Elshereef Rand, Budman Hector, Moresoli Christine, Legge Raymond L
Department of Chemical Engineering, University of Waterloo, Waterloo, ON, Canada, N2L 3G1.
Biotechnol Bioeng. 2008 Feb 15;99(3):567-77. doi: 10.1002/bit.21597.
A soft-sensor for monitoring solubility of native-like alpha-lactalbumin (alpha-LA) and beta-lactoglobulin (beta-LG) and their aggregation behavior following heat treatment of mixtures under different treatment conditions was developed using fluorescence spectroscopy data regressed with a multivariate Partial Least Squares (PLS) regression algorithm. PLS regression was used to correlate the concentrations of alpha-LA and beta-LG to the fluorescence spectra obtained for their mixtures. Data for the calibration and validation of the soft sensor was derived from fluorescence spectra. The process of thermal induced aggregation of beta-LG and alpha-LA protein in mixtures, which involves the disappearance of native-like proteins, was studied under various treatment conditions including different temperatures, pH, total initial protein concentration and proportions of alpha-LA and beta-LG. It was demonstrated that the multivariate regression models used could effectively deconvolute multi-wavelength fluorescence spectra collected under a variety of process conditions and provide a fairly accurate quantification of respective native-like proteins despite the significant overlapping between their emission profiles. It was also demonstrated that a PLS model can be used as a black-box prediction tool for estimating protein aggregation when combined with simple mass balances.
利用多元偏最小二乘法（PLS）回归算法对荧光光谱数据进行回归分析，开发了一种软传感器，用于监测天然α-乳白蛋白（α-LA）和β-乳球蛋白（β-LG）的溶解度及其在不同处理条件下对混合物进行热处理后的聚集行为。PLS回归用于将α-LA和β-LG的浓度与它们混合物的荧光光谱相关联。软传感器校准和验证的数据来自荧光光谱。在包括不同温度、pH值、总初始蛋白质浓度以及α-LA和β-LG比例在内的各种处理条件下，研究了混合物中β-LG和α-LA蛋白质的热诱导聚集过程，该过程涉及天然蛋白质的消失。结果表明，所使用的多元回归模型能够有效地对在各种工艺条件下收集的多波长荧光光谱进行反卷积，尽管它们的发射谱有明显重叠，但仍能对各自的天然蛋白质进行相当准确的定量分析。研究还表明，当与简单的质量平衡相结合时，PLS模型可以用作估计蛋白质聚集的黑箱预测工具。
