Discovery and profiling of small RNAs responsive to stress conditions in the plant pathogen Pectobacterium atrosepticum

Stanford Kwenda, Vladimir Gorshkov, Aadi Moolam Ramesh, Sanushka Naidoo, Enrico Rubagotti, Paul R J Birch, Lucy N. Moleleki (Lead / Corresponding author)

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Abstract

Background: Small RNAs (sRNAs) have emerged as important regulatory molecules and have been studied in several bacteria. However, to date, there have been no whole-transcriptome studies on sRNAs in any of the Soft Rot Enterobacteriaceae (SRE) group of pathogens. Although the main ecological niches for these pathogens are plants, a significant part of their life cycle is undertaken outside their host within adverse soil environment. However, the mechanisms of SRE adaptation to this harsh nutrient-deficient environment are poorly understood. Results: In the study reported herein, by using strand-specific RNA-seq analysis and in silico sRNA predictions, we describe the sRNA pool of Pectobacterium atrosepticum and reveal numerous sRNA candidates, including those that are induced during starvation-activated stress responses. Consequently, strand-specific RNA-seq enabled detection of 137 sRNAs and sRNA candidates under starvation conditions; 25 of these sRNAs were predicted for this bacterium in silico. Functional annotations were computationally assigned to 68 sRNAs. The expression of sRNAs in P. atrosepticum was compared under growth-promoting and starvation conditions: 68 sRNAs were differentially expressed with 47 sRNAs up-regulated under nutrient-deficient conditions. Conservation analysis using BLAST showed that most of the identified sRNAs are conserved within the SRE. Subsequently, we identified 9 novel sRNAs within the P. atrosepticum genome. Conclusions: Since many of the identified sRNAs are starvation-induced, the results of our study suggests that sRNAs play key roles in bacterial adaptive response. Finally, this work provides a basis for future experimental characterization and validation of sRNAs in plant pathogens.

Original languageEnglish
Article number47
Number of pages15
JournalBMC Genomics
Volume17
DOIs
Publication statusPublished - 12 Jan 2016

Keywords

  • 3' UTR
  • 5' UTR
  • in silico prediction
  • Pectobacterium atrosepticum
  • Riboswitches
  • Small RNAs
  • Strand-specific RNA-seq
  • Transcriptome

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