基因编码荧光条形码允许单细胞分析通过光谱流式细胞术

IF 3.9 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Xiaoming Lu, Daniel J. Pritko, Megan E. Abravanel, Jonah R. Huggins, Oluwaferanmi Ogunleye, Tirthankar Biswas, Katia C. Ashy, Semaj K. Woods, Mariclaire W.T. Livingston, Mark A. Blenner* and Marc R. Birtwistle*, 
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引用次数: 0

摘要

基因编码的单细胞条形码在谱系追踪或基因筛选等实验任务中广泛使用。对于此类应用,条形码库理想地具有高多样性(许多独特的条形码)、非破坏性识别(在同一细胞或群体中重复测量)以及快速、廉价的读出(许多细胞和条件)。目前的核酸条形码方法具有较高的多样性,但需要破坏性且读取速度慢/昂贵;目前的荧光条形码方法具有无损、快速和廉价的读取方法,但缺乏较高的多样性。我们最近提出了一种关于荧光蛋白组合如何产生具有无损、快速和廉价识别的高多样性条形码库的理论。在这里,我们提出了一个初步的实验概念验证,通过18种荧光蛋白的双向组合生成约150个条形码库,其中61个进行了实验测试。我们使用了一种混合克隆策略来生成条形码库,该库被验证包含了18种荧光蛋白的每种可能组合。使用单个哺乳动物细胞和光谱流式细胞术的实验结果表明,除了mTFP1和大多数评估条形码外,单个荧光蛋白的分类性能优异,许多真阳性率为99%。该文库兼容数百个基因(或基因对)的遗传筛选和数百个克隆的谱系追踪。这项工作为从数百个光谱可分辨串联荧光蛋白探针生成更大的多样性文库(可能为~ 105个或更多)奠定了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Genetically Encoded Fluorescence Barcodes Allow for Single-Cell Analysis via Spectral Flow Cytometry

Genetically Encoded Fluorescence Barcodes Allow for Single-Cell Analysis via Spectral Flow Cytometry

Genetically encoded, single-cell barcodes are broadly useful for experimental tasks such as lineage tracing or genetic screens. For such applications, a barcode library would ideally have high diversity (many unique barcodes), nondestructive identification (repeated measurements in the same cells or population), and fast, inexpensive readout (many cells and conditions). Current nucleic acid barcoding methods generate high diversity but require destructive and slow/expensive readout, and current fluorescence barcoding methods are nondestructive, fast, and inexpensive to readout but lack high diversity. We recently proposed a theory for how fluorescent protein combinations may generate a high-diversity barcode library with nondestructive, fast, and inexpensive identification. Here, we present an initial experimental proof-of-concept by generating a library of ∼150 barcodes from two-way combinations of 18 fluorescent proteins, 61 of which are tested experimentally. We use a pooled cloning strategy to generate a barcode library that is validated to contain every possible combination of the 18 fluorescent proteins. Experimental results using single mammalian cells and spectral flow cytometry demonstrate excellent classification performance of individual fluorescent proteins, with the exception of mTFP1, and of most evaluated barcodes, with many true positive rates >99%. The library is compatible with genetic screening for hundreds of genes (or gene pairs) and lineage tracing hundreds of clones. This work lays a foundation for greater diversity libraries (potentially ∼105 and more) generated from hundreds of spectrally resolvable tandem fluorescent protein probes.

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来源期刊
CiteScore
8.00
自引率
10.60%
发文量
380
审稿时长
6-12 weeks
期刊介绍: The journal is particularly interested in studies on the design and synthesis of new genetic circuits and gene products; computational methods in the design of systems; and integrative applied approaches to understanding disease and metabolism. Topics may include, but are not limited to: Design and optimization of genetic systems Genetic circuit design and their principles for their organization into programs Computational methods to aid the design of genetic systems Experimental methods to quantify genetic parts, circuits, and metabolic fluxes Genetic parts libraries: their creation, analysis, and ontological representation Protein engineering including computational design Metabolic engineering and cellular manufacturing, including biomass conversion Natural product access, engineering, and production Creative and innovative applications of cellular programming Medical applications, tissue engineering, and the programming of therapeutic cells Minimal cell design and construction Genomics and genome replacement strategies Viral engineering Automated and robotic assembly platforms for synthetic biology DNA synthesis methodologies Metagenomics and synthetic metagenomic analysis Bioinformatics applied to gene discovery, chemoinformatics, and pathway construction Gene optimization Methods for genome-scale measurements of transcription and metabolomics Systems biology and methods to integrate multiple data sources in vitro and cell-free synthetic biology and molecular programming Nucleic acid engineering.
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