Department of Chemistry, University of Wisconsin, Madison, WI, USA.
J Proteome Res. 2011 Jun 3;10(6):2687-702. doi: 10.1021/pr2000495. Epub 2011 Apr 25.
Mass spectrometry (MS) -- based proteomic approaches have evolved as powerful tools for the discovery of biomarkers. However, the identification of potential protein biomarkers from biofluid samples is challenging because of the limited dynamic range of detection. Currently there is a lack of sensitive and reliable premortem diagnostic test for prion diseases. Here, we describe the use of a combined MS-based approach for biomarker discovery in prion diseases from mouse plasma samples. To overcome the limited dynamic range of detection and sample complexity of plasma samples, we used lectin affinity chromatography and multidimensional separations to enrich and isolate glycoproteins at low abundance. Relative quantitation of a panel of proteins was obtained by a combination of isotopic labeling and validated by spectral counting. Overall 708 proteins were identified, 53 of which showed more than 2-fold increase in concentration whereas 58 exhibited more than 2-fold decrease. A few of the potential candidate markers were previously associated with prion or other neurodegenerative diseases.
质谱（MS）-基于蛋白质组学的方法已发展成为发现生物标志物的强大工具。然而，由于检测的动态范围有限，从生物流体样本中鉴定潜在的蛋白质生物标志物具有挑战性。目前，尚无针对朊病毒病的敏感可靠的生前诊断测试。在这里，我们描述了使用基于 MS 的组合方法从鼠血浆样本中发现朊病毒病的生物标志物。为了克服检测的动态范围有限和血浆样本的复杂性，我们使用凝集素亲和层析和多维分离来富集和分离低丰度的糖蛋白。通过同位素标记和光谱计数验证相结合，对一组蛋白质进行相对定量。总共鉴定了 708 种蛋白质，其中 53 种蛋白质的浓度增加了两倍以上，而 58 种蛋白质的浓度降低了两倍以上。一些潜在的候选标志物以前与朊病毒或其他神经退行性疾病有关。
