Uniform pre-processing of bacterial single-cell RNA-seq

Bacteria are highly heterogeneous, even under controlled conditions, making single-cell RNA sequencing (scRNA-seq) essential for studying microbial diversity and symbiosis. Since its first application in 2015, bacterial scRNA-seq has expanded, but different assays depend on distinct, custom, in-house pre-processing making it difficult to analyze data as part of a unified workflow. The kallisto-bustools suite of tools has enabled uniform pre-processing of eukaryotic scRNA-seq while also reducing time and resource demands for pre-processing, but is not optimized for bacterial scRNA-seq. We adapt kallisto-bustools to be suitable for reads generated from operons, as well as for a much shorter gene length distribution, and show that it can efficiently and accurately quantify bacterial scRNA-seq. Our work provides a scalable foundation for uniform pre-processing of microbial single-cell transcriptomics.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2025-12-06
DOI
https://doi.org/10.64898/2025.12.04.692398
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
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article

Uniform pre-processing of bacterial single-cell RNA-seq

Lior Pachter, Vera Beilinson, Margaret McFall‐Ngai, Conrad Oakes
bioRxiv (Cold Spring Harbor Laboratory)
Single-cell and spatial transcriptomics
article

Uniform pre-processing of bacterial single-cell RNA-seq

Lior Pachter, Vera Beilinson, Margaret McFall‐Ngai, Conrad Oakes
article en

Abstract

Bacteria are highly heterogeneous, even under controlled conditions, making single-cell RNA sequencing (scRNA-seq) essential for studying microbial diversity and symbiosis. Since its first application in 2015, bacterial scRNA-seq has expanded, but different assays depend on distinct, custom, in-house pre-processing making it difficult to analyze data as part of a unified workflow. The kallisto-bustools suite of tools has enabled uniform pre-processing of eukaryotic scRNA-seq while also reducing time and resource demands for pre-processing, but is not optimized for bacterial scRNA-seq. We adapt kallisto-bustools to be suitable for reads generated from operons, as well as for a much shorter gene length distribution, and show that it can efficiently and accurately quantify bacterial scRNA-seq. Our work provides a scalable foundation for uniform pre-processing of microbial single-cell transcriptomics.

bioRxiv (Cold Spring Harbor Laboratory)
California Institute of Technology (US), Carnegie Observatories (US)
Openalex Percentile: Top 65%
Single-cell and spatial transcriptomics
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