Evidence map›Paper›PMID 42405781›Full record

ArticleApplied and environmental microbiology2026

High-throughput viral enumeration of aquatic ecosystems via flow cytometry.

Madeline Bellanger, Pieter T Visscher, Richard Allen White

Abstract read
In one paragraph

Article in Applied and environmental 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
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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

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3 · Its place in the literature

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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

3 authors.

Madeline BellangerNorth Carolina Research Center (NCRC), Department of Bioinformatics and Genomics, The University of North Carolina at Charlotte, Kannapolis, North Carolina, USA.
Pieter T VisscherAustralian Centre for Astrobiology, University of New South Wales, Sydney, NSW, Australia.
Richard Allen WhiteNorth Carolina Research Center (NCRC), Department of Bioinformatics and Genomics, The University of North Carolina at Charlotte, Kannapolis, North Carolina, USA.ORCID 0000-0002-6292-5936

Funding

NASA Astrobiology Institute
6 · The paper itself

Abstract

For the past 25 years, flow cytometry (FCM) has been a gold standard for the direct measurement of virus-like particles (VLPs) in aquatic ecosystems. Flow cytometry allows for higher throughput and costs less than alternative enumeration methods, leading to its broad usage in aquatic viral ecology. A major challenge associated with flow cytometry is the degradation of VLPs over time, making the use of high-throughput plates not possible, thus lowering the overall throughput. It has also been difficult to maintain a method with low contamination, high signal-to-noise ratios, and observations of real VLPs vs fake particles. For these reasons, the use of flow cytometry has rapidly declined over the years due to the advent of massively parallel sequencing. Here, we describe a high-throughput method (HTM) in a 96-well plate format that provides a hands-free approach to viral enumeration. In a standard run, 60 samples can be measured for VLPs within 2.25 h, which is ~1 h faster than the standard single-tube approach and ~1.5 h faster than epifluorescence microscopy (EFM). Direct measurement of VLPs still provides a window into the viral-host interactions within aquatic ecosystems, which can be rapidly measured and resolved in a high-throughput manner.IMPORTANCEViruses represent the most numerically abundant biological entity on planet Earth. Enumeration of viruses within aquatic ecosystems (e.g., lakes and oceans) is essential to viral ecology and our understanding of their role within ecosystems. However, reliable and time-efficient high-throughput methods (HTM) for their enumeration are still needed. Here, we present a time saving HTM to count virus-like particles (VLPs) in a consistent and robust manner.

Indexed as

EcosystemFlow CytometryHigh-Throughput Screening AssaysVirusesWater Microbiologyaquatic ecosystemsbacteriophage (phage)flow cytometryfreshwaterhigh throughputmarineviruses

Identifiers

PMID42405781
PMCPMC13390381

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LicenceCC BY
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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.