The propagation of perturbations in rewired bacterial gene networks

Rebecca Baumstark, Sonja Hänzelmann, Saburo Tsuru, Yolanda Schaerli, Mirko Francesconi, Francesco M. Mancuso, Robert Castelo and Mark Isalan ()
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Rebecca Baumstark: EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG)
Sonja Hänzelmann: Research Program on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM)
Saburo Tsuru: Graduate School of Information Science and Technology, Osaka University
Yolanda Schaerli: EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG)
Mirko Francesconi: EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG)
Francesco M. Mancuso: EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG)
Robert Castelo: Research Program on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM)
Mark Isalan: EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG)

Nature Communications, 2015, vol. 6, issue 1, 1-11

Abstract: 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.

Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:6:y:2015:i:1:d:10.1038_ncomms10105

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DOI: 10.1038/ncomms10105

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