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人类组织衍生类器官的功能遗传工具包。

A functional genetic toolbox for human tissue-derived organoids.

机构信息

Wellcome Trust/CRUK Gurdon Institute, University of Cambridge, Cambridge, United Kingdom.

Developmental Biology and Cancer Development, University College London, London, United Kingdom.

出版信息

Elife. 2021 Oct 6;10:e67886. doi: 10.7554/eLife.67886.

Abstract

Human organoid systems recapitulate key features of organs offering platforms for modelling developmental biology and disease. Tissue-derived organoids have been widely used to study the impact of extrinsic niche factors on stem cells. However, they are rarely used to study endogenous gene function due to the lack of efficient gene manipulation tools. Previously, we established a human foetal lung organoid system (Nikolić et al., 2017). Here, using this organoid system as an example, we have systematically developed and optimised a complete genetic toolbox for use in tissue-derived organoids. This includes 'Organoid Easytag', our efficient workflow for targeting all types of gene loci through CRISPR-mediated homologous recombination followed by flow cytometry for enriching correctly targeted cells. Our toolbox also incorporates conditional gene knockdown or overexpression using tightly inducible CRISPR interference and CRISPR activation which is the first efficient application of these techniques to tissue-derived organoids. These tools will facilitate gene perturbation studies in tissue-derived organoids facilitating human disease modelling and providing a functional counterpart to many ongoing descriptive studies, such as the Human Cell Atlas Project.

摘要

人类类器官系统再现了器官的关键特征,为发育生物学和疾病建模提供了平台。组织来源的类器官已被广泛用于研究外在生态位因素对干细胞的影响。然而,由于缺乏有效的基因操作工具,它们很少用于研究内源性基因功能。此前,我们建立了人类胎儿肺类器官系统(Nikolić 等人,2017)。在这里,我们以这个类器官系统为例,系统地开发和优化了一套完整的遗传工具包,用于组织来源的类器官。这包括“类器官 Easytag”,我们通过 CRISPR 介导的同源重组靶向所有类型的基因座的高效工作流程,随后通过流式细胞术富集正确靶向的细胞。我们的工具包还包括使用紧密诱导的 CRISPR 干扰和 CRISPR 激活进行条件性基因敲低或过表达,这是这些技术在组织来源的类器官中的首次有效应用。这些工具将促进组织来源的类器官中的基因扰动研究,促进人类疾病建模,并为许多正在进行的描述性研究提供功能对应物,例如人类细胞图谱项目。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2f1b/8553336/5fc12ac0f82a/elife-67886-fig1.jpg

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