@article { ISI:000357438200013, title = {Metabolic profiling of chickpea-Fusarium interaction identifies differential modulation of disease resistance pathways}, journal = {Phytochemistry}, volume = {116}, year = {2015}, month = {AUG}, pages = {120-129}, publisher = {PERGAMON-ELSEVIER SCIENCE LTD}, address = {THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND}, abstract = {

Chickpea is the third most widely grown legume in the world and mainly used as a vegetarian source of human dietary protein. Fusarium wilt, caused by Fusarium oxysporum f. sp. ciceri (Foc), is one of the major threats to global chickpea production. Host resistance is the best way to protect crops from diseases; however, in spite of using various approaches, the mechanism of Foc resistance in chickpea remains largely obscure. In the present study, non-targeted metabolic profiling at several time points of resistant and susceptible chickpea cultivars using high-resolution liquid chromatography-mass spectrometry was applied to better understand the mechanistic basis of wilt resistance or susceptibility. Multivariate analysis of the data (OPLS-DA) revealed discriminating metabolites in chickpea root tissue after Foc inoculation such as flavonoids, isoflavonoids, alkaloids, amino acids and sugars. Foc inoculated resistant plants had more flavonoids and isoflavonoids along with their malonyl conjugates. Many antifungal metabolites that were induced after Foc infection viz, aurantion-obstine beta-glucosides and querecitin were elevated in resistant cultivar. Overall, diverse genetic and biochemical mechanisms were operational in the resistant cultivar for Foc defense as compared to the susceptible plant. The resistant chickpea plants employed the above-mentioned metabolic pathways as potential defense strategy against Foc. (C) 2015 Elsevier Ltd. All rights reserved.

}, keywords = {Chickpea, Fusarium wilt, LC-MS, Metabolomics, OPLS-DA, Phytoalexin}, issn = {0031-9422}, doi = {10.1016/j.phytochem.2015.04.001}, author = {Kumar, Yashwant and Dholakia, Bhushan B. and Panigrahi, Priyabrata and Kadoo, Narendra Y. and Giri, Ashok P. and Gupta, Vidya S.} } @article { ISI:000378741200010, title = {Fusarium oxysporum mediates systems metabolic reprogramming of chickpea roots as revealed by a combination of proteomics and metabolomics}, journal = {Plant Biotechnology Journal}, volume = {14}, number = {7}, year = {2016}, month = {JUL}, pages = {1589-1603}, publisher = {WILEY-BLACKWELL}, address = {111 RIVER ST, HOBOKEN 07030-5774, NJ USA}, abstract = {

Molecular changes elicited by plants in response to fungal attack and how this affects plant-pathogen interaction, including susceptibility or resistance, remain elusive. We studied the dynamics in root metabolism during compatible and incompatible interactions between chickpea and Fusarium oxysporum f. sp. ciceri (Foc), using quantitative label-free proteomics and NMR-based metabolomics. Results demonstrated differential expression of proteins and metabolites upon Foc inoculations in the resistant plants compared with the susceptible ones. Additionally, expression analysis of candidate genes supported the proteomic and metabolic variations in the chickpea roots upon Foc inoculation. In particular, we found that the resistant plants revealed significant increase in the carbon and nitrogen metabolism; generation of reactive oxygen species (ROS), lignification and phytoalexins. The levels of some of the pathogenesis-related proteins were significantly higher upon Foc inoculation in the resistant plant. Interestingly, results also exhibited the crucial role of altered Yang cycle, which contributed in different methylation reactions and unfolded protein response in the chickpea roots against Foc. Overall, the observed modulations in the metabolic flux as outcome of several orchestrated molecular events are determinant of plant{\textquoteright}s role in chickpea-Foc interactions.

}, keywords = {Chickpea, fusarium oxysporum, Metabolomics, NMR, plant-pathogen interaction, proteomics}, issn = {1467-7644}, doi = {10.1111/pbi.12522}, author = {Kumar, Yashwant and Zhang, Limin and Panigrahi, Priyabrata and Dholakia, Bhushan B. and Dewangan, Veena and Chavan, Sachin G. and Kunjir, Shrikant M. and Wu, Xiangyu and Li, Ning and Rajmohanan, Pattuparambil R. and Kadoo, Narendra Y. and Giri, Ashok P. and Tang, Huiru and Gupta, Vidya S.} } @article {46724, title = {Biosynthesis and tissue-specific partitioning of camphor and eugenol in Ocimum kilimandscharicum}, journal = {Phytochemistry}, volume = {177}, year = {2020}, month = {SEP}, pages = {112451}, type = {Article}, abstract = {

In Ocimum kilimandscharicum, the relative volatile composition of camphor in leaves was as high as 55\%, while that of eugenol in roots was 57\%. These metabolites were differentially partitioned between the aerial and root tissues. Global metabolomics revealed tissue-specific biochemical specialization, evident by the differential distribution of 2588 putative metabolites across nine tissues. Next-generation sequencing analysis indicated differential expression of 51 phenylpropanoid and 55 terpenoid pathway genes in aerial and root tissues. By integrating metabolomics with transcriptomics, the camphor biosynthesis pathway in O. kilimandscharicum was elucidated. In planta bioassays revealed the role of geranyl diphosphate synthase (gpps) and borneol dehydrogenase (bdh) in camphor biosynthesis. Further, the partitioning of camphor was attributed to tissue-specific gene expression of both the pathway entry point (gpps) and terminal (bdh) enzyme. Unlike camphor, eugenol accumulated more in roots; however, absence of the eugenol synthase gene in roots indicated long distance transport from aerial tissues. In silico co-expression analysis indicated the potential involvement of ATP-binding cassette, multidrug and toxic compound extrusion, and sugar transporters in eugenol transport. Similar partitioning was evident across five other Ocimum species. Overall, our work indicates that metabolite partitioning maybe a finely regulated process, which may have implications on plant growth, development, and defense.

}, keywords = {Borneol dehydrogenase, Camphor, Eugenol, Geranyl diphosphate synthase, Lamiaceae, Metabolite partitioning, Metabolomics, Ocimum kilimandscharicum, Transcriptomics}, issn = {0031-9422}, doi = {10.1016/j.phytochem.2020.112451}, author = {Singh, Priyanka and Kalunke, Raviraj M. and Shukla, Anurag and Tzfadia, Oren and Thulasiram, V. Hirekodathakallu and Giri, Ashok P.} } @article {49242, title = {Trehalase inhibition in Helicoverpa armigera activates machinery for alternate energy acquisition}, journal = {JOURNAL OF BIOSCIENCES}, volume = {49}, year = {2024}, month = {JUL }, pages = {74}, type = {Journal Article}, keywords = {Energy metabolism, glucose, Metabolomics, Transcriptomics, trehalase, validamycin A}, issn = {0250-5991}, doi = {10.1007/s12038-024-00453-8}, author = {Tellis, Meenakshi and Mohite, Sharada and Joshi, Rakesh} } @article {49593, title = {Recommendations for sample selection, collection and preparation for NMR-based metabolomics studies of blood}, journal = {Metabolomics}, volume = {21}, year = {2025}, month = {MAY}, pages = {66}, type = {Review}, abstract = {

BackgroundMetabolic profiling of blood metabolites, particularly in plasma and serum, is vital for studying human diseases, human conditions, drug interventions and toxicology. The clinical significance of blood arises from its close ties to all human cells and facile accessibility. However, patient-specific variables such as age, sex, diet, lifestyle and health status, along with pre-analytical conditions (sample handling, storage, etc.), can significantly affect metabolomic measurements in whole blood, plasma, or serum studies. These factors, referred to as confounders, must be mitigated to reveal genuine metabolic changes due to illness or intervention onset.Review objectiveThis review aims to aid metabolomics researchers in collecting reliable, standardized datasets for NMR-based blood (whole/serum/plasma) metabolomics. The goal is to reduce the impact of confounding factors and enhance inter-laboratory comparability, enabling more meaningful outcomes in metabolomics studies.Key conceptsThis review outlines the main factors affecting blood metabolite levels and offers practical suggestions for what to measure and expect, how to mitigate confounding factors, how to properly prepare, handle and store blood, plasma and serum biosamples and how to report data in targeted NMR-based metabolomics studies of blood, plasma and serum.

}, keywords = {Blood, Metabolites, Metabolomics, NMR, Plasma, Serum, Standardization}, issn = {1573-3882}, doi = {10.1007/s11306-025-02259-7}, author = {Emwas, Abdul-Hamid and Zacharias, Helena U. and Alborghetti, Marcos Rodrigo and Gowda, G. A. Nagana and Raftery, Daniel and Mckay, Ryan T. and Chang, Chung-ke and Saccenti, Edoardo and Gronwald, Wolfram and Schuchardt, Sven and Leiminger, Roland and Merzaban, Jasmeen and Madhoun, Nour Y. and Iqbal, Mazhar and Alsiary, Rawiah A. and Shivapurkar, Rupali and Pain, Arnab and Shanmugam, Dhanasekaran and Ryan, Danielle and Roy, Raja and Schirra, Horst Joachim and Morris, Vanessa and Zeri, Ana Carolina and Alahmari, Fatimah and Kaddurah-Daouk, Rima and Salek, Reza M. and LeVatte, Marcia and Berjanskii, Mark and Lee, Brian and Wishart, David S.} }