Jonathan B. Estrada

Strain and rate-dependent neuronal injury in a 3D in vitro compression model of traumatic brain injury

In the United States over 1.7 million cases of traumatic brain injury are reported yearly, but predictive correlation of cellular injury to impact tissue strain is still lacking, particularly for neuronal injury resulting from compression. Given the prevalence of compressive deformations in most blunt head trauma, this information is critically important for the development of future mitigation and diagnosis strategies. Using a 3D in vitro neuronal compression model, we investigated the role of impact strain and strain rate on neuronal lifetime, viability, and pathomorphology. We find that strain magnitude and rate have profound, yet distinctively different effects on the injury pathology. While strain magnitude affects the time of neuronal death, strain rate influences the pathomorphology and extent of population injury. Cellular injury is not initiated through localized deformation of the cytoskeleton but rather driven by excess strain on the entire cell. Furthermore we find that, mechanoporation, one of the key pathological trigger mechanisms in stretch and shear neuronal injuries, was not observed under compression.

Mean deformation metrics for quantifying 3D cell–matrix interactions without requiring information about matrix material properties

Significance Investigations in mechanobiology rely on correlation of cellular processes with mechanical signals, such as matrix stiffness and cell tractions. Almost all cell traction and force quantification methodologies require knowledge of the underlying mechanical properties of the extracellular matrix to convert displacement data into corresponding traction data, which restricts the use of these techniques to systems in which the material properties are known. To overcome this hurdle, we present a new approach that does not require any knowledge of the underlying matrix properties but rather makes use of the intrinsically recorded kinematic displacement data. Through rigorous validation and an application to a neutrophil disease model, we show that such an approach produces both accurate and biologically significant information. Mechanobiology relates cellular processes to mechanical signals, such as determining the effect of variations in matrix stiffness with cell tractions. Cell traction recorded via traction force microscopy (TFM) commonly takes place on materials such as polyacrylamide- and polyethylene glycol-based gels. Such experiments remain limited in physiological relevance because cells natively migrate within complex tissue microenvironments that are spatially heterogeneous and hierarchical. Yet, TFM requires determination of the matrix constitutive law (stress–strain relationship), which is not always readily available. In addition, the currently achievable displacement resolution limits the accuracy of TFM for relatively small cells. To overcome these limitations, and increase the physiological relevance of in vitro experimental design, we present a new approach and a set of associated biomechanical signatures that are based purely on measurements of the matrixs displacements without requiring any knowledge of its constitutive laws. We show that our mean deformation metrics (MDM) approach can provide significant biophysical information without the need to explicitly determine cell tractions. In the process of demonstrating the use of our MDM approach, we succeeded in expanding the capability of our displacement measurement technique such that it can now measure the 3D deformations around relatively small cells (∼10 micrometers), such as neutrophils. Furthermore, we also report previously unseen deformation patterns generated by motile neutrophils in 3D collagen gels.

Differences in Morphology and Traction Generation of Cell Lines Representing Different Stages of Osteogenesis

Osteogenesis is the process by which mesenchymal stem cells differentiate to osteoblasts and form bone. The morphology and root mean squared (RMS) traction of four cell types representing different stages of osteogenesis were quantified. Undifferentiated D1, differentiated D1, MC3T3-E1, and MLO-A5 cell types were evaluated using both automated image analysis of cells stained for F-actin and by traction force microscopy (TFM). Undifferentiated mesenchymal stem cell lines were small, spindly, and exerted low traction, while differentiated osteoblasts were large, had multiple processes, and exerted higher traction. Size, shape, and traction all correlated with the differentiation stage. Thus, cell morphology evolved and RMS traction increased with differentiation. The results provide a foundation for further work with these cell lines to study the mechanobiology of bone formation.