Glycolytic Enzyme Activities and Gene Expression in ... - Springer Link

Appl Biochem Biotechnol (2014) 173:2241–2253 DOI 10.1007/s12010-014-1028-6

Glycolytic Enzyme Activities and Gene Expression in Cicer arietinum Exposed to Water-Deficit Stress Suruchi M. Khanna & Pooja Choudhary Taxak & Pradeep K. Jain & Raman Saini & R. Srinivasan

Received: 6 January 2014 / Accepted: 19 June 2014 / Published online: 10 July 2014 # Springer Science+Business Media New York 2014

Abstract The specific activities and transcript levels of glycolytic enzymes were examined in shoots of chickpea (Cicer arietinum L.) cultivars, Pusa362 (drought tolerant) and SBD377 (drought sensitive), subjected to water-deficit stress 30 days after sowing. Water-deficit stress resulted in decrease in relative water content, chlorophyll content, plant dry weight, and NADP/NADPH ratio and increase in NAD/NADH ratio in both the cultivars. A successive decline in the specific activities of fructose-1,6-bisphosphate aldolase (aldolase), 3phosphoglycerate kinase (PGK), and NADP-glyceraldehyde-3-phosphate dehydrogenase (NADP-GAPDH) and elevation in the specific activities of phosphoglycerate mutase (PGM) and triosephosphate isomerase (TPI) was observed in both the cultivars under stress as compared to their respective control plants. The specific activities of hexokinase, fructose-6phosphate kinase (PFK), and NAD-GAPDH were least affected. The transcript levels of PGK and NADP-GAPDH decreased and that of glucose-6-phosphate isomerase (GPI), PGM, and PFK increased in response to water-deficit stress while water-deficit stress had no effect on the steady-state transcript levels of hexokinase, aldolase, TPI, and NAD-GAPDH. The results suggest that under water-deficit stress, the activities and transcript levels of most of the glycolytic enzymes are not significantly affected, except the increased activity and transcript level of PGM and decreased activities and transcript levels of PGK and NADP-GAPDH. Further, the glycolytic enzymes do not show much variation between the tolerant and sensitive cultivars under water deficit. Keywords Chickpea . Glycolytic enzymes . Water-deficit stress . Transcript Introduction Exposure of plants to various biotic and abiotic stresses exerts adverse effects on their growth, development, productivity, and eventually the yield. Plants resort to various adaptations to acquire stress tolerance which comprise morphological and physiological changes along with S. M. Khanna : P. C. Taxak : P. K. Jain : R. Srinivasan (*) National Research Centre on Plant Biotechnology, Pusa Campus, New Delhi 110012, India e-mail: [email protected] S. M. Khanna : R. Saini Department of Biotechnology, Kurukshetra University, Kurukshetra 136119 Haryana, India

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Appl Biochem Biotechnol (2014) 173:2241–2253

the changes in molecular, metabolic, and biochemical processes [1, 2]. Water-deficit stress, one of the chief abiotic stresses affecting plant endurance leading to serious effects on cellular metabolism, is an important subject of study. Glycolysis is a central metabolic pathway whose primary role is to provide ATP, NADH, and precursor metabolites for biomass production under anaerobic conditions and since water stress causes reduction in O2 uptake [3], glycolysis, a fermentative pathway of respiration, becomes the primary mode of sustained ATP production for meeting the energy demands of metabolic activities. Genes [4–9], proteins, and enzymes [10–18] related to glycolysis have been reported to be affected in response to water stress in different crops. All these studies were performed at the proteomic or transcriptomic level to identify a set of proteins/genes with different functions and differentially regulated under water-deficit stress in the cultivars differing in their drought tolerance. However, limited studies have examined major glycolytic enzymes at the activity and gene transcript level that are associated with drought stress for plants differing in drought tolerance. Chickpea (Cicer arietinum L.) is one of the most important food legumes that thrives well under drought-prone conditions and is planted post rainy season on the residual soil moisture, making terminal drought stress a primary constraint to productivity. In chickpea, most of the earlier understanding of water stress-responsive cellular adaptation has evolved from transcriptome analysis [19–23]. However, knowledge at the proteomic level is relatively limited [24–26]. The data on the genes involved in stress tolerance without knowing their functions at protein level give partial and incomplete information. Additionally, the changes during stress observed at transcript level do not correlate well with the level of the protein, the key player in the cell [27]. Thus, from quantitative messenger RNA (mRNA) data, it is inadequate to predict protein expression level. Again, changes in protein levels alone do not imply changes in function, as many proteins are regulated by post-translational modifications. Moreover, the practical aspect of the enzymatic protein is reliant on its activity rather than on its existence in the proteome. To our knowledge, there have been no efforts directed towards the analysis of changes in the enzyme activities and corresponding transcripts of glycolytic pathway in response to water-deficit stress in chickpea. In the present study, two chickpea cultivars with varying tolerance to water deficit were analyzed to understand the possible role of glycolysis under water-deficit stress by examining the expression and function(s) (enzymatic activities) of glycolytic genes. The investigations of cultivars differing in their drought-tolerance level may serve as a marker in obtaining more productive cultivars. By analyzing differentially expressed glycolytic enzymes, we intend to gain deeper knowledge of plant glycolysis under water stress and to identify key enzymes and corresponding genes that could be used as markers in plant breeding programs aimed at developing stress-tolerant cultivars. For cultivated crops like chickpea, where improvement through conventional breeding is difficult because of narrow genetic base [28], gene and protein expression profiling is an alternate way to identify genes and proteins regulating the stress response.

Materials and Methods Plant Material, Maintenance, and Stress Treatment The two cultivars of chickpea (Pusa362 as tolerant and SBD377 as sensitive to water deficit) were selected after in-field screening and on the basis of 3 years of production (yield) data provided by Pulse Research Laboratory, Indian Agricultural Research Institute, New Delhi (India). Seeds were surface sterilized in 0.05 % HgCl2 followed by thorough washing with double-distilled water and germinated in Petri plates on moist Whatman paper in the dark. After 2 days, they were transferred to 15-cm diameter pots containing autoclaved soilrite in an


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environmentally controlled growth room maintained at a temperature of 25±2 °C, relative humidity of 50±5 %, and a photoperiod of 16 h (270 μmol m−2 s−1 light intensity) with normal watering. Thirty days after sowing, one set of plants was subjected to water stress by withholding irrigation, and tissue was harvested at 3 days interval up to 12 days when the leaves turned yellow and the plants wilted. Another set of plants, serving as control, was irrigated daily. The stressed and control plants were kept in parallel in the same growth room and were harvested at the same time point in the morning at approximately 1030 hours to avoid any diurnal variations. The harvested tissue was instantly frozen in liquid nitrogen and stored at −80 °C until further use. Relative Water Content and Chlorophyll Content Relative water content (RWC) was determined on the second leaf and was calculated as initial weight−dry weight/full turgor weight−dry weight [24]. For chlorophyll estimation, fresh leaf tissue (100 mg) was taken in 10 ml DMSO and kept at 70 °C for 5 h, filtered through cheese cloth to remove leaf pieces; absorbance was recorded at 663 and 645 nm [29]. Chlorophyll was calculated by using the formula given by Arnon [30]: Total chlorophyll mg g−1 fresh wt: ¼ ½ð8:02 A663 Þ þ ð20:2 A645 Þ V =1; 000 W

Where, A663 and A645 represent the absorbance at 663 and 645 nm, respectively. V is the total volume of sample in extraction medium (ml) and W is the weight of the sample (g). Pyridine Nucleotides Content Ratios of NAD/NADH and NADP/NADPH were determined using NAD/NADH and NADP/ NADPH quantification kits, respectively (Sigma Aldrich, USA), following manufacturer’s protocol. Enzyme Extraction Leaf material (200 mg) was macerated to a fine powder with liquid nitrogen in a prechilled pestle and mortar, mixed in a suitable volume (1 mL) of ice-cold extraction buffer (50 mM Tris-HCl, pH 7.8 containing 1 mM EDTA and 1 % PVP), homogenized for 1 min, gently squeezed through four layers of muslin cloth, and centrifuged at 12,400×g for 30 min at 4 °C. Supernatant, thus obtained, was referred to as crude enzyme preparation. Enzyme Assays Immediately after extraction, enzyme activities were measured spectrophotometrically at 340 nm using UV-visible spectrophotometer (Perkin Elmer, Lambda 35, USA) by following the oxidation of NAD(P)H or reduction of NAD(P). Preliminary assays for all the enzymes were conducted to standardize the conditions to obtain linear reaction rates with respect to enzyme concentration and time of incubation. All the enzymes were assayed as per Bergmeyer et al. [31]. The activities were expressed as nanomole per minute per milligram of protein. Activities of hexokinase and fructose-6-phosphate kinase (PFK) were determined using ADP Quest™ HS Assay, a kinase-specific kit (DiscoveRx Corp., CA, USA) following the manufacturer’s protocol. In brief, the assay uses a coupled enzyme reaction system to generate hydrogen peroxide from ADP (produced from kinase reaction). Hydrogen peroxide, when

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combined with acetyl dihydroxy phenoxazine (fluorescent dye precursor) in the presence of peroxidase, generates fluorescently active resorufin dye. The resorufin fluorescence was detected on fluorimeter at excitation and emission wavelength of 530 and 590 nm, respectively, and enzyme activity was expressed as micromolar of ADP per milligram protein. Protein Estimation Crude extract (500 μL) was precipitated with equal volume of 20 % (w/v) trichloroacetic acid (TCA). The precipitate obtained was washed twice with acetone, dried, and dissolved in 2 mL of 0.1 N NaOH. Protein was determined by the method of Lowry et al. [32] using bovine serum albumin as standard. RNA Isolation and RT-PCR Total RNA was isolated from the harvested leaf tissues of both control and stressed plants using TRIzol (Invitrogen, Carlsbad, CA, USA) reagent according to the manufacturer’s instructions. The quality of RNA was checked on MOPs-formaldehyde gel and the yield was quantified spectrophotometrically at 260 nm. Concentration of all the RNA samples was adjusted to 100 ng μL−1. The expression pattern of each gene corresponding to the abovementioned enzymes was obtained by reverse transcriptase-polymerase chain reaction (PCR). The gene-specific primers (Table 1) were designed using Primer Express (v3.0) software (Applied Biosystems, Foster City, CA, USA) from the respective nucleotide sequences available for chickpea at the National Centre for Biotechnology Information (NCBI) and had GC content of 40–60 %, Tm of 50–60 °C, and primer length of 20–25 nucleotides with an expected amplicon size of 200–300 base pairs. Actin gene was used as reference [23]. Reverse transcription of mRNA was performed using QIAGEN OneStep RT-PCR kit following the manufacturer’s instructions. Each RT reaction consisted of 100 ng RNA, 1× RT buffer (containing 1.25 mM MgCl2), 400 μM each dNTP, and 0.6 μM each of forward and reverse primer. All the reactions were performed under the following default conditions: 30 min at 50 °C, 15 min at 95 °C and 25 cycles of 1 min at 94 °C, 1 min at 58–62 °C, and 2 min at 72 °C followed by final extension of 72 °C for 10 min. The PCR products were analyzed by agarose gel electrophoresis. Transcript level measured as band intensity was determined with ImageJ program. Statistical Analysis The experimental design was arranged in a completely randomized design with three replications. The data were analyzed by ANOVA, and the significance of differences between treatment means was checked with Duncan’s multiple range test (p