Single microorganism RNA sequencing of microbiomes using smRandom-Seq.

Area of Science:

• Microbiology
• Genomics
• Molecular Biology

Background:

• Bacteria exhibit significant diversity across various environments.
• Traditional transcriptomics methods average gene expression, masking individual microbial behaviors and heterogeneity.
• Understanding microbial heterogeneity is crucial for fields like microbiome research and infectious disease.

Purpose of the Study:

• To introduce a novel droplet-based, high-throughput single-microorganism RNA sequencing (smRandom-seq) method.
• To provide detailed protocols for implementing smRandom-seq for microbial sample analysis.
• To enable in-depth investigation of microbial heterogeneity at the single-cell level.

Main Methods:

• Developed a droplet-based, high-throughput single-microorganism RNA sequencing (smRandom-seq) protocol.
• Procedures include microbial sample preprocessing, in situ preindexed cDNA synthesis, in situ poly(dA) tailing, droplet barcoding, ribosomal RNA depletion, and library preparation.
• The entire workflow, from sample processing to library construction, is completed in approximately 2 days.

Main Results:

• smRandom-seq achieves highly species-specific and sensitive gene detection.
• The method demonstrates enhanced RNA coverage, reduced doublet rates, and minimized ribosomal RNA contamination.
• Successfully applied to both laboratory cultures and complex microbial community samples.

Conclusions:

• smRandom-seq offers a powerful tool for constructing single-microorganism transcriptomic atlases.
• This method facilitates detailed analysis of microbial heterogeneity in diverse settings.
• It holds significant potential for research in bacterial resistance, microbiome complexity, and host-microorganism interactions.