Genome-Wide Prediction and Validation of Sigma70 Promoters in Lactobacillus plantarum WCFS1 Tilman J. Todt1,2., Michiel Wels1,3,4,5., Roger S. Bongers3,4, Roland S. Siezen1,2,3,4,5,7, Sacha A. F. T. van Hijum1,3,4,5,7*, Michiel Kleerebezem3,4,5,6 1 Center for Molecular and Biomolecular Informatics, Nijmegen Center for Molecular Life Sciences, Radboud University Medical Centre, Nijmegen, The Netherlands, 2 HAN University of Applied Sciences, Institute of Applied Sciences, Nijmegen, The Netherlands, 3 NIZO food research, Ede, The Netherlands, 4 TI Food and Nutrition, Wageningen, The Netherlands, 5 Kluyver Centre for Genomics of Industrial Fermentation, Delft, The Netherlands, 6 Wageningen University, Host Microbe Interactomics Group, Wageningen, The Netherlands, 7 Netherlands Bioinformatics Centre, Nijmegen, The Netherlands Abstract Background: In prokaryotes, sigma factors are essential for directing the transcription machinery towards promoters. Various sigma factors have been described that recognize, and bind to specific DNA sequence motifs in promoter sequences. The canonical sigma factor s70 is commonly involved in transcription of the cell’s housekeeping genes, which is mediated by the conserved s70 promoter sequence motifs. In this study the s70-promoter sequences in Lactobacillus plantarum WCFS1 were predicted using a genome-wide analysis. The accuracy of the transcriptionally-active part of this promoter prediction was subsequently evaluated by correlating locations of predicted promoters with transcription start sites inferred from the 59-ends of transcripts detected by high-resolution tiling array transcriptome datasets. Results: To identify s70-related promoter sequences, we performed a genome-wide sequence motif scan of the L. plantarum WCFS1 genome focussing on the regions upstream of protein-encoding genes. We obtained several highly conserved motifs including those resembling the conserved s70-promoter consensus. Position weight matrices-based models of the recovered s70-promoter sequence motif were employed to identify 3874 motifs with significant similarity (p- value,1024) to the model-motif in the L. plantarum genome. Genome-wide transcript information deduced from whole genome tiling-array transcriptome datasets, was used to infer transcription start sites (TSSs) from the 59-end of transcripts. By this procedure, 1167 putative TSSs were identified that were used to corroborate the transcriptionally active fraction of these predicted promoters. In total, 568 predicted promoters were found in proximity (#40 nucleotides) of the putative TSSs, showing a highly significant co-occurrence of predicted promoter and TSS (p-value,102263). Conclusions: High-resolution tiling arrays provide a suitable source to infer TSSs at a genome-wide level, and allow experimental verification of in silico predicted promoter sequence motifs. Citation: Todt TJ, Wels M, Bongers RS, Siezen RS, van Hijum SAFT, et al. (2012) Genome-Wide Prediction and Validation of Sigma70 Promoters in Lactobacillus plantarum WCFS1. PLoS ONE 7(9): e45097. doi:10.1371/journal.pone.0045097 Editor: Qing Song, Morehouse School of Medicine, United States of America Received March 26, 2012; Accepted August 14, 2012; Published September 20, 2012 Copyright: 2012 Todt et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: T.J. Todt was funded by HAN University of Applied Sciences. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: Michiel Wels, Roger S. Bongers, Roland S. Siezen, Sacha A.F.T. van Hijum and Michiel Kleerebezem are affiliated with NIZO food research and TI Food and Nutrition. Michiel Wels, Roland S. Siezen, Sacha A.F.T. van Hijum and Michiel Kleerebezem are affiliated with Kluyver Centre for Genomics of Industrial Fermentation. This does not alter the authors’ adherence to all the PLoS ONE policies on sharing data and materials.. * E-mail: svhijum@cmbi.ru.nl . These authors contributed equally to this work. Background Methods for predicting protein-coding genes have been extensively optimized [1], while the development of methodology for the structural and functional analysis of intergenic regions has only come into focus more recently. Although the fraction of non-coding and/or intergenic sequences in prokaryotic genomes is relatively low compared to eukaryotes [2], it encompasses a similar complexity in conserved DNA sequence motifs and regulatory elements [3]. In prokaryotes, elements such as binding sites for the sigma factor unit of the RNA-polymerase [4] are essential for appropriate guidance of the transcription machinery. Sigma factors enable the binding of the RNA polymerase core enzyme to the canonical promoter sequences they recognize. Various sigma factors have been identified and many bacteria possess more than one sigma factor [5], each recognizing specific DNA sequence motifs in promoters, which enables cells to respond rapidly to changing conditions by sigma factor-mediated adjustment of gene transcription patterns. Although different sigma factors recognize specific promoter sequences, the target sequence elements recognized by particular classes of sigma factors have been reported to be conserved among bacteria [4,6]. For example, s70 [7,8] and s54 [9] factors were shown to recognize similar sequences in phylogenetically distant bacterial species. Further fine-tuning of transcription activity by the sigma-factor containing RNA polymerase (e.g., harbouring the canonical s70) involves regulatory factors that either repress or activate transcription by binding to specific DNA sequence motifs PLOS ONE | www.plosone.org 1 September 2012 | Volume 7 | Issue 9 | e45097