Evidence map›Paper›PMID 40811063›Full record

ArticleCell reports2025

Intraspecies associations from strain-rich metagenome samples.

Evan B Qu, Jacob S Baker, Laura Markey, Veda Khadka, Chris Mancuso, A Delphine Tripp, Tami D Lieberman

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell reports, 2025. 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. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Evan B QuInstitute for Medical Engineering and Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Jacob S BakerInstitute for Medical Engineering and Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Laura MarkeyInstitute for Medical Engineering and Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Veda KhadkaInstitute for Medical Engineering and Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Chris MancusoInstitute for Medical Engineering and Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
A Delphine TrippInstitute for Medical Engineering and Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Systems Biology, Harvard University, Cambridge, MA 02138, USA.
Tami D LiebermanInstitute for Medical Engineering and Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA; Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139, USA. Electronic address: tami@mit.edu.

Funding

An Evolutionary Framework For Identifying Determinants Of Colonization In Human MicrobiomesDP2GM140922 · NIGMS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI LIEBERMAN, TAMI D · 2020 to 2020
$2.3M
Drivers of adaptation and colonization within individual human microbiomesR35GM156282 · NIGMS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI Tami D Lieberman · 2025 to 2026
$1.1M
NIGMS NIH HHS DP2 GM140922NIGMS NIH HHS R35 GM156282
6 · The paper itself

Abstract

Genetically distinct strains of a species can vary widely in phenotype, reducing the utility of species-resolved microbiome measurements for detecting associations with health or disease. While metagenomics theoretically provides information on all strains in a sample, current strain-resolved analysis methods face a tradeoff: de novo genotyping approaches can detect novel strains but struggle when applied to strain-rich or low-coverage samples, while reference database methods work robustly across sample types but are insensitive to novel diversity. We present PHLAME, a method that bridges this divide by combining the advantages of reference database approaches with novelty awareness. PHLAME explicitly defines clades at multiple phylogenetic levels and introduces a probabilistic, mutation-based framework to quantify novelty from the nearest reference. By applying PHLAME to publicly available human skin and vaginal metagenomes, we find clade associations with coexisting species, geography, and host age. The ability to characterize intraspecies associations and dynamics in previously inaccessible environments will enable strain-level insights from accumulating metagenomic data.

Indexed as

MetagenomeMetagenomicsMicrobiotaFemaleHumansPhylogenySkinVaginaCP: Microbiologymetagenomicsskin microbiomestrainvaginal microbiome

Identifiers

PMID40811063
PMCPMC12452263

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.