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旧戏新角:一项基于计算机模拟的系统水平研究,用于预测细菌基因组中的III型分泌系统和效应蛋白,揭示了III型分泌系统介导的发病机制中的共同主题。

New players in the same old game: a system level in silico study to predict type III secretion system and effector proteins in bacterial genomes reveals common themes in T3SS mediated pathogenesis.

作者信息

Sadarangani Vineet, Datta Sunando, Arunachalam Manonmani

机构信息

National Institute of Immunology, Aruna Asaf Ali Marg, New Delhi 110067, India.

出版信息

BMC Res Notes. 2013 Jul 26;6:297. doi: 10.1186/1756-0500-6-297.

Abstract

BACKGROUND

Type III secretion system (T3SS) plays an important role in virulence or symbiosis of many pathogenic or symbiotic bacteria [CHM 2:291-294, 2007; Physiology (Bethesda) 20:326-339, 2005]. T3SS acts like a tunnel between a bacterium and its host through which the bacterium injects 'effector' proteins into the latter [Nature 444:567-573, 2006; COSB 18:258-266, 2008]. The effectors spatially and temporally modify the host signalling pathways [FEMS Microbiol Rev 35:1100-1125, 2011; Cell Host Microbe5:571-579, 2009]. In spite its crucial role in host-pathogen interaction, the study of T3SS and the associated effectors has been limited to a few bacteria [Cell Microbiol 13:1858-1869, 2011; Nat Rev Microbiol 6:11-16, 2008; Mol Microbiol 80:1420-1438, 2011]. Before one set out to perform systematic experimental studies on an unknown set of bacteria it would be beneficial to identify the potential candidates by developing an in silico screening algorithm. A system level study would also be advantageous over traditional laboratory methods to extract an overriding theme for host-pathogen interaction, if any, from the vast resources of data generated by sequencing multiple bacterial genomes.

RESULTS

We have developed an in silico protocol in which the most conserved set of T3SS proteins was used as the query against the entire bacterial database with increasingly stringent search parameters. It enabled us to identify several uncharacterized T3SS positive bacteria. We adopted a similar strategy to predict the presence of the already known effectors in the newly identified T3SS positive bacteria. The huge resources of biochemical data [FEMS Microbiol Rev 35:1100-1125, 2011; Cell Host Microbe 5:571-579, 2009; BMC Bioinformatics 7(11):S4, 2010] on the T3SS effectors enabled us to search for the common theme in T3SS mediated pathogenesis. We identified few cellular signalling networks in the host, which are manipulated by most of the T3SS containing pathogens. We went on to look for correlation, if any, between the biological quirks of a particular class of bacteria with the effectors they harbour. We could pin point few effectors, which were enriched in certain classes of bacteria.

CONCLUSION

The current study would open up new avenues to explore many uncharacterized T3SS positive bacteria. The experimental validation of the predictions from this study will unravel a generalized mechanism for T3SS positive bacterial infection into host cell.

摘要

背景

III型分泌系统(T3SS)在许多致病或共生细菌的毒力或共生过程中发挥着重要作用[《细胞与分子医学杂志》2:291 - 294,2007年;《生理学(贝塞斯达)》20:326 - 339,2005年]。T3SS就像细菌与其宿主之间的一条通道,细菌通过它将“效应蛋白”注入宿主[《自然》444:567 - 573,2006年;《当代微生物学与免疫学综述》18:258 - 266,2008年]。这些效应蛋白在空间和时间上改变宿主的信号通路[《FEMS微生物学综述》35:1100 - 1125,2011年;《细胞宿主与微生物》5:571 - 579,2009年]。尽管T3SS在宿主 - 病原体相互作用中起着关键作用,但对T3SS及其相关效应蛋白的研究仅限于少数几种细菌[《细胞微生物学》13:1858 - 1869,2011年;《自然评论微生物学》6:11 - 16,2008年;《分子微生物学》80:1420 - 1438,2011年]。在着手对一组未知细菌进行系统实验研究之前,通过开发一种计算机筛选算法来识别潜在的候选对象将是有益的。从多个细菌基因组测序产生的大量数据资源中提取宿主 - 病原体相互作用的首要主题(如果有的话),系统水平的研究也将比传统实验室方法更具优势。

结果

我们开发了一种计算机程序,其中使用最保守的T3SS蛋白集作为查询对象,针对整个细菌数据库,搜索参数越来越严格。这使我们能够识别出几种未被表征的T3SS阳性细菌。我们采用类似的策略来预测新鉴定的T3SS阳性细菌中已知效应蛋白的存在情况。关于T3SS效应蛋白的大量生化数据资源[《FEMS微生物学综述》35:1100 - 1125,2011年;《细胞宿主与微生物》5:571 - 579,2009年;《BMC生物信息学》7(11):S4,2010年]使我们能够寻找T3SS介导的发病机制中的共同主题。我们在宿主中识别出了一些细胞信号网络,这些网络被大多数含有T3SS的病原体所操纵。我们接着寻找特定类别的细菌的生物学特性与其所携带的效应蛋白之间是否存在相关性。我们能够确定一些在某些类别的细菌中富集的效应蛋白。

结论

当前的研究将开辟新的途径来探索许多未被表征的T3SS阳性细菌。对本研究预测结果的实验验证将揭示T3SS阳性细菌感染宿主细胞的一般机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/39b9/3734048/460982250f15/1756-0500-6-297-1.jpg

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