fhlA repression by OxyS RNA: kissing complex formation at two sites results in a stable antisense-target RNA complex

A complex network of small non-coding RNAs regulate motility in Escherichia coli

Small Hfq-dependent non-coding regulatory RNAs (sRNAs) that alter mRNA stability and expression by pairing with target mRNAs have increasingly been shown to be important in influencing the behaviour of bacteria. In Escherichia coli, flhD and flhC, which encode the master regulator of flagellar synthesis, are co-transcribed from a promoter that is regulated by multiple transcription factors that respond to different environmental cues. Here, we show that the 5' untranslated region (5' UTR) of the flhDC mRNA also serves as a hub to integrate additional environmental cues into the decision to make flagella. Four sRNAs, ArcZ, OmrA, OmrB and OxyS, negatively regulated and one sRNA, McaS, positively regulated motility and flhDC expression by base-pairing with the 5' UTR of this mRNA. Another sRNA, MicA, positively regulated motility independent of regulation of flhDC. Furthermore, we demonstrate that the regulation of motility by the ArcB/A two component system is in part due to its regulation of ArcZ. flhDC is the first mRNA that has been shown to be both positively and negatively regulated by direct pairing to sRNAs. Moreover, both positive regulation by McaS and negative regulation by ArcZ require the same binding site in the flhDC mRNA.

A complex network of small non-coding RNAs regulate motility in Escherichia coli

Small Hfq-dependent non-coding regulatory RNAs (sRNAs) that alter mRNA stability and expression by pairing with target mRNAs have increasingly been shown to be important in influencing the behaviour of bacteria. In Escherichia coli, flhD and flhC, which encode the master regulator of flagellar synthesis, are co-transcribed from a promoter that is regulated by multiple transcription factors that respond to different environmental cues. Here, we show that the 5' untranslated region (5' UTR) of the flhDC mRNA also serves as a hub to integrate additional environmental cues into the decision to make flagella. Four sRNAs, ArcZ, OmrA, OmrB and OxyS, negatively regulated and one sRNA, McaS, positively regulated motility and flhDC expression by base-pairing with the 5' UTR of this mRNA. Another sRNA, MicA, positively regulated motility independent of regulation of flhDC. Furthermore, we demonstrate that the regulation of motility by the ArcB/A two component system is in part due to its regulation of ArcZ. flhDC is the first mRNA that has been shown to be both positively and negatively regulated by direct pairing to sRNAs. Moreover, both positive regulation by McaS and negative regulation by ArcZ require the same binding site in the flhDC mRNA.

Multi-target regulation by small RNAs synchronizes gene expression thresholds and may enhance ultrasensitive behavior

Cells respond to external cues by precisely coordinating multiple molecular events. Co-regulation may be established by the so-called single-input module (SIM), where a common regulator controls multiple targets. Using mathematical modeling, we compared the ability of SIM architectures to precisely coordinate protein levels despite environmental fluctuations and uncertainties in parameter values. We find that post-transcriptional co-regulation as exemplified by bacterial small RNAs (sRNAs) is particularly robust: sRNA-mediated regulation establishes highly synchronous gene expression thresholds for all mRNA targets without a need for fine-tuning of kinetic parameters. Our analyses reveal that the non-catalytic nature of sRNA action is essential for robust gene expression synchronization, and that sRNA sequestration effects underlie coupling of multiple mRNA pools. This principle also operates in the temporal regime, implying that sRNAs could robustly coordinate the kinetics of mRNA induction as well. Moreover, we observe that multi-target regulation by a small RNA can strongly enhance ultrasensitivity in mRNA expression when compared to the single-target case. Our findings may explain why bacterial small RNAs frequently coordinate all-or-none responses to cellular stress.

Accessibility and conservation: general features of bacterial small RNA-mRNA interactions?

Bacterial small RNAs (sRNAs) are a class of structural RNAs that often regulate mRNA targets via post-transcriptional base pair interactions. We determined features that discriminate functional from non-functional interactions and assessed the influence of these features on genome-wide target predictions. For this purpose, we compiled a set of 71 experimentally verified sRNA–target pairs from Escherichia coli and Salmonella enterica. Furthermore, we collected full-length 5′ untranslated regions by using genome-wide experimentally verified transcription start sites.

 

Only interaction sites in sRNAs, but not in targets, show significant sequence conservation. In addition to this observation, we found that the base pairing between sRNAs and their targets is not conserved in general across more distantly related species. A closer inspection of RybB and RyhB sRNAs and their targets revealed that the base pairing complementarity is only conserved in a small subset of the targets. In contrast to conservation, accessibility of functional interaction sites is significantly higher in both sRNAs and targets in comparison to non-functional sites. Based on the above observations, we successfully used the following constraints to improve the specificity of genome-wide target predictions: the region of interaction initiation must be located in (1) highly accessible regions in both interaction partners or (2) unstructured conserved sRNA regions derived from reliability profiles of multiple sRNA alignments.

Aligned sequences of homologous sRNAs, functional and non-functional targets, and a sup document with sup tables, figures and references are available at www.bioinf.uni-freiburg.de/Supplements/srna-interact-feat/.

RNA-binding Sm-like proteins of bacteria and archaea. similarity and difference in structure and function

RNA-binding proteins play a significant role in many processes of RNA metabolism, such as splicing and processing, regulation of DNA transcription and RNA translation, etc. Among the great number of RNA-binding proteins, so-called RNA-chaperones occupy an individual niche; they were named for their ability to assist RNA molecules to gain their accurate native spatial structure. When binding with RNAs, they possess the capability of altering (melting) their secondary structure, thus providing a possibility for formation of necessary intramolecular contacts between individual RNA sites for proper folding. These proteins also have an additional helper function in RNA-RNA and RNA-protein interactions. Members of such class of the RNA-binding protein family are Sm and Sm-like proteins (Sm-Like, LSm). The presence of these proteins in bacteria, archaea, and eukaryotes emphasizes their biological significance. These proteins are now attractive for researchers because of their implication in many processes associated with RNAs in bacterial and archaeal cells. This review is focused on a comparison of architecture of bacterial and archaeal LSm proteins and their interaction with different RNA molecules.

The magnitude and colour of noise in genetic negative feedback systems

The comparative ability of transcriptional and small RNA-mediated negative feedback to control fluctuations or ‘noise’ in gene expression remains unexplored. Both autoregulatory mechanisms usually suppress the average (mean) of the protein level and its variability across cells. The variance of the number of proteins per molecule of mean expression is also typically reduced compared with the unregulated system, but is almost never below the value of one. This relative variance often substantially exceeds a recently obtained, theoretical lower limit for biochemical feedback systems. Adding the transcriptional or small RNA-mediated control has different effects. Transcriptional autorepression robustly reduces both the relative variance and persistence (lifetime) of fluctuations. Both benefits combine to reduce noise in downstream gene expression. Autorepression via small RNA can achieve more extreme noise reduction and typically has less effect on the mean expression level. However, it is often more costly to implement and is more sensitive to rate parameters. Theoretical lower limits on the relative variance are known to decrease slowly as a measure of the cost per molecule of mean expression increases. However, the proportional increase in cost to achieve substantial noise suppression can be different away from the optimal frontier—for transcriptional autorepression, it is frequently negligible.

A conserved RpoS-dependent small RNA controls the synthesis of major porin OmpD

A remarkable feature of many small non-coding RNAs (sRNAs) of Escherichia coli and Salmonella is their accumulation in the stationary phase of bacterial growth. Several stress response regulators and sigma factors have been reported to direct the transcription of stationary phase-specific sRNAs, but a widely conserved sRNA gene that is controlled by the major stationary phase and stress sigma factor, σ(S) (RpoS), has remained elusive. We have studied in Salmonella the conserved SdsR sRNA, previously known as RyeB, one of the most abundant stationary phase-specific sRNAs in E. coli. Alignments of the sdsR promoter region and genetic analysis strongly suggest that this sRNA gene is selectively transcribed by σ(S). We show that SdsR down-regulates the synthesis of the major Salmonella porin OmpD by Hfq-dependent base pairing; SdsR thus represents the fourth sRNA to regulate this major outer membrane porin. Similar to the InvR, MicC and RybB sRNAs, SdsR recognizes the ompD mRNA in the coding sequence, suggesting that this mRNA may be primarily targeted downstream of the start codon. The SdsR-binding site in ompD was localized by 3'-RACE, an experimental approach that promises to be of use in predicting other sRNA-target interactions in bacteria.

An in silico model for identification of small RNAs in whole bacterial genomes: characterization of antisense RNAs in pathogenic Escherichia coli and Streptococcus agalactiae strains

Characterization of small non-coding ribonucleic acids (sRNA) among the large volume of data generated by high-throughput RNA-seq or tiling microarray analyses remains a challenge. Thus, there is still a need for accurate in silico prediction methods to identify sRNAs within a given bacterial species. After years of effort, dedicated software were developed based on comparative genomic analyses or mathematical/statistical models. Although these genomic analyses enabled sRNAs in intergenic regions to be efficiently identified, they all failed to predict antisense sRNA genes (asRNA), i.e. RNA genes located on the DNA strand complementary to that which encodes the protein. The statistical models enabled any genomic region to be analyzed theorically but not efficiently. We present a new model for in silico identification of sRNA and asRNA candidates within an entire bacterial genome. This model was successfully used to analyze the Gram-negative Escherichia coli and Gram-positive Streptococcus agalactiae. In both bacteria, numerous asRNAs are transcribed from the complementary strand of genes located in pathogenicity islands, strongly suggesting that these asRNAs are regulators of the virulence expression. In particular, we characterized an asRNA that acted as an enhancer-like regulator of the type 1 fimbriae production involved in the virulence of extra-intestinal pathogenic E. coli.

Structure and stability of RNA/RNA kissing complex: with application to HIV dimerization initiation signal

We develop a statistical mechanical model to predict the structure and folding stability of the RNA/RNA kissing-loop complex. One of the key ingredients of the theory is the conformational entropy for the RNA/RNA kissing complex. We employ the recently developed virtual bond-based RNA folding model (Vfold model) to evaluate the entropy parameters for the different types of kissing loops. A benchmark test against experiments suggests that the entropy calculation is reliable. As an application of the model, we apply the model to investigate the structure and folding thermodynamics for the kissing complex of the HIV-1 dimerization initiation signal. With the physics-based energetic parameters, we compute the free energy landscape for the HIV-1 dimer. From the energy landscape, we identify two minimal free energy structures, which correspond to the kissing-loop dimer and the extended-duplex dimer, respectively. The results support the two-step dimerization process for the HIV-1 replication cycle. Furthermore, based on the Vfold model and energy minimization, the theory can predict the native structure as well as the local minima in the free energy landscape. The root-mean-square deviations (RMSDs) for the predicted kissing-loop dimer and extended-duplex dimer are ~3.0 Å. The method developed here provides a new method to study the RNA/RNA kissing complex.

Isoenergetic microarrays to study the structure and interactions of DsrA and OxyS RNAs in two- and three-component complexes

Information on the secondary structure and interactions of RNA is important to understand the biological function of RNA as well as in applying RNA as a tool for therapeutic purposes. Recently, the isoenergetic microarray mapping method was developed to improve the prediction of RNA secondary structure. Herein, for the first time, isoenergetic microarrays were used to study the binding of RNA to protein or other RNAs as well as the interactions of two different RNAs and protein in a three-component complex. The RNAs used as models were the regulatory DsrA and OxyS RNAs from Escherichia coli, the fragments of their target mRNAs (fhlA and rpoS), and their complexes with Hfq protein. The collected results showed the advantages and some limitations of microarray mapping.

Pervasive post-transcriptional control of genes involved in amino acid metabolism by the Hfq-dependent GcvB small RNA

GcvB is one of the most highly conserved Hfq-associated small RNAs in Gram-negative bacteria and was previously reported to repress several ABC transporters for amino acids. To determine the full extent of GcvB-mediated regulation in Salmonella, we combined a genome-wide experimental approach with biocomputational target prediction. Comparative pulse expression of wild-type versus mutant sRNA variants revealed that GcvB governs a large post-transcriptional regulon, impacting ~1% of all Salmonella genes via its conserved G/U-rich domain R1. Complementary predictions of C/A-rich binding sites in mRNAs and gfp reporter fusion experiments increased the number of validated GcvB targets to more than 20, and doubled the number of regulated amino acid transporters. Unlike the previously described targeting via the single R1 domain, GcvB represses the glycine transporter CycA by exceptionally redundant base-pairing. This novel ability of GcvB is focused upon the one target that could feedback-regulate the glycine-responsive synthesis of GcvB. Several newly discovered mRNA targets involved in amino acid metabolism, including the global regulator Lrp, question the previous assumption that GcvB simply acts to limit unnecessary amino acid uptake. Rather, GcvB rewires primary transcriptional control circuits and seems to act as a distinct regulatory node in amino acid metabolism.

Small RNA-mediated control of the Agrobacterium tumefaciens GABA binding protein

Wounded plants activate a complex defence programme in response to Agrobacterium tumefaciens. They synthesize the non-proteinogenic amino acid γ-aminobutyric acid (GABA), which stimulates degradation of the quorum sensing signal N-(3-oxo-octanoyl) homoserine lactone. GABA is transported into A. tumefaciens via an ABC transporter dependent on the periplasmic binding protein Atu2422. We demonstrate that expression of atu2422 and two other ABC transporter genes is downregulated by the conserved small RNA (sRNA) AbcR1 (for ABC regulator). AbcR1 is encoded in tandem with another sRNA, which is similar in sequence and structure. Both sRNAs accumulate during stationary phase but only the absence of AbcR1 resulted in significant accumulation of Atu2422 and increased GABA import. AbcR1 inhibits initiation of atu2422 translation by masking its Shine-Dalgarno sequence and thereby reduces stability of the atu2422 transcript. It is the first described bacterial sRNA that controls uptake of a plant-generated signalling molecule. Given that similar sRNAs and ABC transporter genes are present in various Rhizobiaceae and in Brucella, it is likely that such sRNA-mediated control impacts a number of host-microbe interactions.

Artificial trans-encoded small non-coding RNAs specifically silence the selected gene expression in bacteria

Recently, many small non-coding RNAs (sRNAs) with important regulatory roles have been identified in bacteria. As their eukaryotic counterparts, a major class of bacterial trans-encoded sRNAs acts by basepairing with target mRNAs, resulting in changes in translation and stability of the mRNA. RNA interference (RNAi) has become a powerful gene silencing tool in eukaryotes. However, such an effective RNA silencing tool remains to be developed for prokaryotes. In this study, we described first the use of artificial trans-encoded sRNAs (atsRNAs) for specific gene silencing in bacteria. Based on the common structural characteristics of natural sRNAs in Gram-negative bacteria, we developed the designing principle of atsRNA. Most of the atsRNAs effectively suppressed the expression of exogenous EGFP gene and endogenous uidA gene in Escherichia coli. Further studies demonstrated that the mRNA base pairing region and AU rich Hfq binding site were crucial for the activity of atsRNA. The atsRNA-mediated gene silencing was Hfq dependent. The atsRNAs led to gene silencing and RNase E dependent degradation of target mRNA. We also designed a series of atsRNAs which targeted the toxic genes in Staphyloccocus aureus, but found no significant interfering effect. We established an effective method for specific gene silencing in Gram-negative bacteria.

Accessibility and evolutionary conservation mark bacterial small-rna target-binding regions

Bacterial small noncoding RNAs have attracted much interest in recent years as posttranscriptional regulators of genes involved in diverse pathways. Small RNAs (sRNAs) are 50 to 400 nucleotides long and exert their regulatory function by directly base pairing with mRNA targets to alter their stability and/or affect their translation. This base pairing is achieved through a region of about 10 to 25 nucleotides, which may be located at various positions along different sRNAs. By compiling a data set of experimentally determined target-binding regions of sRNAs and systematically analyzing their properties, we reveal that they are both more evolutionarily conserved and more accessible than random regions. We demonstrate the use of these properties for computational identification of sRNA target-binding regions with high specificity and sensitivity. Our results show that these predicted regions are likely to base pair with known targets of an sRNA, suggesting that pointing out these regions in a specific sRNA can help in searching for its targets.

Dealing with oxidative stress and iron starvation in microorganisms: an overview

Iron starvation and oxidative stress are 2 hurdles that bacteria must overcome to establish an infection. Pathogenic bacteria have developed many strategies to efficiently infect a broad range of hosts, including humans. The best characterized systems make use of regulatory proteins to sense the environment and adapt accordingly. For example, iron-sulfur clusters are critical for sensing the level and redox state of intracellular iron. The regulatory small RNA (sRNA) RyhB has recently been shown to play a central role in adaptation to iron starvation, while the sRNA OxyS coordinates cellular response to oxidative stress. These regulatory sRNAs are well conserved in many bacteria and have been shown to be essential for establishing a successful infection. An overview of the different strategies used by bacteria to cope with iron starvation and oxidative stress is presented here.

RNA-RNA interaction prediction based on multiple sequence alignments

MOTIVATION

Many computerized methods for RNA-RNA interaction structure prediction have been developed. Recently, O(N(6)) time and O(N(4)) space dynamic programming algorithms have become available that compute the partition function of RNA-RNA interaction complexes. However, few of these methods incorporate the knowledge concerning related sequences, thus relevant evolutionary information is often neglected from the structure determination. Therefore, it is of considerable practical interest to introduce a method taking into consideration both: thermodynamic stability as well as sequence/structure covariation.

RESULTS

We present the a priori folding algorithm ripalign, whose input consists of two (given) multiple sequence alignments (MSA). ripalign outputs (i) the partition function, (ii) base pairing probabilities, (iii) hybrid probabilities and (iv) a set of Boltzmann-sampled suboptimal structures consisting of canonical joint structures that are compatible to the alignments. Compared to the single sequence-pair folding algorithm rip, ripalign requires negligible additional memory resource but offers much better sensitivity and specificity, once alignments of suitable quality are given. ripalign additionally allows to incorporate structure constraints as input parameters.

AVAILABILITY

The algorithm described here is implemented in C as part of the rip package.

PETcofold: predicting conserved interactions and structures of two multiple alignments of RNA sequences

Motivation: Predicting RNA–RNA interactions is essential for determining the function of putative non-coding RNAs. Existing methods for the prediction of interactions are all based on single sequences. Since comparative methods have already been useful in RNA structure determination, we assume that conserved RNA–RNA interactions also imply conserved function. Of these, we further assume that a non-negligible amount of the existing RNA–RNA interactions have also acquired compensating base changes throughout evolution. We implement a method, PETcofold, that can take covariance information in intra-molecular and inter-molecular base pairs into account to predict interactions and secondary structures of two multiple alignments of RNA sequences.

Results:PETcofold's ability to predict RNA–RNA interactions was evaluated on a carefully curated dataset of 32 bacterial small RNAs and their targets, which was manually extracted from the literature. For evaluation of both RNA–RNA interaction and structure prediction, we were able to extract only a few high-quality examples: one vertebrate small nucleolar RNA and four bacterial small RNAs. For these we show that the prediction can be improved by our comparative approach. Furthermore, PETcofold was evaluated on controlled data with phylogenetically simulated sequences enriched for covariance patterns at the interaction sites. We observed increased performance with increased amounts of covariance.

Availability: The program PETcofold is available as source code and can be downloaded from http://rth.dk/resources/petcofold.

Contact:gorodkin@rth.dk; backofen@informatik.uni-freiburg.de

Supplementary information:Supplementary data are available at Bioinformatics online.

An upstream Hfq binding site in the fhlA mRNA leader region facilitates the OxyS-fhlA interaction

BACKGROUND

To survive, bacteria must be able to adapt to environmental stresses. Small regulatory RNAs have been implicated as intermediates in a variety of stress-response pathways allowing dynamic gene regulation. The RNA binding protein Hfq facilitates this process in many cases, helping sRNAs base pair with their target mRNAs and initiate gene regulation. Although Hfq has been identified as a critical component in many RNPs, the manner by which Hfq controls these interactions is not known.

METHODOLOGY/PRINCIPAL FINDINGS

To test the requirement of Hfq in these mRNA-sRNA complexes, the OxyS-fhlA system was used as a model. OxyS is induced in response to oxidative stress and down regulates the translation of fhlA, a gene encoding a transcriptional activator for formate metabolism. Biophysical characterization of this system previously used a minimal construct of the fhlA mRNA which inadvertently removed a critical element within the leader sequence of this mRNA that effected thermodynamics and kinetics for the interaction with Hfq.

CONCLUSIONS/SIGNIFICANCE

Herein, we report thermodynamic, kinetic and structural mapping studies during binary and ternary complex formation between Hfq, OxyS and fhlA mRNA. Hfq binds fhlA mRNA using both the proximal and distal surfaces and stimulates association kinetics between the sRNA and mRNA but remains bound to fhlA forming a ternary complex. The upstream Hfq binding element within fhlA is similar to (ARN)(x) elements recently identified in other mRNAs regulated by Hfq. This work leads to a kinetic model for the dynamics of these complexes and the regulation of gene expression by bacterial sRNAs.

Hierarchical folding of multiple sequence alignments for the prediction of structures and RNA-RNA interactions

BACKGROUND

Many regulatory non-coding RNAs (ncRNAs) function through complementary binding with mRNAs or other ncRNAs, e.g., microRNAs, snoRNAs and bacterial sRNAs. Predicting these RNA interactions is essential for functional studies of putative ncRNAs or for the design of artificial RNAs. Many ncRNAs show clear signs of undergoing compensating base changes over evolutionary time. Here, we postulate that a non-negligible part of the existing RNA-RNA interactions contain preserved but covarying patterns of interactions.

METHODS

We present a novel method that takes compensating base changes across the binding sites into account. The algorithm works in two steps on two pre-generated multiple alignments. In the first step, individual base pairs with high reliability are found using the PETfold algorithm, which includes evolutionary and thermodynamic properties. In step two (where high reliability base pairs from step one are constrained as unpaired), the principle of cofolding is combined with hierarchical folding. The final prediction of intra- and inter-molecular base pairs consists of the reliabilities computed from the constrained expected accuracy scoring, which is an extended version of that used for individual multiple alignments.

RESULTS

We derived a rather extensive algorithm. One of the advantages of our approach (in contrast to other RNA-RNA interaction prediction methods) is the application of covariance detection and prediction of pseudoknots between intra- and inter-molecular base pairs. As a proof of concept, we show an example and discuss the strengths and weaknesses of the approach.

Identification of non-coding RNAs in environmental vibrios

The discovery of non-coding RNA (ncRNA) has been mainly limited to laboratory model systems and human pathogenic bacteria. In this study, we begin to explore the ncRNA diversity in four recently sequenced environmental Vibrio species (Vibrio alginolyticus 40B, Vibrio communis 1DA3, Vibrio mimicus VM573 and Vibrio campbellii BAA-1116) by performing in silico searches using Infernal and Rfam for the identification of putative ncRNA-encoding genes. This search method resulted in the identification of 31-38 putative ncRNA genes per species and the total ncRNA catalogue spanned an assortment of regulatory mechanisms (riboswitches, cis-encoded ncRNAs, trans-encoded ncRNAs, modulators of protein activity, ribonucleoproteins, transcription termination ncRNAs and unknown). We chose to experimentally validate the identifications for V. campbellii BAA-1116 using a microarray-based expression profiling strategy. Transcript hybridization to tiled probes targeting annotated V. campbellii BAA-1116 intergenic regions revealed that 21 of the 38 predicted ncRNA genes were expressed in mid-exponential-phase cultures grown in nutrient-rich medium. The microarray findings were confirmed by testing a subset of three highly expressed (6S, tmRNA and TPP-2) and three moderately expressed (CsrB, GcvB and purine) ncRNAs via reverse transcription PCR. Our findings provide new information on the diversity of ncRNA in environmental vibrios while simultaneously promoting a more accurate annotation of genomic intergenic regions.

Hepatitis C virus genomic RNA dimerization is mediated via a kissing complex intermediate

With over 200 million people infected with hepatitis C virus (HCV) worldwide, there is a need for more effective and better-tolerated therapeutic strategies. The HCV genome is a positive-sense; single-stranded RNA encoding a large polyprotein cleaved at multiple sites to produce at least ten proteins, among them an error-prone RNA polymerase that confers a high mutation rate. Despite considerable overall sequence diversity, in the 3'-untranslated region of the HCV genomic RNA there is a 98-nucleotide (nt) sequence named X RNA, the first 55 nt of which (X55 RNA) are 100% conserved among all HCV strains. The X55 region has been suggested to be responsible for in vitro dimerization of the genomic RNA in the presence of the viral core protein, although the mechanism by which this occurs is unknown. In this study, we analyzed the X55 region and characterized the mechanism by which it mediates HCV genomic RNA dimerization. Similar to a mechanism proposed previously for the human immunodeficiency 1 virus (HIV-1) genome, we show that dimerization of the HCV genome involves formation of a kissing complex intermediate, which is converted to a more stable extended duplex conformation in the presence of the core protein. Mutations in the dimer linkage sequence loop sequence that prevent RNA dimerization in vitro significantly reduced but did not completely ablate the ability of HCV RNA to replicate or produce infectious virus in transfected cells.

RNA-mediated regulation in bacteria: from natural to artificial systems

Bacteria use various means of RNA-mediated gene regulation. Regulatory RNAs include mRNA leaders that affect expression in cis or in trans, non-coding RNAs that trap regulatory proteins or interact with one or multiple target mRNAs, and RNAs that protect the bacteria against foreign and invasive DNA. The aim of this review is to outline the basic principles of bacterial RNA-mediated regulation, with a special focus on both cis-acting regulatory regions of mRNAs and antisense RNAs (asRNAs), and to give a brief overview of selected examples of RNA-based technology that have paved the way for biotechnological applications.

Reprogramming of anaerobic metabolism by the FnrS small RNA

Small RNAs (sRNAs) that act by base pairing with trans-encoded mRNAs modulate metabolism in response to a variety of environmental stimuli. Here, we describe an Hfq-binding sRNA (FnrS) whose expression is induced upon a shift from aerobic to anaerobic conditions and which acts to downregulate the levels of a variety of mRNAs encoding metabolic enzymes. Anaerobic induction in minimal medium depends strongly on FNR but is also affected by the ArcA and CRP transcription regulators. Whole genome expression analysis showed that the levels of at least 32 mRNAs are downregulated upon FnrS overexpression, 15 of which are predicted to base pair with FnrS by TargetRNA. The sRNA is highly conserved across its entire length in numerous Enterobacteria, and mutational analysis revealed that two separate regions of FnrS base pair with different sets of target mRNAs. The majority of the target genes were previously reported to be downregulated in an FNR-dependent manner but lack recognizable FNR binding sites. We thus suggest that FnrS extends the FNR regulon and increases the efficiency of anaerobic metabolism by repressing the synthesis of enzymes that are not needed under these conditions.

Target prediction and a statistical sampling algorithm for RNA-RNA interaction

Motivation: It has been proven that the accessibility of the target sites has a critical influence on RNA–RNA binding, in general and the specificity and efficiency of miRNAs and siRNAs, in particular. Recently, O(N⁶) time and O(N⁴) space dynamic programming (DP) algorithms have become available that compute the partition function of RNA–RNA interaction complexes, thereby providing detailed insights into their thermodynamic properties.

Results: Modifications to the grammars underlying earlier approaches enables the calculation of interaction probabilities for any given interval on the target RNA. The computation of the ‘hybrid probabilities’ is complemented by a stochastic sampling algorithm that produces a Boltzmann weighted ensemble of RNA–RNA interaction structures. The sampling of k structures requires only negligible additional memory resources and runs in O(k·N³).

Availability: The algorithms described here are implemented in C as part of the rip package. The source code of rip2 can be downloaded from http://www.combinatorics.cn/cbpc/rip.html and http://www.bioinf.uni-leipzig.de/Software/rip.html.

Contact:duck@santafe.edu

Supplementary information:Supplementary data are available at Bioinformatics online.

On the approximation of optimal structures for RNA-RNA interaction

The interaction of two RNA molecules is a common mechanism for many biological processes. Small interfering RNAs represent a simple example of such an interaction. But other more elaborate instances of RNA-RNA interaction exist. Therefore, algorithms that predict the structure of the RNA complex thus formed are of great interest. Most of the proposed algorithms are based on dynamic programming. RNA-RNA interaction is generally NP-complete; therefore, these algorithms (and other polynomial time algorithms for that matter) are not expected to produce optimal structures. Our goal is to characterize this suboptimality. We demonstrate the existence of constant factor approximation algorithms that are based on dynamic programming. In particular, we describe 1/2 and 2/3 factor approximation algorithms. We define an entangler and prove that 2/3 is a theoretical upper bound on the approximation factor of algorithms that produce entangler-free solutions, e.g., the mentioned dynamic programming algorithms.

Experimental approaches for the discovery and characterization of regulatory small RNA

Following the pioneering screens for small regulatory RNAs (sRNAs) in Escherichia coli in 2001, sRNAs are now being identified in almost every branch of the eubacterial kingdom. Experimental strategies have become increasingly important for sRNA discovery, thanks to increased availability of tiling arrays and fast progress in the development of high-throughput cDNA sequencing (RNA-Seq). The new technologies also facilitate genome-wide discovery of potential target mRNAs by sRNA pulse-expression coupled to transcriptomics, and immunoprecipitation with RNA-binding proteins such as Hfq. Moreover, the staggering rate of new sRNAs demands mechanistic analysis of target regulation. We will also review the available toolbox for wet lab-based research, including in vivo and in vitro reporter systems, genetic methods and biochemical co-purification of sRNA interaction partners.

Partition function and base pairing probabilities for RNA-RNA interaction prediction

MOTIVATION

The RNA-RNA interaction problem (RIP) consists in finding the energetically optimal structure of two RNA molecules that bind to each other. The standard model allows secondary structures in both partners as well as additional base pairs between the two RNAs subject to certain restrictions that ensure that RIP is solvabale by a polynomial time dynamic programming algorithm. RNA-RNA binding, like RNA folding, is typically not dominated by the ground state structure. Instead, a large ensemble of alternative structures contributes to the interaction thermodynamics.

RESULTS

We present here an O(N(6)) time and O(N(4)) dynamics programming algorithm for computing the full partition function for RIP which is based on the combinatorial notion of 'tight structures'. Albeit equivalent to recent work by H. Chitsaz and collaborators, our approach in addition provides a full-fledged computation of the base pairing probabilities, which relies on the notion of a decomposition tree for joint structures. In practise, our implementation is efficient enough to investigate, for instance, the interactions of small bacterial RNAs and their target mRNAs.

AVAILABILITY

The program rip is implemented in C. The source code is available for download from http://www.combinatorics.cn/cbpc/rip.html and http://www.bioinf.uni-leipzig.de/Software/rip.html.

A partition function algorithm for interacting nucleic acid strands

Recent interests, such as RNA interference and antisense RNA regulation, strongly motivate the problem of predicting whether two nucleic acid strands interact.

Motivation: Regulatory non-coding RNAs (ncRNAs) such as microRNAs play an important role in gene regulation. Studies on both prokaryotic and eukaryotic cells show that such ncRNAs usually bind to their target mRNA to regulate the translation of corresponding genes. The specificity of these interactions depends on the stability of intermolecular and intramolecular base pairing. While methods like deep sequencing allow to discover an ever increasing set of ncRNAs, there are no high-throughput methods available to detect their associated targets. Hence, there is an increasing need for precise computational target prediction. In order to predict base-pairing probability of any two bases in interacting nucleic acids, it is necessary to compute the interaction partition function over the whole ensemble. The partition function is a scalar value from which various thermodynamic quantities can be derived. For example, the equilibrium concentration of each complex nucleic acid species and also the melting temperature of interacting nucleic acids can be calculated based on the partition function of the complex.

Results: We present a model for analyzing the thermodynamics of two interacting nucleic acid strands considering the most general type of interactions studied in the literature. We also present a corresponding dynamic programming algorithm that computes the partition function over (almost) all physically possible joint secondary structures formed by two interacting nucleic acids in O(n⁶) time. We verify the predictive power of our algorithm by computing (i) the melting temperature for interacting RNA pairs studied in the literature and (ii) the equilibrium concentration for several variants of the OxyS–fhlA complex. In both experiments, our algorithm shows high accuracy and outperforms competitors.

Availability: Software and web server is available at http://compbio.cs.sfu.ca/taverna/pirna/

Contact:cenk@cs.sfu.ca; backofen@informatik.uni-freiburg.de

Supplementary information:Supplementary data are avaliable at Bioinformatics online.

Coding sequence targeting by MicC RNA reveals bacterial mRNA silencing downstream of translational initiation

Bacterial small noncoding RNAs (sRNAs) generally recognize target mRNAs in the 5' region to prevent 30S ribosomes from initiating translation. It was thought that the mRNA coding sequence (CDS) was refractory to sRNA-mediated repression, because elongating 70S ribosomes have an efficient RNA helicase activity that prevents stable target pairing. We report that the Hfq-associated MicC sRNA silences Salmonella typhimurium ompD mRNA via a <or=12-bp RNA duplex within the CDS (codons 23-26) that is essential and sufficient for repression. MicC does not inhibit translational initiation at this downstream position but instead acts by accelerating RNase E-dependent ompD mRNA decay. We propose an alternative gene-silencing pathway within bacterial CDS wherein sRNAs repress targets by endonucleolytic mRNA destabilization rather than by the prototypical inhibition of translational initiation. The discovery of CDS targeting markedly expands the sequence space for sRNA target predictions in bacteria.

Protein engineering of the transcriptional activator FhlA To enhance hydrogen production in Escherichia coli

Escherichia coli produces H(2) from formate via the formate hydrogenlyase (FHL) complex during mixed acid fermentation; the FHL complex consists of formate dehydrogenase H (encoded by fdhF) for forming 2H(+), 2e(-), and CO(2) from formate and hydrogenase 3 (encoded by hycGE) for synthesizing H(2) from 2H(+) and 2e(-). FHL protein production is activated by the sigma(54) transcriptional activator FhlA, which activates transcription of fdhF and the hyc, hyp, and hydN-hypF operons. Here, through random mutagenesis using error-prone PCR over the whole gene, as well as over the fhlA region encoding the first 388 amino acids of the 692-amino-acid protein, we evolved FhlA to increase H(2) production. The amino acid replacements in FhlA133 (Q11H, L14V, Y177F, K245R, M288K, and I342F) increased hydrogen production ninefold, and the replacements in FhlA1157 (M6T, S35T, L113P, S146C, and E363K) increased hydrogen production fourfold. Saturation mutagenesis at the codons corresponding to the amino acid replacements in FhlA133 and at position E363 identified the importance of position L14 and of E363 for the increased activity; FhlA with replacements L14G and E363G increased hydrogen production (fourfold and sixfold, respectively) compared to FhlA. Whole-transcriptome and promoter reporter constructs revealed that the mechanism by which the FhlA133 changes increase hydrogen production is by increasing transcription of all of the genes activated by FhlA (the FHL complex). With FhlA133, transcription of P(fdhF) and P(hyc) is less sensitive to formate regulation, and with FhlA363 (E363G), P(hyc) transcription increases but P(hyp) transcription decreases and hydrogen production is less affected by the repressor HycA.

Homologs of the small RNA SgrS are broadly distributed in enteric bacteria but have diverged in size and sequence

Sugar phosphate stress in Escherichia coli is sensed and managed by the transcriptional regulator SgrR and the small RNA (sRNA) SgrS. SgrS is a dual function RNA that performs base pairing-dependent regulation of mRNA targets and encodes a small protein, SgrT. Homologs of SgrR were analyzed for gene synteny and inter-homolog identity to identify those that are likely to be functionally analogous. These 22 SgrR homologs were used to manually locate adjacent sRNAs functionally analogous to SgrS. SgrS homologs shared little sequence identity with E. coli SgrS, but most shared several structural features. The most conserved feature of SgrS homologs was the base pairing region while the most variable feature was the sgrT-coding sequence. Analyses of predicted interactions between SgrS:ptsG mRNA pairs in different organisms revealed interesting differences in the patterns of base pairing interactions. RNA pairs with more interrupted regions of complementarity had a higher proportion of G:C base pairs than those with longer contiguous stretches of complementarity. The identification of this set of homologous sRNAs and their targets sets the stage for future studies to further elucidate the molecular requirements for regulation by SgrS.

Role of the sRNA GcvB in regulation of cycA in Escherichia coli

In Escherichia coli, the gcvB gene encodes a small non-translated RNA that regulates several genes involved in transport of amino acids and peptides (including sstT, oppA and dppA). Microarray analysis identified cycA as an additional regulatory target of GcvB. The cycA gene encodes a permease for the transport of glycine, d-alanine, d-serine and d-cycloserine. RT-PCR confirmed that GcvB and the Hfq protein negatively regulate cycA mRNA in cells grown in Luria-Bertani broth. In addition, deletion of the gcvB gene resulted in increased sensitivity to d-cycloserine, consistent with increased expression of cycA. A cycA : : lacZ translational fusion confirmed that GcvB negatively regulates cycA expression in Luria-Bertani broth and that Hfq is required for the GcvB effect. GcvB had no effect on cycA : : lacZ expression in glucose minimal medium supplemented with glycine. However, Hfq still negatively regulated the fusion in the absence of GcvB. A set of transcriptional fusions of cycA to lacZ identified a sequence in cycA necessary for regulation by GcvB. Analysis of GcvB identified a region complementary to this region of cycA mRNA. However, mutations predicted to disrupt base-pairing between cycA mRNA and GcvB did not alter expression of cycA : : lacZ. A model for GcvB function in cell physiology is discussed.

Noncoding RNA control of the making and breaking of sugars

Noncoding RNA regulators have been implicated in almost all imaginable cellular processes. Here we review how regulatory small RNAs such as Spot42, SgrS, GlmY, and GlmZ and a cis-encoded ribozyme in glmS mRNA control sugar metabolism. Besides discussing the physiological implications, we show how the study of these molecules contributed to our understanding of the mechanisms and of general principles of RNA-based regulation. These include the post-transcriptional repression or activation of gene expression within polycistronic mRNAs; novel ribonucleoprotein complexes composed of small RNA, Hfq, and/or RNase E; and the hierarchical action of regulatory RNAs.

Small RNA binding to 5' mRNA coding region inhibits translational initiation

Small noncoding RNAs (sRNAs) have predominantly been shown to repress bacterial mRNAs by masking the Shine-Dalgarno (SD) or AUG start codon sequence, thereby preventing 30S ribosome entry and, consequently, translation initiation. However, many recently identified sRNAs lack obvious SD and AUG complementarity, indicating that sRNA-mediated translational control could also take place at other mRNA sites. We report that Salmonella RybB sRNA represses ompN mRNA translation by pairing with the 5' coding region. Results of systematic antisense interference with 30S binding to ompN and unrelated mRNAs suggest that sRNAs can act as translational repressors by sequestering sequences within the mRNA down to the fifth codon, even without SD and AUG start codon pairing. This "five codon window" for translational control in the 5' coding region of mRNA not only has implications for sRNA target predictions but might also apply to cis-regulatory systems such as RNA thermosensors and riboswitches.

Small regulatory non-coding RNAs in bacteria: physiology and mechanistic aspects

Regulatory ncRNAs (non-coding RNAs) adjust bacterial physiology in response to environmental cues. ncRNAs can base-pair to mRNAs and change their translation efficiency and/or their stability, or they can bind to proteins and modulate their activity. ncRNAs have been discovered in several species throughout the bacterial kingdom. This review illustrates the diversity of physiological processes and molecular mechanisms where ncRNAs are key regulators.

Small RNAs establish gene expression thresholds

The central role of small RNAs in regulating bacterial gene expression has been elucidated in the past years. Typically, small RNAs act via specific basepairing with target mRNAs, leading to modulation of translation initiation and mRNA stability. Quantitative studies suggest that small RNA regulation is characterized by unique features, which allow it to complement regulation at the transcriptional level. In particular, small RNAs are shown to establish a threshold for the expression of their target, providing safety mechanism against random fluctuations and transient signals. The threshold level is set by the transcription rate of the small RNA and can thus be modulated dynamically to reflect changing environmental conditions.

Exploring TAR-RNA aptamer loop-loop interaction by X-ray crystallography, UV spectroscopy and surface plasmon resonance

In HIV-1, trans-activation of transcription of the viral genome is regulated by an imperfect hairpin, the trans-activating responsive (TAR) RNA element, located at the 5′ untranslated end of all viral transcripts. TAR acts as a binding site for viral and cellular proteins. In an attempt to identify RNA ligands that would interfere with the virus life-cycle by interacting with TAR, an in vitro selection was previously carried out. RNA hairpins that formed kissing-loop dimers with TAR were selected [Ducongé F. and Toulmé JJ (1999) RNA, 5:1605–1614]. We describe here the crystal structure of TAR bound to a high-affinity RNA aptamer. The two hairpins form a kissing complex and interact through six Watson–Crick base pairs. The complex adopts an overall conformation with an inter-helix angle of 28.1°, thus contrasting with previously reported solution and modelling studies. Structural analysis reveals that inter-backbone hydrogen bonds between ribose 2′ hydroxyl and phosphate oxygens at the stem-loop junctions can be formed. Thermal denaturation and surface plasmon resonance experiments with chemically modified 2′-O-methyl incorporated into both hairpins at key positions, clearly demonstrate the involvement of this intermolecular network of hydrogen bonds in complex stability.

IntaRNA: efficient prediction of bacterial sRNA targets incorporating target site accessibility and seed regions

Motivation: During the last few years, several new small regulatory RNAs (sRNAs) have been discovered in bacteria. Most of them act as post-transcriptional regulators by base pairing to a target mRNA, causing translational repression or activation, or mRNA degradation. Numerous sRNAs have already been identified, but the number of experimentally verified targets is considerably lower. Consequently, computational target prediction is in great demand. Many existing target prediction programs neglect the accessibility of target sites and the existence of a seed, while other approaches are either specialized to certain types of RNAs or too slow for genome-wide searches.

Results: We introduce INTARNA, a new general and fast approach to the prediction of RNA–RNA interactions incorporating accessibility of target sites as well as the existence of a user-definable seed. We successfully applied INTARNA to the prediction of bacterial sRNA targets and determined the exact locations of the interactions with a higher accuracy than competing programs.

Availability:http://www.bioinf.uni-freiburg.de/Software/

Contact:IntaRNA@informatik.uni-freiburg.de

Supplementary information:Supplementary data are available at Bioinformatics online.

Real time analysis of the RNAI-RNAII-Rop complex by surface plasmon resonance: from a decaying surface to a standard kinetic analysis

RNA loop-loop complexes are motifs that regulate biological functions in both prokaryotic and eukaryotic organisms. In E. coli, RNAI, an antisense RNA encoded by the ColE1 plasmid, regulates the plasmid replication by recognizing through loop-loop interactions RNAII, the RNA primer that binds to the plasmidic DNA to initiate the replication. Rop, a plasmid-encoded homodimeric protein interacts with this transient RNAI-RNAII kissing complex. A surface plasmon resonance (SPR)-based biosensor was used to investigate this protein-nucleic acid ternary complex, at 5 degrees C, in experimental conditions such as the protein binds either to the loop-loop complex while it dissociates or to a saturated stable RNAI-RNAII surface. The results show that RNAI hairpin dissociates from the RNAII surface 110 times slower in the presence of Rop than in its absence. Rop binds to RNAI-RNAII with an on-rate of 3.6 x 10(6) M(-1) s(-1) and an off-rate of 0.11 s(-1), resulting in a binding equilibrium constant equal to 31 nM. A Scatchard-plot analysis of the interaction monitored by SPR confirms a 1:1 complex of Rop and RNAI-RNAII as observed for non-natural Rop-loop-loop complexes.

Identification of a sigma B-dependent small noncoding RNA in Listeria monocytogenes

In Listeria monocytogenes, the alternative sigma factor sigma(B) plays important roles in stress tolerance and virulence. Here, we present the identification of SbrA, a novel small noncoding RNA that is produced in a sigma(B)-dependent manner. This finding adds the sigma(B) regulon to the growing list of stress-induced regulatory circuits that include small noncoding RNAs.

Small RNAs establish delays and temporal thresholds in gene expression

Noncoding RNAs are crucial regulators of gene expression in prokaryotes and eukaryotes, but how they affect the dynamics of transcriptional networks remains poorly understood. We analyzed the temporal characteristics of the cyanobacterial iron stress response by mathematical modeling and quantitative experimental analyses and focused on the role of a recently discovered small noncoding RNA, IsrR. We found that IsrR is responsible for a pronounced delay in the accumulation of isiA mRNA encoding the late-phase stress protein, IsiA, and that it ensures a rapid decline in isiA levels once external stress triggers are removed. These kinetic properties allow the system to selectively respond to sustained (as opposed to transient) stimuli and thus establish a temporal threshold, which prevents energetically costly IsiA accumulation under short-term stress conditions. Biological information is frequently encoded in the quantitative aspects of intracellular signals (e.g., amplitude and duration). Our simulations reveal that competitive inhibition and regulated degradation allow intracellular regulatory networks to efficiently discriminate between transient and sustained inputs.

TargetRNA: a tool for predicting targets of small RNA action in bacteria

Many small RNA (sRNA) genes in bacteria act as posttranscriptional regulators of target messenger RNAs. Here, we present TargetRNA, a web tool for predicting mRNA targets of sRNA action in bacteria. TargetRNA takes as input a genomic sequence that may correspond to an sRNA gene. TargetRNA then uses a dynamic programming algorithm to search each annotated message in a specified genome for mRNAs that evince basepair-binding potential to the input sRNA sequence. Based on the calculated basepair-binding potential of each message with the given sRNA regulator, TargetRNA outputs a ranked list of candidate mRNA targets along with the predicted basepairing interaction of each target to the sRNA. The predictive performance of TargetRNA has been validated experimentally in several bacterial organisms. TargetRNA is freely available at http://snowwhite.wellesley.edu/targetRNA.

RNA switches regulate initiation of translation in bacteria

A large variety of RNA-based mechanisms have been uncovered in all living organisms to regulate gene expression in response to internal and external changes, and to rapidly adapt cell growth in response to these signals. In bacteria, structural elements in the 5′ leader regions of mRNAs have direct effects on translation initiation of the downstream coding sequences. The docking and unfolding of these mRNAs on the 30S subunit are critical steps in the initiation process directly modulating and timing translation. Structural elements can also undergo conformational changes in response to environmental cues (i.e., temperature sensors) or upon binding of a variety oftrans-acting factors, such as metabolites, non-coding RNAs or regulatory proteins. These RNA switches can temporally regulate translation, leading either to repression or to activation of protein synthesis.