常规培养与缺氧条件下BCG菌体内外sRNA的表达检测

近期发现细菌的sRNA在菌体内和菌体外均具有一定的生物学功能.为研究结核分枝杆菌菌体内外sRNA的表达情况,通过分析卡介苗(Bacillus Calmette-Guerin Vaccine,BCG)菌体和外泌体RNA测序结果,采用RT-qPCR法检测常规培养与缺氧条件下BCG菌体内外sRNA相对表达量,分析菌体内外sR...     

The rpoS mRNA leader recruits Hfq to facilitate annealing with DsrA sRNA

Small noncoding RNAs (sRNAs) regulate the response of bacteria to environmental stress in conjunction with the Sm-like RNA binding protein Hfq. DsrA sRNA stimulates translation of the RpoS stress response factor in Escherichia coli by base-pairing with the 5′ leader of the rpoS mRNA and opening a stem–loop that represses translation initiation. We report that rpoS leader sequences upstream of this stem–loop greatly increase the sensitivity of rpoS mRNA to Hfq and DsrA. Native gel mobility shift assays show that Hfq increases the rate of DsrA binding to the full 576 nt rpoS leader as much as 50-fold. By contrast, base-pairing with a 138-nt RNA containing just the repressor stem–loop is accelerated only twofold. Deletion and mutagenesis experiments showed that sensitivity to Hfq requires an upstream AAYAA sequence. Leaders long enough to contain this sequence bind Hfq tightly and form stable ternary complexes with Hfq and DsrA. A model is proposed in which Hfq recruits DsrA to the rpoS mRNA by binding both RNAs, releasing the self-repressing structure in the mRNA. Once base-pairing between DsrA and rpoS mRNA is established, interactions between Hfq and the mRNA may stabilize the RNA complex by removing Hfq from the sRNA.     

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.     

The small RNA PhrS stimulates synthesis of the Pseudomonas aeruginosa quinolone signal

Quorum sensing, a cell-to-cell communication system based on small signal molecules, is employed by the human pathogen Pseudomonas aeruginosa to regulate virulence and biofilm development. Moreover, regulation by small trans-encoded RNAs has become a focal issue in studies of virulence gene expression of bacterial pathogens. In this study, we have identified the small RNA PhrS as an activator of PqsR synthesis, one of the key quorum-sensing regulators in P. aeruginosa. Genetic studies revealed a novel mode of regulation by a sRNA, whereby PhrS uses a base-pairing mechanism to activate a short upstream open reading frame to which the pqsR gene is translationally coupled. Expression of phrS requires the oxygen-responsive regulator ANR. Thus, PhrS is the first bacterial sRNA that provides a regulatory link between oxygen availability and quorum sensing, which may impact on oxygen-limited growth in P. aeruginosa biofilms.     

Natural Selection Shapes Maintenance of Orthologous sRNAs in Divergent Host-Restricted Bacterial Genomes

Historically it has been difficult to study the evolution of bacterial small RNAs (sRNAs) across distantly related species. For example, identifying homologs of sRNAs is often difficult in genomes that have undergone multiple structural rearrangements. Also, some types of regulatory sRNAs evolve at rapid rates. The high degree of genomic synteny among divergent host-restricted bacterial lineages, including intracellular symbionts, is conducive to sRNA maintenance and homolog identification. In turn, symbiont genomes can provide us with novel insights into sRNA evolution. Here, we examine the sRNA expression profile of the obligate symbiont of psyllids, Carsonella ruddii, which has one of the smallest cellular genomes described. Using RNA-seq, we identified 36 and 32 antisense sRNAs (asRNAs) expressed by Carsonella from the psyllids Bactericera cockerelli (Carsonella-BC) and Diaphorina citri (Carsonella-DC), respectively. The majority of these asRNAs were associated with genes that are involved in essential amino acid biosynthetic pathways. Eleven of the asRNAs were conserved in both Carsonella lineages and the majority were maintained by selection. Notably, five of the corresponding coding sequences are also the targets of conserved asRNAs in a distantly related insect symbiont, Buchnera. We detected differential expression of two asRNAs for genes involved in arginine and leucine biosynthesis occurring between two distinct Carsonella-BC life stages. Using asRNAs identified in Carsonella, Buchnera, and Profftella which are all endosymbionts, and Escherichia coli, we determined that regions upstream of these asRNAs encode unique conserved patterns of AT/GC richness, GC skew, and sequence motifs which may be involved in asRNA regulation.     

A transcriptome‐wide study on the microRNA‐ and the Argonaute 1‐enriched small RNA‐mediated regulatory networks involved in plant leaf senescence

Leaf senescence is an important physiological process during the plant life cycle. However, systemic studies on the impact of microRNAs (miRNAs) on the expression of senescence‐associated genes (SAGs) are lacking. Besides, whether other Argonaute 1 (AGO1)‐enriched small RNAs (sRNAs) play regulatory roles in leaf senescence remains unclear. In this study, a total of 5,123 and 1,399 AGO1‐enriched sRNAs, excluding miRNAs, were identified in Arabidopsis thaliana and rice (Oryza sativa), respectively. After retrieving SAGs from the Leaf Senescence Database, all of the AGO1‐enriched sRNAs and the miRBase‐registered miRNAs of these two plants were included for target identification. Supported by degradome signatures, 200 regulatory pairs involving 120 AGO1‐enriched sRNAs and 40 SAGs, and 266 regulatory pairs involving 64 miRNAs and 42 SAGs were discovered in Arabidopsis. Moreover, 13 genes predicted to interact with some of the above‐identified target genes at protein level were validated as regulated by 17 AGO1‐enriched sRNAs and ten miRNAs in Arabidopsis. In rice, only one SAG was targeted by three AGO1‐enriched sRNAs, and one SAG was targeted by miR395. However, five AGO1‐enriched sRNAs were conserved between Arabidopsis and rice. Target genes conserved between the two plants were identified for three of the above five sRNAs, pointing to the conserved roles of these regulatory pairs in leaf senescence or other developmental procedures. Novel targets were discovered for three of the five AGO1‐enriched sRNAs in rice, indicating species‐specific functions of these sRNA–target pairs. These results could advance our understanding of the sRNA‐involved molecular processes modulating leaf senescence.     

sTarPicker: a method for efficient prediction of bacterial sRNA targets based on a two-step model for hybridization

Background

Bacterial sRNAs are a class of small regulatory RNAs involved in regulation of expression of a variety of genes. Most sRNAs act in trans via base-pairing with target mRNAs, leading to repression or activation of translation or mRNA degradation. To date, more than 1,000 sRNAs have been identified. However, direct targets have been identified for only approximately 50 of these sRNAs. Computational predictions can provide candidates for target validation, thereby increasing the speed of sRNA target identification. Although several methods have been developed, target prediction for bacterial sRNAs remains challenging.

Results

Here, we propose a novel method for sRNA target prediction, termed sTarPicker, which was based on a two-step model for hybridization between an sRNA and an mRNA target. This method first selects stable duplexes after screening all possible duplexes between the sRNA and the potential mRNA target. Next, hybridization between the sRNA and the target is extended to span the entire binding site. Finally, quantitative predictions are produced with an ensemble classifier generated using machine-learning methods. In calculations to determine the hybridization energies of seed regions and binding regions, both thermodynamic stability and site accessibility of the sRNAs and targets were considered. Comparisons with the existing methods showed that sTarPicker performed best in both performance of target prediction and accuracy of the predicted binding sites.

Conclusions

sTarPicker can predict bacterial sRNA targets with higher efficiency and determine the exact locations of the interactions with a higher accuracy than competing programs. sTarPicker is available at http://ccb.bmi.ac.cn/starpicker/.     

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.