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Integrative Computational and Experimental Approaches to Assess Metabolic Complementarity for Precision Microbiota Transplantation Therapies

Award Number: R21AT013617
ORGANIZATION: CENTER FOR DRUG EVALUATION AND RESEARCH, NIH
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 04/01/2026
PERIOD OF PERFORMANCE END DATE: 03/31/2028

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Integrative Computational and Experimental Approaches to Assess Metabolic Complementarity for Precision Microbiota Transplantation Therapies - ABSTRACT The gut microbiome is a cornerstone of host health, shaping immune responses, metabolism, and resilience to disease. However, attempts to treat dysbiosis via fecal microbiota transplantation (FMT) are frequently limited by colonization resistance, where resident microbes inhibit new strains from being introduced. Current reliance on broad-spectrum antibiotics to mitigate this competition typically results in only transient engraftment and limited therapeutic efficacy. Furthermore, despite refinements in donor selection and administration, no models or pipelines exist to allow clinicians to accurately predict FMT outcomes or systematically introduce microbiota into the highly variable patient microbiomes. There is a critical gap in understanding how to identify which microbial communities and donor microbiomes can integrate robustly into individual recipients. This proposal addresses this gap by leveraging computational and experimental approaches to identify “orthogonal” donor communities that bypass metabolic niche competition. We hypothesize that donor consortia whose metabolic requirements differ when compared to the FMT recipient microbiota are more likely to stably engraft. In Aim 1, we will use metabolic models (MICOM) to extract metabolic features from microbial communities and train statistical classifiers that predict FMT engraftment outcomes between microbiomes in both murine and human cohorts. In Aim 2, we will develop a culturomics-based strategy to experimentally profile unused niches within recipient microbiomes and introduce donor-derived communities specific to those niches. We anticipate that these aims will yield a novel computational framework for donor-recipient matching as well as an experimental pipeline to identify niche-associated microbial communities that are capable of engrafting in target recipients. These precise and predictable microbial engraftment strategies will allow for personalized microbiome therapies and more durable non-pharmacological treatments for conditions linked to dysbiosis.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = $428,855 )
2026	2026	UNIVERSITY OF CALIFORNIA, SAN DIEGO	9500 GILMAN DR	LA JOLLA	CA	92093	SAN DIEGO	USA	Research and Training in Complementary and Integrative Health	000	1	3/26/2026	NEW	$428,855
														Subtotal = $428,855

Grand Total All Awards = $428,855

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Integrative Computational and Experimental Approaches to Assess Metabolic Complementarity for Precision Microbiota Transplantation Therapies

Award Number: R21AT013617

ORGANIZATION: CENTER FOR DRUG EVALUATION AND RESEARCH, NIH

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 04/01/2026

PERIOD OF PERFORMANCE END DATE: 03/31/2028

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