Archer Simon C, Bradley Andrew J, Cooper Selin, Davies Peers L, Green Martin J
University of Nottingham, School of Veterinary Medicine and Science, Sutton Bonington Campus, Sutton Bonington, Leicestershire, LE12 5RD, United Kingdom.
University of Nottingham, School of Veterinary Medicine and Science, Sutton Bonington Campus, Sutton Bonington, Leicestershire, LE12 5RD, United Kingdom; Quality Milk Management Services Limited, Cedar Barn, Easton, Wells, Somerset BA5 1DU, United Kingdom.
Prev Vet Med. 2017 Sep 1;144:1-6. doi: 10.1016/j.prevetmed.2017.05.015. Epub 2017 May 17.
The purpose of this study was to evaluate whether the risk of Streptococcus uberis clinical mastitis at cow level could be predicted from the historical presence of specific strains of S. uberis on dairy farms. Matrix-assisted laser desorption ionization time of flight mass spectrometry was used to identify S. uberis isolates potentially capable of contagious transmission. Data were available from 10,652 cows from 52 English and Welsh dairy farms over a 14 month period, and 521 isolates of S. uberis from clinical mastitis cases were available for analysis. As well as the temporal herd history of clinical mastitis associated with particular S. uberis strains, other exposure variables included cow parity, stage of lactation, milk yield, and somatic cell count. Observations were structured longitudinally as repeated weekly measures through the study period for each cow. Data were analyzed in a Bayesian framework using multilevel logistic regression models. Similarity of mass spectral profiles between isolates of S. uberis from consecutive clinical cases of mastitis in herds was used to indicate potential for contagious phenotypic characteristics. Cross validation showed that new isolates with these characteristics could be identified with an accuracy of 90% based on bacterial protein mass spectral characteristics alone. The cow-level risk in any week of these S. uberis clinical mastitis cases increased with the presence of the same specific strains of S. uberis in other cows in the herd during the previous 2 weeks. The final statistical model indicated there would be a 2-3 fold increase in the risk of S. uberis clinical mastitis associated with particular strains if these occurred in the herd 1 and 2 weeks previously. The results suggest that specific strains of S. uberis may be involved with contagious transmission, and predictions based on their occurrence could be used as an early warning surveillance system to enhance the control of S. uberis mastitis.
本研究的目的是评估能否根据奶牛场乳房链球菌特定菌株的既往存在情况,预测奶牛层面乳房链球菌临床型乳腺炎的风险。采用基质辅助激光解吸电离飞行时间质谱法来鉴定可能具有传染性传播能力的乳房链球菌分离株。研究数据来自52个英格兰和威尔士奶牛场的10652头奶牛,为期14个月,共有521份来自临床乳腺炎病例的乳房链球菌分离株可供分析。除了与特定乳房链球菌菌株相关的临床乳腺炎的时间性畜群病史外,其他暴露变量还包括奶牛胎次、泌乳阶段、产奶量和体细胞计数。在整个研究期间,对每头奶牛每周进行重复测量,纵向构建观察数据。使用多水平逻辑回归模型在贝叶斯框架下对数据进行分析。畜群中连续乳腺炎临床病例的乳房链球菌分离株之间的质谱图相似性,用于表明具有传染性表型特征的可能性。交叉验证表明,仅基于细菌蛋白质质谱特征,就能以90%的准确率识别具有这些特征的新分离株。在任何一周,这些乳房链球菌临床型乳腺炎病例的奶牛层面风险,会随着前两周畜群中其他奶牛存在相同特定乳房链球菌菌株而增加。最终的统计模型表明,如果特定菌株在畜群中提前1周和2周出现,与之相关的乳房链球菌临床型乳腺炎风险将增加2至3倍。结果表明,特定的乳房链球菌菌株可能与传染性传播有关,基于其出现情况的预测可作为早期预警监测系统,以加强对乳房链球菌乳腺炎的控制。