An integrated strain-level analytic pipeline utilizing longitudinal metagenomic data.

The advancement in DNA-sequencing technology has enabled the high-resolution identification of microorganisms in microbial communities. Since different microbial strains within species may contain extreme phenotypic variability (e.g., nutrition metabolism, antibiotic resistance, and pathogen virulence), investigating within-species variations holds great scientific promise in understanding the underlying mechanism of microbial biological processes. To fully utilize the shared genomic variants across longitudinal metagenomics samples collected in microbiome studies, we develop an integrated analytic pipeline (LongStrain) for longitudinal metagenomics data. It concurrently leverages the information on proportions of mapped reads for individual strains and genome-wide SNVs to enhance the efficiency and accuracy of strain identification. Our method helps to understand strains' dynamic changes and their association with genome-wide variants. Given the fast-growing longitudinal studies of microbial communities, LongStrain which streamlines analyses of large-scale raw sequencing data should be of great value in microbiome research communities.