Characterization of influenza H1N1 Gag virus-like particles and extracellular vesicles co-produced in HEK-293SF
Bibliographic record
Abstract
One of the concerns associated with the use of influenza virus-like particles (VLPs) as vaccine candidate or delivery system is their heterogeneous composition. Enveloped VLPs take up the host cell membrane at the budding site carrying out not only the viral antigenic proteins but also host proteins. In addition, the intrinsic nature of cells to produce membrane derived vesicles or extracellular vesicles (EVs), which have similar size to the VLPs, makes VLP purification process challenging. To further characterize these particles and identify proteins that are unique to each population, comparative proteomic analyses were completed to ultimately provide guidance for rational design of separation protocols. The VLPs were produced in suspension and serum free media by transient transfection of an inducible clone of a Human Embryonic Kidney (HEK-293SF) cells expressing HA and NA (H1N1/A/Puerto Rico/8/34), with a plasmid containing the gag gene of HIV-1 fused to GFP. EVs were produced independently from the non-transformed HEK-293SF cell line as a control for comparative studies. Both preparations were characterized for total nucleic acids and protein concentrations and extensively analyzed by nanoLC-MS/MS for their protein compositions. The proteomic analyses showed that aside from the recombinant VLP proteins, nucleolin was the most abundant host cell protein uniquely identified within VLPs (considering the MASCOT score value) while lactotransferrin and heat shock protein 90 were the most abundant proteins in EVs. Overall, this comparative study identifies potential target proteins as specific markers to guide VLP purification and discusses the biogenesis of enveloped particles released in HEK-293 cell suspension cultures emphasizing on the biological functions of host cell proteins identified.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 0.000 |
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.
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 teacher head, 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".