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 journalArticlepeer-review


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
Issue number11
StatePublished - Nov 1 2015


  • Bacillus subtilis
  • network inference
  • sporulation
  • transcriptional networks

ASJC Scopus subject areas

  • General Biochemistry, Genetics and Molecular Biology
  • General Immunology and Microbiology
  • General Agricultural and Biological Sciences
  • Applied Mathematics


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