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

ABSTRACT: Objectives: 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. Methods: To explore this question,...

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Main Authors: Xiujuan Zhang, Haihui Li, Yonghui Wang, Yutong Kang, Zhenjun Li
Format: Article
Language:English
Published: Elsevier 2023-09-01
Series:Journal of Global Antimicrobial Resistance
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2213716523000863
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author Xiujuan Zhang
Haihui Li
Yonghui Wang
Yutong Kang
Zhenjun Li
author_facet Xiujuan Zhang
Haihui Li
Yonghui Wang
Yutong Kang
Zhenjun Li
author_sort Xiujuan Zhang
collection DOAJ
description ABSTRACT: Objectives: 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. Methods: 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. Results: 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. Conclusions: Our study provided detailed information about antibiotic resistance patterns in DFI, which has practical implications for suggesting a more specific antibiotic choice.
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spelling doaj.art-378523eb9d9e43d1a7523f108f6b0a532023-09-09T04:55:08ZengElsevierJournal of Global Antimicrobial Resistance2213-71652023-09-0134202210Metagenomic analysis reveals antibiotic resistance profiles in tissue samples from patients with diabetic foot infectionsXiujuan Zhang0Haihui Li1Yonghui Wang2Yutong Kang3Zhenjun Li4Department of Endocrinology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, ChinaDepartment of Endocrinology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, ChinaDepartment of Endocrinology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, ChinaState Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, ChinaState Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China; Corresponding author at: National Institute for Communicable Disease Control and Prevention, State Key Laboratory for Infectious Disease Prevention and Control, 155 Changbai Road, Changping District, Beijing, 102200, China.ABSTRACT: Objectives: 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. Methods: 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. Results: 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. Conclusions: Our study provided detailed information about antibiotic resistance patterns in DFI, which has practical implications for suggesting a more specific antibiotic choice.http://www.sciencedirect.com/science/article/pii/S2213716523000863Diabetic foot infectionsMetagenomic analysisAntibiotic resistance genes
spellingShingle Xiujuan Zhang
Haihui Li
Yonghui Wang
Yutong Kang
Zhenjun Li
Metagenomic analysis reveals antibiotic resistance profiles in tissue samples from patients with diabetic foot infections
Journal of Global Antimicrobial Resistance
Diabetic foot infections
Metagenomic analysis
Antibiotic resistance genes
title Metagenomic analysis reveals antibiotic resistance profiles in tissue samples from patients with diabetic foot infections
title_full Metagenomic analysis reveals antibiotic resistance profiles in tissue samples from patients with diabetic foot infections
title_fullStr Metagenomic analysis reveals antibiotic resistance profiles in tissue samples from patients with diabetic foot infections
title_full_unstemmed Metagenomic analysis reveals antibiotic resistance profiles in tissue samples from patients with diabetic foot infections
title_short Metagenomic analysis reveals antibiotic resistance profiles in tissue samples from patients with diabetic foot infections
title_sort metagenomic analysis reveals antibiotic resistance profiles in tissue samples from patients with diabetic foot infections
topic Diabetic foot infections
Metagenomic analysis
Antibiotic resistance genes
url http://www.sciencedirect.com/science/article/pii/S2213716523000863
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AT yonghuiwang metagenomicanalysisrevealsantibioticresistanceprofilesintissuesamplesfrompatientswithdiabeticfootinfections
AT yutongkang metagenomicanalysisrevealsantibioticresistanceprofilesintissuesamplesfrompatientswithdiabeticfootinfections
AT zhenjunli metagenomicanalysisrevealsantibioticresistanceprofilesintissuesamplesfrompatientswithdiabeticfootinfections