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Small RNA-Based Regulation of Bacterial Quorum Sensing and Biofilm Formation

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  • Author: Sine Lo Svenningsen1
  • Editors: Gisela Storz2, Kai Papenfort3
  • VIEW AFFILIATIONS HIDE AFFILIATIONS
    Affiliations: 1: Department of Biology, University of Copenhagen, 2200 Copenhagen, Denmark; 2: Division of Molecular and Cellular Biology, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD; 3: Department of Biology I, Microbiology, LMU Munich, Martinsried, Germany
  • Source: microbiolspec July 2018 vol. 6 no. 4 doi:10.1128/microbiolspec.RWR-0017-2018
  • Received 03 January 2018 Accepted 07 March 2018 Published 13 July 2018
  • Sine Lo Svenningsen, SLS@bio.ku.dk
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  • Abstract:

    Quorum sensing is a vital property of bacteria that enables community-wide coordination of collective behaviors. A key example of such a behavior is biofilm formation, in which groups of bacteria invest in synthesizing a protective, joint extracellular matrix. Quorum sensing involves the production, release, and subsequent detection of extracellular signaling molecules called autoinducers. The architecture of quorum-sensing signal transduction pathways is highly variable among different species of bacteria, but frequently involves posttranscriptional regulation carried out by small regulatory RNA molecules. This review illustrates the diverse roles small -acting regulatory RNAs can play, from constituting a network’s core to auxiliary roles in adjusting the rate of autoinducer synthesis, mediating cross talk among different parts of a network, or integrating different regulatory inputs to trigger appropriate changes in gene expression. The emphasis is on describing how the study of small RNA-based regulation in quorum sensing and biofilm formation has uncovered new general properties or expanded our understanding of bacterial riboregulation.

  • Citation: Svenningsen S. 2018. Small RNA-Based Regulation of Bacterial Quorum Sensing and Biofilm Formation. Microbiol Spectrum 6(4):RWR-0017-2018. doi:10.1128/microbiolspec.RWR-0017-2018.

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/content/journal/microbiolspec/10.1128/microbiolspec.RWR-0017-2018
2018-07-13
2018-07-18

Abstract:

Quorum sensing is a vital property of bacteria that enables community-wide coordination of collective behaviors. A key example of such a behavior is biofilm formation, in which groups of bacteria invest in synthesizing a protective, joint extracellular matrix. Quorum sensing involves the production, release, and subsequent detection of extracellular signaling molecules called autoinducers. The architecture of quorum-sensing signal transduction pathways is highly variable among different species of bacteria, but frequently involves posttranscriptional regulation carried out by small regulatory RNA molecules. This review illustrates the diverse roles small -acting regulatory RNAs can play, from constituting a network’s core to auxiliary roles in adjusting the rate of autoinducer synthesis, mediating cross talk among different parts of a network, or integrating different regulatory inputs to trigger appropriate changes in gene expression. The emphasis is on describing how the study of small RNA-based regulation in quorum sensing and biofilm formation has uncovered new general properties or expanded our understanding of bacterial riboregulation.

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Image of FIGURE 1
FIGURE 1

RNAIII of . (a) The QS pathway of . Direct posttranscriptional effects of RNAIII (blue oval) on target mRNAs are shown as green arrows (positive regulation) or red blocked arrows (negative regulation). The positive feedback loop of the system is depicted as light blue arrows from the RNAII operon to AgrA∼P. Transcriptional regulation is shown by black arrows. Groups of genes that are regulated but in an RNAIII-independent manner are included as targets of AgrA∼P, although direct transcriptional regulation by AgrA∼P has only been demonstrated for RNAII, RNAIII, and the α- and β-PSMs ( 42 , 191 ). (b) Secondary structure of RNAIII. The ORF is shown in black. Three C-rich regions involved in base-pairing with target mRNAs are shown in red. Adapted from structure determined by Benito et al. ( 46 ) and depicted using Forna ( 192 ). (c) The RNA-based double selector switch of .

Source: microbiolspec July 2018 vol. 6 no. 4 doi:10.1128/microbiolspec.RWR-0017-2018
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Image of FIGURE 2
FIGURE 2

QS regulation by the Qrr sRNAs in . (a) Secondary structure of Qrr4. The region that is completely conserved among Qrr1 to -5 in is shown in red. The 9 nt of stem-loop 1 that are missing in Qrr1 are shown in green. Modified from Shao et al. ( 81 ) and depicted using Forna ( 192 ). (b) The QS pathway of . The symbols and colors are used as in Fig. 1 . Direct autorepression by the transcription factors is omitted for clarity but has been demonstrated for all three of the transcription factors shown (LuxO, AphA, and LuxR). LCD genes, genes expressed at low cell density; HCD genes, genes expressed at high cell density.

Source: microbiolspec July 2018 vol. 6 no. 4 doi:10.1128/microbiolspec.RWR-0017-2018
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Image of FIGURE 3
FIGURE 3

sRNA-based regulation of AI synthase production. AI synthases are shown as red rectangles with a red arrow pointing to the structure of the AI(s) they produce. A curved arrow from the AI to its receptor (brown rectangles) indicates activation of the receptor upon binding to the AI, whereas a curved blocked arrow indicates inactivation of the receptor upon AI binding. Posttranscriptional regulatory interactions are shown by green arrows (increased translation) or red blocked arrows (decreased translation), and transcriptional regulatory interactions are depicted in black. Known signals/conditions that affect sRNA expression are shown below each sRNA. (a) Positive feedback control of 3-oxo-C6-HSL synthesis in . (b) Repression of the HAI-1 synthase, LuxM, by the Qrr sRNAs in . Blocked arrow from HAI-1 to LuxN indicates that HAI-1 binding blocks the kinase activity of LuxN. The phosphatase activity of LuxN is not affected by AI binding ( 193 ). The dashed arrow indicates that LuxN promotes transcription indirectly through a phosphorelay when LuxN is acting as a kinase (see Fig. 2b ). (c) Positive feedback control of C8-HSL synthesis in involves a single Qrr sRNA. Symbols are as in panel b. (d) Positive effect of the RsmYZ sRNAs on the LasI and RhlI AHL synthases of . Regulatory interactions between the two QS systems are excluded for clarity. (e) Positive effects of the ReaL and PhrS sRNAs on PQS production in . (f) Repression of AHL production by the RscR1 sRNA. SinI produces a range of long-chain AHLs, exemplified here by -(tetrahydro-2-oxo-3-furanyl)-dodecanamide ( 194 ). (g) CyaR sRNA represses translation of the AI-2 synthase LuxS in . The depicted isoform of AI-2 is -2-methyl-2,3,3,4-tetrahydroxytetrahydrofuran (R-THMF), which is the AI-2 isoform typically recognized by the Lsr machinery that transports AI-2 into the cytoplasm. AI-2 is phosphorylated before AI-2∼P binds and inactivates the LsrR transcriptional repressor. Inactivation of LsrR feeds back to affect extra- and intracellular AI-2 levels because it derepresses production of the Lsr transport system, which leads to increased AI-2 internalization and depletion of extracellular AI-2. That feedback loop is not included here since it does not affect AI-2 synthesis (reviewed in reference 11 ).

Source: microbiolspec July 2018 vol. 6 no. 4 doi:10.1128/microbiolspec.RWR-0017-2018
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FIGURE 4

Posttranscriptional control of key biofilm regulators in K-12. Direct posttranscriptional effects of sRNAs (blue ovals) on five protein regulators central to the biofilm/motility switch (colored rectangles) are shown as green arrows (positive regulation) or red blocked arrows (negative regulation). Only direct sRNA-target interactions are shown, although several additional sRNAs indirectly regulate one or more of the five targets ( 159 , 164 ). Some transcriptional regulation is included to provide context, but many important regulators and interactions are omitted for clarity. These include all proteins involved in c-di-GMP signaling, and interactions concerning σ-factor competition (reviewed in reference 160 ).

Source: microbiolspec July 2018 vol. 6 no. 4 doi:10.1128/microbiolspec.RWR-0017-2018
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