Translational control and target recognition by Escherichia coli small RNAs in vivo

Small non-coding RNAs (sRNAs) are an emerging class of regulators of bacterial gene expression. Most of the regulatory Escherichia coli sRNAs known to date modulate translation of trans-encoded target mRNAs. We studied the specificity of sRNA target interactions using gene fusions to green fluorescent protein (GFP) as a novel reporter of translational control by bacterial sRNAs in vivo. Target sequences were selected from both monocistronic and polycistronic mRNAs. Upon expression of the cognate sRNA (DsrA, GcvB, MicA, MicC, MicF, RprA, RyhB, SgrS and Spot42), we observed highly specific translation repression/activation of target fusions under various growth conditions. Target regulation was also tested in mutants that lacked Hfq or RNase III, or which expressed a truncated RNase E (rne701). We found that translational regulation by these sRNAs was largely independent of full-length RNase E, e.g. despite the fact that ompA fusion mRNA decay could no longer be promoted by MicA. This is the first study in which multiple well-defined E.coli sRNA target pairs have been studied in a uniform manner in vivo. We expect our GFP fusion approach to be applicable to sRNA targets of other bacteria, and also demonstrate that Vibrio RyhB sRNA represses a Vibrio sodB fusion when co-expressed in E.coli.     

Artificial small RNA-mediated growth inhibition in Escherichia coli and Salmonella enterica serovar Typhimurium

We developed a synthetic RNA approach to identify growth inhibition sequences by cloning random 24-nucleotide (nt) sequences into an arabinose-inducible expression vector. This vector expressed a small RNA (sRNA) of ∼140 nt containing a 24 nt random sequence insert. After transforming Escherichia coli with the vector, 10 out of 954 transformants showed strong growth defect phenotypes and two clones caused cell lysis. We then examined growth inhibition phenotypes in the Salmonella Typhimurium LT2 strain using the twelve sRNAs that exerted an inhibitory effect on E. coli growth. Three of these clones showed strong growth inhibition phenotypes in S. Typhimurium LT2. The most effective sRNA contained the same insert (N1) in both bacteria. The 24 nt random sequence insert of N1 was abundant in guanine residues (ten out of 24 nt), and other random sequences causing growth defects were also highly enriched for guanine (G) nucleotides. We, therefore, generated clones that express sRNAs containing a stretch of 16 to 24 continuous guanine sequences (poly-G₁₆, -G₁₈, -G₂₀, -G₂₂, and -G₂₄). All of these clones induced growth inhibition in both liquid and agar plate media and the poly-G₂₀ clone showed the strongest effect in E. coli. These results demonstrate that our sRNA expression system can be used to identify nucleotide sequences that are potential candidates for oligonucleotide antimicrobial drugs.     

Dynamics of Salmonella small RNA expression in non-growing bacteria located inside eukaryotic cells

Small non-coding regulatory RNAs (sRNAs) have been studied in many bacterial pathogens during infection. However, few studies have focused on how intracellular pathogens modulate sRNA expression inside eukaryotic cells. Here, we monitored expression of all known sRNAs of Salmonella enterica serovar Typhimurium (S. Typhimurium) in bacteria located inside fibroblasts, a host cell type in which this pathogen restrains growth. sRNA sequences known in S. Typhimurium and Escherichia coli were searched in the genome of S. Typhimurium virulent strain SL1344, the subject of this study. Expression of 84 distinct sRNAs was compared in extra- and intracellular bacteria. Non-proliferating intracellular bacteria upregulated six sRNAs, including IsrA, IsrG, IstR-2, RyhB-1, RyhB-2 and RseX while repressed the expression of the sRNAs DsrA, GlmZ, IsrH-1, IsrI, SraL, SroC, SsrS(6S) and RydC. Interestingly, IsrH-1 was previously reported as an sRNA induced by S. Typhimurium inside macrophages. Kinetic analyses unraveled changing expression patterns for some sRNAs along the infection. InvR and T44 expression dropped after an initial induction phase while IstR-2 was induced exclusively at late infection times (> 6 h). Studies focused on the Salmonella-specific sRNA RyhB-2 revealed that intracellular bacteria use this sRNA to regulate negatively YeaQ, a cis-encoded protein of unknown function. RyhB-2, together with RyhB-1, contributes to attenuate intracellular bacterial growth. To our knowledge, these data represent the first comprehensive study of S. Typhimurium sRNA expression in intracellular bacteria and provide the first insights into sRNAs that may direct pathogen adaptation to a non-proliferative state inside the host cell.     

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.     

A Peroxide-Responding sRNA Evolved from a Peroxidase mRNA

Small RNAs (sRNAs) are important gene regulators in bacteria, but it is unclear how new sRNAs originate and become part of regulatory networks that coordinate bacterial response to environmental stimuli. Using a covariance modeling-based approach, we analyzed the presence of hundreds of sRNAs in more than a thousand genomes across Enterobacterales, a bacterial order with a confluence of factors that allows robust genome-scale sRNA analyses: several well-studied organisms with fairly conserved genome structures, an established phylogeny, and substantial nucleotide diversity within a narrow evolutionary space. We discovered that a majority of sRNAs arose recently, and uncovered protein-coding genes as a potential source from which new sRNAs arise. A detailed investigation of the emergence of OxyS, a peroxide-responding sRNA, revealed that it evolved from a fragment of a peroxidase messenger RNA. Importantly, although it replaced the ancestral peroxidase, OxyS continues to be part of the ancestral peroxide-response regulon, indicating that an sRNA that arises from a protein-coding gene would inherently be part of the parental protein’s regulatory network. This new insight provides a fresh framework for understanding sRNA origin and regulatory integration in bacteria.     

sRNA‐FISH: versatile fluorescent in situ detection of small RNAs in plants

Localization of mRNA and small RNAs (sRNAs) is important for understanding their function. Fluorescent in situ hybridization (FISH) has been used extensively in animal systems to study the localization and expression of sRNAs. However, current methods for fluorescent in situ detection of sRNA in plant tissues are less developed. Here we report a protocol (sRNA‐FISH) for efficient fluorescent detection of sRNAs in plants. This protocol is suitable for application in diverse plant species and tissue types. The use of locked nucleic acid probes and antibodies conjugated with different fluorophores allows the detection of two sRNAs in the same sample. Using this method, we have successfully detected the co‐localization of miR2275 and a 24‐nucleotide phased small interfering RNA in maize anther tapetal and archesporial cells. We describe how to overcome the common problem of the wide range of autofluorescence in embedded plant tissue using linear spectral unmixing on a laser scanning confocal microscope. For highly autofluorescent samples, we show that multi‐photon fluorescence excitation microscopy can be used to separate the target sRNA‐FISH signal from background autofluorescence. In contrast to colorimetric in situ hybridization, sRNA‐FISH signals can be imaged using super‐resolution microscopy to examine the subcellular localization of sRNAs. We detected maize miR2275 by super‐resolution structured illumination microscopy and direct stochastic optical reconstruction microscopy. In this study, we describe how we overcame the challenges of adapting FISH for imaging in plant tissue and provide a step‐by‐step sRNA‐FISH protocol for studying sRNAs at the cellular and even subcellular level.     

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.