The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Silver(I), Mercury(II), Cadmium(II), and Zinc(II) Target Exposed Enzymic Iron-Sulfur Clusters when They Toxify Escherichia coli
Open accessAbstract
The toxicity of soft metals is of broad interest to microbiologists, both because such metals influence the community structures in natural environments and because several metals are used as antimicrobial agents. Their potency roughly parallels their thiophilicity, suggesting that their primary biological targets are likely to be enzymes that contain key sulfhydryl moieties. A recent study determined that copper poisons Escherichia coli in part by attacking the exposed [4Fe-4S] clusters of dehydratases. The present investigation sought to test whether other soft metals also target these enzymes. In vitro experiments revealed that low-micromolar concentrations of Ag(I) and Hg(II) directly inactivated purified fumarase A, a member of the dehydratase family. The enzyme was also poisoned by higher levels of Cd(II) and Zn(II), but it was unaffected by even millimolar concentrations of Mn(II), Co(II), Ni(II), and Pb(II). Electron paramagnetic resonance analysis and measurements of released iron confirmed that damage was associated with destruction of the [4Fe-4S] cluster, and indeed, the reconstruction of the cluster fully restored activity. Growth studies were then performed to test whether dehydratase damage might underlie toxicity in vivo . Barely toxic doses of Ag(I), Hg(II), Cd(II), and Zn(II) inactivated all tested members of the [4Fe-4S] dehydratase family. Again, activity was recovered when the clusters were rebuilt. The metals did not diminish the activities of other sampled enzymes, including NADH dehydrogenase I, an iron-sulfur protein whose clusters are shielded by polypeptide. Thus, the data indicate that dehydratases are damaged by the concentrations of metals that initiate bacteriostasis.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Metals, Toxicity and Oxidative Stress
Valko, M., Morris, H., & Cronin, M. (2005) · Current Medicinal Chemistry · doi:10.2174/0929867053764635 · Cited by 5,018
Metallic copper as an antimicrobial surface
Grass, G., Rensing, C., & Solioz, M. (2011) · Applied and Environmental Microbiology · doi:10.1128/aem.02766-10 · Cited by 1,640
Regulating the fate of mRNA: the control of cellular iron metabolism
Klausner, R. D., Rouault, T. A., & Harford, J. B. (1993) · Cell · doi:10.1016/0092-8674(93)90046-s · Cited by 1,210
The zntA gene of Escherichia coli encodes a Zn(II)-translocating P-type ATPase
Rensing, C., Mitra, B., & Rosen, B. P. (1997) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.94.26.14326 · Cited by 419
Anbar, A. D. (2008) · Science · doi:10.1126/science.1163100 · Cited by 365
Cited by
Antimicrobial activity of metals: mechanisms, molecular targets and applications
Lemire, J. A., Harrison, J. J., & Turner, R. J. (2013) · Nature Reviews Microbiology · doi:10.1038/nrmicro3028 · Cited by 2,746
Nutritional immunity: transition metals at the pathogen–host interface
Hood, M. I., & Skaar, E. P. (2012) · Nature Reviews Microbiology · doi:10.1038/nrmicro2836 · Cited by 1,535
Metal homeostasis and resistance in bacteria
Chandrangsu, P., Rensing, C., & Helmann, J. D. (2017) · Nature Reviews Microbiology · doi:10.1038/nrmicro.2017.15 · Cited by 812
Pathogenic adaptations to host-derived antibacterial copper
Chaturvedi, K. S., & Henderson, J. P. (2014) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2014.00003 · Cited by 134
Copper binding in IscA inhibits iron‐sulphur cluster assembly in E scherichia coli
Tan, G., Cheng, Z., Pang, Y., Landry, A. P., Li, J., Lu, J., & Ding, H. (2014) · Molecular Microbiology · doi:10.1111/mmi.12676 · Cited by 103
Metadata
- Authors
- Xu, F. F., & Imlay, J. A.
- Venue
- Applied and Environmental Microbiology
- Publisher
- American Society for Microbiology
- Published
- 2012-05-15
- Volume
- 78
- Issue
- 10
- Pages
- 3614-3621
- ISSN
- 0099-2240 (ISSN-L)
- 1098-5336
- OpenAlex
- W2050711776
- Cited by
- 294
- References
- 5
- FWCI
- 7.41
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Silver(I), Mercury(II), Cadmium(II), and Zinc(II) Target Exposed Enzymic Iron-Sulfur Clusters when They Toxify Escherichia coli. https://app.cochat.ai/papers/10.1128/aem.07368-11
- The paper
- Xu, F. F., & Imlay, J. A. (2012). Silver(I), Mercury(II), Cadmium(II), and Zinc(II) Target Exposed Enzymic Iron-Sulfur Clusters when They Toxify Escherichia coli. Applied and Environmental Microbiology. https://doi.org/10.1128/aem.07368-11
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.