Outer-Membrane Vesicles of Fusobacterium necrophorum: A Proteomic, Lipidomic, and Functional Characterization
Bibliographic record
Abstract
Outer-membrane vesicles (OMVs) are extruded nanostructures shed by Gram-negative bacteria, containing periplasmic contents, and often including virulence factors with immunogenic properties. To assess their potential for use in vaccine development, we purified OMVs from the Fusobacterium necrophorum subspecies necrophorum, an opportunistic necrotic infection-causing pathogen, and characterized these structures using proteomics, lipid-profiling analyses, and cytotoxicity assays. A proteomic analysis of density-gradient-purified F. necrophorum OMVs identified 342 proteins, a large proportion of which were outer-membrane proteins (OMPs), followed by cytoplasmic proteins, based on a subcellular-localization-prediction analysis. The OMPs and toxins were among the proteins with the highest intensity identified, including the 43-kDa-OMP-, OmpA-, and OmpH-family proteins, the cell-surface protein, the FadA adhesin protein, the leukotoxin-LktA-family filamentous adhesin, the N-terminal domain of hemagglutinin, and the OMP transport protein and assembly factor. A Western blot analysis confirmed the presence of several OMPs and toxins in the F. necrophorum OMVs. The lipid-profiling analysis revealed phospholipids, sphingolipids, and acetylcarnitine as the main lipid contents of OMVs. The lactate-dehydrogenase-cytotoxicity assays showed that the OMVs had a high degree of cytotoxicity against a bovine B-lymphocyte cell line (BL-3 cells). Thus, our data suggest the need for further studies to evaluate the ability of OMVs to induce immune responses and assess their vaccine potential in vivo.
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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) | 0.001 | 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 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".