Development of Novel Technologies for Direct Cellular Patterning for the Establishment of Well Controlled Microenvironments to Facilitate Studies on Cellular Signaling, Sensing, and Other Diffusion-Based Phenomena

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Issue Date
2016-05-07
Authors
Hynes, William
Publisher
Keywords
bioprinting , cellular signaling , syntrophic relationships , COMETS
Abstract
This work focuses on the utilization of novel bioprinting technologies for the investigation of cellular signaling, sensing, and other diffusion-based phenomena with spatiotemporal dependencies. Two different printing techniques were developed for the purpose of fabricating controlled microenvironments comprised of cells, nutrients, hydrogels, and soluble signaling molecules in a repeatable fashion. The first application explored was the development of a novel, bioprinted, cell-based biosensor as a nondestructive method for the monitoring of the cellular redox environment. Mammalian cells were engineered to express a redox sensitive protein and were patterned and immobilized within a photopolymerizing hydrogel matrix, resulting in biocompatible, three-dimensional microenvironments which supported cell growth and facilitated small molecule sensing. Exposure of the printed, redox sensitive cells to oxidative and reductive compounds and monitoring via confocal microscopy demonstrated proper and reversible functioning of the living biosensor. Bioprinting was also used to generate complex, micro-scale, multi-species populations of bacteria in order to evaluate the effects of distance and various forms of competition on syntrophic relationships. An artificial, syntrophic bacterial consortium was printed within controlled microenvironments confined by geometry and nutrient availability. The growth of the printed strains was monitored, analyzed, and compared to the predictions of an experimental, computational bacterial growth model known as COMETS. Results indicated that the general trends exhibited in vitro by most of the examined micro-scale interactions can be predicted in silico, and that the effects of microbial interactions on the micro-scale can differ considerably than those observed at the macro-scale.
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