Conserved arginines on the rim of Hfq catalyze base pair formation and exchange

The Sm-like protein Hfq is required for gene regulation by small RNAs (sRNAs) in bacteria and facilitates base pairing between sRNAs and their mRNA targets. The proximal and distal faces of the Hfq hexamer specifically bind sRNA and mRNA targets, but they do not explain how Hfq accelerates the formation and exchange of RNA base pairs. Here, we show that conserved arginines on the outer rim of the hexamer that are known to interact with sRNA bodies are required for Hfq’s chaperone activity. Mutations in the arginine patch lower the ability of Hfq to act in sRNA regulation of rpoS translation and eliminate annealing of natural sRNAs or unstructured oligonucleotides, without preventing binding to either the proximal or distal face. Stopped-flow FRET and fluorescence anisotropy show that complementary RNAs transiently form a ternary complex with Hfq, but the RNAs are not released as a double helix in the absence of rim arginines. RNAs bound to either face of Hfq quench the fluorescence of a tryptophan adjacent to the arginine patch, demonstrating that the rim can simultaneously engage two RNA strands. We propose that the arginine patch overcomes entropic and electrostatic barriers to helix nucleation and constitutes the active site for Hfq’s chaperone function.     

Unveiling the biotransformation mechanism of indole in a Cupriavidus sp. strain

Small RNAs (sRNAs), particularly those that act by limited base pairing with mRNAs, are part of most regulatory networks in bacteria. In many cases, the base‐pairing interaction is facilitated by the RNA chaperone Hfq. However, not all bacteria encode Hfq and some base‐pairing sRNAs do not require Hfq raising the possibility of other RNA chaperones. Candidates are proteins with homology to FinO, a factor that promotes base pairing between the FinP antisense sRNA and the traJ mRNA to control F plasmid transfer. Recent papers have shown that the Salmonella enterica FinO‐domain protein ProQ binds a large suite of sRNAs, including the RaiZ sRNA, which represses translation of the hupA mRNA, and the Legionella pneumophila protein RocC binds the RocR sRNA, which blocks expression of competence genes. Here we discuss what is known about FinO‐domain structures, including the recently solved Escherichia coli ProQ structure, as well as the RNA binding properties of this family of proteins and evidence they act as chaperones. We compare these properties with those of Hfq. We further summarize what is known about the physiological roles of FinO‐domain proteins and enumerate outstanding questions whose answers will establish whether they constitute a second major class of RNA chaperones.     

Identification of bacterial sRNA regulatory targets using ribosome profiling

Bacteria express large numbers of non-coding, regulatory RNAs known as ‘small RNAs’ (sRNAs). sRNAs typically regulate expression of multiple target messenger RNAs (mRNAs) through base-pairing interactions. sRNA:mRNA base-pairing often results in altered mRNA stability and/or altered translation initiation. Computational identification of sRNA targets is challenging due to the requirement for only short regions of base-pairing that can accommodate mismatches. Experimental approaches have been applied to identify sRNA targets on a genomic scale, but these focus only on those targets regulated at the level of mRNA stability. Here, we utilize ribosome profiling (Ribo-seq) to experimentally identify regulatory targets of the Escherichia coli sRNA RyhB. We not only validate a majority of known RyhB targets using the Ribo-seq approach, but also discover many novel ones. We further confirm regulation of a selection of known and novel targets using targeted reporter assays. By mutating nucleotides in the mRNA of a newly discovered target, we demonstrate direct regulation of this target by RyhB. Moreover, we show that Ribo-seq distinguishes between mRNAs regulated at the level of RNA stability and those regulated at the level of translation. Thus, Ribo-seq represents a powerful approach for genome-scale identification of sRNA targets.     

细菌sRNA基因及其靶标预测研究进展

摘要：细菌sRNA是一类长度在40～500 nt之间的非编码RNA,主要以不完全碱基配对方式与靶标mRNA5′端相互作用进而发挥其生物学功能。鉴于预测方法可以为细菌sRNA及其靶标的实验发现提供指导,因此,细菌sRNA与靶标预测研究受到了广泛重视。文章首先将sRNA预测方法分为3类,分别是基于比较基因组学的预测方法、基于转录单元的预测方法和基于机器学习的预测方法;其次,将sRNA靶标预测方法分为2类,分别是序列比较方法与基于RNA二级结构的预测方法;最后对各类方法的原理、核心思想、优点和局限性进行了分析,并探讨了进一步的发展方向。     

Predicting sRNAs and Their Targets in Bacteria

Bacterial small RNAs (sRNAs) are an emerging class of regulatory RNAs of about 40-500 nucleotides in length and, by binding to their target mRNAs or proteins, get involved in many biological processes such as sensing environmental changes and regulating gene expression. Thus, identification of bacterial sRNAs and their targets has become an important part of sRNA biology. Current strategies for discovery of sRNAs and their targets usually involve bioinformatics prediction followed by experimental validation, emphasizing a key role for bioinformatics prediction. Here, therefore, we provided an overview on prediction methods, focusing on the merits and limitations of each class of models. Finally, we will present our thinking on developing related bioinformatics models in future.     

Multiple factors dictate target selection by Hfq-binding small RNAs

Hfq-binding small RNAs (sRNAs) in bacteria modulate the stability and translational efficiency of target mRNAs through limited base-pairing interactions. While these sRNAs are known to regulate numerous mRNAs as part of stress responses, what distinguishes targets and non-targets among the mRNAs predicted to base pair with Hfq-binding sRNAs is poorly understood. Using the Hfq-binding sRNA Spot 42 of Escherichia coli as a model, we found that predictions using only the three unstructured regions of Spot 42 substantially improved the identification of previously known and novel Spot 42 targets. Furthermore, increasing the extent of base-pairing in single or multiple base-pairing regions improved the strength of regulation, but only for the unstructured regions of Spot 42. We also found that non-targets predicted to base pair with Spot 42 lacked an Hfq-binding site, folded into a secondary structure that occluded the Spot 42 targeting site, or had overlapping Hfq-binding and targeting sites. By modifying these features, we could impart Spot 42 regulation on non-target mRNAs. Our results thus provide valuable insights into the requirements for target selection by sRNAs.     

Requirement of upstream Hfq-binding (ARN)x elements in glmS and the Hfq C-terminal region for GlmS upregulation by sRNAs GlmZ and GlmY{dagger}

Hfq is an important RNA-binding protein that helps bacteria adapt to stress. Its primary function is to promote pairing between trans-acting small non-coding RNAs (sRNAs) and their target mRNAs. Identification of essential Hfq-binding motifs in up-stream regions of rpoS and fhlA led us to ask the question whether these elements are a common occurrence among other Hfq-dependent mRNAs as well. Here, we confirm the presence of a similar (ARN)(x) motif in glmS RNA, a gene controlled by two sRNAs (GlmZ and GlmY) in an Hfq-dependent manner. GlmZ represents a canonical sRNA:mRNA pairing system, whereas GlmY is non-canonical, interfacing with the RNA processing protein YhbJ. We show that glmS interacts with both Hfq-binding surfaces in the absence of sRNAs. Even though two (ARN)(x) motifs are present, using a glmS:gfp fusion system, we determined that only one specific (ARN)(x) element is essential for regulation. Furthermore, we show that residues 66-72 in the C-terminal extension of Escherichia coli Hfq are essential for activation of GlmS expression by GlmY, but not with GlmZ. This result shows that the C-terminal extension of Hfq may be required for some forms of non-canonical sRNA regulation involving ancillary components such as additional RNAs or proteins.     

Small RNA interactome of pathogenic E. coli revealed through crosslinking of RNase E

RNA sequencing studies have identified hundreds of non‐coding RNAs in bacteria, including regulatory small RNA (sRNA). However, our understanding of sRNA function has lagged behind their identification due to a lack of tools for the high‐throughput analysis of RNA–RNA interactions in bacteria. Here we demonstrate that in vivo sRNA–mRNA duplexes can be recovered using UV‐crosslinking, ligation and sequencing of hybrids (CLASH). Many sRNAs recruit the endoribonuclease, RNase E, to facilitate processing of mRNAs. We were able to recover base‐paired sRNA–mRNA duplexes in association with RNase E, allowing proximity‐dependent ligation and sequencing of cognate sRNA–mRNA pairs as chimeric reads. We verified that this approach captures bona fide sRNA–mRNA interactions. Clustering analyses identified novel sRNA seed regions and sets of potentially co‐regulated target mRNAs. We identified multiple mRNA targets for the pathotype‐specific sRNA Esr41, which was shown to regulate colicin sensitivity and iron transport in E. coli. Numerous sRNA interactions were also identified with non‐coding RNAs, including sRNAs and tRNAs, demonstrating the high complexity of the sRNA interactome.     

Small RNAs from the plant pathogenic fungus Sclerotinia sclerotiorum highlight host candidate genes associated with quantitative disease resistance

Fungal plant pathogens secrete effector proteins and metabolites to cause disease. Additionally, some species transfer small RNAs (sRNAs) into plant cells to silence host mRNAs through complementary base pairing and suppress plant immunity. The fungus Sclerotinia sclerotiorum infects over 600 plant species, but little is known about the molecular processes that govern interactions with its many hosts. In particular, evidence for the production of sRNAs by S. sclerotiorum during infection is lacking. We sequenced sRNAs produced by S. sclerotiorum in vitro and during infection of two host species, Arabidopsis thaliana and Phaseolus vulgaris. We found that S. sclerotiorum produces at least 374 distinct highly abundant sRNAs during infection, mostly originating from repeat-rich plastic genomic regions. We predicted the targets of these sRNAs in A. thaliana and found that these genes were significantly more down-regulated during infection than the rest of the genome. Predicted targets of S. sclerotiorum sRNAs in A. thaliana were enriched for functional domains associated with plant immunity and were more strongly associated with quantitative disease resistance in a genome-wide association study (GWAS) than the rest of the genome. Mutants in A. thaliana predicted sRNA target genes SERK2 and SNAK2 were more susceptible to S. sclerotiorum than wild-type, suggesting that S. sclerotiorum sRNAs may contribute to the silencing of immune components in plants. The prediction of fungal sRNA targets in plant genomes can be combined with other global approaches, such as GWAS, to assist in the identification of plant genes involved in quantitative disease resistance.     

Alternative Hfq‐sRNA interaction modes dictate alternative mRNA recognition

Many bacteria use small RNAs (sRNAs) and the RNA chaperone Hfq to regulate mRNA stability and translation. Hfq, a ring‐shaped homohexamer, has multiple faces that can bind both sRNAs and their mRNA targets. We find that Hfq has at least two distinct ways in which it interacts with sRNAs; these different binding properties have strong effects on the stability of the sRNA in vivo and the sequence requirements of regulated mRNAs. Class I sRNAs depend on proximal and rim Hfq sites for stability and turn over rapidly. Class II sRNAs are more stable and depend on the proximal and distal Hfq sites for stabilization. Using deletions and chimeras, we find that while Class I sRNAs regulate mRNA targets with previously defined ARN repeats, Class II sRNAs regulate mRNAs carrying UA‐rich rim‐binding sites. We discuss how these different binding modes may correlate with different roles in the cell, with Class I sRNAs acting as emergency responders and Class II sRNAs acting as silencers.     

Competition among Hfq-binding small RNAs in Escherichia coli

A major class of small bacterial RNAs (sRNAs) regulate translation and mRNA stability by pairing with target mRNAs, dependent upon the RNA chaperone Hfq. Hfq, related to the Lsm/Sm families of splicing proteins, binds the sRNAs and stabilizes them in vivo and stimulates pairing with mRNAs in vitro. Although Hfq is abundant, the sRNAs, when induced, are similarly abundant. Therefore, Hfq may be limiting for sRNA function. We find that, when overexpressed, a number of sRNAs competed with endogenous sRNAs for binding to Hfq. This correlated with lower accumulation of the sRNAs (presumably a reflection of the loss of Hfq binding), and lower activity of the sRNAs in regulating gene expression. Hfq was limiting for both positive and negative regulation by the sRNAs. In addition, deletion of the gene for an expressed and particularly effective competitor sRNA improved the regulation of genes by other sRNAs, suggesting that Hfq is limiting during normal growth conditions. These results support the existence of a hierarchy of sRNA competition for Hfq, modulating the function of some sRNAs.