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Bioinformatics. 1998 Jun;14(5):391-400.

Prediction of transcriptional regulatory sites in the complete genome sequence of Escherichia coli K-12.

Author information

  • 1Centro de Investigación sobre Fijación de Nitrógeno, Universidad Nacional Autónoma de México, AP 565-A, Cuernavaca, Morelos 62100, México.

Abstract

MOTIVATION:

As one of the best-characterized free-living organisms, Escherichia coli and its recently completed genomic sequence offer a special opportunity to exploit systematically the variety of regulatory data available in the literature in order to make a comprehensive set of regulatory predictions in the whole genome.

RESULTS:

The complete genome sequence of E.coli was analyzed for the binding of transcriptional regulators upstream of coding sequences. The biological information contained in RegulonDB (Huerta, A.M. et al., Nucleic Acids Res.,26,55-60, 1998) for 56 different transcriptional proteins was the support to implement a stringent strategy combining string search and weight matrices. We estimate that our search included representatives of 15-25% of the total number of regulatory binding proteins in E.coli. This search was performed on the set of 4288 putative regulatory regions, each 450 bp long. Within the regions with predicted sites, 89% are regulated by one protein and 81% involve only one site. These numbers are reasonably consistent with the distribution of experimental regulatory sites. Regulatory sites are found in 603 regions corresponding to 16% of operon regions and 10% of intra-operonic regions. Additional evidence gives stronger support to some of these predictions, including the position of the site, biological consistency with the function of the downstream gene, as well as genetic evidence for the regulatory interaction. The predictions described here were incorporated into the map presented in the paper describing the complete E.coli genome (Blattner,F.R. et al., Science, 277, 1453-1461, 1997).

AVAILABILITY:

The complete set of predictions in GenBank format is available at the url: http://www. cifn.unam.mx/Computational_Biology/E.coli-predictions

CONTACT:

ecoli-reg@cifn.unam.mx, collado@cifn.unam.mx

PMID:
9682052
[PubMed - indexed for MEDLINE]
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