Multiplexed high-throughput image cytometry using encoded carriers

Ravkin, Ilya; Temov, Vladimir; Nelson, Aaron D.; Zarowitz, Michael A.; Hoopes, Matthew I.; Verhovsky, Yuli; Ascue, Gregory; Goldbard, Simon; Beske, Oren; Bhagwat, Bhagyashree; Marciniak, Holly

doi:10.1117/12.528071

Cited by 6 publications

(4 citation statements)

References 13 publications

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“…This Z′ score is considered acceptable for cell-based assays, further validating the functional assay and the image analysis algorithm 14. The V score, unlike the Z′ score, takes into account data points that are not complete positives or negatives (i.e., concentration-dependent response) 15. Using the camptothecin concentration response curves generated with this automated assay, we obtained a V score of 0.97 out of 1.00 (Fig.…”

Section: Resultsmentioning

confidence: 78%

“…14 The V score, unlike the Z′ score, takes into account data points that are not complete positives or negatives (i.e., concentration-dependent response). 15 Using the camptothecin concentration response curves generated with this automated assay, we obtained a V score of 0.97 out of 1.00 (Fig. 5), which again indicates the robustness of the assay parameters.…”

Section: Parameters For Pnc Detection and Assay Fidelitymentioning

confidence: 69%

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Automated High-Content Screening for Compounds That Disassemble the Perinucleolar Compartment

et al. 2009

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All solid malignancies share characteristic traits, including unlimited cellular proliferation, evasion of immune regulation, and the propensity to metastasize. The authors have previously described that a subnuclear structure, the perinucleolar compartment (PNC), is associated with the metastatic phenotype in solid tumor cancer cells. The percentage of cancer cells that contain PNCs (PNC prevalence) is indicative of the malignancy of a tumor both in vitro and in vivo, and thus PNC prevalence is a marker that reflects metastatic capability in a population of tumor cells. Although the function of the PNC remains to be determined, the PNC is highly enriched with small RNAs and RNA binding proteins. The initial chemical biology studies using a set of anticancer drugs that disassemble PNCs revealed a direct association of the structure with DNA. Therefore, PNC prevalence reduction as a phenotypic marker can be used to identify compounds that target cellular processes required for PNC maintenance and hence used to elucidate the nature of the PNC function. Here the authors report the development of an automated high-content screening assay that is capable of detecting PNC prevalence in prostate cancer cells (PC-3M) stably expressing a green fluorescent protein (GFP)-fusion protein that localizes to the PNC. The assay was optimized using known PNC-reducing drugs and non-PNC-reducing cytotoxic drugs. After optimization, the fidelity of the assay was probed with a collection of 8284 compounds and was shown to be robust and capable of detecting known and novel PNC-reducing compounds, making it the first reported high-content phenotypic screen for small changes in nuclear structure.

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Section: Resultsmentioning

confidence: 78%

Section: Parameters For Pnc Detection and Assay Fidelitymentioning

confidence: 69%

Automated High-Content Screening for Compounds That Disassemble the Perinucleolar Compartment

et al. 2009

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“…The DOE was then analyzed based on the EC50 titers and confidence limits, V-factor and dynamic range. The V-factor gives a realistic measure of the overall assay performance by accounting for intermediate points in the dose-response curve that have higher variability due to effects of computation and dispensing errors [34]. V-factor is calculated by using the formula V À Factor ¼ 1 À 6 mean ðsÞ jsrÀ snj where σ is standard deviation (SD) of the curve and σp is the SD for positive control and σn is SD for negative control [35].…”

Section: Assay Optimizationmentioning

confidence: 99%

A high throughput reporter virus particle microneutralization assay for quantitation of Zika virus neutralizing antibodies in multiple species

et al. 2021

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Zika virus is a Flavivirus, transmitted via Aedes mosquitos, that causes a range of symptoms including Zika congenital syndrome. Zika has posed a challenging situation for health, public and economic sectors of affected countries. To quantitate Zika virus neutralizing antibody titers in serum samples, we developed a high throughput plate based Zika virus reporter virus particle (RVP) assay that uses an infective, non-replicating particle encoding Zika virus surface proteins and capsid (CprME) and a reporter gene (Renilla luciferase). This is the first characterization of a Zika virus RVP assay in 384-well format using a Dengue replicon Renilla reporter construct. Serially diluted test sera were incubated with RVPs, followed by incubation with Vero cells. RVPs that have not been neutralized by antibodies in the test sera entered the cells and expressed Renilla luciferase. Quantitative measurements of neutralizing activity were determined using a plate-based assay and commercially available substrate. The principle of limiting the infection to a single round increases the precision of the assay measurements. RVP log10EC50 titers correlated closely with titers determined using a plaque reduction neutralization test (PRNT) (R2>95%). The plate-based Zika virus RVP assay also demonstrated high levels of precision, reproducibility and throughput. The assay employs identical reagents for human, rhesus macaque and mouse serum matrices. Spiking studies indicated that the assay performs equally well in different species, producing comparable titers irrespective of the serum species. The assay is conducted in 384-well plates and can be automated to simultaneously achieve high throughput and high reproducibility.

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“…The standardization of quality control in high throughput screening through the use of the Z’-factor [22, 26], or the strictly standardized mean difference [27], has enabled comparison of assay performance over a wide range of assay types, routine monitoring of assay performance during a screen, and a statistical basis for understanding the impact of assay variability on the selection of hits from a screen. For dose-response assays, the V-factor, a generalization of the Z-factor, provides a robust QC measure that takes into account the complete dose-response, rather than just the maximum and minimum response [21, 28]. To be able to compare cellular heterogeneity in order to interpret the biological meaning, standards and quality control are needed to ensure reproducibility.…”

Section: Introductionmentioning

confidence: 99%

A metric and workflow for quality control in the analysis of heterogeneity in phenotypic profiles and screens

Gough

Shun

Taylor

et al. 2016

Methods

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Heterogeneity is well recognized as a common property of cellular systems that impacts biomedical research and the development of therapeutics and diagnostics. Several studies have shown that analysis of heterogeneity: gives insight into mechanisms of action of perturbagens; can be used to predict optimal combination therapies; and to quantify heterogeneity in tumors where heterogeneity is believed to be associated with adaptation and resistance. Cytometry methods including high content screening (HCS), high throughput microscopy, flow cytometry, mass spec imaging and digital pathology capture cell level data for populations of cells. However it is often assumed that the population response is normally distributed and therefore that the average adequately describes the results. A deeper understanding of the results of the measurements and more effective comparison of perturbagen effects requires analysis that takes into account the distribution of the measurements, i.e. the heterogeneity. However, the reproducibility of heterogeneous data collected on different days, and in different plates/slides has not previously been evaluated. Here we show that conventional assay quality metrics alone are not adequate for quality control of the heterogeneity in the data. To address this need, we demonstrate the use of the Kolmogorov-Smirnov statistic as a metric for monitoring the reproducibility of heterogeneity in an SAR screen, describe a workflow for quality control in heterogeneity analysis. One major challenge in high throughput biology is the evaluation and interpretation of heterogeneity in thousands of samples, such as compounds in a cell-based screen. In this study we also demonstrate that three heterogeneity indices previously reported, capture the shapes of the distributions and provide a means to filter and browse big data sets of cellular distributions in order to compare and identify distributions of interest. These metrics and methods are presented as a workflow for analysis of heterogeneity in large scale biology projects.

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Multiplexed high-throughput image cytometry using encoded carriers

Cited by 6 publications

References 13 publications

Automated High-Content Screening for Compounds That Disassemble the Perinucleolar Compartment

Automated High-Content Screening for Compounds That Disassemble the Perinucleolar Compartment

A high throughput reporter virus particle microneutralization assay for quantitation of Zika virus neutralizing antibodies in multiple species

A metric and workflow for quality control in the analysis of heterogeneity in phenotypic profiles and screens

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