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Metagenomic Frameworks for Monitoring Antibiotic Resistance in Aquatic Environments

Background: High-throughput genomic technologies offer new approaches for environmental health monitoring, including metagenomic surveillance of antibiotic resistance determinants (ARDs). Although natural environments serve as reservoirs for antibiotic resistance genes that can be transferred to pat...

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Autores principales: Port, Jesse A., Cullen, Alison C., Wallace, James C., Smith, Marissa N., Faustman, Elaine M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Institute of Environmental Health Sciences 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3948035/
https://www.ncbi.nlm.nih.gov/pubmed/24334622
http://dx.doi.org/10.1289/ehp.1307009
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author Port, Jesse A.
Cullen, Alison C.
Wallace, James C.
Smith, Marissa N.
Faustman, Elaine M.
author_facet Port, Jesse A.
Cullen, Alison C.
Wallace, James C.
Smith, Marissa N.
Faustman, Elaine M.
author_sort Port, Jesse A.
collection PubMed
description Background: High-throughput genomic technologies offer new approaches for environmental health monitoring, including metagenomic surveillance of antibiotic resistance determinants (ARDs). Although natural environments serve as reservoirs for antibiotic resistance genes that can be transferred to pathogenic and human commensal bacteria, monitoring of these determinants has been infrequent and incomplete. Furthermore, surveillance efforts have not been integrated into public health decision making. Objectives: We used a metagenomic epidemiology–based approach to develop an ARD index that quantifies antibiotic resistance potential, and we analyzed this index for common modal patterns across environmental samples. We also explored how metagenomic data such as this index could be conceptually framed within an early risk management context. Methods: We analyzed 25 published data sets from shotgun pyrosequencing projects. The samples consisted of microbial community DNA collected from marine and freshwater environments across a gradient of human impact. We used principal component analysis to identify index patterns across samples. Results: We observed significant differences in the overall index and index subcategory levels when comparing ecosystems more proximal versus distal to human impact. The selection of different sequence similarity thresholds strongly influenced the index measurements. Unique index subcategory modes distinguished the different metagenomes. Conclusions: Broad-scale screening of ARD potential using this index revealed utility for framing environmental health monitoring and surveillance. This approach holds promise as a screening tool for establishing baseline ARD levels that can be used to inform and prioritize decision making regarding management of ARD sources and human exposure routes. Citation: Port JA, Cullen AC, Wallace JC, Smith MN, Faustman EM. 2014. Metagenomic frameworks for monitoring antibiotic resistance in aquatic environments. Environ Health Perspect 122:222–228; http://dx.doi.org/10.1289/ehp.1307009
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spelling pubmed-39480352014-03-20 Metagenomic Frameworks for Monitoring Antibiotic Resistance in Aquatic Environments Port, Jesse A. Cullen, Alison C. Wallace, James C. Smith, Marissa N. Faustman, Elaine M. Environ Health Perspect Research Background: High-throughput genomic technologies offer new approaches for environmental health monitoring, including metagenomic surveillance of antibiotic resistance determinants (ARDs). Although natural environments serve as reservoirs for antibiotic resistance genes that can be transferred to pathogenic and human commensal bacteria, monitoring of these determinants has been infrequent and incomplete. Furthermore, surveillance efforts have not been integrated into public health decision making. Objectives: We used a metagenomic epidemiology–based approach to develop an ARD index that quantifies antibiotic resistance potential, and we analyzed this index for common modal patterns across environmental samples. We also explored how metagenomic data such as this index could be conceptually framed within an early risk management context. Methods: We analyzed 25 published data sets from shotgun pyrosequencing projects. The samples consisted of microbial community DNA collected from marine and freshwater environments across a gradient of human impact. We used principal component analysis to identify index patterns across samples. Results: We observed significant differences in the overall index and index subcategory levels when comparing ecosystems more proximal versus distal to human impact. The selection of different sequence similarity thresholds strongly influenced the index measurements. Unique index subcategory modes distinguished the different metagenomes. Conclusions: Broad-scale screening of ARD potential using this index revealed utility for framing environmental health monitoring and surveillance. This approach holds promise as a screening tool for establishing baseline ARD levels that can be used to inform and prioritize decision making regarding management of ARD sources and human exposure routes. Citation: Port JA, Cullen AC, Wallace JC, Smith MN, Faustman EM. 2014. Metagenomic frameworks for monitoring antibiotic resistance in aquatic environments. Environ Health Perspect 122:222–228; http://dx.doi.org/10.1289/ehp.1307009 National Institute of Environmental Health Sciences 2013-12-13 2014-03 /pmc/articles/PMC3948035/ /pubmed/24334622 http://dx.doi.org/10.1289/ehp.1307009 Text en http://creativecommons.org/publicdomain/mark/1.0/ Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, “Reproduced with permission from Environmental Health Perspectives”); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
spellingShingle Research
Port, Jesse A.
Cullen, Alison C.
Wallace, James C.
Smith, Marissa N.
Faustman, Elaine M.
Metagenomic Frameworks for Monitoring Antibiotic Resistance in Aquatic Environments
title Metagenomic Frameworks for Monitoring Antibiotic Resistance in Aquatic Environments
title_full Metagenomic Frameworks for Monitoring Antibiotic Resistance in Aquatic Environments
title_fullStr Metagenomic Frameworks for Monitoring Antibiotic Resistance in Aquatic Environments
title_full_unstemmed Metagenomic Frameworks for Monitoring Antibiotic Resistance in Aquatic Environments
title_short Metagenomic Frameworks for Monitoring Antibiotic Resistance in Aquatic Environments
title_sort metagenomic frameworks for monitoring antibiotic resistance in aquatic environments
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3948035/
https://www.ncbi.nlm.nih.gov/pubmed/24334622
http://dx.doi.org/10.1289/ehp.1307009
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