Despite the major role of the matrix (the insoluble environment around cells) in physiology and pathology, there are very few and limited methods that can quantify the surface chemistry of a 3D matrix such as a biomaterial or tissue ECM. This study describes a novel optical-based methodology that can quantify the surface chemistry (density of adhesion ligands for particular cell adhesion receptors) of a matrix in situ. The methodology utilizes fluorescent analogs (markers) of the receptor of interest and a series of binding assays, where the amount of bound markers on the matrix is quantified via spectral multi-photon imaging. The study provides preliminary results for the quantification of the ligands for the two major collagen-binding integrins (α1β1, α2β1) in porous collagen scaffolds that have been shown to be able to induce maximum regeneration in transected peripheral nerves. The developed methodology opens the way for quantitative descriptions of the insoluble microenvironment of cells in physiology and pathology, and for integrating the matrix in quantitative models of cell signaling. α
Cells sense and respond to chemical stimuli on their environment via signal transduction pathways, complex networks of proteins whose interactions transmit chemical information. This work describes an implementation of image informatics, imaging-based methodologies for studying signal transduction networks. The methodology developed focuses on studying signal transduction networks in cells that interact with 3D matrices. It utilizes shRNA-based knock down of network components, 3D high-content imaging of cells inside the matrix by spectral multi-photon microscopy, and single-cell quantification using features that describe both cell morphology and cell-matrix adhesion pattern. The methodology is applied in a pilot study of TGFβ signaling via the SMAD pathway in fibroblasts cultured inside porous collagen-GAG scaffolds, biomaterials similar to the ones used clinically to induce skin regeneration. Preliminary results suggest that knocking down all rSMAD components affects fibroblast response to TGFβ1 and TGFβ3 isoforms in different ways, and suggest a potential role for SMAD1 and SMAD5 in regulating TGFβ isoform response. These preliminary results need to be verified with proteomic results that can provide solid evidence about the particular role of individual components of the SMAD pathway.