Isolating individual cells with complex phenotypes – which is key to understanding how these cells function, including to inform disease – is a technological challenge. Now, overcoming this hurdle, researchers present a high-speed cell sorter that uses fluorescence imaging to enable genome-scale studies of complex phenotypes.
The technique could greatly expand the phenotypic space accessible to cell sorting applications and pooled genetic screening. Single cells show a diversity of phenotypes, ranging from variable gene expression levels, dynamic protein localization, or differing cellular morphology. These phenotypes determine cell function and changes are often associated with disease.
Isolating cells with phenotypes of interest is therefore key to understanding the underlying genetic and molecular processes, and how they determine cell function. However, current approaches to cell sorting and characterization are limited spatially and lack subcellular resolution.
Here, Daniel Schraivogel and colleagues present a fully integrated high-speed image-enabled cell sorter ("ICS"), which records multicolor fluorescence images and sorts cells based on them at speeds upwards of 15,000 events per second. Schraivogel et al. demonstrated ICS's ability to rapidly isolate and quantify cells with complex cellular phenotypes, including cells with differently localized proteins and cells in different mitotic stages.
They combined ICS with CRISPR-pooled screens to identify regulators of a nuclear factor pathway, enabling the completion of genome-wide image-based screens in roughly 9 hours of run time.
ICS provides a fundamentally new capability for probing deep into the molecular mechanisms underlying cell physiology and protein localization," write the authors.
American Association for the Advancement of Science (AAAS)
Schraivogel, D., et al. (2022) High-speed fluorescence image–enabled cell sorting. Science. doi.org/10.1126/science.abj3013.
Posted in: Cell Biology | Genomics
Tags: Cell, Cell Sorting, CRISPR, Fluorescence, Fluorescence Imaging, Gene, Gene Expression, Genetic, Genome, Imaging, Morphology, Physiology, Protein
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