# Aspects of zone-like identity and holotomographic tracking of human stem cell-derived liver sinusoidal endothelial cells

## TL;DR

Researchers developed a method to study liver sinusoidal endothelial cells derived from stem cells using a non-invasive imaging technique and machine learning.

## Contribution

The novel contribution is the use of holotomography and machine learning to track and analyze the structure and function of stem cell-derived liver sinusoidal endothelial cells.

## Key findings

- Stem cell-derived LSEC-like cells were successfully characterized using multiple methods including qPCR and holotomography.
- Holotomography enabled label-free, three-dimensional imaging of intracellular structures in scLSECs.
- Culture-based treatments induced minor changes in LSEC phenotype and metabolism.

## Abstract

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.

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.

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.