Microbial Strain Engraftment, Persistence and Replacement after Fecal Microbiota Transplantation

Abstract

Fecal Microbiota Transplantation (FMT) has been clinically validated as a treatment for recurrent Clostridioides difficile infection (rCDI) and associated with the compositional and functional restoration of the patient gut microbiota. To characterize the underlying microbiota dynamics of patient and donor strain engraftment, persistence and replacement during FMT, we combined new and existing metagenomic sequence data and developed the bioinformatic SameStr program for the species-specific detection of shared subspecies lineages, including non-dominant strains. We show that personal gut strain profiles are identifiable and detect engraftment after successful and failed FMT in rCDI recipients, specifically of those donor strains that are abundant and stable in healthy individuals. We identify microbiota parameters in statistical models to predict donor species and strain engraftment, as well as recipient strain persistence and replacement. Our findings raise concerns over FMT consequences from questionable donors and suggest that personalized FMT strategies are feasible for targeted microbiota modulation.

Strain inheritance and neonatal gut microbiota development: a meta-analysis

“…However, species or genus-level microbiota compositions provide insufficient taxonomic resolution to infer microbial transfer, as distinct sub-lineages within genera or even species can be shared between unrelated samples or individuals (Lloyd-Price et al, 2017). Therefore, in order to detect microbial transfer between infants and their parents and microbial persistence in infants over time, we used the recently developed SameStr program from our group (Podlesny and Fricke, 2020) to identify shared unique subspecies taxa, i.e. strains, between metagenomes from our combined dataset.…”

“…Various definitions of microbial strains exist, based on biological and evolutionary concepts, as well as phenotypic or phylogenetic detection methods (Van Rossum et al, 2020; Yan et al, 2020). SameStr applies a conservative approach to call shared strains, using restrictive thresholds to detect highly similar subspecies genetic variants in distinct metagenomic samples, as indication for strain persistence or transfer between the corresponding microbiomes (Podlesny and Fricke, 2020). Shared strains would be unique in the sense that the corresponding subspecies lineages would only be found in related metagenomes (e.g.…”

“…from mothers or infants without microbiota contact). To identify individual microbial strains, detect overlapping microbiota strain profiles and map microbial exchange based on unique shared strains, the recently introduced SameStr program from our group was used (Podlesny and Fricke, 2020). As an adaptation of the StrainPhlAn tool (Truong et al, 2017), it uses the clade-specific marker gene database from MetaPhlAn2 (Segata et al, 2012) to detect species-specific strains while also allowing for shared strain calls between non-dominant members of multi-strain species populations - a feature which is not available through StrainPhlAn and increases the rate of detected shared strain events between related but not unrelated samples (Podlesny and Fricke, 2020).…”

“…Shared strains were identified with the recently released SameStr program (Podlesny and Fricke, 2020), leveraging within-species phylogenetic sequence variations in clade-specific marker genes. For this, MetaPhlAn2 marker alignments were converted to single nucleotide variant (SNV) profiles, filtered, merged and compared between metagenomes based on maximum variant profile similarity (MVS) that takes all detected single nucleotide variants (SNVs) into consideration, including polymorphic sites (≥10% allele frequency) resulting from multiple strains representing the same species.…”

“…We sought to expand on previous studies by carrying out a large-scale, comprehensive meta-analysis of available metagenomic sequence data from neonates, infants and adolescents, their siblings, mothers and fathers and, in some cases, even grandparents. We used our recently introduced SameStr program (Podlesny and Fricke, 2020) for the sensitive, species-specific shared strains detection, in order to infer microbial transfer to the neonatal and infant microbiota, as well as microbial persistence during infancy, childhood and adolescence. We combined available metagenomes from nine distinct studies, comprising over 1944 samples, which represents the largest meta-analysis of the neonatal and infant microbiota so far.…”