Automated image analysis of nuclear shape: what can we learn from a prematurely aged cell?

The premature aging disorder, Hutchinson-Gilford progeria syndrome (HGPS), is caused by mutant lamin A, which affects the nuclear scaffolding. The phenotypic hallmark of HGPS is nuclear blebbing. Interestingly, similar nuclear blebbing has also been observed in aged cells from healthy individuals. Recent work has shown that treatment with rapamycin, an inhibitor of the mTOR pathway, reduced nuclear blebbing in HGPS fibroblasts. However, the extent of blebbing varies considerably within each cell population, which makes manual blind counting challenging and subjective. Here, we show a novel, automated and high throughput nuclear shape analysis that quantitatively measures curvature, area, perimeter, eccentricity and additional metrics of nuclear morphology for large populations of cells. We examined HGPS fibroblast cells treated with rapamycin and RAD001 (an analog to rapamycin). Our analysis shows that treatment with RAD001 and rapamycin reduces nuclear blebbing, consistent with blind counting controls. In addition, we find that rapamycin treatment reduces the area of the nucleus, but leaves the eccentricity unchanged. Our nuclear shape analysis provides an unbiased, multidimensional "fingerprint" for a population of cells, which can be used to quantify treatment efficacy and analyze cellular aging.