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比较系统发育分析和蛋白质预测揭示了食源菌株的分类学及毒力因子的多样分布。

Comparative Phylogenetic Analysis and Protein Prediction Reveal the Taxonomy and Diverse Distribution of Virulence Factors in Foodborne Strains.

作者信息

Zhang Ming, Yin Zhenzhen

机构信息

School of Yunkang Medicine and Health, Nanfang College, Guangzhou, Guangdong, China.

出版信息

Evol Bioinform Online. 2024 Nov 4;20:11769343241294153. doi: 10.1177/11769343241294153. eCollection 2024.

DOI:10.1177/11769343241294153
PMID:39502941
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11536399/
Abstract

BACKGROUND

and , 2 major foodborne pathogenic fusobacteria, have a variety of virulent protein types with nervous and enterotoxic pathogenic potential, respectively.

OBJECTIVE

The relationship between the molecular evolution of the 2 genomes and virulence proteins was studied via a bioinformatics prediction method. The genetic stability, main features of gene coding and structural characteristics of virulence proteins were compared and analyzed to reveal the phylogenetic characteristics, diversity, and distribution of virulence factors of foodborne strains.

METHODS

The phylogenetic analysis was performed via composition vector and average nucleotide identity based methods. Evolutionary distances of virulence genes relative to those of housekeeping genes were calculated via multilocus sequence analysis. Bioinformatics software and tools were used to predict and compare the main functional features of genes encoding virulence proteins, and the structures of virulence proteins were predicted and analyzed through homology modeling and a deep learning algorithm.

RESULTS

According to the diversity of toxins, genome evolution tended to cluster based on the protein-coding virulence genes. The evolutionary transfer distances of virulence genes relative to those of housekeeping genes in strains were greater than those in strains, and BoNTs and alpha toxin proteins were located extracellularly. The BoNTs have highly similar structures, but BoNT/A/B and BoNT/E/F have significantly different conformations. The beta2 toxin monomer structure is similar to but simpler than the alpha toxin monomer structure, which has 2 mobile loops in the N-terminal domain. The C-terminal domain of the CPE trimer forms a "claudin-binding pocket" shape, which suggests biological relevance, such as in pore formation.

CONCLUSIONS

According to the genotype of protein-coding virulence genes, the evolution of showed a clustering trend. The genetic stability, functional and structural characteristics of foodborne virulence proteins reveal the taxonomy and diverse distribution of virulence factors.

摘要

背景

[两种食源致病性梭菌]以及[另一种食源致病性梭菌]分别具有多种具有神经毒性和肠毒性致病潜力的毒力蛋白类型。

目的

通过生物信息学预测方法研究这两种[梭菌]基因组的分子进化与毒力蛋白之间的关系。比较和分析毒力蛋白的遗传稳定性、基因编码主要特征和结构特征,以揭示食源[梭菌]菌株毒力因子的系统发育特征、多样性和分布。

方法

通过基于组成向量和平均核苷酸同一性的方法进行系统发育分析。通过多位点序列分析计算毒力基因相对于管家基因的进化距离。使用生物信息学软件和工具预测和比较编码毒力蛋白的基因的主要功能特征,并通过同源建模和深度学习算法预测和分析毒力蛋白的结构。

结果

根据毒素的多样性,基因组进化倾向于基于蛋白质编码毒力基因进行聚类。[某种梭菌]菌株中毒力基因相对于管家基因的进化转移距离大于[另一种梭菌]菌株,肉毒毒素(BoNTs)和α毒素蛋白位于细胞外。BoNTs具有高度相似的结构,但BoNT/A/B和BoNT/E/F具有明显不同的构象。β2毒素单体结构与α毒素单体结构相似但更简单,α毒素单体结构在N端结构域有2个可移动环。CPE三聚体的C端结构域形成“紧密连接蛋白结合口袋”形状,这表明其具有生物学相关性,如在孔形成方面。

结论

根据蛋白质编码毒力基因的基因型,[梭菌]的进化呈现聚类趋势。食源[梭菌]毒力蛋白的遗传稳定性、功能和结构特征揭示了毒力因子的分类学和多样分布。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e5a/11536399/b9d0ae976488/10.1177_11769343241294153-fig9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e5a/11536399/b1135ad1a3d3/10.1177_11769343241294153-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e5a/11536399/582951ab16a2/10.1177_11769343241294153-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e5a/11536399/3cc5892699f8/10.1177_11769343241294153-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e5a/11536399/4796efc0da87/10.1177_11769343241294153-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e5a/11536399/8e0b2f349eb3/10.1177_11769343241294153-fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e5a/11536399/f78e3b2a8ef7/10.1177_11769343241294153-fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e5a/11536399/c56fff66c0a1/10.1177_11769343241294153-fig7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e5a/11536399/f5fb09089af8/10.1177_11769343241294153-fig8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e5a/11536399/b9d0ae976488/10.1177_11769343241294153-fig9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e5a/11536399/b1135ad1a3d3/10.1177_11769343241294153-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e5a/11536399/582951ab16a2/10.1177_11769343241294153-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e5a/11536399/3cc5892699f8/10.1177_11769343241294153-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e5a/11536399/4796efc0da87/10.1177_11769343241294153-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e5a/11536399/8e0b2f349eb3/10.1177_11769343241294153-fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e5a/11536399/f78e3b2a8ef7/10.1177_11769343241294153-fig6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e5a/11536399/c56fff66c0a1/10.1177_11769343241294153-fig7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e5a/11536399/f5fb09089af8/10.1177_11769343241294153-fig8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e5a/11536399/b9d0ae976488/10.1177_11769343241294153-fig9.jpg

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