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

Abstract

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.