Engineering Models of the Placental and Blood-Brain Barrier for Developmental Toxicity Testing

The toxicity of drugs in the context of pregnancy is typically unknown due to the exclusion of pregnant women from clinical trials. To address the need for microphysiological systems that can predict safety data during pregnancy, we developed models of the maternal-fetal interface and the developing...

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1. Verfasser: O'Connor, Blakely Bussie
Format: Dissertation
Sprache:eng
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Zusammenfassung:The toxicity of drugs in the context of pregnancy is typically unknown due to the exclusion of pregnant women from clinical trials. To address the need for microphysiological systems that can predict safety data during pregnancy, we developed models of the maternal-fetal interface and the developing blood-brain barrier. In the placenta model, we found that trophoblast fusion and hormone secretion increase on softer substrates that mimic the healthy placental microenvironment. Similarly, fusion on soft gelatin fibers decreased the static permeability of fluorescent molecules through trophoblasts cultured on these substrates. These results suggest that mechanical cues from the placental microenvironment play an important role in regulating trophoblast structure and function. In the blood-brain barrier model, we found that high tissue permeability correlated with nuclear elongation, loss of junction proteins, and increased actin stress fiber formation, indicative of increased contractility at the cell-cell junction. We further tested the applicability of this platform to predict modulations in brain endothelial permeability by exposing cell pairs to engineered nanomaterials, including gold, silver-silica, and cerium oxide nanoparticles, thereby uncovering new insights into the mechanism of nanoparticle-mediated barrier disruption. Overall, our work highlights the importance of mechanical signaling for cell-cell and cell-matrix interactions and informs efforts to model pregnancy for the purposes of predicting drug toxicity. Engineering and Applied Sciences - Engineering Sciences