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Record W6989947436

The characterization of Vig-1’s expression patterns in IPNV-infected, or dsRNA-treated, rainbow trout cells

2024· article· en· W6989947436 on OpenAlexaboutno aff

Bibliographic record

VenueScholars Commons (Wilfrid Laurier University) · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
Topicinterferon and immune responses
Canadian institutionsnot available
Fundersnot available
KeywordsRainbow troutTroutInnate immune systemImmune systemInterferonInfectious hematopoietic necrosis virusGene expressionGene
DOInot available

Abstract

fetched live from OpenAlex

In Canada, annual trout production is valued at over $60M with approximately 10,000 tonnes of trout produced per year. Rainbow trout (Oncorhynchus mykiss) are one of the most commonly farmed fresh-water fish in Canada. The high-density farming practices involved in aquaculture increase rainbow trout susceptibility to aquatic viruses such as infectious pancreatic necrosis virus (IPNV). The innate antiviral immune response in rainbow trout is poorly characterized, and the functions of numerous interferon stimulated genes (ISG) in rainbow trout remain unclear. One such gene, virus-induced gene 1 (vig-1) has been poorly studied; however, the human orthologue for vig-1, viperin (also known as radical S-adenosyl methionine domain containing 2 (RSAD2)), has been widely characterized and numerous antiviral mechanisms have been attributed to it. Vig-1 is thought to be a potentially important interferon-stimulated gene since its expression is induced by various stimulants, including polyinosinic:polycytidylic acid (poly I:C) (a viral double stranded ribonucleic acid (dsRNA) mimic) and viruses. This project sought to better characterize the role of vig-1 in the innate antiviral immune response in rainbow trout cells.\nThis thesis explored the induction kinetics of vig-1 in two rainbow trout cell lines, rainbow trout spleen-11 (RTS-11) and rainbow trout gonad-2 (RTG-2). This was accomplished by analyzing expression of vig-1 at the transcript level using real time quantitative polymerase chain reaction (RT-qPCR) and then expression at the protein level was investigated by western blot. Both analyses were completed following treatment with a range of concentrations of high molecular weight (HMW) poly I:C, or IPNV at various incubation points to better understand the expression patterns of vig-1 at the transcript and protein levels. This work suggests that firstly, vig-1 expression peaks at 24 hours following poly I:C treatment in both RTS-11 and RTG-2 cells, with a greater fold increase observed in RTG-2 cells despite RTS-11 being an immune cell line. Secondly, vig-1 expression in RTG-2 cells was found to increase in a dose-dependent manner when treated with increasing concentrations of poly I:C. Thirdly, infection with IPNV resulted in a transient increase of vig-1 expression at both 24- and 48- hours post-infection. The first steps of identifying vig-1’s antiviral function were completed by optimizing transfection efficiencies in the rainbow trout cell line, RTG-2, and the Atlantic salmon (Salmo salar) cell line, Atlantic salmon gill-10 (ASG-10), with a green fluorescent protein (GFP) expression plasmid and a non-liposomal transfection reagent. This work found that ASG-10 cells exhibited low transfection efficiency and RTG-2 cells exhibited 0% transfection efficiency under the conditions tested, suggesting that ASG-10 cells are more effective at DNA uptake. Given the low and zero transfection efficiencies observed in this study, alternative transfection reagents or methods should be explored for these cell lines before work continues to elucidate vig-1’s antiviral function by overexpression studies. Together, this work contributes to a better understanding of rainbow trout innate immune responses.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.215
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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