Transcriptomic profiling of individual bacteria by MATQ-seq

Abstract

Bacterial single-cell transcriptomics is revolutionizing our understanding of cell-to-cell variation within bacterial populations and enables gene expression profiling in complex microbial communities. Using the eukaryotic multiple annealing and dC-tailing-based quantitative single-cell RNA-sequencing (scRNA-seq) (MATQ-seq) approach, we have developed a robust bacterial scRNA-seq protocol, which integrates index sorting, random priming and rRNA depletion. This method stands out for its high rate of cell retention and its suitability for experiments with limited input material, offering a reliable method even for small sample sizes. Here we provide a step-by-step protocol covering the entire process of generating single-bacteria transcriptomes, including experimental and computational analysis. It involves (i) single-cell isolation via fluorescence-activated cell sorting (FACS) and cell lysis, (ii) reverse transcription and cDNA amplification using robotic liquid handling, (iii) rRNA depletion, (iv) indexing and sequencing, and (v) data processing steps to start comprehensive data analysis. Using model organisms such as Salmonella enterica, we show that the method achieves a retention rate of 95%, defined as the rate of initially sorted cells converted into effective sequencing libraries. This substantially surpasses other available protocols. The method robustly detects 300–600 genes per cell, highlighting its effectiveness in capturing a broad transcriptomic profile. The entire procedure from FACS-based single-cell isolation to raw data generation spans ~5 d. As MATQ-seq has already been proven robust in several bacterial species, it holds promise for the establishment of a streamlined microbial scRNA-seq platform.