Issue 2, 2024

Spectral fingerprinting of cellular lipid droplets using stimulated Raman scattering microscopy and chemometric analysis

Abstract

Hyperspectral stimulated Raman scattering (SRS) microscopy is a powerful method for direct visualisation and compositional analysis of cellular lipid droplets. Here we report the application of spectral phasor analysis as a convenient method for the segmentation of lipid droplets using the hyperspectral SRS spectrum in the high wavenumber and fingerprint region of the spectrum. Spectral phasor analysis was shown to discriminate six fatty acids based on vibrational spectroscopic features in solution. The methodology was then applied to studying fatty acid metabolism and storage in a mammalian cancer cell model and during drug-induced steatosis in a hepatocellular carcinoma cell model. The accumulation of fatty acids into cellular lipid droplets was shown to vary as a function of the degree of unsaturation, whilst in a model of drug-induced steatosis, the detection of increased saturated fatty acid esters was observed. Taking advantage of the fingerprint and high wavenumber regions of the SRS spectrum has yielded a greater insight into lipid droplet composition in a cellular context. This approach will find application in the label-free profiling of intracellular lipids in complex disease models.

Graphical abstract: Spectral fingerprinting of cellular lipid droplets using stimulated Raman scattering microscopy and chemometric analysis

Supplementary files

Article information

Article type
Paper
Submitted
03 Oct 2023
Accepted
06 Dec 2023
First published
07 Dec 2023
This article is Open Access
Creative Commons BY license

Analyst, 2024,149, 553-562

Spectral fingerprinting of cellular lipid droplets using stimulated Raman scattering microscopy and chemometric analysis

A. Rensonnet, W. J. Tipping, C. Malherbe, K. Faulds, G. Eppe and D. Graham, Analyst, 2024, 149, 553 DOI: 10.1039/D3AN01684F

This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. You can use material from this article in other publications without requesting further permissions from the RSC, provided that the correct acknowledgement is given.

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