COVID-19: Using high-throughput flow cytometry to dissect clinical heterogeneity.

Here we consider how high-content flow cytometric methodology at appropriate scale and throughput rapidly provided meaningful biological data in our recent studies of COVID-19, which we discuss in the context of other similar investigations. In our work, high-throughput flow cytometry was instrumental to identify a consensus immune signature in COVID-19 patients, and to investigate the impact of SARS-CoV-2 exposure on patients with either solid or hematological cancers. We provide here some examples of our 'holistic' approach, in which flow cytometry data generated by lymphocyte and myelomonocyte panels were integrated with other analytical metrics, including SARS-CoV-2-specific serum antibody titers, plasma cytokine/chemokine levels, and in-depth clinical annotation. We report how selective differences between T cell subsets were revealed by a newly described flow cytometric TDS assay to distinguish actively cycling T cells in the peripheral blood. By such approaches, our and others' high-content flow cytometry studies collectively identified overt abnormalities and subtle but critical changes that discriminate the immuno-signature of COVID-19 patients from those of healthy donors and patients with non-COVID respiratory infections. Thereby, these studies offered several meaningful biomarkers of COVID-19 severity that have the potential to improve the management of patients and of hospital resources. In sum, flow cytometry provides an important means for rapidly obtaining data that can guide clinical decision-making without requiring highly expensive, sophisticated equipment, and/or "-omics" capabilities. We consider how this approach might be further developed.

Recent advances in high-throughput flow cytometry for drug discovery.

INTRODUCTION: High-throughput flow cytometry (HTFC) has proven to be an important technology in drug discovery. The use of HTFC enables multi-parametric screening of suspension cells containing heterogenous cell populations and coated particles for screening proteins of interest. Novel targets, novel cell markers and compound clusters for drug development have been identified from HTFC screens. AREAS COVERED: In this article, the authors focus on reviewing the recent HTFC applications reported during the last 5-6 years, including drug discovery screens and studies for immune, immune-oncology, infectious and inflammatory diseases. The main HTFC approaches, development of HTFC systems, and automated sample preparation systems for HTFC are also discussed. EXPERT OPINION: The advance of HTFC technology coupled with automated sample acquisition and sample preparation has demonstrated its utility in screening large numbers of compounds using suspension cells, facilitated screening of disease-relevant human primary cells, and enabled deep understanding of mechanism of action by analyzing multiple parameters. The authors see HTFC as a very valuable tool in immune, immune-oncology, infectious and inflammatory diseases where immune cells play essential roles.

Taking advantage of a high-throughput flow cytometer for the implementation of an ADCC assay for regulatory compliance.

Technological advances allowed the development of high-throughput instruments such as IntelliCyt iQue Screener PLUS®. Here, we took advantage of this technology to transfer a previously validated cytotoxicity assay. The evaluated parameters were cell permeability, caspase activation and phosphatidyl serine exposure. The assay was accurate (r2 = 0.90), precise (%CV ≤ 18.90) and specific. These results showed that this technology is suitable to be used in control quality environments. In addition, the automation provided a faster acquisition and analysis of data with precise and accurate results. This application could be implemented to evaluate another in vitro mechanism of action of different biotherapeutics.

Discovery of Small Molecules for the Reversal of T Cell Exhaustion.

Inhibitory receptors (IRs) function as critical regulators of immune responses by tempering T cell activity. In humans, several persisting viruses as well as cancers exploit IR signaling by upregulating IR ligands, resulting in suppression of T cell function (i.e., exhaustion). This allows escape from immune surveillance and continuation of disease. Here, we report the design, implementation, and results of a phenotypic high-throughput screen for molecules that modulate CD8+ T cell activity. We identify 19 compounds from the ReFRAME drug-repurposing collection that restore cytokine production and enhance the proliferation of exhausted T cells. Analysis of our top hit, ingenol mebutate, a protein kinase C (PKC) inducing diterpene ester, reveals a role for this molecule in overriding the suppressive signaling cascade mediated by IR signaling on T cells. Collectively, these results demonstrate a disease-relevant methodology for identifying modulators of T cell function and reveal new targets for immunotherapy.

Cellular systems biology identifies dynamic trophoblast populations in early human placentas.

INTRODUCTION: The human placenta is accessible in early developmental stages and affords a unique opportunity to investigate human organogenesis and the dynamics of transitory cell populations in human placenta development. METHODS: The cell surface proteomic profile of early trophoblast cells of first trimester human placentas was quantified using a high throughput flow cytometry screen of 370 Cluster of Differentiation (CD) antigens. Targeted investigation of candidate trophoblast progenitor populations was done through immunohistochemistry, multi-color flow cytometry, and genome wide expression analysis. RESULTS: Using a novel batch correction and normalization methodology, we identified 23 increasing and 13 decreasing markers of dynamic populations between the week 6 and week 10 of placenta development. We identified and characterized two transient populations expressing either EpCAM (CD326) or CDCP1 (CD318). Immunohistochemistry revealed these CD antigens are expressed by discrete cells with EpCAM localized to the proximal villi columns and CDCP1 to distal columns. Flow analysis confirmed independence of these populations and identified EpCAM cells as positive for EGFR. Microarray analysis indicated EpCAM+/EGFR+ and EFGR + cells showed high degree of gene expression similarities to villus cytotrophoblast but loss of EpCAM expression was concomitant with exit from the cell cycle. Similarly, CDCP1 positive trophoblast are enriched in cell cycle gene sets and expressed genes with significant similarity to extravillous cytotrophoblast. DISCUSSION: Our study indicates at least two distinct subpopulations of cytotrophoblasts exist in the early first trimester within the column that likely maintains pools of actively dividing progenitor cells giving rise to the developing placenta villous tree.

Application of High-Throughput Flow Cytometry in Early Drug Discovery: An AstraZeneca Perspective.

Flow cytometry is a powerful tool providing multiparametric analysis of single cells or particles. The introduction of faster plate-based sampling technologies on flow cytometers has transformed the technology into one that has become attractive for higher throughput drug discovery screening. This article describes AstraZeneca's perspectives on the deployment and application of high-throughput flow cytometry (HTFC) platforms for small-molecule high-throughput screening (HTS), structure-activity relationship (SAR) and phenotypic screening, and antibody screening. We describe the overarching HTFC workflow, including the associated automation and data analysis, along with a high-level overview of our HTFC assay portfolio. We go on to discuss the practical challenges encountered and solutions adopted in the course of our deployment of HTFC, as well as future enhancements and expansion of the technology to new areas of drug discovery.

Comparing Flow Cytometry QBeads PlexScreen Assays with Other Immunoassays for Determining Multiple Analytes.

Immunoassays, utilizing the affinity of antibodies to their antigens, are powerful techniques and have been widely used for quantifying analytes, such as cytokines, in biological samples in the clinic and in drug discovery. Various immunoassays have been developed to fit for different purposes. Recently, bead-based flow cytometry assays have emerged as interesting options for multiplex quantification of analytes. In this study, we compared high-throughput flow cytometry multiplex iQue QBeads PlexScreen assays with several other commonly used immunoassays, including MSD, Luminex, ELISA, HTRF, and AlphaLISA assays. Head-to-head comparisons of quantification data of the following cytokines were made: (1) IL-2, IL-4, IL-6, IL-13, IL-17A, IFNγ, KC/GRO, RANTES, and TNFα in mouse bronchoalveolar lavage fluid samples; (2) IL-10 and TNFα in supernatants from a THP-1 cell assay; (3) IL-6, IL-10, IL-12p70, and TNFα in supernatants from a human monocyte-derived dendritic cell assay; and (4) IL-2 in supernatants from a human CD4+ cell assay. The results demonstrated a good assay correlation between the iQue and the compared assays for the cytokine studied. Although overall good assay correlations were observed, our results showed that the iQue assay generated different absolute cytokine values for some cytokines in the same sample sets compared with other assays.

A Multiplexed Screening Assay to Evaluate Chemotherapy-Induced Myelosuppression Using Healthy Peripheral Blood and Bone Marrow.

Myelosuppression is a major side effect of chemotherapy in cancer patients and can result in infections, bleeding complications, and increased risk of morbidity and mortality, as well as limit the drug dose and frequency of administration. Chemotherapy-induced myelosuppression is caused by the disruption of normal hematopoiesis. Thus, prior understanding of the adverse effects of chemotherapies on hematopoietic cells is essential to minimize the side effects of cancer treatment. Traditional methods such as colony-forming assays for studying chemotherapy-induced myelosuppression are time-consuming and labor intensive. High-throughput flow cytometry technologies and methods to detect rare hematopoietic cell populations are critical in advancing our understanding of how different blood cell types in complex biological samples respond to chemotherapeutic drugs. In the present study, hematopoietic progenitor cells were induced to differentiate into megakaryocytes and myeloid lineage cells. The expanded cells were then used in a multiplexed assay to monitor the dose-response effects of multiple chemotherapies on different stages of megakaryocyte differentiation and myeloid cell populations in a 96-well plate format. The assay offers an alternative method to evaluate the myelosuppressive potential of novel chemotherapeutic drugs compared to traditional lower throughput and labor-intensive assays.

Automated High-Throughput Flow Cytometry for High-Content Screening in Antibody Development.

The tedious sample preparation for flow cytometry limits the throughput and thus its usage as a primary screening method despite its sensitivity and accuracy. With the growing focus on utilizing antibodies as a therapeutic modality in drug discovery, it is critical to develop a high-throughput flow cytometry (HTFC) workflow to cope with the increasing need to support antibody discovery programs. We have developed a seamless HTFC sample preparation and readout workflow using the HighRes modular robotic system and the IntelliCyt iQue Screener PLUS. To fully utilize the advantages offered by flow cytometry, we typically multiplex multiple cell lines of interest in one well to simultaneously quantitate on-target activity and nonspecific activity along with measurement of antibody concentration. The ability to measure multiple parameters coupled with speed and increased accuracy provides gains in productivity and helps speed up antibody lead discovery.

High-Throughput Flow Cytometry Drug Combination Discovery with Novel Synergy Analysis Software, SynScreen.

Classical therapeutic regimens are subject to toxicity, low efficacy, and/or the development of drug resistance. Thus, the discovery of synergistic drug combinations would permit treatment with lower, tolerable dosages of each agent and restored sensitivity. We describe the development and use of the SynScreen software application, which allows for visual and mathematical determinations of compound concentrations that produce super-additive effects. This software uses nonlinear regression fits of dose responses to determine synergism by the Bliss independence and Loewe additivity analysis models. We demonstrate the utility of SynScreen with data analysis from in vitro high-throughput flow cytometry (HTFC) combination screens with repurposed drugs and multiplexed synergy analysis of multiple biologic parameters in parallel. The applicability of SynScreen was confirmed by testing open-source data sets used in published drug combination literature. A key benefit of SynScreen for high-throughput drug combination screening is that observed measurements are graphically depicted in comparison with a three-dimensional surface that represents the theoretical responses at which Bliss additivity would occur. These images and summary tables for the calculated drug interactions are automatically exported. This allows for substantial data sets to be visually assessed, expediting the quick identification of efficacious drug combinations and thereby facilitating the design of confirmatory studies and clinical trials.

A Fully Automated High-Throughput Flow Cytometry Screening System Enabling Phenotypic Drug Discovery.

The goal of high-throughput screening is to enable screening of compound libraries in an automated manner to identify quality starting points for optimization. This often involves screening a large diversity of compounds in an assay that preserves a connection to the disease pathology. Phenotypic screening is a powerful tool for drug identification, in that assays can be run without prior understanding of the target and with primary cells that closely mimic the therapeutic setting. Advanced automation and high-content imaging have enabled many complex assays, but these are still relatively slow and low throughput. To address this limitation, we have developed an automated workflow that is dedicated to processing complex phenotypic assays for flow cytometry. The system can achieve a throughput of 50,000 wells per day, resulting in a fully automated platform that enables robust phenotypic drug discovery. Over the past 5 years, this screening system has been used for a variety of drug discovery programs, across many disease areas, with many molecules advancing quickly into preclinical development and into the clinic. This report will highlight a diversity of approaches that automated flow cytometry has enabled for phenotypic drug discovery.

Cell Separation in Aqueous Two-Phase Systems - Influence of Polymer Molecular Weight and Tie-Line Length on the Resolution of Five Model Cell Lines.

The availability of clinical-scale downstream processing strategies for cell-based products presents a critical juncture between basic research and clinical development. Aqueous two-phase systems (ATPS) facilitate the label-free, scalable, and cost-effective separation of cells, and are a versatile tool for downstream processing of cell-based therapeutics. Here, we report the application of a previously developed robotic screening platform, here extended to enable a multiplexed high-throughput cell partitioning analysis in ATPS. We investigated the influence of polymer molecular weight and tie-line length on the resolution of five model cell lines in "charge-sensitive" polyethylene-glycol (PEG)-dextran ATPS. We show, how these factors influence cell partitioning, and that the combination of low molecular weight PEGs and high molecular weight dextrans enable the highest resolution of the five cell lines. Furthermore, we demonstrate that the separability of each cell line from the mixture is highly dependent on the polymer molecular weight composition and tie-line length. Using a countercurrent distribution model we demonstrate that our screenings yielded conditions that theoretically enable the isolation of four of the five cell lines with high purity (>99.9%) and yield.

A High-Throughput Flow Cytometry Assay for Identification of Inhibitors of 3',5'-Cyclic Adenosine Monophosphate Efflux.

Assays to identify small molecule inhibitors of cell transporters have long been used to develop potential therapies for reversing drug resistance in cancer cells. In flow cytometry, these approaches rely on the use of fluorescent substrates of transporters. Compounds which prevent the loss of cell fluorescence have typically been pursued as inhibitors of specific transporters, but further drug development has been largely unsuccessful. One possible reason for this low success rate could be a substantial overlap in substrate specificities and functions between transporters of different families. Additionally, the fluorescent substrates are often synthetic dyes that exhibit promiscuity among transporters as well. Here, we describe an assay in which a fluorescent analog of a natural metabolite, 3',5'-cyclic adenosine monophosphate (F-cAMP), is actively effluxed by malignant leukemia cells. The F-cAMP is loaded into the cell cytoplasm using a procedure based on the osmotic lysis of pinocytic vesicles. The flow cytometric analysis of the fluorescence retained in F-cAMP-loaded cells incubated with various compounds can subsequently identify inhibitors of cyclic AMP efflux (ICE).

High-throughput downstream process development for cell-based products using aqueous two-phase systems.

As the clinical development of cell-based therapeutics has evolved immensely within the past years, downstream processing strategies become more relevant than ever. Aqueous two-phase systems (ATPS) enable the label-free, scalable, and cost-effective separation of cells, making them a promising tool for downstream processing of cell-based therapeutics. Here, we report the development of an automated robotic screening that enables high-throughput cell partitioning analysis in ATPS. We demonstrate that this setup enables fast and systematic investigation of factors influencing cell partitioning. Moreover, we examined and optimized separation conditions for the differentiable promyelocytic cell line HL-60 and used a counter-current distribution-model to investigate optimal separation conditions for a multi-stage purification process. Finally, we show that the separation of CD11b-positive and CD11b-negative HL-60 cells is possible after partial DMSO-mediated differentiation towards the granulocytic lineage. The modeling data indicate that complete peak separation is possible with 30 transfers, and >93% of CD11b-positive HL-60 cells can be recovered with >99% purity. The here described screening platform facilitates faster, cheaper, and more directed downstream process development for cell-based therapeutics and presents a powerful tool for translational research.

Characterization of novel biomarkers in selecting for subtype specific medulloblastoma phenotypes.

Major research efforts have focused on defining cell surface marker profiles for characterization and selection of brain tumor stem/progenitor cells. Medulloblastoma is the most common primary malignant pediatric brain cancer and consists of 4 molecular subgroups: WNT, SHH, Group 3 and Group 4. Given the heterogeneity within and between medulloblastoma variants, surface marker profiles may be subtype-specific. Here, we employed a high throughput flow cytometry screen to identify differentially expressed cell surface markers in self-renewing vs. non-self-renewing SHH medulloblastoma cells. The top 25 markers were reduced to 4, CD271/p75NTR/NGFR, CD106/VCAM1, EGFR and CD171/NCAM-L1, by evaluating transcript levels in SHH tumors relative to samples representing the other variants. However, only CD271/p75NTR/NGFR and CD171/NCAM-L1 maintain differential expression between variants at the protein level. Functional characterization of CD271, a low affinity neurotrophin receptor, in cell lines and primary cultures suggested that CD271 selects for lower self-renewing progenitors or stem cells. Moreover, CD271 levels were negatively correlated with expression of SHH pathway genes. Our study reveals a novel role for CD271 in SHH medulloblastoma and suggests that targeting CD271 pathways could lead to the design of more selective therapies that lessen the broad impact of current treatments on developing nervous systems.