Document Type
Article
Rights
Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence
Disciplines
1.4 CHEMICAL SCIENCES
Abstract
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.
DOI
https://doi.org/10.1039/C8AN01701H
Recommended Citation
Parachalil, D., Brankin, B, McIntyre, J. & Byrne, H.J. (2018). Raman spectroscopic analysis of high molecular weight proteins in solution – considerations for sample analysis and data pre-processing. Analyst143, pp.5987-5998. doi:10.1039/C8AN01701H
Funder
DIT Fiosraigh scholarship. J. McIntyre was funded by Science Foundation Ireland, PI/11/08.
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Publication Details
Analyst, vol.143