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Ravi Kumar, R. K.

Publications and source records attributed to Ravi Kumar, R. K..

2 recordsLinked to original sources

Ultra-sensitive metaproteomics (uMetaP) redefines the dark field of metaproteome, enables single-bacterium resolution, and discovers hidden functions in the gut microbiome

The gut microbiome is a complex ecosystem with significant inter-individual variability determined by hundreds of low-abundant species as revealed by genomic methods. Functional redundancy demands direct quantification of microbial biological functions to understand their influence on host physiology. This functional landscape remains unexplored due to limited sensitivity in metaproteomics methods. We present uMetaP, an ultra-sensitive metaproteomic solution combining advanced LC-MS technologies with a novel FDR- controlled de novo strategy. uMetaP improves the taxonomic detection limit of the gut "dark metaproteome" by 5,000-fold with exceptional quantification precision and accuracy. In a mouse model of colonic injury, uMetaP extended metagenomics findings and identified host functions and microbial metabolic networks linked to disease. We obtained orthogonal validation using transcriptomic data from biopsies of 204 Crohns patients and presented the concept of a "druggable metaproteome". Among the drug-protein interactions discovered are treatments for intestinal inflammatory diseases, showcasing uMetaPs potential for disease diagnostics and data-driven drug repurposing strategies.

microbiology↗

ChipFilter: Microfluidic Based Comprehensive Sample Preparation Methodology for Metaproteomics

Metaproteomic approach is an attractive way to describe a microbiome at the functional level, allowing the identification and quantification of proteins across a broad dynamic range as well as detection of post-translational modifications. However, it remains relatively underutilized, mainly due to technical challenges that should be addressed, including the complexity in extracting proteins from heterogenous microbial communities. Here, we show that a ChipFilter microfluidic device coupled to LC-MS/MS can successfully be used for identification of microbial proteins. Using cultures of E. coli, B. subtilis and S. cerevisiae, we have shown that it is possible to directly lyse the cells and digest the proteins in the ChipFilter to allow higher number of proteins and peptides identification than standard protocols, even at low cell density. The peptides produced are overall longer after ChipFilter digestion but show no change in their degree of hydrophobicity. Analysis of a more complex mixture of 17 species from the gut microbiome showed that the ChipFilter preparation was able to identify and estimate the amount of 16 of these species. These results show that ChipFilter can be used for the proteomic study of microbiomes, in particular in the case of low volume or low cell density.

biochemistry↗