科微学术
微生物学通报
2025年4月4日 周五
国家“十二五”重大专项项目(No. 2011ZX10004-001)
LI Dong-Mei
1. Department of Vector Biology and Control, State Key Laboratory for Infectious Diseases Prevention and Control, WHO Collaborating Centre for Vector Surveillance and Management, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, ChinaMiao Zhi-Gang
1. Department of Vector Biology and Control, State Key Laboratory for Infectious Diseases Prevention and Control, WHO Collaborating Centre for Vector Surveillance and Management, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China 2. Institute of Neuroscience, Soochow University, Suzhou, Jiangsu 215123, China)Song Xiu-Ping
1. Department of Vector Biology and Control, State Key Laboratory for Infectious Diseases Prevention and Control, WHO Collaborating Centre for Vector Surveillance and Management, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, ChinaWANG Cheng-Gang
1. Department of Vector Biology and Control, State Key Laboratory for Infectious Diseases Prevention and Control, WHO Collaborating Centre for Vector Surveillance and Management, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China 3. College of Basic Medical Sciences, Shandong University of Traditional Chinese Medicine, Jinan, Shandong 250355, ChinaSANG Shao-Wei
1. Department of Vector Biology and Control, State Key Laboratory for Infectious Diseases Prevention and Control, WHO Collaborating Centre for Vector Surveillance and Management, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, ChinaLIU Qi-Yong
1. Department of Vector Biology and Control, State Key Laboratory for Infectious Diseases Prevention and Control, WHO Collaborating Centre for Vector Surveillance and Management, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China【目的】分析影响巴尔通体脂肪酸成分的主要因素，建立适合巴尔通体脂肪酸成分分析的标准化方法，探讨脂肪酸图谱应用于巴尔通体分类鉴定的可能性。【方法】应用气相色谱技术分析不同培养条件下巴尔通体脂肪酸的组成与含量的变化；应用已构建的标准化方法获取10株巴尔通体标准菌株和9株来自不同地区的汉赛巴尔通体猫分离株脂肪酸图谱；应用SPSS 16.0统计软件对获得的数据资料进行聚类分析。【结果】培养基、温度和传代次数主要影响巴尔通体脂肪酸的微量成分；10株巴尔通体标准菌株的成分相似，但也存在构成和含量上的差异；在所测巴尔通体中，检出可分辨脂肪酸成分有20种，共有成分为7种，其中C18:1ω7c、C18:0和C16:0累积含量达80%以上；猫分离株被准确鉴定为汉赛巴尔通体。【结论】巴尔通体脂肪酸成分受培养基、温度等培养条件影响，在脂肪酸提取方法标化后，可用于汉赛巴尔通体种水平分类鉴定。
[Objective] For establishing taxonomic relationships among Bartonella species, gas chromatography (GC) was utilized to investigate their cellular fatty acids (CFAs) compositions with particular attention on the different growth conditions in the qualitative and quantitative changes of CFAs. [Methods] The whole cellular fatty acid methyl esters (FAMEs), from the different base media and the media at different percent of sheep blood, subculture and temperature of incubation, were obtained by saponification, methylation or extraction and then analyzed using the Sherlock Microbial Identification System. The dendrograms of ten strains of Bartonella species, isolated from different hosts (cats, dogs, rats, voles and human), and nine Bartonella strains of cats from different areas, were generated based on the CFAs data matrix using SPSS 16.0 software package. [Results] There were 20 CFAs in Bartonella strains tested. Among them, seven CFAs were common components and detected in all tested type strains of Bartonella species, which include C18:1ω7c, C18:0 and C16:0 and account for more than 80% of the total CFAs. The rest were minor with their presence and relative contents of being affected significantly by differences of culture media and conditions. The dendrogram of the isolates from cats with different type strains was approximately consistent with the hierarchical structure of molecular phylogenetic systematics. [Conclusion] The CFAs profiles are obtained by carefully regulating and standardizing the growth conditions and these profiles are successfully used to identify B. henselae wild isolates. Although these CFAs profiles are very useful in terms of Bartonella taxonomy, they must be viewed with caution until our knowledge of the quantitative and qualitative distributions of fatty acids over a wide variety of taxa and the growth conditions.
栗冬梅,苗志刚,宋秀平,王成岗,桑少伟,刘起勇. 巴尔通体细胞脂肪酸成分分析[J]. 微生物学通报, 2014, 41(2): 417-427
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