中国奶牛乳房炎病原菌群的地区分布特征

Distribution Characteristics of Pathogenic Communities Associated with Bovine Mastitis across Different Regions of China

摘要: 【目的】探明不同地区奶源病原菌群落的分布特征对奶牛乳房炎的有效防控至关重要。【方法】用Excel统计分析传统分离鉴定的病原菌群落组成，基于R语言二维等级聚类法比较病原菌种群间及不同地区群落间差异性。【结果】源于我国7个地理分区的18个省市区共获得30个已知种属及其检出率的类群。不同地区奶牛乳房炎病原菌群落组成差异大。其中，金黄色葡萄球菌、无乳链球菌、大肠杆菌、停乳链球菌和乳房链球菌分别是甘肃等9省市、广东等3省区、辽宁和上海、江苏和湖北、新疆和广西的最优势种群，检出率分别为19.6%~61.5%、23.5%~29.0%、14.4%~19.7%、27.1%~33.3%、15.4%~20.3%。种群间检出率差异最大的金黄色葡萄球菌独占最大分支，群落间辽宁沈阳独占最大分支。【结论】不同地区奶牛乳房炎病原菌群落组成迥异，影响因素复杂。建议结合区域气候及畜间差异、圈舍及卫生措施等因素进行乳房炎病原菌群落生态学研究。

Abstract: [Objective] In order to prevent and control effectively bovine mastitis, it is important to clarify distribution characteristics of pathogenic microbiome in mastitis-affected cow milk from different regions. [Methods] Based on traditional culture and universal identifications, the communities composition of the pathogenic bacteria and fungi was statistically analyzed using Excel worksheets. Furthermore, two-dimensional hierarchical clustering method based on heat map visualization of R language was used to analyze differences among pathogenic populations at species level and communities from different regions. [Results] There were a total of 30 pathogenic species with known detection rates in all mastitis-affected milk samples from 7 geographical regions, including 18 Provinces/Autonomous regions/Municipalities (PAMs) of China. The communities composition of different pathogenic microbiomes at regional scale differed greatly. Among them, Staphylococcus aureus, Streptococcus agalactiae, Escherichia coli, Streptococcus dysgalactiae and Streptococcus uberis were dominated in 9 PAMs, i.e., Gansu and so on, 3 PAMs, i.e., Guangdong and so on, Liaoning and Shanghai, Jiangsu and Hubei, Xinjiang and Guangxi, whose detection rates were 19.6% - 61.5%, 23.5% - 29.0%, 14.4% - 19.7%, 27.1% - 33.3%, 15.4% - 20.3%, respectively. Due to the significant differences of detection rates across pathogenic populations or microbiomes, Staphylococcus aureus and Shenyang accounted for the highest share of populations and microbiomes, respectively. [Conclusions] The detection rates of pathogenic community compositions causing bovine mastitis differed largely from 18 PAMs of China, associated with complicated causes. The results suggest that bovine mastitis pathogenic microbiome should be associated with the regional climate factors, herd-level and cow-level factors, different housing and hygienic measures using the community ecology principles and methods in future.