Synthetase of the methyl donor S-adenosylmethionine from nitrogen-fixing α-rhizobia can bind functionally diverse RNA species

Function of bacterial small non-coding RNAs (sRNAs) and overall RNA metabolism is largely shaped by a vast diversity of RNA-protein interactions. However, in non-model bacteria with defined non-coding transcriptomes the sRNA interactome remains almost unexplored. We used affinity chromatography to capture proteins associated in vivo with MS2-tagged trans-sRNAs that regulate nutrient uptake (AbcR2 and NfeR1) and cell cycle (EcpR1) mRNAs by antisense-based translational inhibition in the nitrogen-fixing α-rhizobia Sinorhizobium meliloti. The three proteomes were rather distinct, with that of EcpR1 particularly enriched in cell cycle-related enzymes, whilst sharing several transcription/translation-related proteins recurrently identified associated with sRNAs. Strikingly, MetK, the synthetase of the major methyl donor S-adenosylmethionine, was reliably recovered as a binding partner of the three sRNAs, which reciprocally co-immunoprecipitated with a FLAG-tagged MetK variant. Induced (over)expression of the trans-sRNAs and MetK depletion did not influence canonical riboregulatory traits, `for example, protein titration or sRNA stability, respectively. An in vitro filter assay confirmed binding of AbcR2, NfeR1 and EcpR1 to MetK and further revealed interaction of the protein with other non-coding and coding transcripts but not with the 5S rRNA. These findings uncover a broad specificity for RNA binding as an unprecedented feature of this housekeeping prokaryotic enzyme.

Comprehensive annotation and characterization of planarian tRNA and tRNA-derived fragments (tRFs)

tRNA-derived fragments (tRFs) have recently gained a lot of scientific interest due to their diverse regulatory roles in several cellular processes. However, their function in dynamic biological processes such as development and regeneration remains unexplored. Here, we show that tRFs are dynamically expressed during planarian regeneration, suggesting a possible role for these small RNAs in the regulation of regeneration. In order to characterize planarian tRFs, we first annotated 457 tRNAs in S. mediterranea combining two tRNA prediction algorithms. Annotation of tRNAs facilitated the identification of three main species of tRFs in planarians-the shorter tRF-5s and itRFs, and the abundantly expressed 5'-tsRNAs. Spatial profiling of tRFs in sequential transverse sections of planarians revealed diverse expression patterns of these small RNAs, including those that are enriched in the head and pharyngeal regions. Expression analysis of these tRF species revealed dynamic expression of these small RNAs over the course of regeneration suggesting an important role in planarian anterior and posterior regeneration. Finally, we show that 5'-tsRNA in planaria interact with all three SMEDWI proteins and an involvement of AGO1 in the processing of itRFs. In summary, our findings implicate a novel role for tRFs in planarian regeneration, highlighting their importance in regulating complex systemic processes. Our study adds to the catalog of posttranscriptional regulatory systems in planaria, providing valuable insights on the biogenesis and the function of tRFs in neoblasts and planarian regeneration.

Compensatory sequence variation between trans-species small RNAs and their target sites

Trans-species small regulatory RNAs (sRNAs) are delivered to host plants from diverse pathogens and parasites and can target host mRNAs. How trans-species sRNAs can be effective on diverse hosts has been unclear. Multiple species of the parasitic plant Cuscuta produce trans-species sRNAs that collectively target many host mRNAs. Confirmed target sites are nearly always in highly conserved, protein-coding regions of host mRNAs. Cuscuta trans-species sRNAs can be grouped into superfamilies that have variation in a three-nucleotide period. These variants compensate for synonymous-site variation in host mRNAs. By targeting host mRNAs at highly conserved protein-coding sites, and simultaneously expressing multiple variants to cover synonymous-site variation, Cuscuta trans-species sRNAs may be able to successfully target multiple homologous mRNAs from diverse hosts.

The discovery potential of RNA processing profiles

Small non-coding RNAs (sncRNAs) are highly abundant molecules that regulate essential cellular processes and are classified according to sequence and structure. Here we argue that read profiles from size-selected RNA sequencing capture the post-transcriptional processing specific to each RNA family, thereby providing functional information independently of sequence and structure. We developed SeRPeNT, a new computational method that exploits reproducibility across replicates and uses dynamic time-warping and density-based clustering algorithms to identify, characterize and compare sncRNAs by harnessing the power of read profiles. We applied SeRPeNT to: (i) generate an extended human annotation with 671 new sncRNAs from known classes and 131 from new potential classes, (ii) show pervasive differential processing of sncRNAs between cell compartments and (iii) predict new molecules with miRNA-like behaviour from snoRNA, tRNA and long non-coding RNA precursors, potentially dependent on the miRNA biogenesis pathway. Furthermore, we validated experimentally four predicted novel non-coding RNAs: a miRNA, a snoRNA-derived miRNA, a processed tRNA and a new uncharacterized sncRNA. SeRPeNT facilitates fast and accurate discovery and characterization of sncRNAs at an unprecedented scale. SeRPeNT code is available under the MIT license at https://github.com/comprna/SeRPeNT.

Stranded Whole Transcriptome RNA-Seq for All RNA Types

Stranded whole transcriptome RNA-Seq described in this unit captures quantitative expression data for all types of RNA including, but not limited to, miRNA (microRNA), piRNA (Piwi-interacting RNA), snoRNA (small nucleolar RNA), lincRNA (large non-coding intergenic RNA), SRP RNA (signal recognition particle RNA), tRNA (transfer RNA), mtRNA (mitochondrial RNA), and mRNA (messenger RNA). The size and nature of these types of RNA are irrelevant to the approach described here. Barcoded libraries for multiplexing on the Illumina platform are generated with this approach but it can be applied to other platforms with a few modifications.

Regulatory non-coding RNAs: revolutionizing the RNA world

The majority of the genomic DNA sequence in mammalian and other higher organisms can be transcribed into abundant functional RNA transcripts, especially regulatory non-coding RNAs (ncRNAs) that are expressed in a developmentally and species-specific regulated manner. Here, we review various regulatory non-coding RNAs, including regulatory small non-coding RNAs (sncRNAs) and long non-coding RNAs (lncRNAs), and summarize two and eight kinds of distinct modes of action for sncRNAs and lncRNAs respectively, by which functional ncRNAs mediate the regulation of intracellular events.

Determination of sRNA expressions by RNA-seq in Yersinia pestis grown in vitro and during infection

Background

Small non-coding RNAs (sRNAs) facilitate host-microbe interactions. They have a central function in the post-transcriptional regulation during pathogenic lifestyles. Hfq, an RNA-binding protein that many sRNAs act in conjunction with, is required for Y. pestis pathogenesis. However, information on how Yersinia pestis modulates the expression of sRNAs during infection is largely unknown.

Methodology and Principal Findings

We used RNA-seq technology to identify the sRNA candidates expressed from Y. pestis grown invitro and in the infected lungs of mice. A total of 104 sRNAs were found, including 26 previously annotated sRNAs, by searching against the Rfam database with 78 novel sRNA candidates. Approximately 89% (93/104) of these sRNAs from Y. pestis are shared with its ancestor Y. pseudotuberculosis. Ninety-seven percent of these sRNAs (101/104) are shared among more than 80 sequenced genomes of 135 Y. pestis strains. These 78 novel sRNAs include 62 intergenic and 16 antisense sRNAs. Fourteen sRNAs were selected for verification by independent Northern blot analysis. Results showed that nine selected sRNA transcripts were Hfq-dependent. Interestingly, three novel sRNAs were identified as new members of the transcription factor CRP regulon. Semi-quantitative analysis revealed that Y. pestis from the infected lungs induced the expressions of six sRNAs including RyhB1, RyhB2, CyaR/RyeE, 6S RNA, RybB and sR039 and repressed the expressions of four sRNAs, including CsrB, CsrC, 4.5S RNA and sR027.

Conclusions and Significance

This study is the first attempt to subject RNA from Y. pestis-infected samples to direct high-throughput sequencing. Many novel sRNAs were identified and the expression patterns of relevant sRNAs in Y. pestis during invitro growth and invivo infection were revealed. The annotated sRNAs accounted for the most abundant sRNAs either expressed in bacteria grown invitro or differentially expressed in the infected lungs. These findings suggested these sRNAs may have important functions in Y. pestis physiology or pathogenesis.

RNA-Seq analyses reveal the order of tRNA processing events and the maturation of C/D box and CRISPR RNAs in the hyperthermophile Methanopyrus kandleri

The methanogenic archaeon Methanopyrus kandleri grows near the upper temperature limit for life. Genome analyses revealed strategies to adapt to these harsh conditions and elucidated a unique transfer RNA (tRNA) C-to-U editing mechanism at base 8 for 30 different tRNA species. Here, RNA-Seq deep sequencing methodology was combined with computational analyses to characterize the small RNome of this hyperthermophilic organism and to obtain insights into the RNA metabolism at extreme temperatures. A large number of 132 small RNAs were identified that guide RNA modifications, which are expected to stabilize structured RNA molecules. The C/D box guide RNAs were shown to exist as circular RNA molecules. In addition, clustered regularly interspaced short palindromic repeats RNA processing and potential regulatory RNAs were identified. Finally, the identification of tRNA precursors before and after the unique C8-to-U8 editing activity enabled the determination of the order of tRNA processing events with termini truncation preceding intron removal. This order of tRNA maturation follows the compartmentalized tRNA processing order found in Eukaryotes and suggests its conservation during evolution.

Classification and comparison of small RNAs from plants

Regulatory small RNAs, which range in size from 20 to 24 nucleotides, are ubiquitous components of endogenous plant transcriptomes, as well as common responses to exogenous viral infections and introduced double-stranded RNA (dsRNA). Endogenous small RNAs derive from the processing of helical RNA precursors and can be categorized into several groups based on differences in biogenesis and function. A major distinction can be observed between small RNAs derived from single-stranded precursors with a hairpin structure [referred to here as hairpin RNAs (hpRNAs)] and those derived from dsRNA precursors [small interfering RNAs (siRNAs)]. hpRNAs in plants can be divided into two secondary groups: microRNAs and those that are not microRNAs. The currently known siRNAs fall mostly into one of three secondary groups: heterochromatic siRNAs, secondary siRNAs, and natural antisense transcript siRNAs. Tertiary subdivisions can be identified within many of the secondary classifications as well. Comparisons between the different classes of plant small RNAs help to illuminate key goals for future research.

Identification and classification of small RNAs in transcriptome sequence data

Current methods for high throughput sequencing (HTS) for the first time offer the opportunity to investigate the entire transcriptome in an essentially unbiased way. In many species, small non-coding RNAs with specific secondary structures constitute a significant part of the transcriptome. Some of these RNA classes, in particular microRNAs and snoRNAs, undergo maturation processes that lead to the production of shorter RNAs. After mapping the sequences to the reference genome specific patterns of short reads can be observed. These read patterns seem to reflect the processing and thus are specific for the RNA transcripts of which they are derived from. We explore here the potential of short read sequence data in the classification and identification of non-coding RNAs.