Inspiring a convergent engineering approach to measure and model the tissue microenvironment.

Understanding the molecular and physical complexity of the tissue microenvironment (TiME) in the context of its spatiotemporal organization has remained an enduring challenge. Recent advances in engineering and data science are now promising the ability to study the structure, functions, and dynamics of the TiME in unprecedented detail; however, many advances still occur in silos that rarely integrate information to study the TiME in its full detail. This review provides an integrative overview of the engineering principles underlying chemical, optical, electrical, mechanical, and computational science to probe, sense, model, and fabricate the TiME. In individual sections, we first summarize the underlying principles, capabilities, and scope of emerging technologies, the breakthrough discoveries enabled by each technology and recent, promising innovations. We provide perspectives on the potential of these advances in answering critical questions about the TiME and its role in various disease and developmental processes. Finally, we present an integrative view that appreciates the major scientific and educational aspects in the study of the TiME.

Desmosomal Cadherin Tension Loss in Pemphigus Vulgaris Mediated by the Inhibition of Active RhoA at Cell-Cell Adhesions.

Binding of autoantibodies to keratinocyte surface antigens, primarily desmoglein 3 (Dsg3) of the desmosomal complex, leads to the dissociation of cell-cell adhesion in the blistering disorder pemphigus vulgaris (PV). After the initial disassembly of desmosomes, cell-cell adhesions actively remodel in association with the cytoskeleton and focal adhesions. Growing evidence highlights the role of adhesion mechanics and mechanotransduction at cell-cell adhesions in this remodeling process, as their active participation may direct autoimmune pathogenicity. However, a large part of the biophysical transformations after antibody binding remains underexplored. Specifically, it is unclear how tension in desmosomes and cell-cell adhesions changes in response to antibodies, and how the altered tensional states translate to cellular responses. Here, we showed a tension loss at Dsg3 using fluorescence resonance energy transfer (FRET)-based tension sensors, a tension loss at the entire cell-cell adhesion, and a potentially compensatory increase in junctional traction force at cell-extracellular matrix adhesions after PV antibody binding. Further, our data indicate that this tension loss is mediated by the inhibition of RhoA at cell-cell contacts, and the extent of RhoA inhibition may be crucial in determining the severity of pathogenicity among different PV antibodies. More importantly, this tension loss can be partially restored by altering actomyosin based cell contractility. Collectively, these findings provide previously unattainable details in our understanding of the mechanisms that govern cell-cell interactions under physiological and autoimmune conditions, which may open the window to entirely new therapeutics aimed at restoring physiological balance to tension dynamics that regulates the maintenance of cell-cell adhesion.

Quantitative Classification of 3D Collagen Fiber Organization From Volumetric Images.

Collagen fibers in biological tissues have a complex 3D organization containing rich information linked to tissue mechanical properties and are affected by mutations that lead to diseases. Quantitative assessment of this 3D collagen fiber organization could help to develop reliable biomechanical models and understand tissue structure-function relationships, which impact diagnosis and treatment of diseases or injuries. While there are advanced techniques for imaging collagen fibers, published methods for quantifying 3D collagen fiber organization have been sparse and give limited structural information which cannot distinguish a wide range of 3D organizations. In this article, we demonstrate an algorithm for quantitative classification of 3D collagen fiber organization. The algorithm first simulates five groups, or classifications, of fiber organization: unidirectional, crimped, disordered, two-fiber family, and helical. These five groups are widespread in natural tissues and are known to affect the tissue's mechanical properties. We use quantitative metrics based on features such as preferred 3D fiber orientation and spherical variance to differentiate each classification in a repeatable manner. We validate our algorithm by applying it to second-harmonic generation images of collagen fibers in tendon and cervix tissue that has been sectioned in specified orientations, and we find strong agreement between classification from simulated data and the physical fiber organization. Our approach provides insight for interpreting 3D fiber organization directly from volumetric images. This algorithm could be applied to other fiber-like structures that are not necessarily made of collagen.

An indentation-based approach to determine the elastic constants of soft anisotropic tissues.

Characterization of the mechanical properties of tissue can help to understand tissue mechanobiology, including disease diagnosis and progression. Indentation is increasingly used to measure the local mechanical properties of tissue, but it has not been fully adapted to capture anisotropic properties. This paper presents an indentation-based method to measure elastic constants of soft anisotropic tissues without additional mechanical tests. The approach uses measurement of the indentation modulus and the aspect ratio of the elliptical contact introduced by anisotropic mechanical properties of tissue to determine the elastic constants from finite element analysis. The imprinted area imparted by a fluorescent bead-coated spherical indenter showed the aspect ratio of the contact area, giving a generalized sense of the level of anisotropy, and instrumented indentation determined the indentation modulus. A parametric study using finite element simulation of the indentation tests established the relationship between the aspect ratio of contact and the non-dimensional ratios, Ex/Ey and Gxy/Ey; here, Ex and Ey are the Young's moduli (Ex > Ey) and Gxy is the shear modulus in the xy plane. For strongly anisotropic materials (Ex/Ey > 150), aspect ratio and indentation modulus are sufficient to determine Gxy and Ey. For weakly anisotropic materials, indentation modulus in the transverse direction, Ey, and the aspect ratio of contact in the anisotropic plane can be used to determine the elastic constants. The proposed approach improves the elastic characterization of soft, anisotropic biological materials from indentation and helps to elucidate the complex mechanical behavior of soft anisotropic tissues.