Selected reaction monitoring mass spectrometry of mastitis milk reveals pathogen-specific regulation of bovine host response proteins
Selected reaction monitoring mass spectrometry of mastitis milk reveals pathogen-specific regulation of bovine host response proteins
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DOI：
10.3168/jds.2017-14312
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发表时间：
2018-07-01
影响因子：
3.5
通讯作者：
Bendixen, Emoke
中科院分区：
文献类型：
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作者：
Kusebauch, Ulrike;Hernandez-Castellano, Lorenzo E.;Bendixen, Emoke
乳房炎是对牛健康的一大挑战。奶牛乳房炎敏感标志物的检测是非常有必要的。合适的生物标志物应该在牛奶中是可测量的，并且应该在早期阶段报告病原体的特定变化，以支持更早的诊断和更有效的治疗。然而，识别牛奶中的敏感生物标志物仍然是一个挑战，部分原因是它们在牛奶中的浓度相对较低。在本研究中，我们使用了选择性反应监测(SRN)质谱学方法，首次实现了对牛奶中13种宿主反应蛋白的绝对定量。用来自革兰氏阴性菌(来自大肠杆菌的脂多糖；LPS)或革兰氏阳性菌(来自金黄色葡萄球菌的肽聚糖；PGN)的细胞壁成分，在活体攻击后的54小时内对这些蛋白质进行了测量。虽然我们的数据清楚地表明，所有被攻击的动物在内毒素和PGN攻击后都有一致的先天免疫反应蛋白上调，但数据也清楚地表明，与PGN攻击相比，内毒素攻击释放的速度更快，宿主反应更强烈。可以区分革兰氏阴性和革兰氏阳性细菌的候选生物标志物包括α-2巨球蛋白、α-1抗胰蛋白酶、结合珠蛋白、血清淀粉样蛋白A3、分化簇14、钙粒蛋白B、组织蛋白酶C、Vanin-1、Galectin 1、Galectin 3和IL-8。我们的方法可以支持对患有自然乳房炎的大型动物队列的进一步研究，以验证这些建议的生物标记物在乳制品生产中的相关性。
Mastitis is a major challenge to bovine health. The detection of sensitive markers for mastitis in dairy herds is of great demand. Suitable biomarkers should be measurable in milk and should report pathogen-specific changes at an early stage to support earlier diagnosis and more efficient treatment. However, the identification of sensitive biomarkers in milk has remained a challenge, in part due to their relatively low concentration in milk. In the present study, we used a selected reaction monitoring (SRN) mass spectrometry approach, which allowed the absolute quantitation of 13 host response proteins in milk for the first time. These proteins were measured over a 54-h period upon an in vivo challenge with cell wall components from either gram-negative (lipopolysaccharide from Escherichia coli; LPS) or gram-positive bacteria (peptidoglycan from Staphylococcus aureus; PGN). Whereas our data clearly demonstrate that all challenged animals have consistent upregulation of innate immune response proteins after both LPS and PGN challenge, the data also reveal clearly that LPS challenge unleashes faster and shows a more intense host response compared with PGN challenge. Biomarker candidates that may distinguish between gram-negative and gram-positive bacteria include alpha-2 macroglobulin, alpha-1 antitrypsin, haptoglobin, serum amyloid A3, cluster of differentiation 14, calgranulin B, cathepsin C, vanin-1, galectin 1, galectin 3, and IL-8. Our approach can support further studies of large cohorts of animals with natural occurring mastitis, to validate the relevance of these suggested biomarkers in dairy production.