The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Concentrations of antibiotics predicted to select for resistant bacteria: Proposed limits for environmental regulation
Open accessAbstract
There are concerns that selection pressure from antibiotics in the environment may accelerate the evolution and dissemination of antibiotic-resistant pathogens. Nevertheless, there is currently no regulatory system that takes such risks into account. In part, this is due to limited knowledge of environmental concentrations that might exert selection for resistant bacteria. To experimentally determine minimal selective concentrations in complex microbial ecosystems for all antibiotics would involve considerable effort. In this work, our aim was to estimate upper boundaries for selective concentrations for all common antibiotics, based on the assumption that selective concentrations a priori need to be lower than those completely inhibiting growth. Data on Minimal Inhibitory Concentrations (MICs) were obtained for 111 antibiotics from the public EUCAST database. The 1% lowest observed MICs were identified, and to compensate for limited species coverage, predicted lowest MICs adjusted for the number of tested species were extrapolated through modeling. Predicted No Effect Concentrations (PNECs) for resistance selection were then assessed using an assessment factor of 10 to account for differences between MICs and minimal selective concentrations. The resulting PNECs ranged from 8 ng/L to 64 μg/L. Furthermore, the link between taxonomic similarity between species and lowest MIC was weak. This work provides estimated upper boundaries for selective concentrations (lowest MICs) and PNECs for resistance selection for all common antibiotics. In most cases, PNECs for selection of resistance were below available PNECs for ecotoxicological effects. The generated PNECs can guide implementation of compound-specific emission limits that take into account risks for resistance promotion.
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Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
Antibiotic resistance is ancient
D’Costa, V. M., King, C. E., Kalan, L., Morar, M., Sung, W. W. L., Schwarz, C., Froese, D., Zazula, G., Calmels, F., Debruyne, R., et al. (2011) · Nature · doi:10.1038/nature10388 · Cited by 2,720
Persister cells, dormancy and infectious disease
Lewis, K. (2007) · Nature Reviews Microbiology · doi:10.1038/nrmicro1557 · Cited by 2,052
Sampling the Antibiotic Resistome
D'Costa, V. M., McGrann, K. M., Hughes, D. W., & Wright, G. D. (2006) · Science · doi:10.1126/science.1120800 · Cited by 1,594
SOS response promotes horizontal dissemination of antibiotic resistance genes
Beaber, J. W., Hochhut, B., & Waldor, M. K. (2004) · Nature · doi:10.1038/nature02241 · Cited by 1,186
Antibiotic resistance in the environment: a link to the clinic?
Wright, G. D. (2010) · Current Opinion in Microbiology · doi:10.1016/j.mib.2010.08.005 · Cited by 831
Cited by
Antibiotic resistance in the environment
Larsson, D. G. J., & Flach, C.-F. (2022) · Nature Reviews Microbiology · doi:10.1038/s41579-021-00649-x · Cited by 3,164
Self-citationTran, N. H., Reinhard, M., & Gin, K. Y.-H. (2018) · Water Research · doi:10.1016/j.watres.2017.12.029 · Cited by 1,686
Ecological effects of antibiotics on natural ecosystems: A review
Grenni, P., Ancona, V., & Barra Caracciolo, A. (2018) · Microchemical Journal · doi:10.1016/j.microc.2017.02.006 · Cited by 1,257
Environmental factors influencing the development and spread of antibiotic resistance
Bengtsson-Palme, J., Kristiansson, E., & Larsson, D. G. J. (2018) · FEMS Microbiology Reviews · doi:10.1093/femsre/fux053 · Cited by 1,167
Self-citationUsage, residue, and human health risk of antibiotics in Chinese aquaculture: A review
Liu, X., Steele, J. C., & Meng, X.-Z. (2017) · Environmental Pollution · doi:10.1016/j.envpol.2017.01.003 · Cited by 964
Metadata
- Authors
- Bengtsson-Palme, J., & Larsson, D. G. J.
- Venue
- Environment International
- Publisher
- Elsevier BV
- Published
- 2016-01
- Volume
- 86
- Pages
- 140-149
- ISSN
- 0160-4120 (ISSN-L)
- OpenAlex
- W2197156841
- Cited by
- 977
- References
- 6
- FWCI
- 21.22
- Type
- journal article
- Language
- en
- Open access
- hybrid
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