Abstract
INTRODUCTION: Liver sinusoidal endothelial cells (LSEC) are specialized endothelial cells with unique metabolic and barrier functions adapted to the needs of the liver sinusoid. LSECs are highly sensitive to their environment, and this fragile nature causes challenges in analyzing their phenotype under in vitro conditions. METHODS: In this work, we first differentiated LSEC-like cells (scLSECs) from two human pluripotent stem cell lines and characterized them by a panel of qPCR markers, immunohistochemistry, substrate oxidation for energy metabolism, scavenger function, and nitric oxide secretion. We then introduced holotomography, a technique that allows to recover quantitative and three-dimensional information about the refractive indexes of cell components, as a tool to image and track scLSEC in vitro in a minimally intrusive, label-free manner. RESULTS AND DISCUSSION: Holotomography and developed machine learning-based algorithm for image processing allowed us to describe and monitor changes in intracellular pore-like structures over time. Finally, we tested the possibility of inducing aspects of zone-specific LSEC phenotype and metabolism using culture-based treatments, which resulted in modest shifts in marker expression and metabolic activity. The presented strategy provides an advanced tool kit for investigating liver endothelial cells.