Bacterial sensitivity distributions for biocides and metals
Journal article, 2026

Understanding how potent metals and biocides are for inhibiting bacterial growth is key for understanding risks for ecological disturbances and for co-selection of resistance to antibiotics. The aim of this study was to gather MIC data from the public literature to generate a centralized biocide and metal minimum inhibitory concentration (MIC) dataset, emulating established specialized datasets for antibiotics. The resulting dataset contains data for 53 antibacterial biocides, 21 metals, and 17 related compounds, collected from 289 publications between 1973 and 2024. The dataset includes 20 378 MIC values across 164 bacterial species, with a strong overrepresentation of clinically relevant organisms such as Staphylococcus aureus and Escherichia coli. Biocides like chlorhexidine and benzalkonium chloride, as well as metals such as copper, zinc, arsenic, cadmium, and silver, were the most represented compounds in each case. Some inconsistent MIC values were observed, complicating cross-study comparisons. The data collected in this study emphasizes the urgent need for standardized susceptibility testing methodology and consistent terminology for research on reduced susceptibility to biocides and metals. By centralizing MIC data, this work provides part of the foundation for future efforts to assess ecological risks and co-selection with antibiotic resistance, identify data gaps, and support future regulatory evaluations.We compiled over 20 000 MIC values for biocides and metals into a single dataset to enable better comparisons, reveal gaps, and could help guiding future resistance research and regulation.

metal

co-selection

biocide

MIC

co-resistance

antimicrobial resistance

Author

Daniel Jaen-Luchoro

University of Gothenburg

D. G. Joakim Larsson

University of Gothenburg

Johan Bengtsson Palme

Chalmers, Life Sciences, Systems and Synthetic Biology

University of Gothenburg

FEMS Microbiology Ecology

0168-6496 (ISSN) 15746941 (eISSN)

Vol. 102 8 fiag075

Predicting future pathogenicity and antibiotic resistance

Swedish Foundation for Strategic Research (SSF) (FFL21-0174), 2022-08-01 -- 2027-12-31.

Subject Categories (SSIF 2025)

Environmental Sciences

DOI

10.1093/femsec/fiag075

PubMed

42429472

More information

Latest update

7/30/2026