Towards a general model for predicting minimal metal concentrations co-selecting for antibiotic resistance plasmids

Sankalp Arya; Alexander Williams; Saul Vazquez Reina; Charles W. Knapp; Jan-Ulrich Kreft; Jon L. Hobman; Dov J. Stekel

doi:10.1016/j.envpol.2021.116602

Towards a general model for predicting minimal metal concentrations co-selecting for antibiotic resistance plasmids

Sankalp Arya, Alexander Williams, Saul Vazquez Reina, Charles W. Knapp, Jan-Ulrich Kreft, Jon L. Hobman, Dov J. Stekel

Biosciences

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

33 Downloads (Pure)

Abstract

Many antibiotic resistance genes co-occur with resistance genes for transition metals, such as copper, zinc, or mercury. In some environments, a positive correlation between high metal concentration and high abundance of antibiotic resistance genes has been observed, suggesting co-selection due to metal presence. Of particular concern is the use of copper and zinc in animal husbandry, leading to potential co-selection for antibiotic resistance in animal gut microbiomes, slurry, manure, or amended soils. For antibiotics, predicted no effect concentrations have been derived from laboratory measured minimum inhibitory concentrations and some minimal selective concentrations have been investigated in environmental settings. However, minimal co-selection concentrations for metals are difficult to identify. Here, we use mathematical modelling to provide a general mechanistic framework to predict minimal co-selective concentrations for metals, given knowledge of their toxicity at different concentrations. We apply the method to copper (Cu), zinc (Zn), mercury (Hg), lead (Pb) and silver (Ag), predicting their minimum co-selective concentrations in mg/L (Cu: 5.5, Zn: 1.6, Hg: 0.0156, Pb: 21.5, Ag: 0.152). To exemplify use of these thresholds, we consider metal concentrations from slurry and slurry-amended soil from a UK dairy farm that uses copper and zinc as additives for feed and antimicrobial footbath: the slurry is predicted to be co-selective, but not the slurry-amended soil. This modelling framework could be used as the basis for defining standards to mitigate risks of antimicrobial resistance applicable to a wide range of environments, including manure, slurry and other waste streams.

Highlights
• Transition metals, e.g. copper and zinc, can co-select for antibiotic resistance.
• Minimum co-selective concentration (MCSC) standards for transition metals are needed.
• We use ordinary differential equations model to form a general method for identifying MCSCs.
• We calibrate and apply the approach to copper, zinc, lead, mercury and silver.
• We exemplify its use in slurry and slurry-amended soil from a dairy farm.

Original language	English
Article number	116602
Number of pages	9
Journal	Environmental Pollution
Volume	275
Early online date	6 Feb 2021
DOIs	https://doi.org/10.1016/j.envpol.2021.116602
Publication status	Published - 15 Apr 2021

Bibliographical note

Funding Information:
Sankalp Arya was funded by a University of Nottingham Vice Chancellor’s Scholarship. Alexander Williams was funded by that Natural and Environmental Sciences Soil Training and Research Studentship. We thank Scott Young for facilitating the ICP-MS work, Helen West as Alex Williams’s primary supervisor, and Wissam Zendjebil for alerting us to Shi et al., 2013 .

Publisher Copyright:
© 2021 Elsevier Ltd

ASJC Scopus subject areas

Toxicology
Pollution
Health, Toxicology and Mutagenesis

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Cite this

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title = "Towards a general model for predicting minimal metal concentrations co-selecting for antibiotic resistance plasmids",

abstract = "Many antibiotic resistance genes co-occur with resistance genes for transition metals, such as copper, zinc, or mercury. In some environments, a positive correlation between high metal concentration and high abundance of antibiotic resistance genes has been observed, suggesting co-selection due to metal presence. Of particular concern is the use of copper and zinc in animal husbandry, leading to potential co-selection for antibiotic resistance in animal gut microbiomes, slurry, manure, or amended soils. For antibiotics, predicted no effect concentrations have been derived from laboratory measured minimum inhibitory concentrations and some minimal selective concentrations have been investigated in environmental settings. However, minimal co-selection concentrations for metals are difficult to identify. Here, we use mathematical modelling to provide a general mechanistic framework to predict minimal co-selective concentrations for metals, given knowledge of their toxicity at different concentrations. We apply the method to copper (Cu), zinc (Zn), mercury (Hg), lead (Pb) and silver (Ag), predicting their minimum co-selective concentrations in mg/L (Cu: 5.5, Zn: 1.6, Hg: 0.0156, Pb: 21.5, Ag: 0.152). To exemplify use of these thresholds, we consider metal concentrations from slurry and slurry-amended soil from a UK dairy farm that uses copper and zinc as additives for feed and antimicrobial footbath: the slurry is predicted to be co-selective, but not the slurry-amended soil. This modelling framework could be used as the basis for defining standards to mitigate risks of antimicrobial resistance applicable to a wide range of environments, including manure, slurry and other waste streams.Highlights• Transition metals, e.g. copper and zinc, can co-select for antibiotic resistance.• Minimum co-selective concentration (MCSC) standards for transition metals are needed.• We use ordinary differential equations model to form a general method for identifying MCSCs.• We calibrate and apply the approach to copper, zinc, lead, mercury and silver.• We exemplify its use in slurry and slurry-amended soil from a dairy farm.",

author = "Sankalp Arya and Alexander Williams and Reina, {Saul Vazquez} and Knapp, {Charles W.} and Jan-Ulrich Kreft and Hobman, {Jon L.} and Stekel, {Dov J.}",

note = "Funding Information: Sankalp Arya was funded by a University of Nottingham Vice Chancellor{\textquoteright}s Scholarship. Alexander Williams was funded by that Natural and Environmental Sciences Soil Training and Research Studentship. We thank Scott Young for facilitating the ICP-MS work, Helen West as Alex Williams{\textquoteright}s primary supervisor, and Wissam Zendjebil for alerting us to Shi et al., 2013 . Publisher Copyright: {\textcopyright} 2021 Elsevier Ltd",

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doi = "10.1016/j.envpol.2021.116602",

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AU - Arya, Sankalp

AU - Williams, Alexander

AU - Reina, Saul Vazquez

AU - Knapp, Charles W.

AU - Kreft, Jan-Ulrich

AU - Hobman, Jon L.

AU - Stekel, Dov J.

N1 - Funding Information: Sankalp Arya was funded by a University of Nottingham Vice Chancellor’s Scholarship. Alexander Williams was funded by that Natural and Environmental Sciences Soil Training and Research Studentship. We thank Scott Young for facilitating the ICP-MS work, Helen West as Alex Williams’s primary supervisor, and Wissam Zendjebil for alerting us to Shi et al., 2013 . Publisher Copyright: © 2021 Elsevier Ltd

PY - 2021/4/15

Y1 - 2021/4/15

N2 - Many antibiotic resistance genes co-occur with resistance genes for transition metals, such as copper, zinc, or mercury. In some environments, a positive correlation between high metal concentration and high abundance of antibiotic resistance genes has been observed, suggesting co-selection due to metal presence. Of particular concern is the use of copper and zinc in animal husbandry, leading to potential co-selection for antibiotic resistance in animal gut microbiomes, slurry, manure, or amended soils. For antibiotics, predicted no effect concentrations have been derived from laboratory measured minimum inhibitory concentrations and some minimal selective concentrations have been investigated in environmental settings. However, minimal co-selection concentrations for metals are difficult to identify. Here, we use mathematical modelling to provide a general mechanistic framework to predict minimal co-selective concentrations for metals, given knowledge of their toxicity at different concentrations. We apply the method to copper (Cu), zinc (Zn), mercury (Hg), lead (Pb) and silver (Ag), predicting their minimum co-selective concentrations in mg/L (Cu: 5.5, Zn: 1.6, Hg: 0.0156, Pb: 21.5, Ag: 0.152). To exemplify use of these thresholds, we consider metal concentrations from slurry and slurry-amended soil from a UK dairy farm that uses copper and zinc as additives for feed and antimicrobial footbath: the slurry is predicted to be co-selective, but not the slurry-amended soil. This modelling framework could be used as the basis for defining standards to mitigate risks of antimicrobial resistance applicable to a wide range of environments, including manure, slurry and other waste streams.Highlights• Transition metals, e.g. copper and zinc, can co-select for antibiotic resistance.• Minimum co-selective concentration (MCSC) standards for transition metals are needed.• We use ordinary differential equations model to form a general method for identifying MCSCs.• We calibrate and apply the approach to copper, zinc, lead, mercury and silver.• We exemplify its use in slurry and slurry-amended soil from a dairy farm.

AB - Many antibiotic resistance genes co-occur with resistance genes for transition metals, such as copper, zinc, or mercury. In some environments, a positive correlation between high metal concentration and high abundance of antibiotic resistance genes has been observed, suggesting co-selection due to metal presence. Of particular concern is the use of copper and zinc in animal husbandry, leading to potential co-selection for antibiotic resistance in animal gut microbiomes, slurry, manure, or amended soils. For antibiotics, predicted no effect concentrations have been derived from laboratory measured minimum inhibitory concentrations and some minimal selective concentrations have been investigated in environmental settings. However, minimal co-selection concentrations for metals are difficult to identify. Here, we use mathematical modelling to provide a general mechanistic framework to predict minimal co-selective concentrations for metals, given knowledge of their toxicity at different concentrations. We apply the method to copper (Cu), zinc (Zn), mercury (Hg), lead (Pb) and silver (Ag), predicting their minimum co-selective concentrations in mg/L (Cu: 5.5, Zn: 1.6, Hg: 0.0156, Pb: 21.5, Ag: 0.152). To exemplify use of these thresholds, we consider metal concentrations from slurry and slurry-amended soil from a UK dairy farm that uses copper and zinc as additives for feed and antimicrobial footbath: the slurry is predicted to be co-selective, but not the slurry-amended soil. This modelling framework could be used as the basis for defining standards to mitigate risks of antimicrobial resistance applicable to a wide range of environments, including manure, slurry and other waste streams.Highlights• Transition metals, e.g. copper and zinc, can co-select for antibiotic resistance.• Minimum co-selective concentration (MCSC) standards for transition metals are needed.• We use ordinary differential equations model to form a general method for identifying MCSCs.• We calibrate and apply the approach to copper, zinc, lead, mercury and silver.• We exemplify its use in slurry and slurry-amended soil from a dairy farm.

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Towards a general model for predicting minimal metal concentrations co-selecting for antibiotic resistance plasmids

Abstract

Bibliographical note

ASJC Scopus subject areas

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