Utilising novel antimicrobial peptides identified from the rumen microbiome as a potential treatment for multiple A. baumannii strains. Issue Volume 1(2019)Issue A (8th March 2019)

• Record Type: Journal Article
• Authors: Alexander, Peter; Oyama, Linda; Huws, Sharon
• Is Part Of: Access microbiology. Volume 1(2019)Issue A
• Publication Date: 2019-03-08
• Subjects: Microbiology -- Periodicals; 579
• DOI: 10.1099/acmi.ac2019.po0043
• Languages: English
• ISSNs: 2516-8290

Abstract

Abstract : Antibiotic and antimicrobial resistance is a global issue, not only for medical and veterinary treatment, but also for economic development. One of the critical bacterial pathogens known to develop resistance to antimicrobial agents is Acinetobacter baumannii, one of the ESKAPE pathogens. A. baumannii is an aerobic Gram-negative coccobacillus bacterium associated with bacteraemia, urinary tract infections and ventilator-associated pneumonia, and is typically viewed as an opportunistic pathogen. Previous research has shown that clinical strains of A. baumannii have susceptibility to novel antimicrobial peptides, specifically those identified from a rumen metagenomic dataset. Using standardised 96 well MIC testing, 3 antimicrobial peptides (Lynronne-1, Lynronne-2, Lynronne-3, identified as part of a previous research project by the Huws Lab) were compared against multiple strains of A. baumannii, in order to show efficacy of treatment against a wider variety of strains. Of the strains tested, a number were clinical isolates with demonstrated resistance (imipenem resistant, OXO-23/OXO-50). The results show that the antimicrobial peptides had noticeable inhibitory effects on the bacterial growth. There was also variation between the 3 peptides utilised, with Lynronne-1 appearing to have the lowest MIC over the majority of the strains tested. Further research as part of this project will utilise other identified antimicrobial peptides, including rationally designed peptides, as well as potentially using another gastrointestinal microbiome metagenomic dataset to identify a greater number of novel antimicrobial peptides.