Evidence map›Paper›PMID 42146067›Full record

ArticleFrontiers in microbiology2026

Arsenic detoxification within thermo-alkaline biofilms.

Gwendolyn Cooper, Stephanie H Ayotte, Martina L Du, Jessica D Wood, Breuklyn Opp, Brian Bothner, Brent M Peyton

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2026. 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

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

7 authors.

Gwendolyn Cooper *Thermal Biology Institute, Montana State University, Bozeman, MT, United States.
Stephanie H Ayotte *Thermal Biology Institute, Montana State University, Bozeman, MT, United States.
Martina L DuThermal Biology Institute, Montana State University, Bozeman, MT, United States.
Jessica D WoodThermal Biology Institute, Montana State University, Bozeman, MT, United States.
Breuklyn OppThermal Biology Institute, Montana State University, Bozeman, MT, United States.
Brian BothnerDepartment of Chemistry and Biochemistry, Montana State University, Bozeman, MT, United States.
Brent M PeytonThermal Biology Institute, Montana State University, Bozeman, MT, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The fundamental principles driving community composition and dynamics of microbial mats in thermoalkaline springs are largely uncharacterized. High in not only temperature but also arsenic (As), the microbial populations of Yellowstone National Parks (YNP), USA thermal springs require unique detoxification mechanisms to survive and carry out basic biological functions. Methods: While many studies have focused on which microorganisms are present, few studies have integrated the use of metagenome sequencing, imaging techniques, and mass spectrometry to gain insight into how structure and function of the mat dwelling organisms might be impacted by the high arsenical species in the ecosystem. Results: Here, we demonstrate via metagenome sequencing that community composition, including microbial genera Discussion: These data demonstrate how microbial mats are modular, stratified systems that shape and are shaped by environmental and geochemical gradients. Together, these findings characterize novel complexity and associations between geochemical cycles of metals and metabolic adaptations necessary for microorganisms to inhabit thermal springs. In conclusion, these findings demonstrate physiochemical heterogeneity of microbial mats in YNP.

Indexed as

arsenicmetabolismmetagenomicsmicrobial matsYellowstone National Park

Identifiers

PMID42146067
PMCPMC13171826

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Registered trials

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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.