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利用多种计算算法和实验分析的综合方法鉴定结核分枝杆菌 H37Rv 的新型黏附素。

Identification of novel adhesins of M. tuberculosis H37Rv using integrated approach of multiple computational algorithms and experimental analysis.

机构信息

Functional Genomics Unit, Council of Scientific and Industrial Research-Institute of Genomics and Integrative Biology (CSIR-IGIB), New Delhi, India.

出版信息

PLoS One. 2013 Jul 29;8(7):e69790. doi: 10.1371/journal.pone.0069790. Print 2013.

DOI:10.1371/journal.pone.0069790
PMID:23922800
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3726780/
Abstract

Pathogenic bacteria interacting with eukaryotic host express adhesins on their surface. These adhesins aid in bacterial attachment to the host cell receptors during colonization. A few adhesins such as Heparin binding hemagglutinin adhesin (HBHA), Apa, Malate Synthase of M. tuberculosis have been identified using specific experimental interaction models based on the biological knowledge of the pathogen. In the present work, we carried out computational screening for adhesins of M. tuberculosis. We used an integrated computational approach using SPAAN for predicting adhesins, PSORTb, SubLoc and LocTree for extracellular localization, and BLAST for verifying non-similarity to human proteins. These steps are among the first of reverse vaccinology. Multiple claims and attacks from different algorithms were processed through argumentative approach. Additional filtration criteria included selection for proteins with low molecular weights and absence of literature reports. We examined binding potential of the selected proteins using an image based ELISA. The protein Rv2599 (membrane protein) binds to human fibronectin, laminin and collagen. Rv3717 (N-acetylmuramoyl-L-alanine amidase) and Rv0309 (L,D-transpeptidase) bind to fibronectin and laminin. We report Rv2599 (membrane protein), Rv0309 and Rv3717 as novel adhesins of M. tuberculosis H37Rv. Our results expand the number of known adhesins of M. tuberculosis and suggest their regulated expression in different stages.

摘要

与真核宿主相互作用的病原细菌在其表面表达黏附素。这些黏附素有助于细菌在定植过程中附着到宿主细胞受体上。已经使用基于病原体生物学知识的特定实验相互作用模型,鉴定了几种黏附素,如肝素结合血凝素黏附素(HBHA)、Apa、结核分枝杆菌的苹果酸合成酶。在本工作中,我们对结核分枝杆菌的黏附素进行了计算筛选。我们使用 SPAAN 进行黏附素预测、PSORTb、SubLoc 和 LocTree 进行细胞外定位以及 BLAST 进行非相似性验证的综合计算方法,这些步骤是反向疫苗学的第一步。来自不同算法的多种要求和攻击都通过争论方法进行处理。额外的过滤标准包括选择具有低分子量的蛋白质和没有文献报道的蛋白质。我们使用基于图像的 ELISA 检查了所选蛋白质的结合潜力。蛋白质 Rv2599(膜蛋白)与人纤维连接蛋白、层粘连蛋白和胶原蛋白结合。Rv3717(N-乙酰基胞壁酰-L-丙氨酸酰胺酶)和 Rv0309(L、D-转肽酶)与纤维连接蛋白和层粘连蛋白结合。我们报告 Rv2599(膜蛋白)、Rv0309 和 Rv3717 是结核分枝杆菌 H37Rv 的新型黏附素。我们的结果扩展了已知结核分枝杆菌黏附素的数量,并表明它们在不同阶段的调节表达。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28f9/3726780/5bd602e8f711/pone.0069790.g008.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/28f9/3726780/5bd602e8f711/pone.0069790.g008.jpg

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