Algorithms for strain-resolved metagenomics

Division Of Basic Sciences - Nci

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Abstract

Long-read metagenomic sequencing has recently been used to recover complete bacterial genomes from various complex metagenomic communities. Metagenome assembly algorithms however are still facing challenges in deconvolution of closely-related species and strains. De novo assemblies of highly heterogeneous bacterial species typically result in tangled assembly graphs, where some sequences could be strain-specific, while others represent species-level consensus. Such partially-collapsed representation of bacterial strains does not take full advantage of the ability of long reads to phase small variants. In this work we develop an algorithm called MetaPhase that extends metagenomic phasing approaches to assembly graphs. The new method will allow for profiling of human metagenomes on the finest level of resolution, and provide insights into microbiome dynamics. In addition, complete bacterial assemblies facilitate discovery of known and new biosynthetic gene clusters, that encode important natural products.