Fructose-1,6-bisphosphate aldolase encoded by a core gene of Mycoplasma hyopneumoniae contributes to host cell adhesion
Bibliographic record
Abstract
Mycoplasma hyopneumoniae is an important respiratory pathogen that causes great economic losses to the pig industry worldwide. Although some putative virulence factors have been reported, pathogenesis remains poorly understood. Herein, we evaluated the relative abundance of proteins in virulent 168 (F107) and attenuated 168L (F380) M. hyopneumoniae strains to identify virulence-associated factors by two-dimensional electrophoresis (2-DE). Seven proteins were found to be ≥ 1.5-fold more abundant in 168, and protein–protein interaction network analysis revealed that all seven interact with putative virulence factors. Unexpectedly, six of these virulence-associated proteins are encoded by core rather than accessory genomic elements. The most differentially abundant of the seven, fructose-1,6-bisphosphate aldolase (FBA), was successfully cloned, expressed and purified. Flow cytometry demonstrated the surface localisation of FBA, recombinant FBA (rFBA) mediated adhesion to swine tracheal epithelial cells (STEC), and anti-rFBA sera decreased adherence to STEC. Surface plasmon resonance showed that rFBA bound to fibronectin with a moderately strong K D of 469 nM. The results demonstrate that core gene expression contributes to adhesion and virulence in M. hyopneumoniae , and FBA moonlights as an important adhesin, mediating binding to host cells via fibronectin.
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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) | 0.000 | 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 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".