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. 2014 Feb 3;9(2):e83979.
doi: 10.1371/journal.pone.0083979. eCollection 2014.

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

Sebastian Behrens  1 , Stefanie Widder  2 , Gopala Krishna Mannala  3 , Xiaoxing Qing  3 , Ramakanth Madhugiri  4 , Nathalie Kefer  5 , Mobarak Abu Mraheil  3 , Thomas Rattei  2 , Torsten Hain  3
Affiliations

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

Sebastian Behrens et al. PLoS One. .

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.

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Conflict of interest statement

Competing Interests: Biomarker Center GmbH) which declares (formerly known as febit biomed GmbH) that CBC, has no competing interest with the manuscript entitled “Ultra deep Sequencing of Listeria monocytogenes sRNA transcriptome revealed new antisense RNAs (see also the attached letter from CBC). N. Kefer present working address is now Life Technologies as stated in the manuscript. This does not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials.

Figures

Figure 1
Figure 1. Schematic representation of the main computational pipeline used in this study and its input and output.
The pipeline is optimized to work with sequence data from fractionated RNA samples containing RNA fragments of different lengths. Data gathered under various conditions can also be used for differential expression analysis. For this study we used data from the SOLiD High Throughput Sequencing (HTS) platform, but the pipeline will also process data from all major HTS platforms. The individual steps within the pipeline are colored either gray or orange representing steps for which existing software was used and newly implemented features respectively. The result of the pipeline will be lists of pre-classified sRNA candidates.
Figure 2
Figure 2. Pileup of reads representing the TSS of the dnaA gene of L. monocytogenes.
Reads are mapped onto the L. monocytogenes genome and depicted as horizontal lines in the top half of the figure. Forward reads are mapped above, reverse reads below the base line. Blue reads are from the sample containing RNA fragments <40 nt, green reads from the sample containing RNA between 40 nt and 150 nt, red reads from the fraction containing RNA >150 nt. The lower half of the figure shows the corresponding annotation at this genome location, with the beginning of the dnaA gene at position 318. Artemis was used to illustrate the mapped reads and annotation of the genome.
Figure 3
Figure 3. sRNAs identified by different studies – and this study and their overlap. sRNAs for this study were identified via automatic identification with our newly developed pipeline.
144 (55%) known sRNAs were recovered with the automated method. Of the 711 sRNAs identified in total, 569 were yet undescribed. The majority of these, however, were later removed due to their likely origin as transcription start site and 5′ UTR of known genes. Most of sRNAs, which were not recalled by the automated method, were found by manual reevaluation, increasing the total recall rate to 90%.
Figure 4
Figure 4. Pileup of reads representing four newly identified asRNAs of L. monocytogenes.
Putative sRNAs are marked with red boxes. Each colored line represents a mapped read either on the forward strand (above the line) or the reverse strand (below the line). Blue reads are from the sample containing RNA fragments <40 nt, green reads from the sample containing RNA between 40 and150 nt. Red reads from the sample of RNAs >150 nt. The lower half of each figure shows the corresponding annotation at this genome location. (A) anti0055 (purA). Shown is the extracellular condition. (B) anti2225 (fumC). Shown is the extracellular condition. (C) anti2330 (lmo2331) in phage locus of L. monocytogenes. Shown is the extracellular condition. (D) anti2367 (pgi). Shown is the intracellular and extracellular condition respectively. Expression of the pgi gene and the boxed antisense RNA is mutual exclusive between the two conditions.
Figure 5
Figure 5. Validation of new asRNA transcripts from L. monocytogenes and their effect on gene regulation after transition to the intracellular growth conditions.
A) The antisense RNA transcript anti0055 (purA) is validated by northern blot analysis and strand-specific qRT-PCR. The graph shows intracellular up-regulation of anti0055. B) Northern blot images of anti0055 and control 5S rRNA EC: Extracellular, IC: Intracellular. C) The presence of antisense transcripts anti2106 (lmo2106), anti2225 (fumC), and anti2330 (lmo2330) was determined by strand-specific qRT-PCR. anti2330 is down-regulated, anti2106 and anti2225 are up-regulated significantly. D) Strand-specific qRT-PCR analysis confirmed the existence and up-regulation of antisense RNA transcript anti2367. pgi (lmo2367) was down-regulated, which indicates the possible role of anti2367 in pgi gene regulation. ‘*’ P≤0.05; ‘**’ P≤0.01; ‘***’ P≤0.001.
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Grants and funding

This work was supported by grants from the German Federal Ministry of Education and Research (BMBF ERA-NET Pathogenomics Network to the sncRNAomics project (62080061) to T.H. as well as the German Centre for Infection Research, Justus-Liebig University Giessen. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.