An open-source FACS automation system for high-throughput cell biology

Area of Science:

• Cell biology
• Biotechnology
• Bioengineering

Background:

• Gene editing advances enable large-scale cell engineering.
• Current cell manufacturing and handling methods require acceleration.
• Fluorescence-Activated Cell Sorting (FACS) is crucial for selecting engineered cells but is labor-intensive and lacks automation.

Purpose of the Study:

• To develop an integrated hardware and software platform for automating Fluorescence-Activated Cell Sorting (FACS).
• To enable high-throughput, walkaway cell selection for engineered cells.
• To provide a universal solution for automating instruments lacking an Application Program Interface (API).

Main Methods:

• Developed an integrated software and hardware platform around a commercial FACS instrument.
• Automated sample handling, instrument control, and algorithmic generation of sorting gates.
• Designed an open-source system with build documentation for broader accessibility.

Main Results:

• Achieved "walkaway" functionality for FACS sample processing.
• Reduced hands-on labor by 93% through automation.
• Eliminated operator errors and standardized gating conditions, improving consistency.

Conclusions:

• The automated FACS platform significantly accelerates the selection of engineered cells.
• The developed strategy for instrument automation is applicable to other instruments lacking an API.
• The open-source nature of the platform fosters a collaborative ecosystem for high-throughput cell biology tools.