Actinobacillus pleuropneumoniae Possesses an Antiviral Activity against Porcine Reproductive and Respiratory Syndrome Virus
Bibliographic record
Abstract
Pigs are often colonized by more than one bacterial and/or viral species during respiratory tract infections. This phenomenon is known as the porcine respiratory disease complex (PRDC). Actinobacillus pleuropneumoniae (App) and porcine reproductive and respiratory syndrome virus (PRRSV) are pathogens that are frequently involved in PRDC. The main objective of this project was to study the in vitro interactions between these two pathogens and the host cells in the context of mixed infections. To fulfill this objective, PRRSV permissive cell lines such as MARC-145, SJPL, and porcine alveolar macrophages (PAM) were used. A pre-infection with PRRSV was performed at 0.5 multiplicity of infection (MOI) followed by an infection with App at 10 MOI. Bacterial adherence and cell death were compared. Results showed that PRRSV pre-infection did not affect bacterial adherence to the cells. PRRSV and App co-infection produced an additive cytotoxicity effect. Interestingly, a pre-infection of SJPL and PAM cells with App blocked completely PRRSV infection. Incubation of SJPL and PAM cells with an App cell-free culture supernatant is also sufficient to significantly block PRRSV infection. This antiviral activity is not due to LPS but rather by small molecular weight, heat-resistant App metabolites (<1 kDa). The antiviral activity was also observed in SJPL cells infected with swine influenza virus but to a much lower extent compared to PRRSV. More importantly, the PRRSV antiviral activity of App was also seen with PAM, the cells targeted by the virus in vivo during infection in pigs. The antiviral activity might be due, at least in part, to the production of interferon γ. The use of in vitro experimental models to study viral and bacterial co-infections will lead to a better understanding of the interactions between pathogens and their host cells, and could allow the development of novel prophylactic and therapeutic tools.
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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 | 0.001 | 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".