Rešetar Maslov Dina, Thomas Funmilola Clara, Beletić Anđelo, Kuleš Josipa, Rubić Ivana, Benić Miroslav, Bačić Goran, Maćešić Nino, Eraghi Vida, Farkaš Vladimir, Lenac Roviš Tihana, Lisnić Berislav, Žubčić Damir, Potočnjak Dalibor, Mrljak Vladimir
Laboratory of Proteomics, Internal Diseases Clinic, Faculty of Veterinary Medicine, University of Zagreb, Heinzelova Street 55, 10000 Zagreb, Croatia.
Department of Chemistry and Biochemistry, Faculty of Veterinary Medicine, University of Zagreb, Heinzelova Street 55, 10000 Zagreb, Croatia.
Animals (Basel). 2023 May 31;13(11):1829. doi: 10.3390/ani13111829.
Bovine mastitis is the most frequent disease on dairy farms, which leads to a decrease in the health welfare of the animals and great economic losses. This study was aimed at determining the quantitative variations in the milk proteome caused by natural infection by and species in order to gain further understanding of any discrepancies in pathophysiology and host immune responses, independent of the mastitis level. After identification of (N = 51) and (N = 67) spp., tandem mass tag (TMT)-labeled quantitative proteomic and liquid chromatography-mass spectrometry (LC-MS/MS) techniques on a modular Ultimate 3000 RSLCnano system coupled to a Q Exactive Plus was applied on aseptically sampled milk from Holstein cows. Proteome Discoverer was used for protein identification and quantitation through the SEQUEST algorithm. Statistical analysis employing R was used to identify differentially abundant proteins between the groups. Protein classes, functions and functional-association networks were determined using the PANTHER and STRING tools and pathway over-representation using the REACTOME. In total, 156 master bovine proteins were identified (two unique peptides, < 0.05 and FDR < 0.001), and 20 proteins showed significantly discrepant abundance between the genera ( < 0.05 and FDR < 0.5). The most discriminatory proteins per group were odorant-binding protein (higher in staphylococci) and fibrinogen beta chain protein (higher in streptococci). The receiver operating characteristic (ROC) curve showed that protein kinase C-binding protein NELL2, thrombospondin-1, and complement factor I have diagnostic potential for differentiating staphylococci and streptococci intramammary infection and inflammation. Improved understanding of the host response mechanisms and recognition of potential biomarkers of specific-pathogen mastitis, which may aid prompt diagnosis for control implementation, are potential benefits of this study.
奶牛乳腺炎是奶牛场最常见的疾病，会导致动物健康福利下降和巨大的经济损失。本研究旨在确定由葡萄球菌属和链球菌属自然感染引起的乳蛋白质组的定量变化，以便在不考虑乳腺炎程度的情况下，进一步了解病理生理学和宿主免疫反应中的任何差异。在鉴定出葡萄球菌属（N = 51）和链球菌属（N = 67）后，将串联质谱标签（TMT）标记的定量蛋白质组学和液相色谱 - 质谱联用（LC-MS/MS）技术应用于模块化的Ultimate 3000 RSLCnano系统与Q Exactive Plus联用，对来自荷斯坦奶牛的无菌采集乳样进行分析。使用Proteome Discoverer通过SEQUEST算法进行蛋白质鉴定和定量。采用R语言进行统计分析，以识别组间差异丰富的蛋白质。使用PANTHER和STRING工具确定蛋白质类别、功能和功能关联网络，并使用REACTOME确定通路过度表达情况。总共鉴定出156种主要牛蛋白质（两个独特肽段，P < 0.05且FDR < 0.001），20种蛋白质在属间显示出显著的丰度差异（P < 0.05且FDR < 0.5）。每组中最具鉴别性的蛋白质是气味结合蛋白（葡萄球菌中含量较高）和纤维蛋白原β链蛋白（链球菌中含量较高）。受试者工作特征（ROC）曲线表明，蛋白激酶C结合蛋白NELL2、血小板反应蛋白-1和补体因子I对区分葡萄球菌和链球菌引起的乳房内感染及炎症具有诊断潜力。更好地理解宿主反应机制以及识别特定病原体乳腺炎的潜在生物标志物，可能有助于及时诊断以实施控制措施，这是本研究的潜在益处。
