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  1. Article ; Online: High‐throughput, microscope‐based sorting to dissect cellular heterogeneity

    Nicholas Hasle / Anthony Cooke / Sanjay Srivatsan / Heather Huang / Jason J Stephany / Zachary Krieger / Dana Jackson / Weiliang Tang / Sriram Pendyala / Raymond J Monnat Jr. / Cole Trapnell / Emily M Hatch / Douglas M Fowler

    Molecular Systems Biology, Vol 16, Iss 6, Pp n/a-n/a (2020)

    2020  

    Abstract: Abstract Microscopy is a powerful tool for characterizing complex cellular phenotypes, but linking these phenotypes to genotype or RNA expression at scale remains challenging. Here, we present Visual Cell Sorting, a method that physically separates ... ...

    Abstract Abstract Microscopy is a powerful tool for characterizing complex cellular phenotypes, but linking these phenotypes to genotype or RNA expression at scale remains challenging. Here, we present Visual Cell Sorting, a method that physically separates hundreds of thousands of live cells based on their visual phenotype. Automated imaging and phenotypic analysis directs selective illumination of Dendra2, a photoconvertible fluorescent protein expressed in live cells; these photoactivated cells are then isolated using fluorescence‐activated cell sorting. First, we use Visual Cell Sorting to assess hundreds of nuclear localization sequence variants in a pooled format, identifying variants that improve nuclear localization and enabling annotation of nuclear localization sequences in thousands of human proteins. Second, we recover cells that retain normal nuclear morphologies after paclitaxel treatment, and then derive their single‐cell transcriptomes to identify pathways associated with paclitaxel resistance in cancers. Unlike alternative methods, Visual Cell Sorting depends on inexpensive reagents and commercially available hardware. As such, it can be readily deployed to uncover the relationships between visual cellular phenotypes and internal states, including genotypes and gene expression programs.
    Keywords genetic screening ; microscopy ; pharmacology ; subcellular localization ; transcriptomics ; Biology (General) ; QH301-705.5 ; Medicine (General) ; R5-920
    Subject code 612
    Language English
    Publishing date 2020-06-01T00:00:00Z
    Publisher Wiley
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Integrative oncogene-dependency mapping identifies RIT1 vulnerabilities and synergies in lung cancer

    Athea Vichas / Amanda K. Riley / Naomi T. Nkinsi / Shriya Kamlapurkar / Phoebe C. R. Parrish / April Lo / Fujiko Duke / Jennifer Chen / Iris Fung / Jacqueline Watson / Matthew Rees / Austin M. Gabel / James D. Thomas / Robert K. Bradley / John K. Lee / Emily M. Hatch / Marina K. Baine / Natasha Rekhtman / Marc Ladanyi /
    Federica Piccioni / Alice H. Berger

    Nature Communications, Vol 12, Iss 1, Pp 1-

    2021  Volume 19

    Abstract: RIT1 mutations are mutually exclusive with other lung cancer drivers and lack targeted therapies. Here the authors examine genetic dependencies of mutant RIT1 with genome-wide CRISPR screens, revealing synergy between RIT1 and YAP1, and increased ... ...

    Abstract RIT1 mutations are mutually exclusive with other lung cancer drivers and lack targeted therapies. Here the authors examine genetic dependencies of mutant RIT1 with genome-wide CRISPR screens, revealing synergy between RIT1 and YAP1, and increased sensitivity to Aurora kinase inhibitors.
    Keywords Science ; Q
    Language English
    Publishing date 2021-08-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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