Sequencing illustrates the transcriptional response of Legionella pneumophila during infection and identifies seventy novel small non-coding RNAs

  • Weissenmayer B
  • Prendergast J
  • Lohan A
 et al. 
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Abstract

Second generation sequencing has prompted a number of groups to re-interrogate the transcriptomes of several bacterial and archaeal species. One of the central findings has been the identification of complex networks of small non-coding RNAs that play central roles in transcriptional regulation in all growth conditions and for the pathogen's interaction with and survival within host cells. Legionella pneumophila is a gram-negative facultative intracellular human pathogen with a distinct biphasic lifestyle. One of its primary environmental hosts in the free-living amoeba Acanthamoeba castellanii and its infection by L. pneumophila mimics that seen in human macrophages. Here we present analysis of strand specific sequencing of the transcriptional response of L. pneumophila during exponential and post-exponential broth growth and during the replicative and transmissive phase of infection inside A. castellanii. We extend previous microarray based studies as well as uncovering evidence of a complex regulatory architecture underpinned by numerous non-coding RNAs. Over seventy new non-coding RNAs could be identified; many of them appear to be strain specific and in configurations not previously reported. We discover a family of non-coding RNAs preferentially expressed during infection conditions and identify a second copy of 6S RNA in L. pneumophila. We show that the newly discovered putative 6S RNA as well as a number of other non-coding RNAs show evidence for antisense transcription. The nature and extent of the non-coding RNAs and their expression patterns suggests that these may well play central roles in the regulation of Legionella spp. specific traits and offer clues as to how L. pneumophila adapts to its intracellular niche. The expression profiles outlined in the study have been deposited into Genbank's Gene Expression Omnibus (GEO) database under the series accession GSE27232.

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Authors

  • Amanda LohanConway Institute, University college Dublin

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  • Barbara A. Weissenmayer

  • James G D Prendergast

  • Brendan J. Loftus

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