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2 results on '"Jyothi Padiadpu"'

1. Multi‐omic network analysis identified betacellulin as a novel target of omega‐3 fatty acid attenuation of western diet‐induced nonalcoholic steatohepatitis

Author

Jyothi Padiadpu, Manuel Garcia‐Jaramillo, Nolan K Newman, Jacob W Pederson, Richard Rodrigues, Zhipeng Li, Sehajvir Singh, Philip Monnier, Giorgio Trinchieri, Kevin Brown, Amiran K Dzutsev, Natalia Shulzhenko, Donald B Jump, and Andrey Morgun

Subjects
betacellulin, docosahexaenoic acid, multi‐omic network, nonalcoholic steatohepatitis, ω3 PUFA, Medicine (General), R5-920, Genetics, QH426-470
Abstract

Abstract Clinical and preclinical studies established that supplementing diets with ω3 polyunsaturated fatty acids (PUFA) can reduce hepatic dysfunction in nonalcoholic steatohepatitis (NASH) but molecular underpinnings of this action were elusive. Herein, we used multi‐omic network analysis that unveiled critical molecular pathways involved in ω3 PUFA effects in a preclinical mouse model of western diet induced NASH. Since NASH is a precursor of liver cancer, we also performed meta‐analysis of human liver cancer transcriptomes that uncovered betacellulin as a key EGFR‐binding protein upregulated in liver cancer and downregulated by ω3 PUFAs in animals and humans with NASH. We then confirmed that betacellulin acts by promoting proliferation of quiescent hepatic stellate cells, inducing transforming growth factor–β2 and increasing collagen production. When used in combination with TLR2/4 agonists, betacellulin upregulated integrins in macrophages thereby potentiating inflammation and fibrosis. Taken together, our results suggest that suppression of betacellulin is one of the key mechanisms associated with anti‐inflammatory and anti‐fibrotic effects of ω3 PUFA on NASH.

Published
2023
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2. Identifying feasible metabolic routes in Mycobacterium smegmatis and possible alterations under diverse nutrient conditions

Author

Kuldeepkumar Ramnaresh Gupta, Anupam Singh, Nagasuma Chandra, Priyanka Baloni, and Jyothi Padiadpu

Subjects
Microbiology (medical), Nitrogen, media_common.quotation_subject, Mycobacterium smegmatis, Computational biology, Biology, Phenome, Bioinformatics, Microbiology, Genome, Adaptability, Feasible metabolic paths, Transcriptome, Phenotypic microarray, Adaptation, media_common, Microarray analysis techniques, Gene Expression Profiling, Molecular Sequence Annotation, biology.organism_classification, Microarray Analysis, Adaptation, Physiological, Carbon, Gene expression profiling, Gene redundancy, Gene expression, Metabolic Networks and Pathways, Research Article
Abstract

Background Many studies on M. tuberculosis have emerged from using M. smegmatis MC2155 (Msm), since they share significant similarities and yet Msm is non-pathogenic and faster growing. Although several individual molecules have been studied from Msm, many questions remain open about its metabolism as a whole and its capability to be versatile. Adaptability and versatility are emergent properties of a system, warranting a molecular systems perspective to understand them. Results We identify feasible metabolic pathways in Msm in reference condition with transcriptome, phenotypic microarray, along with functional annotation of the genome. Together with transcriptome data, specific genes from a set of alternatives have been mapped onto different pathways. About 257 metabolic pathways can be considered to be feasible in Msm. Next, we probe cellular metabolism with an array of alternative carbon and nitrogen sources and identify those that are utilized and favour growth as well as those that do not support growth. In all, about 135 points in the entire metabolic map are probed. Analyzing growth patterns under these conditions, lead us to hypothesize different pathways that can become active in various conditions and possible alternate routes that may be induced, thus explaining the observed physiological adaptations. Conclusions The study provides the first detailed analysis of feasible pathways towards adaptability. We obtain mechanistic insights that explain observed phenotypic behaviour by studying gene-expression profiles and pathways inferred from the genome sequence. Comparison of transcriptome and phenome analysis of Msm and Mtb provides a rationale for understanding commonalities in metabolic adaptability. Electronic supplementary material The online version of this article (doi:10.1186/s12866-014-0276-5) contains supplementary material, which is available to authorized users.

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