Evidence map›Paper›PMID 41180309›Full record

ReviewmLife2025

Profiling the heterogeneity of microbial populations and communities at the single-cell level.

Lu Wu, Wenlong Zuo, Zhaohui Cao, Zepeng Qu, Lei Dai

Abstract readReview
In one paragraph

Review in mLife, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Functional and ecological characterization ofFrontiers in microbiology · 2026
    Article
  4. Review
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.

Lu WuState Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences Shenzhen China.ORCID https://orcid.org/0000-0003-0690-5006
Wenlong ZuoState Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences Shenzhen China.
Zhaohui CaoState Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences Shenzhen China.
Zepeng QuState Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences Shenzhen China.
Lei DaiState Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences Shenzhen China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent advancements in single-cell genomic and transcriptomic sequencing, in situ sequencing, and molecular imaging-based technologies have facilitated the examination of heterogeneity within microbial communities at the single-cell level. These cutting-edge methodologies permit the capture of phenotypic and genotypic heterogeneity, as well as the spatial organization within microbial communities. This enables in-depth investigation into microbial dark matter, the evaluation of microbial responses to perturbations, and a comprehensive exploration of spatial functions involved in community assembly and social interactions within microbial communities. These interactions include inter-microbial relationships, bacteria-phage interactions, and host-microbe interactions. Here, we highlight the key technological breakthroughs achieved, elucidating the perspectives from which these technologies enable us to interpret microbial heterogeneity at the single-cell level. Additionally, we critically examine the limitations associated with these technologies. Furthermore, we explore how these methods could be combined and also their applications in future studies. The integration of these approaches holds great promise for increasing our understanding of the organization and function of microbes in complex ecosystems.

Indexed as

heterogeneitymicrobial populationssingle‐cell levelspatial

Identifiers

PMID41180309
PMCPMC12575089

What OpenQuestion holds

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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.