Strain Tracking Reveals the Determinants of Bacterial Engraftment in the Human Gut Following Fecal Microbiota Transplantation

Abstract

Fecal microbiota transplantation (FMT) from healthy donor to patient is a treatment for microbiome-associated diseases. Although the success of FMT requires donor bacteria to engraft in the patient's gut, the forces governing engraftment in humans are unknown. Here we use an ongoing clinical experiment, the treatment of recurrent Clostridium difficile infection, to uncover the rules of engraftment in humans. We built a statistical model that predicts which bacterial species will engraft in a given host, and developed Strain Finder, a method to infer strain genotypes and track them over time. We find that engraftment can be predicted largely from the abundance and phylogeny of bacteria in the donor and the pre-FMT patient. Furthermore, donor strains within a species engraft in an all-or-nothing manner and previously undetected strains frequently colonize patients receiving FMT. We validated these findings for metabolic syndrome, suggesting that the same principles of engraftment extend to other indications.

Combined Endoscopic and Oral Fecal Microbiota Transplantation in Patients with Antibiotic-Dependent Pouchitis: Low Clinical Efficacy due to Low Donor Microbial Engraftment

“…Despite the small sample size, the results suggest that donor FMT engraftment in this patient group is surprisingly low despite a combined endoscopic and oral high-intensity FMT approach, which is considered one of the factors of success for FMT in patients with UC [14]. In contrast, engraftment of FMT in patients with a preserved colon in FMT trials for recurrent C. difficile infection and UC is at least 80% [15, 16]. Also, as shown in patients with UC undergoing FMT, the microbiome of recipients after transplant is more similar to the donor FMP than the pretransplant recipient sample engraftment, suggesting that FMT engraftment is a prerequisite for therapeutic success [16].…”

Genome‐wide association studies on the phyllosphere microbiome: Embracing complexity in host–microbe interactions

“…(), respectively. Subsequently, genomes assembled de novo from metagenomic reads, or obtained from a collection of publicly available genomes for plant‐associated microbes (Levy et al ., ), can be used as references to delineate and quantify the abundance of up to hundreds of unique strains per bacterial species in each phyllosphere DNA sample (Albanese and Donati, ; Smillie et al ., ). A challenge for these techniques, however, is separation of host and microbe DNA, as the typically larger size of host genomes limits the coverage of small microbial genomes when sequencing mixtures of host and microbe DNA.…”

Clinical translation of microbe‐based therapies: Current clinical landscape and preclinical outlook

“…By using multiple comparative points within the study, this is a stronger assessment of engraftment and cannot be attributed to the formulation residence time in the GI tract. This data, and other data not highlighted here, were used to validate a predictive model of FMT microbe engraftment, which included factors such as the composition of donor samples, the elapsed time since the transplant, type and duration of antibiotics, and route of administration . The model concluded that antibiotic type and use did not significantly affect microbe engraftment, despite conflicting clinical evidence .…”

“…Though it has been difficult to individually evaluate these factors, as they are far from uniform across FMT clinical trials, mathematical modeling approaches may be able to determine their relative importance. This has been shown with a predictive model of microbe engraftment, however, it is still unclear whether microbe engraftment necessarily correlates with therapeutic efficacy. Moving forward, the ability to identify these key factors, develop approaches to study them, and design formulations that consider them will be essential to the rational design of oral FMT therapeutics.…”

“…This data, and other data not highlighted here, 47,48 were used to validate a predictive model of FMT microbe engraftment, which included factors such as the composition of donor samples, the elapsed time since the transplant, type and duration of antibiotics, and route of administration. 49 The model concluded that antibiotic type and use did not significantly affect microbe engraftment, despite conflicting clinical evidence. 50 This discrepancy may indicate that engraftment does not always predict efficacy.…”