# NIH grant: Exploring microbial community metabolism and ecology (1R35GM166442-01) — retained record

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source: [us-gov-api](https://highsignal.app/data/us-gov-api) (us-gov-api:nih-reporter)  published 2026-08-01 00:00 ingested 2026-08-03 09:17

[original source ↗](https://reporter.nih.gov/project-details/1R35GM166442-01)

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NIH grant 1R35GM166442-01: Exploring microbial community metabolism and ecology
Institute: {'code': 'GM', 'abbreviation': 'NIGMS', 'name': 'National Institute of General Medical Sciences', 'admin_org_id': '12500024', 'admin_funding_url': ''}. PI: Alice G Cheng. Award: $451000.
Start: 2026-08-01T00:00:00.
ABSTRACT
The microbiome has been implicated in human health and disease where typically, a physiologic state will
correlate with a specific microbiome configuration. Using current sequencing datasets, we cannot know the
causes underlying this microbiota structure or whether a configuration correlates or drives a physiologic
state. Bridging this gap in our understanding between correlation and causation will require new approaches to
precision engineering of diverse microbial communities. In previous work, we developed a complex but defined
microbiome (hCom2) that stably engrafts in mice and occupies most environmental and nutritional niches in the
murine gut. To start, we propose a systematic interrogation of diet as a way to shape hCom2 configuration in
vitro. We will analyze hCom2 dynamics in the context of a panel of defined diets utilizing complex macronutrients
and growth environments. These experiments will reveal the importance of specific dietary macronutrients and
their interactions to promote the growth of specific microbial clades. Follow-up experiments will interrogate the
genetic and chemical underpinnings of these different microbiome configurations. We will also utilize differential
selection genomic signatures to predict microbiome digestion at the strain and community level. In the second
phase of the project, we will test the robustness of our observations in vivo and ex vivo. What will emerge from
this work is: (i) a mechanistic appreciation of how groups of microbes cooperate to disassemble complex
nutrients, and (ii) dietary and bioinformatic technology that can be used to model and reshape an existing
microbiome.
```



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