Evidence map›Paper›PMID 39432531›Full record

ArticlePloS one2024

A refinement to eRNA and eDNA-based detection methods for reliable and cost-efficient screening of pathogens in Atlantic salmon aquaculture.

Ottavia Benedicenti, Marit Måsøy Amundsen, Saima Nasrin Mohammad, Trude Vrålstad, David A Strand, Simon Chioma Weli, Sonal Patel, Hilde Sindre

Abstract read
In one paragraph

Article in PloS one, 2024. 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. Article
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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

8 authors.

Ottavia BenedicentiNorwegian Veterinary Institute, Ås, Norway.ORCID 0000-0003-4067-7617
Marit Måsøy AmundsenNorwegian Veterinary Institute, Ås, Norway.
Saima Nasrin MohammadNorwegian Veterinary Institute, Ås, Norway.
Trude VrålstadNorwegian Veterinary Institute, Ås, Norway.
David A StrandNorwegian Veterinary Institute, Ås, Norway.
Simon Chioma WeliNorwegian Veterinary Institute, Ås, Norway.
Sonal PatelNorwegian Veterinary Institute, Bergen, Norway.
Hilde SindreNorwegian Veterinary Institute, Ås, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Finfish aquaculture is one of the fastest-growing food production sectors in the world, and numerous infectious diseases are a constant challenge to the fish farming industry, causing decreased fish health and, consequently, economic losses. Specific and sensitive tools for pathogen detection are crucial for the surveillance of environmental samples to prevent the spread of fish pathogens in farms. Monitoring of waterborne pathogens through filtration of water and subsequent molecular detection of target-specific DNA or RNA sequence motifs is an animal-friendly method. This approach could reduce or even replace the sacrifice of fish for monitoring purposes in aquaculture and allow earlier implementation of disease control measures. Sampling methods might be a bottleneck, and there is a need for simple sampling methods that still ensure the best detection probability. In this study, we tested different filtration methods with spiked freshwater and seawater for a panel of fish pathogens to discern a suitable procedure that can be easily applied on-site by farm personnel without compromising detection probability. Specifically, we tested combinations of different filtration flow rates, lysis buffers, and filters for the detection of some of the pathogens relevant to the aquaculture industry. The results showed that a "sandwich" filtration method using two different filters and a flow rate of up to 4.0 L/min ensured good pathogen detection. The filters, consisting of a hydrophilic glass fibre filter with binder resin on the top and a hydrophilic mixed cellulose esters membrane at the bottom, achieved the best concentration and qPCR detection of both viral and bacterial fish pathogens. This up-and-coming tool allows the detection of very different fish pathogens during a single filtration step, and it can be combined with one single automated total nucleic acid extraction step for all the investigated pathogens, reducing both analysis costs and time.

Indexed as

AquacultureFish DiseasesSalmo salarAnimalsFiltration

Identifiers

PMID39432531
PMCPMC11493300

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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.