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Cellular immune responses elicited by vaccination are complex and require polychromatic analysis to accurately characterize the phenotype and function of rare, responding cells. Technical challenges and a lack of instrument standardization between research sites have limited the application of polychromatic cytometry in multicenter clinical trials. Two previously developed six-color T cell subset immunophenotyping reagent panels deliberately designed to accommodate three additional low frequency functional measurements were compared for their reproducibility of staining across three different flow cytometers. We repeatedly measured similar T cell subset frequencies between the two reagent panels and across the three different cytometers. Spectral overlap reduced sensitivity in two of the three open measurement channels (PE [IL-2] and APC [IFNγ]) for one reagent combination, particularly in subsets with low cytokine expression. There was no significant interassay variation for measurements across instrument platforms. Careful panel design will identify reagent combinations that minimize spectral spillover into channels reserved for cytokine measurement and comparable results can be achieved using different cytometers, however, it is important to establish standardized quality control procedures for each instrument to minimize variation between cytometers. © 2008 International Society for Advancement of Cytometry.

Background Viruses alter cellular gene transcription and protein binding at many steps critical for cell cycle regulation to optimize the milieu for productive infection. Reasoning that virus–host cell interactions would result in perturbations of cell cycle kinetics, measurement of the duration of the phases of the cell cycle in normal T lymphocytes infected with human immunodeficiency virus (HIV) was undertaken. Methods Flow cytometric measurement of bromodeoxyuridine-labeled and DNA content-stained cells at multiple points through the cell cycle allowed estimation of the fraction of cells in each phase, the potential doubling-time, and the durations of S and G2/M phases. Separate analysis of the HIV+ and HIV− populations within the infected cultures was performed based on intracellular, anti-HIV core p24 antibody labeling. A novel mathematical model, which accounted for cell loss, was developed to estimate cell cycle phases. Results (a) S phase was prolonged in the HIV-1SF2–infected cells compared with control. (b) This delay in S phase was due to delay in the population of cells not expressing HIV-1 antigens (p24 negative). (c) Accumulation of cells in G2/M phase was confirmed in HIV-1–infected cultures and was proportional to the level of infection as measured by p24 fluorescent intensity. However, all mock and HIV-1–infected populations predicted to proceed through cell division demonstrated similar G2/M-phase durations. (c) Potential doubling times were longer in the infected cultures; in contrast, the p24+ subpopulations accounted for this delay. This suggests an isolated delay in the G0/G1 phase for that population of cells. Conclusions Multiple phases of host cell cycle durations were affected by HIV-1SF2 infection in this in vitro model, suggesting novel HIV-1 pathogenesis mechanisms. Prolonged S-phase durations in HIV-1 infected/p24− and G0/G1-phase durations in HIV-1 infected/p24+ subpopulations require further study to identify mechanistic pathways. © 2005 Wiley-Liss, Inc.

Background In an accompanying paper (Asmuth et al.) it was found necessary to include cell death explicitly to estimate parameters of cell proliferation. The use of bivariate flow cytometry to estimate the phase durations and the doubling times of cells labeled with thymidine analogues is well established. However, these methods of analysis do not consider the possibility of cell death. This report demonstrates that estimating cell death in G2/M is possible. Methods Mathematical models for the experimental quantities, the fraction of labeled undivided cells, the fraction of labeled divided cells, and the relative movement were developed. These models include the possibility that, of the cells with G2/M DNA content, only a certain fraction will divide, with the remainder dying after some time TR. Simulation studies were conducted to test the possibility of using simple methods to estimate phase durations and cell death rates. Results Cell death alters the estimates of phase transit times in a rather complex manner that depends on the lifetime of the doomed cells. However, it is still possible to obtain estimates of the phase durations of cells in S and G2/M and the death rates of cells in G2/M. Conclusions The methods presented herein provide a new way to characterize cell populations that includes cell death rates and common measurements of cell proliferation. © 2005 Wiley-Liss, Inc.