Evidence map›Paper›PMID 41790828›Full record

ArticlePLoS biology2026

Sub-daily virus sampling at the Bermuda Atlantic Time Series reveals diel and depth-structured population dynamics without community-level shifts.

Alfonso Carrillo, Emily Hageman, Lauren Chittick, Anna I Mackey, Kimberley S Ndlovu, Funing Tian, Naomi E Gilbert, Daniel Muratore, Dean Vik, Gary R LeCleir and 6 more

Abstract read
In one paragraph

Article in PLoS biology, 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

16 authors.

Alfonso CarrilloDepartment of Microbiology, The Ohio State University, Columbus, Ohio, United States of America.ORCID https://orcid.org/0009-0006-7224-7186
Emily HagemanDepartment of Microbiology, The Ohio State University, Columbus, Ohio, United States of America.
Lauren ChittickCollege of Veterinary Medicine, Midwestern University, Glendale, Arizona, United States of America.
Anna I MackeyDepartment of Microbiology, The Ohio State University, Columbus, Ohio, United States of America.
Kimberley S NdlovuDepartment of Microbiology, The Ohio State University, Columbus, Ohio, United States of America.
Funing TianDepartment of Microbiology, The Ohio State University, Columbus, Ohio, United States of America.
Naomi E GilbertLawrence Livermore National Laboratory, Livermore, California, United States of America.
Daniel MuratoreSchool of Biology, Georgia Institute of Technology, Atlanta, Georgia, United States of America.
Dean VikDepartment of Microbiology, The Ohio State University, Columbus, Ohio, United States of America.
Gary R LeCleirDepartment of Microbiology, The University of Tennessee, Knoxville, Tennessee, United States of America.
Christine SunDepartment of Microbiology, The Ohio State University, Columbus, Ohio, United States of America.
Ho B JangKorea Virus Research Institute, Daejeon, South Korea.
Ricardo R PavanDepartment of Microbiology, The Ohio State University, Columbus, Ohio, United States of America.
Joshua S WeitzInstitute of Health Computing, The University of Maryland, College Park, Maryland, United States of America.
Steven W WilhelmDepartment of Microbiology, The University of Tennessee, Knoxville, Tennessee, United States of America.
Matthew B SullivanDepartment of Microbiology, The Ohio State University, Columbus, Ohio, United States of America.ORCID https://orcid.org/0000-0001-8398-8234

Funding

Cellular, molecular, and biochemical sciences training grantT32GM141955 · NIGMS · OHIO STATE UNIVERSITY · PI Jane Elizabeth Jackman, JESSE J KWIEK · 2021 to 2026
$2.2M
NIGMS NIH HHS T32 GM141955
6 · The paper itself

Abstract

Ocean microbes contribute to biogeochemical cycles and ecosystem function, but they do so under top-down pressure imposed by viruses. While viruses are increasingly understood spatially and beginning to be incorporated into predictive modeling, high-frequency ocean virus dynamics remain understudied due to methodological challenges. Here we sampled stratified Bermuda Atlantic Time Series (BATS) waters for 112 hours at sub-daily 4- (surface) or 12- (deep chlorophyll maximum) hour intervals, purified viral particles from these samples, sequenced their metagenomes, and used the resulting data to characterize high-frequency virus community dynamics. Aggregated community diversity metrics changed with depth, but were not statistically significant temporally at a fixed location. However, finer-scale population-level analyses revealed both depth and temporal change, including physicochemical depth-driven differences and, in surface waters, thousands of viral populations that exhibited statistically significant diel rhythms. Statistical analyses revealed three main archetypes of temporal dynamics that themselves differed in abundance patterns, host predictions, viral taxonomy, and gene functions. Among these, highlights include viruses resembling an archetype with a night peaking pattern in activity that include an over-representation of viruses that putatively infect Prochlorococcus, a phototrophic cyanobacteria. Together, these efforts provide baseline community- and population-scale short-time-frame observations relevant to future climate state modeling.

Indexed as

SeawaterVirusesAtlantic OceanBermudaEcosystemMetagenomePopulation DynamicsWater Microbiology

Identifiers

PMID41790828
PMCPMC12965618

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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.