Investigating the role of molecular coating in human corneal endothelial cell primary culture using artificial intelligence-driven image analysis

Abstract

Gauthier Travers and Louise Coulomb contributed equally to this work - Gauthier Travers et Louise Coulomb ont contribué à parts égales à ce travailInternational audienceThe monolayer of approximately 300,000 human corneal endothelial cells (hCECs) on the posteriorsurface of the cornea is essential to maintain transparency but is non-self-regenerative. Cornealblindness can currently only be treated by corneal transplantation, hindered by a global donorshortage, highlighting the need for developing tissue and/or cell therapy. The mass production ofthese advanced therapy medicinal products requires obtaining high-yield, high-quality endothelial cellcultures characterized by hexagonal shape, low size variability, and high endothelial cell density (ECD).Among the usual critical quality attributes which combine the expression of differentiation markers,ECD and cell morphological parameters, the latter are not optimally measured in vitro by conventionalimage analysis which poorly recognizes adherent cultured cells. We developed a high-performanceautomated segmentation using Cellpose algorithm and an original analysis method, improving thecalculation of classical morphological parameters (coefficient of variation of cell area and hexagonality)and introducing new parameters specific to hCECs culture in vitro. Considering the importance ofthe extracellular matrix in vivo, and the panel of molecules available for coating cell culture plastics,we used these new tools to perform a comprehensive comparison of 13 molecules (laminins andcollagens). We demonstrated their ability to discriminate subtle differences between cultures