The DOI matches its Crossref record.
Multicenter Evaluation of a Sequence-Based Protocol for Subtyping Shiga Toxins and Standardizing Stx Nomenclature
Open accessAbstract
When Shiga toxin-producing Escherichia coli (STEC) strains emerged as agents of human disease, two types of toxin were identified: Shiga toxin type 1 (Stx1) (almost identical to Shiga toxin produced by Shigella dysenteriae type 1) and the immunologically distinct type 2 (Stx2). Subsequently, numerous STEC strains have been characterized that express toxins with variations in amino acid sequence, some of which confer unique biological properties. These variants were grouped within the Stx1 or Stx2 type and often assigned names to indicate that they were not identical in sequence or phenotype to the main Stx1 or Stx2 type. A lack of specificity or consistency in toxin nomenclature has led to much confusion in the characterization of STEC strains. Because serious outcomes of infection have been attributed to certain Stx subtypes and less so with others, we sought to better define the toxin subtypes within the main Stx1 and Stx2 types. We compared the levels of relatedness of 285 valid sequence variants of Stx1 and Stx2 and identified common sequences characteristic of each of three Stx/Stx1 and seven Stx2 subtypes. A novel, simple PCR subtyping method was developed, independently tested on a battery of 48 prototypic STEC strains, and improved at six clinical and research centers to test the reproducibility, sensitivity, and specificity of the PCR. Using a consistent schema for nomenclature of the Stx toxins and stx genes by phylogenetic sequence-based relatedness of the holotoxin proteins, we developed a typing approach that should obviate the need to bioassay each newly described toxin and that predicts important biological characteristics.
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
Cited by
Joensen, K. G., Tetzschner, A. M. M., Iguchi, A., Aarestrup, F. M., & Scheutz, F. (2015) · Journal of Clinical Microbiology · doi:10.1128/jcm.00008-15 · Cited by 915
Self-citationThe European Union One Health 2018 Zoonoses Report
European Food Safety Authority and European Centre for Disease Prevention and Control (EFSA and ECDC) (2019) · EFSA Journal · doi:10.2903/j.efsa.2019.5926 · Cited by 874
Shane, A. L., Mody, R. K., Crump, J. A., Tarr, P. I., Steiner, T. S., Kotloff, K., Langley, J. M., Wanke, C., Warren, C. A., Cheng, A. C., et al. (2017) · Clinical Infectious Diseases · doi:10.1093/cid/cix669 · Cited by 627
Steil, D., Schepers, C.-L., Pohlentz, G., Legros, N., Runde, J., Humpf, H.-U., Karch, H., & Müthing, J. (2015) · Journal of Lipid Research · doi:10.1194/jlr.m063040 · Cited by 31
Self-citation
Metadata
- Authors
- Scheutz, F., Teel, L. D., Beutin, L., Piérard, D., Buvens, G., Karch, H., Mellmann, A., Caprioli, A., Tozzoli, R., Morabito, S., Strockbine, N. A., Melton-Celsa, A. R., Sanchez, M., Persson, S., & O'Brien, A. D.
- Venue
- Journal of Clinical Microbiology
- Publisher
- American Society for Microbiology
- Published
- 2012-09
- Volume
- 50
- Issue
- 9
- Pages
- 2951-2963
- ISSN
- 0095-1137 (ISSN-L)
- 1098-660X
- OpenAlex
- W2051567318
- Cited by
- 830
- References
- 0
- FWCI
- 37.40
- Type
- journal article
- Language
- en
- Open access
- bronze
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: Multicenter Evaluation of a Sequence-Based Protocol for Subtyping Shiga Toxins and Standardizing Stx Nomenclature. https://app.cochat.ai/papers/10.1128/jcm.00860-12
- The paper
- Scheutz, F., Teel, L. D., Beutin, L., Piérard, D., Buvens, G., Karch, H., Mellmann, A., Caprioli, A., Tozzoli, R., Morabito, S., Strockbine, N. A., Melton-Celsa, A. R., Sanchez, M., Persson, S., & O'Brien, A. D. (2012). Multicenter Evaluation of a Sequence-Based Protocol for Subtyping Shiga Toxins and Standardizing Stx Nomenclature. Journal of Clinical Microbiology. https://doi.org/10.1128/jcm.00860-12
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.