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测序免疫检测可实现细胞的大规模高维表型分析。

Immuno-detection by sequencing enables large-scale high-dimensional phenotyping in cells.

机构信息

Department of Molecular Developmental Biology, Radboud Institute for Molecular Life Sciences, Radboud University, PO Box 9101, 6500 HB, Nijmegen, The Netherlands.

Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, PO Box 9101, 6500 HB, Nijmegen, The Netherlands.

出版信息

Nat Commun. 2018 Jun 19;9(1):2384. doi: 10.1038/s41467-018-04761-0.

DOI:10.1038/s41467-018-04761-0
PMID:29921844
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6008431/
Abstract

Cell-based small molecule screening is an effective strategy leading to new medicines. Scientists in the pharmaceutical industry as well as in academia have made tremendous progress in developing both large-scale and smaller-scale screening assays. However, an accessible and universal technology for measuring large numbers of molecular and cellular phenotypes in many samples in parallel is not available. Here we present the immuno-detection by sequencing (ID-seq) technology that combines antibody-based protein detection and DNA-sequencing via DNA-tagged antibodies. We use ID-seq to simultaneously measure 70 (phospho-)proteins in primary human epidermal stem cells to screen the effects of ~300 kinase inhibitor probes to characterise the role of 225 kinases. The results show an association between decreased mTOR signalling and increased differentiation and uncover 13 kinases potentially regulating epidermal renewal through distinct mechanisms. Taken together, our work establishes ID-seq as a flexible solution for large-scale high-dimensional phenotyping in fixed cell populations.

摘要

基于细胞的小分子筛选是一种有效的策略,可以产生新的药物。制药行业和学术界的科学家在开发大规模和小规模筛选测定方面都取得了巨大的进展。然而,目前还没有一种可用于平行测量大量分子和细胞表型的通用技术。在这里,我们介绍了免疫检测测序(ID-seq)技术,该技术结合了基于抗体的蛋白质检测和通过 DNA 标记抗体的 DNA 测序。我们使用 ID-seq 同时测量原代人表皮干细胞中的 70 种(磷酸化)蛋白,以筛选约 300 种激酶抑制剂探针的作用,从而鉴定 225 种激酶的作用。结果表明,mTOR 信号的降低与分化的增加有关,并揭示了 13 种激酶可能通过不同的机制调节表皮更新。总之,我们的工作确立了 ID-seq 作为固定细胞群体中大规模高维表型分析的一种灵活解决方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03a8/6008431/81780599d944/41467_2018_4761_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03a8/6008431/954f417923fc/41467_2018_4761_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03a8/6008431/83ccf63009c3/41467_2018_4761_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03a8/6008431/d81c76a99024/41467_2018_4761_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03a8/6008431/5e424ee4740e/41467_2018_4761_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03a8/6008431/927f4e94fc56/41467_2018_4761_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03a8/6008431/81780599d944/41467_2018_4761_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03a8/6008431/954f417923fc/41467_2018_4761_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03a8/6008431/83ccf63009c3/41467_2018_4761_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03a8/6008431/d81c76a99024/41467_2018_4761_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03a8/6008431/5e424ee4740e/41467_2018_4761_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03a8/6008431/927f4e94fc56/41467_2018_4761_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03a8/6008431/81780599d944/41467_2018_4761_Fig6_HTML.jpg

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