Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) moonlights as an adhesin in Mycoplasma hyorhinis adhesion to epithelial cells as well as a plasminogen receptor mediating extracellular matrix degradation
Bibliographic record
Abstract
Mycoplasma hyorhinis infects pigs causing polyserositis and polyarthritis, and has also been reported in a variety of human tumor tissues. The occurrence of disease is often linked with the systemic invasion of the pathogen. Glyceraldehyde-3-Phosphate Dehydrogenase (GAPDH), one of the key enzymes of glycolysis, was reported as a surface multifunctional molecule in several bacteria. Here, we investigated whether GAPDH could manifest binary functions; as an adhesin to promote colonization as well as a plasminogen receptor functioning in extracellular matrix (ECM) degradation to promote systemic invasion. The surface localization of GAPDH was observed in M. hyorhinis with flow cytometry and colony blot analysis. Recombinant GAPDH (rGAPDH) was found to be able to bind porcine-derived PK-15 and human-derived NCI-H292 cells. The incubation with anti-GAPDH antibody significantly decreased the adherence of M. hyorhinis to both cell lines. To investigate its function in recruiting plasminogen, firstly, the interaction between rGAPDH and plasminogen was demonstrated by ELISA and Far-Western blot assay. The activation of the rGAPDH-bound plasminogen into plasmin was proved by using a chromogenic substrate, and furtherly confirmed to degrade extracellular matrix by using a reconstituted ECM. Finally, the ability of rGAPDH to bind different ECM components was demonstrated, including fibronectin, laminin, collagen type IV and vitronectin. Collectively, our data imply GAPDH as an important adhesion factor of M. hyrohinis and a receptor for hijacking host plasminogen to degrade ECM. The multifunction of GAPDH to bind both plasminogen and ECM components is believed to increase the targeting of proteolysis and facilitate the dissemination of M. hyorhinis.
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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 | 0.000 |
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".