Abstract:
Antimicrobial usage (AMU) could be reduced by differentiating the causative bacteria in cases of clinical mastitis (CM) as either Gram-positive or Gram-negative bacteria or identifying whether the case is culture-negative (no growth, NG) mastitis. Immunoassays for biomarker analysis and a Tandem Mass Tag (TMT) proteomic investigation were employed to identify differences between samples of milk from cows with CM caused by different bacteria. A total of 94 milk samples were collected from cows diagnosed with CM across seven farms in Scotland, categorized by severity as mild (score 1), moderate (score 2), or severe (score 3). Bovine haptoglobin (Hp), milk amyloid A (MAA), C-reactive protein (CRP), lactoferrin (LF), α-lactalbumin (LA) and cathelicidin (CATHL) were significantly higher in milk from cows with CM, regardless of culture results, than in milk from healthy cows (all P-values <0.001). Milk cathelicidin (CATHL) was evaluated using a novel ELISA technique that utilises an antibody to a peptide sequence of SSEANLYRLLELD (aa49-61) common to CATHL 1-7 isoforms. A classification tree was fitted on the six biomarkers to predict Gram-positive bacteria within mastitis severity scores 1 or 2, revealing that compared to the rest of the samples, Gram-positive samples were associated with CRP < 9.5 μg/ml and LF ≥ 325 μg/ml and MAA < 16 μg/ml. Sensitivity of the tree model was 64%, the specificity was 91%, and the overall misclassification rate was 18%. The area under the ROC curve for this tree model was 0.836 (95% bootstrap confidence interval: 0.742; 0.917). TMT proteomic analysis revealed little difference between the groups in protein abundance when the three groups (Gram-positive, Gram-negative and no growth) were compared, however when each group was compared against the entirety of the remaining samples, 28 differentially abundant protein were identified including β-lactoglobulin and ribonuclease. Whilst further research is required to draw together and refine a suitable biomarker panel and diagnostic algorithm for differentiating Gram- positive/negative and NG CM, these results have highlighted a potential panel and diagnostic decision tree. Host-derived milk biomarkers offer significant potential to refine and reduce AMU and circumvent the many challenges associated with microbiological culture, both within the lab and on the farm, while providing the added benefit of reducing turnaround time from 14 to 16 h of microbiological culture to just 15 min with a lateral flow device (LFD).
摘要:
通过将临床乳腺炎(CM)的致病菌区分为革兰氏阳性或革兰氏阴性细菌,或确定该病例是否为培养阴性(无生长,NG)乳腺炎。采用用于生物标志物分析的免疫测定和串联质量标签(TMT)蛋白质组学研究来鉴定来自具有不同细菌引起的CM的奶牛的牛奶样品之间的差异。从苏格兰七个农场的被诊断为CM的母牛中收集了总共94个牛奶样本,按严重程度分类为轻度(评分1),中等(得分2),或严重(评分3)。牛触珠蛋白(Hp),牛奶淀粉样蛋白A(MAA),C反应蛋白(CRP),乳铁蛋白(LF),α-乳白蛋白(LA)和cathelicidin(CATHL)在来自CM的奶牛的牛奶中明显更高,不管文化结果如何,高于健康奶牛的牛奶(所有P值<0.001)。使用新颖的ELISA技术评估了牛奶cathelicidin(CATHL),该技术利用了针对CATHL1-7同工型常见的SSEANLYRLLELD(aa49-61)肽序列的抗体。在六种生物标志物上拟合分类树以预测乳腺炎严重程度评分1或2内的革兰氏阳性细菌,揭示与其他样品相比,革兰氏阳性样品与CRP<9.5μg/ml和LF≥325μg/ml和MAA<16μg/ml相关。树模型的灵敏度为64%,特异性为91%,总体误分类率为18%。该树模型的ROC曲线下面积为0.836(95%自举置信区间:0.742;0.917)。TMT蛋白质组学分析显示,当三组(革兰氏阳性,比较革兰氏阴性和无生长),然而,当每组与剩余样本的整体进行比较时,鉴定了28种差异丰富的蛋白质,包括β-乳球蛋白和核糖核酸酶。WhilefurtherresearchisrequiredtodrawtogetherandrefineaappropriateboriginpanelanddiagnosticalgorithmfordifferentiatingGram-positive/negativeandNGCM,这些结果突出了潜在的面板和诊断决策树.宿主来源的牛奶生物标志物具有改善和减少AMU并规避与微生物培养相关的许多挑战的巨大潜力。在实验室和农场里,同时提供了额外的好处,即使用侧流装置(LFD)将微生物培养的周转时间从14到16小时减少到仅15分钟。