Image-Based Phenotypic Screening with Human Primary T Cells Using One-Dimensional Imaging Cytometry with Self-Tuning Statistical-Gating Algorithms

Abstract

The parallel microfluidic cytometer (PMC) is an imaging flow cytometer that operates on statistical analysis of low-pixel-count, one-dimensional (1D) line scans. It is highly efficient in data collection and operates on suspension cells. In this article, we present a supervised automated pipeline for the PMC that minimizes operator intervention by incorporating multivariate logistic regression for data scoring. We test the self-tuning statistical algorithms in a human primary T-cell activation assay in flow using nuclear factor of activated T cells (NFAT) translocation as a readout and readily achieve an average Z′ of 0.55 and strictly standardized mean difference of 13 with standard phorbol myristate acetate/ionomycin induction. To implement the tests, we routinely load 4 µL samples and can readout 3000 to 9000 independent conditions from 15 mL of primary human blood (buffy coat fraction). We conclude that the new technology will support primary-cell protein-localization assays and “on-the-fly” data scoring at a sample throughput of more than 100,000 wells per day and that it is, in principle, consistent with a primary pharmaceutical screen.