Dataset Information

Phenotypic quantitative high throughput screening with Caenorhabditis elegans

ABSTRACT: Quantitative high throughput screening (qHTS) pharmacologically evaluates libraries of drugs and investigational agents for potential therapeutic uses, toxicological risk assessment, and increasingly for academic chemical tool discovery. Phenotypic HTS assays aim to interrogate molecular pathways and networks, often relying on cell culture systems, historically with less emphasis on multicellular organisms. C. elegans has served as a powerful eukaryotic model organism for human biology and disease by virtue of genetic conservation and experimental tractability, as well as a surrogate for infectious parasitic nematodes. Here we describe a paradigm to enable C. elegans in qHTS using 384-well microtiter plate laser scanning cytometry for rapid signal acquisition with concurrent quantification of the fluorescent protein-encoded phenotype. E. coli ghost capsules are used as a non-replicating nutrient source to allow compound titration exposures over the full 7-day life cycle to mitigate complications from bacterial overgrowth. We demonstrate the method using 643 anti-infective biased agents tested in 7-pt titration to assess feasibility of nematode-based in vivo qHTS. A pharmacological profile from the primary screen confirmed the efficacy of known anti-parasitic molecules, such as ivermectin and levamisole as well as illuminating anthelmintic properties of general chemical classes, including -secretase, bromodomain and proteasome inhibitors. We anticipate a broader application of laser scanning cytometry-based qHTS will enable the analysis of C. elegans orthologous transgenic phenotypes of human pathologies to facilitate drug discovery for a range of therapeutic indications.

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Caenorhabditis Elegans

TISSUE(S): Cell Culture

SUBMITTER: Dingyin Tao

LAB HEAD: Dingyin Tao

PROVIDER: PXD027733 | Pride | 2023-05-30

REPOSITORIES: Pride

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In vivo quantitative high-throughput screening for drug discovery and comparative toxicology.

Dranchak Patricia K PK Oliphant Erin E Queme Bryan B Lamy Laurence L Wang Yuhong Y Huang Ruili R Xia Menghang M Tao Dingyin D Inglese James J

Disease models & mechanisms 20230320 3

Quantitative high-throughput screening (qHTS) pharmacologically evaluates chemical libraries for therapeutic uses, toxicological risk and, increasingly, for academic probe discovery. Phenotypic high-throughput screening assays interrogate molecular pathways, often relying on cell culture systems, historically less focused on multicellular organisms. Caenorhabditis elegans has served as a eukaryotic model organism for human biology by virtue of genetic conservation and experimental tractability. ...[more]

PMID: 36786055

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Project description:Quantitative high-throughput screening (qHTS) pharmacologically evaluates libraries of drugs and investigational agents for potential therapeutic uses, toxicological risk assessment, and increasingly for academic chemical tool discovery. Phenotypic HTS assays aim to interrogate molecular pathways and networks, often relying on cell culture systems, historically with less emphasis on multicellular organisms. C. elegans has served as a powerful eukaryotic model organism for human biology and disease by virtue of genetic conservation and experimental tractability. Here we describe a paradigm to enable C. elegans in qHTS using 384-well microtiter plate laser scanning cytometry for rapid signal acquisition with concurrent quantification of the fluorescent protein-expressing organism to select phenotype-modifying compounds for subsequent life-stage and proteomic analysis. E. coli bacterial ghosts, a non-replicating nutrient, allow compound exposures over 7-days spanning two life cycles to mitigate complications from bacterial overgrowth. We demonstrate the method using 643 anti-infective biased agents tested in 7-pt titration to assess feasibility of nematode-based in vivo qHTS. A pharmacological profile from the primary screen confirmed the efficacy of known anti-parasitic molecules, such as ivermectin and levamisole as well as illuminating anthelmintic properties of general chemical classes, including MEK, -secretase, bromodomain and proteasome inhibitors. Subsequent life-stage and proteomics analysis helped elucidate the physiologic consequence of specific compounds on C. elegans viability. For example, bortezomib induced a parallel upregulation of core proteasome subunits and the transcription factor skn-1-activating DDI aspartyl protease, while the kinase inhibitor trametinib upregulated the C. elegans MEK-1 ortholog, Mnk-1, downstream aminoacyl tRNA synthetases and ribosomal survival pathway proteins. We anticipate a broader application of this qHTS-coupled proteomics approach will enable the analysis of C. elegans orthologous transgenic phenotypes of human pathologies to facilitate drug and probe profiling from high-impact chemical libraries for a range of therapeutic indications.

Project description:Understanding the cellular heterogeneity and lineage potential of human bone marrow hematopoietic progenitors is required to understand normal differentiation and the mechanisms of hematological disease. Central to this objective are protocols that enable the delineation, isolation and functional characterization or known and novel cell populations, which are traditionally empowered by flow cytometry. Recognizing the need for tackling cellular heterogeneity, we have designed a use case for compiling next-generation processing methods via existing and highly curated single-cell interrogation technologies. Multi-omics approaches, such as Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq), enable concurrent transcriptomic and immunophenotyping at a single-cell level but necessitate precision antibody titration mixes that can be directly integrated with parallel flow cytometry strategies. To bridge this gap, we performed a molecular titration of 266 antibodies using primary human bone marrow cells spanning race and sex to approximate diversity. Through machine learning and user curation, we created an optimized titrated bone marrow CITE-seq panel of 132 antibodies. Multimodal integration of these data using a game-theory driven approach, improved our ability to resolve new stable stem, progenitor, and transitional cell populations, readily defined by unique RNA and ADT markers. Leveraging complexity-matching high-dimensional flow cytometry (pyInfinityFlow), we consolidated the findings from CITE-seq and subsequently developed novel isolation strategies for maturing granulocytes, late-stage erythroid progenitors and improved purification of megakaryocyte/erythrocyte progenitors (MEP). Finally, we integrated CITE-seq with flow cytometry data from matching donors, successfully identified 37 cell surface markers consistently expressed across donors and technologies. The compiled bone marrow cell atlas serves as an advanced digital analytical resource for progenitor analyses in health and disease.

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