Metagenomic analysis reveals antibiotic resistance profiles in tissue samples from patients with diabetic foot infections

• Published in: Journal of global antimicrobial resistance. 2023-09, Vol.34, p.202-210
• Main Authors: Zhang, Xiujuan, Li, Haihui, Wang, Yonghui, Kang, Yutong, Li, Zhenjun
• Format: Article
• Language: English
• Subjects: Antibiotic resistance genes; Diabetic foot infections; Metagenomic analysis
• ISSN: 2213-7165; 2213-7173
• DOI: 10.1016/j.jgar.2023.05.008

•Tissue samples from diabetic foot infection patients detected 229 ARG subtypes.•Multidrug, tetracycline, MLS, and beta-lactam resistance genes were the dominant.•The microbial community composition was the determinant of the ARGs.•A total of 29 species were speculated as potential hosts of the 28 ARGs.•Procrustes analysis suggested mobile genetic elements were determining factors of the ARGs. Treating patients with diabetic foot infection (DFI) is challenging because of high rates of antibiotic resistance. Therefore, to administer a suitable antibiotic treatment, it is necessary to know the antibiotic resistance patterns in DFIs. To explore this question, we selected metagenomic data of 36 tissue samples from patients with DFI in the National Center for Biotechnology Information Sequence Read Archive database. A total of 229 antibiotic-resistant gene (ARG) subtypes belonging to 20 ARG types were detected. The antibiotic resistome of 229 different genes in the tissue samples of patients with DFI comprised 24 core and 205 accessory resistance genes. Among the core antibiotic resistome, multidrug, tetracycline, macrolide-lincosamide-streptogramin, and beta-lactam resistance genes were the dominant categories. Procrustes analysis indicated that both the microbial community composition and mobile genetic elements (MGEs) were determinants of the ARGs. In the network analysis, 29 species were speculated to be potential hosts of 28 ARGs based on the co-occurrence results. Plasmids and transposons were the most common elements that co-occurred with ARGs. Our study provided detailed information about antibiotic resistance patterns in DFI, which has practical implications for suggesting a more specific antibiotic choice.