Biodesix Inc., Boulder, CO 80301, USA.
Molecules. 2022 Feb 1;27(3):997. doi: 10.3390/molecules27030997.
Accurate and precise measurement of the relative protein content of blood-based samples using mass spectrometry is challenging due to the large number of circulating proteins and the dynamic range of their abundances. Traditional spectral processing methods often struggle with accurately detecting overlapping peaks that are observed in these samples. In this work, we develop a novel spectral processing algorithm that effectively detects over 1650 peaks with over 3.5 orders of magnitude in intensity in the 3 to 30 kD m/z range. The algorithm utilizes a convolution of the peak shape to enhance peak detection, and accurate peak fitting to provide highly reproducible relative abundance estimates for both isolated peaks and overlapping peaks. We demonstrate a substantial increase in the reproducibility of the measurements of relative protein abundance when comparing this processing method to a traditional processing method for sample sets run on multiple matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) instruments. By utilizing protein set enrichment analysis, we find a sizable increase in the number of features associated with biological processes compared to previously reported results. The new processing method could be very beneficial when developing high-performance molecular diagnostic tests in disease indications.
由于血液样本中存在大量的循环蛋白和其丰度的动态范围,因此使用质谱法准确、精确地测量相对蛋白质含量具有挑战性。传统的光谱处理方法在准确检测这些样本中观察到的重叠峰方面常常存在困难。在这项工作中,我们开发了一种新颖的光谱处理算法,能够有效地检测到 3 至 30 kD m/z 范围内强度超过 3.5 个数量级的超过 1650 个峰。该算法利用峰形卷积来增强峰检测,并进行准确的峰拟合,为孤立峰和重叠峰提供高度可重复的相对丰度估计。我们通过比较在多个基质辅助激光解吸/电离飞行时间(MALDI-TOF)仪器上运行的样本集的传统处理方法,证明了该处理方法在测量相对蛋白质丰度的重现性方面有了显著提高。通过利用蛋白质集富集分析,与之前报道的结果相比,我们发现与生物学过程相关的特征数量有了相当大的增加。在开发疾病相关的高性能分子诊断测试时,这种新的处理方法可能非常有益。