Evaluation of single‐cell sorting accuracy using antibody‐derived tag‐based <scp>qPCR</scp>
Single-cell sorting (index sorting) is a widely used method to isolate one cell at a time using fluorescence-activated cell sorting (FACS) for downstream applications such as single-cell sequencing or single-cell expansion. Despite widespread use, few assays are available to evaluate the proteomic features of the sorted single cell and further confirm the accuracy of single-cell sorting. With this caveat, we developed a novel assay to confirm the protein expression of sorted single cells by co-staining cells with the same marker using both antibody-derived tags (ADTs) and fluorescent antibodies. After single-cell sorting, we amplified the oligo of the ADT reagent as a surrogate signal for the protein expression using multiplex TaqMan™ qPCR on sorted cells. This assay is not only useful for confirming the identity of a sorted single cell but also an efficient method to profile proteomic features at the single-cell level. Finally, we applied this assay to characterize protein expression on whole cell lysate. Because of the sensitivity of the TaqMan™ qPCR, we can detect protein expression from a small number of cells. In summary, the ADT-based qPCR assay developed here can be utilized to confirm single-cell sorting accuracy and characterizing protein expression on both single cells and whole cell lysate.
Authors
- Aaron J. Tyznik (ORCID: https://orcid.org/0000-0002-9120-8530)
- Aaron Middlebrook (ORCID: https://orcid.org/0000-0003-3597-5636)
- Woodrow E. Lomas
- Vishnu C. Ramani (ORCID: https://orcid.org/0000-0002-2922-0774)
- Stephanie Widmann
- Louise M. D’Cruz (ORCID: https://orcid.org/0000-0003-0388-430X)
- Wei Fan (ORCID: https://orcid.org/0000-0001-5893-6045)
- Xiaoshan Shi (ORCID: https://orcid.org/0000-0002-2442-8429)
Institutions
- BD Biosciences (United States) (US)
Publication Details
- Journal
- Cytometry Part A
- Published
- 2024-08-12
- DOI
- https://doi.org/10.1002/cyto.a.24888
- Citations
- 1
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.23