ReviewmLife2025
Profiling the heterogeneity of microbial populations and communities at the single-cell level.
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.
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
4 citing papers in PubMed.
- Phenotypic heterogeneity in the human gut microbiome revealed by subspecies-resolution single-cell transcriptomics.bioRxiv : the preprint server for biology · 2026Article
- Epigenetic regulation and antimicrobial resistance: functional roles of DNA methylation.FEMS microbiology reviews · 2026Review
- Functional and ecological characterization ofFrontiers in microbiology · 2026Article
- Profiling the heterogeneity of microbial populations and communities at the single-cell level.mLife · 2025Review
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
No grant is acknowledged in the PubMed record.
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
Identifiers
What 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.