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  • Proceedings of the National Academy of Sciences  (3)
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  • Proceedings of the National Academy of Sciences  (3)
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  • 1
    Online Resource
    Online Resource
    Proceedings of the National Academy of Sciences ; 2011
    In:  Proceedings of the National Academy of Sciences Vol. 108, No. 31 ( 2011-08-02), p. 12875-12880
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 108, No. 31 ( 2011-08-02), p. 12875-12880
    Abstract: The Escherichia coli σ E envelope stress response monitors and repairs the outer membrane, a function central to the life of Gram-negative bacteria. The σ E stress response was characterized as a single-tier activation network comprised of ∼100 genes, including the MicA and RybB noncoding sRNAs. These highly expressed sRNAs were thought to carry out the specialized function of halting de novo synthesis of several abundant porins when envelope homeostasis was perturbed. Using a systematic target profiling and validation approach we discovered that MicA and RybB are each global mRNA repressors of both distinct and shared targets, and that the two sRNAs constitute a posttranscriptional repression arm whose regulatory scope rivals that of the protein-based σ E activation arm. Intriguingly, porin mRNAs constitute only ∼1/3 of all targets and new nonporin targets predict roles for MicA and RybB in crosstalk with other regulatory responses. This work also provides an example of evolutionarily unrelated sRNAs that are coinduced and bind the same targets, but at different sites. Our finding that expression of either MicA or RybB sRNA protects the cell from the loss of viability experienced when σ E activity is inadequate illustrates the importance of the posttranscriptional repression arm of the response. σ E is a paradigm of a single-tier stress response with a clear division of labor in which highly expressed noncoding RNAs (MicA, RybB) endow a transcriptional factor intrinsically restricted to gene activation (σ E ) with the opposite repressor function.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    RVK:
    RVK:
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2011
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Online Resource
    Online Resource
    Proceedings of the National Academy of Sciences ; 2002
    In:  Proceedings of the National Academy of Sciences Vol. 99, No. 18 ( 2002-09-03), p. 11772-11777
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 99, No. 18 ( 2002-09-03), p. 11772-11777
    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 ≈1,500 significant patterns, which give rise to ≈160 distinct position-specific weight matrices. A fraction of these matrices match the binding sites of one-third of the ≈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.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    RVK:
    RVK:
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2002
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    Online Resource
    Online Resource
    Proceedings of the National Academy of Sciences ; 2010
    In:  Proceedings of the National Academy of Sciences Vol. 107, No. 7 ( 2010-02-16), p. 2854-2859
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 107, No. 7 ( 2010-02-16), p. 2854-2859
    Abstract: Sequenced bacterial genomes provide a wealth of information but little understanding of transcriptional regulatory circuits largely because accurate prediction of promoters is difficult. We examined two important issues for accurate promoter prediction: (1) the ability to predict promoter strength and (2) the sequence properties that distinguish between active and weak/inactive promoters. We addressed promoter prediction using natural core promoters recognized by the well-studied alternative sigma factor, Escherichia coli σ E , as a representative of group 4  σ s, the largest σ group. To evaluate the contribution of sequence to promoter strength and function, we used modular position weight matrix models comprised of each promoter motif and a penalty score for suboptimal motif location. We find that a combination of select modules is moderately predictive of promoter strength and that imposing minimal motif scores distinguished active from weak/inactive promoters. The combined -35/-10 score is the most important predictor of activity. Our models also identified key sequence features associated with active promoters. A conserved “AAC” motif in the -35 region is likely to be a general predictor of function for promoters recognized by group 4  σ s. These results provide valuable insights into sequences that govern promoter strength, distinguish active and inactive promoters for the first time, and are applicable to both in vivo and in vitro measures of promoter strength.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    RVK:
    RVK:
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2010
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
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