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


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2023
Historique:
received: 12 03 2023
accepted: 19 05 2023
medline: 9 6 2023
pubmed: 7 6 2023
entrez: 7 6 2023
Statut: epublish

Résumé

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.

Identifiants

pubmed: 37285353
doi: 10.1371/journal.pone.0286696
pii: PONE-D-23-06106
pmc: PMC10246843
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0286696

Informations de copyright

Copyright: © 2023 Rezenman et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

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Auteurs

Shahar Rezenman (S)

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

Maor Knafo (M)

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

Ivgeni Tsigalnitski (I)

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

Shiri Barad (S)

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

Ghil Jona (G)

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

Dikla Levi (D)

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

Orly Dym (O)

The Dana and Yossie Hollander Center for Structural Proteomics, Weizmann Institute of Science Rehovot, Rehovot, Israel.

Ziv Reich (Z)

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

Ruti Kapon (R)

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

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