title: Integrative inference of gene-regulatory networks in Escherichia coli using information theoretic concepts and sequence analysis.
abstract: BACKGROUND
  Although Escherichia coli is one of the best studied model organisms, a comprehensive understanding of its gene regulation is not yet achieved. There exist many approaches to reconstruct regulatory interaction networks from gene expression experiments. Mutual information based approaches are most useful for large-scale network inference.
  
  
  RESULTS
  We used a three-step approach in which we combined gene regulatory network inference based on directed information (DTI) and sequence analysis. DTI values were calculated on a set of gene expression profiles from 19 time course experiments extracted from the Many Microbes Microarray Database. Focusing on influences between pairs of genes in which one partner encodes a transcription factor (TF) we derived a network which contains 878 TF - gene interactions of which 166 are known according to RegulonDB. Afterward, we selected a subset of 109 interactions that could be confirmed by the presence of a phylogenetically conserved binding site of the respective regulator. By this second step, the fraction of known interactions increased from 19% to 60%. In the last step, we checked the 44 of the 109 interactions not yet included in RegulonDB for functional relationships between the regulator and the target and, thus, obtained ten TF - target gene interactions. Five of them concern the regulator LexA and have already been reported in the literature. The remaining five influences describe regulations by Fis (with two novel targets), PhdR, PhoP, and KdgR. For the validation of our approach, one of them, the regulation of lipoate synthase (LipA) by the pyruvate-sensing pyruvate dehydrogenate repressor (PdhR), was experimentally checked and confirmed.
  
  
  CONCLUSIONS
  We predicted a set of five novel TF - target gene interactions in E. coli. One of them, the regulation of lipA by the transcriptional regulator PdhR was validated experimentally. Furthermore, we developed DTInfer, a new R-package for the inference of gene-regulatory networks from microarrays using directed information.
authors: Systems Biology/Bioinformatics Group, Leibniz Institute for Natural Product Research and Infection Biology - Hans Knöll Institute, Beutenbergstr, 11a, D-07745 Jena, Germany. christoph.kaleta@uni-jena.de
authors: Christoph
authors: C
authors: Kaleta
authors: Anna
authors: A
authors: Göhler
authors: Stefan
authors: S
authors: Schuster
authors: Knut
authors: K
authors: Jahreis
authors: Reinhard
authors: R
authors: Guthke
authors: Swetlana
authors: S
authors: Nikolajewa
mesh_terms: D001483:Base Sequence; D004926:Escherichia coli / Q000235:genetics* / Q000378:metabolism; D029968:Escherichia coli Proteins / Q000235:genetics / Q000378:metabolism; D053263:Gene Regulatory Networks; D023281:Genomics; D015203:Reproducibility of Results; D017422:Sequence Analysis, DNA; D049490:Systems Biology / Q000379:methods*
chemical_list: D029968:Escherichia coli Proteins