Antimicrobial Resistance in Mycobacterial Infections: From Evolution and Persistence to Precision Therapeutics

Antimicrobial resistance (AMR) in mycobacterial infections has emerged as one of the most pressing challenges to global public health. Despite decades of progress in diagnosis and treatment, the continued rise of multidrug-resistant (MDR) and extensively drug-resistant (XDR) tuberculosis threatens global disease control efforts. At the same time, infections caused by nontuberculous mycobacteria (NTM) are increasing worldwide and often prove exceptionally difficult to treat because of their intrinsic resistance to many antimicrobial agents, prolonged treatment regimens, and high rates of therapeutic failure. Although several new drugs and treatment strategies have been introduced in recent years, treatment outcomes remain suboptimal, underscoring the urgent need for a deeper understanding of the biological processes that enable mycobacteria to survive antimicrobial therapy.Growing evidence suggests that treatment failure cannot be explained solely by the acquisition of genetic resistance. Mycobacteria employ a diverse repertoire of adaptive strategies that allow them to withstand antimicrobial pressure, including drug tolerance, persistence, dormancy, metabolic remodeling, stress-response pathways, biofilm formation, and adaptation to distinct host microenvironments. These dynamic physiological states reduce antimicrobial efficacy, prolong treatment duration, and contribute to relapse even in the absence of classical resistance mutations. Understanding how resistance, persistence, and host-pathogen interactions collectively influence therapeutic outcomes has therefore become a central challenge in contemporary mycobacterial research.Recent technological advances have transformed our ability to investigate these complex biological processes. Whole-genome sequencing, transcriptomics, proteomics, metabolomics, single-cell approaches, functional genomics, CRISPR-based technologies, and systems biology are providing unprecedented insights into the evolution of antimicrobial resistance and the molecular mechanisms that govern bacterial adaptation during infection and treatment. In parallel, improvements in molecular diagnostics and biomarker discovery are enabling more accurate detection of resistance and more effective monitoring of treatment response. Artificial intelligence (AI) and machine learning are increasingly being applied to integrate large-scale biological datasets, predict resistance phenotypes, identify novel therapeutic targets, optimize drug combinations, and support the development of individualized treatment strategies. Together, these multidisciplinary approaches are accelerating the transition from descriptive studies of resistance toward precision therapeutics for both tuberculosis and nontuberculous mycobacterial diseases.This Research Topic aims to provide an interdisciplinary platform for researchers investigating antimicrobial resistance across the full spectrum of mycobacterial biology from fundamental mechanisms of resistance evolution and persistence to translational research and precision medicine. We welcome submissions that advance our understanding of the molecular, cellular, clinical, and computational aspects of antimicrobial resistance, persistence, diagnosis, and treatment in mycobacterial infections.Sub-topics of interest regarding pathogenic mycobacteria include, but are not limited to:• Molecular mechanisms underlying antimicrobial resistance in mycobacteria • Drug tolerance, persistence, dormancy, and phenotypic resistance • Evolution and within-host adaptation of mycobacteria during infection and antimicrobial therapy • Host-pathogen interactions influencing antimicrobial efficacy and treatment outcomes • Antimicrobial resistance in nontuberculous mycobacteria • Biofilm formation, metabolic adaptation, and stress-response pathways • Whole-genome sequencing, molecular epidemiology, and resistance surveillance • Functional genomics, CRISPR-based approaches, and systems biology • Multi-omics approaches to investigate resistance and persistence • Biomarkers, rapid diagnostics, and treatment-response monitoring • Novel antimycobacterial agents, drug repurposing, and rational combination therapies • Pharmacokinetic/pharmacodynamic (PK/PD) modeling and lesion pharmacology • Host-directed therapies and immunomodulatory approaches • Artificial intelligence and machine learning for resistance prediction, drug discovery, and treatment optimization • Precision medicine and personalized therapeutic strategies for mycobacterial infections By bringing together discoveries spanning microbiology, genomics, immunology, pharmacology, computational biology, and clinical research, this Research Topic seeks to provide a comprehensive perspective on why mycobacterial infections remain among the most difficult bacterial diseases to treat. More importantly, it aims to highlight innovative approaches that bridge fundamental discoveries with clinical application, accelerating the development of improved diagnostics, more effective therapeutics, and precision treatment strategies to combat drug-resistant mycobacterial infections.In this Research Topic we consider the following article types: FAIR² DATA Direct Submission, FAIR² Data, Hypothesis and Theory, Methods, Mini Review, Opinion, Original Research, Perspective, Review, Systematic Review, Technology and CodeOriginal Research, Reviews, Mini Reviews, Perspectives, and Methods articles Topic editors: Arun K B, Muzafar A. Rather, Sam Ebenezer Source: https://www.frontiersin.org/research-topics/83590/antimicrobial-resistance-in-mycobacterial-infections-from-evolution-and-persistence-to-precision-therapeutics