Ultra deep sequencing of Listeria monocytogenes sRNA transcriptome revealed new antisense RNAs

Abstract

Listeria monocytogenes, a gram-positive pathogen, and causative agent of listeriosis, has become a widely used model organism for intracellular infections. Recent studies have identified small non-coding RNAs (sRNAs) as important factors for regulating gene expression and pathogenicity of L. monocytogenes. Increased speed and reduced costs of high throughput sequencing (HTS) techniques have made RNA sequencing (RNA-Seq) the state-of-the-art method to study bacterial transcriptomes. We created a large transcriptome dataset of L. monocytogenes containing a total of 21 million reads, using the SOLiD sequencing technology. The dataset contained cDNA sequences generated from L. monocytogenes RNA collected under intracellular and extracellular condition and additionally was size fractioned into three different size ranges from <40 nt, 40 150 nt and >150 nt. We report here, the identification of nine new sRNAs candidates of L. monocytogenes and a reevaluation of known sRNAs of L. monocytogenes EGD-e. Automatic comparison to known sRNAs revealed a high recovery rate of 55%, which was increased to 90% by manual revision of the data. Moreover, thorough classification of known sRNAs shed further light on their possible biological functions. Interestingly among the newly identified sRNA candidates are antisense RNAs (asRNAs) associated to the housekeeping genes purA, fumC and pgi and potentially their regulation, emphasizing the significance of sRNAs for metabolic adaptation in L. monocytogenes.