Identification and characterization of a Streptococcus equi ssp. zooepidemicus immunogenic GroEL protein involved in biofilm formation
Bibliographic record
Abstract
Streptococcus equi ssp. zooepidemicus (S. equi spp. zooepidemicus) is an opportunistic pathogen that causes major economic losses in the swine industry in China and is also a threat for human health. Biofilm formation by this bacterium has been previously reported. In this study, we used an immunoproteomic approach to search for immunogenic proteins expressed by biofilm-grown S. equi spp. zooepidemicus. Seventeen immunoreactive proteins were found, of which nine common immunoreactive proteins were identified in planktonic and biofilm-grown bacteria. The immunogenicity and protective efficacy of the S. equi spp. zooepidemicus immunoreactive GroEL chaperone protein was further investigated in mice. The protein was expressed in vivo and elicited high antibody titers following S. equi spp. zooepidemicus infections of mice. An animal challenge experiment with S. equi spp. zooepidemicus showed that 75% of mice immunized with the GroEL protein were protected. Using in vitro biofilm inhibition assays, evidence was obtained that the chaperonin GroEL may represent a promising target for the prevention and treatment of persistent S. equi spp. zooepidemicus biofilm infections. In summary, our results suggest that the recombinant GroEL protein, which is involved in biofilm formation, may efficiently stimulate an immune response, which protects against S. equi spp. zooepidemicus infections. It may therefore be a candidate of interest to be included in vaccines against S. equi spp. zooepidemicus infections.
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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".