In vivo lipid saturation maps of microscopic nematodes (Caenorhabditis elegans) have been produced using our novel Spectral Interferometric Polarisation Coherent anti-Stokes Raman Scattering (SIP-CARS) imaging technique. This technique employs simple passive polarisation optics and a balanced homodyne detection scheme to exploit symmetries in the CARS polarisation response resulting in the complete cancellation of the non-resonant background (NRB) and real component of the CARS signal (with no prior or post assumptions as regards to their form). The remaining imaginary component of the CARS response is linear with analyte concentration and directly relatable to the spontaneous Raman spectrum . Furthermore, the resonant CARS signal is interferometrically amplified by the non-resonant response, a necessity for rapid imaging at biologically relevant powers .
This technique permits acquisition of a broad NRB-free spectrum, in excess of 1800cm-1, in a single exposure at each pixel. This allows simultaneous determination of lipid droplet saturation, from the fingerprint region, and lipid order, from the C-H stretch region from which maps can be readily constructed. Additionally exploiting the dispersive nature of our signal collection two-photon autofluorescence can be isolated and images subsequently produced.
We have successfully applied this technique to identify differences in lipid saturation distributions in selective C. elegans mutants and demonstrated that the technique is sufficiently sensitive to detect the effects of lipid metabolism altering drugs on wild type C. elegans.
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Bradley Littleton, Thomas Kavanagh, Yu Nie, Vincenzo Abbate, Peter Hylands, Stephen Sturzenbaum, and David Richards, "In vivo lipid saturation study of C. elegans using quantitative broadband coherent anti-Stokes Raman imaging
(Conference Presentation)," Proc. SPIE 9712, Multiphoton Microscopy in the Biomedical Sciences XVI, 97120A (Presented at SPIE BiOS: February 14, 2016; Published: 27 April 2016); https://doi.org/10.1117/12.2211132.4848767259001.
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