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Protein Homology Network Families Reveal Step-Wise Diversification of Type III and Type IV Secretion Systems

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NIAID Data Ecosystem2026-03-06 收录
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https://figshare.com/articles/dataset/Protein_Homology_Network_Families_Reveal_Step_Wise_Diversification_of_Type_III_and_Type_IV_Secretion_Systems/152690
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From the analysis of 251 prokaryotic genomes stored in public databases, the 761,260 deduced proteins were used to reconstruct a complete set of bacterial proteic families. Using the new Overlap algorithm, we have partitioned the Protein Homology Network (PHN), where the proteins are the nodes and the links represent homology relationships. The algorithm identifies the densely connected regions of the PHN that define the families of homologous proteins, here called PHN-Families, recognizing the phylogenetic relationships embedded in the network. By direct comparison with a manually curated dataset, we assessed that this classification algorithm generates data of quality similar to a human expert. Then, we explored the network to identify families involved in the assembly of Type III and Type IV secretion systems (T3SS and T4SS). We noticed that, beside a core of conserved functions (eight proteins for T3SS, seven for T4SS), a variable set of accessory components is always present (one to nine for T3SS, one to five for T4SS). Each member of the core corresponds to a single PHN-Family, while accessory proteins are distributed among different pure families. The PHN-Family classification suggests that T3SS and T4SS have been assembled through a step-wise, discontinuous process, by complementing the conserved core with subgroups of nonconserved proteins. Such genetic modules, independently recruited and probably tuned on specific effectors, contribute to the functional specialization of these organelles to different microenvironments.

本研究依托公共数据库中存储的251个原核生物基因组开展分析,以其中推导得到的761260个推定蛋白质为材料,重构了一套完整的细菌蛋白质家族集合。本研究采用全新的Overlap算法,对蛋白质同源网络(Protein Homology Network, PHN)进行分区:该网络以蛋白质为节点,边则代表蛋白质间的同源关联。该算法可识别PHN中紧密连通的区域,这些区域即为同源蛋白质家族的构成单元,本研究将其命名为PHN家族,并从中挖掘网络所蕴含的系统发育关系。通过与人工注释的基准数据集直接比对,本研究评估发现,该分类算法生成的分类结果质量可与人类专家的工作相媲美。随后,本研究对该PHN展开探索,以筛选参与III型分泌系统(Type III Secretion System, T3SS)与IV型分泌系统(Type IV Secretion System, T4SS)组装过程的蛋白质家族。研究观察到,除了一套保守功能核心组件(T3SS包含8种蛋白质,T4SS包含7种蛋白质)之外,两类分泌系统均配备一套可变的附属组分:T3SS的附属组分数量为1至9种,T4SS则为1至5种。保守功能核心中的每个蛋白质成员均对应唯一的PHN家族,而附属蛋白质则分散于多个独立的PHN家族之中。基于PHN家族的分类结果,本研究推测T3SS与T4SS的组装遵循渐进式、非连续的过程:通过将保守功能核心与非保守蛋白质亚组进行组合,完成系统组装。这些独立招募而来、且可能针对特定效应因子进行适配优化的遗传模块,使得这些分泌细胞器能够针对不同微环境实现功能特化。
创建时间:
2006-12-01
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