Figure 5: Subpopulation discrimination based on hundreds of single-cell RT–PCR reactions.

(a) High throughput single-cell gene expression analysis was performed by loading the microwell array with BB88 cells. A representative florescent micrograph and the well intensity histogram at cycles 0, 20 and 40 are shown. The histograms include the intensity of all the wells (including empty wells and wells containing single cells). Scale bars, 40 μm. (b) The fluorescent threshold is calculated to eliminate the empty low-intensity wells and normalize the fluorescent intensity signals of the higher fluorescing wells. Note that the empty wells’ fluorescence levels remained approximately constant and similar to the background throughout the 40 amplification cycles. In addition, the empty wells are approximately 3- to 10-fold more numerous than the single-cell wells. This characteristic was harnessed to calculate the low intensity well threshold using a linear regression gaussian fit and then setting the threshold (f_tr) at μ_norm+3σ, where μ_norm and σ represent the mean and the s.d., respectively. (c) Histograms of the single-cell well intensities of the RT–PCR reactions of mouse peripheral blood mononuclear cells (PBMCs) cells, which are known to be heterogeneous (bi-modal) for Mac-1 expression. The well intensities are calculated as the ratio of the mean intensity of the free solution fluorescence within the well versus the mean empty well intensity. As predicted in Fig. 1b a statistically significant number (~360) of single cells is required for the histogram distribution to clearly show the presence of two distinct cell populations in the mixture (P<0.1, P-value calculated as shown in Supplementary Fig. 9).