# Optimized identification of therapeutic bacterial strains in ulcerative colitis

> **NIH NIH R01** · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · 2020 · $254,179

## Abstract

PROJECT SUMMARY
Ulcerative colitis (UC) is a chronic gut inflammatory condition thought to be caused by a combination of genetic
and environmental factors. Therapeutic options are only partially effective in inducing and maintaining
remission, and there is currently no cure for UC. Recent studies have found the microbiome of UC patients is
distinct compared to that of healthy controls, suggesting that the microbiome could be a promising therapeutic
target. Fecal microbiota transplant (FMT) has been extremely successful in the treatment of colitis caused by
Clostridium difficile infection, further demonstrating the potential for bacterial therapeutics. The recently
completed FOCUS (Faecal Microbiota Transplantation in Ulcerative Colitis) trial has demonstrated that FMT
from healthy donors can induce clinical remission in 27% of UC patients compared to only 8% in the placebo
group. However, we still lack an understanding of the exact mechanisms by which FMT is able to modulate
disease pathogenesis. The overarching hypothesis of this proposal is that UC remission after FMT is
induced by specific bacteria, and that accurate identification of bacterial strains will be paramount to
develop microbial therapeutics for UC. To test this hypothesis, we will first develop a novel ensemble
method to identify bacterial species and strains from deep metagenomic data. This method combines software
tools using a voting algorithm that is weighted based on the accuracy of each tool. The accuracy of this method
will be tested using microbial culture collections from UC patients, in silico simulations, and a bacterial mock
community as gold standards. We will then apply this approach to metagenomic data generated from the
FOCUS study in order to identify bacterial strains that are associated with UC remission. This will be performed
by using established supervised learning techniques, as well as through a novel method based on co-
occurrence network analysis that identifies clusters of bacteria that act synergistically. Based on these results,
we will finally validate our findings using a gnotobiotic model of colitis. The prophylactic and/or therapeutic
potential of candidate bacteria will be tested by inoculating them to gnotobiotic mice colonized with the
microbiota of UC patients and with colitis induced through the transfer of naïve T cells. Our proposal will be the
first to address the question of how specific bacteria modulate disease progression in a randomized trial of
FMT in UC through the development of more sensitive and accurate methods for strain characterization that
can be experimentally validated. The rational design of our strategy to identify therapeutic bacteria will produce
highly translational results that can be used to guide future clinical trials in UC.

## Key facts

- **NIH application ID:** 10017191
- **Project number:** 5R01DK114038-03
- **Recipient organization:** ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
- **Principal Investigator:** Jose C Clemente
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $254,179
- **Award type:** 5
- **Project period:** 2018-09-15 → 2021-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10017191

## Citation

> US National Institutes of Health, RePORTER application 10017191, Optimized identification of therapeutic bacterial strains in ulcerative colitis (5R01DK114038-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10017191. Licensed CC0.

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