Project Summary/Abstract
The Microbiota-Diet-Host interactions are critical to the balance of health and disease. Understanding
this axis will be important to the development of nutritional precision medicine. Although there are some
important discoveries where microbes make molecules that dramatically affect health, most of the molecules
produced by microbiota still remain structurally uncharacterized. In addition, even when a molecule is known
and the activity is known, this knowledge tends to be buried in papers and there is not a systematic
organization of this knowledge that can be readily leveraged by data scientists. This prevents a deep
mechanistic understanding of the microbiome. The goal of PAR-21-253 to which this application is applying to
and the accompanying RFA (RFA-DK-21-014) is to build a microbial metabolite knowledgebase that can be
used by the larger scientific community. In order to build the knowledgebase, the R01’s funded under PAR-21-
253 are discovery grants that will provide the knowledge of new microbial metabolites and their bioactivities.
This proposal will 1) obtain MS/MS signatures for up to 5,000,000 molecules synthesized, using
combinatorial/diversity driven synthesis, using diet and host precursors that are accessible to human
microbiota. The synthesis is biased towards common bio-transformations. This will be the largest
metabolomics reference data set ever assembled, even when all public and non-public libraries are combined;
2) we will use our big data mining strategies, especially our mass spectrometry search tools, to not only
discover what molecules are made by microbes, but also understand phenotype, disease, organ/tissue/biofluid,
food associations; 3) the newly discovered microbial molecules that are up or down regulated in inflammatory
bowel disease (and other gut metabolic disorders) will be further screened in cell-based assays and colitis
animal studies to understand the biological effects of the newly discovered microbial metabolites; 4) we will
transfer all the knowledge obtained by this R01 to the knowledgebase that will be created by the
accompanying RFA.
The PIs and Co-Is are well suited to help build the proposed knowledge base, due to their expertise in
microbial metabolomics (Dorrestein), synthesis (Dorrestein, Siegel), microbiome (Dorrestein, Knight,
Raffatellu), data science (Dorrestein, Knight) and having a track record of doing very large projects and share
newly discovered knowledge publicly for the benefit of the community – generally made available years before
any publication (Dorrestein, Knight).