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907600.9942ResiDB: 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/.202133495705
816410.9940Antibiotic Resistance - A Cause for Reemergence of Infections. This article can rightly be called 'the rise of the microbial phoenix'; for, all the microbial infections whose doomsday was predicted with the discovery of antibiotics, have thumbed their noses at mankind and reemerged phoenix like. The hubris generated by Sir Alexander Fleming's discovery of Penicillin in 1928, exemplified best by the comment by William H Stewart, the US Surgeon General in 1967, "It is time to close the books on infectious diseases" has been replaced by the realisation that the threat of antibiotic resistance is, in the words of the Chief Medical Officer of England, Dame Sally Davies, "just as important and deadly as climate change and international terrorism". Antimicrobial resistance threatens to negate all the major medical advances of the last century because antimicrobial use is linked to many other fields like organ transplantation and cancer chemotherapy. Antibiotic resistance genes have been there since ancient times in response to naturally occurring antibiotics. Modern medicine has only driven further evolution of antimicrobial resistance by use, misuse, overuse and abuse of antibiotics. Resistant bacteria proliferate by natural selection when their drug sensitive comrades are removed by antibiotics. In this article the authors discuss the various causes of antimicrobial resistance and dwell in some detail on antibiotic resistance in gram-positive and gram-negative organisms. Finally they stress on the important role clinicians have in limiting the development and spread of antimicrobial resistance.202032026301
907920.9939Review, Evaluation, and Directions for Gene-Targeted Assembly for Ecological Analyses of Metagenomes. Shotgun metagenomics has greatly advanced our understanding of microbial communities over the last decade. Metagenomic analyses often include assembly and genome binning, computationally daunting tasks especially for big data from complex environments such as soil and sediments. In many studies, however, only a subset of genes and pathways involved in specific functions are of interest; thus, it is not necessary to attempt global assembly. In addition, methods that target genes can be computationally more efficient and produce more accurate assembly by leveraging rich databases, especially for those genes that are of broad interest such as those involved in biogeochemical cycles, biodegradation, and antibiotic resistance or used as phylogenetic markers. Here, we review six gene-targeted assemblers with unique algorithms for extracting and/or assembling targeted genes: Xander, MegaGTA, SAT-Assembler, HMM-GRASPx, GenSeed-HMM, and MEGAN. We tested these tools using two datasets with known genomes, a synthetic community of artificial reads derived from the genomes of 17 bacteria, shotgun sequence data from a mock community with 48 bacteria and 16 archaea genomes, and a large soil shotgun metagenomic dataset. We compared assemblies of a universal single copy gene (rplB) and two N cycle genes (nifH and nirK). We measured their computational efficiency, sensitivity, specificity, and chimera rate and found Xander and MegaGTA, which both use a probabilistic graph structure to model the genes, have the best overall performance with all three datasets, although MEGAN, a reference matching assembler, had better sensitivity with synthetic and mock community members chosen from its reference collection. Also, Xander and MegaGTA are the only tools that include post-assembly scripts tuned for common molecular ecology and diversity analyses. Additionally, we provide a mathematical model for estimating the probability of assembling targeted genes in a metagenome for estimating required sequencing depth.201931749830
326130.9939A global metagenomic map of urban microbiomes and antimicrobial resistance. We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.202134043940
660040.9939Metagenomic 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.202540788461
966950.9939Genomic encyclopedia of bacteria and archaea: sequencing a myriad of type strains. Microbes hold the key to life. They hold the secrets to our past (as the descendants of the earliest forms of life) and the prospects for our future (as we mine their genes for solutions to some of the planet's most pressing problems, from global warming to antibiotic resistance). However, the piecemeal approach that has defined efforts to study microbial genetic diversity for over 20 years and in over 30,000 genome projects risks squandering that promise. These efforts have covered less than 20% of the diversity of the cultured archaeal and bacterial species, which represent just 15% of the overall known prokaryotic diversity. Here we call for the funding of a systematic effort to produce a comprehensive genomic catalog of all cultured Bacteria and Archaea by sequencing, where available, the type strain of each species with a validly published name (currently∼11,000). This effort will provide an unprecedented level of coverage of our planet's genetic diversity, allow for the large-scale discovery of novel genes and functions, and lead to an improved understanding of microbial evolution and function in the environment.201425093819
326060.9938Profiles of phage in global hospital wastewater: Association with microbial hosts, antibiotic resistance genes, metal resistance genes, and mobile genetic elements. Hospital wastewater (HWW) is known to host taxonomically diverse microbial communities, yet limited information is available on the phages infecting these microorganisms. To fill this knowledge gap, we conducted an in-depth analysis using 377 publicly available HWW metagenomic datasets from 16 countries across 4 continents in the NCBI SRA database to elucidate phage-host dynamics and phage contributions to resistance gene transmission. We first assembled a metagenomic HWW phage catalog comprising 13,812 phage operational taxonomic units (pOTUs). The majority of these pOTUs belonged to the Caudoviricetes order, representing 75.29 % of this catalog. Based on the lifestyle of phages, we found that potentially virulent phages predominated in HWW. Specifically, 583 pOTUs have been predicted to have the capability to lyse 81 potentially pathogenic bacteria, suggesting the promising role of HWW phages as a viable alternative to antibiotics. Among all pOTUs, 1.56 % of pOTUs carry 108 subtypes of antibiotic resistance genes (ARGs), 0.96 % of pOTUs carry 76 subtypes of metal resistance genes (MRGs), and 0.96 % of pOTUs carry 22 subtypes of non-phage mobile genetic elements (MGEs). Predictions indicate that certain phages carrying ARGs, MRGs, and non-phage MGEs could infect bacteria hosts, even potential pathogens. This suggests that phages in HWW may contribute to the dissemination of resistance-associated genes in the environment. This meta-analysis provides the first global catalog of HWW phages, revealing their correlations with microbial hosts and pahge-associated ARGs, MRG, and non-phage MGEs. The insights gained from this research hold promise for advancing the applications of phages in medical and industrial contexts.202438513871
955370.9938A machine learning framework to predict antibiotic resistance traits and yet unknown genes underlying resistance to specific antibiotics in bacterial strains. Recently, the frequency of observing bacterial strains without known genetic components underlying phenotypic resistance to antibiotics has increased. There are several strains of bacteria lacking known resistance genes; however, they demonstrate resistance phenotype to drugs of that family. Although such strains are fewer compared to the overall population, they pose grave emerging threats to an already heavily challenged area of antimicrobial resistance (AMR), where death tolls have reached ~700 000 per year and a grim projection of ~10 million deaths per year by 2050 looms. Considering the fact that development of novel antibiotics is not keeping pace with the emergence and dissemination of resistance, there is a pressing need to decipher yet unknown genetic mechanisms of resistance, which will enable developing strategies for the best use of available interventions and show the way for the development of new drugs. In this study, we present a machine learning framework to predict novel AMR factors that are potentially responsible for resistance to specific antimicrobial drugs. The machine learning framework utilizes whole-genome sequencing AMR genetic data and antimicrobial susceptibility testing phenotypic data to predict resistance phenotypes and rank AMR genes by their importance in discriminating the resistance from the susceptible phenotypes. In summary, we present here a bioinformatics framework for training machine learning models, evaluating their performances, selecting the best performing model(s) and finally predicting the most important AMR loci for the resistance involved.202134015806
999880.9938mSphere of Influence: Uncovering New Ways To Control Multidrug Resistance by Dissecting Essential Cell Processes. Ana L. Flores-Mireles works in the fields of microbial pathogenesis and development of new therapeutics. In this mSphere of Influence article, she reflects on how the papers "Bacterial cell wall biogenesis is mediated by SEDS and PBP polymerase families functioning semi-autonomously" by H. Cho et al. (Nat Microbiol 1:16172, 2016, https://doi.org/10.1038/nmicrobiol.2016.172) and "A comprehensive, CRISPR-based functional analysis of essential genes in bacteria" by J. M. Peters et al. (Cell 165:1493-1506, 2016, https://doi.org/10.1016/j.cell.2016.05.003) made an impact on her approach to dissecting essential processes to understand microbial pathogenesis in catheter-associated urinary tract infections and generate an effective treatment with reduced likelihood of developing resistance.201931554727
955690.9938Recent insights into actinobacteria research in antimicrobial resistance: a review. Antimicrobial resistance (AMR) has emerged as a global health crisis, taking 4.71 million lives in the year 2021 and posing significant challenges to healthcare systems. Actinobacteria, particularly Streptomyces sp., are a well-established source of bioactive secondary metabolites, including antibiotics such as polyketides, aminoglycosides, and macrolides with activity against multidrug-resistant (MDR) bacteria. However, only 10% of the antibiotic genes are expressed, and others are silent in cryptic biosynthetic gene clusters (BGCs) that remain inactive under standard laboratory conditions. Advances in genome mining, bioinformatics tools like antiSMASH, and molecular techniques such as CRISPR-Cas have facilitated the identification of these clusters. Furthermore, innovative strategies such as co-culturing and HDAC inhibitors have shown promise in activating cryptic biosynthetic pathways to combat emerging antimicrobial resistance. Despite these advancements, the rapid evolution of resistance requires continuous research and global collaboration to ensure a sustainable pipeline of effective antibiotics. This review provides insight into actinobacteria-derived antibiotics, resistance mechanisms, and emerging biotechnological interventions to address the AMR crisis, underscoring the urgent need for multidisciplinary antibiotic discovery and stewardship efforts.202540627029
9184100.9938Unlocking the potential of phages: Innovative approaches to harnessing bacteriophages as diagnostic tools for human diseases. Phages, viruses that infect bacteria, have been explored as promising tools for the detection of human disease. By leveraging the specificity of phages for their bacterial hosts, phage-based diagnostic tools can rapidly and accurately detect bacterial infections in clinical samples. In recent years, advances in genetic engineering and biotechnology have enabled the development of more sophisticated phage-based diagnostic tools, including those that express reporter genes or enzymes, or target specific virulence factors or antibiotic resistance genes. However, despite these advancements, there are still challenges and limitations to the use of phage-based diagnostic tools, including concerns over phage safety and efficacy. This review aims to provide a comprehensive overview of the current state of phage-based diagnostic tools, including their advantages, limitations, and potential for future development. By addressing these issues, we hope to contribute to the ongoing efforts to develop safe and effective phage-based diagnostic tools for the detection of human disease.202337770168
8399110.9937SYN-View: A Phylogeny-Based Synteny Exploration Tool for the Identification of Gene Clusters Linked to Antibiotic Resistance. The development of new antibacterial drugs has become one of the most important tasks of the century in order to overcome the posing threat of drug resistance in pathogenic bacteria. Many antibiotics originate from natural products produced by various microorganisms. Over the last decades, bioinformatical approaches have facilitated the discovery and characterization of these small compounds using genome mining methodologies. A key part of this process is the identification of the most promising biosynthetic gene clusters (BGCs), which encode novel natural products. In 2017, the Antibiotic Resistant Target Seeker (ARTS) was developed in order to enable an automated target-directed genome mining approach. ARTS identifies possible resistant target genes within antibiotic gene clusters, in order to detect promising BGCs encoding antibiotics with novel modes of action. Although ARTS can predict promising targets based on multiple criteria, it provides little information about the cluster structures of possible resistant genes. Here, we present SYN-view. Based on a phylogenetic approach, SYN-view allows for easy comparison of gene clusters of interest and distinguishing genes with regular housekeeping functions from genes functioning as antibiotic resistant targets. Our aim is to implement our proposed method into the ARTS web-server, further improving the target-directed genome mining strategy of the ARTS pipeline.202033396183
4748120.9937Bacteria antibiotic resistance: New challenges and opportunities for implant-associated orthopedic infections. There has been a dramatic increase in the emergence of antibiotic-resistant bacterial strains, which has made antibiotic choices for infection control increasingly limited and more expensive. In the U.S. alone, antibiotic-resistant bacteria cause at least 2 million infections and 23,000 deaths a year resulting in a $55-70 billion per year economic impact. Antibiotics are critical to the success of surgical procedures including orthopedic prosthetic surgeries, and antibiotic resistance is occurring in nearly all bacteria that infect people, including the most common bacteria that cause orthopedic infections, such as Staphylococcus aureus (S. aureus). Most clinical cases of orthopedic surgeries have shown that patients infected with antibiotic-resistant bacteria, such as methicillin-resistant S. aureus (MRSA), are associated with increased morbidity and mortality. This paper reviews the severity of antibiotic resistance at the global scale, the consequences of antibiotic resistance, and the pathways bacteria used to develop antibiotic resistance. It highlights the opportunities and challenges in limiting antibiotic resistance through approaches like the development of novel, non-drug approaches to reduce bacteria functions related to orthopedic implant-associated infections. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:22-32, 2018.201828722231
5114130.9937Datasets for benchmarking antimicrobial resistance genes in bacterial metagenomic and whole genome sequencing. Whole genome sequencing (WGS) is a key tool in identifying and characterising disease-associated bacteria across clinical, agricultural, and environmental contexts. One increasingly common use of genomic and metagenomic sequencing is in identifying the type and range of antimicrobial resistance (AMR) genes present in bacterial isolates in order to make predictions regarding their AMR phenotype. However, there are a large number of alternative bioinformatics software and pipelines available, which can lead to dissimilar results. It is, therefore, vital that researchers carefully evaluate their genomic and metagenomic AMR analysis methods using a common dataset. To this end, as part of the Microbial Bioinformatics Hackathon and Workshop 2021, a 'gold standard' reference genomic and simulated metagenomic dataset was generated containing raw sequence reads mapped against their corresponding reference genome from a range of 174 potentially pathogenic bacteria. These datasets and their accompanying metadata are freely available for use in benchmarking studies of bacteria and their antimicrobial resistance genes and will help improve tool development for the identification of AMR genes in complex samples.202235705638
9552140.9937Addressing antibiotic resistance: computational answers to a biological problem? The increasing prevalence of infections caused by antibiotic-resistant bacteria is a global healthcare crisis. Understanding the spread of resistance is predicated on the surveillance of antibiotic resistance genes within an environment. Bioinformatics and artificial intelligence (AI) methods applied to metagenomic sequencing data offer the capacity to detect known and infer yet-unknown resistance mechanisms, and predict future outbreaks of antibiotic-resistant infections. Machine learning methods, in particular, could revive the waning antibiotic discovery pipeline by helping to predict the molecular structure and function of antibiotic resistance compounds, and optimising their interactions with target proteins. Consequently, AI has the capacity to play a central role in guiding antibiotic stewardship and future clinical decision-making around antibiotic resistance.202337031568
9561150.9937The resistance tsunami, antimicrobial stewardship, and the golden age of microbiology. Modern medicine is built on antibiotics. Antibiotics are something that we take for granted. We have however spent over 60 years educating bacteria to become resistant, and the global resistance tsunami has caught everyone unawares. Since bacteria have changed, we also have to change, and to change most of the practices of how we use antibiotics. Because the development of new antibiotics is so expensive, a stewardship approach may help to preserve those that we have now while we work to develop new antibiotics and to develop other approaches to controlling and treating infections. We need to adopt the ethic of Good Stewardship Practice (GSP) as an active and dynamic process of continuous improvement in antibiotic use, a process with many steps of different sizes involving everyone involved in antibiotic use. All antibiotic users have an important role to play in GSP. Although the resistance situation is pessimistic, and the future of antibiotics looks uncertain, we are fortunately entering what may be seen as the golden age of microbiology. This encompasses an astonishing array of technologies for rapid pathogen and resistance gene detection, for clone identification by genome sequencing, for identification of novel bacterial genes and for identification of the Achilles' heels of different pathogens. Future antibiotics may have to be far more targeted to the individual pathogen and the site of infection. A global tax on antibiotics might reduce their use while funding the cost of developing new antibiotics and new approaches to control of infectious diseases.201424646601
6687160.9936Antibiotic Resistance in Aquaculture: Challenges, Trends Analysis, and Alternative Approaches. Antibiotic resistance in aquaculture has emerged as a global crisis, representing a serious threat to the health of aquatic animals, environment, and human. The extensive use of antibiotics in aquaculture has led to rapid development of resistant bacterial strains, resulting in environmental contamination and the dissemination of resistant genes. Understanding of the research trends, key contributors, and thematic evolution of this field is essential for guiding future studies and policy interventions. The study aimed to conduct a bibliometric analysis of research on antibiotic resistance development in aquaculture, identifying key areas of research, leading contributors, emerging challenges, and alternative solutions. Data were extracted from the Web of Science (WoS) database covering the period from 2000 to 2025. A systematic search strategy was employed, utilizing terms including "antibiotic resistance" AND "bacteria," AND "aquaculture". Relevant publications were extracted from the WoS using these keywords. R-tool was then used to analyze the obtained metadata including keywords, citation patterns, and co-authored country. The analysis revealed a remarkable increase in publications over the past 25 years, with key contributions from China, India, and the USA. The most significant articles focused on the presence of multidrug resistant bacteria in the aquatic environments and, antibiotic-resistant genes, and horizontal gene transfer. Probiotics are the alternative solution to overcome the antibiotic resistance and enhance aquaculture sustainability. Future research should focus on the interdisciplinary collaboration, novel antimicrobial alternatives, and global monitoring approaches.202540558188
6507170.9936What 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.202540558133
6688180.9936Antibiotic resistant bacteria: A bibliometric review of literature. Antibiotic-resistant bacteria (ARB) are a serious threat to the health of people and the ecological environment. With this problem becoming more and more serious, more countries made research on the ARB, and the research number has been sharply increased particularly over the past decade. Therefore, it is quite necessary to globally retrace relevant researches on the ARB published from 2010 to 2020. This will help researchers to understand the current research situation, research trends and research hotspots in this field. This paper uses bibliometrics to examine publications in the field of ARB from 2010 to 2020 that were retrieved from the Web of Science (WOS). Our study performed a statistical analysis of the countries, institutions, journals, authors, research areas, author keywords, Essential Science Indicators (ESI) highly cited papers, and ESI hotspots papers to provide an overview of the ARB field as well as research trends, research hotspots, and future research directions in the field. The results showed that the number of related studies is increasing year by year; the USA is most published in the field of ARB; China is the most active in this field in the recent years; the Chinese Acad Sci published the most articles; Sci. Total Environ. published the greatest number of articles; CM Manaia has the most contributions; Environmental Sciences and Ecology is the most popular research area; and "antibiotic resistance," "antibiotics," and "antibiotic resistance genes" were the most frequently occurring author keywords. A citation analysis showed that aquatic environment-related antibiotic resistance is a key research area in this field, while antimicrobial nanomaterial-related research is a recent popular topic.202236466520
5126190.9936Blanket antimicrobial resistance gene database with structural information, BOARDS, provides insights on historical landscape of resistance prevalence and effects of mutations in enzyme structure. Antimicrobial resistance (AMR) in pathogenic bacteria poses a significant threat to public health, yet there is still a need for development in the tools to deeply understand AMR genes based on genetic or structural information. In this study, we present an interactive web database named Blanket Overarching Antimicrobial-Resistance gene Database with Structural information (BOARDS, sbml.unist.ac.kr), a database that comprehensively includes 3,943 reported AMR gene information for 1,997 extended spectrum beta-lactamase (ESBL) and 1,946 other genes as well as a total of 27,395 predicted protein structures. These structures, which include both wild-type AMR genes and their mutants, were derived from 80,094 publicly available whole-genome sequences. In addition, we developed the rapid analysis and detection tool of antimicrobial-resistance (RADAR), a one-stop analysis pipeline to detect AMR genes across whole-genome sequencing (WGSs). By integrating BOARDS and RADAR, the AMR prevalence landscape for eight multi-drug resistant pathogens was reconstructed, leading to unexpected findings such as the pre-existence of the MCR genes before their official reports. Enzymatic structure prediction-based analysis revealed that the occurrence of mutations found in some ESBL genes was found to be closely related to the binding affinities with their antibiotic substrates. Overall, BOARDS can play a significant role in performing in-depth analysis on AMR.IMPORTANCEWhile the increasing antibiotic resistance (AMR) in pathogen has been a burden on public health, effective tools for deep understanding of AMR based on genetic or structural information remain limited. In this study, a blanket overarching antimicrobial-resistance gene database with structure information (BOARDS)-a web-based database that comprehensively collected AMR gene data with predictive protein structural information was constructed. Additionally, we report the development of a RADAR pipeline that can analyze whole-genome sequences as well. BOARDS, which includes sequence and structural information, has shown the historical landscape and prevalence of the AMR genes and can provide insight into single-nucleotide polymorphism effects on antibiotic degrading enzymes within protein structures.202438085058