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  • 标题:A Simple Procedure for Creating Scalable Phenotypic Screening Assays in Human Neurons
  • 本地全文:下载
  • 作者:BanuPriya Sridharan ; Christopher Hubbs ; Nerea Llamosas
  • 期刊名称:Scientific Reports
  • 电子版ISSN:2045-2322
  • 出版年度:2019
  • 卷号:9
  • 期号:1
  • 页码:1-14
  • DOI:10.1038/s41598-019-45265-1
  • 出版社:Springer Nature
  • 摘要:Neurons created from human induced pluripotent stem cells (hiPSCs) provide the capability of identifying biological mechanisms that underlie brain disorders. IPSC-derived human neurons, or iNs, hold promise for advancing precision medicine through drug screening, though it remains unclear to what extent iNs can support early-stage drug discovery efforts in industrial-scale screening centers. Despite several reported approaches to generate iNs from iPSCs, each suffer from technological limitations that challenge their scalability and reproducibility, both requirements for successful screening assays. We addressed these challenges by initially removing the roadblocks related to scaling of iNs for high throughput screening (HTS)-ready assays. We accomplished this by simplifying the production and plating of iNs and adapting them to a freezer-ready format. We then tested the performance of freezer-ready iNs in an HTS-amenable phenotypic assay that measured neurite outgrowth. This assay successfully identified small molecule inhibitors of neurite outgrowth. Importantly, we provide evidence that this scalable iN-based assay was both robust and highly reproducible across different laboratories. These streamlined approaches are compatible with any iPSC line that can produce iNs. Thus, our findings indicate that current methods for producing iPSCs are appropriate for large-scale drug-discovery campaigns (i.e. >10e 5 compounds) that read out simple neuronal phenotypes. However, due to the inherent limitations of currently available iN differentiation protocols, technological advances are required to achieve similar scalability for screens that require more complex phenotypes related to neuronal function.
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