Open Access

High-level expression of sugar inducible gene2 (HSI2) is a negative regulator of drought stress tolerance in Arabidopsis

  • Nirmala Sharma1,
  • Yarnel Bender1,
  • Kerry Boyle1 and
  • Pierre R Fobert1Email author
BMC Plant Biology201313:170

https://doi.org/10.1186/1471-2229-13-170

Received: 23 November 2012

Accepted: 2 October 2013

Published: 29 October 2013

Abstract

Background

HIGH-LEVEL EXPRESSION OF SUGAR INDUCIBLE GENE2 (HSI2), also known as VAL1, is a B3 domain transcriptional repressor that acts redundantly with its closest relative, HSI2-LIKE1 (HSL1), to suppress the seed maturation program following germination. Mutant hsi2 hsl1 seedlings are arrested early in development and differentially express a number of abiotic stress-related genes. To test the potential requirement for HSI2 during abiotic stress, hsi2 single mutants and plants overexpressing HSI2 were subjected to simulated drought stress by withholding watering, and characterized through physiological, metabolic and gene expression studies.

Results

The hsi2 mutants demonstrated reduced wilting and maintained higher relative water content than wild-type after withholding watering, while the overexpressing lines displayed the opposite phenotype. The hsi2 mutant displayed lower constitutive and ABA-induced stomatal conductance than wild-type and accumulated lower levels of ABA metabolites and several osmolytes and osmoprotectants following water withdrawal. Microarray comparisons between wild-type and the hsi2 mutant revealed that steady-state levels of numerous stress-induced genes were up-regulated in the mutant in the absence of stress but down-regulated at visible wilting. Plants with altered levels of HSI2 responded to exogenous application of ABA and a long-lived ABA analog, but the hsi2 mutant did not show altered expression of several ABA-responsive or ABA signalling genes 4 hr after application.

Conclusions

These results implicate HSI2 as a negative regulator of drought stress response in Arabidopsis, acting, at least in part, by regulating transpirational water loss. Metabolic and global transcript profiling comparisons of the hsi2 mutant and wild-type plants do not support a model whereby the greater drought tolerance observed in the hsi2 mutant is conferred by the accumulation of known osmolytes and osmoprotectants. Instead, data are consistent with mutants experiencing a relatively milder dehydration stress following water withdrawal.

Keywords

Abiotic stress Abscisic acid Gene expression Microarray Transcriptome Water stress

Background

Water deficit is a major environmental factor limiting plant fitness and productivity [1]. With patterns of global climate change likely to increase the severity of drought stresses in the future [2], the development of crop plants better adapted to water-limited environments is a priority for sustainable agriculture.

Plants have evolved unique mechanisms to monitor water availability in their environment and adapt to it [3, 4]. In response to mild water deficits, low cellular water potential can be avoided by balancing water uptake and loss through stomatal closure, increased cuticle thickness and enhanced root growth. Should these adaptations be insufficient to restore physiological water potential within the cell, more dramatic measures may be deployed. These are generally distinguished as dehydration avoidance, dehydration tolerance and drought escape [3], although all three responses are highly integrated [5]. A key aspect of dehydration avoidance is the accumulation of compatible solutes (osmolytes), including sugars, sugar alcohols, amino acids and organic acids, that increase cellular osmotic potential, prevent water loss and maintain turgor [6]. Dehydration tolerance consists of measures to protect cell constituents from damage and entails the production of antioxidants and chaperones, such as dehydrins and late-embryogenesis abundant (LEA) proteins [7].

The plant hormone abscisic acid (ABA) plays a pivotal role in coordinating multiple aspects of adaptation to drought stress [8]. Stomatal closure, the accumulation of osmolytes and the synthesis of protective proteins are all correlated with drought-induced increases in endogenous ABA levels. Mutants defective in ABA synthesis or perception are more susceptible to drought, while treatment with exogenous ABA enhances drought tolerance and induces the expression of numerous dehydration-stress responsive genes and proteins. However, several dehydration stress-induced genes do not respond to exogenous application of ABA in Arabidopsis thaliana (L.) [9, 10], suggesting the existence of both ABA-dependent and -independent signal transduction pathways.

Physiological and biochemical aspects of drought adaptation are underpinned by extensive transcriptional re-programming [9]. Drought-induced transcriptomes from several plant species have been reported (reviewed in [11]) and reveal profound changes in numerous processes, including growth, amino acid and carbohydrate metabolism, photosynthesis, protection against oxidative stress, phosphorylation, membrane transport, secretion, cell wall expansion, and hormone homeostasis [10, 1215]. Functional characterization efforts have identified the role of a number of drought-induced transcripts, including many transcription factors, in driving adaptive responses [10, 1618]. Differential gene expression in response to abiotic stress is likely associated with changes in chromatin conformation, such as those mediated by histone tail modifications and chromatin remodeling complexes [19, 20]. Identification and characterization of the factors and mechanisms involved is only now being elucidated and an active area of research.

One group of proteins that may be implicated in regulating plant chromatin conformation is the HIGH-LEVEL EXPRESSION OF SUGAR-INDUCIBLE GENE2 (HSI2) clade of B3 domain proteins. The B3 domain is a plant-specific basic DNA-binding domain originally identified as the third and C-terminus proximal basic domain of the transcription factor ABSICIC ACID INSENSITIVE3 (ABI3) (reviewed in [21]). There are three members of the HSI2 clade in Arabidopsis; HSI2, also known as the VIVIPAROUS ABI3-LIKE1 (VAL1), HSI2-LIKE1 (HSL1, also known as VAL2) and HSI2-LIKE2 (HSL2, also known as VAL3) [2224]. Additional features shared by HSI2 clade proteins include the CW domain and EAR motif. HSI2 and HSL1 also contain a putative plant homeodomain (PHD)-like zinc finger domain absent from HSL2. The CW and PHD-like domains are associated with chromatin remodelling factors, while the EAR motif is a transcriptional repression domain. Functional analysis of HSI2 has demonstrated that the protein is a potent EAR-dependent transcriptional repressor [23] and can repress ABI3-mediated transactivation from the Sph/RY element, the cognate DNA binding site of B3 domain factors [25]. Loss-of-function mutations in HSI2 result in the expression of seed storage proteins in vegetative tissues [23, 24]. The deregulation of embryonic and seed maturation programs in vegetative tissues is more dramatic in hsi2 hsl1 (val1 val2) double mutants, which produce callus and ectopic embryo-like structures when seedlings are cultured in the presence of sucrose. Among genes highly expressed in the double mutant seedlings are ABI3, FUSCA3 (FUS3) and LEAFY COTYLEDON2 (LEC2), which encode key regulators of seed maturation and constitute the AFL (ABI3/FUS3/LEC2) clade of B3 domain proteins. It has been proposed that HSI2 clade proteins suppress the seed maturation program following germination by repressing the transcription of AFL clade genes and/or competing with the encoded transcription factors for Sph/RY sites in the promoter of target genes [22, 24, 25].

The recent analysis of the hsi2-4 allele, which creates a cysteine to tyrosine substitution in the PHD domain, revealed a potential role for this HSI2 domain in the repression of a subset of seed-specific genes during seedling development and in the deposition of the repressive chromatin mark H3K27m3 on target genes [26]. Interestingly, hsi2-4 hsl double mutants were morphologically normal, indicating a unique function for the HSI2 PHD domain.

Molecular genetic analysis of the HSI2 clade has focused on hsi2 hsl1 double mutants at the seedling stage. The potential role of these factors at other times in the plant life cycle remains largely unexplored, despite the fact that HSI2 and HSL1 are expressed in many tissues [23]. A cursory analysis of gene ontology (GO) annotation terms enriched in the list of genes differentially expressed in hsi2 and hsi2 hsl1 mutants [24, 26] identified response to abiotic stimulus as highly significant (data not shown). This prompted us to test whether HSI2 might regulate drought tolerance during the vegetative stage of the plant life cycle. Through loss- and gain-of-function analyses, HSI2 is shown to act as a negative regulator of drought tolerance in Arabidopsis, possibly through a mechanism involving reduced transpirational water loss.

Results

To investigate the role of HSI2 in modulating drought responses, the levels and/or integrity of the gene were stably altered in transgenic Arabidopsis plants. For loss-of-function analysis, two T-DNA insertion alleles were identified (Figure 1A). Both mutant alleles show minimal expression of HSI2 when compared to corresponding wild-types, Col-0 for hsi2-2 and Col-2 for hsi2-5 (Figure 1B). For gain-of-function analysis, the HSI2 coding region was placed under the control of the Cauliflower mosaic virus 35S promoter (35S:HSI2) and used to generate transgenic plants in Col-0 (Figure 1C). Three independent lines showing increased levels of HSI2 transcripts (Figure 1D, OEx lines) were further studied.
Figure 1

HSI2 insertional mutants and overexpressing lines. (A) Diagram of the structure of the HSI2 gene (At2g30470) showing the position of T-DNA insertions (triangles). Open boxes indicate exons, while black boxes indicate untranslated regions. The transcriptional start site is indicated by the number 1. With the exception of T-DNA sizes, the diagram is drawn to scale. (B) Kinetic RT-PCR analysis of HSI2 mRNA abundance in the mutants and corresponding wild-types (hsi2-2/Col-0 and hsi2-5/Col-2). (C) Diagram of the structure of the HSI2 transgene. Open boxes indicate exons; 35S, Cauliflower mosaic virus 35S promoter; nosT, terminator region from the Agrobacterium tumefaciens nopaline synthase gene. (D) Kinetic RT-PCR analysis of HSI2 mRNA abundance in transgenic plants and untransformed Col-0. (E) Kinetic RT-PCR analysis of HSI2 mRNA abundance in 14 day old seedlings of hsi2-2 and Col-0, 4 h following treatment with 25 μM PBI425 or 20% PEG 8000. (F) Kinetic RT-PCR analysis of HSI2 mRNA abundance in 3-week-old leaves of hsi2-2 and Col-0 grown in soil saturated to field capacity or following watering withdrawal and development of visible wilting symptoms. For (F), amplification of the housekeeping gene encoding polypyrimidine tract-binding protein1 (PTB1, AT3G01150) was used as control to normalize expression data. All values represent the averages of three biological replicates, each analyzed three times (technical replicates) ± standard error.

Disruption of HSI2by T-DNA insertions confers better drought tolerance

The response of hsi2 mutants to drought was examined by subjecting plants to a simulated drought stress regime in environmentally controlled growth chambers. To minimize sources of variation attributed to the amount, and the initial moisture content, of the soil in pots, wild-type and corresponding mutant plants were grown side-by-side in the same containers. Both hsi2 mutants displayed reduced rates of wilting after withholding water, by as much as 9%, compared to their wild-type counterparts (Figure 2A). The hsi2 mutants also maintained higher cellular water levels, by as much as 30%, measured as leaf relative water content (RWC; Figure 2B). Additional experiments using different pot sizes and potting mixes yielded similar findings (data not shown). These results indicate that hsi2 mutants have increased tolerance to drought, due at least in part to a reduced rate of water loss from leaves.
Figure 2

Response of hsi2 mutants and 35S:HSI2 overexpressing lines to simulated drought stress. (A) Wilting rates of hsi2 mutants and corresponding wild-types. (B) Leaf relative water content of the hsi2 mutants and corresponding wild-types. (C) Rate of wilting of three independent 35S:HSI2 lines and untransformed wild-type (Col-0). (D) Recovery from drought 24 h upon re-watering. (E) A representative photograph showing the recovery phenotype of Col-0 and 35S:HSI2 line OEx1. For (A) and (B), the hsi2-2 mutant compares with Col-0 and hsi2-5 compares with Col-2; each wild-type and mutant combination were planted in the same sets of containers. Statistical significance, indicated by an asterisk(*), was determined by a paired Student’s t-test (p ≤ 0.05). Data are presented as means of three replicates containing 12 plants each ± standard error of means. In some cases where the standard errors are very small, the graph symbols may obscure the bars. Experiments were repeated at least three times with similar results.

HSI2overexpression enhances drought sensitivity

The three independent OEx lines evaluated showed an early onset and greater severity of visual wilting, and poorer recovery from a drought stress compared to untransformed controls (Figure 2C-E). Differences in visible wilting were most pronounced at 6 and 7 days after withholding water, with OEx lines displaying between 48-60% and 35-45% higher wilting rates, respectively (Figure 2C). When plants were re-watered at the end of the drought period and allowed to recover for 24 h, 66% of the wild-type plants recovered compared to 16, 24, and 44% in the OEx lines (Figure 2D, 2E). Together with data obtained from loss-of-function mutants, the results implicate HSI2 as a negative regulator of drought tolerance.

HSI2altered plants respond to an exogenously applied ABA

To study the possible interaction between HSI2 and ABA during drought stress, we assessed the drought response of the hsi2-2 mutant and line OEx1 pre-treated with (+)-ABA and (+)-8’-acetylene ABA, also known as PBI425 [27]. This synthetic analog is resistant to 8’hydroxylation, the principal ABA catabolic pathway in Arabidopsis[12, 28]. Consequently, PBI425 is more persistent in planta and has stronger hormonal activity [29, 30]. The ability of PBI425 to enhance drought tolerance in Arabidopsis has been shown to be mediated through ABA signalling [29]. Whether PBI425 and ABA act through the same signaling pathway can be tested by binding to the family of PYL receptors. Nevertheless, available information indicate that PBI425 offers several advantages over natural ABA when the sustained presence of hormonal activity is required, as is the case in this study.

In control treatments where plants were root-drenched with water prior to water withdrawal, hsi2-2 plants displayed less wilting, and OEx1 plants more wilting, than the wild-type at all observation times (Figure 3A and 3B). When plants were given a root-drench treatment with ABA (30 μM) or PBI425 (20 μM) before withholding water, the onset of visible wilting was delayed in all genotypes by three to four days (until 7 – 10 days after treatment), after which the mutant continued to display less wilting, and OEx1 more wilting, than the wild-type at all observation times (Figure 3A and 3B). Recovery from wilting upon re-watering was evaluated under control and ABA analog treatments, where the hsi2-2 mutant recovered the best upon re-watering, followed by the wild-type and OEx1 plants (Figure 3C). However, the overall recovery upon re-watering was lower in all genotypes pre-treated with PBI425.
Figure 3

Response of hsi2 mutants and 35S:HSI2 overexpressing lines to simulated drought stress. (A-B) Rate of wilting of wild-type (Col-0), mutant (hsi2-2), and 35S:HSI2 line (OEx1) treated with (+)-ABA (A) or the ABA analog PBI425 (B). (C) Recovery from drought upon re-watering (at 24 h after re-watering under control and PBI425 treatments). Three-week-old plants were root drenched with 0.05% ethanol as control treatment (left side), 30 μM ABA or 20 μM PBI425, dissolved in 0.05% ethanol (right side) to field capacity and watering was stopped thereafter. Data are presented as means of three replicates of 18 plants each ± standard error of means. In some cases where the standard errors are very small, the graph symbols may obscure the bars. These experiments were repeated at least twice with similar results.

Hsi2-2mutants display lower stomatal conductance

Lower stomatal conductance has been associated with higher drought tolerance in many plant species including Arabidopsis[31, 32]. Accordingly, stomatal conductance was measured to investigate possible mechanisms underpinning the increased drought tolerance in the hsi2 mutant. Leaf stomatal conductance in well-watered hsi2-2 plants was 77% of wild-type values (Figure 4A), suggesting lower constitutive stomatal conductance. Pre-treatment with PBI425 resulted in a 2.4-fold reduction in stomatal conductance in the wild-type and a 4.4-fold reduction in hsi2-2 (Figure 4B), with the hsi2-2 mutant displaying 42% of wild-type stomatal conductance following pre-treatment with PBI425 (Figure 4B). These results suggest that the mutant is able to better maintain water status through regulation of stomatal properties and that loss of HSI2 does not substantially affect associated ABA signaling.
Figure 4

Stomatal conductance in the hsi2-2 mutant and corresponding wild-type (Col-0). Stomatal conductance was measured in fully developed young leaves (A) 1 d after watering or (B) 72 h after root drench treatment with 0 or 20 μM PBI425 (in 0.05% ethanol). Data presented as means of three replicates ± standard error of means, each containing 4–6 plants and measurements from two leaves per plant. The experiments were repeated twice with similar results.

The hsi2-2mutant accumulates less ABA metabolites during drought stress

To examine the involvement of HSI2 in ABA metabolism during the drought response, levels of endogenous ABA and its metabolites were measured in leaves of hsi2-2, OEx1, and Col-0 before drought stress, at visible wilting, and upon rehydration. In the absence of drought, levels of all metabolites were similar in the three genotypes (Figure 5). Endogenous ABA content increased dramatically under drought stress in all three genotypes, and reverted to near pre-stress levels upon re-watering. However, hsi2-2 accumulated relatively lower levels of ABA during drought and was better able to recover to original levels after re-watering compared to OEx1 or Col-0. Levels of ABA metabolites, namely ABA-glucose ester (ABA-GE), dihydrophaseic acid (DPA), phaseic acid (PA), and trans-ABA (t-ABA) also increased substantially under drought stress in all genotypes (Figure 5). The hsi2-2 mutant accumulated less of these metabolites than Col-0, while OEx1 contained levels comparable to Col-0, with the exception of t-ABA, which was lower in 35S:HSI2. Consistent with the reports that the 8’-hydroxylation pathway is the most important ABA catabolic pathway in Arabidopsis[12, 28], the products of this pathway (PA and DPA), were the most abundant during drought stress and after rehydration (Figure 5). Unlike ABA, the levels of most metabolites remained much higher after rehydration than they were pre-drought, with DPA levels remaining as high as during drought stress. These results indicate that drought-induced ABA biosynthesis and catabolism is of smaller amplitude in the mutant line, resulting in a more modest increase in both ABA and ABA metabolites, while rehydration reversed the effect of drought on ABA biosynthesis but not ABA catabolism.
Figure 5

Levels of ABA and its metabolites in leaves of HSI2 altered Arabidopsis plants. Levels were quantified by UPLC-ESI-MS/MS using deuterium-labeled internal standards. Each sample consisted of a pool of 6 plants grown under well-watered (to near field capacity) or drought-stressed (visible wilting) conditions, and 24 h after re-watering to soil saturation following drought stress. Values represent averages of three biological replicates ± standard error of means. No error bars are provided in the Total ABA panel. DPA, dihydrophaseic acid; ABAGE, ABA glucose ester; 7’-OH ABA; PA, phaseic acid; t-ABA, trans-ABA, OEx1, 35S:HSI2 line.

The hsi2-2mutant accumulates lower levels of stress-induced metabolites during drought stress

To ascertain the role of HSI2 during stress-induced metabolic reprogramming, levels of several compounds were measured by undirected metabolic profiling and compared between hsi2-2 and Col-0 before drought stress, at visible wilting, and upon rehydration. Overall, drought treatment increased levels of numerous metabolites previously reported to be drought-inducible [33], including soluble sugars, sugar alcohols, amino acids, organic acids and antioxidants (Figure 6; Additional file 1). Levels of several metabolites were also depleted under drought conditions. With some exceptions, most metabolites reverted closer to non-stress levels upon rehydration.
Figure 6

Drought-related levels of selected metabolites showing significant changes in leaves of the hsi2-2 mutant . Each sample consisted of a minimum of 6 plants grown under well-watered (to near field capacity) or drought-stressed (visible wilting) conditions, and 24 h after re-watering to soil saturation following drought stress. Values represent averages of three biological replicates ± standard error. Treatments statistically different by ANOVA (p ≤ 0.05) are marked by asterisks.

Relatively few of the stress-regulated metabolites were found to accumulate differentially in the two genotypes tested (Figure 6; Additional file 1). These included sugars (fructose and glucose), amino acids (proline, tryptophan and aspartate), and the sugar alcohol ribitol, levels of which were lower in the mutant than the wild-type under drought stress. Similarly, the products of the lysine degradation pathway, N6-acetyllysine, 2-aminoadipate and pipecolate, which have been shown to accumulate under osmotic stress in Brassica napus[34] and suggested to have osmoprotectant properties in bacteria (pipecolate [35]) were also lower in the mutant compared to wild-type under drought conditions. In contrast, hsi2-2 had significantly higher levels of ferulate, an intermediate of the phenylpropanoid pathway, before and during drought (Figure 6). Lower levels of known stress-induced osmolytes and osmoprotectants in the hsi2 mutant at wilting are consistent with plants experiencing relatively milder dehydration stress than the wild-type.

Analysis of drought transcriptomes indicates that drought-induced genes are down-regulated in the hsi2mutant

To characterize the consequences of loss of HSI2 function on gene expression relevant to drought stress, genome-wide expression analysis was undertaken with the hsi2-2 mutant under a normal watering regime (no stress; stage 0) and after withholding watering, before the onset of visible wilting (stage 1) and at visible wilting (stage 2). Gene expression in the mutant was compared with its wild-type (Col-0) under each watering regime by co-hybridization using dual color microarrays. Genes corresponding to 441 unique AGIs were identified as being differentially expressed (p ≤ 0.05, 1.5-fold cut-off) at stage 0, and the numbers of differentially expressed unique AGIs increased with the severity of drought to 785 (stage 1) and 1400 (stage 2) (Additional files 2 and 3). Consistent with differences in drought responses observed between the mutant and wild-type (Figures 2, 3, 4), the most significant GO enriched terms for biological process identified in lists of differentially expressed genes were response to stress and response to biotic or abiotic stimulus (Table 1). The relative p-values for these terms decreased with the severity of the drought treatment. The identity of genes differentially regulated under the three watering regimes changed considerably. Of the 441 genes differentially expressed at stage 0, 335 (76%) are specific to this stage and only 48 genes were differentially regulated under all watering regimes. For representative genes, microarray results were validated by kinetic reverse-transcriptase PCR (k-RT-PCR) (Figure 7).
Table 1

Gene Ontology classification terms enriched in the hsi2-2 mutant compared to Col-0 under different simulated drought regimes

  

Stage 0

  

Stage 1

  

Stage 2

 
 

Genes

Enrich.

p-value

Genes

Enrich.

p-value

Genes

Enrich.

p-value

Biological Process

unknown biological processes

160

9.3

1.18E-04

260

12.5

2.67E-11

456

16.9

4.61E-21

other cellular processes

140

9.7

0.029

261

12.8

4.01E-03

480

16.5

5.74E-05

other metabolic processes

138

10.4

0.015

269

13.1

2.93E-05

477

18.3

2.82E-07

protein metabolism

47

6.7

0.042

80

8.6

0.013

161

11.9

0.028

response to stress

40

6.3

9.20E-04

72

8.8

1.48E-05

125

9.1

1.11E-07

developmental processes

31

5

0.013

53

6.6

5.39E-03

86

9

7.36E-03

transcription

31

5.3

0.019

52

6.1

0.013

78

8.4

0.04

transport

28

5.2

0.051

64

8.1

2.31E-04

105

8.8

1.20E-04

response to abiotic or biotic stimulus

26

5.3

0.055

61

8.3

1.68E-04

114

9.5

8.32E-08

signal transduction

25

4.9

3.77E-03

35

5.2

0.018

65

7.7

1.96E-03

other biological processes

23

4.2

0.082

58

7.1

5.15E-04

101

10.9

2.92E-05

cell organization and biogenesis

15

3.6

0.091

22

5.2

0.022

56

7

0.054

electron transport or energy pathways

4

1.7

0.197

5

2.2

0.118

11

2.9

0.103

DNA or RNA metabolism

1

0.8

0.05

8

2.8

0.142

21

4

0.02

Molecular Function

unknown molecular functions

135

8.9

9.60E-06

231

11.5

1.23E-10

404

17

7.56E-20

other binding

76

7.5

3.20E-03

123

9.5

6.42E-03

192

11.9

0.03

other enzyme activity

62

7.1

1.93E-03

120

10.5

1.56E-06

197

12.7

6.77E-07

transferase activity

45

6.4

6.53E-03

66

8.1

0.03

155

13.2

1.75E-07

hydrolase activity

37

5.6

0.053

81

8.3

7.09E-04

131

11.4

1.37E-03

protein binding

36

5.4

0.069

69

7.8

0.036

118

10.3

0.033

nucleotide binding

35

6.4

0.039

39

6

9.76E-03

106

9.4

0.015

transcription factor activity

29

5

0.03

59

6.6

7.33E-04

96

9.4

6.60E-04

kinase activity

25

4.9

0.022

35

5.8

0.059

89

8.3

9.94E-06

DNA or RNA binding

25

5

9.91E-03

50

6.5

8.44E-03

103

9.6

0.019

other molecular functions

24

4.8

0.05

36

6.7

0.067

68

8.7

0.038

transporter activity

16

3.5

0.101

51

6.6

5.99E-05

88

8.1

1.06E-06

nucleic acid binding

9

2.9

1.06E-03

15

3.9

6.61E-06

44

6.4

2.91E-04

receptor binding or activity

7

2.9

0.024

8

2.5

0.087

15

3.6

0.033

structural molecule activity

4

1.7

0.083

8

2.9

0.048

19

4

0.064

Cellular Component

unknown cellular components

164

10.4

0.013

268

12.9

2.12E-05

415

17

1.48E-19

other cellular components

79

8

1.22E-04

110

10.7

0.013

218

14.1

3.31E-05

other membranes

58

7.5

3.99E-03

83

8.4

0.017

189

10.8

1.20E-06

nucleus

35

5.4

0.07

72

7.6

0.058

119

9.9

0.023

other intracellular components

34

6.2

4.18E-04

84

8.5

0.035

191

11.6

0.013

other cytoplasmic components

32

5

0.024

66

7.6

0.037

143

10.5

0.017

chloroplast

28

4

4.61E-03

66

7.6

0.015

152

10.9

7.94E-03

plasma membrane

21

4.6

0.038

50

6.3

0.03

129

10.9

2.07E-06

cell wall

10

2.9

0.083

13

3.6

0.104

32

5

0.017

cytosol

10

3.6

0.127

19

4.4

9.12E-04

34

6

0.061

plastid

7

2.7

0.012

12

3.3

0.086

45

6.9

0.061

mitochondria

6

2.6

4.68E-03

19

4.3

0.112

46

6.1

0.06

extracellular

6

2.5

0.163

12

3.5

0.027

34

5.2

3.21E-04

ER

4

1.9

0.177

10

2.5

0.057

15

3.8

0.102

ribosome

2

1.1

0.035

7

3.4

0.119

18

3.9

0.084

Golgi apparatus

1

0.7

0.142

4

1.7

0.159

11

3.2

0.114

Enrichments were performed at http://bar.utoronto.ca/ntools/cgi-bin/ntools_classification_superviewer.cgi. Statistically significant values (p < 0.05) are in bold. Stage 0, watered to field capacity; Stage 1, dry soil, no visible wilting; Stage 2, visible wilting.

Figure 7

Kinetic RT-PCR validation of microarray analyses for a representative subset of genes. cDNA was synthesized from the areal portion of well watered plants (Stage 0) and at visible drought (Stage 2). Amplification of the housekeeping gene encoding polypyrimidine tract-binding protein1 (PTBpa, AT3G01150) was used as control to normalize PCR expression data. All values represent the averages of three biological replicates, each analyzed three times (technical replicates). Values from microarray expression are ratios of averaged, normalized fluorescent signals.

Genes differentially expressed in the hsi2 mutant were compared with those regulated in response to drought stress. Given the poor overlap of genes reported as being differentially expressed during drought stress in different studies (see [11, 12, 36]), genes regulated by drought in our datasets were identified by comparing probe intensity values from individual channels between stage 2 and stage 0 in Col-0. The direction of change for these genes in our datasets was overwhelmingly the same as those from published studies employing whole genome microarrays and similar drought regimes (Additional file 3).

Genes found to be induced in response to drought stress in our dataset (>2.5-fold) were predominantly down-regulated when differentially expressed in the hsi2 mutant (vs. Col-0) at stage 2 (>92%), while genes repressed by drought were mostly up-regulated (93%) when differentially expressed in the hsi2 mutant at this drought stage (Additional file 3). Similar patterns were observed when genes differentially expressed in hsi2 vs. Col-0 at stage 2 were compared to published lists of drought-regulated transcripts of Huang et al.[12] or the progressive drought (pDr) and ABA-induced genes of Harb et al. [14] (Additional file 3). Analysis of GO terms enriched in genes induced by drought and down-regulated in hsi2 vs. Col-0 at stage 2 identified predominantly drought-associated processes, including response to abiotic stimulus, ABA, and water deprivation (Table 2). These terms were not enriched in the gene list induced by drought and up-regulated in hsi2.
Table 2

Representative GO terms enriched in the hsi2-2 mutant versus Col-0 and regulated by drought stress

Description

GO term

Enrichment

p-value

Example

AGI

Induced by Drought and Down-regulated at Stage 2 ( hsi2 :Col-0)

P* response to abiotic stimulus

GO:0009628

2.03

5.27E-04

ABA receptor GCR2

At1g52920

P response to temperature stimulus

GO:0009266

3.51

3.41E-04

RAB18, RD29B

At5g66400; At5g52300

P response to light intensity

GO:0009642

8.51

5.27E-04

ZAT12

At5g59820

P response to water deprivation

GO:0009414

4.28

2.98E-03

RAB18, ANAC019

At5g66400; At1g52890

P response to abscisic acid stimulus

GO:0009737

3.51

1.18E-03

RAB18, RD29B

At5g66400; At5g52300

F* oxygen binding

GO:0019825

3.63

4.93E-04

CYP705A12, -15, -19

At5g42580; At3g20080; At3g20100

Induced by Drought and Up-regulated at Stage 2 ( hsi2 :Col-0)

P secondary metabolism

GO:0019748

5.48

6.12E-03

4-coumarate-CoA ligase 2

At3g21240

C* plasma membrane

GO:0005886

4.98

8.54E-03

LTP2

At2g38530

Repressed by Drought and Up-regulated at Stage 2 ( hsi2 :Col-0)

P steroid biosynthesis

GO:0006694

12.34

7.97E-03

DWARF 4

At3g50660

P carbohydrate metabolism

GO:0005975

2.22

4.50E-04

Glycosyl hydrolase 9C2, 9B8, and 17

At1g64390; At2g32990; At2g05790

P secondary metabolism

GO:0019748

2.3

9.31E-03

ESM1, CAD4

At3g14210; At3g19450

P carboxylic acid metabolism

GO:0019752

2.28

1.10E-03

LOX2

At3g45140

F water transporter activity

GO:0005372

9.73

1.52E-04

DELTA-TIP, PIP1

At3g16240; At3g61430

F carbon-oxygen lyase activity

GO:0016835

4.31

1.27E-03

α- and β-carbonic anhydrase 1

At3g52720; At3g01500

C endomembrane system

GO:0012505

1.53

1.55E-05

RKL1, LTP7

At1g48480; At2g15050

C plastid thylakoid

GO:0031976

3.18

1.57E-04

β-carbonic anhydrase 1

At3g01500

C anchored to membrane

GO:0031225

3.65

1.31E-04

TOO MANY MOUTHS

At1g80080

Repressed by drought and Down-regulated at Stage 2 ( hsi2 :Col-0)

P DNA metabolism

GO:0006259

6.94

7.51E-04

KRYPTONITE

At5g13960

F protein binding

GO:0005515

2.64

6.11E-03

Variant in methylation 4

At1g66040

Induced by Drought and Down-regulated at Stage 1 ( hsi2 :Col-0)

F electrochemical potential-driven transporter activity

GO:0015290

5.88

1.65E-03

GPT2, ZIFL2

At1g61800; At3g43790

Induced by Drought and Up-regulated at Stage 1 ( hsi2 :Col-0)

P nitrogen compound biosynthesis

GO:0044271

5.07

8.23E-03

GLN1.3

At3g17820

P response to chemical stimulus

GO:0042221

2.23

7.92E-03

FIBRILLIN

At4g04020

F oxidoreductase activity

GO:0016491

2.54

8.39E-04

FERREDOXIN3

At2g27510

F protein ser/thr phosphatase activity

GO:0004722

5.43

6.47E-03

PP2CA2

At1g30220

Repressed by Drought and Up-regulated at Stage 1 ( hsi2 :Col-0)

P cellular carbohydrate metabolism

GO:0044262

4.24

3.01E-03

Cellulose synthase-like B1

At2g32610

F hydrolase activity

GO:0016787

1.86

9.05E-03

Methyl IAA esterase

At5g58310

Induced by Drought and Up-regulated at Stage 0 ( hsi2 :Col-0)

P phenylpropanoid metabolism

GO:0009698

19.64

5.15E-05

TT6G, CAD

At3g51240; At1g09500

P response to temperature stimulus

GO:0009266

7.17

8.46E-03

COR15B

At2g42530

P response to abiotic stimulus

GO:0009628

3.09

3.72E-03

COR15B, AGL19

At2g42530; At4g22950

F oxidoreductase activity

GO:0016491

3.56

3.15E-03

TTG6, CAD

At3g51240; At1g09500

Repressed by Drought and Down-regulated at Stage 0 ( hsi2 :Col-0)

P protein modification

GO:0006464

6.34

7.37E-04

HDAC 18

At5g61070

F kinase activity

GO:0016301

7.34

3.75E-04

Cysteine-rich receptor-like protein kinase 4

At3g45860

* P, Biological Process; F, Biological Function; C, Cellular Component.

In cases where multiple related classifications were significant, only a subset is listed. Lists with fewer than 3 genes are not shown. Enrichments were performed at http://bioinformatics.psb.ugent.be/ATCOECIS using p < 0.05.

Comparisons of gene lists differentially expressed in hsi2 vs. Col-0 at stage 2 to lists from Wilkins et al. [36] or the moderate drought (mDr) treatments of Harb et al. [14] failed to identify a clear trend between the direction of change in hsi2 vs. Col-0 relative to drought inducibility/repression (Additional file 3). However, drought-induced genes from these moderate drought treatments, the pDr of Harb et al.[14], and the present study were predominantly up-regulated when differentially expressed in hsi2 vs. Col-0 at stage 1, reaching over 80% for genes induced in mDr1 and mDr10 of Harb et al. [14] and up-regulated in hsi2 vs. Col-0 at stage 1 (Additional file 3). Genes repressed by drought or ABA did not show the complimentary trend and no clear trends were identified in the stage 0 data. Notable GO terms enriched in drought-regulated genes differentially expressed in hsi2 vs. Col-0 at stage 0 or stage 1 include response to abiotic, temperature and chemical stimuli, and oxidoreductase activity (Table 2). Taken together, these results indicate that the hsi2 mutant constitutively expresses a number of drought- and ABA-responsive genes but under wilting conditions, the induction or repression of drought- and ABA-regulated genes is attenuated relative to the wild-type.

Accumulation of ABA-responsive transcripts in response to the ABA analog PBI425 is not compromised in the hsi2mutant

To ascertain the possible involvement of HSI2 during the early responses to ABA and osmotic stress, RNA was extracted from two-week-old seedlings of Col-0 and hsi2-2, 4 h after treatment with PBI425 or PEG 8000, and the expression of selected genes was analyzed by k-RT-PCR. Steady-state mRNA levels of five well-known ABA responsive marker genes (COR78/RD29A, RD29B, ERD6, KIN1, and RD22[14, 15]) continued to show wild-type induction to PBI425 and PEG 8000 in the hsi2-2 mutant, while RAB18 mRNA levels were higher in hsi2 than Col-0 following exposure to the ABA analog (Figure 8).
Figure 8

Kinetic RT-PCR analysis of gene expression. cDNA was synthesized from total RNA from 14-day old seedlings treated with 25 μM PBI425 or 20% PEG 8000 for 4 h. Amplification of the housekeeping gene encoding polypyrimidine tract-binding protein1 (PTBpa, AT3G01150) was used as control to normalize expression data. All values represent the averages of three biological replicates, each analyzed three times (technical replicates) ± standard error. In cases where expression levels were too small to graph, values are indicated in writing. If no bar is visible and no value indicated, the analysis was not performed.

Of 6 genes tested that have been implicated in ABA signaling, mRNA levels for three (ABF2, ABI2 and HAB1) [37] were highly induced by PBI425 but displayed identical expression patterns in Col-0 and hsi2-2 (Figure 8). Transcripts for PHOSPHOLIPASE Dα1 (PLDα1) and ANAC019, both positive regulators of ABA signalling [38, 39], showed higher levels of expression in the mutant than wild-type following treatment with PBI425. With PLDα1, mRNA levels in hsi2 were also higher in the control and PEG 8000 treatments, suggesting constitutive differences in expression rather than altered responses to ABA and drought. Expression of ERA1, which encodes a farnesyl transferase and a negative regulator of ABA signalling [40], was not inducible by PBI425 and showed no consistent differences between Col-0 and hsi2-2.

Two genes implicated in mediating drought stress (CBF1 and RD20) were highly inducible by PBI425 (Figure 8). While hsi2-2 and Col-0 displayed identical patterns of expression for RD20 in control and PBI425 treatments, expression of the transcription factor CBF1 was higher in hsi2-2 following treatment with the ABA analog. Expression of neither MYB15, MYB88 nor ERECTA were inducible by PBI425; however, levels of MYB15 in hsi2-2 were lower in the control, but not the PBI425 treatment and MYB88 levels were higher in hsi2 following PBI425 treatment. Levels of ERECTA mRNA also showed a trend of being higher in the hsi2 mutant under different treatments, although differences were more obvious in the PEG 8000 treatment. Differences in ERECTA expression were also observed in rosette leaves before and after drought stress (Figure 8). Thus, the loss of HSI2 function did not affect the expression of most genes tested within 4 h of PBI425 treatment. A longer-term study may reveal latent changes in ABA-inducible expression, if any, of these genes in the mutant compared to the wild type.

Discussion

Our analyses establish a role for HSI2 in response to water stress during the vegetative stage of the Arabidopsis life cycle. Specifically, loss of HSI2 function results in plants better able to maintain physiological water potential under limiting water conditions, as indicated by reduced wilting and higher leaf RWC (Figure 2), while overexpression of HSI2 yields a complementary phenotype. These results are consistent with HSI2 acting as a negative regulator. The ability of the hsi2 mutant to avoid low water potential is likely attributed, at least in part, to lower stomatal conductance (Figure 4), effectively reducing transpirational water loss. Consistent with this phenotype, the mutant constitutively expresses higher levels of genes implicated in reducing water loss or improving water use. These include ERECTA, a positive regulator of water use efficiency through control of stomatal density and conductance [31] and PHOSPHOLIPASE Dα1, a positive regulator of ABA-induced stomatal movement and early-stage drought resistance [38] (Figure 8). Conversely, the transcription factor GTL1, a negative regulator of water use efficiency through its effect on stomatal density [32] is down-regulated in hsi2 at stage 0. Despite these changes in gene expression, no differences in stomatal density were obvious between the hsi2 mutants and their corresponding wild-types in preliminary analyses. Stomatal density in Arabidopsis is developmentally controlled and affected by the environment [41]. Accordingly, more detailed analyses are required of both stomatal density and aperture. It is noteworthy that HSI2 transcripts are likely preferentially expressed in guard cells in the absence of stress [42, 43], and thus could be involved in the direct or indirect regulation of guard cell genes.

An unanticipated finding of this study was the reduced levels of numerous metabolites and gene transcripts associated with tolerance to dehydration stress measured in the hsi2-2 mutant, compared to Col-0. This includes lower levels of ABA and several ABA metabolites (Figure 5) as well as osmolytes and osmoprotectants (Figure 6). Global analysis of gene expression revealed that most genes up-regulated under severe drought conditions are expressed at lower levels in hsi2-2 than in Col-0 (Additional file 3). Among GO terms highly enriched in these lists of genes include response to abiotic stimulus, response to water deprivation, and response to ABA stimulus (Table 2). It is noteworthy that levels of many of these metabolites continue to be induced, and levels of gene transcripts up-regulated, under drought conditions; it is the magnitude of change that is dampened in the mutant compared to the wild-type. These results are consistent with hsi2-2 plants experiencing, or at least perceiving, a milder dehydration stress than the wild-type under the conditions tested. One possible explanation for these findings is that the ability of hsi2-2 seedlings to maintain RWC and avoid low water potential for a longer time than Col-0 delays the onset of cellular dehydration and attenuates its severity. Indeed, based on our metabolite and gene expression data, there is no evidence to indicate that hsi2-2 seedlings should have greater tolerance to dehydration stress. This includes expression analysis of several genes associated with dehydration stress in seedlings treated with a PEG solution that simulates dehydration stress (Figure 8). The possibility that HSI2 affects drought tolerance by regulating other, and possibly, novel pathways cannot be excluded at this time and requires further investigation. Among the GO terms most significantly enriched in genes differentially expressed in hsi2 vs Col-0 are endomembranes and chloroplasts and represent potential targets for future studies. Included in the endomembranes group are a number of transporters (amino acid, water channel, polyamine transporters, and membrane) such as MATE efflux family proteins, proton-dependent oligopeptide transport (POT) family proteins, auxin efflux carriers, ABC transporters, a delta TIP (water channel protein), sugar and nitrate transporters and a cytochrome oxidase. Recently, differential expression of genes encoding pumps and transporters were associated with increased drought tolerance of rice near isogenic lines [13].

Seeds acquire desiccation tolerance during the final stages of maturation. Desiccation tolerance is also an important component of drought tolerance, and parallels between the two processes have been drawn previously [7]. HSI2 is known to be required for repression of seed maturation genes upon germination and the transition to vegetative growth [22, 24, 26]. In the absence of direct evidence for altered HSI2 activity in response of drought stress (Figure 1 and [23]), it could be argued that increased drought tolerance of the hsi2 mutant is a secondary effect triggered by the derepression of seed desiccation genes during vegetative growth. Indeed, transcripts of four genes encoding LEA proteins are constitutively up-regulated in leaves of the hsi2 mutant (Additional file 2) and GO terms consistent with antioxidant activity (e.g. flavonoids, oxidoreductases) are enriched (Table 2). However, these changes are unlikely to account for the altered dehydration avoidance responses described above. Overall, 23% of genes differentially regulated in hsi2 at stage 0 are also differentially expressed during the later stages of seed maturation, with 16% showing the same directionality of change in both conditions (data not shown). These values are lower than those observed in seedlings of hsi2 mutants [24, 26]. Given that HSI2 regulation of seed maturation genes is dependent on sugar [22], the differences are likely attributed to the inclusion of sucrose in the media used to grow seedlings. An alternative possibility is that HSI2 may only be required for a limited period of time during vegetative development for repressing seed maturation programs, as reported for PICKLE [44]. Of note, the seedling studies reported up-regulation of gene encoding master regulators of seed maturation (LEC1 and AFL clade B3 transcription factors). Of these, only transcripts of FUS3 were detected above background in leaves three-week-old Col-0 or hsi2 plants, and its expression was not altered by loss of HSI2. Thus, activation of seed maturation genes in leaves of the hsi2 mutant is likely to involve different signalling events. In a number of organisms, genes regulating embryogenic events have been shown to be required at later stages of development, including in response to stress [45, 46]. Thus, a role for HSI2 in repressing seed maturation genes upon germination and later, in response to water stress, is not unprecedented.

Our results indicate that HSI2 is not absolutely required for ABA signalling during drought stress. Both the (+)-ABA and its analog PBI425, which increase drought tolerance by activating ABA responses and ABA signalling [12, 29], continued to effectively induce greater drought tolerance in both the hsi2 mutant and 35S:HSI2 plants without altering the relative tolerance of these genotypes compared to the wild-type (Figure 3). PBI425 was also effective at reducing stomatal conductance in the mutant, with levels continuing to be lower than the wild-type following treatment (Figure 4). Furthermore, the expression of several genes involved in ABA synthesis and signalling was unaltered in the mutant 4 hr after treatment with PBI425 (Figure 8), suggesting the mutant is not affected in its ability to respond to this hyperactive ABA analog, and presumably to ABA itself. In cases where gene expression was different between the mutant and wild-type following PBI425, it was typically also altered in the absence of PBI425, suggesting an ABA-independent cause. Although differences in the levels of several ABA-responsive genes were observed between hsi2 and wild-type when plants displayed visible wilting symptoms, these were measured several days following water withdrawal, thus complicating interpretation. Altered patterns of gene expression under these conditions are likely attributed, at least in part, to different levels of ABA in the mutant at wilting, which in turn we hypothesize to result for better maintenance of water potential in the mutant. Although the effects of PBI425 are mediated through ABA signalling, global transcript profiling indicates that the two compounds do not act in an identical fashion [29]. Furthermore, exogenous application of growth regulators is limited in its ability to resolve the function of endogenous ones. For these reasons, additional research will be required to study the relationship between HSI2 and ABA. This should include evaluating the role of endogenous ABA and ABA signalling by epistatic analysis of hsi2 and mutants defective in ABA synthesis or perception, such as nced3.

Given that HSI2 is an EAR-dependent transcriptional repressor [23], it could act to limit the transcription of a subset of drought-inducible genes when water is abundant. Such target genes would be constitutively de-repressed upon loss of HSI2 function, as observed in comparisons of hsi2 and Col-0 transcriptomes at stage 0 (Table 2 and Additional file 3), conferring a benefit to the mutant upon initial exposure to limiting water conditions. Several previously reported stress responsive genes from Arabidopsis, including SFR6, LEA4-5, ATPAL1, AtCIMS, EGY3, ATCP1, ATHAL3, ATHSP-70, FAR1, and GDH1, are differentially expressed in hsi2 in the absence of a drought stress. Notably, nearly all of the differentially expressed genes involved in cellular/transmembrane transport (of sugar, lipids and metal ions) are up-regulated in the mutant suggesting more active transport and detoxification than in the wild-type. Also consistent with detoxification, possibly of reactive oxygen species known to accumulate in response to abiotic stress, is the enrichment of GO terms for oxidoreductases and flavonoids in hsi2 at stage 0 (Table 2). We speculate that HSI2-mediated transcriptional repression is naturally relieved upon perception of limiting water conditions. Transcript levels of HSI2 do not appear to be altered in response to stress (Figure 1 and [23]), suggesting that de-repression of drought-related HSI2 targets is likely mediated by translational or post-translational modification of HSI2. Several EAR-containing plant proteins have been shown to be post-translationally modified by phosphorylation or poly-ubiquitination, providing a potential means of relieving their repressive effects on gene expression (reviewed in [47]).

Conclusions

By subjecting single hsi2 mutants and plants overexpressing HSI2 to simulated drought stress by withholding watering, we have demonstrated a role for the putative chromatin remodelling factor HSI2 during drought stress at vegetative stage of the Arabidopsis life cycle life. Although elucidating the exact role of HSI2 will require additional research, available information indicates that it fulfils a negative role in maintaining physiological water potential under limiting water conditions and as such represents a potential target for genetic manipulation towards the development of crops better suited for cultivation under water-limited environments. Formal demonstration that HSI2 activity is regulated in response to drought stress will be important to resolving its biological role at this stage of the plant life cycle. The identification of direct targets for HSI2, the dynamics of HSI2 binding to these targets and the associated epigenetic state of the targets following water withdrawal will be required to clarify the involvement and mechanism of action of HSI2 in mediating drought-related gene expression.

Methods

Plant materials and growth conditions

Arabidopsis thaliana (L.) Heynh. was used throughout. T-DNA insertion lines, hsi2-2 (SALK_088606) and hsi2-5 (WiscDsLox388F10) were identified from the Salk Institute Genomic Laboratory Genomic database (http://signal.salk.edu; [48] and obtained from the Arabidopsis Biological Resource Centre (ABRC, http://abrc.osu.edu/). The locations of T-DNA insertions were confirmed by sequencing of PCR fragments and plants homozygous for the T-DNA insertions were identified by PCR (oligos used for PCR amplification are listed in Additional file 4).

To generate plants overexpressing HSI2, the genomic protein-coding region of At2g30470 was amplified by PCR from the BAC T6B20 (ABRC) and inserted sequentially into pDONRZeo (Invitrogen, http://www.invitrogen.com) and the pK7WG2 [49] derivative pER330 (E. Risseeuw and R. Datla, unpublished) using Gateway technology (Invitrogen). The integrity of the resulting 35S:HSI2 gene was confirmed by sequencing. Transgenic plants were generated by dipping inflorescences of Col-0 [50] in a suspension of Agrobacterium tumefaciens GV3101 (MP90) harboring the modified T-DNA binary plasmid and subjecting the resulting seeds to antibiotic selection (30 mg l-1 kanamycin). Independent T3 or T4 lines expressing the transgene were analyzed.

Unless otherwise noted, seeds of different genotypes were stratified for 2 days at 4°C, sown on Sunshine #4 potting mix (Sun Gro Horticulture, http://www.sungro.com/) and transferred to environment-controlled growth chambers with a 16-h photoperiod (200 μmol m-2 s-1) at 22/20°C (day/night). All samples for gene, hormone and metabolite analysis were collected at the same time of day to minimize circadian effects, immediately frozen in liquid nitrogen and stored at -80°C.

Drought treatments and measurements

Plants were watered as needed to maintain the soil moisture near field capacity and fertilized weekly with 20 N:20P:20 K until three-week-old, at which point they were subjected to drought stress by withholding water. Visual wilting, indicated by progressive loss of lush green color of leaves and drooping of leaf blades and petiole, was monitored daily thereafter until more than 80% plants were wilting. At the end of the observation period, plants were re-watered to field capacity, and recovery was recorded 24 h thereafter. Drought response (visual wilting) and recovery from wilting upon re-watering were evaluated in three independent batches of plants, originating from at least 2 different seed lots, with 36–72 plants observed per batch. Leaf water status was measured when more than 50% of the plants started to wilt. Results are presented as leaf Relative Water Content (RWC = fresh weight-dry weight/turgid weight-dry weight) and as percentage of wilted or dead plants at, or over, a certain period of time. In experiments evaluating the effect of the ABA analog on the onset and progress of drought stress, three-week-old plants were subjected to root-dip treatment with 30 μM of (+)-ABA or 20 μM of the long-lived synthetic ABA analog, (+)-8’-acetylene ABA (PBI425) in 0.05% ethanol v/v [27] and watering was withheld thereafter. The concentrations of ABA and the PBI425 were chosen based on information from the published literature [12]. Preliminary dose–response experiments established these levels as being effective at delaying visual wilting in Col-0 without undesired side effects, such as the accumulation of anthocyanins and leaf curling, that were observed when higher concentrations of PBI425 or (+)-ABA were applied. Because the hsi2 mutant responded very similarly to ABA and PBI425, and PBI425 offers several advantages over natural ABA when the sustained presence of hormonal activity is required, the synthetic analog was used in subsequent experiments. Student’s t-test (p ≤ 0.05) was performed to identify significant differences between treatments.

Measurement of stomatal conductance

Stomatal conductance was measured from fully expanded young leaves from well-watered or PBI425-treated plants using a steady state leaf porometer (Model SC-1,Decagon Devices, http://www.decagon.com) following the manufacturer’s instructions. Porometer readings were taken from the adaxial side (lower surface) of leaves by placing the sensor head at the widest part of the leaf and holding it in place until the measurement was complete (~ 30 seconds/reading). Measurements were taken from 2–4 leaves per plant and 8–12 different plants from each genotype and treatment. Porometer readings taken different leaves of a plant were averaged to derive a single value, and genotype and treatment average were calculated thereafter. Measurements were performed between 9:30 am to 11:30 am, two h after lights were turned on in the cabinets.

Quantification of ABA and metabolites by LC-MS/MS

Analysis was conducted at the National Research Council, Saskatoon, by UPLC-ESI-MS/MS (http://www.nrc-cnrc.gc.ca/eng/solutions/advisory/plant_hormone.html) as described in Chiwocha et al.[51]. For ABA profiling, tissues for analysis were harvested from the aerial portion of 3-week-old, well-watered (soil saturated to field capacity), drought-stressed (showing wilting) and re-watered (to field capacity, 24 h) plants. Each sample consisted of material pooled from six plants.

Metabolomic profiling and analysis

For metabolic profiling analyses, tissues were harvested from the aerial portion of 3-week-old, well-watered (to soil saturation, near field capacity), drought-stressed (showing visible wilting) and re-watered (to soil saturation for 24 h) plants and frozen immediately in liquid nitrogen and stored at -80°C until analyzed. Samples were collected in three biological replicates per genotype and each sample (65–250 mg) consisted of material pooled from six plants. Frozen tissues were freeze-dried and analyzed by Metabolon Inc (http://www.metabolon.com) as described by Oliver et al.[52]. Briefly, samples were extracted and prepared for analysis using Metabolon’s standard solvent extraction method. The extracted samples were split into equal parts for analysis on the GC/MS and LC/MS/MS platforms. Also included were several technical replicate samples created from a homogeneous pool containing a small amount of all samples considered in the study. A total 156 named biochemicals were identified. Following log transformation and imputation with minimum observed values for each compound, ANOVA contrasts were used to identify biochemicals that differed significantly between two genotypes at various time points.

Microarray analysis

Gene-expression profiles were generated using Arabidopsis 4 × 44 K oligonucleotide microarrays (http://www.agilent.com). Total RNA was isolated using the Qiagen RNAeasy Plant Mini Kit (http://www.qiagen.com) and quality was assessed using an Agilent-2100 Bioanalyzer. Each sample co-hybridized consisted of rosette leaves from four plants. Four independent biological replicates were analyzed at stage 0 (well-watered to field capacity) and three replicates at each of stage 1 (dry soil following withholding watering but before visible wilting) and stage 2 (visible wilting). Labeling and hybridization were performed following the manufacturer’s protocol using Agilent’s QuickAmp Labeling kit for two-color microarrays and incorporated a dye swap design. After washing, arrays were scanned and signals converted to expression data using GenePix 4000B scanner (GenePix Pro. 6.1, http://www.moleculardevices.com). Further in-house analysis was performed in GeneSpring GX.10 (Agilent). Additional analyses of differentially expressed genes were conducted using the following web-based tools; the Classification SuperViewer (The BAR; http://bar.utoronto.ca/ntools/cgi-bin/ntools_classification_superviewer.cgi), ATCOECIS (http://bioinformatics.psb.ugent.be/ATCOECIS), and Athena (http://www.bioinformatics2.wsu.edu/cgi-bin/Athena/cgi/analysis_select.pl). To compare expression levels of the wild-type before and after drought, single channel intensity values were obtained using the formula intensity calculator plugin in BASE 2.14.0 (http://base.thep.lu.se) and normalized with the Limma software package for R [53], using robust spline for intra-array and quantile for interarray normalizations. MIAME complaint data have been submitted to GEO (Accession # GSE39347).

Kinetic polymerase chain reaction analysis

Total RNA was isolated using the Agilent Plant RNA Isolation Mini Kit and treated with amplification grade DNase I (Invitrogen). The first-strand cDNA was synthesized using SuperScript® II reverse transcriptase (Invitrogen) and kinetic Polymerase Chain Reaction was performed on an MX3005P spectrofluorometric thermal cycler (Stratagene, http://www.stratagene.com) as described by Sharma et al. [54]. Amplification of the housekeeping gene encoding polypyrimidine tract-binding protein1 (PTBpa; AT3G01150) was used as control to normalize expression data. The list of genes analyzed and primers used in k-RT-PCR experiments are presented in Additional file 5.

For analysis of gene expression in response to PBI425 and polyethylene glycol, seeds were surface sterilized, stratified as above, and germinated on agar solidified 0.5× Murashige and Skoog (MS) medium (Sigma, http://www.sigma.com) in 150 × 15 mm Petri plates in a controlled environment chamber (80–100 μmol m-2 s-1 light Intensity, 16-h photoperiod, 24°C). Fourteen-day-old plants were flooded with PBI425 (25 μM) or 20% PEG 8000 on the germination plates and incubated at room temperature for 4 h prior to tissue harvest.

Abbreviations

35S: 

Cauliflower mosaic virus 35S promoter

ABA: 

Abscisic acid

ABA-GE: 

ABA-glucose ester

ABI3: 

Absicic acid insensitive3

AFL: 

ABI3/FUS3/LEC2

DPA: 

Dihydrophaseic acid

FUS3: 

FUSCA3

GO: 

Gene ontology

HSI2: 

High-level expression of sugar inducible gene2

HSL1: 

HSI2-Like1

HSL2: 

HSI2-Like2

k-RT-PCR: 

Kinetic reverse-transcriptase PCR

LEA: 

Late-embryogenesis abundant

LEC2: 

Leafy cotyledon2

mDr: 

Moderate drought

OEx: 

Over expression (lines show increased levels of HSI2 transcripts)

PA: 

Phaseic acid

pDr: 

Progressive drought

PHD: 

Plant homeodomain

PLDα1: 

Phospholipase Dα1

RWC: 

Relative water content

t-ABA: 

Trans-ABA

VAL1: 

Viviparous ABI3-Like1.

Declarations

Acknowledgements

We thank Kasi Williams for technical assistance, Larissa Ramsay and Chad Matsalla for bioinformatics support, Eddie Risseeuw and Raju Datla for pER330, Ken Nelson for PBI425, Irina Zaharia for hormone profiling, and Adrian Cutler and Fawzy Georges for critically reading the manuscript. This research was supported by funding from the National Research Council of Canada through the Genomics and Health Initiative. This publication is NRCC No. 54656.

Authors’ Affiliations

(1)
National Research Council Canada

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