Functional assessment of automatically sorted pancreatic islets using large particle flow cytometry

Area of Science:

• Endocrinology and Metabolism
• Transplantation Biology
• Biotechnology and Bioengineering

Background:

• Human islet preparation size impacts functional potency, survival, and transplantation outcomes.
• Early post-transplantation islet hypoxia, due to diffusion-limited oxygen supply, contributes to graft dysfunction.
• Smaller islets are presumed to have better early survival and function due to shorter diffusion distances.

Purpose of the Study:

• To evaluate Complex Object Parametric Analysis and Sorting (COPAS) for automated human islet sorting.
• To assess COPAS accuracy, sensitivity, and impact on islet viability and function.

Main Methods:

• COPAS device validated using polystyrene beads of known diameters.
• Automated sorting of isolated human islets based on time of flight.
• Viability and function analysis of sorted islets compared to handpicked controls.

Main Results:

• COPAS demonstrated accurate and sensitive automated sorting of human islets.
• Automated sorting did not negatively impact islet integrity or viability.
• COPAS performance was comparable to handpicked islet controls.

Conclusions:

• COPAS is a suitable tool for automated, size-specific analysis of pancreatic islets.
• This technology can be integrated into high-throughput screening platforms for pancreatic islets.
• Automated size-based islet sorting holds promise for improving islet transplantation outcomes.