-
[show abstract]
[hide abstract]
ABSTRACT: Proteolytic cascades are widely implicated in signaling between cellular compartments. In Escherichia coli, accumulation of unassembled outer membrane porins (OMPs) in the envelope leads to expression of sigma(E)-dependent genes in the cytoplasmic cellular compartment. A proteolytic cascade conveys the OMP signal by regulated proteolysis of RseA, a membrane-spanning anti-sigma factor whose cytoplasmic domain inhibits sigma(E)-dependent transcription. Upon activation by OMP C termini, the membrane localized DegS protease cleaves RseA in its periplasmic domain, the membrane-embedded protease RseP (YaeL) cleaves RseA near the inner membrane, and the released cytoplasmic RseA fragment is further degraded. Initiation of RseA degradation by activated DegS makes the system sensitive to a wide range of OMP concentrations and unresponsive to variations in the levels of DegS and RseP proteases. These features rely on the inability of RseP to cleave intact RseA. In the present report, we demonstrate that RseB, which binds to the periplasmic face of RseA, and DegS each independently inhibits RseP cleavage of intact RseA. Thus, the function of RseB, widely conserved among bacteria using the sigma(E) pathway, and the second role of DegS (in addition to RseA proteolysis initiation) is to improve the performance characteristics of this signal transduction system.
Genes & Development 12/2004; 18(21):2686-97. · 11.66 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: We present an algorithm that extracts the binding sites (represented by position-specific weight matrices) for many different transcription factors from the regulatory regions of a genome, without the need for delineating groups of coregulated genes. The algorithm uses the fact that many DNA-binding proteins in bacteria bind to a bipartite motif with two short segments more conserved than the intervening region. It identifies all statistically significant patterns of the form W(1)N(x)W(2), where W(1) and W(2) are two short oligonucleotides separated by x arbitrary bases, and groups them into clusters of similar patterns. These clusters are then used to derive quantitative recognition profiles of putative regulatory proteins. For a given cluster, the algorithm finds the matching sequences plus the flanking regions in the genome and performs a multiple sequence alignment to derive position-specific weight matrices. We have analyzed the Escherichia coli genome with this algorithm and found approximately 1,500 significant patterns, which give rise to approximately 160 distinct position-specific weight matrices. A fraction of these matrices match the binding sites of one-third of the approximately 60 characterized transcription factors with high statistical significance. Many of the remaining matrices are likely to describe binding sites and regulons of uncharacterized transcription factors. The significance of these matrices was evaluated by their specificity, the location of the predicted sites, and the biological functions of the corresponding regulons, allowing us to suggest putative regulatory functions. The algorithm is efficient for analyzing newly sequenced bacterial genomes for which little is known about transcriptional regulation.
Proceedings of the National Academy of Sciences 10/2002; 99(18):11772-7. · 9.68 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: The ability to simultaneously monitor expression of all genes in any bacterium whose genome has been sequenced has only recently become available. This requires not only careful experimentation but also that voluminous data be organized and interpreted. Here we review the emerging technologies that are impacting the study of bacterial global regulatory mechanisms with a view toward discussing both perceived best practices and the current state of the art. To do this, we concentrate upon examples using Escherichia coli and Bacillus subtilis because prior work in these organisms provides a sound basis for comparison.
Annual Review of Microbiology 02/2002; 56:599-624. · 14.35 Impact Factor
