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Molecular subtyping of European swine influenza viruses and scaling to high-throughput analysis

Overview of attention for article published in Virology Journal, January 2018
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Title
Molecular subtyping of European swine influenza viruses and scaling to high-throughput analysis
Published in
Virology Journal, January 2018
DOI 10.1186/s12985-018-0920-z
Pubmed ID
Authors

Emilie Bonin, Stéphane Quéguiner, Cédric Woudstra, Stéphane Gorin, Nicolas Barbier, Timm C. Harder, Patrick Fach, Séverine Hervé, Gaëlle Simon

Abstract

Swine influenza is a respiratory infection of pigs that may have a significant economic impact in affected herds and pose a threat to the human population since swine influenza A viruses (swIAVs) are zoonotic pathogens. Due to the increasing genetic diversity of swIAVs and because novel reassortants or variants may become enzootic or have zoonotic implications, surveillance is strongly encouraged. Therefore, diagnostic tests and advanced technologies able to identify the circulating strains rapidly are critically important. Several reverse transcription real-time PCR assays (RT-qPCRs) were developed to subtype European swIAVs in clinical samples previously identified as containing IAV genome. The RT-qPCRs aimed to discriminate HA genes of four H1 genetic lineages (H1av, H1hu, H1huΔ146-147, H1pdm) and one H3 lineage, and NA genes of two N1 lineages (N1, N1pdm) and one N2 lineage. After individual validation, each RT-qPCR was adapted to high-throughput analyses in parallel to the amplification of the IAV M gene (target for IAV detection) and the β-actin gene (as an internal control), in order to test the ten target genes simultaneously on a large number of clinical samples, using low volumes of reagents and RNA extracts. The RT-qPCRs dedicated to IAV molecular subtyping enabled the identification of swIAVs from the four viral subtypes that are known to be enzootic in European pigs, i.e. H1avN1, H1huN2, H3N2 and H1N1pdm. They also made it possible to discriminate a new antigenic variant (H1huN2Δ146-147) among H1huN2 viruses, as well as reassortant viruses, such as H1huN1 or H1avN2 for example, and virus mixtures. These PCR techniques exhibited a gain in sensitivity as compared to end-point RT-PCRs, enabling the characterization of biological samples with low genetic loads, with considerable time saving. Adaptation to high-throughput analyses appeared effective, both in terms of specificity and sensitivity. This new development opens novel perspectives in diagnostic capacities that could be very useful for swIAV surveillance and large-scale epidemiological studies.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 42 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 19%
Researcher 6 14%
Student > Bachelor 4 10%
Student > Doctoral Student 3 7%
Other 3 7%
Other 8 19%
Unknown 10 24%
Readers by discipline Count As %
Veterinary Science and Veterinary Medicine 10 24%
Agricultural and Biological Sciences 6 14%
Biochemistry, Genetics and Molecular Biology 3 7%
Immunology and Microbiology 3 7%
Business, Management and Accounting 2 5%
Other 5 12%
Unknown 13 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 January 2018.
All research outputs
#17,925,346
of 23,015,156 outputs
Outputs from Virology Journal
#2,253
of 3,061 outputs
Outputs of similar age
#311,394
of 443,280 outputs
Outputs of similar age from Virology Journal
#34
of 50 outputs
Altmetric has tracked 23,015,156 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,061 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 25.8. This one is in the 19th percentile – i.e., 19% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 443,280 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 50 others from the same source and published within six weeks on either side of this one. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.