Understudied, coinfections are more frequent in pig farms than single infections. In pigs, the term “Porcine Respiratory Disease Complex” (PRDC) is often used to describe coinfections involving viruses such as swine Influenza A Virus (swIAV), Porcine Reproductive and Respiratory Syndrome Virus (PRRSV), and Porcine CircoVirus type 2 (PCV2) as well as bacteria likeActinobacillus pleuropneumoniae,Mycoplasma hyopneumoniaeandBordetella bronchiseptica. The clinical outcome of the various coinfection or superinfection situations is usually assessed in the studies while in most of cases there is no clear elucidation of the fine mechanisms shaping the complex interactions occurring between microorganisms. In this comprehensive review, we aimed at identifying the studies dealing with coinfections or superinfections in the pig respiratory tract and at presenting the interactions between pathogens and, when possible, the mechanisms controlling them. Coinfections and superinfections involving viruses and bacteria were considered while research articles including protozoan and fungi were excluded. We discuss the main limitations complicating the interpretation of coinfection/superinfection studies, and the high potential perspectives in this fascinating research field, which is expecting to gain more and more interest in the next years for the obvious benefit of animal health.

Respiratory infections are still a major concern in pigs. Amongst the involved viruses, the porcine reproductive and respiratory syndrome virus (PRRSV) and the swine influenza type A virus (swIAV) have a major impact. These viruses frequently encounter and dual infections are reported. We analyzed here the molecular interactions between viruses and porcine tracheal epithelial cells as well as lung tissue. PRRSV-1 species do not infect porcine respiratory epithelial cells. However, PRRSV-1, when inoculated simultaneously or shortly before swIAV, was able to inhibit swIAV H1N2 infection, modulate the interferon response and alter signaling protein phosphorylations (ERK, AKT, AMPK, and JAK2), in our conditions. SwIAV inhibition was also observed, although at a lower level, by inactivated PRRSV-1, whereas acid wash treatment inactivating non-penetrated viruses suppressed the interference effect. PRRSV-1 and swIAV may interact at several stages, before their attachment to the cells, when they attach to their receptors, and later on. In conclusion, we showed for the first time that PRRSV can alter the relation between swIAV and its main target cells, opening the doors to further studies on the interplay between viruses. Consequences of these peculiar interactions on viral infections and vaccinations using modified live vaccines require further investigations.

The dynamic variations of the Parasympathetic Tone Activity (PTA) index were evaluated to assess nociception in dogs undergoing anaesthetic protocols with different premedication drugs. Sixty-six dogs, divided into three groups of 22 dogs each, were given different premedication drugs “morphine” (0.2 mg/kg), “morphine + medetomidine (5 μg/kg)”, “morphine + acepromazine (0.03 mg/kg)”, then similarly induced and maintained under general anaesthesia. The PTA, HR (heart rate) and MAP (mean arterial pressure) were assessed at S (steady-state), Cut (cutaneous incision), PTA_E (PTA Event, assessed 1 min before a significant PTA decrease), HDR (Haemodynamic reaction, assessed 5 min before an increase of ≥ 20% in HR and/or MAP). For each group, the dynamic variation of PTA (ΔPTA) was calculated and a Receiver Operating Characteristics (ROC) curve was performed to detect if any of the premedication drugs may alter the performance of PTA index to predict intraoperative haemodynamic reactions. In all groups, a haemodynamic reaction was detected after Cut, PTA_E and HDR and was preceded with a significant decrease of PTA, except for “morphine + medetomidine” group which showed a significant drop of PTA only at PTA_E and HDR. The ΔPTA showed a fair performance in all groups (a mean [95% CI] AUC of 0.73 [0.62–0.82], 0.70 [0.59–0.79] and 0.71 [0.59–0.80] respectively in morphine, morphine + ACP and morphine + medetomidine). Although ΔPTA was rather altered by the premedication drug, it was able to predict, to a certain extent, haemodynamic reactions in all groups.