Abstract LB042: An automated workflow for optical pooled screens with massively multiplexed phenotypic readouts on AVITI24
Abstract Optical pooled screening (OPS) is a powerful tool for linking image-based measurements of cellular phenotypes with in situ readouts of genetic perturbations, and has been used to identify the regulators of diverse biological processes, such as immune signaling, mitosis, antiviral response, and cell morphology. Although the conventional OPS approach requires fairly simple hardware - imaging is most commonly performed on a fluorescence microscope equipped with custom filters - adoption of OPS has been restricted to a small number of laboratories due to the sophisticated expertise required for data generation and computational analysis. Furthermore, screens have been limited to measuring < 20 phenotypic markers, making it difficult to capture mechanistic information across a wide range of biological pathways in the same experiment. Here, we establish a fully automated end-to-end workflow for OPS data generation and computational analysis on the AVITI24 sequencing platform. First, we demonstrate highly accurate in situ sequencing-by-synthesis of genetic perturbations with an avidity-based chemistry, and streamline the process of template generation. Next, we combine this workflow with a highly multiplexed AVITI24 phenotyping panel (up to 50 proteins and 350 mRNAs) and apply the combined protocol to perform a 500-gene CRISPR screen for regulators of complex cellular processes. This work lays the foundation for automated OPS data generation, supporting rich profiling of perturbation effects at unprecedented scale. Citation Format: Avtar Singh, Daniel Honigfort, Mariam Dawood, Connor Thompson, Amy Chuong, Orit Rozenblatt-Rosen, Mike Previte. An automated workflow for optical pooled screens with massively multiplexed phenotypic readouts on AVITI24 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_2):Abstract nr LB042.
Authors
- Michael J. R. Previte (ORCID: https://orcid.org/0009-0004-0533-6280)
- Amy S. Chuong
- Daniel J. Honigfort (ORCID: https://orcid.org/0000-0002-2634-5299)
- Mariam Dawood
- Avtar Singh (ORCID: https://orcid.org/0000-0001-5509-8330)
- Connor Thompson (ORCID: https://orcid.org/0000-0002-0083-9530)
- Orit Rozenblatt‐Rosen
Institutions
- Electronic BioSciences (United States) (US)
Publication Details
- Journal
- Cancer Research
- Published
- 2025-04-25
- DOI
- https://doi.org/10.1158/1538-7445.am2025-lb042
- Primary Topic
- Cell Image Analysis Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00