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Record W2033236225 · doi:10.1371/journal.pone.0084673

Identification of Adaptive Mutations in the Influenza A Virus Non-Structural 1 Gene That Increase Cytoplasmic Localization and Differentially Regulate Host Gene Expression

2013· article· en· W2033236225 on OpenAlexafffund
Nicole Forbes, Mohammed Selman, Martin Pelchat, Jian Jun Jia, Alain Stintzi, Earl G. Brown

Bibliographic record

VenuePLoS ONE · 2013
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsUniversity of Ottawa
FundersCanadian Institutes of Health ResearchUniversity of Ottawa
KeywordsBiologyGeneMutantInfluenza A virusGene expressionMolecular biologyVirusCell biologyGenetics

Abstract

fetched live from OpenAlex

The NS1 protein of influenza A virus (IAV) is a multifunctional virulence factor. We have previously characterized gain-of-function mutations in the NS1 protein arising from the experimental adaptation of the human isolate A/Hong Kong/1/1968(H3N2) (HK) to the mouse. The majority of these mouse adapted NS1 mutations were demonstrated to increase virulence, viral fitness, and interferon antagonism, but differ in binding to the post-transcriptional processing factor cleavage and polyadenylation specificity factor 30 (CPSF30). Because nuclear trafficking is a major genetic determinant of influenza virus host adaptation, we assessed subcellular localization and host gene expression of NS1 adaptive mutations. Recombinant HK viruses with adaptive mutations in the NS1 gene were assessed for NS1 protein subcellular localization in mouse and human cells using confocal microscopy and cellular fractionation. In human cells the HK wild-type (HK-wt) virus NS1 protein partitioned equivalently between the cytoplasm and nucleus but was defective in cytoplasmic localization in mouse cells. Several adaptive mutations increased the proportion of NS1 in the cytoplasm of mouse cells with the greatest effects for mutations M106I and D125G. The host gene expression profile of the adaptive mutants was determined by microarray analysis of infected mouse cells to show either high or low extents of host-gene regulation (HGR or LGR) phenotypes. While host genes were predominantly down regulated for the HGR group of mutants (D2N, V23A, F103L, M106I+L98S, L98S, M106V, and M106V+M124I), the LGR phenotype mutants (D125G, M106I, V180A, V226I, and R227K) were characterized by a predominant up regulation of host genes. CPSF30 binding affinity of NS1 mutants did not predict effects on host gene expression. To our knowledge this is the first report of roles of adaptive NS1 mutations that impact intracellular localization and regulation of host gene expression.

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 score0.001
Threshold uncertainty score0.003

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.069
GPT teacher head0.303
Teacher spread0.233 · 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

Citations19
Published2013
Admission routes2
Has abstractyes

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