Evidence map›Paper›PMID 39071345›Full record

ArticlebioRxiv : the preprint server for biology2024

Shared environments complicate the use of strain-resolved metagenomics to infer microbiome transmission.

Reena Debray, Carly C Dickson, Shasta E Webb, Elizabeth A Archie, Jenny Tung

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Reena DebrayDepartment of Primate Behavior and Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig, Saxony, Germany.ORCID 0000-0001-8130-4871
Carly C DicksonDepartment of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, USA.
Shasta E WebbDepartment of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, USA.ORCID 0000-0002-9329-2553
Elizabeth A ArchieDepartment of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, USA.ORCID 0000-0002-1187-0998
Jenny TungDepartment of Primate Behavior and Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig, Saxony, Germany.ORCID 0000-0003-0416-2958

Funding

A life course perspective on gut microbiome aging and health in a non-human primate modelR01AG071684 · NIA · UNIVERSITY OF NOTRE DAME · PI ARCHIE, ELIZABETH · 2021 to 2025
$3.2M
Gene regulation and social relationships across the life course in a nonhuman primate modelR01AG075914 · NIA · DUKE UNIVERSITY · PI ALBERTS, SUSAN C. · 2021 to 2025
$2.6M
Developing insertable cardiac monitors to assess social and environmental effects on the autonomic stress response in a nonhuman primate model of agingR61AG078470 · NIA · UNIVERSITY OF NOTRE DAME · PI ARCHIE, ELIZABETH · 2022 to 2023
$607k
NIA NIH HHS R01 AG071684NIA NIH HHS R01 AG075914NIA NIH HHS R61 AG078470
6 · The paper itself

Abstract

In humans and other social animals, social partners have more similar microbiomes than expected by chance, suggesting that social contact transfers microorganisms. Yet, social microbiome transmission can be difficult to identify based on compositional data alone. To overcome this challenge, recent studies have used information about microbial strain sharing (i.e., the shared presence of highly similar microbial sequences) to infer transmission. However, the degree to which strain sharing is influenced by shared traits and environments among social partners, rather than transmission

Indexed as

dispersalhorizontal transmissionmicrobiomesocial networksocial transmissionstrain sharing

Identifiers

PMID39071345
PMCPMC11275843

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.