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gUMI-BEAR,一种模块化、无监督的群体条形码方法,可高分辨率追踪变体和进化。

gUMI-BEAR, a modular, unsupervised population barcoding method to track variants and evolution at high resolution.

机构信息

Department of Biomolecular Sciences, Weizmann Institute of Science Rehovot, Rehovot, Israel.

Life Sciences Core Facilities, Weizmann Institute of Science Rehovot, Rehovot, Israel.

出版信息

PLoS One. 2023 Jun 7;18(6):e0286696. doi: 10.1371/journal.pone.0286696. eCollection 2023.

Abstract

Cellular lineage tracking provides a means to observe population makeup at the clonal level, allowing exploration of heterogeneity, evolutionary and developmental processes and individual clones' relative fitness. It has thus contributed significantly to understanding microbial evolution, organ differentiation and cancer heterogeneity, among others. Its use, however, is limited because existing methods are highly specific, expensive, labour-intensive, and, critically, do not allow the repetition of experiments. To address these issues, we developed gUMI-BEAR (genomic Unique Molecular Identifier Barcoded Enriched Associated Regions), a modular, cost-effective method for tracking populations at high resolution. We first demonstrate the system's application and resolution by applying it to track tens of thousands of Saccharomyces cerevisiae lineages growing together under varying environmental conditions applied across multiple generations, revealing fitness differences and lineage-specific adaptations. Then, we demonstrate how gUMI-BEAR can be used to perform parallel screening of a huge number of randomly generated variants of the Hsp82 gene. We further show how our method allows isolation of variants, even if their frequency in the population is low, thus enabling unsupervised identification of modifications that lead to a behaviour of interest.

摘要

细胞谱系追踪提供了一种在克隆水平上观察种群构成的方法,允许探索异质性、进化和发育过程以及个体克隆的相对适应性。因此,它为理解微生物进化、器官分化和癌症异质性等做出了重要贡献。然而,它的使用受到限制,因为现有的方法具有高度特异性、昂贵、劳动强度大,而且关键是不能重复实验。为了解决这些问题,我们开发了 gUMI-BEAR(基因组独特分子标识符条形码富集相关区域),这是一种用于以高分辨率跟踪种群的模块化、具有成本效益的方法。我们首先通过将其应用于跟踪在不同环境条件下共同生长的数万株酿酒酵母谱系来展示该系统的应用和分辨率,这些条件跨越多个世代施加,揭示了适应性和谱系特异性适应性的差异。然后,我们展示了 gUMI-BEAR 如何用于对 Hsp82 基因的大量随机生成变体进行并行筛选。我们进一步展示了我们的方法如何允许分离变体,即使它们在种群中的频率很低,从而能够在没有监督的情况下识别导致感兴趣行为的修饰。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a8d5/10246843/3a86c1e80874/pone.0286696.g001.jpg

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