Omic Technologies Illuminate Antimicrobial Resistance: Bridging Genotypic and Phenotypic Insights

Antimicrobial resistance (AMR) remains a critical challenge in microbiology and global public health, with rising concerns about the diminishing efficacy of current antimicrobial therapies. Traditional phenotypic assays have been the cornerstone of AMR detection, yet their relatively slow turnaround and limited molecular resolution often impede timely intervention. Recent advances in omic technologies—including genomics, transcriptomics, proteomics, and metabolomics—are revolutionizing the detection and characterization of resistant pathogens. These high-throughput, data-rich approaches provide comprehensive, multidimensional snapshots of the genetic, functional, and metabolic features underlying resistance. Despite significant progress, translating omic data into actionable clinical and epidemiological insights is met with hurdles relating to data complexity, interpretation, and the integration of genotypic information with phenotypic outcomes.This Research Topic aims to advance understanding of AMR by illuminating the interplay between genotypic traits and phenotypic resistance. Central objectives include identifying molecular signatures and pathways implicated in resistance, refining diagnostic algorithms, and enhancing prediction models for resistance phenotypes using omic datasets. Key questions pertain to how omic-derived markers may inform novel therapeutic strategies, how data integration tools can reconcile disparate omic layers, and how ethical considerations—especially in the context of genomic data sharing—can be addressed responsibly.Research included in this topic should explore the use and integration of omic technologies for AMR characterization, with emphasis on innovative methodologies, translational challenges, and clinical relevance. Incorporation of multi-omic datasets, as well as considerations surrounding the implementation and ethical use of such data, are welcome. To gather further insights in the contextualization of omics for AMR detection and management, we welcome articles addressing, but not limited to, the following themes:- Identification and functional annotation of resistance genes using omic data- Integration of genotypic and phenotypic information for clinical diagnostics- Metabolomic and proteomic profiling of resistant pathogens- Bioinformatics and machine learning approaches in AMR prediction- Translational and ethical challenges in the clinical application of omic data- Strategies for rapid, point-of-care analysis utilizing omic techniquesTopic Editor Yi-Wei Tang holds shares in Danaher Corporation. The other Topic Editors report no competing interests related to this Research Topic. Topic editors: Yi-Wei Tang, Jeong Hwan Shin, Abdullah Kilic Source: https://www.frontiersin.org/research-topics/77888/omic-technologies-illuminate-antimicrobial-resistance-bridging-genotypic-and-phenotypic-insights