Development of Automated Microscopy-Assisted High-Content Multiparametric Assays for Cell Cycle Staging and Foci...

The investigation of cell cycle stage-dependent processes in a population of cells is often performed using flow cytometry. While this approach is high-throughput, it is relatively low in resolution and unable to measure phenotypic changes or processes occurring in subcellular compartments. We integrated automated microscopy with newly developed informatics workflow that enabled the quantitation of multiple fluorescent markers from specific subnuclear regions throughout a population of cells. Telomeres protect chromosome termini and prevent cellular aging. Cancer cells lengthen telomeres by synthesizing new TTAGGG repeats by the enzyme telomerase, while others activate recombination-dependent alternative lengthening of telomeres (ALT). A key feature of the ALT pathway is the specific clustering of promyelocytic leukemia (PML) nuclear bodies at telomeres. These ALT-associated PML bodies (APBs) common in tumors of mesenchymal origin have gained in diagnostic use in the past decade. Here we applied recent improvements in automated microscopy and developed novel informatics workflows for quantitation of multiple fluorescent markers from specific subnuclear regions at the single cell level. Key to this workflow are customized machine learning algorithms within HCS Studio™ Cell Analysis which automatically identify and segment cells into defined regions of interest based on fluorescent markers, measure marker intensities and compute marker colocalizations in specific segmented regions. These multiparametric cellular assays assess cell cycle dynamics as well as the interactome of APBs, are amenable to adherent cells and histological sections, and are adaptable for use with additional markers. In the future we anticipate exploiting these algorithms for a wide range of research questions related to telomere biology with potential to facilitate clinical development of ALT detection assays to benefit patients with these often-poor prognosis tumors. © 2020 International Society for Advancement of Cytometry.