Literature DB >> 26670742

The propagation of perturbations in rewired bacterial gene networks.

Rebecca Baumstark1,2, Sonja Hänzelmann3,4, Saburo Tsuru5, Yolanda Schaerli1,2, Mirko Francesconi1,2, Francesco M Mancuso1,6, Robert Castelo3,4, Mark Isalan1,2,7.   

Abstract

What happens to gene expression when you add new links to a gene regulatory network? To answer this question, we profile 85 network rewirings in E. coli. Here we report that concerted patterns of differential expression propagate from reconnected hub genes. The rewirings link promoter regions to different transcription factor and σ-factor genes, resulting in perturbations that span four orders of magnitude, changing up to ∼ 70% of the transcriptome. Importantly, factor connectivity and promoter activity both associate with perturbation size. Perturbations from related rewirings have more similar transcription profiles and a statistical analysis reveals ∼ 20 underlying states of the system, associating particular gene groups with rewiring constructs. We examine two large clusters (ribosomal and flagellar genes) in detail. These represent alternative global outcomes from different rewirings because of antagonism between these major cell states. This data set of systematically related perturbations enables reverse engineering and discovery of underlying network interactions.

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Year:  2015        PMID: 26670742      PMCID: PMC4703840          DOI: 10.1038/ncomms10105

Source DB:  PubMed          Journal:  Nat Commun        ISSN: 2041-1723            Impact factor:   17.694


  59 in total

1.  Integrating high-throughput and computational data elucidates bacterial networks.

Authors:  Markus W Covert; Eric M Knight; Jennifer L Reed; Markus J Herrgard; Bernhard O Palsson
Journal:  Nature       Date:  2004-05-06       Impact factor: 49.962

2.  Global transcriptional programs reveal a carbon source foraging strategy by Escherichia coli.

Authors:  Mingzhu Liu; Tim Durfee; Julio E Cabrera; Kai Zhao; Ding J Jin; Frederick R Blattner
Journal:  J Biol Chem       Date:  2005-02-10       Impact factor: 5.157

3.  Using GOstats to test gene lists for GO term association.

Authors:  S Falcon; R Gentleman
Journal:  Bioinformatics       Date:  2006-11-10       Impact factor: 6.937

4.  Reverse engineering molecular regulatory networks from microarray data with qp-graphs.

Authors:  Robert Castelo; Alberto Roverato
Journal:  J Comput Biol       Date:  2009-02       Impact factor: 1.479

Review 5.  Tackling the widespread and critical impact of batch effects in high-throughput data.

Authors:  Jeffrey T Leek; Robert B Scharpf; Héctor Corrada Bravo; David Simcha; Benjamin Langmead; W Evan Johnson; Donald Geman; Keith Baggerly; Rafael A Irizarry
Journal:  Nat Rev Genet       Date:  2010-09-14       Impact factor: 53.242

6.  Deciphering the transcriptional regulatory logic of amino acid metabolism.

Authors:  Byung-Kwan Cho; Stephen Federowicz; Young-Seoub Park; Karsten Zengler; Bernhard Ø Palsson
Journal:  Nat Chem Biol       Date:  2011-11-13       Impact factor: 15.040

7.  Effects of Fis on Escherichia coli gene expression during different growth stages.

Authors:  Meranda D Bradley; Michael B Beach; A P Jason de Koning; Timothy S Pratt; Robert Osuna
Journal:  Microbiology       Date:  2007-09       Impact factor: 2.777

8.  Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles.

Authors:  Jeremiah J Faith; Boris Hayete; Joshua T Thaden; Ilaria Mogno; Jamey Wierzbowski; Guillaume Cottarel; Simon Kasif; James J Collins; Timothy S Gardner
Journal:  PLoS Biol       Date:  2007-01       Impact factor: 8.029

9.  MEME SUITE: tools for motif discovery and searching.

Authors:  Timothy L Bailey; Mikael Boden; Fabian A Buske; Martin Frith; Charles E Grant; Luca Clementi; Jingyuan Ren; Wilfred W Li; William S Noble
Journal:  Nucleic Acids Res       Date:  2009-05-20       Impact factor: 16.971

10.  The bacterial response regulator ArcA uses a diverse binding site architecture to regulate carbon oxidation globally.

Authors:  Dan M Park; Md Sohail Akhtar; Aseem Z Ansari; Robert Landick; Patricia J Kiley
Journal:  PLoS Genet       Date:  2013-10-17       Impact factor: 5.917

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  3 in total

1.  A quantitative method for proteome reallocation using minimal regulatory interventions.

Authors:  Gustavo Lastiri-Pancardo; Jonathan S Mercado-Hernández; Juhyun Kim; José I Jiménez; José Utrilla
Journal:  Nat Chem Biol       Date:  2020-07-13       Impact factor: 15.040

2.  Scale free topology as an effective feedback system.

Authors:  Alexander Rivkind; Hallel Schreier; Naama Brenner; Omri Barak
Journal:  PLoS Comput Biol       Date:  2020-05-11       Impact factor: 4.475

3.  Regulatory perturbations of ribosome allocation in bacteria reshape the growth proteome with a trade-off in adaptation capacity.

Authors:  David Hidalgo; César A Martínez-Ortiz; Bernhard O Palsson; José I Jiménez; José Utrilla
Journal:  iScience       Date:  2022-02-07
  3 in total

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