红斑丹毒丝菌蛋白间相互作用网络的构建与分析

doi:10.14088/j.cnki.issn0439-8114.2025.07.024

湖北农业科学 ›› 2025, Vol. 64 ›› Issue (7): 137-141.doi: 10.14088/j.cnki.issn0439-8114.2025.07.024

红斑丹毒丝菌蛋白间相互作用网络的构建与分析

吴雪军¹, 董琦², 周彩琴¹, 章晓炜¹, 刘威³

1.浙江省动物疫病预防控制中心,杭州 311199;
2.黄冈市团风县畜牧兽医发展中心,湖北黄冈 438000;
3.湖北省农业科学院畜牧兽医研究所/农业农村部畜禽细菌病防治制剂创制重点实验室/畜禽病原微生物学湖北省重点实验室,武汉 430064

收稿日期:2025-03-05 出版日期:2025-07-25 发布日期:2025-08-22
通讯作者: 章晓炜（1980-）,男,浙江淳安人,高级畜牧师,主要从事畜牧技术推广研究工作,（电子信箱）18379967@qq.com。
作者简介:吴雪军（1986-）,男,浙江杭州人,兽医师,硕士,主要从事动物传染病研究工作,（电子信箱）xuejun0802@163.com。
基金资助:
浙江省“三农九方”科技协作计划“揭榜挂帅”项目（规模猪场精准消毒技术及数智化管控系统研发与示范应用）

The construction and analysis of the protein-protein interaction network of Erysipelothrix rhusiopathiae

WU Xue-jun¹, DONG Qi², ZHOU Cai-qin¹, ZHANG Xiao-wei¹, LIU Wei³

1. Zhejiang Center for Animal Disease Control and Prevention, Hangzhou 311199, China;
2. Huanggang City Tuanfeng County Animal Husbandry and Veterinary Development Center , Huanggang 438000, Hubei , China;
3. Key Laboratory of Prevention and Control Agents for Animal Bacteriosis (Ministry of Agriculture and Rural Affairs) / Hubei Provincial Key Laboratory of Animal Pathogenic Microbiology / Institute of Animal Husbandry and Veterinary, Hubei Academy of Agricultural Sciences, Wuhan 430064, China

Received:2025-03-05 Published:2025-07-25 Online:2025-08-22

摘要/Abstract

摘要： 病原菌编码蛋白间的相互作用研究是理解其各项生命活动、揭示信号转导机制、预测潜在药物靶标的重要途径。旨在利用DIP蛋白互作数据库和同源蛋白映射方法,构建红斑丹毒丝菌（Erysipelothrix rhusiopathiae）编码蛋白间的相互作用网络。结果表明,所构建的互作网络共包含2 113对非冗余的相互作用关系,涉及330个蛋白,并绘制了互作网络的拓扑结构图。通过全基因组内蛋白之间的互作频率分析,确定了在红斑丹毒丝菌中互作频率最高的40个蛋白,这些蛋白主要与翻译、转录、分子伴侣等功能相关。伴侣蛋白DnaK、DnaJ、GroEL以及DEAD/DEAH解旋酶的互作频率较高,能与核糖体蛋白、代谢相关、伴侣蛋白、细胞分裂蛋白等多种功能蛋白发生相互作用。若DnaK、DnaJ、GroEL、DEAD/DEAH解旋酶的功能受到抑制,则会对红斑丹毒丝菌的正常生命活动造成较大的影响。

关键词: 红斑丹毒丝菌（Erysipelothrix rhusiopathiae）, 蛋白间相互作用, 互作网络

Abstract: Analysis of the interaction between pathogenic proteins was an important way to understand their life activities, reveal the signal transduction mechanism, and predict potential drug targets. The aim of this study was to construct a comprehensive interaction network between the encoded proteins of Erysipelothrix rhusiopathiae by using the DIP protein interaction database and the homologous protein mapping method. The constructed interaction network contains 2 113 pairs of non-redundant interactions involving 330 proteins. Our analysis unraveled 40 proteins with highest interactions in the network, and most of them were related to translation, transcription, molecular chaperone, and other functions. Further analysis showed that chaperone proteins DnaK, DnaJ, GroEL and DEAD/DEAH helicases had high interaction frequencies and could interact with multiple functional proteins such as ribosomal proteins, metabolically related proteins, chaperone proteins, and cell division proteins. The results suggested that if the functions of DnaK, DnaJ, GroEL, DEAD/DEAH helicases were inhibited, the normal life activities of Erysipelothrix rhusiopathiae would be greatly affected.

Key words: Erysipelothrix rhusiopathiae, protein interaction, interaction network

中图分类号:

吴雪军, 董琦, 周彩琴, 章晓炜, 刘威. 红斑丹毒丝菌蛋白间相互作用网络的构建与分析[J]. 湖北农业科学, 2025, 64(7): 137-141.

WU Xue-jun, DONG Qi, ZHOU Cai-qin, ZHANG Xiao-wei, LIU Wei. The construction and analysis of the protein-protein interaction network of Erysipelothrix rhusiopathiae[J]. HUBEI AGRICULTURAL SCIENCES, 2025, 64(7): 137-141.

参考文献

[1] 朱伟峰,陈露,谭凯,等.猪丹毒丝菌GAPDH线性B细胞表位预测与鉴定[J].江苏农业科学,2021,49(22):171-174.
[2] MORIMOTO M, KATO A, KOJIMA H, et al.Serovars and SpaA types of Erysipelothrix rhusiopathiae isolated from pigs in Japan from 2012 to 2019[J]. Current microbiology, 2021, 78(1): 55-66.
[3] ROSTAMIAN M, RAHMATI D, AKYA A.Clinical manifestations, associated diseases, diagnosis, and treatment of human infections caused by Erysipelothrix rhusiopathiae: A systematic review[J]. Germs, 2022, 12(1): 16-31.
[4] WU C, LV C, ZHAO Y, et al.Characterization of Erysipelothrix rhusiopathiae isolates from diseased pigs in 15 Chinese provinces from 2012 to 2018[J]. Microorganisms, 2021, 9(12): 2615.
[5] 张瑞华,任丹宁,高善颂,等. 猪丹毒杆菌的分离鉴定及药敏试验研究[J]. 山东农业科学,2021,53(10):123-127.
[6] 魏文涛,姚焱彬,刘全喜,等. 2012—2015年江淮地区猪丹毒杆菌分离株血清型、spaA基因遗传进化及及PFGE基因型分析[J].微生物学通报,2017,44( 3) :664-672.
[7] 李一经. 兽医微生物学[M].北京:高等教育出版社,2011.
[8] 董建斐,虞一聪,裘贤平,等.猪丹毒的病原学诊断及药敏试验[J].浙江畜牧兽医,2018,43(6):30-32.
[9] BALOOTAKI PA, AMIN M, HAGHPARASTI F, et al.Isolation and detection of Erysipelothrix rhusiopathiae and its distribution in humans and animals by phenotypical and molecular methods in Ahvaz-Iran in 2015[J]. Iranian journal of medical sciences, 2017, 42: 377-383.
[10] DING Y, ZHU D, ZHANG J, et al.Virulence determinants, antimicrobial susceptibility, and molecular profiles of Erysipelothrix rhusiopathiae strains isolated from China[J]. Emerg Microbes Infect, 2015, 4: e69.
[11] CUI T, ZHANG L, WANG X, et al.Uncovering new signaling proteins and potential drug targets through the interactome analysis of Mycobacterium tuberculosis[J]. BMC genomics, 2009, 10: 118.
[12] ALTSCHUL S F, MADDEN T L, SCHAFFER A A, et al.Gapped BLAST and PSI-BLAST: A new generation of protein database search programs[J]. Nucleic Acids Res,1997, 25: 3389-3402.
[13] SHANNON P, MARKIEL A, OZIER O, et al.Cytoscape: A software environment for integrated models of biomolecular interaction networks[J]. Genome Res, 2003, 13:2498-2504.
[14] ZHAXYBAYEVA O, GOGARTEN J P.Bootstrap, Bayesian probability and maximum likelihood mapping:Exploring new tools for comparative genome analyses[J]. BMC genomics, 2002, 3: 4.
[15] 许淑娟,谢晶莹,冯若飞,等. DEAD-box RNA 解旋酶家族在天然免疫应答信号通路中的作用[J].微生物学报, 2021, 61(3):587-595.
[16] HEATON S M, ATKINSON S C, SWEENEY M N, et al.Exportin-1-dependent nuclear export of DEAD-box helicase DDX3X is central to its role in antiviral immunity[J]. Cells, 2019, 8(10): 1181.

红斑丹毒丝菌蛋白间相互作用网络的构建与分析

The construction and analysis of the protein-protein interaction network of Erysipelothrix rhusiopathiae

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