RECTA: Regulon Identification Based on Comparative Genomics and Transcriptomics Analysis

Acid stress caused by lactate increment can lead to the growth inhibition of bacteria and yes has not been fully defined. Regulons, serve as co-regulated gene groups contribute to the transcriptional regulation of microbe genome, have the potential in understanding the underlying regulatory mechanism. Lactococcus lactis is one of the most important Gram-positive lactic acid-producing bacteria, widely used in food industry and has been proved to have advantages in oral delivery of drug and vaccine. In this study, we designed a novel computational pipeline, RECTA, for regulon prediction. The pipeline carried out differentially expressed gene prediction, gene co-expression analysis, cis-regulatory motif finding, and comparative genomic study to predict and validate regulons related to acid stress response in Lactococcus lactis MG1363. A total of 51 regulons were identified, and 14 of them have computational verified significance. Among these 14 regulons, five of them were computationally predicted to be connected with acid stress response with (i) known transcriptional factors in MEME suite database successfully mapped in Lactococcus lactis MG1363; and (ii) differentially expressed genes between pH values of 6.5 (control) and 5.1 (treatment). Validated by 36 literature confirmed acid stress response related proteins and genes, 33 genes in Lactococcus lactis MG1363 were found having orthologous genes using BLAST, associated to six regulons. An acid response related regulatory network was constructed, involving two trans-membrane proteins, eight regulons (llrA, llrC, hllA, ccpA, NHP6A, rcfB, regulons #8 and #39), nine functional modules, and 33 genes with orthologous genes known to be associated to acid stress. Our RECTA pipeline provides an effective way to construct a reliable gene regulatory network based on regulon elucidation. The predicted resistance pathways could serve as promising candidates for better acid tolerance engineering in Lactococcus lactis. It has a strong application power and can be effectively applied to other bacterial genomes, where the elucidation of the transcriptional regulation network is needed.