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PubMed2026

A comprehensive review of AI innovations for tackling antimicrobial resistance.

Antimicrobial resistance (AMR) represents a major global public health concern, rendering available antimicrobials ineffective and leading to infections that are difficult to treat. Artificial intelligence (AI) has been increasingly applied across the AMR continuum, including resistance prediction, rapid diagnostics, new antimicrobial discovery, drug repurposing, antimicrobial surveillance, and clinical decision support. In this review, we aim to highlight recent developments in the use of artificial intelligence (AI) to address antimicrobial resistance (AMR). In addition, we review computational methods that help interpret genomic, phenomic, clinical, and epidemiological data to support the development of treatment strategies and novel antimicrobial agents. The key issues addressed include data quality, model interpretability, external validation, regulatory requirements, privacy, and fairness. While AI is not a complete solution to AMR, it can certainly strengthen the global AMR response by complementing key areas of AMR such as antimicrobial stewardship, infection prevention, laboratory diagnostics, and global surveillance.

Antimicrobial resistance (AMR)↗

PubMed1992

A national collaborative study of resistance to antimicrobial agents in Haemophilus influenzae in Australian hospitals. The Australian Group for Antimicrobial Resistance (AGAR).

An Australia-wide survey of the prevalence of resistance to antimicrobial agents among Haemophilus influenzae was conducted on clinically significant isolates collected between July 1988 and September 1990. Laboratories from the capital cities of each Australian state and territory participated. Nine hundred and seventy clinical isolates were examined for beta-lactamase production and the MICs of ampicillin, coamoxiclav, chloramphenicol, cefaclor, ceftriaxone, cefotaxime, tetracycline, rifampicin, trimethoprim, sulphamethoxazole and co-trimoxazole were determined using the NCCLS agar dilution method with Haemophilus Test Medium. A smaller number of isolates were tested against penicillin V, penicillin G, ciprofloxacin, piperacillin and erythromycin in addition. The proportion of beta-lactamase producing strains was higher among invasive strains (21.6%) than non-invasive strains (14.2%) and varies considerably between states. The highest prevalence of ampicillin resistance was found in invasive strains from Canberra (40.8%), the lowest in non-invasive strains from Adelaide (5.1%). Paradoxically, in non-invasive strains, although beta-lactamase production was less common, resistance to other antimicrobials was commoner than in invasive strains and also varied between states.

Anti-Bacterial Agents↗

PubMed2026

National Antimicrobial Resistance Monitoring System: Three Decades of Advancing Public Health Through Integrated Surveillance of Antimicrobial Resistance.

Antimicrobial resistance (AMR) occurs when bacteria and other microorganisms adapt in ways that make medicines less effective, causing infections that are harder to treat and more likely to spread. According to the Centers for Disease Control and Prevention (CDC), AMR infections affect millions of Americans each year and contribute to thousands of deaths (CDC, 2019). After three decades of operation, the U.S. National Antimicrobial Resistance Monitoring System (NARMS) stands as a model of sustained, collaborative public health surveillance. What began in 1996 as an effort to track resistance in Salmonella and E. coli O157 has evolved into a One Health surveillance network monitoring AMR across the farm-to-fork continuum. Through a partnership among CDC, the Food and Drug Administration (FDA), the U.S. Department of Agriculture (USDA), state and local health departments, and universities, NARMS has become the backbone of foodborne AMR surveillance in the United States. The past decade has been particularly transformative. NARMS explored new sampling to include companion animals, minor livestock, aquaculture, surface water, and wildlife. Whole-genome sequencing (WGS) revolutionized the program's capabilities, enabling timely identification of emerging pathogens and revealing how resistance genes spread. Near real-time public dashboards make NARMS data accessible to researchers, clinicians, regulators, and policymakers. NARMS data shape decisions about new animal drug approvals, guide stewardship programs, and inform clinical treatment guidelines nationwide. As NARMS enters its fourth decade with a 2026-2030 strategic plan, the program will leverage artificial intelligence and metagenomics while expanding surveillance to fill remaining gaps ensuring this vital system continues to protect the food supply and both human and animal health from AMR.

Antimicrobial Resistance (AMR)↗

PubMed2026

Molecular Diagnostics for WHO Priority Bacterial Pathogens: A Bibliometric Mapping of Diagnostic Platforms, Resistance Markers, and Antimicrobial Resistance Research Trends.

Antimicrobial resistance (AMR) constrains effective treatment and carries implications for infection control, surveillance, and public health. The World Health Organization (WHO) priority bacterial pathogen framework has intensified the need for diagnostic innovation by redefining research priorities around organisms combining high disease burden with complex resistance profiles. Molecular diagnostics have accordingly moved beyond culture-based workflows, integrating rapid pathogen identification, resistance-marker detection, genomic surveillance, and clinical decision support. The present study conducted a bibliometric mapping of the literature on WHO priority pathogens. Rather than addressing resistance at a general level or a single pathogen or technology, it integrates priority pathogens, molecular platforms, and resistance markers within a single framework, tracing their joint thematic and temporal evolution along an explicit pathogen-platform-marker axis. Scopus-indexed articles and reviews (2000-2025) were retrieved, yielding 1746 publications after screening adapted from the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Analyses used Bibliometrix/Biblioshiny, R, and VOSviewer. The literature expanded markedly after 2018, led by China and the United States. Methicillin-resistant Staphylococcus aureus (MRSA), Mycobacterium tuberculosis, Enterococcus faecium, and the Enterobacterales-carbapenemase axis constituted the principal thematic cores, whereas conventional polymerase chain reaction (PCR)/nucleic acid amplification testing (NAAT) and whole-genome sequencing were the dominant platforms. Overall, the field has evolved from pathogen detection into an AMR-centered translational domain encompassing resistance prediction, genomic epidemiology, surveillance, and clinical decision support. Diagnostic development, stewardship, and surveillance depend on hybrid workflows coupling rapid marker-targeted assays with genome-based characterization, delivering actionable resistance within clinically meaningful timeframes, and extending coverage to underrepresented pathogens and platforms.

Humans↗

PubMed2026

A liquid handling platform for standardized quantification of cell-free enzymatic activity encoded by antimicrobial resistance genes.

Antimicrobial resistance (AMR) is a growing global threat to human health, and rapid methods for characterizing emerging antimicrobial resistance genes (ARGs) are needed. Here, we develop a semi-automated workflow using cell-free gene expression systems to measure the activity of two ARGs encoded on plasmid DNA that produce rifampicin-inactivating and gentamicin-inactivating enzymes. We validated the use of a small benchtop Myra liquid handling system compared to manual pipetting, with no statistical differences observed. After optimizing the pre-incubation time of ARGs and dispensing protocol, expression of aac(3)-IIa increased the half-maximal inhibition concentration (IC50) of gentamicin by over 150-fold, whilst arr-3 increased the IC50 of rifampicin by ~20-fold compared to controls. This methodology for rapid, semi-automated ARG characterization offers a strategy to combat AMR by assessing novel ARGs identified through genomic surveillance or profiling activity of new or derivative antibiotics.

aminoglycoside resistance↗

PubMed2025

Reflecting on Fleming's caveat: the impact of stakeholder decision-making on antimicrobial resistance evolution.

Antimicrobial resistance poses one of the greatest and most imminent threats to global health, environment and food security, for which an urgent response is mandated. Evolutionary approaches to tackling the crisis tend to focus on proximate issues including the mechanisms and pathways to resistance, with associated calls to action for infection control and antimicrobial stewardship. This is of clear benefit but overlooks the fundamental influence of policy and stakeholder decision-making on resistance evolution. In 1945, Fleming issued a stark warning on the irresponsible use of penicillin and its potential to cause death due to penicillin-resistant infections. Attention to resistance evolution theory and heeding Fleming's advice could have allowed for a vastly different reality. Embedding evolutionary theory within policy, industry and regulatory bodies is not only essential but is now a race against time. Hence, critical appraisal of historical behaviour and attitudes at a global scale can inform a paradigm of anticipatory and adaptive policy. To undertake this exercise, we focused on the largest group of antibiotics with the greatest clinical and economic footprint, the beta-lactams. We examined historical case studies that affected how beta-lactams were developed, produced, approved and utilized, in order to relate stakeholder decision-making to resistance evolution. We derive lessons from these observations and propose sustainable approaches to curb resistance evolution. We set a position that actively incorporates an evolutionary theory of antimicrobial resistance into decision-making within antimicrobial development, production and stewardship.

Anti-Bacterial Agents↗

PubMed2026

From resistance genes to resistance states and enzymatic context-dependence in antimicrobial resistance.

Antimicrobial resistance is often inferred from resistance genes and susceptibility phenotypes measured under standardized conditions. We argue that for many resistance genes, resistance is better viewed as a context-dependent functional state; the same gene can produce different phenotypes depending on the local microenvironment, enzyme kinetics, antibiotic exposure, and bacterial physiology.

Journal Article↗

PubMed2026

The role of microbial genomics in delivering the UK's national action plan for confronting antimicrobial resistance 2024-29.

Antimicrobial resistance (AMR) is a major threat to human and animal health, in addition to environmental resilience. Countries set the agenda on their national action against AMR in the form of National Action Plans (NAPs), with the UK's latest NAP released in May, 2024. Advances in genomics have strengthened our ability to work towards NAP priorities; however, to date, no mapping of the role genomics plays in contributing to specific goals within the NAP has been undertaken. The UK Research and Innovation-funded Transdisciplinary Antimicrobial Resistance Genomics Network brought together a range of stakeholders to discuss the role of genomics for action on AMR and to deliver policy priority-led research, as outlined in the UK NAP 2024-29. We report our discussions in this Personal View, with key roles for genomics, including informing targeted stewardship in health-care settings, supporting AMR literacy, and supporting effective antimicrobial innovation. However, changes in infrastructure, communication, and cross-sector coordination are needed to support implementation.

United Kingdom↗

PubMed2026

Systematic review on genomic insights into antimicrobial resistance in ESKAPE pathogens.

BACKGROUND: Antimicrobial resistance (AMR) is a major global public health threat. ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp.) pose a major threat owing to resistance to last-line antibiotics. Genomic surveillance is crucial to understanding global and regional antimicrobial resistance genes (ARGs) in AMR transmission. AIM: This systematic review synthesised global genomic evidence to identify global and region-specific ARGs distribution among ESKAPE pathogens. METHODS: Following PRISMA guidelines, studies published January 2019 to December 2024 were identified from PubMed, Google Scholar, and Web of Science. Eligible studies reported genomic characteristics and resistance patterns of one or more ESKAPE pathogens from any source. RESULTS: Seventy-seven studies were included, with most originating from Asia, followed by Europe and Africa. Clinical isolates predominated K. pneumoniae was the most frequently investigated pathogen, followed by S. aureus, P. aeruginosa, and A. baumannii. The most reported resistance genes were blaCTX-M, blaNDM, and blaSHV. Distinct regional patterns of antimicrobial resistance gene (ARG) distribution were observed, with tetracycline and quinolone resistance genes prevailing in Africa and South America, and blaOXA variants dominating in Asia and Europe. Region-specific ARG patterns were identified through descriptive synthesis and comparative analysis of study-reported frequencies. CONCLUSION: This review provides a synthesised global map of ARG distribution in ESKAPE pathogens, highlighting surveillance gaps in underrepresented regions and non-clinical settings. Addressing these gaps will support targeted genomic surveillance and stewardship programmes. WHAT THIS STUDY ADDS: This study contributes to the body of knowledge by mapping global and regional antimicrobial resistance gene patterns in ESKAPE pathogens, identifying key surveillance gaps and informing targeted AMR monitoring and stewardship strategies.

ESKAPE pathogens↗

PubMed2026

Evaluation of Oxford nanopore sequencing for antimicrobial resistance surveillance in Salmonella: comparison with phenotypic antimicrobial susceptibility in a large-scale study.

UNLABELLED: Salmonella is a major zoonotic foodborne pathogen, and antimicrobial resistance (AMR) in Salmonella presents a significant public health challenge. Compared with conventional antimicrobial susceptibility testing (AST), whole-genome sequencing (WGS) provides a more rapid and comprehensive approach to AMR characterization, thereby informing antimicrobial selection and supporting public health surveillance. In this study, Oxford Nanopore Technology (ONT)-based WGS was performed on 1,490 Salmonella isolates collected through nationwide surveillance in Taiwan in 2025. Genotypic resistance inferred from WGS data was compared with phenotypic AST results to assess the performance of ONT-WGS. Overall, WGS-inferred resistance showed high concordance with phenotypic resistance for most antimicrobials. However, major genotype-phenotype discordance was observed, attributed to four categories: (i) breakpoint-dependent classification, (ii) reduced or absent phenotypic expression of resistance genes, (iii) minimum inhibitory concentration (MIC) modulation by ramAp, and (iv) absence of known AMR determinants. Notable discrepancies included tigecycline resistance without known genetic determinants, nalidixic acid resistance linked to ramAp-mediated MIC elevation, and a high prevalence of colistin resistance (35.7%) in S. Enteritidis, with most resistant isolates lacking identifiable AMR determinants. Additionally, a significant proportion of ESBL- and AmpC-producing isolates were classified as susceptible or intermediate to cefotaxime and ceftazidime under CLSI criteria, highlighting the potential for misclassification and treatment failure. These findings demonstrate that ONT-WGS enables accurate and comprehensive AMR characterization by directly identifying resistance determinants and avoiding potential misclassification associated with breakpoint-based AST interpretations. When interpreted appropriately, WGS can support better antimicrobial selection and serve as a valuable alternative to conventional susceptibility testing. IMPORTANCE: Accurate prediction of antimicrobial resistance is essential for appropriate therapy and effective surveillance of Salmonella. However, discordance between genotype-based predictions and phenotypic antimicrobial susceptibility testing (AST) can complicate clinical interpretation. In this nationwide study of 1,490 Salmonella isolates, we show that Oxford Nanopore Technology-based whole-genome sequencing (ONT-WGS) provides rapid and comprehensive detection of antimicrobial resistance determinants with high concordance to phenotypic AST. We further identify four major mechanisms underlying genotype-phenotype discordance, including breakpoint-dependent classification, reduced or absent phenotypic expression of resistance genes, minimum inhibitory concentration (MIC) modulation by ramAp, and the absence of known AMR determinants. These findings demonstrate how WGS can complement conventional AST, improve interpretation of challenging susceptibility results, and strengthen genomic surveillance of emerging antimicrobial-resistant Salmonella.

Microbial Sensitivity Tests↗

PubMed1977

Therapy of antimicrobial-resistant typhoid fever.

Antimicrobial-resistant typhoid fever in Saigon was studied by examining in vitro antimicrobial susceptibilities of Salmonella typhi strains and conducting a randomized clinical trial of ampicillin and trimethoprim-sulfamethoxazole (TMP-SMZ). Isolates of S. typhi were obtained from blood or stool cultures of 90 patients. Of 87 isolates tested for antimicrobial susceptibility, 65 (75%) were resistant (R) to chloramphenicol, streptomycin, sulfonamide, and tetracycline, and 22 (25%) were susceptible (S). The drug resistance was transferable to Escherichia coli and was found in 11 different Vi-phage types. All isolates were susceptible to ampicillin and to TMP-SMZ. Agar dilution studies of TMP and SMZ showed synergistic inhibition of growth in all 18 S isolates and in 12 of 48 R isolates tested. The clinical trial of ampicillin and TMP-SMZ showed that both drugs were equally effective. Treatment failure with both drugs was more frequent in patients with S isolates than in patients with R isolates. Therefore, in an area where antimicrobial-resistant typhoid fever exists, patients with R isolates should receive either ampicillin or TMP-SMZ, but patients with S isolates should be treated with chloramphenicol.

Ampicillin↗

PubMed2026

Complete genome sequence of a multidrug-resistant Proteus mirabilis clinical isolate harboring 22 antimicrobial resistance genes including blaCTX-M-15.

Proteus mirabilis causes urinary tract infections and wound infections and frequently exhibits multidrug resistance, complicating patient treatment. Here, we describe the complete genome sequence of a multidrug-resistant P. mirabilis wound isolate from 2025, providing insight into the repertoire of antimicrobial resistance genes in a recent P. mirabilis clinical isolate.

Proteus mirabilis↗

PubMed2026

Herd-level heterogeneity of antimicrobial resistance in commensal Escherichia coli: A nationwide high-throughput survey of Australian pig herds.

Antimicrobial resistance in commensal Escherichia coli provides a useful indicator for overall antimicrobial resistance burden. We applied this approach to assess antimicrobial resistance within and between commercial pig herds across Australia. A high-throughput robotic workflow was used to isolate 2730 E. coli colonies from rectal contents collected in 2022 from healthy slaughter pigs (n = 300) representing 30 herds (∼70% of national production). Up to 94 isolates per herd underwent antimicrobial susceptibility testing using the Robotic Antimicrobial Susceptibility Platform. Isolate- and herd-level antimicrobial resistance indices were calculated, weighting antimicrobials by their human health importance. Resistance to first-line agents was widespread: ampicillin 77% and tetracycline 79%. By contrast, resistance to critically important antimicrobials was rare (ciprofloxacin 0.11%; extended-spectrum cephalosporins 0.04%), and no clinical resistance to carbapenems or colistin was detected. Overall, 56.9% of isolates were multi-class resistant. Herd-level antimicrobial resistance within indices ranged from 1.51 to 5.76, revealing substantial between-herd heterogeneity. Three herds carried critically important antimicrobials-resistant isolates that would likely have been missed using conventional, lower-density sampling approaches. Whole-genome sequencing identified fluoroquinolone-resistant isolates belonging to ST10 and ST69 (both qnrS1), and ST744 (Quinolone Resistance Determining Region mutations plus blaCTX-M-27). By testing approximately tenfold more isolates than conventional surveys, we uncovered considerable antimicrobial resistance with heterogeneity within and between animals and herds, including farm-specific variability. This expanded sampling also enabled detection of critically important antimicrobial resistance at very low prevalence. In conclusion, high-throughput, high-density testing offers a practical early-warning system and herd-level benchmark to inform surveillance and targeted interventions.

Animals↗

PubMed2026

Virus-mediated fate of antimicrobial resistance genes in livestock manure anaerobic digestion.

Antimicrobial resistance (AMR) poses a critical global health challenge, with livestock manure acting as a significant environmental reservoir for antimicrobial resistance genes (ARGs). Anaerobic digestion (AD) is a pivotal process for mitigating ARG dissemination at the livestock-environment-human interface. This study aims to elucidate the global dynamics of ARGs in AD systems, focusing on virus-host interactions and arms race, to identify actionable strategies for AMR control. We analyzed 205 metagenomic (4.5 Tb) and 36 meta-transcriptomic (640 Gb) datasets, including 15 newly generated datasets, revealing that pig manure AD harbors the highest ARG abundance (0.668 ARGs/16S rRNA), while AD systems generally exhibit limited transcriptional activation of ARGs. We constructed a viral dataset for livestock manure AD (GVD_LMAD), comprising 59,316 DNA and 727 RNA viral operational taxonomic units (vOTUs). Virus-host interactions established by CRISPR-Cas spacer, tRNA and homology matches revealed 889 lytic infections of antimicrobial-resistant bacteria (ARB) compared to only 18 ARG transduction events. Further analysis showed that the relative abundance of vOTUs assigned to the reduction role (4.11% ± 3.19%) was substantially higher than that of reproduction (0.72% ± 0.64%) and transduction (0.19% ± 0.30%), demonstrating that, among viral processes, lysis outweighs transduction in contributing to ARG abundance reduction in AD. Furthermore, an antiviral defense system (ADS) catalogue (GADSC_LMAD), derived from 2760 high-quality metagenome-assembled genomes (MAGs) containing 39,307 ADS, with ADS prevalence in ARB (7.8 ± 6.0 per MAG), indicating an intensified virus-host arms race in AD that may shield ARB from phage lysis. The resulting CRISPR-Cas immune network with expressed spacers targets foreign ARG-carrying sequences (primarily plasmids and ICEs), suggesting a mechanism that restricts horizontal gene transfer (HGT) via conjugation and transformation, despite shielding ARB from phage lysis. Collectively, these findings highlight that viral communities significantly contribute to ARG reduction through phage lysis relative to transduction, while the ADS-mediated arms race, despite protecting ARB, constructs a biological firewall that potentially limits HGT of ARGs. This study provides novel insights into virus-host dynamics as a key mechanism for controlling ARG dissemination in AD systems.

Animals↗

PubMed2026

Characterization of the oral microbiota and antimicrobial resistance genes in shelter dogs in Japan.

Companion animals can serve as reservoirs of antimicrobial resistance genes and zoonotic microorganisms, yet information on shelter dogs remains limited. This study characterized the oral microbiota and screened for antimicrobial resistance genes in shelter dogs in Japan. Oral swabs were collected from 81 dogs, microbial genomic DNA was extracted, bacterial communities were profiled by 16S rRNA gene amplicon sequencing, and antimicrobial resistance genes were screened by PCR. We detected genes conferring resistance to several antimicrobial classes, including β-lactams, tetracyclines, macrolide-lincosamide-streptogramin B, phenicols, and sulfonamides. cfxA was detected in all 81 samples, followed by sul1 (66/81), tet(M) and sul2 (65/81), floR (39/81), mecA (17/81), and erm(B) (15/81). We identified potentially pathogenic genera including Capnocytophaga, Pasteurella, Fusobacterium, Campylobacter and Corynebacterium. Microbiome analysis revealed that at the phylum level, Pseudomonadota and Bacteroidota were the most dominant, while Porphyromonas, Frederiksenia and Moraxella were the most prevalent genera. Our findings highlight that (i) the oral microbiota of shelter dogs broadly resembles that reported in companion dogs and (ii) shelter dogs represent an overlooked reservoir of clinically relevant antimicrobial resistance genes and potentially zoonotic bacteria. Therefore, it is necessary to include shelter animals in antimicrobial resistance surveillance programs to capture any potential gaps in the antimicrobial resistance prevalence in companion animals and prevent dissemination of resistant bacteria to humans following adoption of shelter dogs and cats.

antimicrobial resistance gene↗

PubMed2026

Precision medicine in combating antimicrobial resistance: A comprehensive review.

Antimicrobial resistance (AMR) represents one of the most pressing threats to global public health, undermining the effectiveness of modern antimicrobial therapy and challenging decades of medical progress. This comprehensive review examines the transition from broad-spectrum empirical therapy toward precision medicine as an integrated framework for improving antimicrobial use and combating AMR. Precision medicine seeks to tailor treatment decisions by combining pathogen-specific genomic and resistance data with relevant host characteristics to optimize therapy while limiting unnecessary antimicrobial exposure and the selective pressures that drive resistance. The review synthesizes advances reported from 2020, highlighting established and emerging approaches including rapid molecular diagnostics, next-generation sequencing, CRISPR-based detection, machine learning (ML)-assisted decision support, precision dosing, and targeted therapeutics such as bacteriophage therapy, antimicrobial peptides, and bacterial proteolysis-targeting chimeras. Rather than functioning as isolated technologies, these approaches achieve their greatest clinical value when integrated within antimicrobial stewardship programs and a One Health framework that recognizes the interconnected human, animal, and environmental drivers of resistance. Despite considerable progress, important challenges remain, including equitable access to advanced technologies, interpretation of increasingly complex datasets, workforce and infrastructure limitations, and evolving regulatory pathways for novel diagnostics and therapeutics. This review concludes that while precision medicine is not a standalone solution, its successful implementation will depend on coordinated integration of diagnostics, host factors, computational tools, pharmacological optimization, and stewardship strategies to improve patient outcomes while preserving the long-term effectiveness of existing antimicrobials.

Antimicrobial resistance↗

PubMed2026

Soil management practices shape the abundance, diversity, and spread of antimicrobial resistance.

Agricultural soils are critical hotspots of antimicrobial resistance genes (ARGs). Yet, the environmental factors shaping these reservoirs and the hazards they pose to humans and livestock remain poorly understood. Because management practices introduce antibiotics, heavy metals, and nonantibiotic biocides, they can rapidly select for resistance. Most studies have examined components of management practices in isolation, overlooking the multiple stressors of modern industrial agriculture. Here, we used a large-scale field experiment to examine how multiple stressors from soil and crop management interact to shape antimicrobial resistance. We combined shotgun metagenomics, phylogenomics, and risk-score analyses to quantify the diversity of ARGs, mobile genetic elements (MGEs), and the transmission potential of drug-resistant pathogens. Relative to other management systems, intensive, chemically reliant monoculture systems, typical of the US Corn Belt, create strong selective pressures promoting more abundant and diverse ARGs and MGEs. These systems therefore carry greater potential to transmit ARGs, including those with relevance to both livestock and public health such as tetA and blaPAM, likely mediated by integration and excision. In contrast, less-intensive, lower-input systems with diverse crop rotations maintained resistomes with lower abundance, diversity, and transmission potential. Our results suggest that these patterns could arise due to the divergent effects of management practices on overall soil microbial diversity, an ecological barrier that can suppress ARGs. This study highlights the need to understand the combined stressors of agricultural practices, beyond antimicrobial use, to design effective strategies to mitigate antimicrobial resistance.

Soil Microbiology↗

PubMed2026

A Decade of Achievements and Future Directions in Global Antimicrobial Resistance Surveillance System in Korea (Kor-GLASS).

OBJECTIVES: To comprehensively evaluate the 10-year operational outcomes (2016-2025) Global Antimicrobial Resistance Surveillance System in Korea (Kor-GLASS), assess its public health significance for national stewardship and global surveillance, and propose strategies for future development. METHODS: The study described the operational framework of Kor-GLASS, including its strain collection, analysis, and quality control systems, based on surveillance data. It analyzed resistance trends among key bloodstream pathogen isolates collected from 2016 to 2024 and evaluated major achievements, including alignment with the World Health Organization (WHO)'s Global Antimicrobial Resistance Surveillance System (GLASS), integration with the Emerging Antimicrobial Resistance Reporting (EAR) system, and activities as a WHO Collaborating Centre. RESULTS: Kor-GLASS operates on a foundation of standardized, isolate-based surveillance supported by an independent quality management system that complies with WHO GLASS standards. In alignment with the strategic direction of WHO GLASS, the surveillance scope has progressively expanded in terms of catchment areas, target pathogens, specimen types, and antimicrobial panels. From 2016 to 2024, a total of 116,955 clinical isolates were collected and analyzed through the network of collection and analysis centers. This has enabled the continuous generation of nationally representative antimicrobial resistance (AMR) data from general hospitals. The accumulated surveillance data provide fundamental evidence for tracking long-term resistance trends and elucidating the molecular epidemiological characteristics of key pathogens. These outcomes are disseminated through the publication of the "National Antimicrobial Resistance Surveillance Annual Report" and data submissions to WHO GLASS and GLASS-EAR, thereby supporting both national and global AMR surveillance efforts. Furthermore, Kor-GLASS has strengthened international surveillance and One Health collaboration capacities through its designation and redesignation as a WHO Collaborating Centre for AMR Surveillance. CONCLUSIONS: Over the past decade, Kor-GLASS has served as the cornerstone of national antimicrobial resistance surveillance, providing evidence to inform policy and supporting global surveillance systems. Moving forward, Kor-GLASS is expected to evolve into a pivotal national AMR surveillance system through the introduction of whole-genome sequencing and stronger integration with national antimicrobial consumption surveillance.

Anti-bacterial agents↗