Quantifying and predicting antimicrobials and antimicrobial resistance genes in waterbodies through a holistic approach: a study in Minnesota, United States

Abstract The environment plays a key role in the spread and persistence of antimicrobial resistance (AMR). Antimicrobials and antimicrobial resistance genes (ARG) are released into the environment from sources such as wastewater treatment plants, and animal farms. This study describes an approach gu...

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Autores principales:	Irene Bueno, Amanda Beaudoin, William A. Arnold, Taegyu Kim, Lara E. Frankson, Timothy M. LaPara, Kaushi Kanankege, Kristine H. Wammer, Randall S. Singer
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/a2be87ed38d543cd85b37f35b8e8f2e9
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spelling	oai:doaj.org-article:a2be87ed38d543cd85b37f35b8e8f2e92021-12-02T18:13:52ZQuantifying and predicting antimicrobials and antimicrobial resistance genes in waterbodies through a holistic approach: a study in Minnesota, United States10.1038/s41598-021-98300-52045-2322https://doaj.org/article/a2be87ed38d543cd85b37f35b8e8f2e92021-09-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-98300-5https://doaj.org/toc/2045-2322Abstract The environment plays a key role in the spread and persistence of antimicrobial resistance (AMR). Antimicrobials and antimicrobial resistance genes (ARG) are released into the environment from sources such as wastewater treatment plants, and animal farms. This study describes an approach guided by spatial mapping to quantify and predict antimicrobials and ARG in Minnesota’s waterbodies in water and sediment at two spatial scales: macro, throughout the state, and micro, in specific waterbodies. At the macroscale, the highest concentrations across all antimicrobial classes were found near populated areas. Kernel interpolation provided an approximation of antimicrobial concentrations and ARG abundance at unsampled locations. However, there was high uncertainty in these predictions, due in part to low study power and large distances between sites. At the microscale, wastewater treatment plants had an effect on ARG abundance (sul1 and sul2 in water; bla SHV, intl1, mexB, and sul2 in sediment), but not on antimicrobial concentrations. Results from sediment reflected a long-term history, while water reflected a more transient record of antimicrobials and ARG. This study highlights the value of using spatial analyses, different spatial scales, and sampling matrices, to design an environmental monitoring approach to advance our understanding of AMR persistence and dissemination.Irene BuenoAmanda BeaudoinWilliam A. ArnoldTaegyu KimLara E. FranksonTimothy M. LaParaKaushi KanankegeKristine H. WammerRandall S. SingerNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-15 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Irene Bueno Amanda Beaudoin William A. Arnold Taegyu Kim Lara E. Frankson Timothy M. LaPara Kaushi Kanankege Kristine H. Wammer Randall S. Singer Quantifying and predicting antimicrobials and antimicrobial resistance genes in waterbodies through a holistic approach: a study in Minnesota, United States
description	Abstract The environment plays a key role in the spread and persistence of antimicrobial resistance (AMR). Antimicrobials and antimicrobial resistance genes (ARG) are released into the environment from sources such as wastewater treatment plants, and animal farms. This study describes an approach guided by spatial mapping to quantify and predict antimicrobials and ARG in Minnesota’s waterbodies in water and sediment at two spatial scales: macro, throughout the state, and micro, in specific waterbodies. At the macroscale, the highest concentrations across all antimicrobial classes were found near populated areas. Kernel interpolation provided an approximation of antimicrobial concentrations and ARG abundance at unsampled locations. However, there was high uncertainty in these predictions, due in part to low study power and large distances between sites. At the microscale, wastewater treatment plants had an effect on ARG abundance (sul1 and sul2 in water; bla SHV, intl1, mexB, and sul2 in sediment), but not on antimicrobial concentrations. Results from sediment reflected a long-term history, while water reflected a more transient record of antimicrobials and ARG. This study highlights the value of using spatial analyses, different spatial scales, and sampling matrices, to design an environmental monitoring approach to advance our understanding of AMR persistence and dissemination.
format	article
author	Irene Bueno Amanda Beaudoin William A. Arnold Taegyu Kim Lara E. Frankson Timothy M. LaPara Kaushi Kanankege Kristine H. Wammer Randall S. Singer
author_facet	Irene Bueno Amanda Beaudoin William A. Arnold Taegyu Kim Lara E. Frankson Timothy M. LaPara Kaushi Kanankege Kristine H. Wammer Randall S. Singer
author_sort	Irene Bueno
title	Quantifying and predicting antimicrobials and antimicrobial resistance genes in waterbodies through a holistic approach: a study in Minnesota, United States
title_short	Quantifying and predicting antimicrobials and antimicrobial resistance genes in waterbodies through a holistic approach: a study in Minnesota, United States
title_full	Quantifying and predicting antimicrobials and antimicrobial resistance genes in waterbodies through a holistic approach: a study in Minnesota, United States
title_fullStr	Quantifying and predicting antimicrobials and antimicrobial resistance genes in waterbodies through a holistic approach: a study in Minnesota, United States
title_full_unstemmed	Quantifying and predicting antimicrobials and antimicrobial resistance genes in waterbodies through a holistic approach: a study in Minnesota, United States
title_sort	quantifying and predicting antimicrobials and antimicrobial resistance genes in waterbodies through a holistic approach: a study in minnesota, united states
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/a2be87ed38d543cd85b37f35b8e8f2e9
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Quantifying and predicting antimicrobials and antimicrobial resistance genes in waterbodies through a holistic approach: a study in Minnesota, United States

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