Genotype to metabolic phenotype in microbial resistance
Antimicrobial resistance prediction and surveillance remain anchored to individual resistance genes, thus treating it as a binary, context-free property of sequence rather than a quantitative, environment-dependent phenotype.
Genome-scale metabolic models embed resistance determinants within whole-cell metabolic networks, enabling quantitative predictions of resistance severity, minimum inhibitory concentrations, and environment-conditional phenotypes that sequence-based tools cannot provide.
Strain-resolved genome-scale metabolic models extended with mobile genetic elements, horizontal gene transfer, and community-level metabolic interactions allow resistance profiling of polymicrobial infections on an ecological scale.
Whole-network modelling has potential to identify metabolic vulnerabilities, synthetic lethal interactions, and microbiome-targeted strategies, linking surveillance, diagnosis, and drug discovery within a single mechanism-aware framework.
https://www.cell.com/trends/microbiology/fulltext/S0966-842X(26)00278-7
