| RprA RNA | |
|---|---|
 |
|
| Predicted secondary structure and sequence conservation of RprA | |
| Identifiers | |
| Symbol | RprA |
| Rfam | RF00034 |
| Other data | |
| RNA type | Gene; sRNA |
| Domain(s) | Bacteria |
| SO | 0000387 |
The RprA RNA gene encodes a 106 nucleotide regulatory non-coding RNA. Translational regulation of the stationary phase sigma factor RpoS is mediated by the formation of a double-stranded RNA stem-loop structure in the upstream region of the rpoS messenger RNA, occluding the translation initiation site. [1] [2] Clones carrying rprA (RpoS regulator RNA A) increased the translation of RpoS. As with DsrA, RprA is predicted to form three stem-loops. Thus, at least two small RNAs, DsrA and RprA, participate in the positive regulation of RpoS translation. RprA also appears to bind to the RpoS leader.[3] RprA is non-essential.[4] Wasserman et al. demonstrated that this RNA is bound by the Hfq protein.[5] In the presence of Hfq the stability of RprA is influenced by the osmolarity of the cell, this is dependent on the endoribonuclease RNase E.[6]
It has been shown the RprA regulates the protein coding genes, called csgD, this protein encodes a stationary phase-induced biofilm regulator and ydaM, which encodes a diguanylate cyclase involved in activating csgD transcription. These two target genes are repressed by RprA which results in regulation of biofilm formation.[7]
References [link]
- ^ Updegrove T, Wilf N, Sun X, Wartell RM (2008). "Effect of Hfq on RprA-rpoS mRNA pairing: Hfq-RNA binding and the influence of the 5' rpoS mRNA leader region.". Biochemistry 47 (43): 11184–95. DOI:10.1021/bi800479p. PMID 18826256.
- ^ Jones AM, Goodwill A, Elliott T (2006). "Limited Role for the DsrA and RprA Regulatory RNAs in rpoS Regulation in Salmonella enterica". J Bacteriol 188 (14): 5077–88. DOI:10.1128/JB.00206-06. PMC 1539969. PMID 16816180. //www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=1539969.
- ^ Majdalani, N; Hernandez D, Gottesman S (2002). "Regulation and mode of action of the second small RNA activator of RpoS translation, RprA". Mol Microbiol 46 (3): 813–826. DOI:10.1046/j.1365-2958.2002.03203.x. PMID 12410838.
- ^ Majdalani, N; Chen S, Murrow J, St John K, Gottesman S (2001). "Regulation of RpoS by a novel small RNA: the characterization of RprA". Mol Microbiol 39 (5): 1382–1394. DOI:10.1111/j.1365-2958.2001.02329.x. PMID 11251852.
- ^ Wassarman KM, Repoila F, Rosenow C, Storz G, Gottesman S (2001). "Identification of novel small RNAs using comparative genomics and microarrays". Genes Dev. 15 (13): 1637–51. DOI:10.1101/gad.901001. PMC 312727. PMID 11445539. //www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=312727.
- ^ Madhugiri R, Basineni SR, Klug G (2010). "Turn-over of the small non-coding RNA RprA in E. coli is influenced by osmolarity". Mol Genet Genomics 284 (4): 307–18. DOI:10.1007/s00438-010-0568-x. PMID 20717695.
- ^ Mika F, Busse S, Possling A, Berkholz J, Tschowri N, Sommerfeldt N, Pruteanu M, Hengge R (2012). "Targeting of csgD by the small regulatory RNA RprA links stationary phase, biofilm formation and cell envelope stress in Escherichia coli.". Mol Microbiol. PMID 22356413.
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Some RNA molecules play an active role within cells by catalyzing biological reactions, controlling gene expression, or sensing and communicating responses to cellular signals. One of these active processes is protein synthesis, a universal function wherein mRNA molecules direct the assembly of proteins on ribosomes. This process uses transfer RNA (tRNA) molecules to deliver amino acids to the ribosome, where ribosomal RNA (rRNA) then links amino acids together to form proteins.
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The algorithm is conceptually distinct from other methods for predicting microRNA:mRNA heteroduplexes in that it does not use experimentally validated heteroduplexes for training, instead relying only on the sequences of known mature miRNAs that are found in the public databases. The key idea of rna22 is that the reverse complement of any salient sequence features that one can identify in mature microRNA sequences (using pattern discovery techniques) should allow one to identify candidate microRNA target sites in a sequence of interest: rna22 makes use of the Teiresias algorithm to discover such salient features. Once a candidate microRNA target site has been located, the targeting microRNA can be identified with the help of any of several algorithms able to compute RNA:RNA heteroduplexes. A new version (v2.0) of the algorithm is now available: v2.0-beta adds probability estimates to each prediction, gives users the ability to choose the sensitivity/specificity settings on-the-fly, is significantly faster than the original, and can be accessed through http://cm.jefferson.edu/rna22/Interactive/.
