Evidence map›Paper›PMID 40404925›Full record

ReviewNature protocols2026

Single microorganism RNA sequencing of microbiomes using smRandom-Seq.

Ziye Xu, Yuting Wang, Wenjie Cai, Yu Chen, Yongcheng Wang

Abstract readReview
PubMed Publisher
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Ziye Xu *Department of Laboratory Medicine of The First Affiliated Hospital and Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, China.
Yuting Wang *College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.
Wenjie Cai *Department of Laboratory Medicine of The First Affiliated Hospital and Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, China.
Yu ChenDepartment of Laboratory Medicine of The First Affiliated Hospital and Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, China.
Yongcheng WangDepartment of Laboratory Medicine of The First Affiliated Hospital and Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, China. yongcheng@zju.edu.cn.ORCID 0000-0003-2820-4243

Funding

China Postdoctoral Science FoundationKey R&D Program of ZhejiangLeading Innovative and Entrepreneur Team Introduction Program of ZhejiangNational Natural Science Foundation of China (National Science Foundation of China) 32200073National Natural Science Foundation of China (National Science Foundation of China) 32250710678National Natural Science Foundation of China (National Science Foundation of China) 82200977Space Medical Experiment Project of China Manned Space ProgramState Key Laboratory of Space Medicine, China Astronaut Research and Training CenterZhejiang Province
6 · The paper itself

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

BacteriaHigh-Throughput Nucleotide SequencingMicrobiotaRNA, BacterialSequence Analysis, RNAGene LibraryHumansRNA, Bacterial

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.