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Updated: Apr 24, 2026

A Non-Coding Small RNA MicC Contributes to Virulence in Outer Membrane Proteins in Salmonella Enteritidis
Published on: January 27, 2021
Expression of antisense small RNAs in response to stress in Pseudomonas aeruginosa
María Gómez-Lozano, Rasmus L Marvig, Monica V L Tulstrup
1Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark. sm@bio.dtu.dk.
Background:
RNA sequencing technologies reveal that bacteria express RNA molecules other than mRNA, rRNA or tRNA. During the last years genome-wide bacterial transcriptomes have been shown to comprise intergenic RNA, antisense RNA, and untranslated regions, all capable of performing diverse regulatory functions.
Results:
In this study we used RNA-seq to identify 232 antisense RNAs (asRNAs) in the opportunistic pathogen Pseudomonas aeruginosa grown under 13 different conditions. The conditions studied include exponential and stationary growth as well as osmotic, oxidative and antibiotic stress. We found a significant overrepresentation of asRNAs that are transcribed opposite to genes involved in cell division and in cell wall, lipopolysaccharide (LPS), and capsule biosynthesis, most likely reflecting the conditions used in this study. A substantial number of asRNAs significantly changed their expression under osmotic, oxidative and antibiotic stress, suggesting that asRNAs may play regulatory roles during these conditions. We also made a comparison between the asRNAs detected in this study in P. aeruginosa PAO1 with the asRNAs detected in two previous studies in P. aeruginosa PA14, and found that the extent of overlap between the studies is very limited.
Conclusions:
RNA-seq experiments are revealing hundreds of novel transcripts in all bacterial genomes investigated. The comparison between independent studies that used RNA-seq to detect novel asRNAs in P. aeruginosa shows that the overlap between the results reported is very narrow. It is necessary to address how reproducibility of these kind of studies should be reported in order to avoid misleading conclusions when comparing data generated by non-identical methods.
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