Expansion and re-classification of the extracytoplasmic function (ECF) σ factor family.
Expansion and re-classification of the extracytoplasmic function (ECF) σ factor family.
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细胞质外功能（ECF）σ因子家族的扩展和重新分类。
DOI：
10.1093/nar/gkaa1229
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发表时间：
2021-01-25
影响因子：
14.9
通讯作者：
Fritz G
中科院分区：
文献类型：
--
作者：
Casas-Pastor D;Müller RR;Jaenicke S;Brinkrolf K;Becker A;Buttner MJ;Gross CA;Mascher T;Goesmann A;Fritz G
胞质外功能因子（Extracytoplasmic function σ factors，ECFs）在数量、多样性和重要性方面代表了细菌的主要信号转导机制之一，特别是在介导应激反应方面。在这里，我们进行了一个全面的系统发育分析，这个蛋白质家族通过仔细检查NCBI数据库中的所有蛋白质。结果，我们确定了平均每个细菌基因组100个ECF和157个系统发育ECF组，其特征是保守的遗传邻域和类似的调节机制。我们的分析扩展了以前的分类工作150倍，丰富了许多原始的ECF组与以前未分类的蛋白质，并确定了22个全新的ECF组。ECF组在层次上彼此相关，并且进一步由具有密切相关序列的亚组组成。这种两层分类允许准确预测共同的启动子基序和推断推定的调控机制，跨亚组组成的ECF组。ECF家族的系统发育分布的这种全面的、高分辨率的描述，连同分类的ECF序列的大规模扩展和称为“ECF Hub”（https：//www.computational.bio.uni-giessen.de/ecfhub）的可公开访问的数据库，将作为一个强大的假设生成器来指导该领域的未来研究。
Extracytoplasmic function σ factors (ECFs) represent one of the major bacterial signal transduction mechanisms in terms of abundance, diversity and importance, particularly in mediating stress responses. Here, we performed a comprehensive phylogenetic analysis of this protein family by scrutinizing all proteins in the NCBI database. As a result, we identified an average of ∼10 ECFs per bacterial genome and 157 phylogenetic ECF groups that feature a conserved genetic neighborhood and a similar regulation mechanism. Our analysis expands previous classification efforts ∼50-fold, enriches many original ECF groups with previously unclassified proteins and identifies 22 entirely new ECF groups. The ECF groups are hierarchically related to each other and are further composed of subgroups with closely related sequences. This two-tiered classification allows for the accurate prediction of common promoter motifs and the inference of putative regulatory mechanisms across subgroups composing an ECF group. This comprehensive, high-resolution description of the phylogenetic distribution of the ECF family, together with the massive expansion of classified ECF sequences and an openly accessible data repository called ‘ECF Hub’ (https://www.computational.bio.uni-giessen.de/ecfhub), will serve as a powerful hypothesis-generator to guide future research in the field.
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