Label-free discrimination of muscle proteins based on non-resonant background signature of multiplex-coherent anti-Stokes Raman scattering imaging

Abstract Label-free discrimination between protein families within the same biological environment remains a significant challenge for bioimaging. We present a novel method that addresses this issue by exploiting the non-resonant background signal in multiplex-coherent anti-Stokes Raman scattering (M-CARS) spectroscopy, a signal typically regarded as noise. Our approach leverages the contrast between resonant and non-resonant contributions in hyperspectral M-CARS data to enable the distinct detection and spatial mapping of individual protein families. As a proof of concept, we apply this method to distinguish actin and myosin filaments in muscle tissue. Myosin is first localized through its endogenous second harmonic generation (SHG) signal. Pixel-wise analysis of the ratio between resonant and non-resonant components then reveals the location of actin filaments, in agreement with SHG expectations. This work highlights the untapped potential of the silent spectral region, which carries valuable discriminative information. By leveraging the intrinsic differences in nonlinear optical responses between proteins, this strategy enables qualitative label-free imaging and enhances the analytical potential of M-CARS spectroscopy for multifactorial biological studies.