Predicting Vibrio cholerae Infection and Disease Severity Using Metagenomics in a Prospective Cohort Study. (1st July 2020)

• Record Type: Journal Article
• Authors: Levade, Inès; Saber, Morteza M; Midani, Firas S; Chowdhury, Fahima; Khan, Ashraful I; Begum, Yasmin A; Ryan, Edward T; David, Lawrence A; Calderwood, Stephen B; Harris, Jason B; LaRocque, Regina C; Qadri, Firdausi; Shapiro, B Jesse; Weil, Ana A
• Is Part Of: Journal of infectious diseases. Volume 223:Number 2(2021)
• Page Start: 342
• Page End: 351
• Publication Date: 2020-07-01
• Subjects: Vibrio cholera -- cholera -- microbiome -- machine learning -- metagenomics; Communicable diseases -- Periodicals; Diseases -- Causes and theories of causation -- Periodicals; Medicine -- Periodicals; Communicable Diseases -- Periodicals; Electronic journals; 616.9
• DOI: 10.1093/infdis/jiaa358
• Languages: English
• ISSNs: 0022-1899

Abstract

Abstract: Background: Susceptibility to Vibrio cholerae infection is affected by blood group, age, and preexisting immunity, but these factors only partially explain who becomes infected. A recent study used 16S ribosomal RNA 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 were 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. Abstract : Cholera infection and disease severity can be predicted using metagenomic sequencing of the gut microbiome before infection in a prospective cohort, and the results suggest potentially protective bacterial species and genes.