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      Combinatorial control of diverse metabolic and physiological functions by transcriptional regulators of the yeast sulfur assimilation pathway

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          Abstract

          The sulfur assimilation pathway is used to understand how combinatorial transcription coordinates cellular processes. Global gene expression was measured in yeast lacking different combinations of transcription factors in order to determine how these factors coordinate sulfur assimilation with diverse metabolic and physiological processes.

          Abstract

          Methionine abundance affects diverse cellular functions, including cell division, redox homeostasis, survival under starvation, and oxidative stress response. Regulation of the methionine biosynthetic pathway involves three DNA-binding proteins—Met31p, Met32p, and Cbf1p. We hypothesized that there exists a “division of labor” among these proteins that facilitates coordination of methionine biosynthesis with diverse biological processes. To explore combinatorial control in this regulatory circuit, we deleted CBF1, MET31, and MET32 individually and in combination in a strain lacking methionine synthase. We followed genome-wide gene expression as these strains were starved for methionine. Using a combination of bioinformatic methods, we found that these regulators control genes involved in biological processes downstream of sulfur assimilation; many of these processes had not previously been documented as methionine dependent. We also found that the different factors have overlapping but distinct functions. In particular, Met31p and Met32p are important in regulating methionine metabolism, whereas p functions as a “generalist” transcription factor that is not specific to methionine metabolism. In addition, Met31p and Met32p appear to regulate iron–sulfur cluster biogenesis through direct and indirect mechanisms and have distinguishable target specificities. Finally, CBF1 deletion sometimes has the opposite effect on gene expression from MET31 and MET32 deletion.

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          Most cited references40

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          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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            Network motifs in the transcriptional regulation network of Escherichia coli

            Little is known about the design principles of transcriptional regulation networks that control gene expression in cells. Recent advances in data collection and analysis, however, are generating unprecedented amounts of information about gene regulation networks. To understand these complex wiring diagrams, we sought to break down such networks into basic building blocks. We generalize the notion of motifs, widely used for sequence analysis, to the level of networks. We define 'network motifs' as patterns of interconnections that recur in many different parts of a network at frequencies much higher than those found in randomized networks. We applied new algorithms for systematically detecting network motifs to one of the best-characterized regulation networks, that of direct transcriptional interactions in Escherichia coli. We find that much of the network is composed of repeated appearances of three highly significant motifs. Each network motif has a specific function in determining gene expression, such as generating temporal expression programs and governing the responses to fluctuating external signals. The motif structure also allows an easily interpretable view of the entire known transcriptional network of the organism. This approach may help define the basic computational elements of other biological networks.
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              Transcriptional regulatory networks in Saccharomyces cerevisiae.

              We have determined how most of the transcriptional regulators encoded in the eukaryote Saccharomyces cerevisiae associate with genes across the genome in living cells. Just as maps of metabolic networks describe the potential pathways that may be used by a cell to accomplish metabolic processes, this network of regulator-gene interactions describes potential pathways yeast cells can use to regulate global gene expression programs. We use this information to identify network motifs, the simplest units of network architecture, and demonstrate that an automated process can use motifs to assemble a transcriptional regulatory network structure. Our results reveal that eukaryotic cellular functions are highly connected through networks of transcriptional regulators that regulate other transcriptional regulators.
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                Author and article information

                Contributors
                Role: Monitoring Editor
                Journal
                Mol Biol Cell
                Mol. Biol. Cell
                molbiolcell
                mbc
                Mol. Bio. Cell
                Molecular Biology of the Cell
                The American Society for Cell Biology
                1059-1524
                1939-4586
                01 August 2012
                : 23
                : 15
                : 3008-3024
                Affiliations
                [1] aThe Lewis-Sigler Institute for Integrative Genomics, Columbia University, New York, NY 10027
                [2] bGraduate Program in Quantitative and Computational Biology, Columbia University, New York, NY 10027
                [3] cDepartment of Biological Sciences, Columbia University, New York, NY 10027
                [4] dDepartment of Molecular Biology, Princeton University, Princeton, NJ 08544
                University of Toronto
                Author notes

                †These authors contributed equally.

                *Present addresses: Department of Human Genetics, University of Chicago, Chicago, IL 60637

                ‡Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138.

                1Address correspondence to: Allegra A. Petti ( allegra.conbrio@ 123456post.harvard.edu ), David Botstein ( botstein@ 123456genomics.princeton.edu ).
                Article
                E12-03-0233
                10.1091/mbc.E12-03-0233
                3408426
                22696679
                2127ee2f-24e3-437f-b572-112448eeec79
                © 2012 Petti et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License ( http://creativecommons.org/licenses/by-nc-sa/3.0).

                “ASCB®,” “The American Society for Cell Biology®,” and “Molecular Biology of the Cell®” are registered trademarks of The American Society of Cell BD; are registered trademarks of The American Society of Cell Biology.

                History
                : 23 March 2012
                : 04 June 2012
                : 06 June 2012
                Categories
                Articles
                Systems Biology

                Molecular biology
                Molecular biology

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