Inferring the transcriptional network of Bacillus subtilis

Abeer A. Fadda, Ana Carolina Fierro, Karen Lemmens, Pieter Monsieurs, Kristof Engelen, Kathleen Marchal

Research output: Contribution to journalArticle

26 Citations (Scopus)

Abstract

The adaptation of bacteria to the vigorous environmental changes they undergo is crucial to their survival. They achieve this adaptation partly via intricate regulation of the transcription of their genes. In this study, we infer the transcriptional network of the Gram-positive model organism, Bacillus subtilis. We use a data integration workflow, exploiting both motif and expression data, towards the generation of condition-dependent transcriptional modules. In building the motif data, we rely on both known and predicted information. Known motifs were derived from DBTBS, while predicted motifs were generated by a de novo motif detection method that utilizes comparative genomics. The expression data consists of a compendium of microarrays across different platforms. Our results indicate that a considerable part of the B. subtilis network is yet undiscovered; we could predict 417 new regulatory interactions for known regulators and 453 interactions for yet uncharacterized regulators. The regulators in our network showed a preference for regulating modules in certain environmental conditions. Also, substantial condition-dependent intra-operonic regulation seems to take place. Global regulators seem to require functional flexibility to attain their roles by acting as both activators and repressors.

Original languageEnglish
Pages (from-to)1840-1852
Number of pages13
JournalMolecular BioSystems
Volume5
Issue number12
DOIs
Publication statusPublished - 2009
Externally publishedYes

Fingerprint

Gene Regulatory Networks
Bacillus subtilis
Workflow
Genomics
Bacteria
Genes

ASJC Scopus subject areas

  • Biotechnology
  • Molecular Biology

Cite this

Fadda, A. A., Fierro, A. C., Lemmens, K., Monsieurs, P., Engelen, K., & Marchal, K. (2009). Inferring the transcriptional network of Bacillus subtilis. Molecular BioSystems, 5(12), 1840-1852. https://doi.org/10.1039/b907310h

Inferring the transcriptional network of Bacillus subtilis. / Fadda, Abeer A.; Fierro, Ana Carolina; Lemmens, Karen; Monsieurs, Pieter; Engelen, Kristof; Marchal, Kathleen.

In: Molecular BioSystems, Vol. 5, No. 12, 2009, p. 1840-1852.

Research output: Contribution to journalArticle

Fadda, AA, Fierro, AC, Lemmens, K, Monsieurs, P, Engelen, K & Marchal, K 2009, 'Inferring the transcriptional network of Bacillus subtilis', Molecular BioSystems, vol. 5, no. 12, pp. 1840-1852. https://doi.org/10.1039/b907310h
Fadda AA, Fierro AC, Lemmens K, Monsieurs P, Engelen K, Marchal K. Inferring the transcriptional network of Bacillus subtilis. Molecular BioSystems. 2009;5(12):1840-1852. https://doi.org/10.1039/b907310h
Fadda, Abeer A. ; Fierro, Ana Carolina ; Lemmens, Karen ; Monsieurs, Pieter ; Engelen, Kristof ; Marchal, Kathleen. / Inferring the transcriptional network of Bacillus subtilis. In: Molecular BioSystems. 2009 ; Vol. 5, No. 12. pp. 1840-1852.
@article{79ff4ea266bb48809e489a313126a969,
title = "Inferring the transcriptional network of Bacillus subtilis",
abstract = "The adaptation of bacteria to the vigorous environmental changes they undergo is crucial to their survival. They achieve this adaptation partly via intricate regulation of the transcription of their genes. In this study, we infer the transcriptional network of the Gram-positive model organism, Bacillus subtilis. We use a data integration workflow, exploiting both motif and expression data, towards the generation of condition-dependent transcriptional modules. In building the motif data, we rely on both known and predicted information. Known motifs were derived from DBTBS, while predicted motifs were generated by a de novo motif detection method that utilizes comparative genomics. The expression data consists of a compendium of microarrays across different platforms. Our results indicate that a considerable part of the B. subtilis network is yet undiscovered; we could predict 417 new regulatory interactions for known regulators and 453 interactions for yet uncharacterized regulators. The regulators in our network showed a preference for regulating modules in certain environmental conditions. Also, substantial condition-dependent intra-operonic regulation seems to take place. Global regulators seem to require functional flexibility to attain their roles by acting as both activators and repressors.",
author = "Fadda, {Abeer A.} and Fierro, {Ana Carolina} and Karen Lemmens and Pieter Monsieurs and Kristof Engelen and Kathleen Marchal",
year = "2009",
doi = "10.1039/b907310h",
language = "English",
volume = "5",
pages = "1840--1852",
journal = "Molecular BioSystems",
issn = "1742-206X",
publisher = "Royal Society of Chemistry",
number = "12",

}

TY - JOUR

T1 - Inferring the transcriptional network of Bacillus subtilis

AU - Fadda, Abeer A.

AU - Fierro, Ana Carolina

AU - Lemmens, Karen

AU - Monsieurs, Pieter

AU - Engelen, Kristof

AU - Marchal, Kathleen

PY - 2009

Y1 - 2009

N2 - The adaptation of bacteria to the vigorous environmental changes they undergo is crucial to their survival. They achieve this adaptation partly via intricate regulation of the transcription of their genes. In this study, we infer the transcriptional network of the Gram-positive model organism, Bacillus subtilis. We use a data integration workflow, exploiting both motif and expression data, towards the generation of condition-dependent transcriptional modules. In building the motif data, we rely on both known and predicted information. Known motifs were derived from DBTBS, while predicted motifs were generated by a de novo motif detection method that utilizes comparative genomics. The expression data consists of a compendium of microarrays across different platforms. Our results indicate that a considerable part of the B. subtilis network is yet undiscovered; we could predict 417 new regulatory interactions for known regulators and 453 interactions for yet uncharacterized regulators. The regulators in our network showed a preference for regulating modules in certain environmental conditions. Also, substantial condition-dependent intra-operonic regulation seems to take place. Global regulators seem to require functional flexibility to attain their roles by acting as both activators and repressors.

AB - The adaptation of bacteria to the vigorous environmental changes they undergo is crucial to their survival. They achieve this adaptation partly via intricate regulation of the transcription of their genes. In this study, we infer the transcriptional network of the Gram-positive model organism, Bacillus subtilis. We use a data integration workflow, exploiting both motif and expression data, towards the generation of condition-dependent transcriptional modules. In building the motif data, we rely on both known and predicted information. Known motifs were derived from DBTBS, while predicted motifs were generated by a de novo motif detection method that utilizes comparative genomics. The expression data consists of a compendium of microarrays across different platforms. Our results indicate that a considerable part of the B. subtilis network is yet undiscovered; we could predict 417 new regulatory interactions for known regulators and 453 interactions for yet uncharacterized regulators. The regulators in our network showed a preference for regulating modules in certain environmental conditions. Also, substantial condition-dependent intra-operonic regulation seems to take place. Global regulators seem to require functional flexibility to attain their roles by acting as both activators and repressors.

UR - http://www.scopus.com/inward/record.url?scp=73149094538&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=73149094538&partnerID=8YFLogxK

U2 - 10.1039/b907310h

DO - 10.1039/b907310h

M3 - Article

VL - 5

SP - 1840

EP - 1852

JO - Molecular BioSystems

JF - Molecular BioSystems

SN - 1742-206X

IS - 12

ER -