细菌中非编码小RNA的筛选及鉴定

细菌非编码小RNA(small non-coding RNA,sRNA)是一类长度在50-200个核苷酸,不编码蛋白质的RNA.它们通过碱基配对识别靶标mRNA,在转录后水平调节基因的表达,是细菌代谢、毒力和适应环境压力的重要调节因子.近年来,随着生物信息学和RNA组学技术应用于细菌sRNA的筛选,sRNA已被证实存在于大肠埃希杆菌(Escherichia coli),铜绿假单胞菌(Pseudomonas aeruginosa)、霍乱弧菌(Vibrio cholerae)等细菌中,是细菌基因调控中新的调节因子.本文对细菌中非编码小RNA的筛选和鉴定技术作一个简要论述.     

Artificial trans-encoded small non-coding RNAs specifically silence the selected gene expression in bacteria

Recently, many small non-coding RNAs (sRNAs) with important regulatory roles have been identified in bacteria. As their eukaryotic counterparts, a major class of bacterial trans-encoded sRNAs acts by basepairing with target mRNAs, resulting in changes in translation and stability of the mRNA. RNA interference (RNAi) has become a powerful gene silencing tool in eukaryotes. However, such an effective RNA silencing tool remains to be developed for prokaryotes. In this study, we described first the use of artificial trans-encoded sRNAs (atsRNAs) for specific gene silencing in bacteria. Based on the common structural characteristics of natural sRNAs in Gram-negative bacteria, we developed the designing principle of atsRNA. Most of the atsRNAs effectively suppressed the expression of exogenous EGFP gene and endogenous uidA gene in Escherichia coli. Further studies demonstrated that the mRNA base pairing region and AU rich Hfq binding site were crucial for the activity of atsRNA. The atsRNA-mediated gene silencing was Hfq dependent. The atsRNAs led to gene silencing and RNase E dependent degradation of target mRNA. We also designed a series of atsRNAs which targeted the toxic genes in Staphyloccocus aureus, but found no significant interfering effect. We established an effective method for specific gene silencing in Gram-negative bacteria.     

细菌非编码小RNA功能及作用机制研究进展

生物体中除了编码蛋白质的mRNA外,还存在多种具有重要调控功能的非编码RNA。细菌中长度50~500 nt的非编码RNA通常定义为sRNA。sRNA在细菌的整个生命活动中发挥着极为广泛的作用,在感受环境压力、基因表达、细胞周期乃至个体发育等过程中均具有重要的调控作用。sRNA的功能学和调控机制的研究已成为当今细菌学研究的热点。本研究就细菌中的sRNA的特征,在细菌中的作用和作用机制进行文献综述。     

链球菌非编码小RNA研究进展

非编码小RNA(Small non-coding RNA,sRNA)是一种存在于原核和真核生物中的新型调控RNA,长度约为40～500个核苷酸。作为一类关键的调控因子,sRNA通过与靶mRNA或蛋白质结合来调控细胞内的基因表达。大部分细菌sRNA在大肠杆菌等革兰氏阴性菌中被发现并研究,但近十年来越来越多的sRNA在革兰氏阳性菌中被逐步发现。作为一类革兰氏阳性菌,链球菌属中sRNA目前研究主要集中在毒力调节,鲜有其他调控的报道。本文总结了链球菌中sRNA的最新进展,并介绍其主要功能和机理,以期为细菌sRNA研究提供借鉴。     

Diversity of endogenous small non-coding RNAs in Oryza sativa

Small non-coding RNAs play important roles in regulating cell functions by controlling mRNA turnover and translational repression in eukaryotic cells. Here we isolated 162 endogenous small RNA molecules from Oryza sativa, which ranged from 16 to 35 nt in length. Further analysis indicated that they represented a diversity of small RNA molecules, including 17 microRNAs (miRNAs), 30 tiny non-coding RNAs (tncRNAs) and 20 repeat-associated small interfering RNAs (rasiRNAs). Among 17 miRNAs, 13 were novel miRNA candidates and their potential targets were important regulatory genes in the rice genome. We also found that a cluster of small RNAs, including many rasiRNAs, matched to a nuclear DNA fragment that evolutionarily derived from chloroplast. These results demonstrate clearly the existence of distinct types of small RNAs in rice and further suggest that small RNAs may control gene regulation through diverse mechanisms.     

Identification of bacterial small non-coding RNAs: experimental approaches

Almost 140 bacterial small RNAs (sRNAs; sometimes referred to as non-coding RNAs) have been discovered in the past six years. The majority of these sRNAs were discovered in Escherichia coli, and a smaller subset was characterized in other bacteria, many of which were pathogenic. Many of these genes were identified as a result of systematic screens using computational prediction of sRNAs and experimental-based approaches, including microarray and shotgun cloning. A smaller number of sRNAs were discovered by direct labeling or by functional genetic screens. Many of the discovered genes, ranging in size from 50 to 500 nucleotides, are conserved and located in intergenic regions, in-between open reading frames. The expression of many of these genes is growth phase dependent or stress related. As each search employed specific parameters, this led to the identification of genes with distinct characteristics. Consequently, unique sRNAs such as those that are species-specific, sRNA genes that are transcribed under unique conditions or genes located on the antisense strand of protein-encoding genes, were probably missed.     

Identification of small non-coding RNAs from mitochondria and chloroplasts

Small non-protein-coding RNAs (ncRNAs) have been identified in a wide spectrum of organisms ranging from bacteria to humans. In eukarya, systematic searches for ncRNAs have so far been restricted to the nuclear or cytosolic compartments of cells. Whether or not small stable non-coding RNA species also exist in cell organelles, in addition to tRNAs or ribosomal RNAs, is unknown. We have thus generated cDNA libraries from size-selected mammalian mitochondrial RNA and plant chloroplast RNA and searched for small ncRNA species in these two types of DNA-containing cell organelles. In total, we have identified 18 novel candidates for organellar ncRNAs in these two cellular compartments and confirmed expression of six of them by northern blot analysis or RNase A protection assays. Most candidate ncRNA genes map to intergenic regions of the organellar genomes. As found previously in bacteria, the presumptive ancestors of present-day chloroplasts and mitochondria, we also observed examples of antisense ncRNAs that potentially could target organelle-encoded mRNAs. The structural features of the identified ncRNAs as well as their possible cellular functions are discussed. The absence from our libraries of abundant small RNA species that are not encoded by the organellar genomes suggests that the import of RNAs into cell organelles is of very limited significance or does not occur at all.     

CoRAL: predicting non-coding RNAs from small RNA-sequencing data

The surprising observation that virtually the entire human genome is transcribed means we know little about the function of many emerging classes of RNAs, except their astounding diversities. Traditional RNA function prediction methods rely on sequence or alignment information, which are limited in their abilities to classify the various collections of non-coding RNAs (ncRNAs). To address this, we developed Classification of RNAs by Analysis of Length (CoRAL), a machine learning-based approach for classification of RNA molecules. CoRAL uses biologically interpretable features including fragment length and cleavage specificity to distinguish between different ncRNA populations. We evaluated CoRAL using genome-wide small RNA sequencing data sets from four human tissue types and were able to classify six different types of RNAs with ∼80% cross-validation accuracy. Analysis by CoRAL revealed that microRNAs, small nucleolar and transposon-derived RNAs are highly discernible and consistent across all human tissue types assessed, whereas long intergenic ncRNAs, small cytoplasmic RNAs and small nuclear RNAs show less consistent patterns. The ability to reliably annotate loci across tissue types demonstrates the potential of CoRAL to characterize ncRNAs using small RNA sequencing data in less well-characterized organisms.     

The suboptimal structures find the optimal RNAs: homology search for bacterial non-coding RNAs using suboptimal RNA structures

Non-coding RNAs (ncRNAs) are regulatory molecules encoded in the intergenic or intragenic regions of the genome. In prokaryotes, biocomputational identification of homologs of known ncRNAs in other species often fails due to weakly evolutionarily conserved sequences, structures, synteny and genome localization, except in the case of evolutionarily closely related species. To eliminate results from weak conservation, we focused on RNA structure, which is the most conserved ncRNA property. Analysis of the structure of one of the few well-studied bacterial ncRNAs, 6S RNA, demonstrated that unlike optimal and consensus structures, suboptimal structures are capable of capturing RNA homology even in divergent bacterial species. A computational procedure for the identification of homologous ncRNAs using suboptimal structures was created. The suggested procedure was applied to strongly divergent bacterial species and was capable of identifying homologous ncRNAs.     

The diversity of small non-coding RNAs in the diatom Phaeodactylum tricornutum

Background

Marine diatoms constitute a major component of eukaryotic phytoplankton and stand at the crossroads of several evolutionary lineages. These microalgae possess peculiar genomic features and novel combinations of genes acquired from bacterial, animal and plant ancestors. Furthermore, they display both DNA methylation and gene silencing activities. Yet, the biogenesis and regulatory function of small RNAs (sRNAs) remain ill defined in diatoms.

Results

Here we report the first comprehensive characterization of the sRNA landscape and its correlation with genomic and epigenomic information in Phaeodactylum tricornutum. The majority of sRNAs is 25 to 30 nt-long and maps to repetitive and silenced Transposable Elements marked by DNA methylation. A subset of this population also targets DNA methylated protein-coding genes, suggesting that gene body methylation might be sRNA-driven in diatoms. Remarkably, 25-30 nt sRNAs display a well-defined and unprecedented 180 nt-long periodic distribution at several highly methylated regions that awaits characterization. While canonical miRNAs are not detectable, other 21-25 nt sRNAs of unknown origin are highly expressed. Besides, non-coding RNAs with well-described function, namely tRNAs and U2 snRNA, constitute a major source of 21-25 nt sRNAs and likely play important roles under stressful environmental conditions.

Conclusions

P. tricornutum has evolved diversified sRNA pathways, likely implicated in the regulation of largely still uncharacterized genetic and epigenetic processes. These results uncover an unexpected complexity of diatom sRNA population and previously unappreciated features, providing new insights into the diversification of sRNA-based processes in eukaryotes.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-698) contains supplementary material, which is available to authorized users.     

Experimental approaches to identify non-coding RNAs

Cellular RNAs that do not function as messenger RNAs (mRNAs), transfer RNAs (tRNAs) or ribosomal RNAs (rRNAs) comprise a diverse class of molecules that are commonly referred to as non-protein-coding RNAs (ncRNAs). These molecules have been known for quite a while, but their importance was not fully appreciated until recent genome-wide searches discovered thousands of these molecules and their genes in a variety of model organisms. Some of these screens were based on biocomputational prediction of ncRNA candidates within entire genomes of model organisms. Alternatively, direct biochemical isolation of expressed ncRNAs from cells, tissues or entire organisms has been shown to be a powerful approach to identify ncRNAs both at the level of individual molecules and at a global scale. In this review, we will survey several such wet-lab strategies, i.e. direct sequencing of ncRNAs, shotgun cloning of small-sized ncRNAs (cDNA libraries), microarray analysis and genomic SELEX to identify novel ncRNAs, and discuss the advantages and limits of these approaches.     

Identification of new small non-coding RNAs from tobacco and Arabidopsis

Small non-coding RNAs (ncRNAs) have typically been searched in fully sequenced genomes using one of two approaches-experimental or computational. We developed a mixed method, using both types of information, which has the advantage of applying bio-computing methods to actually expressed sequences. Our method allowed the identification of new small ncRNAs in Arabidopsis thaliana and in the unfinished genome of Nicotiana tabacum. We constructed a N. tabacum cDNA library from small RNAs ranging from 20 to 30 nucleotides (nt). The sequences from 73 unique clones were compared to the A. thaliana genome and to all plant sequences using a pattern-matching approach (program Patbank). Thus, we selected 15 clones from the library corresponding mostly to A. thaliana or N. tabacum non-coding sequences. By Northern blot analyses, we confirmed the presence of most RNA candidates in Arabidopsis and in Nicotiana sylvestris with a size range of 21-100 nt. To gain more insight into the possible genesis of 21-24 nt sequences, stable folding of sRNAs with their flanking regions were predicted with the software MIRFOLD dedicated to the folding of microRNAs (miRNA). Stable hairpins structures were observed for some putative miRNAs.