Bacterial Corrinoid Metabolism Across Scales: From Molecular Specificity to Community Dynamics
Project Number5R35GM139633-05
Contact PI/Project LeaderTAGA, MICHIKO E.
Awardee OrganizationUNIVERSITY OF CALIFORNIA BERKELEY
Description
Abstract Text
Project Summary/Abstract
Microbial communities inhabit nearly all environments on earth, including the human body, where they can
influence health in myriad ways. These communities are often composed of hundreds or more species that form
networks of metabolic interactions. Because metabolic interactions are complex and difficult to study at a
molecular level, my research program focuses on interactions involving one family of metabolites – corrinoid
cofactors – as a model to understand metabolic interactions among bacteria. Corrinoids are the vitamin B12 family
of cobalt-containing metabolites that are used as enzyme cofactors for a variety of reactions. Corrinoids, like
many amino acids, nucleobases, and other cofactors, are synthesized by only a fraction of bacteria that use
them, and therefore are considered to be shared metabolites. Corrinoids are unique in their structural diversity,
with over a dozen different forms discovered and up to eight of these forms found in microbial community
samples, including the human gut. This structural diversity is a significant factor in microbial interactions because
most bacteria are selective in the corrinoids they can use. The hypothesis driving this work is that structurally
distinct corrinoids can be used as handles to manipulate microbial communities. Our previous NIGMS-funded
research has laid the groundwork for the proposed research by establishing experimental methods; discovering
and characterizing new genes; investigating corrinoid selectivity in enzymes, riboswitches, and bacteria; and
creating a bioinformatic pipeline to predict corrinoid metabolism in bacteria. Our long-term vision is to build on
this foundation to generate a newly detailed understanding of microbial community interactions through the study
of corrinoids across scales, from molecular mechanisms to whole community perturbations. We will achieve this
goal by (1) identifying genome sequence signatures predictive of bacterial corrinoid preferences in corrinoid-
dependent enzymes and riboswitches, with an emphasis on evolutionary approaches and (2) investigating the
molecular basis of corrinoid-dependent community dynamics by applying sequencing, culture-dependent, and
genetic approaches to a model human gut-derived enrichment culture. As a test of our ability to understand and
predict corrinoid-based metabolism and community dynamics, we will design and build bacterial strains with
corrinoid-dependent metabolic networks, as well as consortia of bacteria with predictable dynamics. This
research will be accomplished by using a combination of genetics, biochemistry, microbiology, and
bioinformatics, building upon the past research of my group. Our work on corrinoids will not only serve as a
model for microbial community interactions across systems, but may also lead to the development of new
methods to alter microbial communities for beneficial outcomes.
Public Health Relevance Statement
Project Narrative
A more complete understanding of the complex microbial communities that inhabit the human body is needed in
order to develop new strategies to manipulate these communities for beneficial health outcomes. This research
addresses this need by examining the vitamin B12 family of essential metabolites that are shared among bacteria
and can influence microbial community structure.
NIH Spending Category
No NIH Spending Category available.
Project Terms
AddressAmino AcidsAutomobile DrivingBacteriaBiochemical PathwayBiochemistryBioinformaticsCobaltCoenzymesCommunitiesComplexCorrinoidsDevelopmentEnvironmentEnzymesFamilyFoundationsFundingGenesGeneticGenomeGoalsHealthHumanHuman bodyMetabolicMetabolismMethodsMicrobiologyModelingMolecularNational Institute of General Medical SciencesOutcomePlanet EarthReactionResearchSamplingSpecificityStructureSystemTestingVitamin B 12Workbioinformatics pipelinecofactordesigngenetic approachhuman modelmicrobial communitymicroorganism interactionnucleobasepredictive signaturepreferenceprograms
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