Mapping Cell Viability Quantitatively and Independently From Cell Density in 3D Gels Noninvasively.

OBJECTIVE: In biomanufacturing there is a need for quantitative methods to map cell viability and density inside 3D bioreactors to assess health and proliferation over time. Recently, noninvasive MRI readouts of cell density have been achieved. However, the ratio of live to dead cells was not varied. Herein we present an approach for measuring the viability of cells embedded in a hydrogel independently from cell density to map cell number and health. METHODS: Independent quantification of cell viability and density was achieved by calibrating the 1H magnetization transfer- (MT) and diffusion-weighted NMR signals to samples of known cell density and viability using a multivariate approach. Maps of cell viability and density were generated by weighting NMR images by these parameters post-calibration. RESULTS: Using this method, the limits of detection (LODs) of total cell density and viable cell density were found to be 3.88 ×108 cells · mL -1· Hz -1/2 and 2.36 ×109 viable cells · mL -1· Hz -1/2 respectively. CONCLUSION: This mapping technique provides a noninvasive means of visualizing cell viability and number density within optically opaque bioreactors. SIGNIFICANCE: We anticipate that such nondestructive readouts will provide valuable feedback for monitoring and controlling cell populations in bioreactors.

Noninvasive Quantification of Cell Density in Three-Dimensional Gels by MRI.

OBJECTIVE: For tissue engineering, there is a need for quantitative methods to map cell density inside three-dimensional (3-D) bioreactors to assess tissue growth over time. The current cell mapping methods in 2-D cultures are based on optical microscopy. However, optical methods fail in 3-D due to increased opacity of the tissue. We present an approach for measuring the density of cells embedded in a hydrogel to generate quantitative maps of cell density in a living, 3-D tissue culture sample. METHODS: Quantification of cell density was obtained by calibrating the 1H T2, magnetization transfer (MT) and diffusion-weighted nuclear magnetic resonance (NMR) signals to samples of known cell density. Maps of cell density were generated by weighting NMR images by these parameters post-calibration. RESULTS: The highest sensitivity weighting arose from MT experiments, which yielded a limit of detection (LOD) of [Formula: see text] cells/mL/ √{Hz} in a 400 MHz (9.4 T) magnet. CONCLUSION: This mapping technique provides a noninvasive means of visualizing cell growth within optically opaque bioreactors. SIGNIFICANCE: We anticipate that such readouts of tissue culture growth will provide valuable feedback for controlled cell growth in bioreactors.

NOTCH1 is a mechanosensor in adult arteries.

Endothelial cells transduce mechanical forces from blood flow into intracellular signals required for vascular homeostasis. Here we show that endothelial NOTCH1 is responsive to shear stress, and is necessary for the maintenance of junctional integrity, cell elongation, and suppression of proliferation, phenotypes induced by laminar shear stress. NOTCH1 receptor localizes downstream of flow and canonical NOTCH signaling scales with the magnitude of fluid shear stress. Reduction of NOTCH1 destabilizes cellular junctions and triggers endothelial proliferation. NOTCH1 suppression results in changes in expression of genes involved in the regulation of intracellular calcium and proliferation, and preventing the increase of calcium signaling rescues the cell-cell junctional defects. Furthermore, loss of Notch1 in adult endothelium increases hypercholesterolemia-induced atherosclerosis in the descending aorta. We propose that NOTCH1 is atheroprotective and acts as a mechanosensor in adult arteries, where it integrates responses to laminar shear stress and regulates junctional integrity through modulation of calcium signaling.

4-D Flow Control in Porous Scaffolds: Toward a Next Generation of Bioreactors.

Tissue engineering (TE) approaches that involve seeding cells into predetermined tissue scaffolds ignore the complex environment where the material properties are spatially inhomogeneous and evolve over time. We present a new approach for controlling mechanical forces inside bioreactors, which enables spatiotemporal control of flow fields in real time. Our adaptive approach offers the flexibility of dialing-in arbitrary shear stress distributions and adjusting flow field patterns in a scaffold over time in response to cell growth without needing to alter scaffold structure. This is achieved with a multi-inlet bioreactor and a control algorithm with learning capabilities to dynamically solve the inverse problem of computing the inlet pressure distribution required over the multiple inlets to obtain a target flow field. The new method constitutes a new platform for studies of cellular responses to mechanical forces in complex environments and opens potentially transformative possibilities for TE.