High Content Analysis of an In Vitro Model for Metabolic Toxicity

In vitro models that accurately and rapidly assess hepatotoxicity and the effects of hepatic metabolism on nonliver cell types are needed by the U.S. Department of Defense and the pharmaceutical industry to screen compound libraries. Here, we report the first use of high content analysis on the Integrated Discrete Multiple Organ Co-Culture (IdMOC) system, a high-throughput method for such studies. We cultured 3T3-L1 cells in the presence and absence of primary human hepatocytes, and exposed the cultures to 4-aminophenol and cyclophosphamide, model toxicants that are respectively detoxified and activated by the liver. Following staining with calcein-AM, ethidium homodimer-1, and Hoechst 33342, high content analysis of the cultures revealed four cytotoxic endpoints: fluorescence intensities of calcein-AM and ethidium homodimer-1, nuclear area, and cell density. Using these endpoints, we observed that the cytotoxicity of 4-aminophenol in 3T3-L1 cells in co-culture was less than that observed for 3T3-L1 monocultures, consistent with the known detoxification of 4-aminophenol by hepatocytes. Conversely, cyclophosphamide cytotoxicity for 3T3-L1 cells was enhanced by co-culturing with hepatocytes, consistent with the known metabolic activation of this toxicant. The use of IdMOC plates combined with high content analysis is therefore a multi-endpoint, high-throughput capability for measuring the effects of metabolism on toxicity.

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Machine learning-assisted high-content analysis of pluripotent stem cell-derived embryos in vitro

Stem Cell Reports ◽

10.1016/j.stemcr.2021.03.018 ◽

2021 ◽

Author(s):

Jianying Guo ◽

Peizhe Wang ◽

Berna Sozen ◽

Hui Qiu ◽

Yonglin Zhu ◽

...

Keyword(s):

Machine Learning ◽

Content Analysis ◽

Stem Cell ◽

Pluripotent Stem Cell ◽

High Content Analysis

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A Novel High Throughput High Content Analysis Assay for Intermediate Filament Perturbing Drugs

Journal of Integrated OMICS ◽

10.5584/jiomics.v4i1.159 ◽

2014 ◽

Vol 4 (1) ◽

Author(s):

Bernard Michael Corfe ◽

Joanna Chowdry ◽

Gareth J. Griffiths ◽

Rod P. Benson

Keyword(s):

Content Analysis ◽

High Throughput ◽

Intermediate Filament ◽

High Content Analysis

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High Throughput in Silico Identification of Novel Phytochemical Inhibitors for the Master Regulator of Inflammation (TNFα)

10.26434/chemrxiv.14178212.v2 ◽

2021 ◽

Author(s):

Pratap Kumar Parida ◽

Dipak Paul ◽

Debamitra Chakravorty

Keyword(s):

Small Molecule ◽

High Throughput ◽

In Silico ◽

Small Molecule Inhibitors ◽

Binding Free Energy ◽

Natural Compounds ◽

Free Energy Calculations ◽

Compound Libraries ◽

Relative Binding

<a>The over expression of Tumor necrosis factor-α (TNFα) has been implicated in a variety of disease and is classified as a therapeutic target for inflammatory diseases (Crohn disease, psoriasis, psoriatic arthritis, rheumatoid arthritis).Commercially available therapeutics are biologics which are associated with several risks and limitations. Small molecule inhibitors and natural compounds (saponins) were identified by researchers as lead molecules against TNFα, however, </a>they were often associated with high IC50 values which can lead to their failure in clinical trials. This warrants research related to identification of better small molecule inhibitors by screening of large compound libraries. Recent developments have demonstrated power of natural compounds as safe therapeutics, hence, in this work, we have identified TNFα phytochemical inhibitors using high throughput in silico screening approaches of 6000 phytochemicals followed by 200 ns molecular dynamics simulations and relative binding free energy calculations. The work yielded potent hits that bind to TNFα at its dimer interface. The mechanism targeted was inhibition of oligomerization of TNFα upon phytochemical binding to restrict its interaction with TNF-R1 receptor. MD simulation analysis resulted in identification of two phytochemicals that showed stable protein-ligand conformations over time. The two compounds were triterpenoids: Momordicilin and Nimbolin A with relative binding energy- calculated by MM/PBSA to be -190.5 kJ/Mol and -188.03 kJ/Mol respectively. Therefore, through this work it is being suggested that these phytochemicals can be used for further in vitro analysis to confirm their inhibitory action against TNFα or can be used as scaffolds to arrive at better drug candidates.

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Integrating High-Throughput Approaches and in vitro Human Trophoblast Models to Decipher Mechanisms Underlying Early Human Placenta Development

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.673065 ◽

2021 ◽

Vol 9 ◽

Author(s):

Bum-Kyu Lee ◽

Jonghwan Kim

Keyword(s):

High Throughput ◽

Human Placenta ◽

Molecular Mechanisms ◽

Molecular Level ◽

Cell Types ◽

Model Systems ◽

Extravillous Trophoblast ◽

Human Trophoblast ◽

Early Human

The placenta is a temporary but pivotal organ for human pregnancy. It consists of multiple specialized trophoblast cell types originating from the trophectoderm of the blastocyst stage of the embryo. While impaired trophoblast differentiation results in pregnancy disorders affecting both mother and fetus, the molecular mechanisms underlying early human placenta development have been poorly understood, partially due to the limited access to developing human placentas and the lack of suitable human in vitro trophoblast models. Recent success in establishing human trophoblast stem cells and other human in vitro trophoblast models with their differentiation protocols into more specialized cell types, such as syncytiotrophoblast and extravillous trophoblast, has provided a tremendous opportunity to understand early human placenta development. Unfortunately, while high-throughput research methods and omics tools have addressed numerous molecular-level questions in various research fields, these tools have not been widely applied to the above-mentioned human trophoblast models. This review aims to provide an overview of various omics approaches that can be utilized in the study of human in vitro placenta models by exemplifying some important lessons obtained from omics studies of mouse model systems and introducing recently available human in vitro trophoblast model systems. We also highlight some key unknown questions that might be addressed by such techniques. Integrating high-throughput omics approaches and human in vitro model systems will facilitate our understanding of molecular-level regulatory mechanisms underlying early human placenta development as well as placenta-associated complications.

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Amyloid fibril-based hydrogels for high-throughput tumor spheroid modeling

10.1101/2020.12.28.424634 ◽

2020 ◽

Author(s):

Namrata Singh ◽

Komal Patel ◽

Ambuja Navalkar ◽

Pradeep Kadu ◽

Debalina Datta ◽

...

Keyword(s):

Drug Resistance ◽

High Throughput ◽

Three Dimensional ◽

3D Cell Culture ◽

Cancer Therapeutics ◽

Cost Effective ◽

Cell Types ◽

Tumor Spheroid ◽

Tumor Modeling

AbstractBiomaterials mimicking extracellular matrices (ECM) for three-dimensional (3D) cultures have gained immense interest in tumor modeling and in vitro organ development. Here, we introduce versatile, thixotropic amyloid hydrogels as a bio-mimetic ECM scaffold for 3D cell culture as well as high-throughput tumor spheroid formation using a drop cast method. The unique cross-β-sheet structure, sticky surface, and thixotropicity of amyloid hydrogels allow robust cell adhesion, survival, proliferation, and migration, which are essential for 3D tumor modeling with various cancer cell types. The spheroids formed show overexpression of the signature cancer biomarkers and confer higher drug resistance compared to two-dimensional (2D) monolayer cultures. Using breast tumor tissue from mouse xenograft, we showed that these hydrogels support the formation of tumor spheroids with a well-defined necrotic core, cancer-associated gene expression, higher drug resistance, and tumor heterogeneity reminiscent of the original tumor. Altogether, we have developed a rapid and cost-effective platform for generating in vitro cancer models for the screening of anti-cancer therapeutics and developing personalized medicines.

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Development and Validation of a High-Throughput Intrinsic ATPase Activity Assay for the Discovery of MEKK2 Inhibitors

CrossRef Listing of Deleted DOIs ◽

10.1177/1087057112466430 ◽

2012 ◽

Vol 18 (4) ◽

pp. 388-399 ◽

Cited By ~ 10

Author(s):

Syed Ahmad ◽

Mark A. Hughes ◽

Gary L. Johnson ◽

John E. Scott

Keyword(s):

Atpase Activity ◽

High Throughput ◽

High Throughput Screening ◽

Selective Inhibition ◽

Mass Spectrometry Analysis ◽

Activity Assay ◽

Spectrometry Analysis ◽

Compound Libraries ◽

Atpase Assay

The kinase MEKK2 (MAP3K2) has recently been implicated in tumor growth and metastasis. Thus, selective inhibition of MEKK2 may be a novel strategy for cancer therapy. To identify inhibitors of MEKK2 kinase activity, we have developed a novel activity assay for MEKK2 based on the discovery that recombinant purified MEKK2 has intrinsic ATPase activity. This MEKK2 ATPase assay was validated for enzyme identity and enzymatic purity by multiple methods including mass spectrometry analysis, testing different sources of MEKK2 and comparing ATPase assay IC50 data for multiple inhibitors to literature values and to IC50 data generated using MEKK2 binding and transphosphorylation assays. Taken together, these data indicated that genuine MEKK2 activity was being measured in this assay and no other ATPases contributed to the signal. A miniaturized version of the assay was validated for high-throughput screening, and compound libraries were screened. The screening hits generated comparable potencies in the MEKK2 intrinsic ATPase, binding, and transphosphorylation assays. We identified a novel MEKK2 inhibitor and confirmed that crizotinib and bosutinib are potent in vitro inhibitors of MEKK2 activity with IC50 values of <100 nM. Thus, this assay has utility for the discovery of small-molecule inhibitors of MEKK2 activity.

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