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Infectious Disease Informatics pp 93–122Cite as

Systems Microbiology: Gaining Insights in Transcriptional Networks

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Abstract

Bacteria are able to adapt to continuously changing environmental conditions. This complex cellular behavior is mediated by the underlying transcriptional network. The advent of high-throughput techniques has allowed large-scale identification of the different cellular entities, their expression patterns, and their biochemical and genetic interactions. Because different “omics” data such as transcription, regulatory motif, or ChIP-chip data unveil distinct aspects of the transcriptional network, their integration leads to a more complete insight into the biological system. Systems microbiology exploits these heterogeneous genome-wide data to obtain global insight into how different biological entities function and interact under various conditions. Several methods for the reconstruction of the corresponding transcriptional networks will be discussed in this chapter. We will also show how their application can contribute to our understanding of biological systems and lead to an improved management of bacterial infections and drug target discovery.

These authors contributed equaly to this work.

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References

  • Ackermann M, Stecher B, Freed NE et al (2008) Self-destructive cooperation mediated by phenotypic noise. Nature 454:987–990

    Article  CAS  PubMed  Google Scholar 

  • Andre J, Godelle B (2005) Multicellular organization in bacteria as a target for drug therapy. Ecol Lett 8:800–810

    Article  Google Scholar 

  • Arifuzzaman M, Maeda M, Itoh A et al (2006) Large-scale identification of protein–protein interaction of Escherichia coli K-12. Genome Res 16:686–691

    Article  CAS  PubMed  Google Scholar 

  • Baba T, Ara T, Hasegawa M et al (2006) Construction of Escherichia coli K-12 in-frame, single-gene knockout mutants: the Keio collection. Mol Syst Biol 2:2006

    Article  Google Scholar 

  • Babu MM, Teichmann SA (2003) Evolution of transcription factors and the gene regulatory network in Escherichia coli. Nucleic Acids Res 31:1234–1244

    Article  Google Scholar 

  • Balaban NQ, Merrin J, Chait R et al (2004) Bacterial persistence as a phenotypic switch. Science 305:1622–1625

    Article  CAS  PubMed  Google Scholar 

  • Bammler T, Beyer RP, Bhattacharya S et al (2005) Standardizing global gene expression analysis between laboratories and across platforms. Nat Methods 2:351–356

    Article  PubMed  Google Scholar 

  • Barrett T, Troup DB, Wilhite SE et al (2007) NCBI GEO: mining tens of millions of expression profiles – database and tools update. Nucleic Acids Res 35:D760–D765

    Article  CAS  PubMed  Google Scholar 

  • Ben Yehuda S, Fujita M, Liu XS et al (2005) Defining a centromere-like element in Bacillus subtilis by identifying the binding sites for the chromosome-anchoring protein RacA. Mol Cell 17:773–782

    Article  CAS  PubMed  Google Scholar 

  • Bergmann S, Ihmels J, Barkai N (2003) Iterative signature algorithm for the analysis of large-scale gene expression data. Phys Rev E Stat Nonlinear Soft Matter Phys 67:031902

    Google Scholar 

  • Blot N, Mavathur R, Geertz M et al (2006) Homeostatic regulation of supercoiling sensitivity coordinates transcription of the bacterial genome. EMBO Rep 7:710–715

    Article  CAS  PubMed  Google Scholar 

  • Bochner BR, Gadzinski P, Panomitros E (2001) Phenotype microarrays for high-throughput phenotypic testing and assay of gene function. Genome Res 11:1246–1255

    Article  CAS  PubMed  Google Scholar 

  • Bonneau R, Reiss DJ, Shannon P et al (2006) The Inferelator: an algorithm for learning parsimonious regulatory networks from systems-biology data sets de novo. Genome Biol 7:R36

    Article  PubMed  Google Scholar 

  • Bonneau R, Facciotti MT, Reiss DJ et al (2007) A predictive model for transcriptional control of physiology in a free living cell. Cell 131:1354–1365

    Article  CAS  PubMed  Google Scholar 

  • Brazma A, Hingamp P, Quackenbush J et al (2001) Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 29:365–371

    Article  CAS  PubMed  Google Scholar 

  • Brenner S, Johnson M, Bridgham J et al (2000) Gene expression analysis by massively parallel signature sequencing (MPSS) on microbead arrays. Nat Biotechnol 18:630–634

    Article  CAS  PubMed  Google Scholar 

  • Bruggeman FJ, Westerhoff HV (2007) The nature of systems biology. Trends Microbiol 15:45–50

    Article  CAS  PubMed  Google Scholar 

  • Bumann D (2008) Has nature already identified all useful antibacterial targets? Curr Opin Microbiol 11:387–392

    Article  CAS  PubMed  Google Scholar 

  • Butland G, Peregrin-Alvarez JM, Li J et al (2005) Interaction network containing conserved and essential protein complexes in Escherichia coli. Nature 433:531–537

    Article  CAS  PubMed  Google Scholar 

  • Butland G, Babu M, Diaz-Mejia JJ et al (2008) eSGA: E. coli synthetic genetic array analysis. Nat Methods 5:789–795

    Article  CAS  PubMed  Google Scholar 

  • Cegelski L, Marshall GR, Eldridge GR et al (2008) The biology and future prospects of antivirulence therapies. Nat Rev Microbiol 6:17–27

    Article  CAS  PubMed  Google Scholar 

  • Cheng Y, Church GM (2000) Biclustering of expression data. Proc Int Conf Intell Syst Mol Biol 8:93–103

    CAS  PubMed  Google Scholar 

  • Cho BK, Knight EM, Barrett CL et al (2008a) Genome-wide analysis of Fis binding in Escherichia coli indicates a causative role for A-/AT-tracts. Genome Res 18:900–910

    Article  CAS  PubMed  Google Scholar 

  • Cho BK, Barrett CL, Knight EM et al (2008b) Genome-scale reconstruction of the Lrp regulatory network in Escherichia coli. Proc Natl Acad Sci USA 105:19462–19467

    Article  CAS  PubMed  Google Scholar 

  • de Hoon MJ, Makita Y, Imoto S et al (2004) Predicting gene regulation by sigma factors in Bacillus subtilis from genome-wide data. Bioinform 20(Suppl 1):i101–i108

    Article  Google Scholar 

  • De Keersmaecker SC, Thijs IM, Vanderleyden J et al (2006) Integration of omics data: how well does it work for bacteria? Mol Microbiol 62:1239–1250

    Article  PubMed  Google Scholar 

  • Demeter J, Beauheim C, Gollub J et al (2007) The Stanford Microarray Database: implementation of new analysis tools and open source release of software. Nucleic Acids Res 35:D766–D770

    Article  CAS  PubMed  Google Scholar 

  • Dhollander T, Sheng Q, Lemmens K et al (2007) Query-driven module discovery in microarray data. Bioinformatics 23:2573–2580

    Article  CAS  PubMed  Google Scholar 

  • Dwyer DJ, Kohanski MA, Collins JJ (2008) Networking opportunities for bacteria. Cell 135:1153–1156

    Article  CAS  PubMed  Google Scholar 

  • Eriksson S, Lucchini S, Thompson A et al (2003) Unravelling the biology of macrophage infection by gene expression profiling of intracellular Salmonella enterica. Mol Microbiol 47:103–118

    Article  CAS  PubMed  Google Scholar 

  • Ernst J, Beg QK, Kay KA et al (2008) A semi-supervised method for predicting transcription factor–gene interactions in Escherichia coli. PLoS Comput Biol 4:e1000044

    Article  PubMed  Google Scholar 

  • Faith JJ, Hayete B, Thaden JT et al (2007) Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles. PLoS Biol 5:e8

    Article  PubMed  Google Scholar 

  • Freiberg C, Brotz-Oesterhelt H (2005) Functional genomics in antibacterial drug discovery. Drug Discov Today 10:927–935

    Article  CAS  PubMed  Google Scholar 

  • Freiberg C, Brotz-Oesterhelt H, Labischinski H (2004) The impact of transcriptome and proteome analyses on antibiotic drug discovery. Curr Opin Microbiol 7:451–459

    Article  CAS  PubMed  Google Scholar 

  • Gama-Castro S, Jimenez-Jacinto V, Peralta-Gil M et al (2008) RegulonDB (version 6.0): gene regulation model of Escherichia coli K-12 beyond transcription, active (experimental) annotated promoters and Textpresso navigation. Nucleic Acids Res 36:D120–D124

    Article  CAS  PubMed  Google Scholar 

  • Gao F, Foat BC, Bussemaker HJ (2004) Defining transcriptional networks through integrative modeling of mRNA expression and transcription factor binding data. BMC Bioinform 5:31

    Article  Google Scholar 

  • Getz G, Levine E, Domany E (2000) Coupled two-way clustering analysis of gene microarray data. Proc Natl Acad Sci USA 97:12079–12084

    Article  CAS  PubMed  Google Scholar 

  • Grainger DC, Hurd D, Harrison M et al (2005) Studies of the distribution of Escherichia coli cAMP-receptor protein and RNA polymerase along the E. coli chromosome. Proc Natl Acad Sci USA 102:17693–17698

    Article  CAS  PubMed  Google Scholar 

  • Grainger DC, Hurd D, Goldberg MD et al (2006) Association of nucleoid proteins with coding and non-coding segments of the Escherichia coli genome. Nucleic Acids Res 34:4642–4652

    Article  CAS  PubMed  Google Scholar 

  • Grainger DC, Aiba H, Hurd D et al (2007) Transcription factor distribution in Escherichia coli: studies with FNR protein. Nucleic Acids Res 35:269–278

    Article  CAS  PubMed  Google Scholar 

  • Grifantini R, Bartolini E, Muzzi A et al (2002) Previously unrecognized vaccine candidates against group B meningococcus identified by DNA microarrays. Nat Biotechnol 20:914–921

    Article  CAS  PubMed  Google Scholar 

  • Grote A, Klein J, Retter I et al (2009) PRODORIC (release 2009): a database and tool platform for the analysis of gene regulation in prokaryotes. Nucleic Acids Res 37:D61-–D65

    Article  CAS  PubMed  Google Scholar 

  • Hartwell LH, Hopfield JJ, Leibler S et al (1999) From molecular to modular cell biology. Nature 402:C47–C52

    Article  CAS  PubMed  Google Scholar 

  • Herrgard MJ, Covert MW, Palsson BO (2003) Reconciling gene expression data with known genome-scale regulatory network structures. Genome Res 13(11):2423–2434; Epub (14 Oct 12003) 13:2423–2434

    Article  CAS  PubMed  Google Scholar 

  • Hertzberg L, Zuk O, Getz G et al (2005) Finding motifs in promoter regions. J Comput Biol 12:314–330

    Article  CAS  PubMed  Google Scholar 

  • Hibbs MA, Hess DC, Myers CL et al (2007) Exploring the functional landscape of gene expression: directed search of large microarray compendia. Bioinformatics 23:2692–2699

    Article  CAS  PubMed  Google Scholar 

  • Hutter B, Schaab C, Albrecht S et al (2004) Prediction of mechanisms of action of antibacterial compounds by gene expression profiling. Antimicrob Agents Chemother 48:2838–2844

    Article  CAS  PubMed  Google Scholar 

  • Ihmels J, Bergmann S, Barkai N (2004) Defining transcription modules using large-scale gene expression data. Bioinformatics 20:1993–2003

    Article  CAS  PubMed  Google Scholar 

  • Irizarry RA, Warren D, Spencer F et al (2005) Multiple-laboratory comparison of microarray platforms. Nat Methods 2:345–350

    Article  CAS  PubMed  Google Scholar 

  • Johnson DS, Mortazavi A, Myers RM et al (2007) Genome-wide mapping of in vivo protein-DNA interactions. Science 316:1497–1502

    Article  CAS  PubMed  Google Scholar 

  • Joshi A, De SR, Marchal K et al (2009) Module networks revisited: computational assessment and prioritization of model predictions. Bioinform 25:490–496

    Article  CAS  Google Scholar 

  • Kaern M, Elston TC, Blake WJ et al (2005) Stochasticity in gene expression: from theories to phenotypes. Nat Rev Genet 6:451–464

    Article  CAS  PubMed  Google Scholar 

  • Kaushik DK, Sehgal D (2008) Developing antibacterial vaccines in genomics and proteomics era. Scand J Immunol 67:544–552

    Article  CAS  PubMed  Google Scholar 

  • Keseler IM, Bonavides-Martinez C, Collado-Vides J et al (2009) EcoCyc: a comprehensive view of Escherichia coli biology. Nucleic Acids Res 37:D464–D470

    Article  CAS  PubMed  Google Scholar 

  • Kitano H (2002) Computational systems biology. Nature 420:206–210

    Article  CAS  PubMed  Google Scholar 

  • Laub MT, Chen SL, Shapiro L et al (2002) Genes directly controlled by CtrA, a master regulator of the Caulobacter cell cycle. Proc Natl Acad Sci USA 99:4632–4637

    Article  CAS  PubMed  Google Scholar 

  • Lazzeroni L, Owen A (2002) Plaid models for gene expression data. Statist Sinica 2:61–86

    Google Scholar 

  • Lemmens K, De Bie T, Dhollander T et al (2009) DISTILLER: a data integration framework to reveal condition dependency of complex regulons in Escherichia coli. Genome Biol 10:R27

    Article  PubMed  Google Scholar 

  • Lucchini S, Rowley G, Goldberg MD et al (2006) H-NS mediates the silencing of laterally acquired genes in bacteria. PLoS Pathog 2:e81

    Article  PubMed  Google Scholar 

  • Luscombe NM, Babu MM, Yu H et al (2004) Genomic analysis of regulatory network dynamics reveals large topological changes. Nature 431:308–312

    Article  CAS  PubMed  Google Scholar 

  • Madeira SC, Oliveira AL (2004) Biclustering algorithms for biological data analysis: a survey. IEEE/ACM Trans Comput Biol Bioinform 1:24–45

    Article  CAS  PubMed  Google Scholar 

  • Marchal K, De Keersmaecker S, Monsieurs P et al (2004) In silico identification and experimental validation of PmrAB targets in Salmonella typhimurium by regulatory motif detection. Genome Biol 5:R9

    Article  PubMed  Google Scholar 

  • Margolin AA, Nemenman I, Basso K et al (2006) ARACNE: an algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context. BMC Bioinform 7(1):S7

    Article  Google Scholar 

  • Matys V, Kel-Margoulis OV, Fricke E et al (2006) TRANSFAC and its module TRANSCompel: transcriptional gene regulation in eukaryotes. Nucleic Acids Res 34:D108–D110

    Article  CAS  PubMed  Google Scholar 

  • Merrell DS, Butler SM, Qadri F et al (2002) Host-induced epidemic spread of the cholera bacterium. Nature 417:642–645

    Article  CAS  PubMed  Google Scholar 

  • Michoel T, De Smet R, Joshi A et al (2009) Comparative analysis of module-based versus direct methods for reverse-engineering transcriptional regulatory networks BMC Syst Biol 3:49

    Google Scholar 

  • Molle V, Fujita M, Jensen ST et al (2003a) The Spo0A regulon of Bacillus subtilis. Mol Microbiol 50:1683–1701

    Article  CAS  PubMed  Google Scholar 

  • Molle V, Nakaura Y, Shivers RP et al (2003b) Additional targets of the Bacillus subtilis global regulator CodY identified by chromatin immunoprecipitation and genome-wide transcript analysis. J Bacteriol 185:1911–1922

    Article  CAS  PubMed  Google Scholar 

  • Mordelet F, Vert JP (2008) SIRENE: supervised inference of regulatory networks. Bioinform 24:i76–i82

    Article  Google Scholar 

  • Murali TM, Kasif S (2003) Extracting conserved gene expression motifs from gene expression data. Pacific Symp Biocomput 8:77–88

    Google Scholar 

  • Navarre WW, Porwollik S, Wang Y et al (2006) Selective silencing of foreign DNA with low GC content by the H-NS protein in Salmonella. Science 313:236–238

    Article  CAS  PubMed  Google Scholar 

  • Orlando V (2000) Mapping chromosomal proteins in vivo by formaldehyde-crosslinked-chromatin immunoprecipitation. Trends Biochem Sci 25:99–104

    Article  CAS  PubMed  Google Scholar 

  • Parkinson H, Kapushesky M, Shojatalab M et al (2007) ArrayExpress – a public database of microarray experiments and gene expression profiles. Nucleic Acids Res 35:D747–D750

    Article  CAS  PubMed  Google Scholar 

  • Perez AG, Angarica VE, Vasconcelos AT et al (2007) Tractor_DB (version 2.0): a database of regulatory interactions in gamma-proteobacterial genomes. Nucleic Acids Res 35:D132–D136

    Article  CAS  PubMed  Google Scholar 

  • Qi Y, Ge H (2006) Modularity and dynamics of cellular networks. PLoS Comput Biol 2:e174

    Article  PubMed  Google Scholar 

  • Quackenbush J (2001) Computational analysis of microarray data. Nat Rev Genet 2:418–427

    Article  CAS  PubMed  Google Scholar 

  • Reiss DJ, Baliga NS, Bonneau R (2006) Integrated biclustering of heterogeneous genome-wide datasets for the inference of global regulatory networks. BMC Bioinform 7:280

    Article  Google Scholar 

  • Ren B, Robert F, Wyrick JJ et al (2000) Genome-wide location and function of DNA binding proteins. Science 290:2306–2309

    Article  CAS  PubMed  Google Scholar 

  • Robertson G, Hirst M, Bainbridge M et al (2007) Genome-wide profiles of STAT1 DNA association using chromatin immunoprecipitation and massively parallel sequencing. Nat Methods 4:651–657

    Article  CAS  PubMed  Google Scholar 

  • Sasik R, Woelk CH, Corbeil J (2004) Microarray truths and consequences. J Mol Endocrinol 33:1–9

    Article  CAS  PubMed  Google Scholar 

  • Segal E, Shapira M, Regev A et al (2003) Module networks: identifying regulatory modules and their condition-specific regulators from gene expression data. Nat Genet 34:166–176

    Article  CAS  PubMed  Google Scholar 

  • Sheng Q, Moreau Y, De Moor B (2003) Biclustering microarray data by Gibbs sampling. Bioinform 19(Suppl 2):ii196–ii205

    Google Scholar 

  • Shi Y, Shi Y (2004) Metabolic enzymes and coenzymes in transcription – a direct link between metabolism and transcription? Trends Genet 20:445–452

    Article  CAS  PubMed  Google Scholar 

  • Sierro N, Makita Y, de Hoon M et al (2008) DBTBS: a database of transcriptional regulation in Bacillus subtilis containing upstream intergenic conservation information. Nucleic Acids Res 36:D93–D96

    Article  CAS  PubMed  Google Scholar 

  • Stickler D (1999) Biofilms. Curr Opin Microbiol 2:270–275

    Article  CAS  PubMed  Google Scholar 

  • Stolovitzky G, Monroe D, Califano A (2007) Dialogue on reverse-engineering assessment and methods: the DREAM of high-throughput pathway inference. Ann N Y Acad Sci 1115:1–22

    Article  PubMed  Google Scholar 

  • Tanay A, Sharan R, Shamir R (2002) Discovering statistically significant biclusters in gene expression data. Bioinformatics 18(Suppl 1):S136–S144

    Google Scholar 

  • Thieffry D, Huerta AM, Perez-Rueda E et al (1998) From specific gene regulation to genomic networks: a global analysis of transcriptional regulation in Escherichia coli. Bioessays 20:433–440

    Article  CAS  PubMed  Google Scholar 

  • Thijs IM, De Keersmaecker SC, Fadda A et al (2007) Delineation of the Salmonella enterica serovar Typhimurium HilA regulon through genome-wide location and transcript analysis. J Bacteriol 189:4587–4596

    Article  CAS  PubMed  Google Scholar 

  • Tompa M, Li N, Bailey TL et al (2005) Assessing computational tools for the discovery of transcription factor binding sites. Nat Biotechnol 23:137–144

    Article  CAS  PubMed  Google Scholar 

  • Typas A, Nichols RJ, Siegele DA et al (2008) High-throughput, quantitative analyses of genetic interactions in E. coli. Nat Methods 5:781–787

    Article  CAS  PubMed  Google Scholar 

  • Van den Bulcke T, Lemmens K, Van de Peer Y et al (2006a) Inferring transcriptional networks by mining omics data. Curr Bioinform 1:301–313

    Article  Google Scholar 

  • Van den Bulcke T, Van LK, Naudts B et al (2006b) SynTReN: a generator of synthetic gene expression data for design and analysis of structure learning algorithms. BMC Bioinform 7:43

    Article  Google Scholar 

  • Voyich JM, Sturdevant DE, Braughton KR et al (2003) Genome-wide protective response used by group A Streptococcus to evade destruction by human polymorphonuclear leukocytes. Proc Natl Acad Sci USA 100:1996–2001

    Article  CAS  PubMed  Google Scholar 

  • Waters LS, Storz G (2009) Regulatory RNAs in bacteria. Cell 136:615–628

    Article  CAS  PubMed  Google Scholar 

  • Yang HL, Zhu YZ, Qin JH et al (2006) In silico and microarray-based genomic approaches to identifying potential vaccine candidates against Leptospira interrogans. BMC Genom 7:293

    Article  Google Scholar 

  • Yue H, Eastman PS, Wang BB et al (2001) An evaluation of the performance of cDNA microarrays for detecting changes in global mRNA expression. Nucleic Acids Res 29:E41

    Article  CAS  PubMed  Google Scholar 

  • Zaki MJ, Hsiao C (2002) CHARM: an efficient algorithm for closed itemset mining. In: Grossman R, Han J, Kumar V, Mannila H, Motwani R (eds) Proc Second SIAM International Conference on Data Mining (SDM ‘02)

    Google Scholar 

  • Zhou L, Lei XH, Bochner BR et al (2003) Phenotype microarray analysis of Escherichia coli K-12 mutants with deletions of all two-component systems. J Bacteriol 185:4956–4972

    Article  CAS  PubMed  Google Scholar 

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Authors and Affiliations

  1. Department of Microbial and Molecular Systems, KU Leuven, Kasteelpark Arenberg 20, 3001, Heverlee, Belgium

    Riet De Smet, Karen Lemmens, Ana Carolina Fierro & Kathleen Marchal

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  1. Riet De Smet
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  2. Karen Lemmens
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  1. Sydney Medical School, University of Sydney, Sydney, 2006, Australia

    Vitali Sintchenko

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De Smet, R., Lemmens, K., Fierro, A.C., Marchal, K. (2010). Systems Microbiology: Gaining Insights in Transcriptional Networks. In: Sintchenko, V. (eds) Infectious Disease Informatics. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-1327-2_5

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