Sassi Alexander P, Andel Frank, Bitter Hans-Marcus L, Brown Michael P S, Chapman Robert G, Espiritu Jeraldine, Greenquist Alfred C, Guyon Isabelle, Horchi-Alegre Mariana, Stults Kathy L, Wainright Ann, Heller Jonathan C, Stults John T
Predicant Biosciences, Inc., South San Francisco, CA 94080, USA.
Electrophoresis. 2005 Apr;26(7-8):1500-12. doi: 10.1002/elps.200410127.
A capillary electrophoresis-mass spectrometry (CE-MS) method has been developed to perform routine, automated analysis of low-molecular-weight peptides in human serum. The method incorporates transient isotachophoresis for in-line preconcentration and a sheathless electrospray interface. To evaluate the performance of the method and demonstrate the utility of the approach, an experiment was designed in which peptides were added to sera from individuals at each of two different concentrations, artificially creating two groups of samples. The CE-MS data from the serum samples were divided into separate training and test sets. A pattern-recognition/feature-selection algorithm based on support vector machines was used to select the mass-to-charge (m/z) values from the training set data that distinguished the two groups of samples from each other. The added peptides were identified correctly as the distinguishing features, and pattern recognition based on these peptides was used to assign each sample in the independent test set to its respective group. A twofold difference in peptide concentration could be detected with statistical significance (p-value < 0.0001). The accuracy of the assignment was 95%, demonstrating the utility of this technique for the discovery of patterns of biomarkers in serum.
已开发出一种毛细管电泳-质谱联用（CE-MS）方法，用于对人血清中的低分子量肽进行常规自动化分析。该方法采用瞬态等速电泳进行在线预浓缩，并使用无鞘电喷雾接口。为评估该方法的性能并证明该方法的实用性，设计了一项实验，将肽以两种不同浓度添加到个体血清中，人工创建两组样本。血清样本的CE-MS数据被分为单独的训练集和测试集。使用基于支持向量机的模式识别/特征选择算法从训练集数据中选择区分两组样本的质荷比（m/z）值。添加的肽被正确识别为区分特征，并基于这些肽的模式识别用于将独立测试集中的每个样本分配到其各自的组。肽浓度两倍的差异可被检测到且具有统计学意义（p值<0.0001）。分配的准确率为95%，证明了该技术在发现血清中生物标志物模式方面的实用性。
