Effects of individual base-pairs on in vivo target search and destruction kinetics of bacterial small RNA

Base-pairing interactions mediate many intermolecular target recognition events. Even a single base-pair mismatch can cause a substantial difference in activity but how such changes influence the target search kinetics in vivo is unknown. Here, we use high-throughput sequencing and quantitative super-resolution imaging to probe the mutants of bacterial small RNA, SgrS, and their regulation of ptsG mRNA target. Mutations that disrupt binding of a chaperone protein, Hfq, and are distal to the mRNA annealing region still decrease the rate of target association, kon, and increase the dissociation rate, koff, showing that Hfq directly facilitates sRNA–mRNA annealing in vivo. Single base-pair mismatches in the annealing region reduce kon by 24–31% and increase koff by 14–25%, extending the time it takes to find and destroy the target by about a third. The effects of disrupting contiguous base-pairing are much more modest than that expected from thermodynamics, suggesting that Hfq buffers base-pair disruptions.

PresRAT: A server for identification of bacterial small-RNA sequences and their targets with probable binding region

Bacterial small-RNA (sRNA) sequences are functional RNAs, which play an important role in regulating the expression of a diverse class of genes. It is thus critical to identify such sRNA sequences and their probable mRNA targets. Here, we discuss new procedures to identify and characterize sRNA and their targets via the introduction of an integrated online platform named PresRAT (Prediction of sRNA and their Targets). PresRAT uses the primary and secondary structural attributes of sRNA sequences to predict sRNA from a given sequence or bacterial genome. PresRAT also finds probable target mRNAs of sRNA sequences from a given bacterial chromosome and further concentrates on identification of the probable sRNA-mRNA binding regions. Using PresRAT we have identified a total of 60,518 potential sRNA sequences from 54 bacterial genomes and 2447 potential targets from 13 bacterial genomes. We have also implemented a protocol to build and refine 3D models of sRNA and sRNA-mRNA duplex regions and generated 3D models of 50 known sRNAs and 81 sRNA-mRNA duplexes using this platform. Along with the server part, PresRAT also contains a database section, which enlists the predicted sRNA sequences, sRNA targets and their corresponding 3D models with structural dynamics information.

C. elegans “reads” bacterial non-coding RNAs to learn pathogenic avoidance

C. elegans is exposed to many different bacteria in its environment, and must distinguish pathogenic from nutritious bacterial food sources. Here, we show that a single exposure to purified small RNAs isolated from pathogenic Pseudomonas aeruginosa (PA14) is sufficient to induce pathogen avoidance, both in the treated animals and in four subsequent generations of progeny. The RNA interference and piRNA pathways, the germline, and the ASI neuron are required for bacterial small RNA-induced avoidance behavior and transgenerational inheritance. A single non-coding RNA, P11, is both necessary and sufficient to convey learned avoidance of PA14, and its C. elegans target, maco-1, is required for avoidance. A natural microbiome Pseudomonas isolate, GRb0427, can induce avoidance via its small RNAs, and the wild C. elegans strain JU1580 responds similarly to bacterial sRNA. Our results suggest that this ncRNA-dependent mechanism evolved to survey the worm’s microbial environment, use this information to make appropriate behavioral decisions, and pass this information on to its progeny.

Identification of miRNAs and their corresponding mRNA targets from chickpea nodules and functional characterization of candidate miRNAs by overexpression in chickpea roots

SummaryLegumes developed symbiotic associations with rhizobia to meet its nitrogen requirement. The nitrogen fixation takes place in root nodules which involves bacterial colonization, organogenesis and nitrogen fixation.One microRNA and four parallel analysis of RNA ends (PARE) libraries were sequenced to unravel the miRNA mediated regulation of symbiosis in chickpea.Sequencing of microRNA library identified a set of 91 miRNAs comprising of 84 conserved and 7 novel miRNAs. Additionally, PARE library analysis revealed 564 genes being targeted by 85 miRNAs.Phylogenetic analysis of the precursor sequences of the 91 miRNAs clearly indicated a clustering of two distinct miRNAs in the same clade representing a close ancestral precursor.Further, biogenesis of miRNAs was predicted using the miRNAs identified from different legume genomes.The miRNA reads from the nodule library were also mapped onto bacterial genomes from which bacterial small RNA were predicted.The antagonistic expression of some of the miRNA-target pairs was investigated and the negative co-related expression profiling proved the validity of the libraries and the miRNA-target pairs. Four miRNAs were selected based on the antagonistic expression profiling and were ectopically expressed in chickpea roots by hairy root transformation.The overexpression lines showed significant change in nodule numbers. The target of miR171f (NRK), miR394 (HP) and miR1509 (AK) are novel ones being reported for the first time. This analysis opens a wide arena for investigation of the novel miRNAs and target pairs, polycistronic miRNAs and the bacterial derived smRNAs predicted in this study.

Rhizobial tRNA-derived small RNAs are signal molecules regulating plant nodulation

Rhizobial infection and root nodule formation in legumes require recognition of signal molecules produced by the bacteria and their hosts. Here, we show that rhizobial transfer RNA (tRNA)-derived small RNA fragments (tRFs) are signal molecules that modulate host nodulation. Three families of rhizobial tRFs were confirmed to regulate host genes associated with nodule initiation and development through hijacking the host RNA-interference machinery that involves ARGONAUTE 1. Silencing individual tRFs with the use of short tandem target mimics or by overexpressing their targets represses root hair curling and nodule formation, whereas repressing these targets with artificial microRNAs identical to the respective tRFs or mutating these targets with CRISPR-Cas9 promotes nodulation. Our findings thus uncover a bacterial small RNA–mediated mechanism for prokaryote-eukaryote interaction and may pave the way for enhancing nodulation efficiency in legumes.