23 2 CORRESPONDING AUTHOR : jesse.shapiro@umontreal.ca 24 25 RUNNING TITLE: Stool metagenomics predicts cholera 26 ABSTRACT (word count: 196) 27 28Background: Susceptibility to Vibrio cholerae infection is impacted by blood group, age, and 29 pre-existing immunity, but these factors only partially explain who becomes infected. A recent 30 study used 16S rRNA amplicon sequencing to quantify the composition of the gut microbiome 31 and identify predictive biomarkers of infection with limited taxonomic resolution. 32
Methods:To achieve increased resolution of gut microbial factors associated with V. cholerae 33 susceptibility and identify predictors of symptomatic disease, we applied deep shotgun 34 metagenomic sequencing to a cohort of household contacts of patients with cholera. 35Results: Using machine learning, we resolved species, strains, gene families, and cellular 36 pathways in the microbiome at the time of exposure to V. cholerae to identify markers that 37 predict infection and symptoms. Use of metagenomic features improved the precision and 38 accuracy of prediction relative to 16S sequencing. We also predicted disease severity, although 39 with greater uncertainty than our infection prediction. Species within the genera Prevotella and 40Bifidobacterium predicted protection from infection, and genes involved in iron metabolism also 41 correlated with protection. 42
Conclusion:Our results highlight the power of metagenomics to predict disease outcomes and 43 suggest specific species and genes for experimental testing to investigate mechanisms of 44 microbiome-related protection from cholera. 45 46