CleanBar: A versatile demultiplexing tool for split-and-pool barcoding in single-cell omics

Data availability: The sequencing data are available at NCBI with BioProject ID: PRJNA1199928. The CleanBar program source code and test files coming from the same sequence dataset are available at the GitHub repository https://github.com/tbcgit/cleanbar The complete FASTQ outputs of the CleanBar pr...

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Autores: Arnau, Vicente, Ortiz-Maiques, Alicia, Valero Tebar, Juan, Mora-Quilis, Lucas, Kurmauskaite, Vaida, Campos Dopazo, Lorea, Domingo-Calap, Pilar, Džunková, Mária
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2025
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/404950
Acceso en línea:http://hdl.handle.net/10261/404950
Access Level:acceso abierto
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dc.title.none.fl_str_mv CleanBar: A versatile demultiplexing tool for split-and-pool barcoding in single-cell omics
title CleanBar: A versatile demultiplexing tool for split-and-pool barcoding in single-cell omics
spellingShingle CleanBar: A versatile demultiplexing tool for split-and-pool barcoding in single-cell omics
Arnau, Vicente
title_short CleanBar: A versatile demultiplexing tool for split-and-pool barcoding in single-cell omics
title_full CleanBar: A versatile demultiplexing tool for split-and-pool barcoding in single-cell omics
title_fullStr CleanBar: A versatile demultiplexing tool for split-and-pool barcoding in single-cell omics
title_full_unstemmed CleanBar: A versatile demultiplexing tool for split-and-pool barcoding in single-cell omics
title_sort CleanBar: A versatile demultiplexing tool for split-and-pool barcoding in single-cell omics
dc.creator.none.fl_str_mv Arnau, Vicente
Ortiz-Maiques, Alicia
Valero Tebar, Juan
Mora-Quilis, Lucas
Kurmauskaite, Vaida
Campos Dopazo, Lorea
Domingo-Calap, Pilar
Džunková, Mária
author Arnau, Vicente
author_facet Arnau, Vicente
Ortiz-Maiques, Alicia
Valero Tebar, Juan
Mora-Quilis, Lucas
Kurmauskaite, Vaida
Campos Dopazo, Lorea
Domingo-Calap, Pilar
Džunková, Mária
author_role author
author2 Ortiz-Maiques, Alicia
Valero Tebar, Juan
Mora-Quilis, Lucas
Kurmauskaite, Vaida
Campos Dopazo, Lorea
Domingo-Calap, Pilar
Džunková, Mária
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Generalitat Valenciana
Ministerio de Ciencia, Innovación y Universidades (España)
Agencia Estatal de Investigación (España)
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
description Data availability: The sequencing data are available at NCBI with BioProject ID: PRJNA1199928. The CleanBar program source code and test files coming from the same sequence dataset are available at the GitHub repository https://github.com/tbcgit/cleanbar The complete FASTQ outputs of the CleanBar program (individual FASTQ files containing 4 barcodes and the FASTQ files with 2 or 3 barcodes), as well as the R script for generating raw figures with the corresponding source files are available for download from the repository of University of Valencia https://nuvol.uv.es/owncloud/index.php/s/pSpjXkmx7EW8Oum
publishDate 2025
dc.date.none.fl_str_mv 2025
2025
2025
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http://purl.org/coar/resource_type/c_6501
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info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RYC2019-028015-I
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-112835RA-I00
https://doi.org/10.1093/ismeco/ycaf134
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dc.publisher.none.fl_str_mv Oxford University Press
publisher.none.fl_str_mv Oxford University Press
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spelling CleanBar: A versatile demultiplexing tool for split-and-pool barcoding in single-cell omicsArnau, VicenteOrtiz-Maiques, AliciaValero Tebar, JuanMora-Quilis, LucasKurmauskaite, VaidaCampos Dopazo, LoreaDomingo-Calap, PilarDžunková, MáriaData availability: The sequencing data are available at NCBI with BioProject ID: PRJNA1199928. The CleanBar program source code and test files coming from the same sequence dataset are available at the GitHub repository https://github.com/tbcgit/cleanbar The complete FASTQ outputs of the CleanBar program (individual FASTQ files containing 4 barcodes and the FASTQ files with 2 or 3 barcodes), as well as the R script for generating raw figures with the corresponding source files are available for download from the repository of University of Valencia https://nuvol.uv.es/owncloud/index.php/s/pSpjXkmx7EW8OumSplit-and-pool barcoding generates thousands of unique barcode strings through sequential ligations in 96-well plates, making single-cell omics more accessible, thus advancing microbial ecology, particularly in studies of bacterial interactions with plasmids and bacteriophages. While the wet-lab aspects of the split-and-pool barcoding are well-documented, no universally applicable bioinformatic tool exists for demultiplexing single cells barcoded with this approach. We present CleanBar (https://github.com/tbcgit/cleanbar), a flexible tool for demultiplexing reads tagged with sequentially ligated barcodes, accommodating variations in barcode positions and linker lengths while preventing misclassification of natural barcode-like sequences and handling diverse ligation errors. It also provides statistics useful for optimizing laboratory procedures. We demonstrate CleanBar’s performance with the Atrandi platform for microbial single-cell genomics, coupled with PacBio sequencing, to reach a cell throughput comparable with traditional bulk metagenomics, but overcoming its limitations in studying phage-bacteria interactions. In four Klebsiella strains infected with their corresponding phages and a control phage, the single-cell genomics revealed infection heterogeneity and enabled phage copy number estimation per cell. By combining efficiency, adaptability, and precision, CleanBar, when applied to the Atrandi split-and-pool barcoding platform and PacBio sequencing, serves as a powerful high-throughput tool for advancing microbial single-cell genomics and understanding microbial ecology and evolution.M.D. received funding from the Generalitat Valenciana programs Gen-T (grant number CDEIGENT/2021/008) and Investigo (grant number INVEST/2023/173), and from the Spanish Ministry of Science, Innovation and Universities MCIN/AEI/10.13039/501100011033 (grant number PID2022-136298NA-I00). P.D.C. was supported by a Ramón y Cajal contract RYC2019–028015-I funded by MCIN/AEI/10.13039/501100011033, ESF Invest in your future, project PID2020-112835RA-I00 funded by MCIN/AEI/10.13039/501100011033, and project SEJIGENT/2021/014 funded by Conselleria d’Innovació, Universitats, Ciència i Societat Digital (Generalitat Valenciana). L.M.Q. was funded by a PhD fellowship from Spanish MCIU FPU19/04611. J.V.T. was funded by Generalitat Valenciana PhD fellowship CIACIF/2023/109.Peer reviewedOxford University PressGeneralitat ValencianaMinisterio de Ciencia, Innovación y Universidades (España)Agencia Estatal de Investigación (España)Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202520252025info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Publisher's versioninfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10261/404950reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE##PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2022-136298NA-I00info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RYC2019-028015-Iinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-112835RA-I00https://doi.org/10.1093/ismeco/ycaf134Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/4049502026-05-22T06:33:51Z
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