Reliable transfer of transcriptional gene regulatory networks between taxonomically related organisms

Here we present an integrated bioinformatics workflow that assures the reliability of transferred gene regulatory networks. Our approach combines three methods that can be applied on a large-scale: re-assessment of annotated binding sites, subsequent binding site prediction, and homology detection. A gene regulatory interaction is considered to be conserved if (1) the transcription factor, (2) the adjusted binding site, and (3) the target gene are conserved. The power of the approach is demonstrated by transferring gene regulations from the model organism Corynebacterium glutamicum to the human pathogens C. diphtheriae, C. jeikeium, and the biotechnologically relevant C. efficiens. For these three organisms we identified reliable transcriptional regulations for ~40% of the common transcription factors, compared to ~5% for which knowledge was available before.Our results suggest that trustworthy genome-scale transfer of gene regulatory networks between organisms is feasible in general but still limited by the level of evolutionary conservation.In the post genome era we observe a continuously growing, vast amount of sequenced organisms spread over all domains of life. Besides the identification and annotation of functional sites within the emerging nucleic acid sequences, an important task in molecular genetics, biotechnology, and human medicine is to unravel the regulation of these sites. DNA-binding transcription factors (TFs) are the most important components of the cell's regulatory machinery [1]. They recognize specific operator sequences close-by the promoter regions of the controlled target genes, referred to as transcription factor binding sites (TFBSs), and thereby influence the amount of produced proteins. Although inevitable for the understanding of the cell's handling of changing environmental conditions, the wet-lab reconstruction of the resulting transcriptional regulatory networks is cost-intensive, time-consuming, and impossible to perform for any spec