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Mar 1, 2009 (Vol. 29, No. 5)

Measuring Multiplexed Signal Transduction

Amnis’ Platform Was Developed to Assist in Assessment of NF-kappa-B Translocation

  • Nuclear Localization of NF-kappa-B

    Click Image To Enlarge +
    Figure 1. Similarity scores for cells spanning the range from untranslocated to translocated are shown as well as histograms of the Similarity scores for two samples.

    Assessment of NF-kB translocation is generally performed using nuclear and NF-kB fluorescence images of a cell. These images are used to define the nuclear and cytoplasmic compartments, followed by an assessment of the relative amount of NF-kB fluorescence in each compartment. While this approach works well for cells with low nuclear to cytoplasmic (N/C) areas, it is less reliable for immune cells, which have characteristically high N/C ratios and correspondingly small cytoplasmic areas. These limitations can be overcome by using an image-correlation algorithm that does not rely on an accurate definition of the cytoplasmic compartment. Assay robustness is further improved by imaging large numbers of cells for increased statistical measurement accuracy.

    To measure NF-kB nuclear localization, THP1 cells are labeled with propidium iodide and Cy3 anti-NF-kB antibodies. Nuclear localization of NF-kB was measured on a per-cell basis using the Similarity score, a measure of the correlation between the NF-kB and nuclear image pairs. 

    The Cy3 and PI images for an untranslocated cell look different from one another and thus score low for similarity (Figure 1). As NF-kB translocates to the nucleus the Cy3 and PI images look more alike, increasing the Similarity score. The Similarity score is plotted for thousands of cells from two samples, one exposed to 10 ng/mL TNF-α (Sample 30) and the other to only 0.1 pg/mL.

    The percentage of cells in each sample that exhibit translocation is derived by setting a threshold and calculating the fraction of the distribution above the threshold. Alternatively, the position and shape of the distribution can be defined using a wide array of statistical metrics (mean, standard deviation). With the ability to image thousands of cells per sample, even subtle changes in sample response due to dosage or time can be detected by shifts in the percentage of translocated cells or the mean Similarity score of a given sample.



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