本文選題：肺炎克雷伯菌 + 細(xì)菌Ⅵ型分泌系統(tǒng)�。� 參考：《上海交通大學(xué)》2015年博士論文

【摘要】：肺炎克雷伯菌(Klebsiella pneumoniae)是院內(nèi)感染最重要的多重耐藥條件致病菌之一。11個不同來源的肺炎克雷伯菌基因組已被全測序,包括耐碳青霉烯類抗生素的、屬于ST11型中國流行克隆株的臨床菌株HS11286。近期發(fā)現(xiàn)的Ⅵ分泌系統(tǒng)(type Ⅵ secretion system,T6SS)是一種細(xì)胞接觸依賴性的多組件跨膜通道,在細(xì)菌致病機(jī)制及細(xì)菌間拮抗作用中扮演著重要角色。T6SS已被發(fā)現(xiàn)存在于銅綠假單胞菌和霍亂弧菌等多個革蘭陰性細(xì)菌中;但是在肺炎克雷伯菌中鮮有研究。本論文推測T6SS與肺炎克雷伯菌的致病性、耐藥性、自然生存和傳播性等關(guān)鍵生物學(xué)特性相關(guān),利用生物信息學(xué)方法對已測序肺炎克雷伯菌基因組的T6SS基因簇和分泌效應(yīng)物進(jìn)行了系統(tǒng)地識別和比較,以輔助實驗研究來解析T6SS的生物學(xué)功能。本文首先預(yù)測了肺炎克雷伯菌的T6SS基因簇。通過文獻(xiàn)挖掘和生物信息學(xué)預(yù)測,本文識別了498個細(xì)菌菌株中的906個T6SS基因簇數(shù)據(jù),主要包括:(i)經(jīng)過對708篇PubMed收錄文獻(xiàn)的檢索和人工校驗,收集的57個菌株中64個T6SS、92個T6SE和25個免疫蛋白及127個調(diào)控因子;(ii)基于T6SS保守組件氨基酸序列的高度相似性預(yù)測的T6SS。SecReT6根據(jù)T6SS核心組件的序列相似性和基因排布,將這些T6SS系統(tǒng)地分為3種類型:i,ii和iii。利用PostgreSQL關(guān)系型數(shù)據(jù)庫管理系統(tǒng),本文建立了開放數(shù)據(jù)庫SecReT6。SecReT6整合了多種異源數(shù)據(jù),提供了基于Web的T6SS核心組件、T6SE和免疫蛋白、調(diào)控因子等功能和分類信息的瀏覽和查詢服務(wù)。SecReT6還提供了相似性搜索、基因簇比對和系統(tǒng)發(fā)生學(xué)分析等在線工具。此外,基于不同類型T6SS核心組件的隱馬爾科夫模型特征譜,開發(fā)了T6SS基因簇識別工具T6SS-HMMER。利用T6SS-HMMER工具,本文在11個已全測序的肺炎克雷伯菌基因組中識別了26個T6SS。其中,在肺炎克雷伯菌HS11286中識別2個T6SS基因簇:編碼了12個T6SS核心組件的T6SS-1(KPHS_22970..KPHS_23190),及編碼9個T6SS組件的T6SS-2(KPHS_32450..KPHS_32770)。其次,本文采用了三種方法來預(yù)測肺炎克雷伯菌T6SS分泌效應(yīng)物(T6SE):(i)SecReT6收錄了和已知T6SE高序列相似性的蛋白;(ii)通過T6SS基因簇比較分析發(fā)現(xiàn),插入T6SS保守組件基因中的可變區(qū)可能攜帶了新的T6SE和相鄰的免疫蛋白;(iii)基于已知T6SE的多重序列特征,提出一個基于支持向量機(jī)分類器的算法來預(yù)測零散分布在基因組的新T6SE。本文在肺炎克雷伯菌HS11286中識別了T6SS-1基因簇編碼的效應(yīng)蛋白KPHS_23105和4個免疫蛋白KPHS_23060-KPHS_23090。最后,本文將T6SS保守基因簇的識別工作擴(kuò)展到細(xì)菌III型和IV型等多組件分泌系統(tǒng),以及原噬菌體、整合性接合元件、整合子、插入序列和基因組島等可移動遺傳元件的識別。這些分泌系統(tǒng)和可移動遺傳元件常攜帶致病因子和獲得性耐藥基因,可視為病原細(xì)菌感染的風(fēng)險基因。針對細(xì)菌基因組序列中這些致病和耐藥相關(guān)風(fēng)險基因的準(zhǔn)確和快速識別需求,本文開發(fā)了基于高性能計算機(jī)群的在線預(yù)測服務(wù)STeP。STeP提供的VRprofile工具可在10分鐘內(nèi)完成肺炎克雷伯菌HS11286的5.3Mb染色體序列的分析任務(wù);對預(yù)測出來的T3SS/T4SS/T6SS/T7SS和可移動遺傳元件,VRprofile還提供了對后臺數(shù)據(jù)庫MobilomeDB收錄已知元件的可視化比較分析服務(wù)。STeP服務(wù)器還提供了對完全或部分測序細(xì)菌基因組快速注釋工具CDSeasy,細(xì)菌保守基因簇識別工具CGCfinder,COG基因集的可視化共定位工具COGviewer�？傊�,本論文以肺炎克雷伯菌為切入點,對已測序細(xì)菌基因組中T6SS及分泌效應(yīng)物的分布進(jìn)行了系統(tǒng)地考查。所構(gòu)建的T6SS開放系統(tǒng)數(shù)據(jù)庫和T6SE識別工具,有助于實驗研究肺炎克雷伯菌及其他重要的革蘭陰性病原細(xì)菌中T6SS與致病機(jī)制及細(xì)菌間拮抗作用之間的關(guān)系。細(xì)菌致病和耐藥相關(guān)基因簇的生物信息學(xué)分析工具集將有助于從基因組序列水平快速預(yù)測病原細(xì)菌的潛在致病和耐藥能力。
[Abstract]:Klebsiella pneumoniae (Klebsiella pneumoniae) is one of the most important multidrug resistant condition pathogenic bacteria in hospital infection. The genome of Klebsiella pneumoniae, one of the different sources of.11, has been fully sequenced, including the carbapenems, which belongs to the ST11 type Chinese popular clone strain HS11286. recently found in the VI secretory system (type VI). Secretion system, T6SS) is a cell contact dependent multicomponent transmembrane channel, which plays an important role in the pathogenic mechanism of bacteria and the antagonism of bacteria..T6SS has been found in many Gram-negative bacteria such as Pseudomonas aeruginosa and Vibrio cholerae, but there are few studies in Klebsiella pneumoniae. This paper speculated that T6SS It is related to the key biological characteristics of Klebsiella pneumoniae, such as the pathogenicity, resistance, natural survival and transmission, and systematically identifies and compares the T6SS gene cluster and secretory effector of the genome of Klebsiella pneumoniae by bioinformatics method, in order to assist the analysis of the biological function of T6SS. The T6SS gene cluster of Klebsiella pneumoniae was predicted. Through literature mining and bioinformatics prediction, this paper identified 906 T6SS gene cluster data of 498 bacterial strains, including: (I) after retrieving and manually checking 708 PubMed collections, 64 T6SS, 92 T6SE, 25 immunoglobulin and 127 of the collected strains were collected. Regulatory factors; (II) T6SS.SecReT6 based on the high similarity prediction based on the amino acid sequence of the T6SS conservative component, T6SS.SecReT6 is divided into 3 types based on the sequence similarity and gene arrangement of the T6SS core components: I, II and III. use PostgreSQL relational database management system, and the integration of the open database SecReT6.SecReT6 is established in this paper. A variety of heterogeneous data, providing Web based T6SS core components, T6SE and immunoglobulin, regulatory factors and other functions and classification information browsing and query services.SecReT6 also provide online tools such as similarity search, gene cluster comparison and phylogenetic analysis. In addition, hidden Markov model based on different types of T6SS core components The T6SS gene cluster identification tool, T6SS-HMMER., was developed using the T6SS-HMMER tool to identify 26 T6SS. in 11 fully sequencing Klebsiella pneumoniae genome, and 2 T6SS gene clusters were identified in Klebsiella pneumoniae HS11286: T6SS-1 (KPHS_22970..KPHS_23190) of 12 T6SS core components and 9 T6SS groups T6SS-2 (KPHS_32450..KPHS_32770). Secondly, three methods are used to predict the T6SS secretory effector of Klebsiella pneumoniae (T6SE): (I) SecReT6 includes a protein that is similar to the known high sequence of T6SE sequences; (II) it is found that the variable region inserted into the T6SS conservative component gene may carry a new T6SE and a new T6SE sequence. Adjacent immune proteins; (III) based on the multiple sequence characteristics of known T6SE, an algorithm based on the support vector machine classifier is proposed to predict the scattered distribution in the genome. The effect protein KPHS_23105 and the 4 immune protein KPHS_23060-KPHS_23090., which are encoded by the T6SS-1 gene cluster, are identified in the Klebsiella pneumoniae HS11286. This paper extends the identification of T6SS conserved gene clusters to multi component secretory systems such as bacterial III and IV, as well as the identification of removable genetic elements such as original phage, integrated conjugation elements, integrons, insertion sequences and genome islands. These secretory systems and removable relic elements often carry pathogenic factors and acquired resistance genes, In view of the accurate and rapid identification requirements of these pathogenic and drug-resistant risk genes in the bacterial genome sequence, the VRprofile tool provided by the online prediction service STeP.STeP based on high performance computer group can complete the 5.3Mb dyeing of Klebsiella pneumoniae HS11286 within 10 minutes. The analysis task of the sequence of color bodies; for the predicted T3SS/T4SS/T6SS/T7SS and removable genetic components, VRprofile also provides a visual comparative analysis service for a background database MobilomeDB that contains known components..STeP server also provides a rapid annotation tool for complete or partial sequencing of bacterial gene groups CDSeasy, a bacterial conservative gene cluster. The identification tool CGCfinder, the Visual Co location tool of the COG gene set COGviewer., in this paper, the distribution of the T6SS and the secretory effectors in the genome of the sequenced bacteria was systematically investigated with Klebsiella pneumoniae as the breakthrough point. The T6SS open system database and the T6SE identification tool were used to study the experimental study of pneumonia Klein. The relationship between T6SS and the pathogenic mechanism and the antagonism among the other important gram-negative pathogenic bacteria. The bioinformatics analysis tool set for bacterial and drug-resistant gene clusters will help to quickly predict the potential pathogenicity and drug resistance of pathogenic bacteria from the genome sequence level.
【學(xué)位授予單位】：上海交通大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2015
【分類號】：R378
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本文編號：1948867