Abstract
Raman spectroscopy has been used extensively for the analysis of biological samples in vitro, ex vivo and in vivo. While important progress has been made towards using this analytical technique in clinical applications, there is a limit to how much chemically specific information can be extracted from a spectrum of a biological sample, which consists of multiple overlapping peaks from a large number of species in any particular sample. In an attempt to elucidate more specific information regarding individual biochemical species, as opposed to very broad assignments by species class, we propose a bottom-up approach beginning with a detailed analysis of pure biochemical components. Here, we demonstrate a simple ratiometric approach applied to fatty acids, a subsection of the lipid class, to allow the key structural features, in particular degree of saturation and chain length, to be predicted. This is proposed as a starting point for allowing more chemically and species-specific information to be elucidated from the highly multiplexed spectrum of multiple overlapping signals found in a real biological sample. The power of simple ratiometric analysis is also demonstrated by comparing the prediction of degree of unsaturation in food oil samples using ratiometric and multivariate analysis techniques which could be used for food oil authentication.
Highlights
This article has been edited by the Royal Society of Chemistry, including the commissioning, peer review process and editorial aspects up to the point of acceptance. †Present address: Department of Chemistry, Princeton University, Princeton, NJ 08544, USA
This study has demonstrated powerful evidence for the use of ratiometric analysis for dissecting complicated spectral information in order to extract key features of biological samples
While multivariate analysis using partial least squares regression (PLSR) was able to predict degree of unsaturation reasonably well in multiplex food oil samples and could be a useful tool in certain cases, predictions using the ratiometric approach were much closer to the theoretical degree of unsaturation
Summary
While important progress has been made towards using this analytical technique in clinical applications, there is a limit to how much chemically specific information can be extracted from a spectrum of a biological sample, which consists of multiple overlapping peaks from a large number of species in any particular sample. We demonstrate a simple ratiometric approach applied to fatty acids, a subsection of the lipid class, to allow the key structural features, in particular degree of saturation and chain length, to be predicted. This is proposed as a starting point for allowing more chemically and species-specific information to be elucidated from the highly multiplexed spectrum of multiple overlapping signals found in a real biological sample.
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