ReviewNature protocols2026
Single microorganism RNA sequencing of microbiomes using smRandom-Seq.
Review in Nature protocols, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Spatial Total RNA Sequencing of Formalin-Fixed Paraffin-Embedded Tissue by spRandom-seq.Small (Weinheim an der Bergstrasse, Germany) · 2026Article
- A new paradigm of bidirectional regulation of the gut-spinal cord axis.Neural regeneration research · 2026Article
- A Microcapsule-Integrated smRandom-seq Platform Enables Fixation-Free Single Microbe RNA Sequencing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Microbial single-cell transcriptomics links gut microbiota functional states to metabolic changes in male mice.Nature communications · 2026Article
- From triangle to pyramid: Understanding host-pathogen-microniome-environment interplay for sustainable, enviromics-empowered management of plant diseases.Plant communications · 2026Review
- Microbial single-cell omics in situ.Cell genomics · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Bacteria colonize nearly every part of the human body and various environments, displaying remarkable diversity. Traditional population-level transcriptomics measurements provide only average population behaviors, often overlooking the heterogeneity within bacterial communities. To address this limitation, we have developed a droplet-based, high-throughput single-microorganism RNA sequencing method (smRandom-seq) that offers highly species specific and sensitive gene detection. Here we detail procedures for microbial sample preprocessing, in situ preindexed cDNA synthesis, in situ poly(dA) tailing, droplet barcoding, ribosomal RNA depletion and library preparation. The main smRandom-seq workflow, including sample processing, in situ reactions and library construction, takes ~2 days. This method features enhanced RNA coverage, reduced doublet rates and minimized ribosomal RNA contamination, thus enabling in-depth analysis of microbial heterogeneity. smRandom-seq is compatible with microorganisms from both laboratory cultures and complex microbial community samples, making it well suited for constructing single-microorganism transcriptomic atlases of bacterial strains and diverse microbial communities. This Protocol requires experience in molecular biology and RNA sequencing techniques, and it holds promising potential for researchers investigating bacterial resistance, microbiome heterogeneity and host-microorganism interactions.
Indexed as
Identifiers
40404925What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.