RT Journal Article SR Electronic T1 Predicting Vibrio cholerae infection and disease severity using metagenomics in a prospective cohort study JF bioRxiv FD Cold Spring Harbor Laboratory SP 2020.02.25.960930 DO 10.1101/2020.02.25.960930 A1 Inès Levade A1 Morteza M. Saber A1 Firas Midani A1 Fahima Chowdhury A1 Ashraful I. Khan A1 Yasmin A. Begum A1 Edward T. Ryan A1 Lawrence David A1 Stephen B. Calderwood A1 Jason B. Harris A1 Regina C. LaRocque A1 Firdausi Qadri A1 B. Jesse Shapiro A1 Ana A. Weil YR 2020 UL http://biorxiv.org/content/early/2020/02/25/2020.02.25.960930.abstract AB Background Susceptibility to Vibrio cholerae infection is impacted by blood group, age, and pre-existing immunity, but these factors only partially explain who becomes infected. A recent study used 16S rRNA amplicon sequencing to quantify the composition of the gut microbiome and identify predictive biomarkers of infection with limited taxonomic resolution.Methods To achieve increased resolution of gut microbial factors associated with V. cholerae susceptibility and identify predictors of symptomatic disease, we applied deep shotgun metagenomic sequencing to a cohort of household contacts of patients with cholera.Results Using machine learning, we resolved species, strains, gene families, and cellular pathways in the microbiome at the time of exposure to V. cholerae to identify markers that predict infection and symptoms. Use of metagenomic features improved the precision and accuracy of prediction relative to 16S sequencing. We also predicted disease severity, although with greater uncertainty than our infection prediction. Species within the genera Prevotella and Bifidobacterium predicted protection from infection, and genes involved in iron metabolism also correlated with protection.Conclusion Our results highlight the power of metagenomics to predict disease outcomes and suggest specific species and genes for experimental testing to investigate mechanisms of microbiome-related protection from cholera.