Advanced Open-Source Experimental-Design Tools for Microplate-Based Assays with Acoustic Liquid Handling

Area of Science:

• Biotechnology
• Assay Development
• Bioinformatics

Background:

• Acoustic droplet ejection (ADE) facilitates nanoliter-scale liquid handling for microplate assays.
• Translating experimental designs into validated, instrument-ready instructions for ADE is a significant bottleneck.

Purpose of the Study:

• To present PickliPy, an open-source framework for converting spreadsheet-based assay designs into validated ADE picklists.
• To support various assay types, including combinatorial, dose-response, and time-course experiments.
• To enable high-throughput workflows like library reformatting and shortlisting.

Main Methods:

• Developed PickliPy, an open-source software framework with .Assay and .Screen modules.
• Applied the framework to generate ADE picklists for diverse biological assays.
• Integrated PickliPy with deep-learning image analysis for wash-free, live-cell screening.

Main Results:

• PickliPy successfully generated reproducible, assay-ready plates across different biological contexts.
• Demonstrated enhanced bioenergetic phenotyping of human skeletal muscle mitochondria and improved dose-response precision in pancreatic β-cells.
• Showcased a wash-free, live-cell screen of mitochondrial function and morphology with ADE and deep learning.

Conclusions:

• PickliPy standardizes and simplifies the design and scaling of complex ADE experiments.
• The framework facilitates reproducible assay execution from benchtop to screening campaigns.
• Agentic use of these tools enhances the ease and efficiency of ADE experimental design and execution.