Fecal microbiota transplants (FMTs) are one of the most researched microbiome-based therapeutics that aim to substitute an unfavorable resident gut microbiota with a favorable one from a healthy donor. This intervention has shown efficacy for managing recurrent Clostridioides difficile infections and emerging clinical evidence shows its potential for inflammatory bowel disease, neurological disorders, obesity and improving responses to immune checkpoint inhibitors.
Despite clinical data supporting FMT efficacy, drivers of the response to this intervention are not fully understood. Two meta-analyses conducted by Schmidt et al. and Ianiro et al. of metagenomics-based clinical trials in Nature Medicine explore factors linked to FMT success in different disease indications from recurrent C. difficile infection to metabolic syndrome.
In contrast to a synthetic drug, fecal transplants are live materials, and it is difficult to predict whether their efficacy is driven by the presence of live microorganisms, or their metabolites present in donor’s stool or the shift of problematic species in recipients. While Ianiro et al. found that improved strain engraftment in the recipient was related to improved clinical outcomes, Schmidt et al. did not report an association between donor strain colonization and clinical outcomes. In an accompanying observation, Aonghus Lavelle and Harry Sokol explained that “this disagreement may be due to the different studies included and the different approaches used for defining, tracking and modeling strain and community dynamics”.
Matching between donor and recipient – in terms of the donor’s clinical status and microbiome factors – and the technical characteristics of the procedure, explained ecological dynamics after FMT and its clinical success. Both studies found combined routes of administration (i.e., FMT by capsules and colonoscopy), antibiotic treatment before FMT and infectious disease indications increased the likelihood of engraftment in the recipient.
Microbiome-related factors such as abundance of the recipient’s species and the similarity of the gut microbiota between donor and recipient influenced colonization patterns. For instance, the incorporation of donor strains or persistence of recipient strains was more common if the strains belonging to the same species were present in either the donor or the recipient before FMT, which was evident in Bacteroides and Faecalibacterium. Belonging to specific phyla may also explain engraftment success as members of the Bacteroidetes and Actinobacteria phyla (such as Bifidobacteria) showed higher engraftment than members of Firmicutes and Proteobacteria.
The dominance by donor strains and/or new or previously undetectable strains in the post-FMT microbiome was highly predictable and was driven by the richness of the recipient’s low species richness and the difference between donor and recipient, which is a hallmark of recurrent C. difficile infection and ulcerative colitis. The recipient’s gut microbiome exerted a key effect in predicting donor microbiome engraftment, with certain species inhibiting colonization of donor species and other species acting as facilitators.
By using simulation-based approaches, Ianiro et al. identified donors with the potential to shape the recipient’s microbial composition towards specific gut microbiota composition or desired health outcomes. These findings open the potential of machine learning models to develop tailored FMT interventions based on the selection of an optimal donor.
Lavelle and Sokol acknowledged certain limitations in both studies: “It is important to note that other unmeasured host factors, such as host immunity and diet, might influence colonization success. Furthermore, it is possible that the magnitude of donor colonization may be more important for therapeutic efficacy in certain conditions – such as chronic immune-mediated ones – than in others (such as recurrent C. difficile infection) where the primary defect is microbial, and most donor communities will suffice to re-boot the depleted microbiome environment”.
Overall, these studies highlight potential predictors for the clinical success of FMT, including donor-related factors (e.g., microbial richness), recipient-related factors (e.g., species shared between the donor and the recipient before FMT) and procedure-related factors (e.g., route of administration and recipient pre-conditions). However, there is still the need to track and measure gut microbiome changes that affect efficacy outcomes. For a further reading on determinants of success in FMT see this new review published after the two studies covered in this post.
References:
Schmidt TSB, Li SS, Maistrenko OM, et al. Drivers and determinants of strain dynamics following fecal microbiota transplantation. Nat Med. 2022; 28(9):1902-1912. doi: 10.1038/s41591-022-01913-0.
Ianiro G, Punčochář M, Karcher N, et al. Variability of strain engraftment and predictability of microbiome composition after fecal microbiota transplantation across different diseases. Nat Med. 2022; 28(9):1913-1923. doi: 10.1038/s41591-022-01964-3.
Lavelle A, Sokol H. Understanding and predicting the efficacy of FMT. Nat Med. 2022; 28(9):1759-1760. doi: 10.1038/s41591-022-01991-0.
