Monendra Grover

Identification of Putative RuBisCo Activase (TaRca1)—The Catalytic Chaperone Regulating Carbon Assimilatory Pathway in Wheat (Triticum aestivum) under the Heat Stress

RuBisCo activase (Rca) is a catalytic chaperone involved in modulating the activity of RuBisCo (key enzyme of photosynthetic pathway). Here, we identified eight novel transcripts from wheat through data mining predicted to be Rca and cloned a transcript of 1.4 kb from cv. HD2985, named as TaRca1 (GenBank acc. no. KC776912). Single copy number of TaRca1 was observed in wheat genome. Expression analysis in diverse wheat genotypes (HD2985, Halna, PBW621, and HD2329) showed very high relative expression of TaRca1 in Halna under control and HS-treated, as compared to other cultivars at different stages of growth. TaRca1 protein was predicted to be chloroplast-localized with numerous potential phosphorylation sites. Northern blot analysis showed maximum accumulation of TaRca1 transcript in thermotolerant cv. during mealy-ripe stage, as compared to thermosusceptible. Decrease in the photosynthetic parameters was observed in all the cultivars, except PBW621 in response to HS. We observed significant increase in the Rca activity in all the cultivars under HS at different stages of growth. HS causes decrease in the RuBisCo activity; maximum reduction was observed during pollination stage in thermosusceptible cvs. as validated through immunoblotting. We observed uniform carbon distribution in different tissues of thermotolerant cvs., as compared to thermosusceptible. Similarly, tolerance level of leaf was observed maximum in Halna having high Rca activity under HS. A positive correlation was observed between the transcript and activity of TaRca1 in HS-treated Halna. Similarly, TaRca1 enzyme showed positive correlation with the activity of RuBisCo. There is, however, need to manipulate the thermal stability of TaRca1 enzyme through protein engineering for sustaining the photosynthetic rate under HS—a novel approach toward development of “climate-smart” crop.

The Halophile Protein Database

Halophilic archaea/bacteria adapt to different salt concentration, namely extreme, moderate and low. These type of adaptations may occur as a result of modification of protein structure and other changes in different cell organelles. Thus proteins may play an important role in the adaptation of halophilic archaea/bacteria to saline conditions. The Halophile protein database (HProtDB) is a systematic attempt to document the biochemical and biophysical properties of proteins from halophilic archaea/bacteria which may be involved in adaptation of these organisms to saline conditions. In this database, various physicochemical properties such as molecular weight, theoretical pI, amino acid composition, atomic composition, estimated half-life, instability index, aliphatic index and grand average of hydropathicity (Gravy) have been listed. These physicochemical properties play an important role in identifying the protein structure, bonding pattern and function of the specific proteins. This database is comprehensive, manually curated, non-redundant catalogue of proteins. The database currently contains 59 897 proteins properties extracted from 21 different strains of halophilic archaea/bacteria. The database can be accessed through link. Database URL: http://webapp.cabgrid.res.in/protein/

SSH Analysis of Endosperm Transcripts and Characterization of Heat Stress Regulated Expressed Sequence Tags in Bread Wheat.

Heat stress is one of the major problems in agriculturally important cereal crops, especially wheat. Here, we have constructed a subtracted cDNA library from the endosperm of HS-treated (42°C for 2 h) wheat cv. HD2985 by suppression subtractive hybridization (SSH). We identified ~550 recombinant clones ranging from 200 to 500 bp with an average size of 300 bp. Sangers sequencing was performed with 205 positive clones to generate the differentially expressed sequence tags (ESTs). Most of the ESTs were observed to be localized on the long arm of chromosome 2A and associated with heat stress tolerance and metabolic pathways. Identified ESTs were BLAST search using Ensemble, TriFLD, and TIGR databases and the predicted CDS were translated and aligned with the protein sequences available in pfam and InterProScan 5 databases to predict the differentially expressed proteins (DEPs). We observed eight different types of post-translational modifications (PTMs) in the DEPs corresponds to the cloned ESTs-147 sites with phosphorylation, 21 sites with sumoylation, 237 with palmitoylation, 96 sites with S-nitrosylation, 3066 calpain cleavage sites, and 103 tyrosine nitration sites, predicted to sense the heat stress and regulate the expression of stress genes. Twelve DEPs were observed to have transmembrane helixes (TMH) in their structure, predicted to play the role of sensors of HS. Quantitative Real-Time PCR of randomly selected ESTs showed very high relative expression of HSP17 under HS; up-regulation was observed more in wheat cv. HD2985 (thermotolerant), as compared to HD2329 (thermosusceptible) during grain-filling. The abundance of transcripts was further validated through northern blot analysis. The ESTs and their corresponding DEPs can be used as molecular marker for screening or targeted precision breeding program. PTMs identified in the DEPs can be used to elucidate the thermotolerance mechanism of wheat—a novel step toward the development of “climate-smart” wheat.

HEPNet: A Knowledge Base Model of Human Energy Pool Network for Predicting the Energy Availability Status of an Individual.

HEPNet is an electronic representation of metabolic reactions occurring within human cellular organization focusing on inflow and outflow of the energy currency ATP, GTP and other energy associated moieties. The backbone of HEPNet consists of primary bio-molecules such as carbohydrates, proteins and fats which ultimately constitute the chief source for the synthesis and obliteration of energy currencies in a cell. A series of biochemical pathways and reactions constituting the catabolism and anabolism of various metabolites are portrayed through cellular compartmentalization. The depicted pathways function synchronously toward an overarching goal of producing ATP and other energy associated moieties to bring into play a variety of cellular functions. HEPNet is manually curated with raw data from experiments and is also connected to KEGG and Reactome databases. This model has been validated by simulating it with physiological states like fasting, starvation, exercise and disease conditions like glycaemia, uremia and dihydrolipoamide dehydrogenase deficiency (DLDD). The results clearly indicate that ATP is the master regulator under different metabolic conditions and physiological states. The results also highlight that energy currencies play a minor role. However, the moiety creatine phosphate has a unique character, since it is a ready-made source of phosphoryl groups for the rapid synthesis of ATP from ADP. HEPNet provides a framework for further expanding the network diverse age groups of both the sexes, followed by the understanding of energetics in more complex metabolic pathways that are related to human disorders.

Sumoylation May Play an Important Role in Modification of Large Number of Proteins Associated with Heat Stress in Plants

Heat stress is an important factor affecting the agricultural production. At the molecular level post translational modifications have been shown to be influenced in plants under heat stress. The authors have studied palmitoylation, sumoylation, S-nitrosylation and nitration in the plant gene sequences associated or not associated with heat stress. In the present paper it has been shown that sumoylation is an important property which is possibly influences a large number of proteins associated with heat stress in a wide variety of plants. This property can be utilized for identifying novel sequences associated with heat stress in plants.

nifPred: Proteome-Wide Identification and Categorization of Nitrogen-Fixation Proteins of Diaztrophs Based on Composition-Transition-Distribution Features Using Support Vector Machine

As inorganic nitrogen compounds are essential for basic building blocks of life (e.g., nucleotides and amino acids), the role of biological nitrogen-fixation (BNF) is indispensible. All nitrogen fixing microbes rely on the same nitrogenase enzyme for nitrogen reduction, which is in fact an enzyme complex consists of as many as 20 genes. However, the occurrence of six genes viz., nifB, nifD, nifE, nifH, nifK, and nifN has been proposed to be essential for a functional nitrogenase enzyme. Therefore, identification of these genes is important to understand the mechanism of BNF as well as to explore the possibilities for improving BNF from agricultural sustainability point of view. Further, though the computational tools are available for the annotation and phylogenetic analysis of nifH gene sequences alone, to the best of our knowledge no tool is available for the computational prediction of the above mentioned six categories of nitrogen-fixation (nif) genes or proteins. Thus, we proposed an approach, which is first of its kind for the computational identification of nif proteins encoded by the six categories of nif genes. Sequence-derived features were employed to map the input sequences into vectors of numeric observations that were subsequently fed to the support vector machine as input. Two types of classifier were constructed: (i) a binary classifier for classification of nif and non-nitrogen-fixation (non-nif) proteins, and (ii) a multi-class classifier for classification of six categories of nif proteins. Higher accuracies were observed for the combination of composition-transition-distribution (CTD) feature set and radial kernel, as compared to the other feature-kernel combinations. The overall accuracies were observed >90% in both binary and multi-class classifications. The developed approach further achieved >92% accuracy, while evaluated with blind (independent) test datasets. The developed approach also produced higher accuracy in identifying nif proteins, while evaluated using proteome-wide datasets of several species. Furthermore, we established a prediction server nifPred (http://webapp.cabgrid.res.in/nifPred) to assist the scientific community for proteome-wide identification of six categories of nif proteins. Besides, the source code of nifPred is also available at https://github.com/PrabinaMeher/nifPred. The developed web server is expected to supplement the transcriptional profiling and comparative genomics studies for the identification and functional annotation of genes related to BNF.