New technology can track beneficial bacteria after fecal microbiota transplants

Researchers at the Icahn School of Medicine at Mount Sinai and their collaborators have developed a new technology to track beneficial bacteria after fecal microbiota transplants (FMT). The approach provides a detailed view of how donor microbes take hold and persist in the patients' gut-not only which bacteria successfully colonized but how they change over time. These insights may guide the design of safer and more effective microbiome-based therapies.

The study was published in the October 22 online issue of Nature Microbiology [DOI: https://doi.org/10.1038/s41564-025-02164-8].

FMT-the transfer of stool from a healthy donor into a patient's intestine-has been proven highly effective in treating Clostridioides difficile infection and is being explored for other conditions, such as inflammatory bowel disease (IBD) and cancer. Yet it has remained unclear which bacterial strains are responsible for long-term recovery and how they adapt within their new host environment.

The new approach harnesses long-read DNA sequencing, which reads much longer stretches of a microbe's genetic code than traditional techniques, with a computational method developed at Mount Sinai called LongTrack. Together, they allow scientists to distinguish even closely related bacterial strains and identify each one's unique genetic "fingerprint." This enables researchers to follow donor bacteria from the time of transplant through up to five years of adaptation in the patient's gut.

We can follow donor bacteria strain by strain with a level of reliability and scalability that wasn't possible before using approaches that were based on short-read sequencing. It gives us insight into what happens to the hundreds of donor bacteria after fecal transplants, how they adapt to new patients' gastrointestinal environments, and points the way toward safer, more consistent, and ultimately more precise treatments."

Gang Fang, PhD, senior and corresponding author, Professor of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai

Using this approach, the team collaborated with study co-author Jeremiah Faith, PhD, Professor of Immunology and Immunotherapy at the Icahn School of Medicine at Mount Sinai. The team analyzed stool samples from FMT donors and recipients treated for C. difficile infection and IBD. Samples collected before and after treatment, including some taken up to five years later, showed that many donor bacteria took hold and persisted in the recipients' microbiome. Some strains even displayed genetic mutations indicating adaptation to their new hosts, suggesting that different gut environments can shape bacterial evolution from one individual to another, says Dr. Fang.

By pinpointing which bacteria successfully colonize after FMT, the study provides a roadmap for systematically identifying mixtures of beneficial microbes that could be developed as novel microbiome interventions. These could replace or improve upon whole-stool transplants with treatments that are safer, more predictable, and easier to regulate.

"Our findings bring us closer to precision medicine for the microbiome," says Dr. Fang. "We can now track beneficial bacteria reliably and on a large scale over time, and importantly, understand the genetic mutations involved in their adaptation in the recipients-a key step toward designing treatments that are both effective and consistent."

Next, the researchers plan to apply the same approach to larger patient cohorts and to additional diseases in which the gut microbiome plays a role, building on previous and future FMT studies across multiple human conditions. They aim to use LongTrack to identify beneficial bacterial strains that could form the basis of next-generation microbial therapeutics.

The paper is titled "Long-read metagenomics for strain tracking after faecal microbiota transplant."

The study's authors, as listed in the journal, are Yu Fan, Mi Ni, Varun Aggarwala, Edward A. Mead, Magdalena Ksiezarek, Lei Cao, Michael A. Kamm, Thomas J. Borody, Sudarshan Paramsothy, Nadeem O. Kaakoush, Ari Grinspan, Jeremiah J. Faith, and Gang Fang.

This work was supported by the National Institutes of Health (NIH) under grant number R35 GM139655.