Modeling mechanisms underlying differential inflammatory responses to COVID-19 in type 2 diabetes using a patient-derived microphysiological organ-on-a-chip system.

Background: COVID-19 pandemic has caused more than 6 million deaths worldwide. Co-morbid conditions such as Type 2 Diabetes (T2D) have increased mortality in COVID-19. With limited translatability of in vitro and small animal models to human disease, human organ-on-a-chip models are an attractive platform to model in vivo disease conditions and test potential therapeutics. Methods: T2D or non-diabetic patient-derived macrophages and human liver sinusoidal endothelial cells were seeded, along with normal hepatocytes and stellate cells in the liver-on-a-chip (LAMPS - liver acinus micro physiological system), perfused with media mimicking non-diabetic fasting or T2D (high levels of glucose, fatty acids, insulin, glucagon) states. The macrophages and endothelial cells were transduced to overexpress the SARS-CoV2-S (spike) protein with appropriate controls before their incorporation into LAMPS. Cytokine concentrations in the efflux served as a read-out of the effects of S-protein expression in the different experimental conditions (non-diabetic-LAMPS, T2D-LAMPS), including incubation with tocilizumab, an FDA-approved drug for severe COVID-19. Findings: S-protein expression in the non-diabetic LAMPS led to increased cytokines, but in the T2D-LAMPS, this was significantly amplified both in the number and magnitude of key pro-inflammatory cytokines (IL6, CCL3, IL1ß, IL2, TNFα, etc.) involved in cytokine storm syndrome (CSS), mimicking severe COVID-19 infection in T2D patients. Compared to vehicle control, tocilizumab (IL6-receptor antagonist) decreased the pro-inflammatory cytokine secretion in T2D-COVID-19-LAMPS but not in non-diabetic-COVID-19-LAMPS. Interpretation: macrophages and endothelial cells play a synergistic role in the pathophysiology of the hyper-inflammatory response seen with COVID-19 and T2D. The effect of Tocilizumab was consistent with large clinical trials that demonstrated Tocilizumab's efficacy only in critically ill patients with severe disease, providing confirmatory evidence that the T2D-COVID-19-LAMPS is a robust platform to model human in vivo pathophysiology of COVID-19 in T2D and for screening potential therapeutics.

Validation of a high throughput screening assay to identify small molecules that target the eukaryotic replicative helicase.

Mcm2-7 is the catalytic core of the eukaryotic replicative helicase, which together with CDC45 and the GINS complex unwind parental DNA to generate templates for DNA polymerase. Being a highly regulated and complex enzyme that operates via an incompletely understood multi-step mechanism, molecular probes of Mcm2-7 that interrogate specific mechanistic steps would be useful tools for research and potential future chemotherapy. Based upon a synthetic lethal approach, we previously developed a budding yeast multivariate cell-based high throughput screening (HTS) assay to identify putative Mcm inhibitors by their ability to specifically cause a growth defect in an mcm mutant relative to a wild-type strain[1]. Here, as proof of concept, we used this assay to screen a 1280-member compound library (LOPAC) for potential Mcm2-7 inhibitors. Primary screening and dose-dependent retesting identified twelve compounds from this library that specifically inhibited the growth of the Mcm mutant relative to the corresponding wild-type strain (0.9 % hit rate). Secondary assays were employed to rule out non-specific DNA damaging agents, establish direct protein-ligand interaction via biophysical methods, and verify in vivo DNA replication inhibition via fluorescence activated cell sorter analysis (FACS). We identified one agent (ß-carboline-3-carboxylic acid N-methylamide, CMA) that physically bound to the purified Mcm2-7 complex (Kdapp119 µM), and at slightly higher concentrations specifically blocked S-phase cell cycle progression of the wild-type strain. In total, identification of Mcm2-7 as a CMA target validates our synthetic lethal HTS assay paradigm as a tool to identify chemical probes for the Mcm2-7 replicative helicase.

A 3D microfluidic liver model for high throughput compound toxicity screening in the OrganoPlate®.

We report the development, automation and validation of a 3D, microfluidic liver-on-a-chip for high throughput hepatotoxicity screening, the OrganoPlate LiverTox™. The model is comprised of aggregates of induced pluripotent stem cell (iPSC)-derived hepatocytes (iHep) seeded in an extracellular matrix in the organ channel and co-cultured with endothelial cells and THP-1 monoblasts differentiated to macrophages seeded in the vascular channel of the 96 well Mimetas OrganoPlate 2-lane. A key component of high throughput screening is automation and we report a protocol to seed, dose, collect and replenish media and add assay reagents in the OrganoPlate 2-lane using a standard laboratory liquid handling robot. A combination of secretome measurements and image-based analysis was used to demonstrate stable 15 day cell viability, albumin and urea secretion. Over the same time-period, CYP3A4 activity increased and alpha-fetoprotein secretion decreased suggesting further maturation of the iHeps. Troglitazone, a clinical hepatotoxin, was chosen as a control compound for validation studies. Albumin, urea, hepatocyte nuclear size and viability staining provided Robust Z'factors > 0.2 in plates treated 72 h with 180 µM troglitazone compared with a vehicle control. The viability assay provided the most robust statistic for a Robust Z' factor = 0.6. A small library of 159 compounds with known liver effects was added to the OrganoPlate LiverTox model for 72 h at 50 µM and the Toxicological Prioritization scores were calculated. A follow up dose-response evaluation of select hits revealed the albumin assay to be the most sensitive in calculating TC50 values. This platform provides a robust, novel model which can be used for high throughput hepatotoxicity screening.

Confirmation of Selected Synergistic Cancer Drug Combinations Identified in an HTS Campaign and Exploration of Drug Efflux Transporter Contributions to the Mode of Synergy.

Systematic unbiased high-throughput screening (HTS) of drug combinations (DCs) in well-characterized tumor cell lines is a data-driven strategy to identify novel DCs with potential to be developed into effective therapies. Four DCs from a DC HTS campaign were selected for confirmation; only one appears in clinicaltrials.gov and limited preclinical in vitro data indicates that the drug pairs interact synergistically. Nineteen DC-tumor cell line sets were confirmed to interact synergistically in three pharmacological interaction models. We developed an imaging assay to quantify accumulation of the ABCG2 efflux transporter substrate Hoechst. Gefitinib and raloxifene enhanced Hoechst accumulation in ABCG2 (BCRP)-expressing cells, consistent with inhibition of ABCG2 efflux. Both drugs also inhibit ABCB1 efflux. Mitoxantrone, daunorubicin, and vinorelbine are substrates of one or more of the ABCG2, ABCB1, or ABCC1 efflux transporters expressed to varying extents in the selected cell lines. Interactions between ABC drug efflux transporter inhibitors and substrates may have contributed to the observed synergy; however, other mechanisms may be involved. Novel synergistic DCs identified by HTS were confirmed in vitro, and plausible mechanisms of action studied. Similar approaches may justify the testing of novel HTS-derived DCs in mouse xenograft human cancer models and support the clinical evaluation of effective in vivo DCs in patients.

Implementation of the NCI-60 Human Tumor Cell Line Panel to Screen 2260 Cancer Drug Combinations to Generate >3 Million Data Points Used to Populate a Large Matrix of Anti-Neoplastic Agent Combinations (ALMANAC) Database.

Animal and clinical studies demonstrate that cancer drug combinations (DCs) are more effective than single agents. However, it is difficult to predict which DCs will be more efficacious than individual drugs. Systematic DC high-throughput screening (HTS) of 100 approved drugs in the National Cancer Institute's panel of 60 cancer cell lines (NCI-60) produced data to help select DCs for further consideration. We miniaturized growth inhibition assays into 384-well format, increased the fetal bovine serum amount to 10%, lengthened compound exposure to 72 h, and used a homogeneous detection reagent. We determined the growth inhibition 50% values of individual drugs across 60 cell lines, selected drug concentrations for 4 × 4 DC matrices (DCMs), created DCM master and replica daughter plate sets, implemented the HTS, quality control reviewed the data, and analyzed the results. A total of 2620 DCMs were screened in 60 cancer cell lines to generate 3.04 million data points for the NCI ALMANAC (A Large Matrix of Anti-Neoplastic Agent Combinations) database. We confirmed in vitro a synergistic drug interaction flagged in the DC HTS between the vinca-alkaloid microtubule assembly inhibitor vinorelbine (Navelbine) tartrate and the epidermal growth factor-receptor tyrosine kinase inhibitor gefitinib (Iressa) in the SK-MEL-5 melanoma cell line. Seventy-five percent of the DCs examined in the screen are not currently in the clinical trials database. Selected synergistic drug interactions flagged in the DC HTS described herein were subsequently confirmed by the NCI in vitro, evaluated mechanistically, and were shown to have greater than single-agent efficacy in mouse xenograft human cancer models. Enrollment is open for two clinical trials for DCs that were identified in the DC HTS. The NCI ALMANAC database therefore constitutes a valuable resource for selecting promising DCs for confirmation, mechanistic studies, and clinical translation.

Connecting Neuronal Cell Protective Pathways and Drug Combinations in a Huntington's Disease Model through the Application of Quantitative Systems Pharmacology.

Quantitative Systems Pharmacology (QSP) is a drug discovery approach that integrates computational and experimental methods in an iterative way to gain a comprehensive, unbiased understanding of disease processes to inform effective therapeutic strategies. We report the implementation of QSP to Huntington's Disease, with the application of a chemogenomics platform to identify strategies to protect neuronal cells from mutant huntingtin induced death. Using the STHdh Q111 cell model, we investigated the protective effects of small molecule probes having diverse canonical modes-of-action to infer pathways of neuronal cell protection connected to drug mechanism. Several mechanistically diverse protective probes were identified, most of which showed less than 50% efficacy. Specific combinations of these probes were synergistic in enhancing efficacy. Computational analysis of these probes revealed a convergence of pathways indicating activation of PKA. Analysis of phospho-PKA levels showed lower cytoplasmic levels in STHdh Q111 cells compared to wild type STHdh Q7 cells, and these levels were increased by several of the protective compounds. Pharmacological inhibition of PKA activity reduced protection supporting the hypothesis that protection may be working, in part, through activation of the PKA network. The systems-level studies described here can be broadly applied to any discovery strategy involving small molecule modulation of disease phenotype.

Exploiting Analysis of Heterogeneity to Increase the Information Content Extracted from Fluorescence Micrographs of Transgenic Zebrafish Embryos.

Zebrafish embryos are a near-ideal animal model for drug discovery because of their high genetic and physiological similarity to mammals, small size, high fecundity, and optical transparency. The latter properties make zebrafish at larval stages especially suited for high-content analysis and high throughput screening (HTS). However, inherent biological complexity and the inability to screen multiple specimens in a single well present a challenge for HTS because limiting replicates and high variability often prevent assays from reaching the stringent performance criteria demanded of large-scale screening assays. In this report, we present methodology that overcomes these obstacles. We used our previously developed Tg(lhx1a:EGFP)pt303 line, which expresses a fluorescent transgene that enables live real-time measurements of kidney progenitor cell expansion. Since transgenes are expressed in specific cell populations, whose localization is precisely controlled, both spatially and temporally, we considered the developing embryo to be a "host" for a cell population, analogous to a well of a cell culture microplate, rather than a single specimen. By adopting this view, parameters routinely used to analyze cultured cells became applicable to characterize and quantify zebrafish transgene appearance beyond the overall intensity or area measurements, which are analogous to calculating well average data. Using the pixel-level distribution of transgene intensity as a proxy to cell-level data, we applied population-based intensity and heterogeneity measurements to quantitatively describe and characterize transgene expression in each embryo. Subsequent linear discriminant analysis on eight such parameters captured and condensed this information into a single assay parameter that maximizes the difference between positive and negative responses. The improvements in assay performance resulted in the Tg(lhx1a:EGFP)pt303 assay achieving HTS compatible assay performance in multi-day variability studies, documenting readiness for HTS of compounds that expand kidney progenitor cell populations.

Biologically Relevant Heterogeneity: Metrics and Practical Insights.

Heterogeneity is a fundamental property of biological systems at all scales that must be addressed in a wide range of biomedical applications, including basic biomedical research, drug discovery, diagnostics, and the implementation of precision medicine. There are a number of published approaches to characterizing heterogeneity in cells in vitro and in tissue sections. However, there are no generally accepted approaches for the detection and quantitation of heterogeneity that can be applied in a relatively high-throughput workflow. This review and perspective emphasizes the experimental methods that capture multiplexed cell-level data, as well as the need for standard metrics of the spatial, temporal, and population components of heterogeneity. A recommendation is made for the adoption of a set of three heterogeneity indices that can be implemented in any high-throughput workflow to optimize the decision-making process. In addition, a pairwise mutual information method is suggested as an approach to characterizing the spatial features of heterogeneity, especially in tissue-based imaging. Furthermore, metrics for temporal heterogeneity are in the early stages of development. Example studies indicate that the analysis of functional phenotypic heterogeneity can be exploited to guide decisions in the interpretation of biomedical experiments, drug discovery, diagnostics, and the design of optimal therapeutic strategies for individual patients.

Development and Implementation of a High-Throughput High-Content Screening Assay to Identify Inhibitors of Androgen Receptor Nuclear Localization in Castration-Resistant Prostate Cancer Cells.

Patients with castration-resistant prostate cancer (CRPC) can be treated with abiraterone, a potent inhibitor of androgen synthesis, or enzalutamide, a second-generation androgen receptor (AR) antagonist, both targeting AR signaling. However, most patients relapse after several months of therapy and a majority of patients with relapsed CRPC tumors express the AR target gene prostate-specific antigen (PSA), suggesting that AR signaling is reactivated and can be targeted again to inhibit the relapsed tumors. Novel small molecules capable of inhibiting AR function may lead to urgently needed therapies for patients resistant to abiraterone, enzalutamide, and/or other previously approved antiandrogen therapies. Here, we describe a high-throughput high-content screening (HCS) campaign to identify small-molecule inhibitors of AR nuclear localization in the C4-2 CRPC cell line stably transfected with GFP-AR-GFP (2GFP-AR). The implementation of this HCS assay to screen a National Institutes of Health library of 219,055 compounds led to the discovery of 3 small molecules capable of inhibiting AR nuclear localization and function in C4-2 cells, demonstrating the feasibility of using this cell-based phenotypic assay to identify small molecules targeting the subcellular localization of AR. Furthermore, the three hit compounds provide opportunities to develop novel AR drugs with potential for therapeutic intervention in CRPC patients who have relapsed after treatment with antiandrogens, such as abiraterone and/or enzalutamide.

Identification of druggable targets for radiation mitigation using a small interfering RNA screening assay.

Currently, there is a serious absence of pharmaceutically attractive small molecules that mitigate the lethal effects of an accidental or intentional public exposure to toxic doses of ionizing radiation. Moreover, cellular systems that emulate the radiobiologically relevant cell populations and that are suitable for high-throughput screening have not been established. Therefore, we examined two human pluripotent embryonal carcinoma cell lines for use in an unbiased phenotypic small interfering RNA (siRNA) assay to identify proteins with the potential of being drug targets for the protection of human cell populations against clinically relevant ionizing radiation doses that cause acute radiation syndrome. Of the two human cell lines tested, NCCIT cells had optimal growth characteristics in a 384 well format, exhibited radiation sensitivity (D(0) = 1.3 ± 0.1 Gy and ñ = 2.0 ± 0.6) comparable to the radiosensitivity of stem cell populations associated with human death within 30 days after total-body irradiation. Moreover, they internalized siRNA after 4 Gy irradiation enabling siRNA library screening. Therefore, we used the human NCCIT cell line for the radiation mitigation study with a siRNA library that silenced 5,520 genes known or hypothesized to be potential therapeutic targets. Exploiting computational methodologies, we identified 113 siRNAs with potential radiomitigative properties, which were further refined to 29 siRNAs with phosphoinositide-3-kinase regulatory subunit 1 (p85α) being among the highest confidence candidate gene products. Colony formation assays revealed radiation mitigation when the phosphoinositide-3-kinase inhibitor LY294002 was given after irradiation of 32D cl 3 cells (D(0) = 1.3 ± 0.1 Gy and ñ = 2.3 ± 0.3 for the vehicle control treated cells compared to D(0) = 1.2 ± 0.1 Gy and ñ = 6.0 ± 0.8 for the LY294002 treated cells, P = 0.0004). LY294002 and two other PI3K inhibitors, PI 828 and GSK 1059615, also mitigated radiation-induced apoptosis in NCCIT cells. Treatment of mice with a single intraperitoneal LY294002 dose of 30 mg/kg at 10 min, 4, or 24 h after LD(50/30) whole-body dose of irradiation (9.25 Gy) enhanced survival. This study documents that an unbiased siRNA assay can identify new genes, signaling pathways, and chemotypes as radiation mitigators and implicate the PI3K pathway in the human radiation response.

Identification of potent chemotypes targeting Leishmania major using a high-throughput, low-stringency, computationally enhanced, small molecule screen.

Patients with clinical manifestations of leishmaniasis, including cutaneous leishmaniasis, have limited treatment options, and existing therapies frequently have significant untoward liabilities. Rapid expansion in the diversity of available cutaneous leishmanicidal chemotypes is the initial step in finding alternative efficacious treatments. To this end, we combined a low-stringency Leishmania major promastigote growth inhibition assay with a structural computational filtering algorithm. After a rigorous assay validation process, we interrogated approximately 200,000 unique compounds for L. major promastigote growth inhibition. Using iterative computational filtering of the compounds exhibiting > 50% inhibition, we identified 553 structural clusters and 640 compound singletons. Secondary confirmation assays yielded 93 compounds with EC(50)s < or = 1 microM, with none of the identified chemotypes being structurally similar to known leishmanicidals and most having favorable in silico predicted bioavailability characteristics. The leishmanicidal activity of a representative subset of 15 chemotypes was confirmed in two independent assay formats, and L. major parasite specificity was demonstrated by assaying against a panel of human cell lines. Thirteen chemotypes inhibited the growth of a L. major axenic amastigote-like population. Murine in vivo efficacy studies using one of the new chemotypes document inhibition of footpad lesion development. These results authenticate that low stringency, large-scale compound screening combined with computational structure filtering can rapidly expand the chemotypes targeting in vitro and in vivo Leishmania growth and viability.

Automated measurement of cell motility and proliferation.

BACKGROUND: Time-lapse microscopic imaging provides a powerful approach for following changes in cell phenotype over time. Visible responses of whole cells can yield insight into functional changes that underlie physiological processes in health and disease. For example, features of cell motility accompany molecular changes that are central to the immune response, to carcinogenesis and metastasis, to wound healing and tissue regeneration, and to the myriad developmental processes that generate an organism. Previously reported image processing methods for motility analysis required custom viewing devices and manual interactions that may introduce bias, that slow throughput, and that constrain the scope of experiments in terms of the number of treatment variables, time period of observation, replication and statistical options. Here we describe a fully automated system in which images are acquired 24/7 from 384 well plates and are automatically processed to yield high-content motility and morphological data. RESULTS: We have applied this technology to study the effects of different extracellular matrix compounds on human osteoblast-like cell lines to explore functional changes that may underlie processes involved in bone formation and maintenance. We show dose-response and kinetic data for induction of increased motility by laminin and collagen type I without significant effects on growth rate. Differential motility response was evident within 4 hours of plating cells; long-term responses differed depending upon cell type and surface coating. Average velocities were increased approximately 0.1 microm/min by ten-fold increases in laminin coating concentration in some cases. Comparison with manual tracking demonstrated the accuracy of the automated method and highlighted the comparative imprecision of human tracking for analysis of cell motility data. Quality statistics are reported that associate with stage noise, interference by non-cell objects, and uncertainty in the outlining and positioning of cells by automated image analysis. Exponential growth, as monitored by total cell area, did not linearly correlate with absolute cell number, but proved valuable for selection of reliable tracking data and for disclosing between-experiment variations in cell growth. CONCLUSION: These results demonstrate the applicability of a system that uses fully automated image acquisition and analysis to study cell motility and growth. Cellular motility response is determined in an unbiased and comparatively high throughput manner. Abundant ancillary data provide opportunities for uniform filtering according to criteria that select for biological relevance and for providing insight into features of system performance. Data quality measures have been developed that can serve as a basis for the design and quality control of experiments that are facilitated by automation and the 384 well plate format. This system is applicable to large-scale studies such as drug screening and research into effects of complex combinations of factors and matrices on cell phenotype.