Biology subjects

Sharma, V.

Publications and source records attributed to Sharma, V..

4 recordsLinked to original sources

bioRxiv2018

Genome-scale metabolic reconstruction and metabolic versatility of an obligate methanotroph Methylococcus capsulatus str. Bath

The increase in greenhouse gases with high global warming potential such as methane is a matter of concern and requires multifaceted efforts to reduce its emission and increase its mitigation from the environment. Microbes such as methanotrophs can assist in methane mitigation. To understand the metabolic capabilities of methanotrophs, a complete genome-scale metabolic model of an obligate methanotroph, Methylococcus capsulatus str. Bath was reconstructed. The model contains 535 genes, 898 reactions and 784 unique metabolites and is named iMC535. The predictive potential of the model was validated using previously-reported experimental data. The model predicted the Entner-Duodoroff (ED) pathway to be essential for the growth of this bacterium, whereas the Embden-Meyerhof-Parnas (EMP) pathway was found non-essential. The performance of the model was simulated on various carbon and nitrogen sources and found that M. capsulatus can grow on amino acids. The analysis of network topology of the model identified that six amino acids were in the top-ranked metabolic hubs. Using flux balance analysis (FBA), 29% of the metabolic genes were predicted to be essential, and 76 double knockout combinations involving 92 unique genes were predicted to be lethal. In conclusion, we have reconstructed a genome-scale metabolic model of a unique methanotroph Methylococcus capsulatus str. Bath. The model will serve as a knowledge-base for deeper understanding, as a platform for exploring the metabolic potential, and as a tool to engineer this bacterium for methane mitigation and industrial applications.

bioengineering↗

bioRxiv2018

A study of phenotypic plasticity of Saccharomyces cerevisiae in natural grape juices shed light on allelic variation under balanced selection.

The ability of a genotype to produce different phenotypes according to its surrounding environment is known as phenotypic plasticity. Within different individuals of the same species, phenotypic plasticity can vary greatly. This contrasted response is due to allelic variations and is caused by gene-by-environment interactions (GxE). Finding the genes and the cellular functions that interact with the environment is a current challenge for better understanding the genetic bases of phenotypic plasticity. In order to study the impact of natural allelic variations having a contrasted but relevant effect in a changing environment, we investigated the phenotypic response of the wine yeast Saccharomyces cerevisiae fermented in various grape juices. In this study we implemented a QTL mapping program using two independent offspring (~100 progeny) in order to investigate the molecular basis of yeast phenotypic response in a wine fermentation context. Thanks to high throughput sequencing approaches, both populations were genotyped, providing saturated genetic maps of thousands of markers. Linkage analyses allowed the detection of 78 QTLs including 21 with significant interaction with the nature of the fermented juice or fermentation conditions. Molecular dissection of a major QTL showed that the sulfite pump Ssu1p has a pleiotropic effect and impacts the phenotypic plasticity of several traits. Both alleles have positive effect according to external condition in phenotypes related to yeast fitness suggesting an example of balanced selection. All together these results pave the way for exploiting and deciphering the genetic determinism of phenotypic plasticity.

genetics↗

bioRxiv2017

Induction of autophagy by trehalose limits opportunistic mycobacterial infections in HIV-infected macrophages

Opportunistic bacterial infections amongst HIV-infected individuals pose serious health challenge. While immediate control of bacterial pathogens is typically attributed to innate defense mechanisms, whether HIV-mediated modulation of innate mechanisms like autophagy promote opportunistic infections, remains obscure. Using U1.1 and U937 macrophages, we show, HIV activation or infection inhibits autophagy and helps survival of pathogenic Mycobacterium tuberculosis and non-pathogenic non-tuberculous mycobacterial strains (NTMs) like Mycobacterium avium complex and Mycobacterium fortuitum. HIV achieves this by blocking xenophagy flux, which could be reversed by the autophagy inducer trehalose that kills intracellular Mtb and NTMs. We found trehalose acts as a PI (3,5) P2 agonist and activates TRPML1 to induce autophagy. Remarkably, trehalose treatment significantly reduced p24 levels in PBMCs infected with clinical HIV strains and in PBMCs derived from treatment-naive HIV patients. Taken together, our study highlights the immense potential of autophagy modulators in the therapeutic intervention of HIV and associated opportunistic infection.

immunology↗

bioRxiv2017

A Library of Phosphoproteomic and Chromatin Signatures for Characterizing Cellular Responses to Drug Perturbations

Though the added value of proteomic measurements to gene expression profiling has been demonstrated, profiling of gene expression on its own remains the dominant means of understanding cellular responses to perturbation. Direct protein measurements are typically limited due to issues of cost and scale; however, the recent development of high-throughput, targeted sentinel mass spectrometry assays provides an opportunity for proteomics to contribute at a meaningful scale in high-value areas for drug development. To demonstrate the feasibility of a systematic and comprehensive library of perturbational proteomic signatures, we profiled 90 drugs (in triplicate) in six cell lines using two different proteomic assays -- one measuring global changes of epigenetic marks on histone proteins and another measuring a set of peptides reporting on the phosphoproteome -- for a total of more than 3,400 samples. This effort represents a first-of-its-kind resource for proteomics. The majority of tested drugs generated reproducible responses in both phosphosignaling and chromatin states, but we observed differences in the responses that were cell line-and assay-specific. We formalized the process of comparing response signatures within the data using a concept called connectivity, which enabled us to integrate data across cell types and assays. Furthermore, it facilitated incorporation of transcriptional signatures. Consistent connectivity among cell types revealed cellular responses that transcended cell-specific effects, while consistent connectivity among assays revealed unexpected associations between drugs that were confirmed by experimental follow-up. We further demonstrated how the resource could be leveraged against public domain external datasets to recognize therapeutic hypotheses that are consistent with ongoing clinical trials for the treatment of multiple myeloma and acute lymphocytic leukemia (ALL). These data are available for download via the Gene Expression Omnibus (accession GSE101406), and web apps for interacting with this resource are available at https://clue.io/proteomics.\n\nHighlightsO_LIFirst-of-its-kind public resource of proteomic responses to systematically administered perturbagens\nC_LIO_LIDirect proteomic profiling of phosphosignaling and chromatin states in cells for 90 drugs in six different cell lines\nC_LIO_LIExtends Connectivity Map concept to proteomic data for integration with transcriptional data\nC_LIO_LIEnables recognition of unexpected, cell type-specific activities and potential translational therapeutic opportunities\nC_LI

systems biology↗