Staphylococcus aureus is considered one of the most widespread bacterial pathogens for both animals and humans, being the causative agent of various diseases like food poisoning, respiratory tract infections, nosocomial bacteremia, and surgical site and cardiovascular infections in humans, as well as clinical and subclinical mastitis, dermatitis, and suppurative infections in animals. Thanks to their genetic flexibility, several virulent and drug-resistant strains have evolved mainly due to horizontal gene transfer and insurgence of point mutations. Infections caused by the colonization of such strains are particularly problematic due to frequently occurring antibiotic resistance, particulary methicillin-resistant S. aureus (MRSA), and are characterized by increased mortality, morbidity, and hospitalization rates compared to those caused by methicillin-sensitive S. aureus (MSSA). S. aureus infections in humans and animals are a prime example of a disease that may be managed by a One Health strategy. In fact, S. aureus is a significant target for control efforts due to its zoonotic potential, the frequency of its illnesses in both humans and animals, and the threat posed by S. aureus antibiotic resistance globally. The results of an epidemiological analysis on a worldwide public database (NCBI Pathogen Detection Isolate Browser; NPDIB) of 35,026 S. aureus isolates were described. We considered the diffusion of antibiotic resistance genes (ARGs), in both human and animal setting, and the results may be considered alarming. The result of this study allowed us to identify the presence of clusters with specific ARG patterns, and that these clusters are associated with different sources of isolation (e.g., human, non-human).

Streptococcus agalactiae is a well-known pathogen in humans and food-producing animals. Therefore, this bacterium is a paradigmatic example of a pathogen to be controlled by a One Health approach. Indeed, the zoonotic and reverse-zoonotic potential of the bacteria, the prevalence of Group B Streptococci (GBS) diseases in both human and animal domains, and the threatening global situation on GBS antibiotic resistance make these bacteria an important target for control programs. An epidemiological analysis using a public database containing sequences of S. agalactiae from all over the world was conducted to evaluate the frequency and evolution of antibiotic resistance genes in those isolates. The database we considered (NCBI pathogen detection isolate browser—NPDIB) is maintained on a voluntary basis. Therefore, it does not follow strict epidemiological criteria. However, it may be considered representative of the bacterial population related to human diseases. The results showed that the number of reported sequences increased largely in the last four years, and about 50% are of European origin. The frequency data and the cluster analysis showed that the AMR genes increased in frequency in recent years and suggest the importance of verifying the application of prudent protocols for antimicrobials in areas with an increasing frequency of GBS infections both in human and veterinary medicine.

Mastitis is a major cause of antimicrobial treatments either during lactation or at drying off. From a One Health perspective, there should be a balance between the risk of IMI that may impair cow health and welfare and the reduction of antimicrobial usage to decrease antimicrobial resistance, as may happen when applying selective dry-cow therapy. This reduction may be achieved by an early and accurate diagnosis followed by prudent and rationale therapeutical protocols. This study aims to assess the accuracy of PLCC (neutrophils + lymphocyte count/mL) in identifying cows at risk of having IMI due to major pathogens (S.aureus, Str.agalactiae, Str.uberis, and Str.dysgalactiae), and to simulate the impact of this early diagnosis on the potential number of treatments using a decision-tree model. The results of this study showed that PLCC had an overall accuracy of 77.6%. The results of the decision-tree model based on data from the 12 participating herds, with an overall prevalence of major pathogens of 1.5%, showed a potential decrease in the number of treatments of about 30% (from 3.4% to 2.5%) when PLCC in early lactation (days 5–16) was used to identify cows at risk for major pathogens compared with using SCC at the first milk test (days 17–43). The study confirmed that it is possible to improve animal health and reduce the risk of antimicrobial use through early IMI detection based on PLCC and applying a rationale and prudent antimicrobial protocol.