Harnessing genome synteny to identify microbial strain sharing and within host evolution

In bacteria, phenotypic variance is often observed between strains of the same species.

In the human-gut microbiome, specific strains emerge due to within-host evolution and can occasionally be transferred to or from other hosts. Surveilling strains of the same species, within and between individuals, can further our knowledge about the way in which microbial diversity is generated and maintained in host populations. Existing methods to estimate the biological relatedness of similar strains usually rely on either Single Nucleotide Variant detection, an error-prone process owing to sequencing errors and natural variation in the population, or on the analysis of pangenomes, which could be limited by the requirement for an extensive gene database. To overcome these limitations, we developed SynTracker, a new method to track closely related strains based on genome-microsynteny (i.e., the comparison of the arrangement of sequence blocks in two chromosomes) of homologous genomic regions between pairs of metagenomic assemblies or genomes. Our method is executed in a species-specific manner, has a low sensitivity to SNVs, does not require a preexisting database, and can correctly classify genomes (complete or partially assembled) and metagenomic samples using a fraction of the full genome length. When applied to metagenomic datasets, we detected person-specific strains with high sensitivity and specificity, strain-sharing events in mother-infant pairs, and created species-specific strain-similarity networks. Our method could be used to study the population structure of specific microbial species between and within environments, to identify evolutionary trajectories in longitudinal datasets, and to further our understanding of strain sharing networks.