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Record W2802660058 · doi:10.3389/fimmu.2018.00829

Understanding Viral dsRNA-Mediated Innate Immune Responses at the Cellular Level Using a Rainbow Trout Model

2018· article· en· W2802660058 on OpenAlexaff
Sarah J. Poynter, Stephanie J. DeWitte‐Orr

Bibliographic record

VenueFrontiers in Immunology · 2018
Typearticle
Languageen
FieldImmunology and Microbiology
Topicinterferon and immune responses
Canadian institutionsWilfrid Laurier UniversityUniversity of Waterloo
Fundersnot available
KeywordsRNA silencingMDA5Innate immune systemBiologyInterferonReceptorRNAVirologyMolecular biologyCell biologyGeneRNA interferenceBiochemistry

Abstract

fetched live from OpenAlex

Viruses across genome types produce long dsRNA molecules during replication (viral (v-) dsRNA). DsRNA is a potent signaling molecule and inducer of type I interferon (IFN), leading to the production of interferon-stimulated genes (ISGs), and a protective antiviral state within the cell. Research on dsRNA-induced immune responses has relied heavily on a commercially available, and biologically irrelevant dsRNA, polyinosinic:polycytidylic acid (poly I:C). Alternatively, dsRNA can be produced by in vitro transcription, (ivt-) dsRNA, with a defined sequence and length. We hypothesized that ivt-dsRNA, containing legitimate viral sequence and length, would be a more appropriate proxy for v-dsRNA, compared to poly I:C. This is the first study to investigate the effects of v-dsRNA on the innate antiviral response and to compare v-dsRNA to ivt-dsRNA induced responses in fish cells, specifically rainbow trout. Previously, class A scavenger receptors (SR-As) were found to be surface receptors for poly I:C in rainbow trout cells. In the current study, ivt-dsRNA binding was blocked by poly I:C and v-dsRNA, as well as SR-A competitive ligands, suggesting all three dsRNA molecules are recognised by SR-As. Downstream innate antiviral effects were determined by measuring IFN and ISG transcript levels using qRT-PCR and antiviral assays. Similar to what has been shown previously with ivt-dsRNA, v-dsRNA was able to induce IFN and ISG transcript production between 3h and 24h, and its effects were length dependent (ie. longer v-dsRNA produced a stronger response). Interestingly, when v-dsRNA and ivt-dsRNA were length and sequence matched both molecules induced statistically similar IFN and ISG transcript levels, which resulted in similar antiviral states against two aquatic viruses. To pursue sequence effects further, three ivt-dsRNA molecules of the same length but different sequences (including host and viral sequences) were tested for their ability to induce IFN/ISG transcripts and an antiviral state. All three induced responses similarly. This study is the first of its kind to look at the effects v-dsRNA in fish cells as well as to compare ivt-dsRNA to v-dsRNA, and suggests that ivt-dsRNA may be a good surrogate for v-dsRNA in the study of dsRNA-induced responses and potential future antiviral therapies.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
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 score0.051
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.079
GPT teacher head0.269
Teacher spread0.190 · 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 teacher head, not a consensus.

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

Citations36
Published2018
Admission routes1
Has abstractyes

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