A Scalable Pipeline for High-Throughput Flow Cytometry. (August 2018)

• Record Type: Journal Article
• Authors: Wilson, Aaron C.; Moutsatsos, Ioannis K.; Yu, Gary; Pineda, Javier J.; Feng, Yan; Auld, Douglas S.
• Other Names: Ding Mei guest-editor.; Edwards Bruce S. guest-editor.
• Is Part Of: SLAS discovery. Volume 23:Number 7(2018)
• Page Start: 708
• Page End: 718
• Publication Date: 2018-08
• Subjects: flow cytometry -- high throughput -- phenotypic assay; Drugs -- Analysis -- Periodicals; Drugs -- Testing -- Periodicals; Biomolecules -- Analysis -- Periodicals; Biomolecules -- Analysis; Drugs -- Analysis; Drugs -- Testing; Drug Evaluation, Preclinical; Molecular Biology -- methods; Periodicals; Periodicals; 615.1
• DOI: 10.1177/2472555218774770
• Languages: English
• ISSNs: 2472-5552

Abstract

Flow cytometry (FC) provides high-content data for a variety of applications, including phenotypic analysis of cell surface and intracellular markers, characterization of cell supernatant or lysates, and gene expression analysis. Historically, sample preparation, acquisition, and analysis have presented as a bottleneck for running such types of assays at scale. This article will outline the solutions that have been implemented at Novartis which have allowed high-throughput FC to be successfully conducted and analyzed for a variety of cell-based assays. While these experiments were generally conducted to measure phenotypic responses from a well-characterized and information-rich small molecular probe library known as the Mechanism-of-Action (MoA) Box, they are broadly applicable to any type of test sample. The article focuses on application of automated methods for FC sample preparation in 384-well assay plates. It also highlights a pipeline for analyzing large volumes of FC data, covering a visualization approach that facilitates review of screen-level data by dynamically embedding FlowJo (FJ) workspace images for each sample into a Spotfire file, directly linking them to the metric being observed. Finally, an application of these methods to a screen for MHC-I expression upregulators is discussed.