapelle, A., Burt, R.W., Jones, D.A., Kopelovich, L. and Yeung, A.T. (2013) Immunodepletion plasma proteomics by tripleTOF 5600 and Orbitrap elite/LTQ- Orbitrap Velos/Q exactive mass spectrometers. J Proteome Res, 12, 4351-4365.

Jung, J.Y., Kim, Y.W., Kwak, J.M., Hwang, J.U., Young, J., Schroeder, J.I., Hwang, I. and Lee, Y.S. (2002) Phosphatidylinositol 3-and 4-phosphate are required for normal stomatal movements. Plant Cell, 14, 2399-2412.

174

Katsir, L., Schilmiller, A.L., Staswick, P.E., He, S.Y. and Howe, G.A. (2008) COI1 is a critical component of a receptor for jasmonate and the bacterial virulence factor coronatine. Proceedings of the National Academy of Sciences, 105, 7100-7105.

Kelly, G., Moshelion, M., David-Schwartz, R., Halperin, O., Wallach, R., Attia, Z., Belausov, E. and Granot, D. (2013) Hexokinase mediates stomatal closure. Plant J., 75, 977-988.

Kepinski, S. (2007) The anatomy of auxin perception. BioEssays, 29, 953-956.

Khokon, M.A.R., Okuma, E., Hossain, M.A., Munemasa, S., Uraji, M., Nakamura, Y., Mori, I.C. and Murata, Y. (2011) Involvement of extracellular oxidative burst in salicylic acid-induced stomatal closure in Arabidopsis. Plant, Cell & Environment, 34, 434-443.

Khokon, M.A.R., Salam, M.A., Jammes, F., Ye, W., Hossain, M.A., Uraji, M., Nakamura, Y., Mori, I.C., Kwak, J.M. and Murata, Y. (2015) Two guard cell mitogen-activated protein kinases, MPK9 and MPK12, function in methyl jasmonate-induced stomatal closure in Arabidopsis thaliana. Plant Biology, 17, 946-952.

Kim, S.G., Kim, S.T., Wang, Y., Kim, S.-K., Lee, C.H., Kim, K.-K., Kim, J.-K., Lee, S.Y. and Kang, K.Y. (2010a) Overexpression of rice isoflavone reductase-like gene (OsIRL) confers tolerance to reactive oxygen species. Physiologia Plantarum, 138, 1-9.

Kim, T.-H., Böhmer, M., Hu, H., Nishimura, N. and Schroeder, J.I. (2010b) Guard cell signal transduction network: advances in understanding abscisic acid, CO2, and Ca2+ signaling. Annual Review of Plant Biology, 61, 561-591.

Kimball, B.A. (1983) Carbon Dioxide and Agricultural Yield: An Assemblage and Analysis of 430 Prior Observations1. Agronomy Journal, 75, 779-788.

Kirschbaum, M.U.F. (2011) Does enhanced photosynthesis enhance growth? Lessons learned from CO2 enrichment studies. Plant Physiology, 155, 117-124.

Klambt, H.D. (1962) Conversion in Plants of Benzoic Acid to Salicylic Acid and its [beta]d-Glucoside. Nature, 196, 491-491.

Kolla, V.A., Vavasseur, A. and Raghavendra, A.S. (2007) Hydrogen peroxide production is an early event during bicarbonate induced stomatal closure in abaxial epidermis of Arabidopsis. Planta, 225, 1421-1429.

Kollist, H., Nuhkat, M. and Roelfsema, M.R. (2014) Closing gaps: linking elements that control stomatal movement. New Phytologist, 203, 44-62.

175

Kopka, J., Schauer, N., Krueger, S., Birkemeyer, C., Usadel, B., Bergmüller, E., Dörmann, P., Weckwerth, W., Gibon, Y., Stitt, M., Willmitzer, L., Fernie, A.R. and Steinhauser, D. (2005) [email protected]: the Golm Metabolome Database. Bioinformatics, 21, 1635-1638.

Kunz, H.H., Häusler, R.E., Fettke, J., Herbst, K., Niewiadomski, P., Gierth, M., Bell, K., Steup, M., Flügge, U.I. and Schneider, A. (2010) The role of plastidial glucose-6- phosphate/phosphate translocators in vegetative tissues of Arabidopsis thaliana mutants impaired in starch biosynthesis. Plant Biology, 12, 115-128.

Kwak, J.M., Mori, I.C., Pei, Z.-M., Leonhardt, N., Torres, M.A., Dangl, J.L., Bloom, R.E., Bodde, S., Jones, J.D.G. and Schroeder, J.I. (2003) NADPH oxidase AtrbohD and AtrbohF genes function in ROS-dependent ABA signaling in Arabidopsis. The EMBO Journal, 22, 2623-2633.

Kwak, J.M., Murata, Y., Baizabal-Aguirre, V.M., Merrill, J., Wang, M., Kemper, A., Hawke, S.D., Tallman, G. and Schroeder, J.I. (2001) Dominant Negative Guard Cell K+ Channel Mutants Reduce Inward-Rectifying K+ Currents and Light- Induced Stomatal Opening in Arabidopsis. Plant Physiology, 127, 473-485.

L., T. (2008) Reductions in mesophyll and guard cell photosynthesis impact on the control of stomatal responses to light and CO(2). journal of experimental botany.

Laudert, D., Pfannschmidt, U., Lottspeich, F., Holländer-Czytko, H. and Weiler, E.W. (1996) Cloning, molecular and functional characterization of Arabidopsis thaliana allene oxide synthase (CYP 74), the first enzyme of the octadecanoid pathway to jasmonates. Plant Molecular Biology, 31, 323-335.

Laurie-Berry, N., Joardar, V., Street, I.H. and Kunkel, B.N. (2006) The Arabidopsis thaliana JASMONATE INSENSITIVE 1 gene is required for suppression of salicylic acid-dependent defenses during infection by Pseudomonas syringae. Molecular Plant-Microbe Interactions, 19, 789-800.

Lawson, T. (2009a) Guard cell photosynthesis and stomatal function. New Phytologist, 181, 13-34.

Lawson, T. (2009b) Guard cell photosynthesis and stomatal function. New Phytol, 181, 13-34.

Lawson, T., Simkin, A.J., Kelly, G. and Granot, D. (2014) Mesophyll photosynthesis and guard cell metabolism impacts on stomatal behaviour. New Phytol, 203, 1064- 1081.

Lawton, K.A., Berger, A., Mitchell, M., Milgram, K.E., Evans, A.M., Guo, L., Hanson, R.W., Kalhan, S.C., Ryals, J.A. and Milburn, M.V. (2008) Analysis of the adult human plasma metabolome. Pharmacogenomics, 9, 383-397.

176

Leakey, A.D. (2009) Rising atmospheric carbon dioxide concentration and the future of C4 crops for food and fuel. Proceedings of the Royal Society B Biological Sciences, 276, 2333-2343.

Lee, M., Choi, Y., Burla, B., Kim, Y.-Y., Jeon, B., Maeshima, M., Yoo, J.-Y., Martinoia, E. and Lee, Y. (2008) The ABC transporter AtABCB14 is a malate importer and modulates stomatal response to CO2. Nature Cell Biology, 10, 1217-1223.

Lee, S.C., Lan, W., Buchanan, B.B. and Luan, S. (2009) A protein kinase-phosphatase pair interacts with an ion channel to regulate ABA signaling in plant guard cells. Proceedings of the National Academy of Sciences, 106, 21419-21424.

Lee, Y. and Assmann, S.M. (1991) Diacylglycerols induce both ion pumping in patch- clamped guard-cell protoplasts and opening of intact stomata. Proceedings of the National Academy of Sciences, 88, 2127-2131.

Leshem, Y. and Levine, A. (2013) Zooming into sub-organellar localization of reactive oxygen species in guard cell chloroplasts during abscisic acid and methyl jasmonate treatments. Plant Signaling & Behavior, 8, e25689.

Li, C., Tan, D.X., Liang, D., Chang, C., Jia, D.F. and Ma, F.W. (2015a) Melatonin mediates the regulation of ABA metabolism, free-radical scavenging, and stomatal behaviour in two Malus species under drought stress. Journal of Experimental Botany, 66, 669-680.

Li, X., Ahammed, G.J., Zhang, Y.Q., Zhang, G.Q., Sun, Z.H., Zhou, J., Zhou, Y.H., Xia, X.J., Yu, J.Q. and Shi, K. (2015b) Carbon dioxide enrichment alleviates heat stress by improving cellular redox homeostasis through an ABA-independent process in tomato plants. Plant Biololgy, 17, 81-89.

Li, X., Sun, Z., Shao, S., Zhang, S., Ahammed, G.J., Zhang, G., Jiang, Y., Zhou, J., Xia, X., Zhou, Y., Yu, J. and Shi, K. (2015c) Tomato-Pseudomonas syringae interactions under elevated CO2 concentration: the role of stomata. J Exp Bot, 66, 307-316.

Lisec, J., Schauer, N., Kopka, J., Willmitzer, L. and Fernie, A.R. (2006) Gas chromatography mass spectrometry-based metabolite profiling in plants. Nat. Protocols, 1, 387-396.

Liu, X.Q., Li, F., Tang, J.Y., Wang, W.H., Zhang, F.X., Wang, G.D., Chu, J.F., Yan, C.Y., Wang, T.Q., Chu, C.C. and Li, C.Y. (2012) Activation of the Jasmonic Acid Pathway by Depletion of the Hydroperoxide Lyase OsHPL3 Reveals Crosstalk between the HPL and AOS Branches of the Oxylipin Pathway in Rice. Plos One, 7.

Ludlow, M.M. and Jarvis, P.G. (1971) Photosynthesis in Sitka Spruce (Picea sitchensis) (Bong.) Carr.). I. General Characteristics. Journal of Applied Ecology, 8, 925-953.

177

Lüscher, A., Hartwig, U.A., Suter, D. and Nösberger, J. (2000) Direct evidence that symbiotic N2 fixation in fertile grassland is an important trait for a strong response of plants to elevated atmospheric CO2. Global Change Biology, 6, 655-662.

Ma, Y., Szostkiewicz, I., Korte, A., Moes, D., Yang, Y., Christmann, A. and Grill, E. (2009) Regulators of PP2C Phosphatase Activity Function as Abscisic Acid Sensors. Science, 324, 1064-1068.

Marc, G.R.W.a.B.B.a.L.B.a.R.G.a.W.H.A.L.a.T.L.a.M.M.a.A.M.a.S.M.a. (2015) gplots: Various R Programming Tools for Plotting Data. http://CRAN.R- project.org/package=gplots

Matrosova, A., Bogireddi, H., Mateo-Penas, A., Hashimoto-Sugimoto, M., Iba, K., Schroeder, J.I. and Israelsson-Nordstrom, M. (2015) The HT1 protein kinase is essential for red light-induced stomatal opening and genetically interacts with OST1 in red light and CO2-induced stomatal movement responses. New Phytologist, 208, 1126-1137.

McElwain, J.C. and Chaloner, W.G. (1995) Stomatal Density and Index of Fossil Plants Track Atmospheric Carbon Dioxide in the Palaeozoic. Annals of Botany, 76, 389- 395.

McLachlan, Deirdre H., Lan, J., Geilfus, C.-M., Dodd, Antony N., Larson, T., Baker, A., Hõrak, H., Kollist, H., He, Z., Graham, I., Mickelbart, Michael V. and Hetherington, Alistair M. (2016) The Breakdown of Stored Triacylglycerols Is Required during Light-Induced Stomatal Opening. Current Biology, 26, 707-712.

Medeiros, D.B., Martins, S.C.V., Cavalcanti, J.H.F., Daloso, D.M., Martinoia, E., Nunes- Nesi, A., DaMatta, F.M., Fernie, A.R. and Araújo, W.L. (2016) Enhanced photosynthesis and growth in atquac1 knockout mutants are due to altered organic acid accumulation and an increase in both stomatal and mesophyll conductance. Plant Physiology, 170, 86-101.

Melotto, M., Underwood, W., Koczan, J., Nomura, K. and He, S.Y. (2006) Plant stomata function in innate immunity against bacterial invasion. Cell, 126, 969-980.

Merilo, E., Jalakas, P., Laanemets, K., Mohammadi, O., Horak, H., Kollist, H. and Brosche, M. (2015) Abscisic acid transport and homeostasis in the context of stomatal regulation. Molecular Plant, 8, 1321-1333.

Merilo, E., Laanemets, K., Hu, H., Xue, S., Jakobson, L., Tulva, I., Gonzalez-Guzman, M., Rodriguez, P.L., Schroeder, J.I., Brosche, M. and Kollist, H. (2013) PYR/RCAR receptors contribute to ozone-, reduced air humidity-, darkness-, and CO2-induced stomatal regulation. Plant Physiol, 162, 1652-1668.

178

Meyer, S., Mumm, P., Imes, D., Endler, A., Weder, B., Al-Rasheid, K.A.S., Geiger, D., Marten, I., Martinoia, E. and Hedrich, R. (2010) AtALMT12 represents an R-type anion channel required for stomatal movement in Arabidopsis guard cells. Plant J., 63, 1054-1062.

Misra, B., Acharya, B.R., Granot, D., Assmann, S.M. and Chen, S. (2015a) The guard cell metabolome: functions in stomatal movement and global food security. Frontiers in Plant Science, 6.

Misra, B.B., de Armas, E., Tong, Z. and Chen, S. (2015b) Metabolomic Responses of Guard Cells and Mesophyll Cells to Bicarbonate. PLoS One, 10, e0144206.

Montillet, J.-L., Leonhardt, N., Mondy, S., Tranchimand, S., Rumeau, D., Boudsocq, M., Garcia, A.V., Douki, T., Bigeard, J., Laurière, C., Chevalier, A., Castresana, C. and Hirt, H. (2013) An abscisic acid-independent oxylipin pathway controls stomatal closure and immune defense in Arabidopsis. PLoS Biology, 11, e1001513.

Montillet, J.L. and Hirt, H. (2013) New checkpoints in stomatal defense. Trends in Plant Science, 18, 295-297.

Morison, J.I.L. and Jarvis, P.G. (1983) Direct and indirect effects of light on stomata. II. In Commelina Communis L. Plant Cell and Environment, 6, 103-109.

Mostafa, I., Zhu, N., Yoo, M.-J., Balmant, K.M., Misra, B.B., Dufresne, C., Abou- Hashem, M., Chen, S. and El-Domiaty, M. (2016) New nodes and edges in the glucosinolate molecular network revealed by proteomics and metabolomics of Arabidopsis myb28/29 and cyp79B2/B3 glucosinolate mutants. J Proteomics, 138, 1-19.

Munemasa, S., Hauser, F., Park, J., Waadt, R., Brandt, B. and Schroeder, J.I. (2015) Mechanisms of abscisic acid-mediated control of stomatal aperture. Current Opinion in Plant Biology, 28, 154-162.

Munemasa, S., Mori, I.C. and Murata, Y. (2014) Methyl jasmonate signaling and signal crosstalk between methyl jasmonate and abscisic acid in guard cells. Plant Signaling & Behavior, 6, 939-941.

Murashige, T. and Skoog, F. (1962) A revised medium for rapid growth and bio assays with tobacco tissue cultures. Physiologia Plantarum, 15, 473-497.

Murata, Y., Mori, I.C. and Munemasa, S. (2015) Diverse stomatal signaling and the signal integration mechanism. Annu Rev Plant Biol, 66, 369-392.

Nambara, E. and Marion-Poll, A. (2005) Abscisic acid biosynthesis and catabolism. Annual Review of Plant Biology, 56, 165-185.

179

Naoumkina, M., Farag, M.A., Sumner, L.W., Tang, Y., Liu, C.-J. and Dixon, R.A. (2007) Different mechanisms for phytoalexin induction by pathogen and wound signals in Medicago truncatula. Proceedings of the National Academy of Sciences, 104, 17909-17915.

Neill, S., Barros, R., Bright, J., Desikan, R., Hancock, J., Harrison, J., Morris, P., Ribeiro, D. and Wilson, I. (2008) Nitric oxide, stomatal closure, and abiotic stress. J Exp Bot, 59, 165-176.

Ng, C.K.Y., Carr, K., McAinsh, M.R., Powell, B. and Hetherington, A.M. (2001) Drought- induced guard cell signal transduction involves sphingosine-1-phosphate. Nature, 410, 596-599.

Ng, P.A.P. and Jarvis, P.G. (1980) Hysteresis in the response of stomatal conductance in Pinus-Sylvestris L needles to light - observations and a hypothesis. Plant Cell and Environment, 3, 207-216.

Noguchi, K., Watanabe, C.K. and Terashima, I. (2015) Effects of elevated atmospheric CO2 on primary metabolite levels in Arabidopsis thaliana Col-0 leaves: an examination of metabolome data. Plant and Cell Physiology.

Ottman, M.J., Kimball, B.A., Pinter, P.J., Wall, G.W., Vanderlip, R.L., Leavitt, S.W., LaMorte, R.L., Matthias, A.D. and Brooks, T.J. (2001) Elevated CO2 increases sorghum biomass under drought conditions. New Phytologist, 150, 261-273.

Outlaw, W.H. and Lowry, O.H. (1977) Organic-acid and potassium accumulation in guard cells during stomatal opening. Proceedings of the National Academy of Sciences of the United States of America, 74, 4434-4438.

Outlaw, W.H., Tarczynski, M.C. and Anderson, L.C. (1982) Taxonomic Survey for the Presence of Ribulose-1,5-Bisphosphate Carboxylase Activity in Guard Cells. Plant Physiology, 70, 1218-1220.

Park, S.-Y., Fung, P., Nishimura, N., Jensen, D.R., Fujii, H., Zhao, Y., Lumba, S., Santiago, J., Rodrigues, A., Chow, T.-f.F., Alfred, S.E., Bonetta, D., Finkelstein, R., Provart, N.J., Desveaux, D., Rodriguez, P.L., McCourt, P., Zhu, J.-K., Schroeder, J.I., Volkman, B.F. and Cutler, S.R. (2009) Abscisic Acid Inhibits Type 2C Protein Phosphatases via the PYR/PYL Family of START Proteins. Science, 324, 1068-1071.

Penfield, S., Clements, S., Bailey, K.J., Gilday, A.D., Leegood, R.C., Gray, J.E. and Graham, I.A. (2012) Expression and manipulation of phosphoenolpyruvate carboxykinase 1 identifies a role for malate metabolism in stomatal closure. Plant J, 69, 679-688.

180

Pham, J. and Desikan, R. (2009) ROS Signalling in Stomata. 55-71.

Pharmawati, M., Billington, T. and Gehring, C.A. (1998) Stomatal guard cell responses to kinetin and natriuretic peptides are cGMP-dependent. Cellular and molecular life sciences : CMLS, 54, 272-276.

Pluskal, T., Castillo, S., Villar-Briones, A. and Oresic, M. (2010) MZmine 2: modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data. BMC Bioinformatics, 11, 395.

Post-Beittenmiller, D. (1996) Biochemistry and molecular biology of wax production in plants. Annual Review of Plant Physiology and Plant Molecular Biology, 47, 405- 430.

Post-Beittenmiller, D. (1998) The cloned Eceriferum genes of Arabidopsis and the corresponding Glossy genes in maize. Plant Physiology and Biochemistry, 36, 157-166.

R Development Core Team (2015) R: A Language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.

Raghavendra, A.S. and Vani, T. (1989) Respiration in guard cells, pattern and possible role in stomatal function. Journal of Plant Physiology, 135, 3-8.

Reckmann, U., Scheibe, R. and Raschke, K. (1990) Rubisco Activity in Guard Cells Compared with the Solute Requirement for Stomatal Opening. Plant Physiology, 92, 246-253.

Sage, R.F. (1990) A Model Describing the Regulation of Ribulose-1,5-Bisphosphate Carboxylase, Electron Transport, and Triose Phosphate Use in Response to Light Intensity and CO(2) in C(3) Plants. Plant Physiology, 94, 1728-1734.

Sakaki, T., Satoh, A., Tanaka, K., Omasa, K. and Shimazaki, K.-I. (1995) Lipids and fatty acids in guard-cell protoplasts from Vicia faba leaves. Phytochemistry, 40, 1065-1070.

Sato, A., Sato, Y., Fukao, Y., Fujiwara, M., Umezawa, T., Shinozaki, K., Hibi, T., Taniguchi, M., Miyake, H., Goto, Derek B. and Uozumi, N. (2009) Threonine at position 306 of the KAT1 potassium channel is essential for channel activity and is a target site for ABA-activated SnRK2/OST1/SnRK2.6 protein kinase. Biochem J, 424, 439-448.

Scheibe, R., Reckmann, U., Hedrich, R. and Raschke, K. (1990) Malate Dehydrogenases in Guard Cells of Pisum sativum. Plant Physiology, 93, 1358- 1364.

181

Schnabl, H., WeissenbÖCk, G. and Scharf, H. (1986) In vivo-microspectrophotometric characterization of flavonol glycosides in Vicia faba guard and epidermal cells. Journal of Experimental Botany, 37, 61-72.

Schwartz, A., Ilan, N. and Grantz, D.A. (1988) Calcium effects on stomatal movement in Commelina-Communis L. - use of EGTA to modulate stomatal response to light, KCl and CO2. Plant Physiology, 87, 583-587.

Sembdner, G. and Parthier, B. (1993) The Biochemistry and the Physiological and Molecular Actions of Jasmonates. Annual Review of Plant Physiology and Plant Molecular Biology, 44, 569-589.

She, X.P. and Song, X.G. (2006) Cytokinin- and auxin-induced stomatal opening is related to the change of nitric oxide levels in guard cells in broad bean. Physiologia Plantarum, 128, 569-579.

Shi, K., Li, X., Zhang, H., Zhang, G., Liu, Y., Zhou, Y., Xia, X., Chen, Z. and Yu, J. (2015) Guard cell hydrogen peroxide and nitric oxide mediate elevated CO2 - induced stomatal movement in tomato. New Phytologist, 208, 342-353.

Sirichandra, C., Davanture, M., Turk, B.E., Zivy, M., Valot, B., Leung, J. and Merlot, S. (2010) The Arabidopsis ABA-activated kinase OST1 phosphorylates the bZIP transcription factor ABF3 and creates a 14-3-3 binding dite involved in its turnover. PLoS ONE, 5, e13935.

Song, X.G., She, X.P., He, J.M., Huang, C. and Song, T.S. (2006) Cytokinin- and auxin- induced stomatal opening involves a decrease in levels of hydrogen peroxide in guard cells of Vicia faba. Funct Plant Biol, 33, 573-583.

Song, Y., Miao, Y. and Song, C.-P. (2014) Behind the scenes: the roles of reactive oxygen species in guard cells. New Phytologist, 201, 1121-1140.

Staswick, P.E., Su, W. and Howell, S.H. (1992) Methyl jasmonate inhibition of root growth and induction of a leaf protein are decreased in an Arabidopsis thaliana mutant. Proceedings of the National Academy of Sciences, 89, 6837-6840.

Stein, S.E. (1999) An integrated method for spectrum extraction and compound identification from gas chromatography/mass spectrometry data. Journal of the American Society for Mass Spectrometry, 10, 770-781.

Stenzel, I., Hause, B., Miersch, O., Kurz, T., Maucher, H., Weichert, H., Ziegler, J., Feussner, I. and Wasternack, C. (2003) Jasmonate biosynthesis and the allene oxide cyclase family of Arabidopsis thaliana. Plant Molecular Biology, 51, 895- 911.

Stitt, M. and Krapp, A. (1999a) The interaction between elevated carbon dioxide and nitrogen nutrition: the physiological and molecular background. Plant, Cell & Environment, 22, 583-621.

182

Stitt, M. and Krapp, A. (1999b) The interaction between elevated carbon dioxide and nitrogen nutrition: the physiological and molecular background. Plant Cell Environ., 22.

Storey JD, L.J.a.B.A. (2015) edge: Extraction of Differential Gene Expression.

Suhita, D., Raghavendra, A.S., Kwak, J.M. and Vavasseur, A. (2004) Cytoplasmic alkalization precedes reactive oxygen species production during methyl jasmonate and abscisic acid-induced stomatal closure. Plant Physiology, 134, 1536-1545.

Sun, Y., Guo, H., Zhu-Salzman, K. and Ge, F. (2013) Elevated CO2 increases the abundance of the peach aphid on Arabidopsis by reducing jasmonic acid defenses. Plant Science, 210, 128-140.

Sun, Z., Jin, X., Albert, R. and Assmann, S.M. (2014) Multi-level modeling of light- induced stomatal opening offers new insights into its regulation by drought. PLoS Computational Biology, 10, e1003930.

Svozil, J., Gruissem, W. and Baerenfaller, K. (2015) Proteasome targeting of proteins in Arabidopsis leaf mesophyll, epidermal and vascular tissues. Frontiers in Plant Science, 6, 376.

Talbott, L.D. and Zeiger, E. (1993) Sugar and organic acid accumulation in guard cells of Vicia Faba in response to red and blue light. Plant Physiology, 102, 1163- 1169.

Talbott, L.D. and Zeiger, E. (1998) The role of sucrose in guard cell osmoregulation. Journal of Experimental Botany, 49, 329-337.

Tang, H., Vasconcelos, A.C. and Berkowitz, G.A. (1996) Physical association of KAB1 with plant K+ channel alpha subunits. The Plant Cell, 8, 1545-1553.

Tarczynski, M.C. and Outlaw Jr, W.H. (1993) The Interactive Effects of pH, L-Malate, and Glucose-6-Phosphate on Guard-Cell Phosphoenolpyruvate Carboxylase. Plant Physiology, 103, 1189-1194.

Tian, W., Hou, C., Ren, Z., Pan, Y., Jia, J., Zhang, H., Bai, F., Zhang, P., Zhu, H., He, Y., Luo, S., Li, L. and Luan, S. (2015) A molecular pathway for CO2 response in Arabidopsis guard cells. Nature Communications, 6, 6057.

Tiwari, S.B., Hagen, G. and Guilfoyle, T.J. (2004) Aux/IAA Proteins Contain a Potent Transcriptional Repression Domain. The Plant Cell, 16, 533-543.

Tominaga, M., Kinoshita, T. and Shimazaki, K. (2001) Guard-cell chloroplasts provide ATP required for H+ pumping in the plasma membrane and stomatal opening. Plant and Cell Physiology, 42, 795-802.

183

Vaughan, M.M., Huffaker, A., Schmelz, E.A., Dafoe, N.J., Christensen, S., Sims, J., Martins, V.F., Swerbilow, J., Romero, M., Alborn, H.T., Allen, L.H. and Teal, P.E.A. (2014) Effects of elevated [CO2] on maize defence against mycotoxigenic Fusarium verticillioides. Plant Cell and Environment, 37, 2691-2706.

Wang, C., Hu, H., Qin, X., Zeise, B., Xu, D., Rappel, W.J., Boron, W.F. and Schroeder, J.I. (2016) Reconstitution of CO2 Regulation of SLAC1 Anion Channel and Function of CO2-Permeable PIP2;1 Aquaporin as CARBONIC ANHYDRASE4 Interactor. Plant Cell, 28, 568-582.

Wang, Y.Q., Feechan, A., Yun, B.W., Shafiei, R., Hofmann, A., Taylor, P., Xue, P., Yang, F.Q., Xie, Z.S., Pallas, J.A., Chu, C.C. and Loake, G.J. (2009) S- nitrosylation of AtSABP3 antagonizes the expression of plant immunity. J Biol Chem, 284, 2131-2137.

Watkins, J.M., Hechler, P.J. and Muday, G.K. (2014) Ethylene-induced flavonol accumulation in guard cells suppresses reactive oxygen species and moderates stomatal aperture. Plant Physiology, 164, 1707-1717.

Watson, B.S., Bedair, M.F., Urbanczyk-Wochniak, E., Huhman, D.V., Yang, D.S., Allen, S.N., Li, W., Tang, Y. and Sumner, L.W. (2015) Integrated metabolomics and transcriptomics reveal rnhanced specialized metabolism in Medicago truncatula root border cells. Plant Physiology, 167, 1699-1716.

Webb, A.A.R., McAinsh, M.R., Mansfield, T.A. and Hetherington, A.M. (1996) Carbon dioxide induces increases in guard cell cytosolic free calcium. The Plant Journal, 9, 297-304.

Weissenbock, G., Schnabl, H., Sachs, G., Elbert, C. and Heller, F.O. (1984) Flavonol content of guard-cell and mesophyll cell protoplasts isolated from Vicia faba Leaves. Physiologia Plantarum, 62, 356-362.

Wickham, H. (2009) ggplot2: elegant graphics for data analysis: Springer New York.

Wildermuth, M.C., Dewdney, J., Wu, G. and Ausubel, F.M. (2001) Isochorismate synthase is required to synthesize salicylic acid for plant defence. Nature, 414, 562-565.

Willmer, C., Kanai, R., Pallas, J.E., Jr. and Black, C.C., Jr. (1973b) Detection of high levels of phosphoenolpyruvate carboxylase in leaf epidermal tissue and its significance in stomatal movements. Life sciences. Pt. 2: Biochemistry, general and molecular biology, 12, 155-159.

Willmer, C.M. and Dittrich, P. (1974) Carbon dioxide fixation by epidermal and mesophyll tissues of Tulipa and Commelina. Planta, 117, 123-132.

184

Willmer, C.M., Don, R. and Parker, W. (1978) Levels of short-chain fatty acids and of abscisic acid in water-stressed and non-stressed leaves and their effects on stomata in epidermal strips and excised leaves. Planta, 139, 281-287.

Willmer, C.M., Grammatikopoulos, G., LascÈve, G. and Vavasseur, A. (1995) Characterization of the vacuolar-type H+-ATPase from guard cell protoplasts of Commelina. Journal of Experimental Botany, 46, 383-389.

Willmer, C.M., Pallas, J.E. and Black, C.C. (1973a) Carbon Dioxide Metabolism in Leaf Epidermal Tissue. Plant Physiology, 52, 448-452.

Woodward, F.I. (1987) Stomatal numbers are sensitive to increases in CO2 from pre- industrial levels. Nature, 327, 617-618.

Wu, F.H., Shen, S.C., Lee, L.Y., Lee, S.H., Chan, M.T. and Lin, C.S. (2009) Tape- Arabidopsis sandwich - a simpler Arabidopsis protoplast isolation method. Plant Methods, 5, 16.

Wu, S., Huang, A., Zhang, B., Huan, L., Zhao, P., Lin, A. and Wang, G. (2015) Enzyme activity highlights the importance of the oxidative pentose phosphate pathway in lipid accumulation and growth of Phaeodactylum tricornutum under CO2 concentration. Biotechnology for Biofuels, 8, 1-11.

Xia, J., Sinelnikov, I.V., Han, B. and Wishart, D.S. (2015) MetaboAnalyst 3.0-making metabolomics more meaningful. Nucleic Acids Research, 43, W251-257.

Xia, X.-J., Gao, C.-J., Song, L.-X., Zhou, Y.-H., Shi, K.A.I. and Yu, J.-Q. (2014a) Role of H2O2 dynamics in brassinosteroid-induced stomatal closure and opening in Solanum lycopersicum. Plant, Cell & Environment, 37, 2036-2050.

Xia, X.J., Gao, C.J., Song, L.X., Zhou, Y.H., Shi, K. and Yu, J.Q. (2014b) Role of H2O2 dynamics in brassinosteroid-induced stomatal closure and opening in Solanum lycopersicum. Plant Cell and Environment, 37, 2036-2050.

Xie, D.X., Feys, B.F., James, S., Nieto-Rostro, M. and Turner, J.G. (1998) COI1: An Arabidopsis gene required for jasmonate-regulated defense and fertility. Science, 280, 1091-1094.

Xu, H.L., Shida, A., Futatsuya, F. and Kumura, A. (1994a) Effects of Epibrassinolide and Abscisic-Acid on Sorghum Plants Growing under Soil-Water Deficit .1. Effects on Growth and Survival. Jpn J Crop Sci, 63, 671-675.

Xu, H.L., Shida, A., Futatsuya, F. and Kumura, A. (1994b) Effects of Epibrassinolide and Abscisic-Acid on Sorghum Plants Growing under Soil-Water Deficit .2. Physiological-Basis for Drought Resistance Induced by Exogenous Epibrassinolide and Abscisic-Acid. Jpn J Crop Sci, 63, 676-681.

185

Xue, S., Hu, H., Ries, A., Merilo, E., Kollist, H. and Schroeder, J.I. (2011) Central functions of bicarbonate in S-type anion channel activation and OST1 protein kinase in CO2 signal transduction in guard cell. EMBO J, 30, 1645-1658.

Yan, H., Yoo, M.J., Koh, J., Liu, L., Chen, Y., Acikgoz, D., Wang, Q. and Chen, S. (2014) Molecular reprogramming of Arabidopsis in response to perturbation of jasmonate signaling. J Proteome Res, 13, 5751-5766.

Young, J.J., Mehta, S., Israelsson, M., Godoski, J., Grill, E. and Schroeder, J.I. (2006) 2+ CO2 signaling in guard cells: calcium sensitivity response modulation, a Ca - independent phase, and CO2 insensitivity of the gca2 mutant. Proc Natl Acad Sci USA, 103, 7506-7511.

Youngsook, L., Ho Joung, L., Crain, R.C., Lee, A. and Korn, S.J. (1994) Polyunsaturated fatty acids modulates stomatal aperture and two distinct K+ channel currents in guard cells. Cellular Signalling, 6, 181-186.

Zeiger, E. and Zhu, J.X. (1998) Role of zeaxanthin in blue light photoreception and the modulation of light-CO2 interactions in guard cells. Journal of Experimental Botany, 49, 433-442.

Zemel, E. and Gepstein, S. (1985) Immunological Evidence for the Presence of Ribulose Bisphosphate Carboxylase in Guard Cell Chloroplasts. Plant Physiology, 78, 586-590.

Zenser, N., Ellsmore, A., Leasure, C. and Callis, J. (2001) Auxin modulates the degradation rate of Aux/IAA proteins. Proceedings of the National Academy of Sciences, 98, 11795-11800.

Zhang, S., Li, X., Sun, Z., Shao, S., Hu, L., Ye, M., Zhou, Y., Xia, X., Yu, J. and Shi, K. (2015) Antagonism between phytohormone signalling underlies the variation in disease susceptibility of tomato plants under elevated CO2. Journal of Experimental Botany, 66, 1951-1963.

Zhang, S.Q., Outlaw, W.H. and Chollet, R. (1994) Lessened malate inhibition of guard- cell phosphoenolpyruvate carboxylase velocity during stomatal opening. FEBS Letters, 352, 45-48.

Zhang, W., Nilson, S.E. and Assmann, S.M. (2008) Isolation and whole-cell patch clamping of Arabidopsis guard cell protoplasts. Cold Spring Harbor Protocols, 2008, pdb prot5014.

Zhang, Y., Zhu, H., Zhang, Q., Li, M., Yan, M., Wang, R., Wang, L., Welti, R., Zhang, W. and Wang, X. (2009) Phospholipase Dα1 and Phosphatidic Acid Regulate NADPH Oxidase Activity and Production of Reactive Oxygen Species in ABA- Mediated Stomatal Closure in Arabidopsis. The Plant Cell, 21, 2357-2377.

186

Zheng, X.Y., Spivey, N.W., Zeng, W.Q., Liu, P.P., Fu, Z.Q., Klessig, D.F., He, S.Y. and Dong, X.N. (2012) Coronatine promotes Pseudomonas syringae virulence in plants by activating a signaling cascade that inhibits salicylic acid accumulation. Cell Host Microbe, 11, 587-596.

Zhu, J., Talbott, L.D., Jin, X. and Zeiger, E. (1998) The stomatal response to CO2 is linked to changes in guard cell zeaxanthin. Plant Cell and Environment, 21, 813- 820.

Zhu, M., Dai, S., Zhu, N., Booy, A., Simons, B., Yi, S. and Chen, S. (2012) Methyl jasmonate responsive proteins in Brassica napus guard cells revealed by iTRAQ- based quantitative proteomics. Journal of Proteome Research, 11, 3728-3742.

Zhu, M., Jeon, B.W., Geng, S., Yu, Y., Balmant, K., Chen, S. and Assmann, S.M. (2016) Preparation of epidermal peels and guard cell protoplasts for cellular, electrophysiological, and -omics assays of guard cell function. In Plant Signal Transduction: Methods and Protocols (Botella, J.R. and Botella, M.A. eds), pp. 89-121.

Zhu, M., Simons, B., Zhu, N., Oppenheimer, D.G. and Chen, S. (2010) Analysis of abscisic acid responsive proteins in Brassica napus guard cells by multiplexed isobaric tagging. Journal of Proteomics, 73, 790-805.

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BIOGRAPHICAL SKETCH

Sisi Geng was born in 1989 in Jiangsu Province, China. She was admitted to

China Agricultural University in Beijing, China in August 2007 for her undergrad study, majoring in biochemistry and molecular biology. From May 2009 to July 2011, she did her undergraduate thesis research in Dr. Xingwang Deng’s lab in Peking University,

Beijing, China. She worked on the constructing and expressing CONSTANS (CO) antigen expression and antiserum preparation for in vivo detection of CO. Upon graduation in July 2011, She was admitted to the Plant Molecular and Cellular Biology

(PMCB) graduate program at University of Florida, Gainesville, Florida, USA. She joined

Drs. Sixue Chen, Kevin Folta and Kenneth Cline’s laboratories for three 10-week rotations, respectively. Since May, 2012, she has worked in Dr. Sixue Chen’s lab for her

Ph.D. research project focusing on characterization of the CO2 responsive metabolomes in stomatal guard cells. Sisi Geng received her Ph.D. from University of

Florida in the summer of 2016.

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