# | Rank | Similarity | Title + Abs. | Year | PMID |
|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 |
| 2525 | 0 | 0.9873 | Review of antimicrobial resistance surveillance programmes in livestock and meat in EU with focus on humans. OBJECTIVES: In this review, we describe surveillance programmes reporting antimicrobial resistance (AMR) and resistance genes in bacterial isolates from livestock and meat and compare them with those relevant for human health. METHODS: Publications on AMR in European countries were assessed. PubMed was reviewed and AMR monitoring programmes were identified from reports retrieved by Internet searches and by contacting national authorities in EU/European Economic Area (EEA) member states. RESULTS: Three types of systems were identified: EU programmes, industry-funded supranational programmes and national surveillance systems. The mandatory EU-financed programme has led to some harmonization in national monitoring and provides relevant information on AMR and extended-spectrum β-lactamase/AmpC- and carbapenemase-producing bacteria. At the national level, AMR surveillance systems in livestock apply heterogeneous sampling, testing and reporting modalities, resulting in results that cannot be compared. Most reports are not publicly available or are written in a local language. The industry-funded monitoring systems undertaken by the Centre Européen d'Etudes pour la Santé Animale (CEESA) examines AMR in bacteria in food-producing animals. CONCLUSIONS: Characterization of AMR genes in livestock is applied heterogeneously among countries. Most antibiotics of human interest are included in animal surveillance, although results are difficult to compare as a result of lack of representativeness of animal samples. We suggest that EU/EEA countries provide better uniform AMR monitoring and reporting in livestock and link them better to surveillance systems in humans. Reducing the delay between data collection and publication is also important to allow prompt identification of new resistance patterns. | 2018 | 28970159 |
| 9076 | 1 | 0.9862 | ResiDB: An automated database manager for sequence data. The amount of publicly available DNA sequence data is drastically increasing, making it a tedious task to create sequence databases necessary for the design of diagnostic assays. The selection of appropriate sequences is especially challenging in genes affected by frequent point mutations such as antibiotic resistance genes. To overcome this issue, we have designed the webtool resiDB, a rapid and user-friendly sequence database manager for bacteria, fungi, viruses, protozoa, invertebrates, plants, archaea, environmental and whole genome shotgun sequence data. It automatically identifies and curates sequence clusters to create custom sequence databases based on user-defined input sequences. A collection of helpful visualization tools gives the user the opportunity to easily access, evaluate, edit, and download the newly created database. Consequently, researchers do no longer have to manually manage sequence data retrieval, deal with hardware limitations, and run multiple independent software tools, each having its own requirements, input and output formats. Our tool was developed within the H2020 project FAPIC aiming to develop a single diagnostic assay targeting all sepsis-relevant pathogens and antibiotic resistance mechanisms. ResiDB is freely accessible to all users through https://residb.ait.ac.at/. | 2021 | 33495705 |
| 9075 | 2 | 0.9860 | CamPype: an open-source workflow for automated bacterial whole-genome sequencing analysis focused on Campylobacter. BACKGROUND: The rapid expansion of Whole-Genome Sequencing has revolutionized the fields of clinical and food microbiology. However, its implementation as a routine laboratory technique remains challenging due to the growth of data at a faster rate than can be effectively analyzed and critical gaps in bioinformatics knowledge. RESULTS: To address both issues, CamPype was developed as a new bioinformatics workflow for the genomics analysis of sequencing data of bacteria, especially Campylobacter, which is the main cause of gastroenteritis worldwide making a negative impact on the economy of the public health systems. CamPype allows fully customization of stages to run and tools to use, including read quality control filtering, read contamination, reads extension and assembly, bacterial typing, genome annotation, searching for antibiotic resistance genes, virulence genes and plasmids, pangenome construction and identification of nucleotide variants. All results are processed and resumed in an interactive HTML report for best data visualization and interpretation. CONCLUSIONS: The minimal user intervention of CamPype makes of this workflow an attractive resource for microbiology laboratories with no expertise in bioinformatics as a first line method for bacterial typing and epidemiological analyses, that would help to reduce the costs of disease outbreaks, or for comparative genomic analyses. CamPype is publicly available at https://github.com/JoseBarbero/CamPype . | 2023 | 37474912 |
| 6508 | 3 | 0.9858 | Synergizing Ecotoxicology and Microbiome Data Is Key for Developing Global Indicators of Environmental Antimicrobial Resistance. The One Health concept recognises the interconnectedness of humans, plants, animals and the environment. Recent research strongly supports the idea that the environment serves as a significant reservoir for antimicrobial resistance (AMR). However, the complexity of natural environments makes efforts at AMR public health risk assessment difficult. We lack sufficient data on key ecological parameters that influence AMR, as well as the primary proxies necessary for evaluating risks to human health. Developing environmental AMR 'early warning systems' requires models with well-defined parameters. This is necessary to support the implementation of clear and targeted interventions. In this review, we provide a comprehensive overview of the current tools used globally for environmental AMR human health risk assessment and the underlying knowledge gaps. We highlight the urgent need for standardised, cost-effective risk assessment frameworks that are adaptable across different environments and regions to enhance comparability and reliability. These frameworks must also account for previously understudied AMR sources, such as horticulture, and emerging threats like climate change. In addition, integrating traditional ecotoxicology with modern 'omics' approaches will be essential for developing more comprehensive risk models and informing targeted AMR mitigation strategies. | 2024 | 39611949 |
| 6686 | 4 | 0.9858 | The Impact of Wastewater on Antimicrobial Resistance: A Scoping Review of Transmission Pathways and Contributing Factors. BACKGROUND/OBJECTIVES: Antimicrobial resistance (AMR) is a global issue driven by the overuse of antibiotics in healthcare, agriculture, and veterinary settings. Wastewater and treatment plants (WWTPs) act as reservoirs for antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs). The One Health approach emphasizes the interconnectedness of human, animal, and environmental health in addressing AMR. This scoping review analyzes wastewater's role in the AMR spread, identifies influencing factors, and highlights research gaps to guide interventions. METHODS: This scoping review followed the PRISMA-ScR guidelines. A comprehensive literature search was conducted across the PubMed and Web of Science databases for articles published up to June 2024, supplemented by manual reference checks. The review focused on wastewater as a source of AMR, including hospital effluents, industrial and urban sewage, and agricultural runoff. Screening and selection were independently performed by two reviewers, with conflicts resolved by a third. RESULTS: Of 3367 studies identified, 70 met the inclusion criteria. The findings indicated that antibiotic residues, heavy metals, and microbial interactions in wastewater are key drivers of AMR development. Although WWTPs aim to reduce contaminants, they often create conditions conducive to horizontal gene transfer, amplifying resistance. Promising interventions, such as advanced treatment methods and regulatory measures, exist but require further research and implementation. CONCLUSIONS: Wastewater plays a pivotal role in AMR dissemination. Targeted interventions in wastewater management are essential to mitigate AMR risks. Future studies should prioritize understanding AMR dynamics in wastewater ecosystems and evaluating scalable mitigation strategies to support global health efforts. | 2025 | 40001375 |
| 6689 | 5 | 0.9856 | Wastewater-Based Epidemiology as a Complementary Tool for Antimicrobial Resistance Surveillance: Overcoming Barriers to Integration. This commentary highlights the potential of wastewater-based epidemiology (WBE) as a complementary tool for antimicrobial resistance (AMR) surveillance. WBE can support the early detection of resistance trends at the population level, including in underserved communities. However, several challenges remain, including technical variability, complexities in data interpretation, and regulatory gaps. An additional limitation is the uncertainty surrounding the origin of resistant bacteria and their genes in wastewater, which may derive not only from human sources but also from industrial, agricultural, or infrastructural contributors. Therefore, effective integration of WBE into public health systems will require standardized methods, sustained investment, and cross-sector collaboration. This could be achieved through joint monitoring initiatives that combine hospital wastewater data with agricultural and municipal surveillance to inform antibiotic stewardship policies. Overcoming these barriers could position WBE as an innovative tool for AMR monitoring, enhancing early warning systems and supporting more responsive, equitable, and preventive public health strategies. | 2025 | 40522150 |
| 6653 | 6 | 0.9856 | Making waves: How does the emergence of antimicrobial resistance affect policymaking? This article considers current trends in antimicrobial resistance (AMR) research and knowledge gaps relevant to policymaking in the water sector. Specifically, biological indicators of AMR (antibiotic-resistant bacteria and their resistance genes) and detection methods that have been used so far are identified and discussed, as well as the problems with and solutions to the collection of AMR data, sewage surveillance lessons from the COVID-19 pandemic, and the financial burden caused by AMR, which could be synergically used to improve advocacy on AMR issues in the water sector. Finally, this article proposes solutions to overcoming existing hurdles and shortening the time it will take to have an impact on policymaking and regulation in the sector. | 2021 | 34688095 |
| 9074 | 7 | 0.9856 | BacAnt: A Combination Annotation Server for Bacterial DNA Sequences to Identify Antibiotic Resistance Genes, Integrons, and Transposable Elements. Whole genome sequencing (WGS) of bacteria has become a routine method in diagnostic laboratories. One of the clinically most useful advantages of WGS is the ability to predict antimicrobial resistance genes (ARGs) and mobile genetic elements (MGEs) in bacterial sequences. This allows comprehensive investigations of such genetic features but can also be used for epidemiological studies. A plethora of software programs have been developed for the detailed annotation of bacterial DNA sequences, such as rapid annotation using subsystem technology (RAST), Resfinder, ISfinder, INTEGRALL and The Transposon Registry. Unfortunately, to this day, a reliable annotation tool of the combination of ARGs and MGEs is not available, and the generation of genbank files requires much manual input. Here, we present a new webserver which allows the annotation of ARGs, integrons and transposable elements at the same time. The pipeline generates genbank files automatically, which are compatible with Easyfig for comparative genomic analysis. Our BacAnt code and standalone software package are available at https://github.com/xthua/bacant with an accompanying web application at http://bacant.net. | 2021 | 34367079 |
| 5120 | 8 | 0.9855 | ARIBA: rapid antimicrobial resistance genotyping directly from sequencing reads. Antimicrobial resistance (AMR) is one of the major threats to human and animal health worldwide, yet few high-throughput tools exist to analyse and predict the resistance of a bacterial isolate from sequencing data. Here we present a new tool, ARIBA, that identifies AMR-associated genes and single nucleotide polymorphisms directly from short reads, and generates detailed and customizable output. The accuracy and advantages of ARIBA over other tools are demonstrated on three datasets from Gram-positive and Gram-negative bacteria, with ARIBA outperforming existing methods. | 2017 | 29177089 |
| 9078 | 9 | 0.9854 | MetaCherchant: analyzing genomic context of antibiotic resistance genes in gut microbiota. MOTIVATION: Antibiotic resistance is an important global public health problem. Human gut microbiota is an accumulator of resistance genes potentially providing them to pathogens. It is important to develop tools for identifying the mechanisms of how resistance is transmitted between gut microbial species and pathogens. RESULTS: We developed MetaCherchant-an algorithm for extracting the genomic environment of antibiotic resistance genes from metagenomic data in the form of a graph. The algorithm was validated on a number of simulated and published datasets, as well as applied to new 'shotgun' metagenomes of gut microbiota from patients with Helicobacter pylori who underwent antibiotic therapy. Genomic context was reconstructed for several major resistance genes. Taxonomic annotation of the context suggests that within a single metagenome, the resistance genes can be contained in genomes of multiple species. MetaCherchant allows reconstruction of mobile elements with resistance genes within the genomes of bacteria using metagenomic data. Application of MetaCherchant in differential mode produced specific graph structures suggesting the evidence of possible resistance gene transmission within a mobile element that occurred as a result of the antibiotic therapy. MetaCherchant is a promising tool giving researchers an opportunity to get an insight into dynamics of resistance transmission in vivo basing on metagenomic data. AVAILABILITY AND IMPLEMENTATION: Source code and binaries are freely available for download at https://github.com/ctlab/metacherchant. The code is written in Java and is platform-independent. COTANCT: ulyantsev@rain.ifmo.ru. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. | 2018 | 29092015 |
| 6634 | 10 | 0.9853 | Making waves: The NORMAN antibiotic resistant bacteria and resistance genes database (NORMAN ARB&ARG)-An invitation for collaboration to tackle antibiotic resistance. With the global concerns on antibiotic resistance (AR) as a public health issue, it is pivotal to have data exchange platforms for studies on antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in the environment. For this purpose, the NORMAN Association is hosting the NORMAN ARB&ARG database, which was developed within the European project ANSWER. The present article provides an overview on the database functionalities, the extraction and the contribution of data to the database. In this study, AR data from three studies from China and Nepal were extracted and imported into the NORMAN ARB&ARG in addition to the existing AR data from 11 studies (mainly European studies) on the database. This feasibility study demonstrates how the scientific community can share their data on AR to generate an international evidence base to inform AR mitigation strategies. The open and FAIR data are of high potential relevance for regulatory applications, including the development of emission limit values / environmental quality standards in relation to AR. The growth in sharing of data and analytical methods will foster collaboration on risk management of AR worldwide, and facilitate the harmonization in the effort for identification and surveillance of critical hotspots of AR. The NORMAN ARB&ARG database is publicly available at: https://www.norman-network.com/nds/bacteria/. | 2024 | 38723350 |
| 6609 | 11 | 0.9853 | Antimicrobial-resistant bacteria in international travelers. PURPOSE OF REVIEW: Antimicrobial resistance (AMR) in bacteria poses a major risk to global public health, with many factors contributing to the observed increase in AMR. International travel is one recognized contributor. The purpose of this review is to summarize current knowledge regarding the acquisition, carriage and spread of AMR bacteria by international travelers. RECENT FINDINGS: Recent studies have highlighted that travel is an important risk factor for the acquisition of AMR bacteria, with approximately 30% of studied travelers returning with an acquired AMR bacterium. Epidemiological studies have shown there are three major risk factors for acquisition: travel destination, antimicrobial usage and travelers' diarrhea (TD). Analyses have begun to illustrate the AMR genes that are acquired and spread by travelers, risk factors for acquisition and carriage of AMR bacteria, and local transmission of imported AMR organisms. SUMMARY: International travel is a contributor to the acquisition and dissemination of AMR organisms globally. Efforts to reduce the burden of AMR organisms should include a focus on international travelers. Routine genomic surveillance would further elucidate the role of international travel in the global spread of AMR bacteria. | 2021 | 34267046 |
| 6506 | 12 | 0.9852 | Mitigating antimicrobial resistance through effective hospital wastewater management in low- and middle-income countries. Hospital wastewater (HWW) is a significant environmental and public health threat, containing high levels of pollutants such as antibiotic-resistant bacteria (ARB), antibiotic-resistant genes (ARGs), antibiotics, disinfectants, and heavy metals. This threat is of particular concern in low- and middle-income countries (LMICs), where untreated effluents are often used for irrigating vegetables crops, leading to direct and indirect human exposure. Despite being a potential hotspot for the spread of antimicrobial resistance (AMR), existing HWW treatment systems in LMICs primarily target conventional pollutants and lack effective standards for monitoring the removal of ARB and ARGs. Consequently, untreated or inadequately treated HWW continues to disseminate ARB and ARGs, exacerbating the risk of AMR proliferation. Addressing this requires targeted interventions, including cost-effective treatment solutions, robust AMR monitoring protocols, and policy-driven strategies tailored to LMICs. This perspective calls for a paradigm shift in HWW management in LMIC, emphasizing the broader implementation of onsite treatment systems, which are currently rare. Key recommendations include developing affordable and contextually adaptable technologies for eliminating ARB and ARGs and enforcing local regulations for AMR monitoring and control in wastewater. Addressing these challenges is essential for protecting public health, preventing the environmental spread of resistance, and contributing to a global effort to preserve the efficacy of antibiotics. Recommendations include integrating scalable onsite technologies, leveraging local knowledge, and implementing comprehensive AMR-focused regulatory frameworks. | 2024 | 39944563 |
| 6656 | 13 | 0.9852 | Understanding the Evolution and Transmission Dynamics of Antibiotic Resistance Genes: A Comprehensive Review. Antibiotic resistance poses a formidable challenge to global public health, necessitating comprehensive understanding and strategic interventions. This review explores the evolution and transmission dynamics of antibiotic resistance genes, with a focus on Bangladesh. The indiscriminate use of antibiotics, compounded by substandard formulations and clinical misdiagnosis, fuels the emergence and spread of resistance in the country. Studies reveal high resistance rates among common pathogens, emphasizing the urgent need for targeted interventions and rational antibiotic use. Molecular assessments uncover a diverse array of antibiotic resistance genes in environmental reservoirs, highlighting the complex interplay between human activities and resistance dissemination. Horizontal gene transfer mechanisms, particularly plasmid-mediated conjugation, facilitate the exchange of resistance determinants among bacterial populations, driving the evolution of multidrug-resistant strains. The review discusses clinical implications, emphasizing the interconnectedness of environmental and clinical settings in resistance dynamics. Furthermore, bioinformatic and experimental evidence elucidates novel mechanisms of resistance gene transfer, underscoring the dynamic nature of resistance evolution. In conclusion, combating antibiotic resistance requires a multifaceted approach, integrating surveillance, stewardship, and innovative research to preserve the efficacy of antimicrobial agents and safeguard public health. | 2024 | 39113256 |
| 6507 | 14 | 0.9852 | What Are the Drivers Triggering Antimicrobial Resistance Emergence and Spread? Outlook from a One Health Perspective. Antimicrobial resistance (AMR) has emerged as a critical global public health threat, exacerbating healthcare burdens and imposing substantial economic costs. Currently, AMR contributes to nearly five million deaths annually worldwide, surpassing mortality rates of any single infectious disease. The economic burden associated with AMR-related disease management is estimated at approximately $730 billion per year. This review synthesizes current research on the mechanisms and multifaceted drivers of AMR development and dissemination through the lens of the One Health framework, which integrates human, animal, and environmental health perspectives. Intrinsic factors, including antimicrobial resistance genes (ARGs) and mobile genetic elements (MGEs), enable bacteria to evolve adaptive resistance mechanisms such as enzymatic inactivation, efflux pumps, and biofilm formation. Extrinsic drivers span environmental stressors (e.g., antimicrobials, heavy metals, disinfectants), socioeconomic practices, healthcare policies, and climate change, collectively accelerating AMR proliferation. Horizontal gene transfer and ecological pressures further facilitate the spread of antimicrobial-resistant bacteria across ecosystems. The cascading impacts of AMR threaten human health and agricultural productivity, elevate foodborne infection risks, and impose substantial economic burdens, particularly in low- and middle-income countries. To address this complex issue, the review advocates for interdisciplinary collaboration, robust policy implementation (e.g., antimicrobial stewardship), and innovative technologies (e.g., genomic surveillance, predictive modeling) under the One Health paradigm. Such integrated strategies are essential to mitigate AMR transmission, safeguard global health, and ensure sustainable development. | 2025 | 40558133 |
| 6606 | 15 | 0.9850 | Comprehensive analysis of antimicrobial resistance in the Southwest Indian Ocean: focus on WHO critical and high priority pathogens. The spread of antimicrobial resistance (AMR) is a major global concern, and the islands of the Southwest Indian Ocean (SWIO) are not exempt from this phenomenon. As strategic crossroads between Southern Africa and the Indian subcontinent, these islands are constantly threatened by the importation of multidrug-resistant bacteria from these regions. In this systematic review, our aim was to assess the epidemiological situation of AMR in humans in the SWIO islands, focusing on bacterial species listed as priority by the World Health Organization. Specifically, we examined Enterobacterales, Acinetobacter spp., Pseudomonas spp. resistant to carbapenems, and Enterococcus spp. resistant to vancomycin. Our main objectives were to map the distribution of these resistant bacteria in the SWIO islands and identify the genes involved in their resistance mechanisms. We conducted literature review focusing on Comoros, Madagascar, Maldives, Mauritius, Mayotte, Reunion Island, Seychelles, Sri Lanka, and Zanzibar. Our findings revealed a growing interest in the investigation of these pathogens and provided evidence of their active circulation in many of the territories investigated. However, we also identified disparities in terms of data availability between the targeted bacteria and among the different territories, emphasizing the need to strengthen collaborative efforts to establish an efficient regional surveillance network. | 2024 | 38628847 |
| 9083 | 16 | 0.9850 | ARGNet: using deep neural networks for robust identification and classification of antibiotic resistance genes from sequences. BACKGROUND: Emergence of antibiotic resistance in bacteria is an important threat to global health. Antibiotic resistance genes (ARGs) are some of the key components to define bacterial resistance and their spread in different environments. Identification of ARGs, particularly from high-throughput sequencing data of the specimens, is the state-of-the-art method for comprehensively monitoring their spread and evolution. Current computational methods to identify ARGs mainly rely on alignment-based sequence similarities with known ARGs. Such approaches are limited by choice of reference databases and may potentially miss novel ARGs. The similarity thresholds are usually simple and could not accommodate variations across different gene families and regions. It is also difficult to scale up when sequence data are increasing. RESULTS: In this study, we developed ARGNet, a deep neural network that incorporates an unsupervised learning autoencoder model to identify ARGs and a multiclass classification convolutional neural network to classify ARGs that do not depend on sequence alignment. This approach enables a more efficient discovery of both known and novel ARGs. ARGNet accepts both amino acid and nucleotide sequences of variable lengths, from partial (30-50 aa; 100-150 nt) sequences to full-length protein or genes, allowing its application in both target sequencing and metagenomic sequencing. Our performance evaluation showed that ARGNet outperformed other deep learning models including DeepARG and HMD-ARG in most of the application scenarios especially quasi-negative test and the analysis of prediction consistency with phylogenetic tree. ARGNet has a reduced inference runtime by up to 57% relative to DeepARG. CONCLUSIONS: ARGNet is flexible, efficient, and accurate at predicting a broad range of ARGs from the sequencing data. ARGNet is freely available at https://github.com/id-bioinfo/ARGNet , with an online service provided at https://ARGNet.hku.hk . Video Abstract. | 2024 | 38725076 |
| 5115 | 17 | 0.9850 | Search Engine for Antimicrobial Resistance: A Cloud Compatible Pipeline and Web Interface for Rapidly Detecting Antimicrobial Resistance Genes Directly from Sequence Data. BACKGROUND: Antimicrobial resistance remains a growing and significant concern in human and veterinary medicine. Current laboratory methods for the detection and surveillance of antimicrobial resistant bacteria are limited in their effectiveness and scope. With the rapidly developing field of whole genome sequencing beginning to be utilised in clinical practice, the ability to interrogate sequencing data quickly and easily for the presence of antimicrobial resistance genes will become increasingly important and useful for informing clinical decisions. Additionally, use of such tools will provide insight into the dynamics of antimicrobial resistance genes in metagenomic samples such as those used in environmental monitoring. RESULTS: Here we present the Search Engine for Antimicrobial Resistance (SEAR), a pipeline and web interface for detection of horizontally acquired antimicrobial resistance genes in raw sequencing data. The pipeline provides gene information, abundance estimation and the reconstructed sequence of antimicrobial resistance genes; it also provides web links to additional information on each gene. The pipeline utilises clustering and read mapping to annotate full-length genes relative to a user-defined database. It also uses local alignment of annotated genes to a range of online databases to provide additional information. We demonstrate SEAR's application in the detection and abundance estimation of antimicrobial resistance genes in two novel environmental metagenomes, 32 human faecal microbiome datasets and 126 clinical isolates of Shigella sonnei. CONCLUSIONS: We have developed a pipeline that contributes to the improved capacity for antimicrobial resistance detection afforded by next generation sequencing technologies, allowing for rapid detection of antimicrobial resistance genes directly from sequencing data. SEAR uses raw sequencing data via an intuitive interface so can be run rapidly without requiring advanced bioinformatic skills or resources. Finally, we show that SEAR is effective in detecting antimicrobial resistance genes in metagenomic and isolate sequencing data from both environmental metagenomes and sequencing data from clinical isolates. | 2015 | 26197475 |
| 6668 | 18 | 0.9850 | Complexities in understanding antimicrobial resistance across domesticated animal, human, and environmental systems. Antimicrobial resistance (AMR) is a significant threat to both human and animal health. The spread of AMR bacteria and genes across systems can occur through a myriad of pathways, both related and unrelated to agriculture, including via wastewater, soils, manure applications, direct exchange between humans and animals, and food exposure. Tracing origins and drivers of AMR bacteria and genes is challenging due to the array of contexts and the complexity of interactions overlapping health practice, microbiology, genetics, applied science and engineering, as well as social and human factors. Critically assessing the diverse and sometimes contradictory AMR literature is a valuable step in identifying tractable mitigation options to stem AMR spread. In this article we review research on the nonfoodborne spread of AMR, with a focus on domesticated animals and the environment and possible exposures to humans. Attention is especially placed on delineating possible sources and causes of AMR bacterial phenotypes, including underpinning the genetics important to human and animal health. | 2019 | 30924539 |
| 6600 | 19 | 0.9850 | Metagenomic approaches for the quantification of antibiotic resistance genes in swine wastewater treatment system: a systematic review. This systematic review aims to identify the metagenomic methodological approaches employed for the detection of antimicrobial resistance genes (ARGs) in swine wastewater treatment systems. The search terms used were metagenome AND bacteria AND ("antimicrobial resistance gene" OR resistome OR ARG) AND wastewater AND (swine OR pig), and the search was conducted across the following electronic databases: PubMed, Scopus, ScienceDirect, Web of Science, Embase, and Cochrane Library. The search was limited to studies published between 2020 and 2024. Of the 220 studies retrieved, eight met the eligibility criteria for full-text analysis. The number of publications in this research area has increased in recent years, with China contributing the highest number of studies. ARGs are typically identified using bioinformatics pipelines that include steps such as quality trimming, assembly, metagenome-assembled genome (MAG) reconstruction, open reading frame (ORF) prediction, and ARG annotation. However, comparing ARGs quantification across studies remains challenging due to methodological differences and variability in quantification approaches. Therefore, this systematic review highlights the need for methodological standardization to facilitate comparison and enhance our understanding of antimicrobial resistance in swine wastewater treatment systems through metagenomic approaches. | 2025 | 40788461 |