High content Image Analysis to study phenotypic heterogeneity in endothelial cell monolayers.
IF: 5.235


Endothelial cells (EC) are heterogeneous across and within tissues, reflecting distinct, specialised functions. EC heterogeneity has been proposed to underpin EC plasticity independently from vessel microenvironments. However, heterogeneity driven by contact-dependent or short-range cell-cell crosstalk cannot be evaluated with single cell transcriptomic approaches as spatial and contextual information is lost. Nonetheless, quantification of EC heterogeneity and understanding of its molecular drivers is key to developing novel therapeutics for cancer, cardiovascular diseases and for revascularisation in regenerative medicine. Here, we developed an EC profiling tool (ECPT) to examine individual cells within intact monolayers. We used ECPT to characterise different phenotypes in arterial, venous and microvascular EC populations. In line with other studies, we measured heterogeneity in terms of cell cycle, proliferation, and junction organisation. ECPT uncovered a previously under-appreciated single-cell heterogeneity in NOTCH activation. We correlated cell proliferation with different NOTCH activation states at the single cell and population levels. The positional and relational information extracted with our novel approach is key to elucidating the molecular mechanisms underpinning EC heterogeneity.


Endothelial cells
High Content Analysis
Machine learning


Chesnais, Francois
Hue, Jonas
Roy, Errin
Branco, Marco
Stokes, Ruby
Pellon, Aize
Le Caillec, Juliette
Elbahtety, Eyad
Battilocchi, Matteo
Danovi, Davide
Veschini, Lorenzo