| Autor: |
Larsen SJ; Department of Mathematics and Computer Science, University of Southern Denmark, Campusvej 55, 5230 Odense, Denmark., Röttger R; Department of Mathematics and Computer Science, University of Southern Denmark, Campusvej 55, 5230 Odense, Denmark., Schmidt HHHW; Department of Pharmacology and Personalised Medicine, MaCSBio, Maastricht University, Universiteitssingel 60, 6229 ER, Maastricht, The Netherlands., Baumbach J; Department of Mathematics and Computer Science, University of Southern Denmark, Campusvej 55, 5230 Odense, Denmark.; Chair of Experimental Bioinformatics, Wissenschaftszentrum Weihenstephan, Technical University of Munich, Maximus-von-Imhof-Forum 3, 85354 Freising-Weihenstephan, Germany. |
| Abstrakt: |
Gene regulatory networks (GRNs) and gene expression data form a core element of systems biology-based phenotyping. Changes in the expression of transcription factors are commonly believed to have a causal effect on the expression of their targets. Here we evaluated in the best researched model organism, Escherichia coli, the consistency between a GRN and a large gene expression compendium. Surprisingly, a modest correlation was observed between the expression of transcription factors and their targets and, most noteworthy, both activating and repressing interactions were associated with positive correlation. When evaluated using a sign consistency model we found the regulatory network was not more consistent with measured expression than random network models. We conclude that, at least in E. coli, one cannot expect a causal relationship between the expression of transcription and factors their targets, and that the current static GRN does not adequately explain transcriptional regulation. The implications of this are profound as they question what we consider established knowledge of the systemic biology of cells and point to methodological limitations with respect to single omics analysis, static networks and temporality. |
