Biology subjects

Shekhawat, R. S.

Publications and source records attributed to Shekhawat, R. S..

3 recordsLinked to original sources

bioRxiv2023

Peribacillus frigoritolerans T7-IITJ, a potential biofertilizer, induces plant growth-promotinggenes of Arabidopsis thaliana

This study aimed to isolate plant growth and drought tolerance-promoting bacteria from the nutrient- poor rhizosphere soil of several plant species from the Thar desert and unravel their molecular mechanisms of plant growth promotion, to develop effective biofertilizers for arid agriculture. Among our isolates of Thar desert rhizobacteria, Enterobacter cloacae C1P-IITJ, Kalamiella piersonii J4-IITJ, and Peribacillus frigoritolerans T7-IITJ, significantly enhanced root and shoot growth in the model plant Arabidopsis thaliana under PEG-induced drought stress in the lab. Whole genome sequencing and biochemical analyses of the non-pathogenic bacterium T7-IITJ revealed its plant growth-promoting traits, viz., solubilization of phosphate, iron, and nitrate and production of exopolysaccharides and auxin. Transcriptome analysis of Arabidopsis thaliana inoculated with T7-IITJ and exposure to drought revealed the induction of plant genes for photosynthesis, auxin and jasmonate signaling, nutrient mining and sequestration, redox homeostasis, and secondary metabolite biosynthesis pathways related to beneficial bacteria-plant interaction, but repression of many stress-responsive genes. Biochemical analyses indicated enhanced proline, chlorophyll, iron, phosphorous, and nitrogen content and reduced reactive oxygen species in plant tissues due to T7-IITJ inoculation. This bacterium could also improve the germination and seedling growth of Tephrosia purpurea, Triticum aestivum, and Setaria italica under drought. Additionally, T7-IITJ inhibited the growth of two plant pathogenic fungi, Rhizoctonia solani, and Fusarium oxysporum. These results suggest P. frigoritolerans T7-IITJ is a potent biofertilizer which can regulate plant genes promoting growth and drought tolerance.

plant biology↗

bioRxiv2023

In silico characterization of five novel disease-resistance proteins in Oryza sativa sp. japonica against bacterial leaf blight and rice blast diseases

Oryza sativa sp. japonica is the most widely cultivated variety of rice. It has evolved several defense mechanisms, including PAMP-triggered immunity (PTI) and effector-triggered immunity (ETI), which provide resistance against different pathogens to overcome biotic stresses. Several disease-resistance genes and proteins, such as R genes and PRR proteins, have been reported in the scientific literature which shows resistance against Xanthomonas oryzae pv. oryzae (Xoo), a causative agent for bacterial leaf blight disease (BB), and Magnaporthe oryzae (M. oryzae), causing rice blast disease (RB). Although some of these resistance proteins have been studied, the functional characterization of resistance proteins in rice is not exhaustive. In the current study, we identified five novel resistance proteins against BB and RB diseases through gene network analysis. Structure and function prediction, disease-resistance domain identification, protein-protein interaction (PPI), and pathway analysis revealed that the five new proteins played a role in the disease resistance against BB and RB. In silico modeling, refinement, and model quality assessment were performed to predict the best structures of these five proteins, and submitted to ModelArchive for future use. The functional annotation of the proteins revealed their involvement in the bacterial disease resistance of rice. We predicted that the new resistance proteins could be localized to the nucleus and plasma membrane. This study provides insight into developing disease-resistant rice varieties by predicting novel candidate resistance proteins, which will pave the way for their future characterization and assist rice breeders in improving crop yield and addressing future food security.

bioinformatics↗

bioRxiv2022

Gene expression profiling and protein-protein network analysis revealed prognostic hub biomarkers linking cancer risk in type 2 diabetic patients

Type 2 diabetes mellitus (T2DM) and cancer are highly prevalent diseases imposing major health burden globally. Several epidemiological studies indicate increased susceptibility to cancer in T2DM patients. However, genetic factors linking T2DM with cancer are poorly studied so far. We used computational approach on the raw gene expression data of peripheral blood mononuclear cells of Homo sapiens available at the gene expression omnibus (GEO) database, to identify shared differentially expressed genes (DEGs) in T2DM and three common cancer types namely, pancreatic (PC), liver (LC) and breast cancer (BC). Additional functional and pathway enrichment analysis of identified common DEGs highlighted involvement of important biological pathways including cell cycle events, immune system process, cell morphogenesis, gene expression and metabolism. Furthermore, we retrieved the PPI network for crucial DEGs obtained from above analysis to deduce molecular level interactions. Based on the result of network analysis, we found 8, 5 and 9 common hub genes in T2DM vs PC, T2DM vs LC and T2DM vs BC, respectively. Overall, our analysis identified important genetic markers potentially able to predict the chances of pancreatic, liver and breast cancer onset in T2DM patients.

bioinformatics↗