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

Area of Science:

• Microbiology
• Bioinformatics
• Genomics

Background:

• Bacteria exhibit significant heterogeneity, necessitating single-cell RNA sequencing (scRNA-seq) for microbial diversity and symbiosis studies.
• Existing bacterial scRNA-seq methods lack unified preprocessing, hindering data integration and analysis.
• Current tools like kallisto-bustools are optimized for eukaryotes, not bacteria.

Purpose of the Study:

• To adapt the kallisto-bustools pipeline for efficient and accurate bacterial scRNA-seq data preprocessing.
• To establish a scalable foundation for unified analysis of microbial single-cell transcriptomics.

Main Methods:

• Modified kallisto-bustools to accommodate bacterial operons and shorter gene length distributions.
• Evaluated the efficiency and accuracy of the adapted tool for bacterial scRNA-seq quantification.

Main Results:

• The adapted kallisto-bustools efficiently and accurately quantifies bacterial scRNA-seq data.
• The modified pipeline is suitable for reads generated from operons and shorter gene lengths.

Conclusions:

• The adapted kallisto-bustools offers a scalable and unified solution for bacterial scRNA-seq preprocessing.
• This work facilitates more standardized and accessible analysis of microbial single-cell transcriptomics.