Measuring alignment of structural proteins in engineered tissue constructs using polarized Raman spectroscopy

Measures of structural protein alignment within biological and engineered tissues are needed for improved understanding of their mechanical behavior and functionality. We advance our method of measuring protein alignment using polarized Raman spectroscopy (PRS). It provides a promising alternative to conventional microscopy-based methods as it is non-destructive and allows analysis of extracellular components without additional protein labeling. Previously, we used a machine learning-based alignment metric to compare the extent of alignment between various soft tissues. This study demonstrates that PRS can be successfully used to provide a sensitive measure of alignment in engineered tissues despite the challenges of water-dominated spectra, which have limited prior efforts. A framework for capturing spatial variation of the amplitude and angle of bulk protein alignment was developed. Engineered tissue constructs were generated using collagen type-I solutions seeded with mouse myoblast (C2C12) cells. Tissue alignment was introduced as samples contracted over 12 days of culture. PRS measures of alignment within three selected regions captured a 32% change in extent of alignment and a 30° change in angle between center and corner regions. A computational model was used to bridge between discrete fiber measures of alignment determined with standard immunofluorescence microscopy and our PRS technique. The model applied contraction strains within a hyperelastic continuum to model cell contraction, and model-derived alignment measures showed good agreement between microscopy and PRS measures. Overall, our study provides additional analysis tools for quantifying alignment with PRS and showed the high potential of this PRS technique to non-invasively measure spatial variation within engineered tissues. Such measurement tools are needed to engineer regional alignments aimed at capturing specific mechanical and functional capabilities.