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Wu J, Hu Y, Perlin MH, Danko D, Lu J, Oliveira M, Werner J, Zambrano MM, Sierra MA, Osuolale OO, Łabaj P, Rascovan N, Hazrin-Chong NH, Jang S, Suzuki H, Nieto-Caballero M, Prithiviraj B, Lee PKH, Chmielarczyk A, Różańska A, Zhao Y, Wang L, Mason CE, Shi T. Landscape of global urban environmental resistome and its association with local socioeconomic and medical status. SCIENCE CHINA. LIFE SCIENCES 2024; 67:1292-1301. [PMID: 38489008 DOI: 10.1007/s11427-023-2504-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 12/06/2023] [Indexed: 03/17/2024]
Abstract
Antimicrobial resistance (AMR) poses a critical threat to global health and development, with environmental factors-particularly in urban areas-contributing significantly to the spread of antibiotic resistance genes (ARGs). However, most research to date has been conducted at a local level, leaving significant gaps in our understanding of the global status of antibiotic resistance in urban environments. To address this issue, we thoroughly analyzed a total of 86,213 ARGs detected within 4,728 metagenome samples, which were collected by the MetaSUB International Consortium involving diverse urban environments in 60 cities of 27 countries, utilizing a deep-learning based methodology. Our findings demonstrated the strong geographical specificity of urban environmental resistome, and their correlation with various local socioeconomic and medical conditions. We also identified distinctive evolutionary patterns of ARG-related biosynthetic gene clusters (BGCs) across different countries, and discovered that the urban environment represents a rich source of novel antibiotics. Our study provides a comprehensive overview of the global urban environmental resistome, and fills a significant gap in our knowledge of large-scale urban antibiotic resistome analysis.
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Affiliation(s)
- Jun Wu
- Center for Bioinformatics and Computational Biology, and the Institute of Biomedical Sciences, School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Yige Hu
- Center for Bioinformatics and Computational Biology, and the Institute of Biomedical Sciences, School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Michael H Perlin
- Department of Biology, Program on Disease Evolution, University of Louisville, Louisville, 40292, USA
| | - David Danko
- Weill Cornell Medicine, New York, 10065, USA
- The Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, New York, 10065, USA
| | - Jun Lu
- Department of Pulmonary Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200025, China
| | - Manuela Oliveira
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, 4050-290, Portugal
- Ipatimup - Instituto de Patologia e Imunologia Molecular da Universidade do Porto, Porto, 4200-465, Portugal
- Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Porto, 4050-290, Portugal
| | - Johannes Werner
- High Performance and Cloud Computing Group, Zentrum für Datenverarbeitung (ZDV), Eberhard Karls University of Tübingen, Wächterstraße 76, 72074, Tübingen, Germany
| | | | - Maria A Sierra
- Weill Cornell Medicine, New York, 10065, USA
- The Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, New York, 10065, USA
| | - Olayinka O Osuolale
- Applied Environmental Metagenomics and Infectious Diseases Research (AEMIDR), Department of Biological Sciences, Elizade University, Ilara-Mokin, 340271, Nigeria
| | - Paweł Łabaj
- Maopolska Centre of Biotechnology, Jagiellonian University, Kraków, 30-005, Poland
| | - Nicolás Rascovan
- Aix-Marseille Université, Mediterranean Institute of Oceanology, Université de Toulon, CNRS, IRD, UM 110, Marseille, 83041, France
| | - Nur Hazlin Hazrin-Chong
- Department of Biological Sciences and Biotechnology, Faculty of Science and Technology, Universiti Kebangsaan Malaysia UKM, 43600, Bangi, Selangor, Malaysia
| | - Soojin Jang
- Institut Pasteur Korea, Seoul, 13488, Republic of Korea
| | - Haruo Suzuki
- Faculty of Environment and Information Studies, Keio University, Fujisawa, Kanagawa, 252-0882, Japan
| | - Marina Nieto-Caballero
- Civil, Environmental and Architectural Department, University of Colorado at Boulder, Boulder, 80303, USA
| | | | - Patrick K H Lee
- School of Energy and Environment, City University of Hong Kong, Hong Kong, 999077, China
| | - Agnieszka Chmielarczyk
- Department of Microbiology, Faculty of Medicine, Jagiellonian University, Krakow, 30-005, Poland
| | - Anna Różańska
- Department of Microbiology, Faculty of Medicine, Jagiellonian University, Krakow, 30-005, Poland
| | - Yongxiang Zhao
- Biological Targeting Diagnosis and Therapy Research Center, Guangxi Medical University, Nanning, 530021, China.
| | - Lan Wang
- College of Architecture and Urban Planning, Tongji University, Shanghai, 200092, China.
| | - Christopher E Mason
- Weill Cornell Medicine, New York, 10065, USA.
- The Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, New York, 10065, USA.
| | - Tieliu Shi
- Center for Bioinformatics and Computational Biology, and the Institute of Biomedical Sciences, School of Life Sciences, East China Normal University, Shanghai, 200241, China.
- Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University & Capital Medical University, Beijing, 100083, China.
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Jensen EEB, Sedor V, Eshun E, Njage P, Otani S, Aarestrup FM. The resistomes of rural and urban pigs and poultry in Ghana. mSystems 2023; 8:e0062923. [PMID: 37737585 PMCID: PMC10654090 DOI: 10.1128/msystems.00629-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 08/02/2023] [Indexed: 09/23/2023] Open
Abstract
IMPORTANCE To the best of our knowledge, this is the first report on the resistomes that are measured using metagenomics in livestock from Sub-Saharan Africa. We find notable differences in the microbiomes between both pigs and poultry, and those also varied markedly compared to similar samples from Europe. However, for both animal species, the same bacterial taxa drove such differences. In pigs and urban free-range poultry, we find a very low abundance of antimicrobial resistance genes (ARGs), whereas rural free-range poultry displayed similarity to the European average, and industrialized poultry exhibited higher levels. These findings show how different African livestock bacterial communities and resistomes are from their European counterparts. They also underscore the importance of continued surveillance and investigation into antimicrobial resistance across diverse ecosystems, contributing significantly to global efforts toward combating the threat of antibiotic resistance.
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Affiliation(s)
| | - Victoria Sedor
- Veterinary Services Department, Ministry of Food and Agriculture, National Food Safety Laboratory, Accra, Ghana
| | - Emmanuel Eshun
- Veterinary Services Department, Ministry of Food and Agriculture, National Food Safety Laboratory, Accra, Ghana
| | - Patrick Njage
- Technical University of Denmark, Kemitorvet, Denmark
| | - Saria Otani
- Technical University of Denmark, Kemitorvet, Denmark
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Grenni P. Antimicrobial Resistance in Rivers: A Review of the Genes Detected and New Challenges. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2022; 41:687-714. [PMID: 35191071 DOI: 10.1002/etc.5289] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 11/11/2021] [Accepted: 01/06/2022] [Indexed: 06/14/2023]
Abstract
River ecosystems are very important parts of the water cycle and an excellent habitat, food, and drinking water source for many organisms, including humans. Antibiotics are emerging contaminants which can enter rivers from various sources. Several antibiotics and their related antibiotic resistance genes (ARGs) have been detected in these ecosystems by various research programs and could constitute a substantial problem. The presence of antibiotics and other resistance cofactors can boost the development of ARGs in the chromosomes or mobile genetic elements of natural bacteria in rivers. The ARGs in environmental bacteria can also be transferred to clinically important pathogens. However, antibiotics and their resistance genes are both not currently monitored by national or international authorities responsible for controlling the quality of water bodies. For example, they are not included in the contaminant list in the European Water Framework Directive or in the US list of Water-Quality Benchmarks for Contaminants. Although ARGs are naturally present in the environment, very few studies have focused on non-impacted rivers to assess the background ARG levels in rivers, which could provide some useful indications for future environmental regulation and legislation. The present study reviews the antibiotics and associated ARGs most commonly measured and detected in rivers, including the primary analysis tools used for their assessment. In addition, other factors that could enhance antibiotic resistance, such as the effects of chemical mixtures, the effects of climate change, and the potential effects of the coronavirus disease 2019 pandemic, are discussed. Environ Toxicol Chem 2022;41:687-714. © 2022 SETAC.
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Affiliation(s)
- Paola Grenni
- Water Research Institute, National Research Council of Italy, via Salaria km 29.300, Monterotondo, Rome, 00015, Italy
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Guernier-Cambert V, Chamings A, Collier F, Alexandersen S. Diverse Bacterial Resistance Genes Detected in Fecal Samples From Clinically Healthy Women and Infants in Australia-A Descriptive Pilot Study. Front Microbiol 2021; 12:596984. [PMID: 34603219 PMCID: PMC8484959 DOI: 10.3389/fmicb.2021.596984] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Accepted: 08/18/2021] [Indexed: 11/27/2022] Open
Abstract
The gut microbiota is an immense reservoir of antimicrobial resistance genes (ARGs), the so-called “resistome.” In Australia, where antibiotic use is high and resistance rates in some common pathogens are increasing, very little is known about the human resistome. To assess the presence and diversity of ARGs in the gut of Australians from south-eastern Victoria, we investigated fecal samples from clinically healthy infants and pregnant women using non-targeted (shotgun metagenomics sequencing or SMS) and targeted sequencing (two Ion AmpliseqTM panels). All methods detected ARGs in all samples, with the detection overall of 64 unique genes conferring resistance to 12 classes of antibiotics. Predominant ARGs belonged to three classes of antibiotics that are the most frequently prescribed in Australia: tetracycline, β-lactams and MLSB (macrolide, lincosamide, streptogramin B). The three bacterial Orders commonly identified as carrying ARGs were Clostridiales, Bacteroidales, and Enterobacteriales. Our preliminary results indicate that ARGs are ubiquitously present and diverse among the gut microbiota of clinically healthy humans from south-eastern Victoria, Australia. The observed resistance pattern partly overlaps with antimicrobial usage in human medicine in Australia, but ARGs to tetracycline are more common than could be expected. Our current sample is small and limited to south-eastern Victoria, and more data on healthy individuals will be needed to better depict resistance patterns at the population level, which could guide population and/or environmental monitoring and surveillance of antibiotic resistance on various spatio-temporal scales in Australia. For future studies, we recommend using the Ion AmpliseqTM Antimicrobial Resistance Research panel, which is sensitive and user-friendly, or combining several methods to increase the detected diversity.
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Affiliation(s)
- Vanina Guernier-Cambert
- Geelong Centre for Emerging Infectious Diseases, Geelong, VIC, Australia.,School of Medicine, Deakin University, Geelong, VIC, Australia
| | - Anthony Chamings
- Geelong Centre for Emerging Infectious Diseases, Geelong, VIC, Australia.,School of Medicine, Deakin University, Geelong, VIC, Australia
| | - Fiona Collier
- Geelong Centre for Emerging Infectious Diseases, Geelong, VIC, Australia.,School of Medicine, Deakin University, Geelong, VIC, Australia.,Barwon Health, University Hospital Geelong, Geelong, VIC, Australia
| | - Soren Alexandersen
- Geelong Centre for Emerging Infectious Diseases, Geelong, VIC, Australia.,School of Medicine, Deakin University, Geelong, VIC, Australia.,Barwon Health, University Hospital Geelong, Geelong, VIC, Australia
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Anyaso-Samuel S, Sachdeva A, Guha S, Datta S. Metagenomic Geolocation Prediction Using an Adaptive Ensemble Classifier. Front Genet 2021; 12:642282. [PMID: 33959149 PMCID: PMC8093763 DOI: 10.3389/fgene.2021.642282] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 03/18/2021] [Indexed: 11/13/2022] Open
Abstract
Microbiome samples harvested from urban environments can be informative in predicting the geographic location of unknown samples. The idea that different cities may have geographically disparate microbial signatures can be utilized to predict the geographical location based on city-specific microbiome samples. We implemented this idea first; by utilizing standard bioinformatics procedures to pre-process the raw metagenomics samples provided by the CAMDA organizers. We trained several component classifiers and a robust ensemble classifier with data generated from taxonomy-dependent and taxonomy-free approaches. Also, we implemented class weighting and an optimal oversampling technique to overcome the class imbalance in the primary data. In each instance, we observed that the component classifiers performed differently, whereas the ensemble classifier consistently yielded optimal performance. Finally, we predicted the source cities of mystery samples provided by the organizers. Our results highlight the unreliability of restricting the classification of metagenomic samples to source origins to a single classification algorithm. By combining several component classifiers via the ensemble approach, we obtained classification results that were as good as the best-performing component classifier.
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Affiliation(s)
- Samuel Anyaso-Samuel
- Department of Biostatistics, University of Florida, Gainesville, FL, United States
| | - Archie Sachdeva
- Department of Biostatistics, University of Florida, Gainesville, FL, United States
| | - Subharup Guha
- Department of Biostatistics, University of Florida, Gainesville, FL, United States
| | - Somnath Datta
- Department of Biostatistics, University of Florida, Gainesville, FL, United States
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Dhariwal A, Junges R, Chen T, Petersen FC. ResistoXplorer: a web-based tool for visual, statistical and exploratory data analysis of resistome data. NAR Genom Bioinform 2021; 3:lqab018. [PMID: 33796850 PMCID: PMC7991225 DOI: 10.1093/nargab/lqab018] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 12/25/2020] [Accepted: 03/01/2021] [Indexed: 12/13/2022] Open
Abstract
The study of resistomes using whole metagenomic sequencing enables high-throughput identification of resistance genes in complex microbial communities, such as the human microbiome. Over recent years, sophisticated and diverse pipelines have been established to facilitate raw data processing and annotation. Despite the progress, there are no easy-to-use tools for comprehensive visual, statistical and functional analysis of resistome data. Thus, exploration of the resulting large complex datasets remains a key bottleneck requiring robust computational resources and technical expertise, which creates a significant hurdle for advancements in the field. Here, we introduce ResistoXplorer, a user-friendly tool that integrates recent advancements in statistics and visualization, coupled with extensive functional annotations and phenotype collection, to enable high-throughput analysis of common outputs generated from metagenomic resistome studies. ResistoXplorer contains three modules—the ‘Antimicrobial Resistance Gene Table’ module offers various options for composition profiling, functional profiling and comparative analysis of resistome data; the ‘Integration’ module supports integrative exploratory analysis of resistome and microbiome abundance profiles derived from metagenomic samples; finally, the ‘Antimicrobial Resistance Gene List’ module enables users to intuitively explore the associations between antimicrobial resistance genes and the microbial hosts using network visual analytics to gain biological insights. ResistoXplorer is publicly available at http://www.resistoxplorer.no.
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Affiliation(s)
- Achal Dhariwal
- Institute of Oral Biology, Faculty of Dentistry, University of Oslo, 0372 Oslo, Norway
| | - Roger Junges
- Institute of Oral Biology, Faculty of Dentistry, University of Oslo, 0372 Oslo, Norway
| | - Tsute Chen
- Department of Microbiology, The Forsyth Institute, 02142 Cambridge, MA, USA
| | - Fernanda C Petersen
- Institute of Oral Biology, Faculty of Dentistry, University of Oslo, 0372 Oslo, Norway
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Rubin J, Mussio K, Xu Y, Suh J, Riley LW. Prevalence of Antimicrobial Resistance Genes and Integrons in Commensal Gram-Negative Bacteria in a College Community. Microb Drug Resist 2020; 26:1227-1235. [PMID: 31985343 DOI: 10.1089/mdr.2019.0279] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Although the human intestinal microbiome has been shown to harbor antimicrobial drug resistance genes (ARGs), the prevalence of such genes in a healthy population and their impact on extraintestinal infections that occur in that community are not well established. This study sought to identify ARG prevalence and their mobile elements in the intestines of a healthy community population at a California University, and compared these genes to those previously identified among uropathogenic Escherichia coli isolated from patients with urinary tract infection from the same community. We isolated Gram-negative bacteria (GNB) from fecal samples of healthy volunteers and screened them by polymerase chain reaction for class 1 integron cassette sequences and ARGs encoding resistance against ampicillin, trimethoprim-sulfamethoxazole, gentamicin, and colistin. We found antimicrobial-resistant GNB from 83 (81%) of 102 nonredundant rectal swab samples. Seventy-four (72%) of these samples contained β-lactamase genes (blaTEM, blaSHV, blaCTX-M, blaOXA, and blaOXY), dihydrofolate reductase (DHFR) genes (dhfr-A17, dhfr-A12, dhfr-A7, dhfr-A5, dhfr-A21, dhfr-A1, dhfr-A13, and dhfr-7), and aminoglycoside resistance genes (aadA5, aadA2, aadA1, and aadB). Integron sequences were found in 37 (36%) fecal samples. These genes were found in 11 different GNB species. The high prevalence of clinically common ARGs and integrons harbored by GNB in the intestine of a healthy population suggest that human intestines may serve as a major reservoir of these mobile ARGs that appear in E. coli strains causing extraintestinal infections in the same community.
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Affiliation(s)
- Julia Rubin
- Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, California, USA
| | - Kaitlyn Mussio
- Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, California, USA
| | - Yuqi Xu
- Department of Biochemistry and Molecular Biology, College of Life Sciences, Peking University, Beijing, China
| | - Joy Suh
- Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, California, USA
| | - Lee W Riley
- Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, California, USA
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Abstract
Antimicrobial resistance (AMR) has emerged as an obstacle in the supple administration of antimicrobial agents to critical diarrheal patients. Most diarrheal pathogens have developed resistance against the major classes of antibiotics commonly used for assuaging diarrheal symptoms. Antimicrobial resistance develops when pathogens acquire antimicrobial resistance genes (ARGs) through genetic recombination from commensals and pathogens. These are the constituents of the complex microbiota in all ecological niches. The recombination events may occur in the environment or in the gut. Containment of AMR can be achieved through a complete understanding of the complex and diverse structure and function of the microbiota. Its taxonomic entities serve as focal points for the dissemination of antimicrobial resistance genetic determinants. Molecular methods complemented with culture-based diagnostics have been historically implemented to document these natural events. However, the advent of next-generation sequencing has revolutionized the field of molecular epidemiology. It has revolutionized the method of addressing relevant problems like diagnosis and surveillance of infectious diseases and the issue of antimicrobial resistance. Metagenomics is one such next-generation technique that has proved to be a monumental advancement in the area of molecular taxonomy. Current understanding of structure, function and dysbiosis of microbiota associated with antimicrobial resistance was realized due to its conception. This review describes the major milestones achieved due to the advent and implementation of this new technique in the context of antimicrobial resistance. These achievements span a wide panorama from the discovery of novel microorganisms to invention of translational value.
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