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      Conserved and Variable Functions of the σ E Stress Response in Related Genomes

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          Abstract

          Bacteria often cope with environmental stress by inducing alternative sigma (σ) factors, which direct RNA polymerase to specific promoters, thereby inducing a set of genes called a regulon to combat the stress. To understand the conserved and organism-specific functions of each σ, it is necessary to be able to predict their promoters, so that their regulons can be followed across species. However, the variability of promoter sequences and motif spacing makes their prediction difficult. We developed and validated an accurate promoter prediction model for Escherichia coli σ E, which enabled us to predict a total of 89 unique σ E-controlled transcription units in E. coli K-12 and eight related genomes. σ E controls the envelope stress response in E. coli K-12. The portion of the regulon conserved across genomes is functionally coherent, ensuring the synthesis, assembly, and homeostasis of lipopolysaccharide and outer membrane porins, the key constituents of the outer membrane of Gram-negative bacteria. The larger variable portion is predicted to perform pathogenesis-associated functions, suggesting that σ E provides organism-specific functions necessary for optimal host interaction. The success of our promoter prediction model for σ E suggests that it will be applicable for the prediction of promoter elements for many alternative σ factors.

          Abstract

          A model for predicting the variable promoter sequences associated with the bacterial stress response is developed and used to identify constituents of the transcriptional response to σ E.

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          Molecular Cloning : A Laboratory Manual

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            Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation.

            Y. H. Yang (2002)
            There are many sources of systematic variation in cDNA microarray experiments which affect the measured gene expression levels (e.g. differences in labeling efficiency between the two fluorescent dyes). The term normalization refers to the process of removing such variation. A constant adjustment is often used to force the distribution of the intensity log ratios to have a median of zero for each slide. However, such global normalization approaches are not adequate in situations where dye biases can depend on spot overall intensity and/or spatial location within the array. This article proposes normalization methods that are based on robust local regression and account for intensity and spatial dependence in dye biases for different types of cDNA microarray experiments. The selection of appropriate controls for normalization is discussed and a novel set of controls (microarray sample pool, MSP) is introduced to aid in intensity-dependent normalization. Lastly, to allow for comparisons of expression levels across slides, a robust method based on maximum likelihood estimation is proposed to adjust for scale differences among slides.
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              Quantitative monitoring of gene expression patterns with a complementary DNA microarray.

              A high-capacity system was developed to monitor the expression of many genes in parallel. Microarrays prepared by high-speed robotic printing of complementary DNAs on glass were used for quantitative expression measurements of the corresponding genes. Because of the small format and high density of the arrays, hybridization volumes of 2 microliters could be used that enabled detection of rare transcripts in probe mixtures derived from 2 micrograms of total cellular messenger RNA. Differential expression measurements of 45 Arabidopsis genes were made by means of simultaneous, two-color fluorescence hybridization.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS Biol
                pbio
                PLoS Biology
                Public Library of Science (San Francisco, USA )
                1544-9173
                1545-7885
                January 2006
                20 December 2005
                : 4
                : 1
                : e2
                Affiliations
                [1] 1 Department of Microbiology and Immunology, University of California, San Francisco, California, United States of America
                [2] 2 Department of Cell and Tissue Biology, University of California, San Francisco, California, United States of America
                The Institute for Genomic Research United States of America
                Article
                10.1371/journal.pbio.0040002
                1312014
                16336047
                1d2cca07-5cbc-4a66-8cba-5c7dc5534e1b
                Copyright: © 2006 Rhodius et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 17 March 2005
                : 13 October 2005
                Categories
                Research Article
                Bioinformatics/Computational Biology
                Microbiology
                Systems Biology

                Life sciences
                Life sciences

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