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1.
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。  相似文献   

2.
细菌小RNA(small RNA,sRNA)是一类长度为50~500个碱基,具有调控转录、翻译和mRNA稳定性的非编码调节性RNA。随着越来越多的sRNA被鉴定,部分细菌的sRNA功能已逐步阐明,主要参与调控细菌的基因表达、增殖、毒力及对环境的应激反应等生物学过程。本文就胞内菌(如沙门菌、李斯特菌、嗜肺军团菌等)sRNA对其自身在宿主细胞内的生长、毒力和铁水平的调控作用进行综述。  相似文献   

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细菌sRNA是一类长度在50~500 nt的调控小RNA(small regulatory RNA),主要通过与靶标mRNA或靶标蛋白质结合发挥多种生物学功能。目前,随着生物信息学与高通量测序的应用,发现了越来越多的细菌sRNA,开发了多个相关数据库。为了sRNA工作者系统了解与应用这些数据,本文拟对包含细菌sRNA的综合数据库和细菌sRNA专业数据库作一概述,并对sRNA数据库的未来发展进行展望。  相似文献   

4.
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.  相似文献   

5.
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。  相似文献   

6.
细菌sRNA是一类长度在50~500 nt的调控小RNA(small regulatory RNA),主要通过与靶标mRNA或靶标蛋白质结合发挥多种生物学功能。目前,随着生物信息学与高通量测序的应用,发现了越来越多的细菌sRNA,开发了多个相关数据库。为了sRNA工作者系统了解与应用这些数据,本文拟对包含细菌sRNA的综合数据库和细菌sRNA专业数据库作一概述,并对sRNA数据库的未来发展进行展望。  相似文献   

7.
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。  相似文献   

8.
细菌小RNA (Small RNAs,sRNAs)是一类长度大约在40?400个核酸之间,不编码蛋白质的RNA,在细菌适应环境方面起重要的调节作用。当环境中温度、营养、外膜蛋白、pH、铁等条件改变时,sRNA常常通过连接双组分信号转导系统和调节蛋白,来传递压力信号并调节应激响应,其作用方式一般是通过碱基互补配对的方式与靶mRNA结合,从而调控靶mRNA的翻译和稳定性;或直接与靶标蛋白质结合,调节靶标蛋白质的生物活性。本文总结了细菌在多种环境压力下,sRNA的调控响应机制。  相似文献   

9.
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。  相似文献   

10.
细菌非编码小RNA研究进展   总被引:3,自引:1,他引:2  
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。  相似文献   

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Identifying Hfq-binding small RNA targets in Escherichia coli   总被引:3,自引:0,他引:3  
The Hfq-binding small RNAs (sRNAs) have recently drawn much attention as regulators of translation in Escherichia coli. We attempt to identify the targets of this class of sRNAs in genome scale and gain further insight into the complexity of translational regulation induced by Hfq-binding sRNAs. Using a new alignment algorithm, most known negatively regulated targets of Hfq-binding sRNAs were identified. The results also show several interesting aspects of the regulatory function of Hfq-binding sRNAs.  相似文献   

13.
周泉  许煜泉 《生命科学》2008,20(5):779-783
原核生物中的小RNA(small RNA,sRNA)长度通常在50—250nt之间,一般在细胞内不被翻译,对基因转录后水平的调控发挥着关键作用。最初在大肠杆菌中发现,通过计算机预测和实验技术分析,查明的种类现已近140种,其作用机制包括;与目标mRNA的翻译起始位点或前导链结合分别抑制或促进翻译;或者模拟其他核酸的二级结构,去除mRNA结合蛋白对翻译的阻抑作用,促进翻译。此外,在转录水平上,SRNA还能模拟开放的启动子结构与RNA聚合酶结合阻止转录。  相似文献   

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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.  相似文献   

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Small RNAs (sRNAs) exert important functions in pseudomonads. Classical sRNAs comprise the 4.5S, 6S, 10Sa and 10Sb RNAs, which are known in enteric bacteria as part of the signal recognition particle, a regulatory component of RNA polymerase, transfer–messenger RNA (tmRNA) and the RNA component of RNase P, respectively. Their homologues in pseudomonads are presumed to have analogous functions. Other sRNAs of pseudomonads generally have little or no sequence similarity with sRNAs of enteric bacteria. Numerous sRNAs repress or activate the translation of target mRNAs by a base-pairing mechanism. Examples of this group in Pseudomonas aeruginosa are the iron-repressible PrrF1 and PrrF2 sRNAs, which repress the translation of genes encoding iron-containing proteins, and PhrS, an anaerobically inducible sRNA, which activates the expression of PqsR, a regulator of the Pseudomonas quinolone signal. Other sRNAs sequester RNA-binding proteins that act as translational repressors. Examples of this group in P. aeruginosa include RsmY and RsmZ, which are central regulatory elements in the GacS/GacA signal transduction pathway, and CrcZ, which is a key regulator in the CbrA/CbrB signal transduction pathway. These pathways largely control the extracellular activities (including virulence traits) and the selection of the energetically most favourable carbon sources, respectively, in pseudomonads.  相似文献   

19.
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.  相似文献   

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