Spectral fingerprinting of cellular lipid droplets using stimulated Raman scattering microscopy and chemometric analysis
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 hyperspec...
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description | 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.
Hyperspectral stimulated Raman scattering (SRS) microscopy coupled to spectral phasor analysis is a powerful method for the detection of fatty acids in solution and in cellular lipid droplets. |
doi_str_mv | 10.1039/d3an01684f |
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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.
Hyperspectral stimulated Raman scattering (SRS) microscopy coupled to spectral phasor analysis is a powerful method for the detection of fatty acids in solution and in cellular lipid droplets.</abstract><cop>England</cop><pub>Royal Society of Chemistry</pub><pmid>38088863</pmid><doi>10.1039/d3an01684f</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0003-4273-2691</orcidid><orcidid>https://orcid.org/0000-0002-5567-7399</orcidid><orcidid>https://orcid.org/0000-0002-6079-2105</orcidid><orcidid>https://orcid.org/0000-0001-5146-6706</orcidid><orcidid>https://orcid.org/0000-0002-4821-3115</orcidid><orcidid>https://orcid.org/0009-0005-2047-2683</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Analytical Chemistry Biochemistry Cancer Chemistry Chimie Droplets Electrochemistry Environmental Chemistry Esters Fatty acids Fingerprinting Fingerprints Lipids Microscopy Phasors Physical, chemical, mathematical & earth Sciences Physique, chimie, mathématiques & sciences de la terre Raman spectra Spectroscopy Wavelengths |
title | Spectral fingerprinting of cellular lipid droplets using stimulated Raman scattering microscopy and chemometric analysis |
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