Quantifying proliferative and surface marker heterogeneity in colony‐founding connective tissue progenitors and their progeny using time‐lapse microscopy

Connective tissue progenitors (CTPs) are defined as the heterogeneous population of tissue‐resident stem and progenitor cells that are capable of proliferating and differentiating into connective tissue phenotypes. The prevalence and variation in clonal progeny of CTPs can be characterized using a colony formation assay. However, colony assays do not directly assess the characteristics of the colony‐founding CTP. We performed large, field‐of‐view, time‐lapse microscopy to manually track colonies back to the founding cells. Image processing and analysis was used to characterize the colonies and their founding cells. We found that the traditional colony‐forming unit (CFU) assay underestimates the number of founding cells as colonies can be formed by more than one founding cell. After 6 days in culture, colonies do not completely express CD73, CD90, and CD105. Heterogeneity in colony cells was characterized by two cell populations, proliferative and spread cells. Regression modelling of duration of lag phase and doubling time by cell marker suggests the presence of CD90 and CD105 in CTP subpopulations with different proliferative capabilities. From mathematical modelling of clonal colonies, we quantitatively characterized proliferation, migration, and cell marker expression rates to identify desirable clones for selection. Direct assessment of colony formation parameters led to more accurate assessment of CFU heterogeneity. Furthermore, these parameters can be used to quantify the diversity and hierarchy of stem and progenitor cells from a cell source or tissue for tissue engineering applications

Modeling and experimental methods to predict oxygen distribution in bone defects following cell transplantation

We have developed a mathematical model that allows simulation of oxygen distribution in a bone defect as a tool to explore the likely effects of local changes in cell concentration, defect size or geometry, local oxygen delivery with oxygen-generating biomaterials (OGBs), and changes in the rate of oxygen consumption by cells within a defect. Experimental data for the oxygen release rate from an OGB and the oxygen consumption rate of a transplanted cell population are incorporated into the model. With these data, model simulations allow prediction of spatiotemporal oxygen concentration within a given defect and the sensitivity of oxygen tension to changes in critical variables. This information may help to minimize the number of experiments in animal models that determine the optimal combinations of cells, scaffolds, and OGBs in the design of current and future bone regeneration strategies. Bone marrow-derived nucleated cell data suggest that oxygen consumption is dependent on oxygen concentration. OGB oxygen release is shown to be a time-dependent function that must be measured for accurate simulation. Simulations quantify the dependency of oxygen gradients in an avascular defect on cell concentration, cell oxygen consumption rate, OGB oxygen generation rate, and OGB geometry

Metabolic Dynamics in Skeletal Muscle during Acute Reduction in Blood Flow and Oxygen Supply to Mitochondria: In-Silico Studies Using a Multi-Scale, Top-Down Integrated Model

Control mechanisms of cellular metabolism and energetics in skeletal muscle that may become evident in response to physiological stresses such as reduction in blood flow and oxygen supply to mitochondria can be quantitatively understood using a multi-scale computational model. The analysis of dynamic responses from such a model can provide insights into mechanisms of metabolic regulation that may not be evident from experimental studies. For the purpose, a physiologically-based, multi-scale computational model of skeletal muscle cellular metabolism and energetics was developed to describe dynamic responses of key chemical species and reaction fluxes to muscle ischemia. The model, which incorporates key transport and metabolic processes and subcellular compartmentalization, is based on dynamic mass balances of 30 chemical species in both capillary blood and tissue cells (cytosol and mitochondria) domains. The reaction fluxes in cytosol and mitochondria are expressed in terms of a general phenomenological Michaelis-Menten equation involving the compartmentalized energy controller ratios ATP/ADP and NADH/NAD+. The unknown transport and reaction parameters in the model are estimated simultaneously by minimizing the differences between available in vivo experimental data on muscle ischemia and corresponding model outputs in coupled with the resting linear flux balance constraints using a robust, nonlinear, constrained-based, reduced gradient optimization algorithm. With the optimal parameter values, the model is able to simulate dynamic responses to reduced blood flow and oxygen supply to mitochondria associated with muscle ischemia of several key metabolite concentrations and metabolic fluxes in the subcellular cytosolic and mitochondrial compartments, some that can be measured and others that can not be measured with the current experimental techniques. The model can be applied to test complex hypotheses involving dynamic regulation of cellular metabolism and energetics in skeletal muscle during physiological stresses such as ischemia, hypoxia, and exercise

Technical Briefs Model Transformations to Evaluate Transient Thermal Responses at a Tissue Surface

For a spatially distributed model describing the transient temperature response of a thermistor-tissue system