Enhancing Drug Efficacy against Mastitis Pathogens—An In Vitro Pilot Study in Staphylococcus aureus and Staphylococcus epidermidis

Autor: Saravana Babu Chidambaram, Jian Yang, Meena Kishore Sakharkar, Karthic Rajamanickam
Rok vydání: 2020
Předmět:
Zdroj: Animals, Vol 10, Iss 2117, p 2117 (2020)
Animals
Volume 10
Issue 11
ISSN: 2076-2615
Popis: Background: Bovine mastitis is one of the major infectious diseases in dairy cattle, resulting in large economic loss due to decreased milk production and increased production cost to the dairy industry. Antibiotics are commonly used to prevent/treat bovine mastitis infections. However, increased antibiotic resistance and consumers&rsquo
concern regarding antibiotic overuse make it prudent and urgent to develop novel therapeutic protocols for this disease. Materials and methods: Potential druggable targets were found in 20 mastitis-causing pathogens and conserved and unique targets were identified. Bacterial strains Staphylococcus aureus (ATCC 29213, and two clinical isolates CI 1 and CI 2) and Staphylococcus epidermidis (ATCC 12228, and two clinical isolates CI 1 and CI 2) were used in the present study for validation of an effective drug combination. Results: In the current study, we identified the common and the unique druggable targets for twenty mastitis-causing pathogens using an integrative approach. Furthermore, we showed that phosphorylcholine, a drug for a unique target gamma-hemolysin component B in Staphylococcus aureus, and ceftiofur, the mostly used veterinary antibiotic that is FDA approved for treating mastitis infections, exhibit a synergistic effect against S. aureus and a strong additive effect against Staphylococcus epidermidis in vitro. Conclusion: Based on the data generated in this study, we propose that combination therapy with drugs that work synergistically against conserved and unique targets can help increase efficacy and lower the usage of antibiotics for treating bacterial infections. However, these data need further validations in animal models of infection.
Databáze: OpenAIRE
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