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Curr Protoc ; 1(8): e229, 2021 Aug.
Article in English | MEDLINE | ID: mdl-34416100

ABSTRACT

Flow cytometry is a powerful method, widely used to identify cell types present in tissues, to describe their phenotypes, and to purify cells for functional analyses. As a single cell technique, flow cytometry relies on identifying and excluding cell doublets and aggregates present in samples in the initial gating steps. This identification is based on detection of events generating electrical pulses falling outside of linear variations of pulse height, width, and area in a singlet population with increasing cell sizes. In heterogeneous cell mixtures, however, with cell types varying extensively in size and granularity, exclusion of doublets has the risk of removing single cells that co-localize with doublets of another cell type. This is particularly the case when doublets of a smaller cell type overlap with large cells of a distinct, larger cell type. Here, we describe a gating method to reduce this risk. In this protocol, initial gating steps aim to segregate cells according to physical characteristics (such as size and granularity) and gene expression properties in order to obtain more homogeneous cell clusters. Doublet exclusion is then performed separately in each cluster, minimizing the risk of confusion between single cells and doublets. To illustrate this protocol, human blood monocytes are separated and analyzed. By implementing this protocol, we were able to reveal the existence of a population of large monocytes previously unrecognized using conventional gating strategies. In subsequent functional assays, we have shown that this novel population exhibits unique inflammatory responses, highlighting the need and pertinence of this approach to identify and characterize infrequent-yet functionally relevant-cell populations present in complex cell mixtures. © 2021 Wiley Periodicals LLC. Basic Protocol: Distinguishing single cells from doublets in heterogeneous cell mixtures by flow cytometry.


Subject(s)
Monocytes , Flow Cytometry , Humans , Phenotype
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