Design and Preclinical Development of a Phage Product for the Treatment of Antibiotic-Resistant Staphylococcus aureus Infections.
Susan M LehmanGillian MearnsDeborah RankinRobert A ColeFrenk SmrekarSteven D BranstonSandra MoralesPublished in: Viruses (2019)
Bacteriophages, viruses that only kill specific bacteria, are receiving substantial attention as nontraditional antibacterial agents that may help alleviate the growing antibiotic resistance problem in medicine. We describe the design and preclinical development of AB-SA01, a fixed-composition bacteriophage product intended to treat Staphylococcus aureus infections. AB-SA01 contains three naturally occurring, obligately lytic myoviruses related to Staphylococcus phage K. AB-SA01 component phages have been sequenced and contain no identifiable bacterial virulence or antibiotic resistance genes. In vitro, AB-SA01 killed 94.5% of 401 clinical Staphylococcus aureus isolates, including methicillin-resistant and vancomycin-intermediate ones for a total of 95% of the 205 known multidrug-resistant isolates. The spontaneous frequency of resistance to AB-SA01 was ≤3 × 10-9, and resistance emerging to one component phage could be complemented by the activity of another component phage. In both neutropenic and immunocompetent mouse models of acute pneumonia, AB-SA01 reduced lung S. aureus populations equivalently to vancomycin. Overall, the inherent characteristics of AB-SA01 component phages meet regulatory and generally accepted criteria for human use, and the preclinical data presented here have supported production under good manufacturing practices and phase 1 clinical studies with AB-SA01.
Keyphrases
- staphylococcus aureus
- pseudomonas aeruginosa
- methicillin resistant staphylococcus aureus
- biofilm formation
- multidrug resistant
- antibiotic resistance genes
- healthcare
- endothelial cells
- cell therapy
- escherichia coli
- cystic fibrosis
- primary care
- mouse model
- microbial community
- stem cells
- liver failure
- transcription factor
- deep learning
- candida albicans
- data analysis