FOCAS Research Institute, Dublin Institute of Technology, Kevin Street, Dublin 8, Ireland.
Analyst. 2018 Dec 3;143(24):5987-5998. doi: 10.1039/c8an01701h.
This study explores the potential of Raman spectroscopy, coupled with multivariate regression techniques and a protein separation technique (ion exchange chromatography), to quantitatively monitor diagnostically relevant changes in high molecular weight proteins in liquid plasma. Measurement protocols to detect the imbalances in plasma proteins as an indicator of various diseases using Raman spectroscopy are optimised, such that strategic clinical applications for early stage disease diagnostics can be evaluated. In a simulated plasma protein mixture, concentrations of two proteins of identified diagnostic potential (albumin and fibrinogen) were systematically varied within physiologically relevant ranges. Scattering from the poorly soluble fibrinogen fraction is identified as a significant impediment to the accuracy of measurement of mixed proteins in solution, although careful consideration of pre-processing methods allows construction of an accurate multivariate regression prediction model for detecting subtle changes in the protein concentration. Furthermore, ion exchange chromatography is utilised to separate fibrinogen from the rest of the proteins and mild sonication is used to improve the dispersion and therefore quality of the prediction. The proposed approach can be expeditiously employed for early detection of pathological disorders associated with high or low plasma/serum proteins.
本研究探索了拉曼光谱结合多元回归技术和蛋白质分离技术(离子交换色谱),以定量监测液体血浆中高分子量蛋白质中与诊断相关的变化的潜力。优化了使用拉曼光谱检测血浆蛋白失衡作为各种疾病指标的测量方案,以便评估早期疾病诊断的战略临床应用。在模拟的血浆蛋白混合物中,两种具有明确诊断潜力的蛋白质(白蛋白和纤维蛋白原)的浓度在生理相关范围内进行系统变化。尽管仔细考虑预处理方法允许构建用于检测蛋白质浓度细微变化的准确多元回归预测模型,但从较差可溶性纤维蛋白原部分散射被鉴定为测量溶液中混合蛋白质准确性的重大障碍。此外,离子交换色谱用于将纤维蛋白原与其余蛋白质分离,并且温和的超声处理用于改善分散度,从而提高预测质量。该方法可快速用于检测与高或低血浆/血清蛋白相关的病理紊乱。