Literature DB >> 32546035

Phenotypic Profiling of Reference Chemicals across Biologically Diverse Cell Types Using the Cell Painting Assay.

Clinton Willis1,2, Johanna Nyffeler1,3, Joshua Harrill1.   

Abstract

Cell Painting is a high-throughput phenotypic profiling assay that uses fluorescent cytochemistry to visualize a variety of organelles and high-content imaging to derive a large number of morphological features at the single-cell level. Most Cell Painting studies have used the U-2 OS cell line for chemical or functional genomics screening. The Cell Painting assay can be used with many other human-derived cell types, given that the assay is based on the use of fluoroprobes that label organelles that are present in most (if not all) human cells. Questions remain, however, regarding the optimization steps required and overall ease of deployment of the Cell Painting assay to novel cell types. Here, we used the Cell Painting assay to characterize the phenotypic effects of 14 phenotypic reference chemicals in concentration-response screening mode across six biologically diverse human-derived cell lines (U-2 OS, MCF7, HepG2, A549, HTB-9 and ARPE-19). All cell lines were labeled using the same cytochemistry protocol, and the same set of phenotypic features was calculated. We found it necessary to optimize image acquisition settings and cell segmentation parameters for each cell type, but did not adjust the cytochemistry protocol. For some reference chemicals, similar subsets of phenotypic features corresponding to a particular organelle were associated with the highest-effect magnitudes in each affected cell type. Overall, for certain chemicals, the Cell Painting assay yielded qualitatively similar biological activity profiles among a group of diverse, morphologically distinct human-derived cell lines without the requirement for cell type-specific optimization of cytochemistry protocols.

Entities:  

Keywords:  cell-based assays; high-content screening; image analysis; microscopy; toxicology

Mesh:

Year:  2020        PMID: 32546035     DOI: 10.1177/2472555220928004

Source DB:  PubMed          Journal:  SLAS Discov        ISSN: 2472-5552            Impact factor:   3.341


  7 in total

Review 1.  Particle Safety Assessment in Additive Manufacturing: From Exposure Risks to Advanced Toxicology Testing.

Authors:  Andi Alijagic; Magnus Engwall; Eva Särndahl; Helen Karlsson; Alexander Hedbrant; Lena Andersson; Patrik Karlsson; Magnus Dalemo; Nikolai Scherbak; Kim Färnlund; Maria Larsson; Alexander Persson
Journal:  Front Toxicol       Date:  2022-04-25

Review 2.  Nuisance compounds in cellular assays.

Authors:  Jayme L Dahlin; Douglas S Auld; Ina Rothenaigner; Steve Haney; Jonathan Z Sexton; J Willem M Nissink; Jarrod Walsh; Jonathan A Lee; John M Strelow; Francis S Willard; Lori Ferrins; Jonathan B Baell; Michael A Walters; Bruce K Hua; Kamyar Hadian; Bridget K Wagner
Journal:  Cell Chem Biol       Date:  2021-02-15       Impact factor: 8.116

3.  Comparison of Approaches for Determining Bioactivity Hits from High-Dimensional Profiling Data.

Authors:  Johanna Nyffeler; Derik E Haggard; Clinton Willis; R Woodrow Setzer; Richard Judson; Katie Paul-Friedman; Logan J Everett; Joshua A Harrill
Journal:  SLAS Discov       Date:  2020-08-29       Impact factor: 3.341

4.  Optimization of Human Neural Progenitor Cells for an Imaging-Based High-Throughput Phenotypic Profiling Assay for Developmental Neurotoxicity Screening.

Authors:  Megan Culbreth; Johanna Nyffeler; Clinton Willis; Joshua A Harrill
Journal:  Front Toxicol       Date:  2022-02-16

5.  Integrating cell morphology with gene expression and chemical structure to aid mitochondrial toxicity detection.

Authors:  Srijit Seal; Jordi Carreras-Puigvert; Maria-Anna Trapotsi; Hongbin Yang; Ola Spjuth; Andreas Bender
Journal:  Commun Biol       Date:  2022-08-23

6.  Label-free prediction of cell painting from brightfield images.

Authors:  Riku Turkki; Yinhai Wang; Jan Oscar Cross-Zamirski; Elizabeth Mouchet; Guy Williams; Carola-Bibiane Schönlieb
Journal:  Sci Rep       Date:  2022-06-15       Impact factor: 4.996

7.  A phenomics approach for antiviral drug discovery.

Authors:  Jonne Rietdijk; Marianna Tampere; Aleksandra Pettke; Polina Georgiev; Maris Lapins; Ulrika Warpman-Berglund; Ola Spjuth; Marjo-Riitta Puumalainen; Jordi Carreras-Puigvert
Journal:  BMC Biol       Date:  2021-08-02       Impact factor: 7.431

  7 in total

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