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

The introduction of full spectral technology in flow cytometry has facilitated access to an increasing number of markers to define cell subsets with higher precision. Cell sorting has a unique advantage to combine high throughput single cell analysis and recovery of rare live single cells for further downstream multi-omics analysis. Many studies have focused on advancing high dimensional single cell analysis; however, strategies to maximize cell sorting recovery in the context of deep immunophenotyping remain poorly defined. In this study, we evaluated sort performance in a six-way simultaneous cell sort setup. We modified a protocol using counting beads to assess absolute count in different sort decision criteria or modes. We demonstrate that the number of events collected can vary as much as 20% from the values indicated by the sort counter and is dependent on sort mode. Using the absolute count assay, we confirmed optimal conditions for six-way sorting of diverse human peripheral blood cell subsets defined by a 35-color panel and delineated pitfalls that can ultimately lead to suboptimal yield. Together, these findings provide novel insights into optimization of sort performance for advanced sorting and introduce a new approach for refining strategies for the simultaneous isolation of complex or rare cell subsets.