Plasma membrane assays and three-compartment image cytometry for high content screening.

High throughput image cytometers analyze individual cells in digital photomicrographs by first assigning pixels within each image to plasma membrane, cytoplasm, nucleus, or other regions. In this study, we report on a novel algorithm that: 1) identifies plasma membrane regions to measure changes in plasma membrane-associated proteins (protein kinase C [PKC] alpha, N-cadherin, E-cadherin, vascular endothelium [VE]-cadherin, and pan-cadherin) that regulate cell division, migration, and adhesion and 2) delineates the cell for generalized three-compartment image cytometry. Validation assays were performed for these proteins on cells cultured in 96-well plates and also for tissue sections obtained from transgenic and chemical carcinogenic models of skin cancer. The algorithm successfully quantified phorbol 12-myristate 13-acetate (PMA)-induced plasma membrane localization of PKCalpha in HeLa cells (Z' of 0.88). Additionally, PMA activated translocation to the plasma membrane at P < .01 of N-cadherin (in HeLa cells), E-cadherin (in A431 cells), and VE-cadherin (in human dermal microvascular endothelial cells), suggesting a relationship between PKCalpha activity and cadherin localization. For VE-cadherin, a Z' of 0.52 was obtained between serum-free medium, which increased VE-cadherin, and EGTA, which diminished VE-cadherin at the plasma membrane. For sections obtained from the transgenic skin cancer model, analysis of images with the plasma membrane algorithm revealed that tumor cells exhibited cadherin expression that was just 34% of that expressed by surrounding normal tissue; furthermore, tumor cells expressed elevated DNA content, consistent with development of aneuploidy. In contrast, increased DNA content did not occur for tumor cells produced by chemical carcinogenesis. The results demonstrate that this new algorithm for plasma membrane image cytometry enables statistically significant analyses in a variety of applications in both cultured cells and tissue sections.

A live cell, image-based approach to understanding the enzymology and pharmacology of 2-bromopalmitate and palmitoylation.

The addition of a lipid moiety to a protein increases its hydrophobicity and subsequently its attraction to lipophilic environments like membranes. Indeed most lipid-modified proteins are localized to membranes where they associate with multiprotein signaling complexes. Acylation and prenylation are the two common categories of lipidation. The enzymology and pharmacology of prenylation are well understood but relatively very little is known about palmitoylation, the most common form of acylation. One distinguishing characteristic of palmitoylation is that it is a dynamic modification. To understand more about how palmitoylation is regulated, we fused palmitoylation substrates to fluorescent proteins and reported their subcellular distribution and trafficking. We used automated high-throughput fluorescence microscopy and a specialized computer algorithm to image and measure the fraction of palmitoylation reporter on the plasma membrane versus the cytoplasm. Using this system we determined the residence half-life of palmitate on the dipalmitoyl substrate peptide from GAP43 as well as the EC(50) for 2-bromopalmitate, a common inhibitor of palmitoylation.

Identification of the tyrosine phosphatase PTP-MEG2 as an antagonist of hepatic insulin signaling.

Insulin resistance is a primary defect in type 2 diabetes characterized by impaired peripheral glucose uptake and insufficient suppression of hepatic glucose output. Insulin signaling inhibits liver glucose production by inducing nuclear exclusion of the gluconeogenic transcription factor FOXO1 in an Akt-dependent manner. Through the concomitant application of genome-scale functional screening and quantitative image analysis, we have identified PTP-MEG2 as a modulator of insulin-dependent FOXO1 subcellular localization. Ectopic expression of PTP-MEG2 in cells inhibited insulin-induced phosphorylation of the insulin receptor, while RNAi-mediated reduction of PTP-MEG2 transcript levels enhanced insulin action. Additionally, adenoviral-mediated depletion of PTP-MEG2 in livers of diabetic (db/db) mice resulted in insulin sensitization and normalization of hyperglycemia. These data implicate PTP-MEG2 as a mediator of blood glucose homeostasis through antagonism of insulin signaling, and suggest that modulation of PTP-MEG2 activity may be an effective strategy in the treatment of type 2 diabetes.

Statistics of assay validation in high throughput cell imaging of nuclear factor kappaB nuclear translocation.

This report describes statistical validation methods implemented on assay data for inhibition of subcellular redistribution of nuclear factor kappaB (NF kappaB) in HeLa cells. We quantified cellular inhibition of cytoplasmic-nuclear translocation of NF kappaB in response to a range of concentrations of interleukin-1 (IL-1) receptor antagonist in the presence of IL-1alpha using eight replicate rows in each four 96-well plates scanned five times on each of 2 days. Translocation was measured as the fractional localized intensity of the nucleus (FLIN), an implementation of our more general fractional localized intensity of the compartments (FLIC), which analyzes whole compartments in the context of the entire cell. The NF kappaB antagonist assay (inhibition of IL-1- induced NF kappaB translocation) data were collected on a Q3DM (San Diego, CA) EIDAQtrade mark 100 high throughput microscopy system. [In 2003, Q3DM was purchased by Beckman Coulter Inc. (Fullerton, CA), which released the IC 100 successor to the EIDAQ 100.] The generalized FLIC method is described along with two-point (minimum-maximum) and multiple point titration statistical methods. As a ratio of compartment intensities that tend to change proportionally, FLIN was resistant to photobleaching errors. Two-point minimum-maximum statistical analyses yielded the following: a Z' of 0.174 with the data as n = 320 independent well samples; Z' by row data in a range of 0.393-0.933, with a mean of 0.766; by-plate Z' data of 0.310, 0.443, 0.545, and 0.794; and by-plate means of columns Z' data of 0.879, 0.927, 0.945, and 0.963. The mean 50% inhibitory concentration (IC50) for IL-1 receptor antagonist over all experiments was 213 ng/ml. The combined IC50 coefficients of variation (CVs) were 0.74%, 0.85%, 2.09%, and 2.52% for the four plates. Repeatability IC50 CVs were as follows: day to day 3.0%, row to row 8.0%, plate to plate 2.8%, and day to day 0.6%. The number of cells required for statistically resolvable differences in dose concentrations, plotted in a family of FLIN sigma/deltamicro (SD/range) curves and tabulated, demonstrated cell-by-cell assay precision with our combined sigma/deltamicro = 0.32 that required approximately 10-fold fewer cells than in a previously reported NF kappaB assay with sigma/deltamicro = 1.52. To better understand the relationship between cell-by-cell measurements and IC50 precision, 500 Monte Carlo simulations with varying cell-measurement SDs were used to explore three-, five-, seven-, and 11-point model titrations. The reductions in deltaIC50 90% confidence intervals from 11- to three-point titrations were 10-fold with the previously reported sigma/deltamicro = 1.52 and twofold with our sigma/deltamicro = 0.32. With these normalized parameters, this report provides a common statistical foundation, independent of the assay details, for evaluating the performance of imaging data on any instrument.

Identification of novel mammalian growth regulatory factors by genome-scale quantitative image analysis.

Functional profiling technologies using arrayed collections of genome-scale siRNA and cDNA arrayed libraries enable the comprehensive global analysis of gene function. However, the current repertoire of high-throughput detection methodologies has limited the scope of cellular phenotypes that can be studied. In this report, we describe the systematic identification of mammalian growth-regulatory factors achieved through the integration of automated microscopy, pattern recognition analysis, and cell-based functional genomics. The effects of 7364 human and mouse proteins, encoded by individually arrayed cDNAs, upon proliferation and viability in U2OS osteosarcoma cells were evaluated in a live-cell, kinetic assay using quantitative image analysis. Overexpression of more than 86 cDNAs (1.15%) conferred dramatic increases in the proliferation, as determined cell enumeration. These included several known growth regulators, as well as previously uncharacterized ones (LRRK1, Ankrd25). In addition, novel functional roles for two genes (5033414D02Rik, 2810429O05Rik), now termed Gatp1 and Gatp2, respectively, were identified. Further analysis demonstrated that these encoded proteins promoted cellular proliferation and transformation in primary cells. Conversely, cells depleted for Gatp1 underwent apoptosis upon serum reduction, suggesting that Gatp1 is essential for cell survival under growth-factor-restricted conditions. Taken together, our findings offer new insight into the regulation of cellular growth and proliferation, and demonstrate the value and feasibility of assessing cellular phenotypes through genome-level computational image analysis.