ReviewFrontiers in microbiology2016
Tracking Strains in the Microbiome: Insights from Metagenomics and Models.
Review in Frontiers in microbiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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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.
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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.
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Who cites it
33 citing papers in PubMed.
- Citywide metagenomic surveillance of food centres reveals local microbial signatures and antibiotic resistance gene enrichment.npj antimicrobials and resistance · 2025Article
- Genomic evidence for flies as carriers of zoonotic pathogens on dairy farms.NPJ biofilms and microbiomes · 2025Article
- Shared environments complicate the use of strain-resolved metagenomics to infer microbiome transmission.Microbiome · 2025Article
- Analysis of metagenomic data.Nature reviews. Methods primers · 2025Article
- Shared environments complicate the use of strain-resolved metagenomics to infer microbiome transmission.bioRxiv : the preprint server for biology · 2024Article
- Mora: abundance aware metagenomic read re-assignment for disentangling similar strains.BMC bioinformatics · 2024Article
- The composition of the bacterial communities collected from the PMScientific reports · 2024Article
- Ecology and evolution of the social microbiome.Annual review of ecology, evolution, and systematics · 2024Article
- Investigation of bacterial and fungal population structure on environmental surfaces of three medical institutions during the COVID-19 pandemic.Frontiers in microbiology · 2023Article
- Infant gut strain persistence is associated with maternal origin, phylogeny, and traits including surface adhesion and iron acquisition.Cell reports. Medicine · 2021Article
- Article
- inStrain profiles population microdiversity from metagenomic data and sensitively detects shared microbial strains.Nature biotechnology · 2021Article
- Challenges, Strategies, and Perspectives for Reference-Independent Longitudinal Multi-Omic Microbiome Studies.Frontiers in genetics · 2021Article
- Toward Accurate and Robust Environmental Surveillance Using Metagenomics.Frontiers in genetics · 2021Article
- Digital microbiology.Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2020Review
- Understanding the impact of antibiotic perturbation on the human microbiome.Genome medicine · 2020Review
- Microbial transmission in animal social networks and the social microbiome.Nature ecology & evolution · 2020Review
- Exploring neighborhoods in large metagenome assembly graphs using spacegraphcats reveals hidden sequence diversity.Genome biology · 2020Article
- Zebrafish microbiome studies make waves.Lab animal · 2020Review
- Construction of habitat-specific training sets to achieve species-level assignment in 16S rRNA gene datasets.Microbiome · 2020Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Transmission usually refers to the movement of pathogenic organisms. Yet, commensal microbes that inhabit the human body also move between individuals and environments. Surprisingly little is known about the transmission of these endogenous microbes, despite increasing realizations of their importance for human health. The health impacts arising from the transmission of commensal bacteria range widely, from the prevention of autoimmune disorders to the spread of antibiotic resistance genes. Despite this importance, there are outstanding basic questions: what is the fraction of the microbiome that is transmissible? What are the primary mechanisms of transmission? Which organisms are the most highly transmissible? Higher resolution genomic data is required to accurately link microbial sources (such as environmental reservoirs or other individuals) with sinks (such as a single person's microbiome). New computational advances enable strain-level resolution of organisms from shotgun metagenomic data, allowing the transmission of strains to be followed over time and after discrete exposure events. Here, we highlight the latest techniques that reveal strain-level resolution from raw metagenomic reads and new studies that are tracking strains across people and environments. We also propose how models of pathogenic transmission may be applied to study the movement of commensals between microbial communities.
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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.