Label-free quantification of soft tissue alignment by polarized Raman spectroscopy

The organization of proteins is an important determinant of functionality in soft tissues. However, such organization is difficult to monitor over time in soft tissue with complex compositions. Here, we establish a method to determine the alignment of proteins in soft tissues of varying composition by polarized Raman spectroscopy (PRS). Unlike most conventional microscopy methods, PRS leverages non-destructive, label-free sample preparation. PRS data from highly aligned muscle layers were utilized to derive a weighting function for aligned proteins via principal component analysis (PCA). This trained weighting function was used as a master loading function to calculate a principal component score (PC1 Score) as a function of polarized angle for tendon, dermis, hypodermis, and fabricated collagen gels. Since the PC1 Score calculated at arbitrary angles was insufficient to determine level of alignment, we developed an Amplitude Alignment Metric by fitting a sine function to PC1 Score with respect to polarized angle. We found that our PRS-based Amplitude Alignment Metric can be used as an indicator of level of protein alignment in soft tissues in a non-destructive manner with label-free preparation and has similar discriminatory capacity among isotropic and anisotropic samples compared to microscopy-based image processing method. This PRS method does not require a priori knowledge of sample orientation nor composition and appears insensitive to changes in protein composition among different tissues. The Amplitude Alignment Metric introduced here could enable convenient and adaptable evaluation of protein alignment in soft tissues of varying protein and cell composition. STATEMENT OF SIGNIFICANCE: Polarized Raman spectroscopy (PRS) has been used to characterize the of organization of soft tissues. However, most of the reported applications of PRS have been on collagen-rich tissues and reliant on intensities of collagen-related vibrations. This work describes a PRS method via a multivariate analysis to characterize alignment in soft tissues composed of varying proteins. Of note, the highly aligned muscle layer of mouse skin was used to train a master function then applied to other soft tissue samples, and the degree of anisotropy in the PRS response was evaluated to obtain the level of alignment in tissues. We have demonstrated that this method supports convenient and adaptable evaluation of protein alignment in soft tissues of varying protein and cell composition.