ID
45691
Description
Principal Investigator: Sarah Highlander, PhD, J Craig Venter Institute, La Jolla, CA, USA MeSH: Diarrhea,Escherichia coli,Salmonella,Campylobacter,Norovirus,Astroviridae,Adenoviridae,Gastroenteritis,Rotavirus https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001260 The study of antimicrobial resistance (AMR) in infectious diarrhea has generally been limited to cultivation, antimicrobial susceptibility testing and targeted PCR assays. When individual strains of significance are identified, whole genome shotgun (WGS) sequencing of important clones and clades is performed. Genes that encode resistance to antibiotics have been detected in environmental, insect, human and animal metagenomes and are known as "resistomes". While metagenomic datasets have been mined to characterize the healthy human gut resistome in the Human Microbiome Project and MetaHIT and in a Yanomani Amerindian cohort, directed metagenomic sequencing has not been used to examine the epidemiology of AMR. Especially in developing countries where sanitation is poor, diarrhea and enteric pathogens likely serve to disseminate antibiotic resistance elements of clinical significance. Unregulated use of antibiotics further exacerbates the problem by selection for acquisition of resistance. This is exemplified by recent reports of multiple antibiotic resistance in Shigella strains in India, in Escherichia coli in India and Pakistan, and in nontyphoidal Salmonella (NTS) in South-East Asia. We propose to use deep metagenomic sequencing and genome level assembly to study the epidemiology of AMR in stools of children suffering from diarrhea. Here the epidemiology component will be surveillance and analysis of the microbial composition (to the bacterial species/strain level where possible) and its constituent antimicrobial resistance genetic elements (such as plasmids, integrons, transposons and other mobile genetic elements, or MGEs) in samples from a cohort where diarrhea is prevalent and antibiotic exposure is endemic. The goal will be to assess whether consortia of specific mobile antimicrobial resistance elements associate with species/strains and whether their presence is enhanced or amplified in diarrheal microbiomes and in the presence of antibiotic exposure. This work could potentially identify clonal complexes of organisms and MGEs with enhanced resistance and the potential to transfer this resistance to other enteric pathogens. We have performed WGS, metagenomic assembly and gene/protein mapping to examine and characterize the types of AMR genes and transfer elements (transposons, integrons, bacteriophage, plasmids) and their distribution in bacterial species and strains assembled from DNA isolated from diarrheal and non-diarrheal stools. The samples were acquired from a cohort of pediatric patients and controls from Colombia, South America where antibiotic use is prevalent. As a control, the distribution and abundance of AMR genes can be compared to published studies where resistome gene lists from healthy cohort sequences were compiled. Our approach is more epidemiologic in nature, as we plan to identify and catalogue antimicrobial elements on MGEs capable of spread through a local population and further we will, where possible, link mobile antimicrobial resistance elements with specific strains within the population.
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Versions (1)
- 05/05/2023 05/05/2023 - Simon Heim
Détendeur de droits
Sarah Highlander, PhD, J Craig Venter Institute, La Jolla, CA, USA
Téléchargé le
5 mai 2023
DOI
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Licence
Creative Commons BY 4.0
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dbGaP phs001260 Metagenomic Epidemiology of Antibiotic Resistance in Infectious Diarrhea
This subject phenotype table contains subject IDs, gender, age, height, weight, race, children temperature, if there is diarrhea or vomiting during illness, the highest temperature measured, Rotavirus immunization and immunization doses, drinking water management and water source in the house, if there is disponibility of water everyday in a year, and sewage arrangement in the house.
- StudyEvent: SEV1
- Eligibility Criteria
- The subject consent file includes subject IDs, consent information, subject aliases, and affection status of the subject for diarrhea.
- This data table contains a mapping of study subject IDs to sample IDs. Samples are the final preps submitted for genotyping, sequencing, and/or expression data. For example, if one patient (subject ID) gave one sample, and that sample was processed differently to generate 2 sequencing runs, there would be two rows, both using the same subject ID, but having 2 unique sample IDs. The data table also includes sample aliases and sample use.
- This subject phenotype table contains subject IDs, gender, age, height, weight, race, children temperature, if there is diarrhea or vomiting during illness, the highest temperature measured, Rotavirus immunization and immunization doses, drinking water management and water source in the house, if there is disponibility of water everyday in a year, and sewage arrangement in the house.
- This sample attributes table contains sample IDs, body site, analyte type, bacterial species (n=7 variables; salmonella, campylobacter, enteroaggregative E. coli, diffusely adherent E. coli, atypical enteropathic E. coli, enteroinvasive E. coli, and enterotoxigenic E. coli), norovirus genotypes G1 and G2, astrovirus, adenovirus, and name of the center which conducted sequencing.
Similar models
This subject phenotype table contains subject IDs, gender, age, height, weight, race, children temperature, if there is diarrhea or vomiting during illness, the highest temperature measured, Rotavirus immunization and immunization doses, drinking water management and water source in the house, if there is disponibility of water everyday in a year, and sewage arrangement in the house.
- StudyEvent: SEV1
- Eligibility Criteria
- The subject consent file includes subject IDs, consent information, subject aliases, and affection status of the subject for diarrhea.
- This data table contains a mapping of study subject IDs to sample IDs. Samples are the final preps submitted for genotyping, sequencing, and/or expression data. For example, if one patient (subject ID) gave one sample, and that sample was processed differently to generate 2 sequencing runs, there would be two rows, both using the same subject ID, but having 2 unique sample IDs. The data table also includes sample aliases and sample use.
- This subject phenotype table contains subject IDs, gender, age, height, weight, race, children temperature, if there is diarrhea or vomiting during illness, the highest temperature measured, Rotavirus immunization and immunization doses, drinking water management and water source in the house, if there is disponibility of water everyday in a year, and sewage arrangement in the house.
- This sample attributes table contains sample IDs, body site, analyte type, bacterial species (n=7 variables; salmonella, campylobacter, enteroaggregative E. coli, diffusely adherent E. coli, atypical enteropathic E. coli, enteroinvasive E. coli, and enterotoxigenic E. coli), norovirus genotypes G1 and G2, astrovirus, adenovirus, and name of the center which conducted sequencing.
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