Plant-derived virus-like particle vaccines drive cross-presentation of influenza A hemagglutinin peptides by human monocyte-derived macrophages
Bibliographic record
Abstract
Abstract A growing body of evidence supports the importance of T cell responses to protect against severe influenza, promote viral clearance, and ensure long-term immunity. Plant-derived virus-like particle (VLP) vaccines bearing influenza hemagglutinin (HA) have been shown to elicit strong humoral and CD4+T cell responses in both pre-clinical and clinical studies. To better understand the immunogenicity of these vaccines, we tracked the intracellular fate of a model HA (A/California/07/2009 H1N1) in human monocyte-derived macrophages (MDMs) following delivery either as VLPs (H1-VLP) or in soluble form. Compared to exposure to soluble HA, pulsing with VLPs resulted in ~3-fold greater intracellular accumulation of HA at 15 min that was driven by clathrin-mediated and clathrin-independent endocytosis as well as macropinocytosis/phagocytosis. At 45 min, soluble HA had largely disappeared suggesting its handling primarily by high-degradative endosomal pathways. Although the overall fluorescence intensity/cell had declined 25% at 45 min after H1-VLP exposure, the endosomal distribution pattern and degree of aggregation suggested that HA delivered by VLP had entered both high-degradative late and low-degradative static early and/or recycling endosomal pathways. At 45 min in the cells pulsed with VLPs, HA was strongly co-localized with Rab5, Rab7, Rab11, MHC II, and MHC I. High-resolution tandem mass spectrometry identified 115 HA-derived peptides associated with MHC I in the H1-VLP-treated MDMs. These data suggest that HA delivery to antigen-presenting cells on plant-derived VLPs facilitates antigen uptake, endosomal processing, and cross-presentation. These observations may help to explain the broad and cross-reactive immune responses generated by these vaccines.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".