An adaptable soft-mold embossing process for fabricating optically-accessible, microfeature-based culture systems and application toward liver stage antimalarial compound testing

Advanced cell culture methods for modeling organ-level structure have been demonstrated to replicate in vivo conditions more accurately than traditional in vitro cell culture. Given that the liver is particularly important to human health, several advanced culture methods have been developed to experiment with liver disease states, including infection with Plasmodium parasites, the causative agent of malaria. These models have demonstrated that intrahepatic parasites require functionally stable hepatocytes to thrive and robust characterization of the parasite populations' response to investigational therapies is dependent on high-content and high-resolution imaging (HC/RI). We previously reported abiotic confinement extends the functional longevity of primary hepatocytes in a microfluidic platform and set out to instill confinement in a microtiter plate platform while maintaining optical accessibility for HC/RI; with an end-goal of producing an improved P. vivax liver stage culture model. We developed a novel fabrication process in which a PDMS soft mold embosses hepatocyte-confining microfeatures into polystyrene, resulting in microfeature-based hepatocyte confinement (μHEP) slides and plates. Our process was optimized to form both microfeatures and culture wells in a single embossing step, resulting in a 100 μm-thick bottom ideal for HC/RI, and was found inexpensively amendable to microfeature design changes. Microfeatures improved intrahepatic parasite infection rates and μHEP systems were used to reconfirm the activity of reference antimalarials in phenotypic dose-response assays. RNAseq of hepatocytes in μHEP systems demonstrated microfeatures sustain hepatic differentiation and function, suggesting broader utility for preclinical hepatic assays; while our tailorable embossing process could be repurposed for developing additional organ models.