Chen Ping, Lu Yao, Harrington Peter B
Center for Intelligent Chemical Instrumentation, Department of Chemistry and Biochemistry, Clippinger Laboratories, Ohio University, Athens, Ohio 45701-2979, USA.
Anal Chem. 2008 Mar 1;80(5):1474-81. doi: 10.1021/ac7018798. Epub 2008 Jan 30.
Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) has proved useful for the characterization of bacteria and the detection of biomarkers. Key challenges for MALDI-MS measurements of bacteria are overcoming the relatively large variability in peak intensities. A soft tool, combining analysis of variance and principal component analysis (ANOVA-PCA) (Harrington, P. D.; Vieira, N. E.; Chen, P.; Espinoza, J.; Nien, J. K.; Romero, R.; Yergey, A. L. Chemom. Intell. Lab. Syst. 2006, 82, 283-293. Harrington, P. D.; Vieira, N. E.; Espinoza, J.; Nien, J. K.; Romero, R.; Yergey, A. L. Anal. Chim. Acta. 2005, 544, 118-127) was applied to investigate the effects of the experimental factors associated with MALDI-MS studies of microorganisms. The variance of the measurements was partitioned with ANOVA and the variance of target factors combined with the residual error was subjected to PCA to provide an easy to understand statistical test. The statistical significance of these factors can be visualized with 95% Hotelling T2 confidence intervals. ANOVA-PCA is useful to facilitate the detection of biomarkers in that it can remove the variance corresponding to other experimental factors from the measurements that might be mistaken for a biomarker. Four strains of Escherichia coli at four different growth ages were used for the study of reproducibility of MALDI-MS measurements. ANOVA-PCA was used to disclose potential biomarker proteins associated with different growth stages.
基质辅助激光解吸/电离质谱（MALDI-MS）已被证明可用于细菌表征和生物标志物检测。MALDI-MS测量细菌的关键挑战在于克服峰强度相对较大的变异性。一种结合方差分析和主成分分析的软工具（ANOVA-PCA）（哈林顿，P.D.；维埃拉，N.E.；陈，P.；埃斯皮诺萨，J.；尼恩，J.K.；罗梅罗，R.；耶尔盖，A.L.《化学计量学与智能实验室系统》2006年，82卷，283 - 293页。哈林顿，P.D.；维埃拉，N.E.；埃斯皮诺萨，J.；尼恩，J.K.；罗梅罗，R.；耶尔盖，A.L.《分析化学学报》2005年，544卷，118 - 127页）被用于研究与微生物MALDI-MS研究相关的实验因素的影响。测量的方差通过方差分析进行划分，目标因素的方差与残差误差相结合后进行主成分分析，以提供一个易于理解的统计检验。这些因素的统计显著性可以用95%的霍特林T2置信区间来可视化。ANOVA-PCA有助于促进生物标志物的检测，因为它可以从可能被误认为生物标志物的测量值中去除与其他实验因素对应的方差。使用四株处于四个不同生长阶段的大肠杆菌来研究MALDI-MS测量的重现性。ANOVA-PCA被用于揭示与不同生长阶段相关的潜在生物标志物蛋白。
