MIMOSA2: A metabolic network-based tool for inferring mechanism-supported relationships in microbiome-metabolome data

BioRxiv : the Preprint Server for Biology
Cecilia NoeckerElhanan Borenstein


Motivation: Recent technological developments have facilitated an expansion of microbiome-metabolome studies, in which a set of microbiome samples are assayed using both genomic and metabolomic technologies to characterize the composition of microbial taxa and the concentrations of various metabolites. A common goal of many of these studies is to identify microbial features (species or genes) that contribute to differences in metabolite levels across samples. Previous work indicated that integrating these datasets with reference knowledge on microbial metabolic capacities may enable more precise and confident inference of such microbe-metabolite links. Results: We present MIMOSA2, an R package and web application for model-based integrative analysis of microbiome-metabolome datasets. MIMOSA2 uses reference databases to construct a community metabolic model based on microbiome data and uses this model to predict differences in metabolite levels across samples. These predictions are compared with metabolomics data to identify putative microbiome-governed metabolites and specific taxonomic contributors to metabolite variation. MIMOSA2 supports various input data types and can be customized to incorporate user-defined metabolic pat...Continue Reading

Methods Mentioned

amplicon sequencing

Software Mentioned

Flux Balance Analysis
biomartR R package
MIMOSA ( Model - based Integration of Metabolite Observations ...

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