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Record W2339541037 · doi:10.1128/jvi.00452-16

Influenza Virus Hemagglutinin Glycoproteins with Different N-Glycan Patterns Activate Dendritic Cells <i>In Vitro</i>

2016· article· en· W2339541037 on OpenAlexaff
Wen‐Chun Liu, Yu‐Li Lin, Maureen Spearman, Pei‐Yun Cheng, Michael Butler, Suh‐Chin Wu

Bibliographic record

VenueJournal of Virology · 2016
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsUniversity of Manitoba
FundersNational Tsing Hua UniversityMinistry of Science and Technology, Taiwan
KeywordsBiologyGlycanHemagglutinin (influenza)Chinese hamster ovary cellGlycoproteinGlycosylationVirologyInfluenza A virusImmune systemVirusMannose receptorMannoseSurfactant protein DMicrobiologyInnate immune systemMolecular biologyIn vitroImmunologyBiochemistryReceptorMacrophage

Abstract

fetched live from OpenAlex

UNLABELLED: Influenza virus hemagglutinin (HA) N-glycans play important regulatory roles in the control of virus virulence, antigenicity, receptor-binding specificity, and viral escape from the immune response. Considered essential for controlling innate and adaptive immune responses against influenza virus infections, dendritic cells (DCs) trigger proinflammatory and adaptive immune responses in hosts. In this study, we engineered Chinese hamster ovary (CHO) cell lines expressing recombinant HA from pandemic H1, H5, and H7 influenza viruses. rH1HA, rH5HA, and rH7HA were obtained as wild-type proteins or in the presence of kifunensine (KIF) or further with endo-β-N-acetylglucosaminidase-treated KIF (KIF+E) to generate single-N-acetylglucosamine (GlcNAc) N-glycans consisting of (i) terminally sialylated complex-type N-glycans, (ii) high-mannose-type N-glycans, and (iii) single-GlcNAc-type N-glycans. Our results show that high-mannose-type and single-GlcNAc-type N-glycans, but not complex-type N-glycans, are capable of inducing more active hIL12 p40, hIL12 p70, and hIL-10 production in human DCs. Significantly higher HLA-DR, CD40, CD83, and CD86 expression levels, as well reduced endocytotic capacity in human DCs, were noted in the high-mannose-type rH1HA and single-GlcNAc-type rH1HA groups than in the complex-type N-glycan rH1HA group. Our data indicate that native avian rHA proteins (H5N1 and H7N9) are more immunostimulatory than human rHA protein (pH1N1). The high-mannose-type or single-GlcNAc-type N-glycans of both avian and human HA types are more stimulatory than the complex-type N-glycans. HA-stimulated DC activation was accomplished partially through a mannose receptor(s). These results provide more understanding of the contribution of glycosylation of viral proteins to the immune responses and may have implications for vaccine development. IMPORTANCE: Influenza viruses trigger seasonal epidemics or pandemics with mild-to-severe consequences for human and poultry populations. DCs are the most potent professional antigen-presenting cells, which play a crucial role in the link between innate and adaptive immunity. In this study, we obtained stable-expression CHO cells to produce rH1HA, rH5HA, and rH7HA proteins containing distinct N-glycan patterns. These rHA proteins, each with a distinct N-glycan pattern, were used to investigate interactions with mouse and human DCs. Our data indicate that native avian rHA proteins (H5N1 and H7N9) are more immunostimulatory than human rHA protein (pH1N1). High-mannose-type and single-GlcNAc-type N-glycans were more effective than complex-type N-glycans in triggering mouse and human DC activation and maturation. We believe these results provide some useful information for influenza vaccine development regarding how influenza virus HA proteins with different types of N-glycans activate DCs.

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 score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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)0.0020.001

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 head0.036
GPT teacher head0.321
Teacher spread0.286 · 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".

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Citations30
Published2016
Admission routes1
Has abstractyes

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