Optimizing Cell Sorting Performance: A Comparative Study Utilizing Spectral Flow Cytometry

Area of Science:

• Immunology
• Biotechnology
• Cell Biology

Background:

• Full spectral technology in flow cytometry enhances cell subset definition with more markers.
• Cell sorting enables high-throughput single-cell analysis and recovery of rare cells for multi-omics.
• Strategies for maximizing cell sorting recovery in deep immunophenotyping require further definition.

Purpose of the Study:

• To evaluate cell sorting performance in a six-way simultaneous sort setup.
• To assess the impact of different sort decision criteria on cell collection yield.
• To optimize conditions for isolating diverse human peripheral blood cell subsets.

Main Methods:

• Modified a protocol using counting beads to determine absolute cell counts.
• Assessed sort performance across various sort modes in a six-way cell sorter.
• Utilized a 35-color panel for deep immunophenotyping of human peripheral blood cells.

Main Results:

• The number of collected events can deviate up to 20% from the sort counter's indication, varying by sort mode.
• Identified optimal conditions for six-way sorting of multiple human peripheral blood cell subsets.
• Delineated specific pitfalls leading to suboptimal cell sorting yield.

Conclusions:

• Sort mode significantly influences cell collection efficiency, impacting downstream analysis.
• The developed absolute count assay provides a method to refine cell sorting strategies.
• Novel insights into optimizing sort performance enable improved isolation of complex and rare cell subsets.