The DOI matches its Crossref record; 57 of the 57 references it cites were found in a registry or an index.
The Genetic Basis for Bacterial Mercury Methylation
Abstract
Mercury Methylating Microbes: Mercury (Hg) most commonly becomes bioavailable and enters the food web as the organic form methylmercury, where it induces acute toxicity effects that can be magnified up the food chain. But most natural and anthropogenic Hg exists as inorganic Hg 2+ and is only transformed into methylmercury by anaerobic microorganisms—typically sulfur-reducing bacteria. Using comparative genomics, Parks et al. (p. 1332 , published online 7 February; see the Perspective by Poulain and Barkay ) identified two genes that encode a corrinoid and iron-sulfur proteins in six known Hg-methylating bacteria but were absent in nonmethylating bacteria. In two distantly related model Hg-methylating bacteria, deletion of either gene—or both genes simultaneously—reduced the ability for the bacteria to produce methylmercury but did not impair cellular growth. The presence of this two-gene cluster in several other bacterial and lineages for which genome sequences are available suggests the ability to produce methylmercury may be more broadly distributed in the microbial world than previously recognized.
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
Bradford, M. M. (1976) · Analytical Biochemistry · doi:10.1016/0003-2697(76)90527-3 · Cited by 255,302
Gapped BLAST and PSI-BLAST: a new generation of protein database search programs
Altschul, S. (1997) · Nucleic Acids Research · doi:10.1093/nar/25.17.3389 · Cited by 73,302
Features and development of Coot
Emsley, P., Lohkamp, B., Scott, W. G., & Cowtan, K. (2010) · Acta Crystallographica Section D Biological Crystallography · doi:10.1107/s0907444910007493 · Cited by 29,915
Fast, scalable generation of high‐quality protein multiple sequence alignments using Clustal Omega
Sievers, F., Wilm, A., Dineen, D., Gibson, T. J., Karplus, K., Li, W., Lopez, R., McWilliam, H., Remmert, M., Söding, J., et al. (2011) · Molecular Systems Biology · doi:10.1038/msb.2011.75 · Cited by 15,355
The Pfam Protein Families Database
Bateman, A. (2002) · Nucleic Acids Research · doi:10.1093/nar/30.1.276 · Cited by 14,000
Comparative Protein Modelling by Satisfaction of Spatial Restraints
Šali, A., & Blundell, T. L. (1993) · Journal of Molecular Biology · doi:10.1006/jmbi.1993.1626 · Cited by 12,977
Krogh, A., Larsson, B., von Heijne, G., & Sonnhammer, E. L. L. (2001) · Journal of Molecular Biology · doi:10.1006/jmbi.2000.4315 · Cited by 12,654
Jalview Version 2—a multiple sequence alignment editor and analysis workbench
Waterhouse, A. M., Procter, J. B., Martin, D. M. A., Clamp, M., & Barton, G. J. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp033 · Cited by 10,235
Enzymatic assembly of DNA molecules up to several hundred kilobases
Gibson, D. G., Young, L., Chuang, R.-Y., Venter, J. C., Hutchison, C. A., & Smith, H. O. (2009) · Nature Methods · doi:10.1038/nmeth.1318 · Cited by 9,996
SignalP 4.0: discriminating signal peptides from transmembrane regions
Petersen, T. N., Brunak, S., von Heijne, G., & Nielsen, H. (2011) · Nature Methods · doi:10.1038/nmeth.1701 · Cited by 8,847
Cited by
Mercury Methylation by Novel Microorganisms from New Environments
Gilmour, C. C., Podar, M., Bullock, A. L., Graham, A. M., Brown, S. D., Somenahally, A. C., Johs, A., Hurt, R. A., Bailey, K. L., & Elias, D. A. (2013) · Environmental Science & Technology · doi:10.1021/es403075t · Cited by 734
Self-citationGeochemistry of Mercury in the Environment
Fitzgerald, W. F., & Lamborg, C. H. (2014) · Treatise on Geochemistry · doi:10.1016/b978-0-08-095975-7.00904-9 · Cited by 275
Ye, M., Xiang, Y., Gong, J., Wang, X., Mao, Z., & Liu, Z. (2023) · Journal of Hazardous Materials · doi:10.1016/j.jhazmat.2022.130612 · Cited by 37
Moreno, C. E., Fjeld, E., & Lydersen, E. (2016) · Environmental Monitoring and Assessment · doi:10.1007/s10661-016-5148-z · Cited by 14
Matson, P. G., Stevenson, L. M., Griffiths, N. A., DeRolph, C. R., Jett, R. T., Fortner, A. M., Jones, M. W., Jones, N. J., & Mathews, T. J. (2021) · Hydrological Processes · doi:10.1002/hyp.14340 · Cited by 10
Metadata
- Authors
- Parks, J. M., Johs, A., Podar, M., Bridou, R., Hurt, R. A., Smith, S. D., Tomanicek, S. J., Qian, Y., Brown, S. D., Brandt, C. C., Palumbo, A. V., Smith, J. C., Wall, J. D., Elias, D. A., & Liang, L.
- Venue
- Science
- Published
- 2013-03-15
- Volume
- 339
- Issue
- 6125
- Pages
- 1332-1335
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2004999616
- Cited by
- 965
- References
- 57
- FWCI
- 47.42
- Type
- journal article
- Language
- en
- Open access
- closed
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: The Genetic Basis for Bacterial Mercury Methylation. https://app.cochat.ai/papers/10.1126/science.1230667
- The paper
- Parks, J. M., Johs, A., Podar, M., Bridou, R., Hurt, R. A., Smith, S. D., Tomanicek, S. J., Qian, Y., Brown, S. D., Brandt, C. C., Palumbo, A. V., Smith, J. C., Wall, J. D., Elias, D. A., & Liang, L. (2013). The Genetic Basis for Bacterial Mercury Methylation. Science. https://doi.org/10.1126/science.1230667
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.