A framework to trace microbial engraftment at the strain level during fecal microbiota transplantation

BackgroundFecal microbiota transplantation (FMT) may treat microbiome-associated diseases effectively. However, the mechanism and pattern of the FMT process require expositions. Previous studies indicated the necessity to track the FMT process at the microbial strain level. At this moment, shotgun metagenomic sequencing enables us to study strain variations during the FMT. ResultWe implemented a software package PStrain-tracer to study microbial strain variations during FMT from the shotgun metagenomic sequencing data. The package visualizes the strain alteration and traces the microbial engraftment during the FMT process. We applied the package to two typical FMT datasets: one ulcerative colitis (UC) dataset and one Clostridium difficile infection (CDI) dataset. We observed that when the engrafted species has more than one strain in the source sample, 99.3% of the engrafted species will engraft only a subset of strains. We further confirmed that the all-or-nothing manner unsuited the engraftment of species with multiple strains by heterozygous single-nucleotide polymorphisms (SNPs) count, revealing that strains prefer to engraft independently. Furthermore, we discovered a primary determinant of strain engrafted success is their proportion in species, as the engrafted strains from the donor and the pre-FMT recipient with proportions 33.10 % (p-value = 6e - 06) and 37.08 % (p-value = 9e - 05) significantly higher than ungrafted strains on average, respectively. All the datasets indicated that the diversity of strains bursts after FMT and decreases to one after eight weeks for twelve species. Previous studies neglected strains with their corresponding species showing insignificant differences between different samples. With the package, from the UC dataset, we successfully determined the strain variations of the species Roseburia intestinalis, a beneficial species reducing intestinal inflammation, colonized in the cured UC patient being engrafted from the donor, even if the patient hosted the same species yet before treatment. We found seven strains in donors from the CDI dataset and one strain in pre-FMT recipients from eight species that associated CDI FMT failure. ConclusionPStrain-tracer is the first framework that tracks strain alterations in metagenomic sequencing data of FMT. PStrain-tracer implemented several methods specialized for FMT experiment samples, such as visualization of strains abundance alteration in the FMT experiment and determinant strains detection in FMT failure. We applied PStrain-tracer on two published datasets, uncovered novel strains related to FMT failure, and demonstrated the necessity of analyzing the whole-genome shotgun metagenomic data of FMT at the strain level. We also developed an online visualizer of PStrain-tracer for the users to adjust their visualized results online. The package is available at https://github.com/deepomicslab/PStrain-tracer.