Influence of 4- and 6-color flow cytometers and acquisition/analysis softwares on the determination of lymphocyte subsets in HIV infection

Abstract

Background and objectives: Lymphocyte immunophenotyping provides valuable information for the diagnosis and monitoring of patients with cellular immunodeficiencies, such as HIV/AIDS. In this study, we have assessed the influence of 4-color and 6-color flow cytometers, and respective analytical softwares on the enumeration of lymphocytes in HIV infected individuals.

Methods: The expression of various cell surface markers on lymphocytes was measured from the EDTA blood of 66 HIV infected patients on the FACSCalibur (4-color) and FACSCanto (6-color) flow cytometers. Percentage of lymphocytes expressing a particular cell surface marker was analyzed on FACSCalibur using the Cell Quest Pro software (v 5.2), while the analysis on FACSCanto was done using FACSCanto (v 1.0.3) and FACSDiva (v 4.1) softwares respectively.

Results: The data shows significantly higher mean CD3 T-cell counts on FACSCalibur, Cell Quest Pro (1,864 +/- 1,044 cells/microl) as compared to FACSCanto (1,840 +/- 1,040 cells/microl) (P < 0.05). The CD4 T-cell counts were also higher on FACSCalibur, Cell Quest Pro (885 +/- 770 cells/microl), and FACSDiva (892 +/- 773 cells/microl) versus FACSCanto (867 +/- 767 cells/microl) (P < 0.05). FACSCalibur, Cell Quest Pro, and FACSDiva showed similar values except for CD8 T-lymphocytes where FACSDiva had significantly lower values (P < 0.05). The B-cell counts were unaffected when either of the instruments or softwares were used, while the natural killer (NK) cells (CD16 + 56 positive cells) showed similar trend like CD3 and CD4 counts with significant differences in the mean cell counts between FACSCalibur, Cell Quest Pro (240 +/- 165 cells/microl), and FACSDiva (238 +/- 163 cells/microl) versus FACSCanto with higher NK cell counts (260 +/- 176 cells/microl).

Conclusions: The enumeration of lymphocyte subsets was comparable between FACSCalibur, Cell Quest Pro, and FACSDiva, based analysis and it was significantly different than FACSCanto software based analysis. Our observations suggest that FACSDiva software should be preferred over the FACSCanto software for immunophenotyping on FACSCanto flow cytometer and the laboratories should report the instrument and software used for the specimen analysis while reporting immunophenotyping results.