Small RNAs endow a transcriptional activator with essential repressor functions for single-tier control of a global stress regulon

Contributed by Carol A. Gross, June 20, 2011 (sent for review May 10, 2011)
July 18, 2011
108 (31) 12875-12880

Abstract

The Escherichia coli σE envelope stress response monitors and repairs the outer membrane, a function central to the life of Gram-negative bacteria. The σE stress response was characterized as a single-tier activation network comprised of ∼100 genes, including the MicA and RybB noncoding sRNAs. These highly expressed sRNAs were thought to carry out the specialized function of halting de novo synthesis of several abundant porins when envelope homeostasis was perturbed. Using a systematic target profiling and validation approach we discovered that MicA and RybB are each global mRNA repressors of both distinct and shared targets, and that the two sRNAs constitute a posttranscriptional repression arm whose regulatory scope rivals that of the protein-based σE activation arm. Intriguingly, porin mRNAs constitute only ∼1/3 of all targets and new nonporin targets predict roles for MicA and RybB in crosstalk with other regulatory responses. This work also provides an example of evolutionarily unrelated sRNAs that are coinduced and bind the same targets, but at different sites. Our finding that expression of either MicA or RybB sRNA protects the cell from the loss of viability experienced when σE activity is inadequate illustrates the importance of the posttranscriptional repression arm of the response. σE is a paradigm of a single-tier stress response with a clear division of labor in which highly expressed noncoding RNAs (MicA, RybB) endow a transcriptional factor intrinsically restricted to gene activation (σE) with the opposite repressor function.
Bacteria respond to cellular stresses and environmental cues by altering the activity of transcription factors. The mode of DNA binding by the transcription factor determines whether it is an activator, repressor or both. Dual activity can be advantageous because it permits simultaneous activation of some genes while repressing incompatible genes and boosts regulatory versatility within a transcriptional network by increasing the achievable number of network motifs in bacteria (e.g., feed-forward loops; ref. 1). The alternative solution, recruiting an opposite regulatory activity through a downstream transcription factor, is rare in bacteria.
The σE response to envelope stress is one of the best characterized bacterial transcription programs (2). σE is sequestered in an inactive form at the inner membrane under nonstress conditions. Perturbation of envelope homeostasis, caused by damage of the outer membrane (OM) or the accumulation of unfolded outer membrane proteins (OMPs) such as porins, triggers release of σE to the cytoplasm, where it directs RNA polymerase to transcribe the σE regulon (Fig. 1). Promoters recognized by σE have been mapped to saturation in Escherichia coli, revealing that σE directly activates ∼60 transcriptional units that comprise a total of ∼100 genes (3, 4). The few targets with transcriptional function (rpoE, rpoH, greA) potentiate positive regulation, suggesting that the σE network is restricted to transcriptional activation. Thus, repressors boosting complexity must operate posttranscriptionally. Intriguingly, the distribution of promoter strengths in the σE regulon suggests candidates for such repressors (Fig. 1), as two of the three strong promoters transcribe small noncoding RNAs (sRNAs).
Fig. 1.
Initiation of the σE response and its immediate effects. This figure illustrates how the σE response has both activator (protein arm) and repressor (sRNA arm) functions that act primarily to survey and maintain cell envelope homeostasis. Genes targeted for down-regulation by the known σE-dependent sRNAs are shown in the Venn diagrams; those in blue are outer membrane proteins or lipoproteins associated with the cell envelope.
These two sRNAs, MicA and RybB, are conserved in many enterobacteria and belong to the growing class of sRNAs associated with the RNA chaperone Hfq that use short base pairing interactions to modulate the translation and decay rates of trans-encoded target mRNAs (5, 6). Previous studies of MicA and RybB in E. coli and Salmonella showed that both repress the synthesis of several major OMPs by binding in the 5′ mRNA region (715). This has led to a simplistic model that the specialized function of these sRNAs is to halt de novo synthesis of very abundant OMPs upon σE induction. However, the full target suites of MicA and RybB were unknown, and biocomputational algorithms readily predicted many additional mRNA interactions. Additionally, Hfq and σE oppositely regulated a number of E. coli mRNAs, as expected if they were MicA and RybB targets (16). Finally, σE induced repression of several E. coli mRNAs, such as ompX and fiu, required Hfq, again suggesting regulation by a σE-dependent sRNA (4, 16).
Using a systematic target profiling and validation approach, we discovered that MicA and RybB are each global repressors of both distinct and shared targets, the latter resulting in convergent target regulation by bacterial sRNAs. These two noncoding regulators constitute a posttranscriptional repression arm that is of roughly comparable regulatory scope to the protein-based transcriptional activation arm of the σE response, playing a far broader role than simply preventing the accumulation of unassembled OMPs. We demonstrate that it is the combined activity of the activation and repression arms that enables single-tier transcription factor σE to monitor and maintain a trait as complex as envelope homeostasis.

Results

Quality Control Functions of MicA and RybB Are Central to the σE Response.

Lack of σE is lethal to E. coli (17). Analyses of suppressors of rpoE deletion strains suggested that lethality results from induction of a cell death pathway as a result of imbalanced expression of other envelope stress responses (18, 19). To evaluate the physiological impact of MicA and RybB, we used cell death as readout after targeted shutoff of σE following overexpression of its two antagonists, RseA and RseB. When active σE is depleted by RseA/B overexpression, growth ceases prematurely and viability decreases (Fig. 2), as reported in ref. 19. Importantly, concomitant overexpression of either MicA or RybB rescues both growth and viability phenotypes exhibited following σE shutoff (Fig. 2 A and B). Rescue by MicA or RybB does not result from inadequate inactivation of σE: Upon RseAB overexpression, σE activity is similarly low whether or not MicA or RybB is overexpressed (Fig. 2C). Together, these results indicate that the repressor function of each sRNA provides σE with an immediate stress reduction response to imbalances in the OM that is sufficient to avert cell death. Parenthetically, as expected, overexpression of either MicA or RybB prevents the normal growth-phase dependent increase in σE activity (Fig. 2C), most likely because reducing OMP synthesis is known to decrease σE activity (2).
Fig. 2.
RybB and MicA protect cells from lysis during σE shutoff. The growth (A), viability (B), and σE activity (C) of strains before and after overexpression of RseA/B in the σE shutoff plasmid (+: contains σE shutoff plasmid; −: empty vector plasmid) without (−sRNA plasmid) or with concomitant overexpression of the plasmid-encoded sRNA (RybB or MicA). rseAB as well as MicA and RybB are controlled by IPTG inducible promoters. (A) The strain with the σE shutoff plasmid only (+σE shutoff, −sRNA plasmid; filled black squares) exhibited decreased growth upon σE shutoff; all other strains grew almost identically as shown by the overlapping symbols. (B) The strain with σE shutoff plasmid only (+σE shutoff, −sRNA plasmid) showed reduced colony forming units following σE shutoff. Concomitant overexpression of either sRNA (+σE shutoff, RybB; +σE shutoff, MicA) fully restored viability. (C) σE activity of each strain shown in A both before and after σE shutoff/sRNA overexpression was determined from the β-galactosidase activity of a chromosomally encoded σE dependent rpoHP3-lacZ reporter. Bacteria grown overnight at 30 °C in LB with ampicillin and chloramphenicol were subcultured to OD600 = 0.03 in fresh media and grown at 30 °C. IPTG (1 mM) was added just before 135 min of growth (OD600 ∼ 0.1) to induce overexpression of RseA/B, MicA and RybB, as indicated by the arrow. The “−” sample was taken just before 135 min of growth, and the “+” sample was taken at 255 min of growth. The average of three experiments with SD is shown.

Combinatorial Target Searches Identify MicA and RybB as Regulators With Global Reach.

To comprehensively define the target suite of the two sRNAs, we used high-density tiling arrays to identify changes in mRNA abundance after short overexpression of MicA or RybB from inducible plasmids. We used four different conditions to accommodate the possibility that regulation was growth-phase specific (exponential vs. stationary phase), as noted previously for the Hfq-associated ArcZ sRNA (20), or media specific (glucose vs. maltose; columns 1–6 of Table S1, Table S2, and Fig. S1A).
We identified 31 regulated mRNAs, all of which were negatively regulated; 80% responded in at least three conditions, and ∼20% were condition specific. Quantitative real-time PCR (qRT-PCR) validated that RybB regulated 16 genes; MicA regulated 9 genes; and both sRNAs regulated 6 genes (Fig. 1). Importantly, although previous results suggested that RybB had only two targets in E. coli (10), the candidate targets in the new data set include all Salmonella targets identified for RybB (7, 11). An exception is the ompN mRNA, which was not regulated in E. coli, likely because of two critical bases in the mapped RybB site that differ from Salmonella ompN (Fig. S1C; ref. 9). As suggested previously (16), the yhcN and lpp mRNAs gave a very small (≤twofold) change to both σE or sRNA overexpression, suggesting little regulation, or regulation taking place solely at the level of translation (Fig. S1C). MicA and RybB not only down-regulate all major E. coli porins, but also have many additional candidate targets, including some without envelope related functions. Thus, the two sRNAs are global regulators, controlling many mRNAs transcribed from physically unlinked genes.
We determined whether targets were also repressed by overexpression of σE, as expected because this condition induces chromosomal MicA and RybB (10, 12, 21). Many targets (15 in total) were significantly repressed under this condition (column 2 of Table S1), but three targets were up-regulated (htrG, yfeK, and yhjJ). All three genes have upstream σE-dependent promoters (4), leading to net up-regulation irrespective of concomitant posttranscriptional repression of their mRNAs by MicA and/or RybB. No significant σE-dependent regulation was observed for 13 targets. Our additional experiments validate these as direct targets (see below). The most likely explanation is that MicA or RybB primarily act to repress translation of these targets, so that decreased mRNA levels are apparent only when the sRNAs are highly overexpressed. This explanation is in line with previous studies indicating that, when regulation is primarily translational, changes in mRNA levels are below the threshold for significance in microarray studies (22, 23). Alternatively, compensatory activities in the regulon may mask repression. A time course of σE overexpression for select targets indicated some temporal distinction in the dynamics of mRNA level changes (Fig. S2). For example, nmpC was fourfold repressed after 5 min of σE overexpression, which is 50% of the repression level observed after 20 min of σE overexpression. In contrast, ompF exhibited little repression at 5 min, but was repressed 64-fold after 20 min of σE overexpression.

Conserved 5′ End of RybB Regulates Many New Targets in E. coli.

Analysis of Salmonella RybB established that the highly conserved nucleotides 1–16 of RybB (called R16) is usually sufficient for target repression, and that regulation critically depends on the GCC motif at the very 5′ end of RybB (7, 11). The RNAhybrid algorithm (24) predicts that most newly discovered RybB targets are also guided by R16 (Fig. S3). Therefore, we tested the importance of R16 and the GCC motif by comparing target repression by authentic RybB with two variants, RybB-M2 and R16TOM (Fig. 3). RybB-M2 has a C2-to-G change, thereby disrupting its 5′ terminal GCC motif. R16TOM is a fusion of R16 to TOM, an unrelated control sRNA derived from 5′ truncation of E. coli OmrB sRNA (9, 25, 26). Of the 17 candidate targets predicted to use the R16 region of RybB, 16 of 17 are significantly down-regulated by R16TOM (exception ydeN; Fig. 3A). Moreover, RybB-M2 (C2-to-G change) is unable to down-regulate 13 of 14 targets predicted to use RybB C2 for interaction (exception ompW), whereas 3 of 4 targets predicted not to use mutation RybB C2 (lamB, fimA, ydeN) maintain down-regulation (Fig. 3A). These results strongly argue that R16 and the GCC motif are critical for repression (columns 8–13 of Table S1).
Fig. 3.
Region and nucleotide specific binding by RybB. Regulation of select mRNAs targeted by RybB after overexpression of RybB, R16TOM or RybB-M2 as indicated in A. Data shown are the average of three experiments with SD. The double asterisk indicates R16TOM should not be sufficient to regulate rraB, and the single asterisk indicates R16TOM should be sufficient to regulate ydeN. A schematic of interaction map and the mutations used for validation are depicted for fiu (B Left) and rluD (C Left). Experimental results from gfp translational reporters monitored by Western blot for fiu (B Right) and rluC (C Right). Bacterial growth, induction, qRT-PCR, and analysis are described in SI Materials and Methods.
To prove direct target regulation in vivo, we used a well established reporter assay where a sRNA is coexpressed with a translational fusion of the target 5′ mRNA region to green fluorescent protein (GFP; ref. 27). This assay validated E. coli nmpC, ompC, and ompF as direct RybB targets (Fig. S4). Note that our data revise a previously proposed RybB–ompC pairing (10) showing that RybB recognized ompC in the upstream 5′ UTR, as it does in Salmonella (7, 11). We also validated two new targets, fiu and rluD (Fig. 3 B and C), encoding a catecholate siderophore receptor in the OM and a conserved cytosolic 23S rRNA pseudouridine synthase, respectively. Mutant RybB-M2 failed to repress the fiu::gfp or rluD::gfp fusions. Importantly, compensatory M2′ alleles of the two target fusions, predicted to restore base pairing (G-to-C change at positions −71 (Fig. 3B) or +4 (Fig. 3C) relative to the AUG of fiu or rluD, respectively) restored target repression but were now insensitive to wild-type sRNA. These results validate the predicted short RNA duplexes of R16 with these targets. Taken together, the weight of our experimental data suggests that almost all RybB regulated mRNAs (Table S1) are direct targets.

MicA Is a Global Regulator.

Our microarray analysis predicted 15 candidate targets for E. coli MicA, significantly more than previously known in any organism (Fig. 1). Using conservation of MicA sequences as a guide (Fig. 4A), we constructed a series of MicA truncations/mutations (schematized in Fig. 4A), and examined their repression capacity to identify critical features of MicA. All 10 targets tested were down-regulated by the highly conserved nucleotides 1–24 and half were also down-regulated by nucleotides 8–24 (Fig. 4B; Table S1, columns 8–10; note that ycfS was regulated by the TOM scaffold RNA alone, and therefore could not be assessed by this procedure, Fig. S5). We expected that MicA nucleotides 1–7 would be dispensable for some targets based on validated biochemically mapped interactions (i.e., nucleotides 1–7 do not interact with ompA and lamB) and our computationally predicted pairings (e.g., no predicted interaction of MicA nucleotides 1–6 with htrG). However, the sufficiency of MicA 8–24 was surprising for other targets. Both phoP and yfeK are examples of targets that are predicted to interact with nucleotides 3–7 of MicA, and phoP interaction with nucleotides 4–7 of MicA has been validated (28).
Our mutational analysis of the GC cluster, CGCGC, spanning nucleotides 7–11, may explain this discrepancy. Given our deletion data for MicA, predicted pairings between MicA and its targets, and the fact that a GC cluster had been observed to be crucial in RybB–target interactions, we addressed the importance of MicA C7 and C11 in target recognition. Down-regulation was abrogated by mutational change when pairing was predicted (6/6 for C7-to-G; 10/10 for C11-to-G; Fig. 4C), and maintained for all 4 targets predicted not to use C7 (Fig. 4C, Table S1, columns 11–13). These mutational results provide evidence that the 5′ proximal GC cluster of MicA is an important determinant for target recognition. These results also indicate that whereas loss of pairing of C7 is tolerated (Fig. 4B), an unpaired G nucleotide in both MicA and the target is not. The G–G clash at position 7 may have a negative impact on the ability of the remainder of the MicA GC cluster to pair with target, thereby abrogating repression. In contrast, binding at adjacent positions of the GC cluster may still allow repression even though the initial base-pairing interaction was eliminated.
We experimentally validated one new target predicted to depend on both C7 and the very 5′ end of MicA (ompX; Fig. 4D). Using an ompX::gfp fusion and a compensatory M7′ allele, we demonstrated that C7 is essential for the repression of this target (Fig. 4E), which gives us a clue as to why the 5′ terminal positions of MicA are highly conserved (Fig. 4A).
Fig. 4.
Region and nucleotide specific binding by MicA. (A) The conservation of MicA sequence and schematized deletions and mutations to study MicA function. (B) Regulation of select mRNAs targeted by MicA after overexpression of full-length and truncated MicA constructs. (C) The effect of point mutations at MicA position 7 and 11; see SI Materials and Methods for details. (D) The proposed interaction map of MicA and OmpX and the mutations used for validation. (E) Fluorescence readings from gfp translational reporters. Data are expressed as the fold change relative to a strain expressing the gfp reporter only. All data shown are the average of three experiments with SD.

Convergent Target Regulation by MicA and RybB.

Our results suggest that MicA and RybB regulate some targets in common (Fig. 1). We tested tsx and ompA for joint regulation by both sRNAs (Fig. 5). For ompA, we examined the predicted interaction with RybB (Fig. 5A), as the MicA–ompA duplex is already well defined (13, 14). RybB regulation of ompA was disrupted by a M2 or M2′ mutation in sRNA or target, respectively, yet restored upon combining both mutations (RybB-M2, ompA-M2′::gfp; Fig. 5B). Significantly, a mutation in the RybB site of ompA mRNA has no effect on its regulation by MicA (MicA, ompA-M2′::gfp). In other words, ompA is subject to both parallel yet independent regulation by MicA and RybB.
Fig. 5.
Convergent target regulation by MicA and RybB Dual regulation of ompA and tsx by MicA and RybB. Schematics of proposed RNA/target interactions and the mutation changes used for validation are shown for ompA (A) and tsx (C). Results from gfp transational reporter assays using these constructs performed as described in Fig. 4E are shown in for RybB/ompA (B), MicA/tsx (D), and RybB/tsx (E).
We used the same strategy to validate the MicA binding site on tsx (Fig. 5C). Notably, a mutation in the MicA binding site has no effect on the ability of RybB to interact with tsx mRNA (Fig. 5D: RybB, tsx::gfp M11′), which argues that the predicted site for RybB is clearly distinct from that of MicA, and that tsx also is subject to dual sRNA regulation. The RybB-tsx pairing (Fig. 5C) has been validated in Salmonella using RybB-M2 and a compensatory tsx-M2′ allele (11). Surprisingly, although the nucleotides involved are conserved both between E. coli and Salmonella, we found that a M2′ allele of E. coli tsx was regulated by neither RybB-M2 nor MicA (Fig. 5E). The latter indicates that tsx M2′ may have an altered mRNA structure and that other strategies will have to be used to study dual sRNA control of this target in E. coli.

Discussion

The σE envelope stress response, central to the life of Gram-negative bacteria, had been seen as a single-tier regulatory network, with a positive regulator (σE) sufficient to monitor and repair the OM. The possibility of a more complex architecture was indicated by the fact that σE also activated two sRNAs, MicA and RybB, whose promoters are the strongest in the σE regulon (3, 4, 29). Here, we show that MicA and RybB are global regulators that together target >30 mRNAs of E. coli. This posttranscriptional noncoding RNA repression arm is of roughly comparable regulatory scope to the protein-based transcriptional activation arm, which consists of ∼100 genes. Moreover, the two arms of the response have distinct functions. The protein activation arm controls core elements of the envelope assembly machinery (30, 31), whereas the repression arm alleviates stress and interconnects regulatory networks (see below). The physiological importance of the sRNA arm is graphically illustrated by our demonstration that expression of either MicA or RybB sRNA protects the cell from the loss of viability experienced when σE activity is inadequate. Thus, the σE stress response is a paradigm for how a noncoding RNA component endows a transcriptional activation pathway with an essential repressor function (32). Interestingly, the unfolded protein response (UPR) that counteracts protein folding stress in the endoplasmic reticulum (ER) compartment of metazoan cells also involves a dual response strategy: Transcription factors up-regulate protein folding chaperones and catalysts; simultaneously, protein synthesis is down-regulated by a separate pathway to stem the flow of precursors into the ER (33).
This study clearly establishes that MicA and RybB are global regulators of the σE response, both with a large suite of targets. We confirm and expand the notion that repression of porins is a major function of these sRNAs. They regulate every major porin, including OmpX, the archetypal porin stimulus of σE activity (34, 35). However, porins are only 30% of the sRNA targets, indicating that the scope of the sRNA response extends considerably beyond porin control. The sRNAs regulate several genes previously found to be involved in increased production of outer membrane vesicles (porins, ycsF, pal, ybgF), which enhance bacterial survival during exposure to stress or toxic unfolded proteins, by providing a mechanism for release of the unwanted periplasmic component (3638). Interestingly, the σE controlled VrrA sRNA of Vibrio cholera, which is evolutionary unrelated to MicA/RybB, also regulates major two porins and controls OMV production (39, 40). Additional nonporin targets intermesh the σE response with other global regulatory systems. These include phoP (28), which monitors aspects of OM status; and possibly OmpR and σS through regulation of ecnB encoding a lipoprotein with a cell death phenotype (41). Finally, rraB and rluD are two RybB targets with a potential to globally affect the protein content of the cell. RraB binds to RNase E to alter endonucleolytic mRNA cleavage activity (42). RluD, a 23S rRNA pseudouridine synthase, is important for proper ribosome assembly function and biogenesis and affects translation termination (43, 44). Given these many targets, the exceptional strength of the micA and rybB promoters is likely necessary to continuously replenish the pool of the two sRNAs, because Hfq-dependent sRNAs are often codegraded with their mRNA targets (45).
Two network motifs warrant further study. First, three targets are both expressed by σE and down-regulated by the sRNAs. This creates the potential for an incoherent feed-forward loop, as σE can simultaneously provide positive and negative input to each target. Strikingly, two of these genes are deleterious when overexpressed, leading to cessation of growth (yfeK) or lysis (htrG; ref. 46). The incoherent feed-forward loop could prevent sRNA down-regulation of these genes implicated in cell death under severe conditions where homeostasis cannot be restored. Unconstrained σE activation could eliminate the most damaged cells, preventing them from competing for resources if growth resumed at a later time. Second, convergent target regulation by coactivated but unrelated sRNAs is unique (32). Both sRNAs recognize targets via conserved small GC-rich clusters near the 5′ end of the sRNA, but contact the mRNAs in disparate regions (e.g., tsx or ompA; Fig. 5), which validates the nonhomology of MicA and RybB. Other known cases of coinduced sRNAs use homologous sRNAs, which recognize the same region of the target mRNA, such as Qrr, OmrA and OmrB, or CyaR (5, 6, 47). It is possible that, under physiologically relevant conditions, MicA and RybB might need to partner for repression to achieve the optimal dosage. If so, this is an example of requiring concomitant activity of two coinduced regulators for target regulation. Whether σE-directed stress responses without predictable MicA/RybB homologs also use multiple unrelated sRNAs to create a repression arm remains an intriguing question.
The activation and repression arms of the σE response together ensure dynamic homeostatic control of the envelope compartment. Briefly, unassembled porins activate the DegS protease, which controls the rate of degradation of the σE antisigma, RseA (2). Because of extremely tight binding between RseA and σE, degradation of RseA is the predominant mechanism for generating free σE. Hence, the rate of RseA degradation sets σE activity (48). Rapid generation and degradation of sRNAs during the regulation process enables continuous adjustment of the flow of porin precursors to the envelope, enabling the cell to continuously adjust the activity of σE either upward or downward. The molecular dynamics of this control system are likely to be influenced by the kinetics of sRNA–target interactions and the growth-dependent occupancy of Hfq protein, as well as the distinct characteristics of the strong sRNA promoters themselves, which show differential activation in stationary phase (3).
There are intriguing similarities between the RyhB/Fur network that maintains Fe2+ homeostasis and the MicA/RybB/σE network. Fur is an active repressor in high Fe2+ conditions, but is inactive in low Fe2+ conditions. Hence, its repressed targets, including the RyhB sRNA, are expressed. The ∼18 RyhB down-regulated target mRNAs are predominantly nonessential Fe2+-containing proteins (49). Thus, target downregulation by ryhB effectively increases the Fe2+ pool so that Fur is again active as a repressor. In both networks, the sRNAs control a coherent set of mRNAs, providing a posttranscriptional repression mechanism as a counterpoint to transcriptional activation (or de-repression in the case of Fur). By influencing the signal controlling their respective transcription factors, both sRNAs intermesh the two arms of the response. The sRNA arms of both networks seem essential during time of rapid change in the signal. This concordance suggests that temporal control may be a core aspect in constructing networks subject to extensive sRNA control, as has been argued in a recent kinetic analysis of mRNA regulation by CRP protein/Spot42 RNA (22). Given the extensive information now available for both the transcriptional and posttranscriptional events, the MicA/RybB/σE network will be an ideal test bed for understanding how hierarchical control and temporal differentiation are achieved in complex sRNA control systems.

Materials and Methods

Bacterial strains, plasmids, oligonucleotides, probes for hybridization, details of plasmid construction, and primers for qRT-PCR are provided in SI Materials and Methods. Cultures were grown in Luria Bertani (LB) or M9 complete minimal media as indicated. For a full description of materials and methods, see SI Materials and Methods.

Acknowledgments

We thank M. Gao for technical assistance. This work was supported by the DFG Priority Program SPP1258 Sensory and Regulatory RNAs in Prokaryotes (DFG Grant Vo875/3-2; to J.V.), National Institutes of Health Grant RO1 GM036278-23 (to C.A.G.), and Training Grant T32 AI060537-07 (to E.B.G.).

Supporting Information

Supporting Information (PDF)
Supporting Information
sd01.xls
sd02.xls
sd03.xls
sd04.xls

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Information & Authors

Information

Published in

The cover image for PNAS Vol.108; No.31
Proceedings of the National Academy of Sciences
Vol. 108 | No. 31
August 2, 2011
PubMed: 21768388

Classifications

Submission history

Published online: July 18, 2011
Published in issue: August 2, 2011

Keywords

  1. seed pairing
  2. sigma factor

Acknowledgments

We thank M. Gao for technical assistance. This work was supported by the DFG Priority Program SPP1258 Sensory and Regulatory RNAs in Prokaryotes (DFG Grant Vo875/3-2; to J.V.), National Institutes of Health Grant RO1 GM036278-23 (to C.A.G.), and Training Grant T32 AI060537-07 (to E.B.G.).

Authors

Affiliations

Emily B. Gogol
Biomedical Sciences Graduate Program,
Program in Microbial Pathogenesis and Host Defense,
Department of Microbiology and Immunology, and
Virgil A. Rhodius
Department of Microbiology and Immunology, and
Kai Papenfort
Institute of Molecular Infection Biology, University of Würzburg, Würzburg D-97080, Germany
Institute of Molecular Infection Biology, University of Würzburg, Würzburg D-97080, Germany
Carol A. Gross1 [email protected]
Department of Microbiology and Immunology, and
Department of Cell and Tissue Biology, University of California, San Francisco, CA 94158; and

Notes

1
To whom correspondence may be addressed: E-mail: [email protected] or [email protected].
Author contributions: E.B.G., J.V., and C.A.G. designed research; E.B.G. and K.P. performed research; E.B.G. contributed new reagents/analytic tools; E.B.G., V.A.R., and K.P. analyzed data; and E.B.G., J.V., K.P., and C.A.G. wrote the paper.

Competing Interests

The authors declare no conflict of interest.

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    Small RNAs endow a transcriptional activator with essential repressor functions for single-tier control of a global stress regulon
    Proceedings of the National Academy of Sciences
    • Vol. 108
    • No. 31
    • pp. 12561-E409

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