{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T23:37:38Z","timestamp":1792712258641,"version":"4.5.0"},"reference-count":75,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T00:00:00Z","timestamp":1790640000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000268","name":"Biotechnology and Biological Sciences Research Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000268","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000265","name":"UK Research and Innovation Medical Research Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000265","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["cell.com","clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Trends in Microbiology"],"published-print":{"date-parts":[[2026,10]]},"DOI":"10.1016\/j.tim.2026.09.009","type":"journal-article","created":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T20:23:50Z","timestamp":1792614230000},"update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"title":["Microbial resistance from genotype to metabolic phenotype"],"prefix":"10.1016","author":[{"given":"Frederick","family":"Clasen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yi","family":"Jin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"James","family":"Brett","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fernando","family":"Garcia-Guevara","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"S. Dusko","family":"Ehrlich","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5834-4533","authenticated-orcid":false,"given":"Saeed","family":"Shoaie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.tim.2026.09.009_bb0005","doi-asserted-by":"crossref","first-page":"629","DOI":"10.1016\/S0140-6736(21)02724-0","article-title":"Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis","volume":"399","year":"2022","journal-title":"Lancet"},{"key":"10.1016\/j.tim.2026.09.009_bb0010","first-page":"1199","article-title":"Antimicrobial Resistance Collaborators (2024) Global burden of bacterial antimicrobial resistance 1990-2021: a systematic analysis with forecasts to 2050","volume":"404","author":"GBD","year":"2021","journal-title":"Lancet"},{"key":"10.1016\/j.tim.2026.09.009_bb0015","doi-asserted-by":"crossref","first-page":"D690","DOI":"10.1093\/nar\/gkac920","article-title":"CARD 2023: expanded curation, support for machine learning, and resistome prediction at the Comprehensive Antibiotic Resistance Database","volume":"51","author":"Alcock","year":"2023","journal-title":"Nucleic Acids Res."},{"key":"10.1016\/j.tim.2026.09.009_bb0020","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-021-91456-0","article-title":"AMRFinderPlus and the Reference Gene Catalog facilitate examination of the genomic links among antimicrobial resistance, stress response, and virulence","volume":"11","author":"Feldgarden","year":"2021","journal-title":"Sci. Rep."},{"key":"10.1016\/j.tim.2026.09.009_bb0025","article-title":"ResFinder - an open online resource for identification of antimicrobial resistance genes in next-generation sequencing data and prediction of phenotypes from genotypes","volume":"8","author":"Florensa","year":"2022","journal-title":"Microb. Genom."},{"key":"10.1016\/j.tim.2026.09.009_bb0030","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.cmi.2016.11.012","article-title":"The role of whole genome sequencing in antimicrobial susceptibility testing of bacteria: report from the EUCAST Subcommittee","volume":"23","author":"Ellington","year":"2017","journal-title":"Clin. Microbiol. Infect."},{"key":"10.1016\/j.tim.2026.09.009_bb0035","doi-asserted-by":"crossref","DOI":"10.1128\/JCM.01405-18","article-title":"Genome-based prediction of bacterial antibiotic resistance","volume":"57","author":"Su","year":"2019","journal-title":"J. Clin. Microbiol."},{"key":"10.1016\/j.tim.2026.09.009_bb0040","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1186\/s40168-018-0401-z","article-title":"DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data","volume":"6","author":"Arango-Argoty","year":"2018","journal-title":"Microbiome"},{"key":"10.1016\/j.tim.2026.09.009_bb0045","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1038\/s44259-024-00033-8","article-title":"Limitations of current techniques in clinical antimicrobial resistance diagnosis: examples and future prospects","volume":"2","author":"Hassall","year":"2024","journal-title":"NPJ Antimicrob. Resist."},{"key":"10.1016\/j.tim.2026.09.009_bb0050","doi-asserted-by":"crossref","DOI":"10.1038\/s41598-024-75973-2","article-title":"Integrating genomic and molecular data to predict antimicrobial minimum inhibitory concentration in Klebsiella pneumoniae","volume":"14","author":"Ryu","year":"2024","journal-title":"Sci. Rep."},{"key":"10.1016\/j.tim.2026.09.009_bb0055","article-title":"Sequence-based modelling of bacterial genomes enables accurate antibiotic resistance prediction","author":"Wiatrak","year":"2024","journal-title":"bioRxiv"},{"key":"10.1016\/j.tim.2026.09.009_bb0060","doi-asserted-by":"crossref","first-page":"896","DOI":"10.3390\/antibiotics12050896","article-title":"Understanding antimicrobial resistance using genome-scale metabolic modeling","volume":"12","author":"Alonso-V\u00e1squez","year":"2023","journal-title":"Antibiotics"},{"key":"10.1016\/j.tim.2026.09.009_bb0065","doi-asserted-by":"crossref","DOI":"10.1016\/j.engmic.2022.100021","article-title":"Genome-scale metabolic modeling in antimicrobial pharmacology","volume":"2","author":"Zhu","year":"2022","journal-title":"Eng. Microbiol."},{"key":"10.1016\/j.tim.2026.09.009_bb0070","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1038\/s41579-025-01155-0","article-title":"The role of bacterial metabolism in antimicrobial resistance","volume":"23","author":"Ahmad","year":"2025","journal-title":"Nat. Rev. Microbiol."},{"key":"10.1016\/j.tim.2026.09.009_bb0075","doi-asserted-by":"crossref","DOI":"10.1128\/CMR.00088-17","article-title":"Mobile genetic elements associated with antimicrobial resistance","volume":"31","author":"Partridge","year":"2018","journal-title":"Clin. Microbiol. Rev."},{"key":"10.1016\/j.tim.2026.09.009_bb0080","doi-asserted-by":"crossref","first-page":"296","DOI":"10.3390\/antibiotics14030296","article-title":"Metagenomics as a transformative tool for antibiotic resistance surveillance: highlighting the impact of mobile genetic elements with a focus on the complex role of phages","volume":"14","author":"Olsen","year":"2025","journal-title":"Antibiotics"},{"key":"10.1016\/j.tim.2026.09.009_bb0085","doi-asserted-by":"crossref","first-page":"328","DOI":"10.3390\/antibiotics12020328","article-title":"Horizontal gene transfer of antibiotic resistance genes in biofilms","volume":"12","author":"Michaelis","year":"2023","journal-title":"Antibiotics"},{"key":"10.1016\/j.tim.2026.09.009_bb0090","doi-asserted-by":"crossref","first-page":"917","DOI":"10.15252\/msb.20167028","article-title":"Metabolic constraints on the evolution of antibiotic resistance","volume":"13","author":"Zampieri","year":"2017","journal-title":"Mol. Syst. Biol."},{"key":"10.1016\/j.tim.2026.09.009_bb0095","doi-asserted-by":"crossref","first-page":"2109","DOI":"10.1038\/s41564-019-0536-0","article-title":"Bacterial metabolic state more accurately predicts antibiotic lethality than growth rate","volume":"4","author":"Lopatkin","year":"2019","journal-title":"Nat. Microbiol."},{"key":"10.1016\/j.tim.2026.09.009_bb0100","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1186\/s13059-019-1730-3","article-title":"Current status and applications of genome-scale metabolic models","volume":"20","author":"Gu","year":"2019","journal-title":"Genome Biol."},{"key":"10.1016\/j.tim.2026.09.009_bb0105","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1038\/nrg3643","article-title":"Constraint-based models predict metabolic and associated cellular functions","volume":"15","author":"Bordbar","year":"2014","journal-title":"Nat. Rev. Genet."},{"key":"10.1016\/j.tim.2026.09.009_bb0110","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1006302","article-title":"COBRAme: a computational framework for genome-scale models of metabolism and gene expression","volume":"14","author":"Lloyd","year":"2018","journal-title":"PLoS Comput. Biol."},{"key":"10.1016\/j.tim.2026.09.009_bb0115","doi-asserted-by":"crossref","DOI":"10.3389\/fcell.2020.566702","article-title":"Genome-scale metabolic modeling for unraveling molecular mechanisms of high threat pathogens","volume":"8","author":"Sertbas","year":"2020","journal-title":"Front. Cell Dev. Biol."},{"key":"10.1016\/j.tim.2026.09.009_bb0120","doi-asserted-by":"crossref","DOI":"10.1128\/msystems.00913-20","article-title":"Genome-scale metabolic models and machine learning reveal genetic determinants of antibiotic resistance in Escherichia coli and unravel the underlying metabolic adaptation mechanisms","volume":"6","author":"Pearcy","year":"2021","journal-title":"mSystems"},{"key":"10.1016\/j.tim.2026.09.009_bb0125","doi-asserted-by":"crossref","DOI":"10.1073\/pnas.2016886118","article-title":"Genomic evolution of antibiotic resistance is contingent on genetic background following a long-term experiment with Escherichia coli","volume":"118","author":"Card","year":"2021","journal-title":"Proc. Natl. Acad. Sci. U. S. A."},{"key":"10.1016\/j.tim.2026.09.009_bb0130","doi-asserted-by":"crossref","first-page":"3105","DOI":"10.1038\/s41467-020-16932-z","article-title":"Highly parallel lab evolution reveals that epistasis can curb the evolution of antibiotic resistance","volume":"11","author":"Lukacisinova","year":"2020","journal-title":"Nat. Commun."},{"key":"10.1016\/j.tim.2026.09.009_bb0135","doi-asserted-by":"crossref","DOI":"10.1093\/molbev\/msae086","article-title":"Unpredictability of the fitness effects of antimicrobial resistance mutations across environments in Escherichia coli","volume":"41","author":"Hinz","year":"2024","journal-title":"Mol. Biol. Evol."},{"key":"10.1016\/j.tim.2026.09.009_bb0140","doi-asserted-by":"crossref","DOI":"10.1093\/bib\/bbad439","article-title":"Applications of genome-scale metabolic models to investigate microbial metabolic adaptations in response to genetic or environmental perturbations","volume":"25","author":"Carter","year":"2023","journal-title":"Brief. Bioinform."},{"key":"10.1016\/j.tim.2026.09.009_bb0145","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1003580","article-title":"Systematic evaluation of methods for integration of transcriptomic data into constraint-based models of metabolism","volume":"10","author":"Machado","year":"2014","journal-title":"PLoS Comput. Biol."},{"key":"10.1016\/j.tim.2026.09.009_bb0150","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1038\/s44320-024-00084-z","article-title":"Metabolic mutations reduce antibiotic susceptibility of E. coli by pathway-specific bottlenecks","volume":"21","author":"Lubrano","year":"2025","journal-title":"Mol. Syst. Biol."},{"key":"10.1016\/j.tim.2026.09.009_bb0155","doi-asserted-by":"crossref","first-page":"3796","DOI":"10.1038\/s41467-018-06219-9","article-title":"Evolution of gene knockout strains of E. coli reveal regulatory architectures governed by metabolism","volume":"9","author":"McCloskey","year":"2018","journal-title":"Nat. Commun."},{"key":"10.1016\/j.tim.2026.09.009_bb0160","doi-asserted-by":"crossref","first-page":"D134","DOI":"10.1093\/nar\/gkad903","article-title":"GenBank 2024 update","volume":"52","author":"Sayers","year":"2024","journal-title":"Nucleic Acids Res."},{"key":"10.1016\/j.tim.2026.09.009_bb0165","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1038\/nrg3351","article-title":"Understanding, predicting and manipulating the genotypic evolution of antibiotic resistance","volume":"14","author":"Palmer","year":"2013","journal-title":"Nat. Rev. Genet."},{"key":"10.1016\/j.tim.2026.09.009_bb0170","doi-asserted-by":"crossref","DOI":"10.7554\/eLife.94144.3","article-title":"Distinguishing mutants that resist drugs via different mechanisms by examining fitness tradeoffs","volume":"13","author":"Schmidlin","year":"2024","journal-title":"Elife"},{"key":"10.1016\/j.tim.2026.09.009_bb0175","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1005568","article-title":"On the effects of alternative optima in context-specific metabolic model predictions","volume":"13","author":"Robaina-Estevez","year":"2017","journal-title":"PLoS Comput. Biol."},{"key":"10.1016\/j.tim.2026.09.009_bb0180","doi-asserted-by":"crossref","first-page":"929","DOI":"10.1038\/ncomms1928","article-title":"In silico method for modelling metabolism and gene product expression at genome scale","volume":"3","author":"Lerman","year":"2012","journal-title":"Nat. Commun."},{"key":"10.1016\/j.tim.2026.09.009_bb0185","first-page":"693","article-title":"Genome-scale models of metabolism and gene expression extend and refine growth phenotype prediction","volume":"9","author":"O\u2019Brien","year":"2013","journal-title":"Mol. Syst. Biol."},{"key":"10.1016\/j.tim.2026.09.009_bb0190","doi-asserted-by":"crossref","first-page":"442","DOI":"10.1038\/s41579-021-00534-7","article-title":"Examining horizontal gene transfer in microbial communities","volume":"19","author":"Brito","year":"2021","journal-title":"Nat. Rev. Microbiol."},{"key":"10.1016\/j.tim.2026.09.009_bb0195","doi-asserted-by":"crossref","first-page":"167","DOI":"10.2147\/IDR.S48820","article-title":"Horizontal gene transfer in the human gastrointestinal tract: potential spread of antibiotic resistance genes","volume":"7","author":"Huddleston","year":"2014","journal-title":"Infect. Drug Resist."},{"key":"10.1016\/j.tim.2026.09.009_bb0200","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1038\/s41564-019-0625-0","article-title":"Tracking microbial evolution in the human gut using Hi-C reveals extensive horizontal gene transfer, persistence and adaptation","volume":"5","author":"Yaffe","year":"2020","journal-title":"Nat. Microbiol."},{"key":"10.1016\/j.tim.2026.09.009_bb0205","doi-asserted-by":"crossref","DOI":"10.1093\/nar\/gkab815","article-title":"metaGEM: reconstruction of genome scale metabolic models directly from metagenomes","volume":"49","author":"Zorrilla","year":"2021","journal-title":"Nucleic Acids Res."},{"key":"10.1016\/j.tim.2026.09.009_bb0210","doi-asserted-by":"crossref","first-page":"1139","DOI":"10.1038\/s41586-026-10373-2","article-title":"Transposable elements are driving rapid adaptation of Enterococcus faecium","volume":"653","author":"Grieshop","year":"2026","journal-title":"Nature"},{"key":"10.1016\/j.tim.2026.09.009_bb0215","doi-asserted-by":"crossref","DOI":"10.1371\/journal.ppat.0030007","article-title":"Insertion sequence-driven diversification creates a globally dispersed emerging multiresistant subspecies of E. faecium","volume":"3","author":"Leavis","year":"2007","journal-title":"PLoS Pathog."},{"key":"10.1016\/j.tim.2026.09.009_bb0220","doi-asserted-by":"crossref","first-page":"264","DOI":"10.1016\/j.ymben.2003.09.002","article-title":"The effects of alternate optimal solutions in constraint-based genome-scale metabolic models","volume":"5","author":"Mahadevan","year":"2003","journal-title":"Metab. Eng."},{"key":"10.1016\/j.tim.2026.09.009_bb0225","doi-asserted-by":"crossref","first-page":"725","DOI":"10.1038\/nbt.3893","article-title":"Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea","volume":"35","author":"Bowers","year":"2017","journal-title":"Nat. Biotechnol."},{"key":"10.1016\/j.tim.2026.09.009_bb0230","doi-asserted-by":"crossref","first-page":"606","DOI":"10.1093\/femsre\/fuaa025","article-title":"Experimental approaches to tracking mobile genetic elements in microbial communities","volume":"44","author":"Saak","year":"2020","journal-title":"FEMS Microbiol. Rev."},{"key":"10.1016\/j.tim.2026.09.009_bb0235","doi-asserted-by":"crossref","first-page":"7542","DOI":"10.1093\/nar\/gky537","article-title":"Fast automated reconstruction of genome-scale metabolic models for microbial species and communities","volume":"46","author":"Machado","year":"2018","journal-title":"Nucleic Acids Res."},{"key":"10.1016\/j.tim.2026.09.009_bb0240","doi-asserted-by":"crossref","first-page":"272","DOI":"10.1038\/s41587-020-0446-y","article-title":"MEMOTE for standardized genome-scale metabolic model testing","volume":"38","author":"Lieven","year":"2020","journal-title":"Nat. Biotechnol."},{"key":"10.1016\/j.tim.2026.09.009_bb0245","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1038\/nprot.2009.203","article-title":"A protocol for generating a high-quality genome-scale metabolic reconstruction","volume":"5","author":"Thiele","year":"2010","journal-title":"Nat. Protoc."},{"key":"10.1016\/j.tim.2026.09.009_bb0250","doi-asserted-by":"crossref","first-page":"389","DOI":"10.1016\/j.tig.2020.09.018","article-title":"Gene regulation and cellular metabolism: an essential partnership","volume":"37","author":"Carthew","year":"2021","journal-title":"Trends Genet."},{"key":"10.1016\/j.tim.2026.09.009_bb0255","doi-asserted-by":"crossref","DOI":"10.1016\/j.isci.2023.106040","article-title":"Systematic diet composition swap in a mouse genome-scale metabolic model reveals determinants of obesogenic diet metabolism in liver cancer","volume":"26","author":"Clasen","year":"2023","journal-title":"iScience"},{"key":"10.1016\/j.tim.2026.09.009_bb0260","doi-asserted-by":"crossref","first-page":"320","DOI":"10.1016\/j.cmet.2015.07.001","article-title":"Quantifying diet-induced metabolic changes of the human gut microbiome","volume":"22","author":"Shoaie","year":"2015","journal-title":"Cell Metab."},{"key":"10.1016\/j.tim.2026.09.009_bb0265","doi-asserted-by":"crossref","DOI":"10.1128\/msystems.00606-19","article-title":"MICOM: metagenome-scale modeling to infer metabolic interactions in the gut microbiota","volume":"5","author":"Diener","year":"2020","journal-title":"mSystems"},{"key":"10.1016\/j.tim.2026.09.009_bb0270","doi-asserted-by":"crossref","DOI":"10.1371\/journal.ppat.1012528","article-title":"Exploring the metabolic profile of A. baumannii for antimicrobial development using genome-scale modeling","volume":"20","author":"Leonidou","year":"2024","journal-title":"PLoS Pathog."},{"key":"10.1016\/j.tim.2026.09.009_bb0275","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1038\/s42003-023-04540-8","article-title":"Genome-scale model of Pseudomonas aeruginosa metabolism unveils virulence and drug potentiation","volume":"6","author":"Dahal","year":"2023","journal-title":"Commun. Biol."},{"key":"10.1016\/j.tim.2026.09.009_bb0280","doi-asserted-by":"crossref","first-page":"423","DOI":"10.1038\/nrmicro2333","article-title":"How antibiotics kill bacteria: from targets to networks","volume":"8","author":"Kohanski","year":"2010","journal-title":"Nat. Rev. Microbiol."},{"key":"10.1016\/j.tim.2026.09.009_bb0285","doi-asserted-by":"crossref","first-page":"797","DOI":"10.1016\/j.cell.2007.06.049","article-title":"A common mechanism of cellular death induced by bactericidal antibiotics","volume":"130","author":"Kohanski","year":"2007","journal-title":"Cell"},{"key":"10.1016\/j.tim.2026.09.009_bb0290","doi-asserted-by":"crossref","first-page":"1649","DOI":"10.1016\/j.cell.2019.04.016","article-title":"A white-box machine learning approach for revealing antibiotic mechanisms of action","volume":"177","author":"Yang","year":"2019","journal-title":"Cell"},{"key":"10.1016\/j.tim.2026.09.009_bb0295","doi-asserted-by":"crossref","first-page":"320","DOI":"10.1038\/nrmicro.2016.34","article-title":"Distinguishing between resistance, tolerance and persistence to antibiotic treatment","volume":"14","author":"Brauner","year":"2016","journal-title":"Nat. Rev. Microbiol."},{"key":"10.1016\/j.tim.2026.09.009_bb0300","doi-asserted-by":"crossref","DOI":"10.1038\/ncomms13806","article-title":"A genome-scale Escherichia coli kinetic metabolic model k-ecoli457 satisfying flux data for multiple mutant strains","volume":"7","author":"Khodayari","year":"2016","journal-title":"Nat. Commun."},{"key":"10.1016\/j.tim.2026.09.009_bb0305","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1038\/nature02456","article-title":"Integrating high-throughput and computational data elucidates bacterial networks","volume":"429","author":"Covert","year":"2004","journal-title":"Nature"},{"key":"10.1016\/j.tim.2026.09.009_bb0310","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1186\/s12961-020-00549-1","article-title":"Strengthening the science of addressing antimicrobial resistance: a framework for planning, conducting and disseminating antimicrobial resistance intervention research","volume":"18","author":"Rogers Van Katwyk","year":"2020","journal-title":"Health Res. Policy Syst."},{"key":"10.1016\/j.tim.2026.09.009_bb0315","doi-asserted-by":"crossref","first-page":"1362","DOI":"10.1038\/s41591-026-04257-1","article-title":"Evaluation of antimicrobial resistance governance across 193 countries to inform the 2026 Global Action Plan update","volume":"32","author":"Chen","year":"2026","journal-title":"Nat. Med."},{"key":"10.1016\/j.tim.2026.09.009_bb0320","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pgph.0005256","article-title":"Monitoring antimicrobial resistance trends from global genomics data: amr.watch","volume":"5","author":"David","year":"2025","journal-title":"PLOS Glob. Public Health"},{"key":"10.1016\/j.tim.2026.09.009_bb0325","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1038\/s44259-025-00105-3","article-title":"Tools and challenges in the use of routine clinical data for antimicrobial resistance surveillance","volume":"3","author":"Holt","year":"2025","journal-title":"NPJ Antimicrob. Resist."},{"key":"10.1016\/j.tim.2026.09.009_bb0330","doi-asserted-by":"crossref","first-page":"2917","DOI":"10.1038\/s41467-022-30635-7","article-title":"Seeking patterns of antibiotic resistance in ATLAS, an open, raw MIC database with patient metadata","volume":"13","author":"Catalan","year":"2022","journal-title":"Nat. Commun."},{"key":"10.1016\/j.tim.2026.09.009_bb0335","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1016\/S1473-3099(17)30753-3","article-title":"Discovery, research, and development of new antibiotics: the WHO priority list of antibiotic-resistant bacteria and tuberculosis","volume":"18","author":"Tacconelli","year":"2018","journal-title":"Lancet Infect. Dis."},{"key":"10.1016\/j.tim.2026.09.009_bb0340","doi-asserted-by":"crossref","first-page":"726","DOI":"10.1038\/s41570-021-00313-1","article-title":"Towards the sustainable discovery and development of new antibiotics","volume":"5","author":"Miethke","year":"2021","journal-title":"Nat. Rev. Chem."},{"key":"10.1016\/j.tim.2026.09.009_bb0345","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1056\/NEJMp1215093","article-title":"The future of antibiotics and resistance","volume":"368","author":"Spellberg","year":"2013","journal-title":"N. Engl. J. Med."},{"key":"10.1016\/j.tim.2026.09.009_bb0350","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1038\/s41579-020-0356-5","volume":"18","year":"2020","journal-title":"Nat. Rev. Microbiol."},{"key":"10.1016\/j.tim.2026.09.009_bb0355","doi-asserted-by":"crossref","first-page":"542","DOI":"10.1038\/s41564-022-01072-5","article-title":"Microbial communities form rich extracellular metabolomes that foster metabolic interactions and promote drug tolerance","volume":"7","author":"Yu","year":"2022","journal-title":"Nat. Microbiol."},{"key":"10.1016\/j.tim.2026.09.009_bb0360","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/j.jbiotec.2024.07.006","article-title":"Comparing genome-scale metabolic models of the non-resistant Enterococcus faecalis ATCC 19433 and the multi-resistant Enterococcus faecalis V583","volume":"392","author":"Loghmani","year":"2024","journal-title":"J. Biotechnol."},{"key":"10.1016\/j.tim.2026.09.009_bb0365","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1038\/s41540-021-00188-4","article-title":"Curating and comparing 114 strain-specific genome-scale metabolic models of Staphylococcus aureus","volume":"7","author":"Renz","year":"2021","journal-title":"npj Syst. Biol. Appl."},{"key":"10.1016\/j.tim.2026.09.009_bb0370","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1038\/s41540-022-00252-7","article-title":"Genome-scale metabolic modeling reveals increased reliance on valine catabolism in clinical isolates of Klebsiella pneumoniae","volume":"8","author":"Jenior","year":"2022","journal-title":"npj Syst. Biol. Appl."},{"key":"10.1016\/j.tim.2026.09.009_bb0375","doi-asserted-by":"crossref","first-page":"480","DOI":"10.1038\/nrg3744","article-title":"Empirical fitness landscapes and the predictability of evolution","volume":"15","author":"de Visser","year":"2014","journal-title":"Nat. Rev. Genet."}],"container-title":["Trends in Microbiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0966842X26002787?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0966842X26002787?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T22:39:32Z","timestamp":1792708772000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0966842X26002787"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10]]},"references-count":75,"alternative-id":["S0966842X26002787"],"URL":"https:\/\/doi.org\/10.1016\/j.tim.2026.09.009","relation":{},"ISSN":["0966-842X"],"issn-type":[{"value":"0966-842X","type":"print"}],"subject":[],"published":{"date-parts":[[2026,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Microbial resistance from genotype to metabolic phenotype","name":"articletitle","label":"Article Title"},{"value":"Trends in Microbiology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.tim.2026.09.009","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Author(s). Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}]}}