Is it possible to identify genotypes underlying resistant phenotypes in Gram-negative pathogens?

Linking genotypes to resistant phenotypes in Gram-negative pathogens remains complex. While phenotypic AST ensures reliability for therapy, genotypic methods provide unprecedented insight into resistance mechanisms and epidemiology. Discrepancies between the two highlight the need for integrated diagnostic platforms that combine functional and genomic perspectives. Artificial intelligence-driven predictive models and curated resistance databases hold promise for improving accuracy, but widespread adoption requires robust datasets, clinical validation, and harmonized interpretative frameworks. Ultimately, integrating phenotypic and genotypic data represents the most effective strategy to provide mechanism-informed, clinically actionable diagnostics for antimicrobial resistance management.