Comparing Cytoskeletal Alignment Analysis Methods for Biomimetic Tendon Scaffolds

Abstract

In healthy tendon, the extracellular matrix (ECM) is highly organized with elongated tenocytes, whereas pathologic tendons exhibit disorganized ECM and rounded tenocytes. Understanding cell–matrix interactions is essential for uncovering repair pathways that guide regenerative medicine. As such, nanofibrous scaffold models that mimic healthy aligned and unhealthy unaligned tendon can be leveraged to decouple cells and matrix to determine the isolated cellular response and isolated matrix response to load. In this study, we quantified tendon-derived cell (TDC) cytoskeletal morphology to characterize alignment as an indicator of cellular health. Multiple methods for quantifying cytoskeletal alignment exist; however, an optimal method is not established for TDCs on nanofibrous scaffolds. TDCs were seeded on tissue culture polystyrene (TCP), unaligned scaffolds, and aligned scaffolds (n=3/group/timepoint) and stained with Phalloidin (F-actin) and DAPI (nuclei) staining at 3, 4, 5, and 6 days after seeding. Image analysis was conducted via three methods: (1) ImageJ analysis (directionality analysis), (2) Cell Profiler morphology analysis, and (3) semi-automatic MATLAB analysis. Images exhibiting complete alignment and unalignment were generated via image editing to validate methods. We hypothesize that MATLAB-based analyses will yield the most accurate alignment measurements due to their use of weighted histograms to determine dominant fiber orientation. Identifying optimal analysis methods enables future work to quantify differences between health and disease within biomimetic systems.