Cargando…
Data-Driven Analysis of Antimicrobial Resistance in Foodborne Pathogens from Six States within the US
Foodborne pathogens cause thousands of illnesses across the US each year. However, these pathogens gain resistance to the antimicrobials that are commonly used to treat them. Typically, antimicrobial resistance is caused by mechanisms encoded by multiple antimicrobial-resistance genes. These are car...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6572035/ https://www.ncbi.nlm.nih.gov/pubmed/31121814 http://dx.doi.org/10.3390/ijerph16101811 |
_version_ | 1783427548008415232 |
---|---|
author | Zhang, Nina Liu, Emily Tang, Alexander Ye, Martin Cheng Wang, Kevin Jia, Qian Huang, Zuyi |
author_facet | Zhang, Nina Liu, Emily Tang, Alexander Ye, Martin Cheng Wang, Kevin Jia, Qian Huang, Zuyi |
author_sort | Zhang, Nina |
collection | PubMed |
description | Foodborne pathogens cause thousands of illnesses across the US each year. However, these pathogens gain resistance to the antimicrobials that are commonly used to treat them. Typically, antimicrobial resistance is caused by mechanisms encoded by multiple antimicrobial-resistance genes. These are carried through pathogens found in foods such as meats. It is, thus, important to study the genes that are most related to antimicrobial resistance, the pathogens, and the meats carrying antimicrobial-resistance genes. This information can be further used to correlate the antimicrobial-resistance genes found in humans for improving human health. Therefore, we perform the first multivariate statistical analysis of the antimicrobial-resistance gene data provided in the NCBI Pathogen Detection Isolates Browser database, covering six states that are geographically either in close proximity to one another (i.e., Pennsylvania (PA), Maryland (MD), and New York (NY)) or far (i.e., New Mexico (NM), Minnesota (MN), and California (CA)). Hundreds of multidimensional data points were projected onto a two-dimensional space that was specified by the first and second principal components, which were then categorized with a hierarchical clustering approach. It turns out that aadA, aph(3’’), aph(3’’)-Ib, aph(6)-I, aph(6)-Id, bla, blaCMY, tet, tet(A), and sul2 constructed the assembly of ten genes that were most commonly involved in antimicrobial resistance in these six states. While geographically close states like PA, MD and NY share more similar antimicrobial-resistance genes, geographically far states like NM, MN, and CA also contain most of these common antimicrobial-resistance genes. One potential reason for this spread of antimicrobial-resistance genes beyond the geographic limitation is that animal meats like chicken and turkey act as the carriers for the nationwide spread of these genes. |
format | Online Article Text |
id | pubmed-6572035 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-65720352019-06-18 Data-Driven Analysis of Antimicrobial Resistance in Foodborne Pathogens from Six States within the US Zhang, Nina Liu, Emily Tang, Alexander Ye, Martin Cheng Wang, Kevin Jia, Qian Huang, Zuyi Int J Environ Res Public Health Article Foodborne pathogens cause thousands of illnesses across the US each year. However, these pathogens gain resistance to the antimicrobials that are commonly used to treat them. Typically, antimicrobial resistance is caused by mechanisms encoded by multiple antimicrobial-resistance genes. These are carried through pathogens found in foods such as meats. It is, thus, important to study the genes that are most related to antimicrobial resistance, the pathogens, and the meats carrying antimicrobial-resistance genes. This information can be further used to correlate the antimicrobial-resistance genes found in humans for improving human health. Therefore, we perform the first multivariate statistical analysis of the antimicrobial-resistance gene data provided in the NCBI Pathogen Detection Isolates Browser database, covering six states that are geographically either in close proximity to one another (i.e., Pennsylvania (PA), Maryland (MD), and New York (NY)) or far (i.e., New Mexico (NM), Minnesota (MN), and California (CA)). Hundreds of multidimensional data points were projected onto a two-dimensional space that was specified by the first and second principal components, which were then categorized with a hierarchical clustering approach. It turns out that aadA, aph(3’’), aph(3’’)-Ib, aph(6)-I, aph(6)-Id, bla, blaCMY, tet, tet(A), and sul2 constructed the assembly of ten genes that were most commonly involved in antimicrobial resistance in these six states. While geographically close states like PA, MD and NY share more similar antimicrobial-resistance genes, geographically far states like NM, MN, and CA also contain most of these common antimicrobial-resistance genes. One potential reason for this spread of antimicrobial-resistance genes beyond the geographic limitation is that animal meats like chicken and turkey act as the carriers for the nationwide spread of these genes. MDPI 2019-05-22 2019-05 /pmc/articles/PMC6572035/ /pubmed/31121814 http://dx.doi.org/10.3390/ijerph16101811 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zhang, Nina Liu, Emily Tang, Alexander Ye, Martin Cheng Wang, Kevin Jia, Qian Huang, Zuyi Data-Driven Analysis of Antimicrobial Resistance in Foodborne Pathogens from Six States within the US |
title | Data-Driven Analysis of Antimicrobial Resistance in Foodborne Pathogens from Six States within the US |
title_full | Data-Driven Analysis of Antimicrobial Resistance in Foodborne Pathogens from Six States within the US |
title_fullStr | Data-Driven Analysis of Antimicrobial Resistance in Foodborne Pathogens from Six States within the US |
title_full_unstemmed | Data-Driven Analysis of Antimicrobial Resistance in Foodborne Pathogens from Six States within the US |
title_short | Data-Driven Analysis of Antimicrobial Resistance in Foodborne Pathogens from Six States within the US |
title_sort | data-driven analysis of antimicrobial resistance in foodborne pathogens from six states within the us |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6572035/ https://www.ncbi.nlm.nih.gov/pubmed/31121814 http://dx.doi.org/10.3390/ijerph16101811 |
work_keys_str_mv | AT zhangnina datadrivenanalysisofantimicrobialresistanceinfoodbornepathogensfromsixstateswithintheus AT liuemily datadrivenanalysisofantimicrobialresistanceinfoodbornepathogensfromsixstateswithintheus AT tangalexander datadrivenanalysisofantimicrobialresistanceinfoodbornepathogensfromsixstateswithintheus AT yemartincheng datadrivenanalysisofantimicrobialresistanceinfoodbornepathogensfromsixstateswithintheus AT wangkevin datadrivenanalysisofantimicrobialresistanceinfoodbornepathogensfromsixstateswithintheus AT jiaqian datadrivenanalysisofantimicrobialresistanceinfoodbornepathogensfromsixstateswithintheus AT huangzuyi datadrivenanalysisofantimicrobialresistanceinfoodbornepathogensfromsixstateswithintheus |