Department of Pathology and Laboratory Medicine, University of Tennessee Health Sciences Center, Memphis, Tennessee, United States of America.
PLoS One. 2011;6(11):e26657. doi: 10.1371/journal.pone.0026657. Epub 2011 Nov 4.
The study of ex vivo phagocytosis via flow cytometry requires that one distinguish experimentally between uptake and adsorption of fluorescently labeled targets by phagocytes. Removal of the latter quantity from the analysis is the most common means of analyzing such data. Because the probability of phagocytosis is a function of the probability of adsorption, and because partially quenched fluorescence after uptake often overlaps with that of negative controls, this approach is suboptimal at best. Here, we describe a numerical analysis model which overcomes these limitations. We posit that the random adsorption of targets to macrophages, and subsequent phagocytosis, is a function of three parameters: the ratio of targets to macrophages (m), the mean fluorescence intensity imparted to the phagocyte by the internalized target (alpha), and the probability of phagocytosis per adsorbed target (p). The potential values of these parameters define a parameter space and their values at any point in parameter space can be used to predict the fraction of adsorption(+) and [adsorption(-), phagocytosis(+)] cells that might be observed experimentally. By systematically evaluating the points in parameter space for the latter two values and comparing them to experimental data, the model arrives at sets of parameter values that optimally predict such data. Using activated THP-1 cells as macrophages and platelets as targets, we validate the model by demonstrating that it can distinguish between the effects of experimental changes in m, alpha, and p. Finally, we use the model to demonstrate that platelets from a congenitally thrombocytopenic WAS patient show an increased probability of ex vivo phagocytosis. This finding correlates with other evidence that rapid in vivo platelet consumption contributes significantly to the thrombocytopenia of WAS. Our numerical analysis method represents a useful and innovative approach to multivariate analysis.
通过流式细胞术研究细胞外吞噬作用，需要区分实验中吞噬细胞对荧光标记靶标的摄取和吸附。从分析中去除后者是分析此类数据的最常见方法。由于吞噬作用的概率是吸附概率的函数，并且由于摄取后部分荧光猝灭经常与阴性对照重叠，因此这种方法充其量是次优的。在这里，我们描述了一种克服这些限制的数值分析模型。我们假设，目标物随机吸附到巨噬细胞上，随后被吞噬，这是三个参数的函数：目标物与巨噬细胞的比率 (m)、被内化的目标物赋予吞噬细胞的平均荧光强度 (α) 和每个被吸附的目标物的吞噬概率 (p)。这些参数的潜在值定义了一个参数空间，并且其在参数空间中的任何点的值都可用于预测可能在实验中观察到的吸附 (+) 和 [吸附 (-)，吞噬 (+)] 细胞的分数。通过系统地评估后两个值的参数空间中的点，并将其与实验数据进行比较，该模型得出了最佳预测此类数据的参数值集。使用活化的 THP-1 细胞作为巨噬细胞，血小板作为靶标，我们通过证明它可以区分 m、α 和 p 实验变化的影响，验证了该模型。最后，我们使用该模型证明了来自先天性血小板减少症 WAS 患者的血小板表现出增加的体外吞噬作用的概率。这一发现与其他证据相关，即体内血小板的快速消耗对 WAS 的血小板减少症有重要贡献。我们的数值分析方法代表了一种有用且创新的多元分析方法。
