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首页> 外文期刊>Journal of proteomics >Development of MS-based methods for identification and quantification of proteins altered during early pregnancy in dogs
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Development of MS-based methods for identification and quantification of proteins altered during early pregnancy in dogs

机译:犬早期妊娠早期鉴定和定量蛋白质鉴定和定量的发展

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Increased knowledge on serum protein profiles during early pregnancy in dogs would be valuable for several reasons, including animal welfare. Inflammatory changes during this period have been described. Today, mass spectrometry (MS) is a well-established technique to perform unbiased qualitative and quantitative studies of proteins in body fluids regardless of species. In the present study, a shotgun proteomic analysis based on nano-liquid chromatography-MS was performed to identify proteins of altered abundance during canine pregnancy, and, thereafter, a targeted parallel reaction monitoring (PRM)-method was developed and applied to absolutely quantify the concentrations of a selection of these proteins. Among the 32 proteins found altered between pregnant and non-pregnant dogs in the initial analysis, 12 were selected based on their changes in concentration and known biological importance, and these were analyzed using the PRM method. The PRM method showed good linearity, repeatability and sensitivity, and confirmed the higher concentration of Fibrinogen A, protein S alpha and C-reactive protein at early time points in pregnant bitches. In conclusion, the combination of both methods allowed the identification of several altered proteins, and the quantification and description of the concentration patterns for a selection of them during the early stage of dog pregnancy.
机译:由于诸多原因,包括动物福利,增加了血清蛋白曲线的知识将是有价值的。已经描述了此期间的炎症变化。如今,质谱(MS)是一种良好的技术,用于在不管物种的情况下对体液中蛋白质的蛋白质进行无偏见的定性和定量研究。在本研究中,进行基于纳米液相色谱-SMS的霰弹枪蛋白质组学分析,以鉴定犬妊娠期间的变化的蛋白质,此后,开发出靶向的并联反应监测(PRM) - 方法并施加绝对量化这些蛋白质选择的浓度。在初始分析中怀孕和非孕犬之间发生改变的32种蛋白质中,基于它们的浓度和已知的生物重要性的变化来选择12,并使用PRM方法分析这些。 PRM方法显示出良好的线性,可重复性和敏感性,并在怀孕母狗的早期点确认纤维蛋白原A,蛋白质α和C反应蛋白的浓度较高。总之,两种方法的组合允许鉴定几种改变的蛋白质,以及在狗妊娠早期选择它们的浓度模式的量化和描述。

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