The DOI matches its Crossref record; 72 of the 72 references it cites were found in a registry or an index.
Genome‐wide analysis of the general stress response in Bacillus subtilis
Open accessAbstract
Bacteria respond to diverse growth‐limiting stresses by producing a large set of general stress proteins. In Bacillus subtilis and related Gram‐positive pathogens, this response is governed by the σ B transcription factor. To establish the range of cellular functions associated with the general stress response, we compared the transcriptional profiles of wild and mutant strains under conditions that induce σ B activity. Macroarrays representing more than 3900 annotated reading frames of the B. subtilis genome were hybridized to 33 P‐labelled cDNA populations derived from (i) wild‐type and sigB mutant strains that had been subjected to ethanol stress; and (ii) a strain in which σ B expression was controlled by an inducible promoter. On the basis of their significant σ B‐dependent expression in three independent experiments, we identified 127 genes as prime candidates for members of the σ B regulon. Of these genes, 30 were known previously or inferred to be σ B dependent by other means. To assist in the analysis of the 97 new genes, we constructed hidden Markov models (HMM) that identified possible σ B recognition sequences preceding 21 of them. To test the HMM and to provide an independent validation of the hybridization experiments, we mapped the σ B‐dependent messages for seven representative genes. For all seven, the 5′ end of the message lay near typical σ B recognition sequences, and these had been predicted correctly by the HMM for five of the seven examples. Lastly, all 127 gene products were assigned to functional groups by considering their similarity to known proteins. Notably, products with a direct protective function were in the minority. Instead, the general stress response increased relative message levels for known or predicted regulatory proteins, for transporters controlling solute influx and efflux, including potential drug efflux pumps, and for products implicated in carbon metabolism, envelope function and macromolecular turnover.
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
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
Cluster analysis and display of genome-wide expression patterns
Eisen, M. B., Spellman, P. T., Brown, P. O., & Botstein, D. (1998) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.95.25.14863 · Cited by 16,184
Bacterial Biofilms: A Common Cause of Persistent Infections
Costerton, J. W., Stewart, P. S., & Greenberg, E. P. (1999) · Science · doi:10.1126/science.284.5418.1318 · Cited by 12,167
The complete genome sequence of the gram-positive bacterium Bacillus subtilis.
Kunst, F., Ogasawara, N., Moszer, I., Albertini, A. M., Alloni, G., Azevedo, V., Bertero, M. G., Bessières, P., Bolotin, A., Borchert, S., et al. (1997) · Nature · doi:10.1038/36786 · Cited by 3,679
Biological sequence analysis probabilistic models of proteins and nucleic acids
Durbin, R. M., Eddy, S. R., Krogh, A., & Mitchison, G. (1998) · Cited by 3,565
Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids
Durbin, R., Eddy, S. R., Krogh, A., & Mitchison, G. (1998) · Cambridge University Press eBooks · doi:10.1017/cbo9780511790492 · Cited by 3,246
The Transcriptional Program in the Response of Human Fibroblasts to Serum
Iyer, V. R., Eisen, M. B., Ross, D. T., Schuler, G., Moore, T., Lee, J. C. F., Trent, J. M., Staudt, L. M., Hudson, J., Boguski, M. S., et al. (1999) · Science · doi:10.1126/science.283.5398.83 · Cited by 1,965
The COG database: new developments in phylogenetic classification of proteins from complete genomes
Tatusov, R. L. (2001) · Nucleic Acids Research · doi:10.1093/nar/29.1.22 · Cited by 1,895
The Transcriptional Program of Sporulation in Budding Yeast
Chu, S., DeRisi, J., Eisen, M., Mulholland, J., Botstein, D., Brown, P. O., & Herskowitz, I. (1998) · Science · doi:10.1126/science.282.5389.699 · Cited by 1,860
gisela-storz (2000) · Cited by 866
Cited by
Condition-Dependent Transcriptome Reveals High-Level Regulatory Architecture in Bacillus subtilis
Nicolas, P., Mäder, U., Dervyn, E., Rochat, T., Leduc, A., Pigeonneau, N., Bidnenko, E., Marchadier, E., Hoebeke, M., Aymerich, S., et al. (2012) · Science · doi:10.1126/science.1206848 · Cited by 910
Horsburgh, M. J., Aish, J. L., White, I. J., Shaw, L., Lithgow, J. K., & Foster, S. J. (2002) · Journal of Bacteriology · doi:10.1128/jb.184.19.5457-5467.2002 · Cited by 699
Stress responses in lactic acid bacteria
van de Guchte, M., Serror, P., Chervaux, C., Smokvina, T., Ehrlich, S. D., & Maguin, E. (2002) · Antonie van Leeuwenhoek · doi:10.1023/a:1020631532202 · Cited by 648
SigB-Dependent General Stress Response in Bacillus subtilis and Related Gram-Positive Bacteria
Hecker, M., Pané-Farré, J., & Uwe, V. (2007) · Annual Review of Microbiology · doi:10.1146/annurev.micro.61.080706.093445 · Cited by 474
A Comprehensive Proteomics and Transcriptomics Analysis of Bacillus subtilis Salt Stress Adaptation
Hahne, H., Mäder, U., Otto, A., Bonn, F., Steil, L., Bremer, E., Hecker, M., & Becher, D. (2010) · Journal of Bacteriology · doi:10.1128/jb.01106-09 · Cited by 183
Metadata
- Authors
- Price, C. W., Fawcett, P., Cérémonie, H., Su, N., Murphy, C. K., & Youngman, P.
- Venue
- Molecular Microbiology
- Publisher
- Wiley
- Published
- 2001-08
- Volume
- 41
- Issue
- 4
- Pages
- 757-774
- ISSN
- 0950-382X (ISSN-L)
- 1365-2958
- OpenAlex
- W1549068883
- Cited by
- 271
- References
- 72
- FWCI
- 11.56
- 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: Genome‐wide analysis of the general stress response in Bacillus subtilis. https://app.cochat.ai/papers/10.1046/j.1365-2958.2001.02534.x
- The paper
- Price, C. W., Fawcett, P., Cérémonie, H., Su, N., Murphy, C. K., & Youngman, P. (2001). Genome‐wide analysis of the general stress response in Bacillus subtilis. Molecular Microbiology. https://doi.org/10.1046/j.1365-2958.2001.02534.x
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.