Dataset Information

Human Gut Microbiota Predicts Susceptibility to Vibrio cholerae Infection.

ABSTRACT:

Background

Cholera is a public health problem worldwide, and the risk factors for infection are only partially understood.

Methods

We prospectively studied household contacts of patients with cholera to compare those who were infected to those who were not. We constructed predictive machine learning models of susceptibility, using baseline gut microbiota data. We identified bacterial taxa associated with susceptibility to Vibrio cholerae infection and tested these taxa for interactions with V. cholerae in vitro.

Results

We found that machine learning models based on gut microbiota, as well as models based on known clinical and epidemiological risk factors, predicted V. cholerae infection. A predictive gut microbiota of roughly 100 bacterial taxa discriminated between contacts who developed infection and those who did not. Susceptibility to cholera was associated with depleted levels of microbes from the phylum Bacteroidetes. By contrast, a microbe associated with cholera by our modeling framework, Paracoccus aminovorans, promoted the in vitro growth of V. cholerae. Gut microbiota structure, clinical outcome, and age were also linked.

Conclusion

These findings support the hypothesis that abnormal gut microbial communities are a host factor related to V. cholerae susceptibility.

SUBMITTER: Midani FS

PROVIDER: S-EPMC6047457 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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Publications

Human Gut Microbiota Predicts Susceptibility to Vibrio cholerae Infection.

Midani Firas S FS Weil Ana A AA Chowdhury Fahima F Begum Yasmin A YA Khan Ashraful I AI Debela Meti D MD Durand Heather K HK Reese Aspen T AT Nimmagadda Sai N SN Silverman Justin D JD Ellis Crystal N CN Ryan Edward T ET Calderwood Stephen B SB Harris Jason B JB Qadri Firdausi F David Lawrence A LA LaRocque Regina C RC

The Journal of infectious diseases 20180701 4

<h4>Background</h4>Cholera is a public health problem worldwide, and the risk factors for infection are only partially understood.<h4>Methods</h4>We prospectively studied household contacts of patients with cholera to compare those who were infected to those who were not. We constructed predictive machine learning models of susceptibility, using baseline gut microbiota data. We identified bacterial taxa associated with susceptibility to Vibrio cholerae infection and tested these taxa for interac ...[more]

PMID: 29659916

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Project description:Given the global burden of diarrhoeal diseases, it is important to understand how members of the gut microbiota affect the risk for, course of, and recovery from disease in children and adults. The acute, voluminous diarrhoea caused by Vibrio cholerae represents a dramatic example of enteropathogen invasion and gut microbial community disruption. Here we conduct a detailed time-series metagenomic study of faecal microbiota collected during the acute diarrhoeal and recovery phases of cholera in a cohort of Bangladeshi adults living in an area with a high burden of disease. We find that recovery is characterized by a pattern of accumulation of bacterial taxa that shows similarities to the pattern of assembly/maturation of the gut microbiota in healthy Bangladeshi children. To define the underlying mechanisms, we introduce into gnotobiotic mice an artificial community composed of human gut bacterial species that directly correlate with recovery from cholera in adults and are indicative of normal microbiota maturation in healthy Bangladeshi children. One of the species, Ruminococcus obeum, exhibits consistent increases in its relative abundance upon V. cholerae infection of the mice. Follow-up analyses, including mono- and co-colonization studies, establish that R. obeum restricts V. cholerae colonization, that R. obeum luxS (autoinducer-2 (AI-2) synthase) expression and AI-2 production increase significantly with V. cholerae invasion, and that R. obeum AI-2 causes quorum-sensing-mediated repression of several V. cholerae colonization factors. Co-colonization with V. cholerae mutants discloses that R. obeum AI-2 reduces Vibrio colonization/pathogenicity through a novel pathway that does not depend on the V. cholerae AI-2 sensor, LuxP. The approach described can be used to mine the gut microbiota of Bangladeshi or other populations for members that use autoinducers and/or other mechanisms to limit colonization with V. cholerae, or conceivably other enteropathogens.

Project description:Distribution, investigation, surveillance and control (DISC) of cholera outbreaks in endemic/non-endemic regions has been a concerted approach towards the management of the causal pathogen. Relevant organization, government, health systems and the public have implemented several steps towards controlling the menace, yet pathogen continues to occur with diverse phenotypes/genotypes of high clinical and epidemiological relevance. The study determines antibiotic susceptibility/resistance pattern of Vibrio cholerae isolates retrieved from six domestic water sources between March and August 2018. Serological and molecular typing methods (polymerase chain reaction or PCR) were used to confirm the isolates identity. Antibiotic susceptibility testing was conducted using six commonly employed antibiotics of V. cholerae according to the recommendation of Clinical Laboratory Standard and European Committee for Antimicrobial Susceptibility Testing with other relevant antibiotics of investigative epidemiology and infection control, employing both disc diffusion test and PCR gene detection. Samples presumptive counts ranged between 1.10 to 7.91 log10 CFU/mL. Amongst the 759 presumptive isolates retrieved, sixty-one were confirmed as V. cholerae which were further serogrouped as Non-O1/Non-O139 V. cholerae. Various V. cholerae resistant phenotypes/genoytypes were detected vis: carbapenemase (CR-Vc; 31.1%/5.3%). New Delhi Metallobetalactamase (NDM-1-Vc; 23.0%/42.5%), extended spectrum betalactamase (ESBL-Vc; 42.6%/blaTEM:86,7%), chloramphenicol resistance (62.3%/Flor: 46.2%}, tetracycline resistance (70.5%/46.7%), AmpC resistance (21.0 (34.4%/56.7%)) and various other resistant genotypes/phenotypes. It was observed that more than 50% of the confirmed V. cholerae isolates possess resistance to two or more antibiotic classes/groups with multiple antibiotic resistance index (MARI) ranging from 0.031 to 0.5. This observation provides necessary information and updates for surveillance, planning and implementation of control strategies for cholera. It would also encourage decision making, formulation of policy by the government and cholera control authorities.

Dataset Information

Human Gut Microbiota Predicts Susceptibility to Vibrio cholerae Infection.

Background

Methods

Results

Conclusion

Publications

Human Gut Microbiota Predicts Susceptibility to Vibrio cholerae Infection.

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