The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Influence of the Two-Component System SaeRS on Global Gene Expression in Two Different Staphylococcus aureus Strains
Open accessAbstract
The two-component system SaeRS consisting of the histidin kinase SaeS and the response regulator SaeR is known to act on virulence gene expression in Staphylococcus aureus . In order to get a more comprehensive picture on SaeR-regulated genes, we studied the contribution of the two-component system on global gene expression by using both the proteomic and transcriptomic approach. Altogether, a loss of SaeRS resulted in a decreased amount of at least 17 extracellular proteins and two cell surface-associated proteins, among them several important virulence factors such as HlgA, HlgB, HlgC, LukF, and LukM. SaeRS activates the expression of these genes at the transcriptional level. The amount of the five proteins Aur, SspA, SsaA, Plc, and GlpQ was negatively influenced by SaeRS. However, the transcription of the corresponding genes was not affected by the two-component system. SaeRS had also no measurable influence on the transcription of the regulatory genes agr , sarA , arlRS , and sigB that contribute to the regulation of SaeRS-dependent virulence factors identified in this investigation. Our results clearly show that SaeRS is strongly involved in the tight temporal control of virulence factor expression in S. aureus . Its precise role within the regulatory network remains to be determined.
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
Smyth, G. K. (2004) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1027 · Cited by 11,829
limma: Linear Models for Microarray Data
Smyth, G. K. (2005) · Statistics for Biology and Health · doi:10.1007/0-387-29362-0_23 · Cited by 5,796
Cited by
The role of antibiotics and antibiotic resistance in nature
Aminov, R. I. (2009) · Environmental Microbiology · doi:10.1111/j.1462-2920.2009.01972.x · Cited by 687
Biofilms and chronic wound inflammation
Wolcott, R. D., Rhoads, D. D., & Dowd, S. E. (2008) · Journal of Wound Care · doi:10.12968/jowc.2008.17.8.30796 · Cited by 417
Bayer, A. S., Schneider, T., & Sahl, H. (2013) · Annals of the New York Academy of Sciences · doi:10.1111/j.1749-6632.2012.06819.x · Cited by 311
Basis of Virulence in Enterotoxin-Mediated Staphylococcal Food Poisoning
Fisher, E. L., Otto, M., & Cheung, G. Y. C. (2018) · Frontiers in Microbiology · doi:10.3389/fmicb.2018.00436 · Cited by 285
Megli, C. J., Carlin, S. M., Giacobe, E. J., Hillebrand, G. H., & Hooven, T. A. (2025) · Virulence · doi:10.1080/21505594.2025.2451173 · Cited by 24
Metadata
- Authors
- Rogasch, K., Rühmling, V., Pané-Farré, J., Höper, D., Weinberg, C., Fuchs, S., Schmudde, M., Bröker, B. M., Wolz, C., Hecker, M., & Engelmann, S.
- Venue
- Journal of Bacteriology
- Publisher
- American Society for Microbiology
- Published
- 2006-11-15
- Volume
- 188
- Issue
- 22
- Pages
- 7742-7758
- ISSN
- 0021-9193 (ISSN-L)
- 1098-5530
- OpenAlex
- W2135403526
- Cited by
- 188
- References
- 2
- FWCI
- 5.35
- 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: Influence of the Two-Component System SaeRS on Global Gene Expression in Two Different Staphylococcus aureus Strains. https://app.cochat.ai/papers/10.1128/jb.00555-06
- The paper
- Rogasch, K., Rühmling, V., Pané-Farré, J., Höper, D., Weinberg, C., Fuchs, S., Schmudde, M., Bröker, B. M., Wolz, C., Hecker, M., & Engelmann, S. (2006). Influence of the Two-Component System SaeRS on Global Gene Expression in Two Different Staphylococcus aureus Strains. Journal of Bacteriology. https://doi.org/10.1128/jb.00555-06
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.