Large-Scale Label-Free Quantitative Mapping of the Sputum Proteome
Large-Scale Label-Free Quantitative Mapping of the Sputum Proteome
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DOI：
10.1021/acs.jproteome.8b00018
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发表时间：
2018-06-01
影响因子：
4.4
通讯作者：
Skipp, Paul J.
中科院分区：
文献类型：
--
作者：
Burg, Dominic;Schofield, James P. R.;Skipp, Paul J.
分析诱导痰上皮液是一种微创的方法来研究上皮衬里液，从而提供对正常肺生物学和肺部疾病的病理生物学的洞察。我们在这里提出了一种新的蛋白质组学方法来进行痰分析，该方法是在U-BIOPRED(无偏生物标记物预测呼吸道疾病结果)国际项目中开发的。我们提出了实用和分析技术，以优化蛋白质组研究中稳健的生物标记物的检测。正常的痰蛋白质组是使用独立于数据的HDMSE获得的，应用于40名健康的不吸烟参与者，这为比较呼吸系统疾病中蛋白质表达的调节提供了基本的基线。“核心”痰蛋白质组(在40%的参与者中检测到的蛋白质)由284个蛋白质组成，而扩展蛋白质组(在3个参与者中检测到的蛋白质)包含1666个蛋白质。为了优化痰蛋白测定的准确性和一致性，并分析痰蛋白在健康人群中的分布，制定了质量控制程序。分析表明，HDMSE对蛋白质的定量受到几个因素的影响，所有参与者的样本中都有一些蛋白质被测量，同一患者的样品之间的测量差异很小。一些蛋白质的测量在重复分析之间变化很大，容易受到样品处理效果的影响，或者很难通过质谱学准确地定量。其他蛋白质表现出很高的个体间差异。我们还强调，健康个体的痰蛋白质组与痰中性粒细胞水平有关，而与性别或过敏反应无关。我们说明了设计和解释疾病生物标记物研究的重要性，考虑到这样的蛋白质群体和技术测量差异。
Analysis of induced sputum supematant is a minimally invasive approach to study the epithelial lining fluid and, thereby, provide insight into normal lung biology and the pathobiology of lung diseases. We present here a novel proteomics approach to sputum analysis developed within the U-BIOPRED (unbiased biomarkers predictive of respiratory disease outcomes) international project. We present practical and analytical techniques to optimize the detection of robust biomarkers in proteomic studies. The normal sputum proteome was derived using data-independent HDMSE applied to 40 healthy nonsmoking participants, which provides an essential baseline from which to compare modulation of protein expression in respiratory diseases. The "core" sputum proteome (proteins detected in >= 40% of participants) was composed of 284 proteins, and the extended proteome (proteins detected in >= 3 participants) contained 1666 proteins. Quality control procedures were developed to optimize the accuracy and consistency of measurement of sputum proteins and analyze the distribution of sputum proteins in the healthy population. The analysis showed that quantitation of proteins by HDMSE is influenced by several factors, with some proteins being measured in all participants' samples and with low measurement variance between samples from the same patient. The measurement of some proteins is highly variable between repeat analyses, susceptible to sample processing effects, or difficult to accurately quantify by mass spectrometry. Other proteins show high interindividual variance. We also highlight that the sputum proteome of healthy individuals is related to sputum neutrophil levels, but not gender or allergic sensitization. We illustrate the importance of design and interpretation of disease biomarker studies considering such protein population and technical measurement variance.