CAMTA 1 regulates drought responses in Arabidopsis thaliana
© Pandey et al.; licensee BioMed Central Ltd. 2013
Received: 30 August 2012
Accepted: 22 March 2013
Published: 2 April 2013
Transcription factors (TF) play a crucial role in regulating gene expression and are fit to regulate diverse cellular processes by interacting with other proteins. A TF named calmodulin binding transcription activator (CAMTA) was identified in Arabidopsis thaliana (AtCAMTA1-6). To explore the role of CAMTA1 in drought response, the phenotypic differences and gene expression was studied between camta1 and Col-0 under drought condition.
In camta1, root development was abolished showing high-susceptibility to induced osmotic stress resulting in small wrinkled rosette leaves and stunted primary root. In camta1 under drought condition, we identified growth retardation, poor WUE, low photosystem II efficiency, decline in RWC and higher sensitivity to drought with reduced survivability. The microarray analysis of drought treated camta1 revealed that CAMTA1 regulates “drought recovery” as most indicative pathway along with other stress response, osmotic balance, apoptosis, DNA methylation and photosynthesis. Interestingly, majority of positively regulated genes were related to plasma membrane and chloroplast. Further, our analysis indicates that CAMTA1 regulates several stress responsive genes including RD26, ERD7, RAB18, LTPs, COR78, CBF1, HSPs etc. and promoter of these genes were enriched with CAMTA recognition cis-element. CAMTA1 probably regulate drought recovery by regulating expression of AP2-EREBP transcription factors and Abscisic acid response.
CAMTA1 rapidly changes broad spectrum of responsive genes of membrane integrity and photosynthetic machinery by generating ABA response for challenging drought stress. Our results demonstrate the important role of CAMTA1 in regulating drought response in Arabidopsis, thus could be genetically engineered for improving drought tolerance in crop.
KeywordsCAMTA1 mutant WUE RWC Osmotic stress Microarray Gene expression Drought recovery
Abiotic and biotic stress is one of the major environmental factors limiting crop productivity worldwide. Water deficiency is one of the primary causes for the reduction in crop yield . Previously, Several studies shows that calcium, a key messenger, involved in several signalling pathways and regulates many growth and developmental processes, plays a crucial role in stress signalling and adaptation [2–6] and in response to various biotic (pathogens, defence elicitors, and insect feeding) and abiotic stresses such as light, UV light, high and low temperature, salt, drought, osmotic stress, mechanical stimuli including touch and wind, oxidative stress, ozone, and hypoxia [7–9]. Within cells, calcium signatures are perceived by the EF-hand families of calcium-modulated proteins (calmodulin - CaM, Calcium dependent protein kinase - CDPK and calcineurin B-like protein - CBL) which are well characterised in plants [10–12]. When intracellular calcium rises to about 1 μM, calmodulin (CaM) binds calcium, undergoes a change in conformation, and activates the target gene thereby producing the respective cellular response [4, 6]. To elucidate the mechanisms underlying calcium/calmodulin regulated gene expression in plants, previous reports identified a family of six Arabidopsis genes encoding calmodulin binding transcription activators (CAMTAs) [5, 13] also referred to as signal-responsive (SR) protein  or ethylene-induced CaM binding proteins (EICBP) . This factor, designated AtCAMTA (Arabidopsis thaliana CaM-binding transcription activator), is highly conserved and contains a CG-1 homology DNA-binding domain at the N terminus (binding site includes the CGCG and CGTG motif), a TIG domain (an immunoglobulin-like fold involved in nonspecific DNA binding), three ankyrin repeats (implicated in protein-protein interaction) and five putative CaM-binding motifs called as IQ motif [5, 13, 14, 16]. In Arabidopsis, there are six CAMTAs (CAMTA1-6), whose transcript accumulates (up-regulated) or diminish (down-regulated) rapidly and transiently to various abiotic and biotic stress. Each member has distinct or overlapping spatial and temporal expression pattern in different plant developmental stages under various biotic and abiotic stresses [15, 17]. The first evidence of biological and physiological function of CAMTA protein was recently reported in Arabidopsis CAMTA3 (AtSR1) loss of function mutant through a reverse genetic approach . CAMTA 3- knockout plants during developmental stages accumulates high level of reactive oxygen species (ROS), showed enhanced resistance towards fungal and bacterial pathogen by suppressing plant responses. It negatively regulates the defence response to pathogens and interacts with WRKY33 TF in camta3 mutants [16, 18]. Similarly another study by Galon Y. et al., 2010 on CAMTA1 reports the increased sensitivity for auxin in camta1 mutant suggesting a role in suppressing the plant responses to auxin when induced under stress condition . There is considerable information about the changes in gene expression regulated by CAMTA 1 under various stresses like cold, salt, heat and ultra-voilet [20, 21]. The promoters of Drought responsive element binding protein 1C (DREB1C) and ZAT12 binds with CAMTA3 in plants  indicating a calcium-signal driven gene expression. Besides various findings on function of CAMTA protein on stress physiology,  were first to report down-stream gene of the CAMTA protein and showed pollen-specific expression of AtCAMTA1 and AtCAMTA5 which possibly increased Arabidopsis VPPase (AVP1) gene expression in pollen by binding to the pollen-specific cis-acting region of AVP1 . The DNA cis-element that binds to CAMTA was identified as CGCG and CGTG binding motif in Arabidopsis, AtCAMTA3  and Rice, Os-CBT . The consensus sequence of CGCG core motif is (A/C)CGCG(C/G/T), giving the name to the DNA binding domain of the protein as CG-1, a novel cis-element which was first isolated from the parsley cDNA library . The consensus sequence of CGTG core motif is (A/C)CGTGT and includes classical abscisic acid responsive element (ABRE) motif (ACGTGT), which is recognised by bZIP proteins . The most recent report on CAMTA (SlSR) in tomato revealed its role in fruit development and ripening , they cloned seven SlSR genes and their expression levels were differentially regulated mainly by development signals, as well as by ethylene and suggested that SlSRs were located downstream of the Rin-regulated network. On taking these results together, CAMTA have the potential of relaying calcium signalling via calmodulin binding domain and stress signalling via CG-1 and ABRE binding motif.
The aim of our research is to study and characterise the molecular function of CAMTA1 gene under drought condition and establish a possible role of CAMTA1 protein in drought stress. The present study provides considerable information about the changes in gene expression, metabolic pathways, CGTG and CGCG motif dependent gene expression in CAMTA1 under drought stress. In brief, we hypothesized CAMTA1 to be essential for successful drought recovery.
The knockout camta1showed drought sensitivity, poor WUE and decline in RWC
Microarray experimental design to identify CAMTA1 dependent genes
The expression profiles (fold change value) of genes obtained through microarray were experimentally validated through RT-PCR using 6 genes belonging to dihydroflavonoid 4-reductase, LEA, oxidoreductase, lipid transfer protein, glutathionin s-transferase and anthocyanidin synthase. The results obtained from all the 6 genes tested by RT-PCR agree with the trend of regulation identified by microarray analysis (Figure 4). Thus results of RT-PCR validate the microarray data.
The strategy depicted in Figure 3 (analysis scheme) is to understand the role of CAMTA1 in drought condition which is the unique part of our study. CAMTA1 may have a role in normal physiology, also revealed by the fact that CAMTA1 gene expresses ubiquitously at control and drought condition in Arabidopsis (Additional file 10). We made the comparison between WT-C and M1-C and identified that camta1 does regulate a group of genes since in leaf tissue, 169 genes were down-regulated and 209 genes were up-regulated in camta1-3 as compared to Col-0 under water condition. In root tissue, 670 genes were up regulated and 635 genes were down regulated. The AgriGO analysis of these differentially expressed genes indicate that the camta1 under control condition regulates pathways over represented by response to stimulus, response to chemical stimulus, response to organic stimulus substance, response to chitin, response to endogenous stimulus, response to hormone stimulus etc., (Additional file 10). The pathways involved in various regulatory mechanisms were also altered in camta1-3 under control like transcription regulator activity, regulation of macromolecule biosynthetic process, regulation of primary metabolic process, regulation of nitrogen compound metabolic process etc. (Additional file 10). Alternatively this has facilitated in inferring the tissue specific pathways regulated by camta1-3 under water condition. The most significant pathway exclusively present in leaf tissue includes transcription regulator activity, response to carbohydrate stimulus, response to chitin etc. The pathways over represented in only root tissue were oxidoreductase activity, regulation of biosynthetic process, metal ion binding etc. (Additional file 10).
The analysis of CAMTA1 dependent genes for identifying biological processes and pathways regulated by CAMTA1
To elucidate the mechanisms underlying the enhanced sensitivity of the camta1-3 towards limited water condition, we identified and analysed biological pathways, gene regulation networks and protein interaction maps with CAMTA1 dependent genes by Pathway Studio 9.0 and agriGO (GO Analysis Toolkit and Database for Agricultural Community) analysis tools keeping a stringent cut-off of p-value ≤ 0.05 for identifying significant biological identities. The analysis was carried out firstly with LCDPRG, LCDNRG and RCDPRG, RCDNGR and simultaneously the genes containing CAMTA1-recognition motif were analysed to identify specific cis-elements governed potential changes in cellular functions and associated transcriptome interaction networks. This data analysis strategy, in a global and unbiased manner, identifies cellular changes driven specifically by CAMTA1 along with its recognition motif (CGCG or CGTG).
CAMTA1 dependent positive regulation: Involved in stress response and maintained osmotic balance of cell under drought stress and targets plasma membrane
CAMTA1 dependent negative regulation: involved in cell differentiation – apoptosis, affect photosynthesis efficiency and targets chloroplast
CAMTA1 dependent negatively regulated genes had several pathways related to cell differentiation and propagation imparting controlled cell division which could be ascribed to decreased rate of cell death (apoptosis) and senescence. Various such cell processes were cell differentiation, DNA methylation, apoptosis, abscission, dehiscence, cytokinesis, cell proliferation, S phase, chromatin remodeling, chloroplast organization and biogenesis (Figure 5B, 7B). The over-represented pathways in LCDNRG were related to leaf anatomy and photosynthesis like, leaf shape, stomatal density, leaf senescence, transpiration, photosynthetic electron transport (Figure 5B). Other important cell processes negatively regulated by CAMTA1 were ROS generation, xenobiotic clearance, fatty acid metabolism, pentose phosphate shunt, microgametogenesis (Figure 5B and 7B). The motif specific cell processes in LCDNRG were chloroplast function, glycolysis, photorespiration, phenyl propanoid metabolism, RNA splicing etc. (Figure 6B). Likewise in RCDNRG, motif specific cell process were post transcriptional gene silencing (PTGS), sulphate assimilates, nitrogen assimilates, seed abscission etc. (Figure 8B). The functional class for LCDNRG includes cellulose synthase, plastocyanin and for RCDNRG includes aspartate transaminase, glutathione transferase (GST) (Figure 5B, 6B, 7B and 8B). The GO analysis of LCDNRG revealed large number of genes related to photosynthesis machinery like chloroplast, plastid, thylakoid, photosystem, photosynthetic membrane etc. (Figure 5C and 6C). The significant GO terms in RCDNRG were response to hydrogen peroxide, glutathione transferase activity, peptide transport, phenylpropanoid metabolic process, fatty acid metabolic process etc. (Figure 7C and 8C).
CAMTA1 involvement in abiotic stress management
CAMTA1 regulate prominent stress responsive genes
We next examined the substantial relationship between the expressions of stress induced transcripts between different abiotic stress conditions. For LCDPRG, 21 stress-responsive genes that responded to all three stress condition had more than 90% similarity with CAMTA1 recognition motif (Figure 9A). Among these we found 5 well established stress inducible genes including early-responsive to dehydration 7 (ERD7) (3-CGCG; 1-CGTG), responsive to ABA 18 (RAB18) (2-CGCG; 5-CGTG), responsive to desiccation 26/22 (RD26/22) (1-CGCG; 6-CGTG), cold regulated 78 (COR78) (1-CGCG; 2-CGTG), low temperature-induced 30 (LTI30) (1-CGTG) (Additional file 11-worksheet 1). These stress induced genes were probably expressed under the influence of CAMTA as they were enriched with CAMTA1 binding cis-elements hence presumed to be its direct binding targets. Other important genes showing positive regulation in all 3 stresses were late embryogenesis abundant protein (LEA), cytochrome P450, glyoxylate aminotransferase 3, phosphatase 2CA, ABA-responsive protein, etc. (Additional file 11-worksheet 1). There were 6 genes positively correlated by both drought and cold, 9 genes for cold and salinity and 25 genes regulated by both drought and high salinity. Some genes were unique to their stress condition, 33 genes were exclusively regulated by drought, 23 genes by cold and 32 genes induced only under high salinity (Figure 9A). In LCDPRG, genes modulated only under the drought stress includes NAC TF (1-CGTG; 1-CGCG), MYB TF (5-CGTG), lipid transfer protein 4/3 (LTP4/3) (2-CGTG), glucose phosphate translocator 2 (GPT2) (1-CGTG), UDP-glucosyl transferase 85A5 (2-CGTG; 1-CGCG), scarecrow-like 13 (SCL13), cytochrome P450, AAA-type ATPase, senescence-related gene 1, etc. (Additional file 11-worksheet 1). Expression of genes altered exclusively by salt were WD-40 repeat family protein (WD-40) (1-CGTG; 2-CGCG), GCR2-like 1 (GCL1) (5-CGTG; 2-CGCG), hexokinase 2, jasmonic acid responsive 2, H(+)-ATPase 3, cystatin, etc. (Additional file 11-worksheet 1). Exclusively, cold related genes include expansin A9 (2-CGCG), phosphatidyl serine decarboxylase 3 (1-CGCG), RAP2.2 and 2.1 (2-CGTG), ethylene response sensor 1 (ERS1) (2-CGTG), AP2-TF, copper chaperone, glucose-6-phosphate dehydrogenase 5, etc. (Additional file 11-worksheet 1). Similarly, for RCDPRG, analysis enabled in identifying gene expression with overlapped and/or for specific stress condition. We found 16 genes whose expression was positively regulated under drought, cold and salinity and among these some of the known stress inducible genes driven by CAMTA1 were RD28, nodulin protein, CBL-interacting protein kinase 3, dark inducible 6 (3-CGTG), ferretin 1 (2-CGTG;1-CGCG) (Figure 9B, Additional file 12-worksheet 1). In RCDPRG, 29 genes got affected under both drought and salt, 12 genes by drought and cold and 21 genes got affected by salinity and cold (Figure 9B). Some of the important genes showing positive correlation in drought and salt includes phytoene desaturation 1, RD19 (2-CGTG), acyl-COA oxidase 2 (4-CGTG; 2-CGCG), phytoene desaturation 1 (PDS1) (3-CGTG), MYC2 (1-CGTG; 1-CGCG), tetraspanin 3 (2-CGTG), cinnamyl-alcohol dehydrogenase (1-CGTG), ORA47 transcription factor (1-CGTG; 2-CGCG) (Additional file 12-worksheet 1). Genes that showed altered expression under both drought and cold were ethylene-responsive element binding factor 13 (ERF13) (1-CGCG), C-repeat/DRE binding factor 2 (CBF2) (1-CGCG), dormancy-associated protein 1 (DRM1) (1-CGTG), ABA1 (2-CGTG), WRKY33 (1-CGTG), sensitive to freezing 2, etc. Genes affected under salt and cold includes acetolactate synthase (1-CGTG; 3-CGCG), plasma membrane intrinsic protein 1A, peroxidase 27, etc. (Additional file 12-worksheet 1). There were 31 genes positively modulated exclusively by drought stress like lipoxygenase (1-CGCT; 1-CGCG), protein kinase 19 (3-CGTG; 1-CGCG), glycosyl hydrolase (1-CGTG; 2-CGCG), carboxyesterase 12 (2-CGTG; 1-CGCG), etc. There were 53 and 45 genes specifically related to salt and cold, respectively with positive correlation (upregulated) (Figure 9B)
The LCDNRG had 22 genes negatively correlated (down-regulated) to all 3 stresses (drought, cold and high salinity) and among them majority of genes has been well characterized for stress adaptation like salt tolerance zinc finger (3-CGTG), Arabidopsis NAC domain containing protein 102 (ANAC102) (5-CGTG; 1-CGCG), germin-like protein 1 (1-CGTG), ERD9 (2-CGTG), photosystem I subunit H (PSI-H), carbonic anhydrase1 (Figure 9A, Additional file 11-worksheet 2). The negatively regulated genes had functional redundancy by showing altered expression in more than one stress condition. There were 13 genes modulated under drought and salt condition, 11 genes affected by both cold and drought condition while 20 genes got affected by salinity and cold (Figure 9A). Genes specifically modulated by drought has 18 genes, among them some of the important genes include cinnamoyl CoA reductase 1, auxin-responsive protein, fructose-bisphosphatealdolase, oxidoreductase, tonoplast intrinsic protein 2 etc. There were 22 cold specific genes like Beta galactosidase 1 (BGAL1), MYB91, sugar transporter 1, BTB domain protein 2 (BT2), beta-amylase 9, UDP-glucosyl transferase 73B1 etc. (Additional file 11-worksheet 2). There were 56 genes exclusively affected under cold condition, some of the important genes were MYB77, ERF5, hydrolase 9, Glutathione S-transferase (GST20), ANAC059, ACC synthase 6, etc. (Additional file 11-worksheet 2). In RCDNRG, 19 genes were specifically negatively altered by drought like oxidoreductase, alanine aminotransferase (1-CGCG), DNAJ heat shock protein 20 (HSP20) (1-CGCG), 2-alkenal reductase (1-CGTG; 1-CGCG), beta-ketoacyl-CoA synthase (1-CGTG; 1-CGCG), carboxyesterase 16 (1-CGTG; 1-CGCG), etc. Genes specifically modulated (negative correlation) by cold and salinity were 37 and 24, respectively (Figure 9A, Additional file 12-worksheet 2). In RCDNRG, 15 genes were affected by all the 3 stress condition and majority of them were known stress responsive genes like HSP70, RAB18 (5-CGTG; 2-CGCG), LEA, COR15A, ERD9/10, LTI30, COR47, etc. For either of the 2 stress condition CAMTA1 had 16, 3 and 14 genes affected by drought-salt, drought-cold and salt-cold, respectively (Figure 9B, Additional file 12-worksheet 1).
Interaction of CAMTA1 with different hormonal pathways
CAMTA1 regulate expression of various global transcription factors involved in abiotic stress
The transcriptome of camta1-2 and camta1-3
The transcriptome of camta1-2 by Galon et al., 2010 (published data) was compared with the gene expression profiling of camta1-3 (our data) and has a correlation of r = 0.86 (Additional file 17). The 63 genes were commonly up-regulated while 33 genes were commonly down regulated in both camta1-2 and camta1-3 as compared to wild type Col-0. Some of the interesting commonly expressed genes have been listed in additional file 17. The expression of chalcone synthase, UDP-glucoronosyl, polygalacturonase, early light-inducable protein, cysteine proteinase, ethylene-responsive element-binding family protein, disease resistance protein etc. were found to be repressed in both camta1-2 and camta1-3. Similarly, some of the commonly up regulated genes include mannitol transporter, wall-associated kinase, glycine-rich protein, cytochrome p450, ARR15 (auxin response regulator15), WRKY26 etc. (Additional file 17). As reported in Galon et. al, 2010 study , the transcriptome comparative study between two alleles of camta1 mutant (camta1-1 and camta1-2) through Mapman showed similar pathways when analysed for camta1-3. The similar pathways between camta1-3 and camta1-2 includes cytokinin metabolism, metabolism of sulphur containing compounds, flavanoids (Additional file 17). Therefore the transcript profiling of camta1-3 was in concurrent with earlier reported pathways affected by camta1 mutant.
This is the first report elucidating the role of CAMTA1 gene in drought stress, exploring through the transcript analysis of the camta1-3 mutant. We identified that camta1 was most susceptible to drought stress (Figure 1 and 2). The most striking difference was that camta1-2 and camta1-3 showed inward adaxial rolling of leaf and severe loss of chlorophyll showing apparently damaged yellow to purplish-black appearance and stunted growth which revealed enhanced effect of drought on camta1 as compared to Col-0 (Figure 2A). The different abiotic stress response of plants depends on root growth and the stage of development . Therefore, we tried to determine the effect of osmotic stress on camta1 by root bending assay. Under osmotic stress (mannitol and PEG), the reduction in shoot weight and inhibition of root growth was more in camta1-3 as compared to Col-0 (p < 0.05). At 300mM mannitol and 6.5% PEG, significant growth retardation in terms of rosette leaves, shoot weight and primary root length could be ascribed to the silencing of the CAMTA1 gene in mutant (knock-out mutant) (Figure 1). Thus, we hypothesize that CAMTA1 acts as positive regulator of plant growth under drought stress based on our observation in osmotic and drought stress experiment in soil (Figure 1 and 2, Additional file 3). After rewatering, the camta1 mutant (camta1-2 and camta1-3) exhibited growth inhibition, whereas the Col-0 plants thrived well indicating that loss of functional CAMTA1 protein in mutants had a negative role against drought stress (P < 0.05). The carbon isotopes discrimination (CID), relative water content (RWC) and photosystem II efficiency (Fv/Fm ratio) can prove an important criterion for the selection of plant with variable drought tolerance. According to Farquhar GD et.al, a shift in the CID ratio of plant gives information about the plant water use efficiency (WUE) and indicates the plant inherent trait to adapt under stress condition and confirms the stress induced changes in the 12C/13C ratio . The variation between the CID values of Col-0 and camta1 indicates that the plant significantly discriminate between heavier and lighter carbon during photosynthesis (Figure 2E). Earlier report states that the variation in CID was known to arise from variation in photosynthetic capacity, stomatal conductance, WUE . The reduction in Fv/Fm ratio might primarily be due to decline in RWC. The low WUE, RWC and decreased efficiency of photosystem II of the camta1 attributes to the poor tolerance of plant for the drought stress which may be due the loss of CAMTA1 function in the mutant suggesting its probable role in stress tolerance. In brief, we hypothesized that camta1 apparently plays a role in the natural plant development under stress condition, because its mutation clearly results in stunted plant growth with altered root development and increased sensitivity to osmotic stress. The data indicates that the CAMTA1 gene is required for stress responses that improve drought tolerance through various response mechanisms (Additional file 10). The disruption of functional CAMTA protein in mutant resulted in alteration of various regulatory pathways and stress responses (Additional file 10). To broaden our knowledge horizon for the role of CAMTA1 gene, the comparative analysis of gene profiling under drought and control condition of Col-0 and camta1-3 was studied. The transcript analysis showed decreased gene count in camta1-3 than Col-0 under drought condition (Additional file 4 and 7). This clearly reflects that expression of large number of stress induced transcripts were reduced to non-significant level (FC ≤ 2) due to the disruption of the CAMTA1 protein in the mutant resulting in masked expression of its respective target genes. Secondly, the increase in gene count in Col-0 was due to drought stress imposed on plant which depicts large number of genes have undergone reprogramming under drought stress (Additional file 5, 8).
To identify in equitable and unprejudiced way, genes regulated by CAMTA1, the genes were selected on the basis of their non-significant expression level in camta1-3 with respect to its respective significant expression in the Col-0. Thus CAMTA1 dependent genes were classified as either positively regulated viz., LCDPRG and RCDPRG or negatively regulated viz., LCDNRG and RCDNRG. Motif-analysis facilitated in identifying CAMTA1 binding site in various abiotic stress, phytohormone and TFs related genes which could be later used in establishing their binding affinity to the CAMTA1 cis-element (MCGCGB, MCGTGT) (Figure 3E and 3F). The pathway analysis strategy, in a global and unbiased manner, identifies cellular changes driven by specific CAMTA1 recognition motif genes. The most distinguished cell process was “drought recovery” as it clearly indicates the potential nature of CAMTA1 protein to combat and recover under drought stress (Figure 5A and 6A). Drought stress does not affect the plant in isolation but comes in combitorial with other stress condition. For the plant to sustain drought stress, CAMTA1 protein channelizes several stress responsive cell processes and develops plethora of responses that might help the plant to acclimatize and survive in the stressed environment. The higher number of stress responsive genes, signal sensors and transporters in LCDPRG and RCDPRG indicates the expression of more genes associated with stress mechanism. Signal transduction and transporters play major role under drought condition by maintaining osmotic homeostasis, operates the signalling and growth development pathways (Figure 5A and 7A) . The genes encoding plasma membrane and its constituents acted as positive regulator indicating the presence of several genes associated to membrane integrity and biogenesis which were involved in the formation, organization, maintenance of the membrane and in turn protects the cell against mechanical damage, osmotic strength (Figure 4C and 5C) . The higher expression of these under the influence of CAMTA1 maintains membrane structure and preserve cell compartmentation and by synthesizing constituent macromolecules under drought condition provides rapid tolerance to stress . The accumulation of flavonoid is a trademark of plant stress  which aims at countering the generation of ROS and leads to the inactivation of antioxidant enzymes constituting a secondary ROS-scavenging system in plants which are exposed to stress conditions (Figure 5C) . Thus positive regulation of the flavonoid biosynthesis imparts tolerance to the plant when exposed to the drought condition. Photosynthesis plays a pivotal role in plant performance under drought. In LCDNRG, there were several genes related to photosynthesis, stomata, chlorophyll, heme, FAD and transpiration (Figure 5B, 5C and 6B). The decline in photosynthesis machinery results in lower net carbon uptake in leaf under water deficit condition which is followed by an alteration in partitioning of the photoassimilates at the plant level, consequently leads to an increase in the root to shoot ratio (Figure 5B, 5C, 6B and 6C) . This is the prima facie for the maintenance of root growth under decreasing water in the soil. In general, this response is mediated by phytohormone, namely by abscisic acid (ABA) . The CAMTA1 generates response to ABA and auxin which induces lateral root formation for optimal water uptake as profilic root system is vital for drought tolerance (Figure 7A). Tightly regulated expression of phytohormone under drought condition determines lateral root meristem activation via an ABA-auxin signalling crosstalk and ethylene (Figure 10A) . In previous reports growth promotion is considered a specific feature for ethylene response, so to establish equilibrium, plant optimize growth and tolerate stress response which involves the synthesis of ethylene . During drought stress response, ABA regulates stomatal aperture and leads to activation of several genes and secondary messengers, including calcium, Inositol trisphosphate, cADP, ribose, etc. [32, 38]. Hence conjugated effect of phytohormones induced development and photosynthetic regulation directs the plant for survival in stress environment. The presence of ABA indicates the concerted action of CAMTA1 in cell signalling which progressively leads to a massive reprogramming to combat stress (Figure 10A and 10B). Heat shock proteins (HSPs), known as molecular chaperon, rapidly accumulates under stress condition and play a major role in protein folding (Figure 5A) . Numerous studies on histone and DNA methylation highlights its key role in gene expression and plant development under stress . Apart from its role in development under stress, DNA methylation was also associated with gene silencing and transposon control in plant and fungi . Recent studies indicate that transcriptional gene silencing and post transcriptional gene silencing (PTGS) were mechanistically related because they were correlated to same events, including changes in DNA methylation . The cell differentiation, propogation and reprogramming were governed by major changes in the epigenome . CAMTA1 acts as a negative regulator for the DNA methylation, gene silencing, apoptosis, cell proliferation, PTGS. Hence by negatively regulating the epigenetic mediated gene silencing and cell differentiation, CAMTA1 probably decreases the rate of silenced gene and PTGS and allows the expression of several genes potential for generating appropriate cellular responses which could be otherwise masked by the effect of DNA methylation (Figure 5B and 7B). Secondly by inhibiting DNA methylation and cell differentiation, CAMTA1 tightly regulates genetics events governing plants death or else the cell differentiation could eventually leads to developmental cell senescence . Therefore by acting as a negative regulator to DNA methylation and cell proliferation CAMTA1 protects the plant from untimely stress induced senescence and directs the expression of stress responsive genes. Study on cellulose synthase by Chen Z et.al in 2005 revealed that its mutant were more tolerant to drought stress as well as to NaCl, mannitol and found higher accumulation of osmolytes and ABA in mutant than Col-0 . Hence decrease in cellulose synthase gene expression enhances drought tolerance which was in concurrent with the reduction of the cellulose synthase by CAMTA1 (Figure 6B). The LEA proteins protect various macromolecules, such as enzymes and lipids, from dehydration .
The results establish a role for CAMTA1 in drought acclimation and provide a possible point of integrating various molecular and biological pathways with drought stress regulated gene expression. The interaction with several stress responsive genes, maintenance of osmoticum, regulating membrane biogenesis, generating ABA response, guarding photosynthesis and interaction with AP2-EREBP were some of the key regulatory components of CAMTA1 in response to drought stress. These findings provide insight for further investigation of CAMTA1 function under drought stress and open new perspectives for improving drought tolerance which could eventually lead to better crop production.
Plant material and treatments
The Col-0 Arabidopsis thaliana (Columbia-0 ecotype) and homozygous T-DNA insertion line of AtCAMTAs (background Columbia-0) was obtained from the Arabidopsis Biological Resource Centre (ABRC, the Ohio State University, Columbus, OH, USA) (Additional file 1). To evaluate the osmotic sensitivity of Col-0 and camta1-3, seeds were surface sterilized in 4% (v/v) sodium hypochlorite for 5 min, washed 8 times with sterilized water. The Murashige and Skoog (half strength; 1/2 MS) medium with 1% (w/v) sucrose, 0.8% (w/v) agar and pH 5.7 was prepared. The seedlings from Col-0 and camta1-3 were cultured in MS medium for one week and then transferred to MS (control) or MS supplemented with variable concentration of mannitol (100, 200, 250 and 300 mM) and PEG (1.5, 3.0, 4.5 and 6%) solutions and allowed to grow vertically along with control for 14 days. The seedlings growth (shoot weight) and root length was measured and photographed. The experiment was performed in triplicates.
The efficiency of photosystem II (Fv/Fm ratio) was determined on first or second leaves from the tip of branches, using MAXI-version of Imaging-PAM (Walz, Effeltrich, Germany).
All experiments were performed at least three times independently. Results were assessed by Student’s t test. Significance was defined as P < 0.05. The statistically significant changes have been marked with an asterisk (*) in respective figure (p < 0.05).
RNA extraction, cRNA preparation, microarray hybridization and processing
A total 24 samples were processed for Affymetrix gene chip ATH1 analysis. The ecotype Col-0 and camta1 mutant were grown under drought stress and water condition. Three biological replicates sample were collected from camta1-3 and Col-0 in watered and drought stressed condition (when drooping effect in leaves were observed and soil moisture was below 30%). Leaf tissues were directly harvested for RNA isolation at 10th day of drought stress. Plants were up-rooted and roots were grinded in liquid nitrogen for RNA isolation. Total RNA was extracted from leaf and root tissue of Col-0 and camta1-3 using the Spectrum Plant Total RNA Isolation kit (Sigma-Aldrich, USA) by incorporating a DNaseI treatment step using RNase-free DNaseI set (Ambion), according to the manufacturer’s instructions. Total 24 samples were prepared which comprises 3 leaf samples of each Col-0 and camta1-3 in water condition and drought condition (3x2x2 = 12), similarly 3 root samples of Col-0 and camta1-3 in water and drought condition (3x2x2 = 12). A total of 250 ng of each RNA was subjected to cDNA/double strand DNA synthesis using one-cycle cDNA Synthesis Kit (Affymetrix, Inc., Santa Clara, CA). The biotin-labelled nucleotides were incorporated during the second step in vitro transcription reaction by using the gene chip IVT Labelling Kit (Affymetrix). The resulting labelled anti-sense RNA samples were fragmented and 15 μg each per array was hybridized to 24 gene chip, ATH1 Arabidopsis Genome Arrays (Affymetrix) for 16 h at 45°C. Once completed, arrays were processed according to the manufacturer’s protocol and scanned using the Gene Chip® Scanner 3000 (Affymetrix).
Microarray data analysis, identification of CAMTA dependent genes and its analysis
The Arabidopsis gene chip ATH1 Genome array (Affymetrix) contains more than 22,500 probe sets corresponding to approximately 24,000 transcripts. The arrays images were first quantified using Gene Chip Operating Software (GCOS, Affymetrix). The Affymetrix Arabidopsis genome array cel files were analysed by Array Assist Software 5.2.2 (Agilent Technologies, Santa Clara, CA, USA). The Affymetrix microarray data is submitted to GEO with accession series GSE40061. The GC-RMA algorithm with quantile normalization was used to summarize the probes from the arrays . Differentially expressed genes with a detection p-value less than 0.05 (p-value ≤ 0.05) and fold change greater or equal to 2 (FC ≥ 2) were considered significant in three biological replicate experiments. The GraphPad prism5 (http://www.graphpad.com/prism) software was used for the identification of CAMTA1 dependent genes, for this, ratio between the fold change of differentially regulated gene list of camta1-3 (M1-D/M1-C) and Col-0 (WT-D/WT-C) were taken as input for this software. The column statistics analysis was performed which computes descriptive statistics (and normality tests) for each gene. The ratios of genes with values greater or equal to threshold value (99% of confidence of interval) were defined as CAMTA1 dependent genes. The de-novo computational identification of CAMTA1 binding sites (MCGTGT and MCGCGB) in a set of upstream regions (1000bp) of CAMTA1 regulated genes was performed by Suite for Computational identification Of Promoter Elements (SCOPE) . CAMTA1 positively and negatively regulated gene list were taken as input in SCOPE for searching particular binding sites related genes. Pathway analysis of CAMTA1 positively and negatively regulated genes was done with Pathway Studio software 9.0 (http://www.ariadnegenomics.com). The TAIR ID of these genes was taken as input for shortest path algorithm in pathway studio. Proteins, metabolites (or small molecules), functional classes and cell processes were taken as entity type for establishment of pathway by using plant ResNet 4.0 database (Ariadne Genomics) employing four interaction type namely regulation, direct regulation, expression and binding . Genes without interactions with others were removed according to the original references recorded by the software. The Gene Ontology (GO) analysis was done with AgriGO (bioinfo.cau.edu.cn/agriGO/index.php) for CAMTA1 dependent genes of leaf and root tissues. The numbers of significant GO terms were large; therefore multiple testing method was performed in order to control the rate of errors. We used SEA (Singular Enrichment Analysis) algorithm, which performs the Fisher statistical test method and by default Benjamini–Yekutieli method with 0.05 significance level to do the multiple comparison correction is used. The Abiotic stress related data was obtained from STIFDB (Stress Responsive Transcription Factor Database) (http://caps.ncbs.res.in/stifdb) and genes related to drought, salt and cold were retrieved . CAMTA positively and negatively regulated genes were queried to the gene list with stress related data. Arabidopsis hormone related genes were downloaded from Arabidopsis Hormone Database 2.0 . TAIR ID of CAMTA1 positively and negatively regulated genes from leaf and root tissues were taken as input for searching particular hormone related gene. On the similarity search basis genes were grouped them into respective phytohormone. Retrieval of particular transcription factor related genes was done by AGRIS . Frequency of CAMTA1 positively and negatively regulated genes was calculated on similarity basis with the locus IDs of these genes to the IDs of transcription factor related genes present in this database.
Validation of microarray data using RT-PCR
Following total RNA extraction from all 24 samples, cDNA was synthesized in a 40 μl reaction volume using SuperScript ® III reverse transcriptase kit (Invitrogen) supplemented with 200 ng of random primers (Invitrogen) according to the manufacturer’s instructions. The cDNA synthesis reaction conditions were 70°C for 5 min, 25°C for 5 min, 50°C for 1 h, followed by heat inactivation of the enzyme at 75°C for 15 min. Relative transcript abundance of selected genes were assessed by performing RT-PCR using the ABI Prism 7300 Sequence Detection System (Applied Biosystems Foster City, CA, USA). ). Primer sequences used in reactions are described in Additional file 18 and reaction of RT-PCR was performed in a 10 μl reaction volume by adding 0.5 μl cDNA aliquot of each sample to the PCR mix containing gene specific primers and 50% SYBR® Green PCR Master mix. Quantification of transcript (mRNA expression) levels was carried out by using the ΔΔCt quantitative methods. Normalization was carried out by subtracting the ΔΔCt values of ubiquitin from the corresponding ΔΔCt values of the target gene. Following normalization the relative abundance of transcript was calculated from the expression ratios to calculate a fold change value.
Calmodulin binding transcription activator
Leaf CAMTA1 dependent positively regulated genes
Leaf CAMTA1 dependent negatively regulated genes
Leaf CAMTA1 independent drought induced genes
Leaf CAMTA1 independent drought repressed genes
Root CAMTA1 dependent positively regulated genes
Root CAMTA1 dependent negatively regulated genes
Root CAMTA1 independent drought induced genes
Root CAMTA1 independent drought repressed genes.
We would like to thank Prof. Hillel Fromm for the kind gift of camta1-2 seeds (Salk_008187). The work in our laboratory was supported by the Council of Scientific and Industrial Research (CSIR) India. This work was supported under CSIR supra-institutional projects SIP05, SIP09 and NMITLI.
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