Platform-agnostic CellNet enables cross-study analysis of cell fate engineering protocols

Area of Science:

• Biotechnology
• Computational Biology
• Cell Engineering

Background:

• Standardized quality metrics are crucial for optimizing cell engineering protocols.
• Previous tools like CellNet assessed transcriptional fidelity but had limitations in comparing diverse data sources and protocols.
• A need exists for a standardized platform to compare new cell engineering protocols against established methods.

Purpose of the Study:

• To develop a platform-agnostic computational tool (PACNet) for standardized comparison of cell engineering protocols.
• To address limitations in comparing data from different sources and assessing new protocols against state-of-the-art methods.
• To provide an accessible tool for researchers to evaluate their cell engineering protocols.

Main Methods:

• Utilized the top-scoring pair transformation to build the platform-agnostic CellNet (PACNet) computational tool.
• Applied PACNet to analyze thousands of samples from over 100 studies covering seven distinct cell types.
• Performed in-depth analysis of hepatocyte and cardiomyocyte protocols to identify best practices and variations.

Main Results:

• PACNet successfully analyzed diverse cell engineering protocols across numerous studies.
• Identified best-performing protocols for hepatocyte and cardiomyocyte generation.
• Characterized intra-protocol and inter-lab variation, revealing common off-target signatures, including a neural signature in liver organoids.

Conclusions:

• PACNet offers a standardized, platform-agnostic approach to evaluate cell engineering protocols.
• The tool facilitates the identification of optimal protocols, variations, and potential off-target effects.
• PACNet is available as a web application and open-source code to aid the cell engineering research community.