A genome-wide study of gene expression regulation in the Gram-negative fish pathogen Aliivibrio salmonicida

Abstract

Regulation of gene expression is essential for all bacteria to function and survive. The expression of genes into proteins is dependent on a number of steps, each of which can be subjected to regulation. In the literature much emphasis has typically been placed on transcriptional regulation, but during recent years gene regulation at the post-transcriptional level has also gained much attention. One contributing factor to this shift in knowledge is the accumulating amount of genomic data that has become available, and computational methods now play important roles in mapping expression regulation (such as genomic features). In this present work the Gram-negative fish pathogen Aliivibrio salmonicida has been used as a model for computational genome-wide predictions of transcription factor binding sites (TFBSs) and prediction of small regulatory RNAs (sRNAs). In Paper 1, a bioinformatical search for Ferric uptake regulator (Fur) TFBSs resulted in the identification of several genes previously not known to be regulated by Fur. The prediction and validation of genes that encode sRNAs in Paper 2 increased the knowledge of the non-coding RNA pool in our model system. Paper 3 and Paper 4 provide in-depth studies on two of the identified sRNAs from Paper 2, the Spot42 homolog and the novel VSsrna24. Overall, the results from these studies have increased our general understanding on gene regulation in A. salmonicida. In addition, the work has generated a number of good starting points for future experiments.