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Russell, R. K.

Publications and source records attributed to Russell, R. K..

2 recordsLinked to original sources

Pan-repository analysis reveals a drug-activating function of microbial bile acid conjugation

Microbially modified bile acids shape host physiology by regulating nutrient absorption, glucose homeostasis, circadian rhythms and thermoregulation. Here we identify a previously unrecognized drug-activating function of microbial bile acid conjugation. By systematically mining human LC-MS/MS datasets across public repositories and linking uncharacterized bile acid spectra to health-associated metadata, we discovered conjugates of the >75-year-old anti-inflammatory drug 5-aminosalicylic acid (5-ASA) with primary and secondary bile acids, including cholic, deoxycholic and lithocholic acids. These bile acid-drug conjugates were detected specifically in individuals treated with 5-ASA or its prodrugs. Multiple gut bacteria, including members of the Bacteroidota and Bacillota, generated cholyl-5-ASA in vitro, and bile salt hydrolase-associated transaminase activity was required for conjugate formation. In a mouse model of colitis, cholyl-5-ASA was associated with reduced intestinal inflammatory pathology and showed markedly enhanced activation of PPAR-{gamma} in cell-based reporter assays compared with 5-ASA alone. Consistent with this activity, cholyl-5-ASA elicited selective immunophenotypic changes in CD4 T cells in vitro, including increased Foxp3+ regulatory T cells. Together with prior evidence that 5-ASA efficacy depends on the microbiome, these findings support a model in which microbial bile acid conjugation represents a key activation step for 5-ASA therapy. More broadly, this work demonstrates how pan-repository metabolomics can uncover previously unrecognized microbiome-dependent chemical functions with direct therapeutic relevance.

biochemistry↗

CViewer: A Java-based statistical framework for integration of shotgun metagenomics with other omics datasets

We have developed CViewer, a java-based framework to consolidate, visualize, and explore enormous amount of information recovered from shotgun sequencing experiments. This information includes and integrates all levels of gene products, mRNA, protein, metabolites, as well as their interactions in a single platform. The software provides a single platform to give statistical inference, and employs algorithms, some borrowed from numerical ecology literature to allow exploratory as well as hypothesis driven analyses. The end product is a highly interactive toolkit with multiple document interface, that makes it easier for a person without specialized knowledge to perform analysis of multiomics datasets and unravel biologically relevant hypotheses. As a proof-of-concept, we have used CViewer to explore two distinct metagenomics datasets: a dietary intervention study to understand Crohns disease changes during a dietary treatment to include remission, as well as a gut microbiome profile for an obesity dataset comparing subjects who suffer from obesity of different aetiologies and against controls who were lean.

bioinformatics↗