Metagenomics-Based Analysis of the Age-Related Cumulative Effect of Antibiotic Resistance Genes in Gut Microbiota

Antibiotic resistance in bacteria has become a major global health problem. One of the main reservoirs of antibiotic resistance genes is the human gut microbiota. To characterise these genes, a metagenomic approach was used. In this study, a comprehensive antibiotic resistome catalog was established...

Full description

Bibliographic Details
Main Authors: Lei Wu, Xinqiang Xie, Ying Li, Tingting Liang, Haojie Zhong, Jun Ma, Lingshuang Yang, Juan Yang, Longyan Li, Yu Xi, Haixin Li, Jumei Zhang, Xuefeng Chen, Yu Ding, Qingping Wu
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Antibiotics
Subjects:
Online Access:https://www.mdpi.com/2079-6382/10/8/1006
_version_ 1797524858868858880
author Lei Wu
Xinqiang Xie
Ying Li
Tingting Liang
Haojie Zhong
Jun Ma
Lingshuang Yang
Juan Yang
Longyan Li
Yu Xi
Haixin Li
Jumei Zhang
Xuefeng Chen
Yu Ding
Qingping Wu
author_facet Lei Wu
Xinqiang Xie
Ying Li
Tingting Liang
Haojie Zhong
Jun Ma
Lingshuang Yang
Juan Yang
Longyan Li
Yu Xi
Haixin Li
Jumei Zhang
Xuefeng Chen
Yu Ding
Qingping Wu
author_sort Lei Wu
collection DOAJ
description Antibiotic resistance in bacteria has become a major global health problem. One of the main reservoirs of antibiotic resistance genes is the human gut microbiota. To characterise these genes, a metagenomic approach was used. In this study, a comprehensive antibiotic resistome catalog was established using fecal samples from 246 healthy individuals from world’s longevity township in Jiaoling, China. In total, 606 antibiotic resistance genes were detected. Our results indicated that antibiotic resistance genes in the human gut microbiota accumulate and become more complex with age as older groups harbour the highest abundance of these genes. Tetracycline resistance gene type <i>tetQ</i> was the most abundant group of antibiotic resistance genes in gut microbiota, and the main carrier of antibiotic resistance genes was <i>Bacteroides</i>. Antibiotic efflux, inactivation, and target alteration were found to be the dominant antimicrobial resistance mechanisms. This research may help to establish a comprehensive antibiotic resistance catalog that includes extremely long-lived healthy people such as centenarians, and may provide potential recommendations for controlling the use of antibiotics.
first_indexed 2024-03-10T09:03:33Z
format Article
id doaj.art-a99a01c95c6b4273a50bd6ee5dc05cfd
institution Directory Open Access Journal
issn 2079-6382
language English
last_indexed 2024-03-10T09:03:33Z
publishDate 2021-08-01
publisher MDPI AG
record_format Article
series Antibiotics
spelling doaj.art-a99a01c95c6b4273a50bd6ee5dc05cfd2023-11-22T06:34:35ZengMDPI AGAntibiotics2079-63822021-08-01108100610.3390/antibiotics10081006Metagenomics-Based Analysis of the Age-Related Cumulative Effect of Antibiotic Resistance Genes in Gut MicrobiotaLei Wu0Xinqiang Xie1Ying Li2Tingting Liang3Haojie Zhong4Jun Ma5Lingshuang Yang6Juan Yang7Longyan Li8Yu Xi9Haixin Li10Jumei Zhang11Xuefeng Chen12Yu Ding13Qingping Wu14School of Food and Biological Engineering, Shaanxi University of Science and Technology, Xi’an 710021, ChinaGuangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, ChinaGuangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, ChinaSchool of Food and Biological Engineering, Shaanxi University of Science and Technology, Xi’an 710021, ChinaThe First Affiliated Hospital, School of Clinical Medicine of Guangdong Pharmaceutical University, Guangzhou 510080, ChinaSchool of Food and Biological Engineering, Shaanxi University of Science and Technology, Xi’an 710021, ChinaGuangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, ChinaSchool of Food and Biological Engineering, Shaanxi University of Science and Technology, Xi’an 710021, ChinaGuangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, ChinaGuangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, ChinaGuangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, ChinaGuangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, ChinaSchool of Food and Biological Engineering, Shaanxi University of Science and Technology, Xi’an 710021, ChinaDepartment of Food Science and Technology, Institute of Food Safety and Nutrition, Jinan University, Guangzhou 510632, ChinaGuangdong Provincial Key Laboratory of Microbial Safety and Health, State Key Laboratory of Applied Microbiology Southern China, Institute of Microbiology, Guangdong Academy of Sciences, Guangzhou 510070, ChinaAntibiotic resistance in bacteria has become a major global health problem. One of the main reservoirs of antibiotic resistance genes is the human gut microbiota. To characterise these genes, a metagenomic approach was used. In this study, a comprehensive antibiotic resistome catalog was established using fecal samples from 246 healthy individuals from world’s longevity township in Jiaoling, China. In total, 606 antibiotic resistance genes were detected. Our results indicated that antibiotic resistance genes in the human gut microbiota accumulate and become more complex with age as older groups harbour the highest abundance of these genes. Tetracycline resistance gene type <i>tetQ</i> was the most abundant group of antibiotic resistance genes in gut microbiota, and the main carrier of antibiotic resistance genes was <i>Bacteroides</i>. Antibiotic efflux, inactivation, and target alteration were found to be the dominant antimicrobial resistance mechanisms. This research may help to establish a comprehensive antibiotic resistance catalog that includes extremely long-lived healthy people such as centenarians, and may provide potential recommendations for controlling the use of antibiotics.https://www.mdpi.com/2079-6382/10/8/1006metagenomicsgut microbiotaantibiotic resistance geneslongevity peoplecumulative effect
spellingShingle Lei Wu
Xinqiang Xie
Ying Li
Tingting Liang
Haojie Zhong
Jun Ma
Lingshuang Yang
Juan Yang
Longyan Li
Yu Xi
Haixin Li
Jumei Zhang
Xuefeng Chen
Yu Ding
Qingping Wu
Metagenomics-Based Analysis of the Age-Related Cumulative Effect of Antibiotic Resistance Genes in Gut Microbiota
Antibiotics
metagenomics
gut microbiota
antibiotic resistance genes
longevity people
cumulative effect
title Metagenomics-Based Analysis of the Age-Related Cumulative Effect of Antibiotic Resistance Genes in Gut Microbiota
title_full Metagenomics-Based Analysis of the Age-Related Cumulative Effect of Antibiotic Resistance Genes in Gut Microbiota
title_fullStr Metagenomics-Based Analysis of the Age-Related Cumulative Effect of Antibiotic Resistance Genes in Gut Microbiota
title_full_unstemmed Metagenomics-Based Analysis of the Age-Related Cumulative Effect of Antibiotic Resistance Genes in Gut Microbiota
title_short Metagenomics-Based Analysis of the Age-Related Cumulative Effect of Antibiotic Resistance Genes in Gut Microbiota
title_sort metagenomics based analysis of the age related cumulative effect of antibiotic resistance genes in gut microbiota
topic metagenomics
gut microbiota
antibiotic resistance genes
longevity people
cumulative effect
url https://www.mdpi.com/2079-6382/10/8/1006
work_keys_str_mv AT leiwu metagenomicsbasedanalysisoftheagerelatedcumulativeeffectofantibioticresistancegenesingutmicrobiota
AT xinqiangxie metagenomicsbasedanalysisoftheagerelatedcumulativeeffectofantibioticresistancegenesingutmicrobiota
AT yingli metagenomicsbasedanalysisoftheagerelatedcumulativeeffectofantibioticresistancegenesingutmicrobiota
AT tingtingliang metagenomicsbasedanalysisoftheagerelatedcumulativeeffectofantibioticresistancegenesingutmicrobiota
AT haojiezhong metagenomicsbasedanalysisoftheagerelatedcumulativeeffectofantibioticresistancegenesingutmicrobiota
AT junma metagenomicsbasedanalysisoftheagerelatedcumulativeeffectofantibioticresistancegenesingutmicrobiota
AT lingshuangyang metagenomicsbasedanalysisoftheagerelatedcumulativeeffectofantibioticresistancegenesingutmicrobiota
AT juanyang metagenomicsbasedanalysisoftheagerelatedcumulativeeffectofantibioticresistancegenesingutmicrobiota
AT longyanli metagenomicsbasedanalysisoftheagerelatedcumulativeeffectofantibioticresistancegenesingutmicrobiota
AT yuxi metagenomicsbasedanalysisoftheagerelatedcumulativeeffectofantibioticresistancegenesingutmicrobiota
AT haixinli metagenomicsbasedanalysisoftheagerelatedcumulativeeffectofantibioticresistancegenesingutmicrobiota
AT jumeizhang metagenomicsbasedanalysisoftheagerelatedcumulativeeffectofantibioticresistancegenesingutmicrobiota
AT xuefengchen metagenomicsbasedanalysisoftheagerelatedcumulativeeffectofantibioticresistancegenesingutmicrobiota
AT yuding metagenomicsbasedanalysisoftheagerelatedcumulativeeffectofantibioticresistancegenesingutmicrobiota
AT qingpingwu metagenomicsbasedanalysisoftheagerelatedcumulativeeffectofantibioticresistancegenesingutmicrobiota