基于转录终点序列特征预测大肠杆菌sRNA

细菌sRNA是一类长度在40～500nt的调控RNA,在细菌与环境相互作用中发挥重要功能,因此,细菌sRNA识别研究具有重要意义。然而,与蛋白编码基因具有易于识别的特征不同,目前细菌sRNA识别仍是一件比较困难的事。此方法介绍了一个基于已知细菌sRNA转录终点的碱基频率矩阵来识别sRNA的预测策略,并在大肠杆菌K-12 MG1655中进行了sRNA的预测。结果表明,该模型在独立测试集中具有较高的特异性和阳性检出率,因此,这一方法将为实验发现细菌sRNA提供较好的生物信息学支持。     

细菌sRNA基因及其靶标预测研究进展

摘要：细菌sRNA是一类长度在40～500 nt之间的非编码RNA,主要以不完全碱基配对方式与靶标mRNA5′端相互作用进而发挥其生物学功能。鉴于预测方法可以为细菌sRNA及其靶标的实验发现提供指导,因此,细菌sRNA与靶标预测研究受到了广泛重视。文章首先将sRNA预测方法分为3类,分别是基于比较基因组学的预测方法、基于转录单元的预测方法和基于机器学习的预测方法;其次,将sRNA靶标预测方法分为2类,分别是序列比较方法与基于RNA二级结构的预测方法;最后对各类方法的原理、核心思想、优点和局限性进行了分析,并探讨了进一步的发展方向。     

细菌非编码小RNA研究进展

细菌非编码小RNA(small non-coding RNA, sRNA)是一类长度在50~500个核苷酸, 不编码蛋白质的RNA。迄今, 在各种细菌中共发现超过150多种sRNA。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。细菌sRNA的研究技术主要有基于生物信息学的计算机预测法和基于实验室的检测分析方法。这些方法所得到的sRNA都需要进行实验室确认, 然后再进一步通过各种实验手段研究其功能。     

细菌中的小RNA

小RNA（sRNA）或非编码RNA（ncRNA）在原核生物和真核生物中广泛分布。迄今,在各种细菌中共发现超过150种sRNA,在大肠杆菌中发现了约80种sRNA。sRNA通过与靶mRNA配对而发生作用,导致mRNA翻译和稳定性的变化;sRNA的功能涉及从结构调节到催化作用,影响生物体内各种各样的加工过程,一个单独的sRNA就能调控大量的基因并对细胞生理产生深远影响。目前,对sRNA的研究主要采用生物信息学预测结合分子生物学实验的方法。     

细菌小RNA识别研究方法进展

细菌小RNA(sRNA)是一类长度在50～500 nt的调控RNA,主要通过与靶标mRNA以不完全配对方式结合来发挥调控作用,sRNA参与细菌基因的转录、翻译、mRNA稳定、成熟和加工等多个过程,因此,sRNA的发现及功能注释对了解细菌的致病机制至关重要。该文将对研究sRNA的各种计算机和实验方法进行综述,阐述各种方法的优缺点,并讨论今后的发展方向。     

非编码小RNA对细菌毒力及耐药性的调控作用研究进展

近年来的研究发现,细菌非编码小RNA (small non-coding RNA, sRNA)对其不同生理进程起到了重要的调控作用。随着大量sRNA被发现并鉴定,细菌sRNA的功能被逐步阐明,其可在转录后水平广泛调控细菌的生理代谢、毒力及耐药性等。本文综述了sRNA对细菌毒力和耐药性调控作用的研究进展,对揭示细菌转录后水平毒力及耐药性调控机制具有一定意义。     

病原菌非编码sRNA的功能及研究新方法北大核心CSCD

细菌中的非编码小RNA(small RNA,sRNA)作为一种靶向调控分子在细胞生理代谢过程中具有重要作用。sRNA作用于特定靶标,调控基因的表达。大肠杆菌大约有100种sRNA,其中1/3sRNA需要伴侣蛋白Hfq的介导。病原细菌中sRNA分子如何调控致病基因的表达,目前研究仍处于初级阶段。本文将从生物膜形成、细菌耐药性以及对宿主的影响等方面,结合新颖的sRNA的研究方法,综述sRNA在调控代谢网络及控制病原菌致病性方面的作用。     

病原菌非编码sRNA的功能及研究新方法

细菌中的非编码小RNA（small RNA, sRNA）作为一种靶向调控分子在细胞生理代谢过程中具有重要作用。sRNA作用于特定靶标,调控基因的表达。大肠杆菌大约有100种sRNA,其中1/3 sRNA需要伴侣蛋白Hfq的介导。病原细菌中sRNA分子如何调控致病基因的表达,目前研究仍处于初级阶段。本文将从生物膜形成、细菌耐药性以及对宿主的影响等方面,结合新颖的sRNA的研究方法,综述sRNA在调控代谢网络及控制病原菌致病性方面的作用。     

大肠杆菌O157:H7 sRNA基因E40缺失突变株的构建

目的:利用Red系统构建肠出血性大肠杆菌O157:H7的sRNA基因E40缺失突变株。方法:选取本实验室预测并经过实验验证的sRNA基因,根据NCBI上相应的序列,设计2对引物分别扩增该sRNA基因的上下游分别长464和455bp的同源臂,经PCR扩增,构建到相应的载体,最后以构建好的含上下游同源臂和卡那霉素抗性基因的长约2500bp的线性片段作为打靶片段,在Red重组系统的作用下与sRNA基因E40的上下游同源区域发生同组,从而把sRNA基因从基因组上置换下来,之后利用质粒pCP20将FRT位点间的卡那霉素抗性基因消除。结果与结论:构建了出血性大肠杆菌O157:H7的sRNA基因E40的缺失突变株,为进一步研究sRNA基因在出血性大肠杆菌O157:H7生长及致病过程中所起的功能奠定了良好的基础。     

细菌小RNA的调控及在代谢工程中的应用

细菌代谢工程需要优化基因的表达来平衡代谢物通量分布和减少有毒的中间体积累,从而提高产物生物合成。细菌小RNA(small RNA,sRNAs)与靶标mRNA通过碱基互补配对结合来抑制或激活其靶标基因的表达。sRNA在细菌的生理过程中都起到了至关重要的调控作用,因此被认为是细菌代谢工程中调节靶标基因表达的有力工具。近年来,越来越多的人工合成sRNA在细菌代谢工程中得到应用,分别就细菌sRNA的靶标识别和其对靶标的调控及代谢工程中的应用做了总结概括。     

Small noncoding RNAs controlling pathogenesis

Infectious diseases are a leading cause of mortality worldwide. A major challenge in achieving their eradication is a better understanding of bacterial pathogenesis processes. The recent discovery of small noncoding RNAs (sRNAs) as modulators of gene expression in response to environmental cues has brought a new insight into bacterial regulation. sRNAs coordinate complex networks of stress adaptation and virulence gene expression. sRNAs generally ensure such a regulation by pairing to mRNAs of effector and/or regulatory genes, or by binding to proteins. An updated view on bacterial models responsible for important infections illustrates the key role of sRNAs in the control of pathogenesis.     

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 screening system for artificial small RNAs that inhibit the growth of Escherichia coli

We have developed a screening system for artificial small RNAs (sRNAs) that inhibit the growth of Escherichia coli. In this system, we used a plasmid library to express artificial sRNAs (approximately 200 bases long) containing 60 bases of random nucleotide sequence. The induced expression of the known rydB sRNA in the system reduced the amount of its possible target mRNA, rpoS, supporting the reliability of the method. To isolate clones of sRNAs that inhibited the growth of E. coli, we used two successive screening steps: (i) colony size selection on plates and (ii) monitoring E. coli growth in a 96-well plate format. As a result, 83 artificial sRNAs were identified that showed a range of inhibitory effects on bacterial growth. We also introduced nucleotide replacements into one of the highly inhibitory sRNA clones, H12, which partially abolished the inhibition of bacterial growth, suggesting that bacterial growth was inhibited in a sequence-specific manner.     

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.     

Identification of small RNAs in diverse bacterial species

Small, non-coding bacterial RNAs (sRNAs) have been shown to regulate a plethora of biological processes. Up until recently, most sRNAs had been identified and characterized in E. coli. However, in the past few years, dozens of sRNAs have been discovered in a wide variety of bacterial species. Whereas numerous sRNAs have been isolated or detected through experimental approaches, most have been identified in predictive bioinformatic searches. Recently developed computational tools have greatly facilitated the efficient prediction of sRNAs in diverse species. Although the number of known sRNAs has dramatically increased in recent years, many challenges in the identification and characterization of sRNAs lie ahead.     

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.