S10 funds will be used to create a novel integrated instrumentation system enabling high-throughput phenotypic screens (HPS) across a diverse array of whole-organism (e.g., worms, flies, mosquitos, fish) and three-dimensional (3D) cell culture models (e.g., stem cell-derived ?organoids?). Modern ?omics technologies and drug discovery methods create massive amounts of data and numerous compound ?hits?, respectively. This creates bottlenecks in testing the large numbers of predictions made due to current limitations in experimental capacities, particularly for assays performed in vivo. The HPS platform addresses this issue by supporting true high-throughput screening (HTS) rates for in vivo assays?i.e., tens of thousands of specimens processed per day. This, in turn, enables large-scale genetic screens designed to test big data predictions across entire gene networks as well as high-throughput chemical screens that place living disease models at the start, rather than the end, of the drug discovery process to increase the pace of new drug development. The HPS platform combines two complementary phenotypic screening methods designed to accommodate living model systems: ARQiv (Automated Reporter Quantification in vivo), a plate reader-based approach enabling true HTS rates in vivo, and VAST (Vertebrate Automated Screening Technology), an automated microfluidics-based system facilitating rapid high-content imaging (HCI). We will update the capabilities of these systems by updating them to support: 1) Faster throughput, 2) Longitudinal screens, and 3) High-resolution 3D imaging. For the latter, we will couple cutting-edge Light Sheet Fluorescence Microscopy (LSFM, aka SPIM) to VAST. ARQiv and VAST systems will be integrated into a unified screening platform via a custom-designed robotics workstation that automates all aspects of in vivo screening processes: 1) Compound dispensing and dilution schemes, 2) Sorting and dispensing model systems into microtiter plates, 3) Plate handling, and 4) Microfluidics-based sample handling (e.g., sample orientation for imaging). The proposed platform thereby provides both high-throughput screening capacities (via ARQiv) and high-content imaging (via VAST/LSFM) for in vivo assay paradigms. Moreover, real-time data processing will facilitate a hierarchical phenotypic screening strategy where VAST-based imaging will be limited to ARQiv-flagged samples of interest (i.e., ?hits?); enabling maximal throughput without sacrificing enriched data content and addressing a key bottleneck in applying HCI methods to more complex 3D model systems. The platform will anchor a HPS Core facility supporting cutting-edge in vivo discovery capabilities and unique training opportunities for researchers at JHU and nearby academic institutions; expanding HTS-paced phenotypic screening to multiple model systems and reporter-based assay paradigms, and facilitating collaborative cross- species initiatives designed to reveal evolutionarily conserved genetic and chemical signaling pathways at the heart of complex biological processes and debilitating diseases.

Public Health Relevance

S10 funds will be used establish a novel High-throughput Phenotypic Screening Platform (HPS) which will enable large-scale chemical and genetic screens in whole organisms (e.g., worms, flies, fish) and complex 3D cell culture models (e.g., organoids). The HPS platform addresses a problematic mismatch in scale between ?big data? bioinformatics and experimental capacities by providing a means to perform high-throughput phenotypic screens for testing ?omics-based predictions across systems-level gene networks directly in living 3D models. Similarly, this system allows living disease models to be placed at the start, rather than the end, of the drug discovery pipeline; a strategy that can circumvent the high rate of failure attending late stage tests in animal models and the clinic, decreasing the cost and increasing the pace of drug development.

Agency
National Institute of Health (NIH)
Institute
Office of The Director, National Institutes of Health (OD)
Type
Biomedical Research Support Shared Instrumentation Grants (S10)
Project #
1S10OD026909-01A1
Application #
9939116
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Wang, Guanghu
Project Start
2020-08-15
Project End
2021-08-14
Budget Start
2020-08-15
Budget End
2021-08-14
Support Year
1
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Johns Hopkins University
Department
Ophthalmology
Type
Schools of Medicine
DUNS #
001910777
City
Baltimore
State
MD
Country
United States
Zip Code
21205