@article {45500, title = {Integrative omics analysis in Pandanus odorifer (Forssk.) Kuntze reveals the role of Asparagine synthetase in salinity tolerance}, journal = {Scientific Reports}, volume = {9}, year = {2019}, month = {JAN }, pages = {Article Number: 932}, type = {Article}, abstract = {

Pandanus odorifer (Forssk) Kuntze grows naturally along the coastal regions and withstands salt-sprays as well as strong winds. A combination of omics approaches and enzyme activity studies was employed to comprehend the mechanistic basis of high salinity tolerance in P. odorifer. The young seedlings of P. odorifer were exposed to 1 M salt stress for up to three weeks and analyzed using RNAsequencing (RNAseq) and LC-MS. Integrative omics analysis revealed high expression of the Asparagine synthetase (AS) (EC 6.3.5.4) (8.95 fold) and remarkable levels of Asparagine (Asn) (28.5 fold). This indicated that salt stress promoted Asn accumulation in P. odorifer. To understand this further, the Asn biosynthesis pathway was traced out in P. odorifer. It was noticed that seven genes involved in Asn bisynthetic pathway namely glutamine synthetase (GS) (EC 6.3.1.2) glutamate synthase (GOGAT) (EC 1.4.1.14), aspartate kinase (EC 2.7.2.4), pyruvate kinase (EC 2.7.1.40), aspartate aminotransferase (AspAT) (EC 2.6.1.1), phosphoenolpyruvate carboxylase (PEPC) (EC 4.1.1.31) and AS were up-regulated under salt stress. AS transcripts were most abundant thereby showed its highest activity and thus were generating maximal Asn under salt stress. Also, an up-regulated Na+/H+ antiporter (NHX1) facilitated compartmentalization of Na+ into vacuoles, suggesting P. odorifer as salt accumulator species.

}, issn = {2045-2322}, doi = {10.1038/s41598-018-37039-y}, author = {Rashmi, Deo and Barvkar, Vitthal T. and Nadaf, Altafhusain and Mundhe, Swapnil and Kadoo, Narendra Y.} } @article {46828, title = {Insights of Bipolaris sorokinianasecretome-anin silicoapproach}, journal = {Biologia}, volume = {75}, year = {2020}, month = {DEC}, pages = {2367-2381}, type = {Article}, abstract = {

The plant pathogen,Bipolaris sorokiniana(teleomorph:Cochliobolus sativus), is of global concern as it attacks many economically important cereals and grasses. During the infection process, phytopathogenic fungi are known to secrete a variety of proteins collectively known as the secretome, analyzing which can help in deciphering the mechanism of fungal pathogenesis. In this study, we performedin silicosecretome analysis ofC. sativusstrain ND90Pr using established secretome prediction pipeline involving software tools such as SignalP, TargetP, TMHMM, big-PI Fungal Predictor, ProtComp, and WoLF PSORT. Using these software and other prediction criteria, we identified 196 probable secretory proteins from theB. sorokinianaproteome. Characterization of the predicted secretome revealed proteins that may have probable functions in degradation of the plant cell wall, lipids, proteins, and nucleic acids, as well as in pathogenesis and metabolism. Further, the PHI-base analysis identified 38 proteins having a possible role in pathogenicity and virulence. This study helped to predict the composition of the secretome ofB. sorokinianaand extrapolate its role in plant infection and pathogen survival. It may provide clues for developing new control strategies targeting the vital fungal secretory proteins.

}, keywords = {Cochliobolus sativus, pathogenesis, Phytopathogenic fungi, Secretory proteins, Virulence}, issn = {0006-3088}, doi = {10.2478/s11756-020-00537-4, Early Access Date = JUN 2020}, author = {Pathak, Gauri M. and Gurjar, Gayatri S. and Kadoo, Narendra Y.} } @article {49768, title = {Integrative multi-omics and computer-aided biofungicide design approach to combat fusarium wilt of chickpea}, journal = {Planta}, volume = {262}, year = {2025}, month = {SEP}, pages = {107}, type = {Review}, abstract = {

Main conclusionIntegrating multi-omics and computer-aided drug discovery approaches can overcome the limitations of traditional methods and help develop highly effective, specific, and environmentally safe biofungicides to control crop diseases.AbstractChickpea is a valuable legume crop in terms of nutrition, food security, economic sustainability, and environmental benefits. Fusarium wilt caused by the soil-borne fungus Fusarium oxysporum f.sp. ciceri is one of the most important diseases affecting chickpea. Several disease management methods, including crop rotation, soil fumigation with chemical fungicides, soil solarization, etc., are practiced to manage the disease. However, these methods have various limitations and cannot completely control the disease. Moreover, chemical fungicides indiscriminately kill even the beneficial soil microbes, pollute groundwater, and enter the food chain. Hence, modern approaches emphasizing innovative strategies and technologies need to be explored to manage the disease effectively. In this review, we propose integrating multi-omics (genomics, proteomics, metabolomics, etc.) and computer-aided drug discovery (CADD) approaches to develop biofungicides targeting vital pathogen proteins. Multi-omics approaches can delve deeper into the plant-pathogen interaction and reveal essential pathogen genes or proteins. These proteins could be targeted using CADD to identify phytochemical-based potential biofungicides, either using structure- or ligand-based drug design approaches. The potential biofungicides can be subjected to the prediction of carcinogenicity, hepatotoxicity, mutagenicity, etc., to identify biofungicides that are safe to use and are highly specific to the target pathogen. In vivo and in vitro validation studies can be followed to establish the efficacy and safety of the identified biofungicides for their practical application. This integrated approach can reduce the time and cost compared to the traditional methods and accelerate the discovery of highly effective biofungicides to protect crops from various diseases.

}, keywords = {CADD, docking, Fungal diseases, MD Simulation, Protein structure prediction, Transcriptomics}, issn = {0032-0935}, doi = {10.1007/s00425-025-04821-y}, author = {Sahoo, Rosaleen and Kadoo, Narendra Y.} }