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

Split-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 asp...

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Detalles Bibliográficos
Autores: Arnau, Vicente, Ortiz-Maiques, Alicia, Valero-Tebar, Juan, Mora-Quilis, Lucas, Kurmauskaite, Vaida, Campos Dopazo, Lorea, Domingo-Calap, Pilar, Dzunkova, Maria
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2025
País:España
Institución:Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunitat Valenciana (FISABIO)
Repositorio:r-FISABIO. Repositorio Institucional de Producción Científica
OAI Identifier:oai:dnet:r-fisabio___::36ee26c51de2a69e9a5cdf3bd34afaea
Acceso en línea:https://fisabio.portalinvestigacion.com/publicaciones/20938
Access Level:acceso abierto
Palabra clave:split-and-pool barcoding
microbial single-cell genomics
phage-bacteria interactions
demultiplexing
Atrandi
PacBio
Descripción
Sumario:Split-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.