Strain-resolved microbiome sequencing reveals mobile elements that drive bacterial competition on a clinical timescale

Abstract

Although shotgun short-read sequencing has facilitated the study of strain-level architecture within complex microbial communities, existing metagenomic approaches often cannot capture structural differences between closely related co-occurring strains. Recent methods, which employ read cloud sequencing and specialized assembly techniques, provide significantly improved genome drafts and show potential to capture these strain-level differences. Here, we apply this read cloud metagenomic approach to longitudinal stool samples from a patient undergoing hematopoietic cell transplantation. The patients microbiome is profoundly disrupted and is eventually dominated by Bacteroides caccae. Comparative analysis of B. caccae genomes obtained using read cloud sequencing together with metagenomic RNA sequencing allows us to predict that particular mobile element integrations result in increased antibiotic resistance, which we further support using in vitro antibiotic susceptibility testing. Thus, we find read cloud sequencing to be useful in identifying strain-level differences that underlie differential fitness.