How to Prevent yourself from Seeing Double

THE analysis of rare cells in flow cytometry data requires the acquisition of large data sets to visualize a sufficient number of events. Accurate identification of rare cells within a large number of events is hampered by the presence of artifacts and requires setting exclusionary gates to eliminate dying cells, cellular debris, autofluorescent cells, and cell doublets within analyzed populations (1). Doublet events are often observed in flow cytometry data, whether a sample is obtained from tissue or blood (2, 3). As cytometry data are further parsed to describe new rare populations of cells, the need for methods to properly discriminate contaminating doublets from true single cells has become an important aspect of data analysis. A newly described rare population of lymphocytes coexpressing both a T-cell receptor (TCR) and B-cell receptor (BCR), termed dual expressing (DE) cells (4) has been identified in the blood of patients with Type 1 diabetes (T1D). In this issue, Burel and colleagues (in this issue, page 1127– 1135) determine that commonly used analysis methods of nonimaging flow cytometric data do not efficiently resolve DE cells from a contaminating doublet population consisting of T-cell B-cell conjugates. The authors develop a gating strategy to limit T-and B-cell conjugate contamination from the analysis of DE cell populations through the use of imaging flow cytometry, which provides additional key parameters, such as bright-field area and bright-field aspect ratio. Utilizing this new strategy for doublet discrimination, the authors argue that a majority of DE cells, identified by traditional singlet gating strategies, are actually T-cell B-cell conjugates. Though they share a common stem cell progenitor, the development of the Tand B-cell lineages occur in spatially distinct locations, thymus, and bone marrow, respectively, via highly regulated and selective processes centered on the expression and signaling events that emanate from the Tor B-cell antigen receptors, TCR, and BCR (5, 6). Following development, naïve T cells circulate through the blood and secondary lymphoid organs surveilling an organism for the signs of foreign antigen (7). For major histocompatibility class II restricted CD4 T cells, this surveillance occurs through interactions with antigen presenting cells (APCs) such as dendritic cells, monocytes, B cells, and macrophages (8). These interactions between T cells and APCs can result in the formation of cell: cell conjugates mediated through cell surface adhesion molecules (9). It is therefore not surprising that T-cell conjugates have been observed in the peripheral blood of humans. The frequency of T-cell conjugates and the phenotype of the cells that comprise them often change in response to an organisms’ inflammatory state, such as following immunization or in cases of tuberculosis, dengue virus, and HIV infection (10, 11). These findings suggest that changes in T-cell conjugates are likely hallmarks of an active immune response. Two different types of gating strategies are commonly employed to exclude cell doublets from flow cytometry data. First, events can be excluded that deviate from the linear correlation between the forward scatter area (FSC-A) and the FSC height (FSC-H) parameters. Alternatively, events can be passed through two successive gates of FSC-A by FSC width (FSC-W) and side scatter area (SSC-A) by SSC width (SSC-W) utilizing the low pulse width signal indicative of single cells (Fig. 1) (3). While these methods are highly effective in eliminating the majority of contaminating doublets, not all T-cell conjugates are removed from the data by these criteria alone (3). To define cytometry analysis parameters that more efficiently discriminate T-cell conjugates from DE cells, Burel and colleagues leverage their knowledge of T-cell monocyte conjugates found in the peripheral blood of humans (10). Despite using a doublet discrimination gating strategy, they identify events expressing both T-cell and monocyte-specific markers CD3 and CD14. The authors find that mean fluorescent intensity (MFI) of both FCS-A and SSC-A increase between CD3 CD14 double-positive and single-positive populations. However, using high FSC-A and SSC-A intensity Department of Pathology, University of Massachusetts Medical School, Worcester, Massachusetts