An experimentally supported model of the Bacillus subtilis global transcriptional regulatory network

Mario L. Arrieta-Ortiz, Christoph Hafemeister, Ashley Rose Bate, Timothy Chu, Alex Greenfield, Bentley Shuster, Samantha N. Barry, Matthew Gallitto, Brian Liu, Thadeous Kacmarczyk, Francis Santoriello, Jie Chen, Christopher Da Rodrigues, Tsutomu Sato, David Z. Rudner, Adam Driks, Richard Bonneau, Patrick Eichenberger

Research output: Contribution to journalArticle

Abstract

Organisms from all domains of life use gene regulation networks to control cell growth, identity, function, and responses to environmental challenges. Although accurate global regulatory models would provide critical evolutionary and functional insights, they remain incomplete, even for the best studied organisms. Efforts to build comprehensive networks are confounded by challenges including network scale, degree of connectivity, complexity of organism-environment interactions, and difficulty of estimating the activity of regulatory factors. Taking advantage of the large number of known regulatory interactions in Bacillus subtilis and two transcriptomics datasets (including one with 38 separate experiments collected specifically for this study), we use a new combination of network component analysis and model selection to simultaneously estimate transcription factor activities and learn a substantially expanded transcriptional regulatory network for this bacterium. In total, we predict 2,258 novel regulatory interactions and recall 74% of the previously known interactions. We obtained experimental support for 391 (out of 635 evaluated) novel regulatory edges (62% accuracy), thus significantly increasing our understanding of various cell processes, such as spore formation.

Original languageEnglish (US)
Article number839
JournalMolecular systems biology [electronic resource].
Volume11
Issue number11
DOIs
StatePublished - Nov 1 2015

Fingerprint

Gene Regulatory Networks
Regulatory Networks
Bacilli
Bacillus subtilis
Network components
Transcription factors
organisms
Cell growth
Spores
Interaction
Gene expression
Bacteria
Transcription Factors
Identity function
transcriptomics
new combination
Gene Regulation
cell growth
Cell
transcription factors

Keywords

  • Bacillus subtilis
  • network inference
  • sporulation
  • transcriptional networks

ASJC Scopus subject areas

  • Applied Mathematics
  • Information Systems
  • Computational Theory and Mathematics
  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Medicine(all)

Cite this

An experimentally supported model of the Bacillus subtilis global transcriptional regulatory network. / Arrieta-Ortiz, Mario L.; Hafemeister, Christoph; Bate, Ashley Rose; Chu, Timothy; Greenfield, Alex; Shuster, Bentley; Barry, Samantha N.; Gallitto, Matthew; Liu, Brian; Kacmarczyk, Thadeous; Santoriello, Francis; Chen, Jie; Rodrigues, Christopher Da; Sato, Tsutomu; Rudner, David Z.; Driks, Adam; Bonneau, Richard; Eichenberger, Patrick.

In: Molecular systems biology [electronic resource]., Vol. 11, No. 11, 839, 01.11.2015.

Research output: Contribution to journalArticle

Arrieta-Ortiz, ML, Hafemeister, C, Bate, AR, Chu, T, Greenfield, A, Shuster, B, Barry, SN, Gallitto, M, Liu, B, Kacmarczyk, T, Santoriello, F, Chen, J, Rodrigues, CD, Sato, T, Rudner, DZ, Driks, A, Bonneau, R & Eichenberger, P 2015, 'An experimentally supported model of the Bacillus subtilis global transcriptional regulatory network', Molecular systems biology [electronic resource]., vol. 11, no. 11, 839. https://doi.org/10.15252/msb.20156236
Arrieta-Ortiz, Mario L. ; Hafemeister, Christoph ; Bate, Ashley Rose ; Chu, Timothy ; Greenfield, Alex ; Shuster, Bentley ; Barry, Samantha N. ; Gallitto, Matthew ; Liu, Brian ; Kacmarczyk, Thadeous ; Santoriello, Francis ; Chen, Jie ; Rodrigues, Christopher Da ; Sato, Tsutomu ; Rudner, David Z. ; Driks, Adam ; Bonneau, Richard ; Eichenberger, Patrick. / An experimentally supported model of the Bacillus subtilis global transcriptional regulatory network. In: Molecular systems biology [electronic resource]. 2015 ; Vol. 11, No. 11.
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