Experimental approaches to identify small RNAs and their diverse roles in bacteria--what we have learnt in one decade of MicA research

Abstract

Nowadays the identification of small RNAs (sRNAs) and characterization of their role within regulatory networks takes a prominent place in deciphering complex bacterial phenotypes. Compared to the study of other components of bacterial cells, this is a relatively new but fast-growing research field. Although reports on new sRNAs appear regularly, some sRNAs are already subject of research for a longer time. One of such sRNAs is MicA, a sRNA best described for its role in outer membrane remodeling, but probably having a much broader function than anticipated. An overview of what we have learnt from MicA led to the conclusion that even for this well-described sRNA, we still do not have the overall picture. More general, the story of MicA might become an experimental lead for unraveling the many sRNAs with unknown functions. In this review, three important topics in the sRNA field are covered, exemplified from the perspective of MicA: (i) identification of new sRNAs, (ii) target identification and unraveling the biological function, (iii) structural analysis. The complex mechanisms of action of MicA deliver some original insights in the sRNA field which includes the existence of dimer formation or simultaneous cis and trans regulation, and might further inspire the understanding of the function of other sRNAs.

Keywords: Conservation; MicA; sRNA; structure; target identification.

Figure 1

Genomic region of micA in Escherichia coli. The genomic region of micA and its neighboring genes luxS and gshA are schematically shown. The transcription start sites of luxS, as determined by Udekwu (2010) are indicated.

Figure 2

Conservation of MicA among the Enterobacteriaceae. (A) Homologous MicA sequences were searched with Basic Local Alignment Search Tool (BLAST) (http://blast.ncbi.nlm.nih.gov/Blast.cgi) of the E. coli MG1655 K-12 (U00096.3) MicA sequence over the complete nucleotide collection of NCBI. Conserved sequences were selected from Shigella flexneri 2a str. 301 (AE005674.2), Salmonella bongori N268-08 (CP006608.1), Salmonella enterica subsp. enterica serovar Typhimurium SL1344 (FQ312003.1), Citrobacter rodentium ICC168 (FN543502.1), Enterobacter cloacae subsp. cloacae ENHKU01 (CP003737.1), Serratia liquefaciens ATCC 27592 (CP006252.1), Yersinia enterocolitica (type O:5) YE53/03 (HF571988.1), Yersinia pestis Z176003 (CP001593.1), Cronobacter sakazakii CMCC 45402 (CP006731.1), Klebsiella pneumoniae subsp. pneumoniae KP5-1 (CP008700.1), Pantoea ananatis LMG 5342 (HE617160.1), Erwinia amylovora ATCC 49946 (FN666575.1), Rahnella aquatilis HX2 (CP003403.1), Pectobacterium carotovorum subsp. carotovorum PCC21 (CP003776.1), Dickeya dadantii 3937 (CP002038.1), Edwardsiella tarda EIB202 (CP001135.1), Raoultella ornithinolytica B6 (CP004142.1), Sodalis sp. HS1 (CP006569.1). An alignment of these sequences, mapped on the E. coli reference sequence of MicA, is shown. The position of stem loop 1 (SL 1), stem loop 2 (SL 2) and alternative stem loop 1 (SL 1′) as determined by Udekwu et al. (2005), Rasmussen et al. (2005) and Henderson et al. (2013) is mapped on the E. coli sequence. The functional properties of these structures are described below in this review. (B) A phylogenetic tree was built using PHYLM based on the alignment shown in panel A. The Tamurai-Nei algorithm was used with a bootstrap of 1000 repeats.

Figure 3

Schematic overview of the MicA regulatory network. MicA is controlled by the envelope stress sigma factor (σ^E) and directly acts upon many mRNAs. The effect on the antisense encoded luxS remains unclear, as well as the possibility for more unknown targets. MicA has been shown to be linked to functionalities such as motility, biofilm formation and virulence. Until today, these effects cannot be directly explained by known targets (for references, see text).

Figure 4

Different conformations of MicA. (A) In the unbound MicA conformation, the target mRNA binding region is partly blocked by loop 1 (Rasmussen et al. ; Udekwu et al. 2005). (B) Upon target mRNA binding, the MicA conformation changes which causes that the mRNA binding region is completely exposed for binding (Udekwu et al. ; Henderson et al. 2013). The black lines indicate the mRNA complementary region and the Hfq binding site as predicted by Rasmussen et al. (2005). The conformational switch between the structures shown in panel A and B is dependent upon whether MicA is bound to its target mRNA or not. (C) MicA dimerization as predicted by Henderson et al. (2013). Based on the alignment described and shown in Figure2A, mean pairwise identities were calculated per nucleotide of the E. coli reference MicA sequence (calculated with the Geneious software package (Biomatters Limited). The nucleotides are colored by their identity percentage (nucleotides with at least 0, 10, 20, 30, 40, 50, 60, 70, 80, and 90% identity).