Genomic Determinants of Divergent Evolutionary Responses to Ceftriaxone–Azithromycin Combination Therapy in Neisseria gonorrhoeae

This dataset contains the full supplementary materials associated with the study “Genomic Determinants of Divergent Evolutionary Responses to Ceftriaxone–Azithromycin Combination Therapy in Neisseria gonorrhoeae.” It includes all genomic, phenotypic, evolutionary and statistical datasets generated from short‑term experimental evolution of six N. gonorrhoeae strains under ceftriaxone (CRO) alone or CRO plus sub‑MIC azithromycin (AZT). The collection comprises: Complete mutation catalogues for all evolutionary lineages across all timepoints, including single‑nucleotide variants, indels, multicodon changes, and structural micro‑indels, with full gene annotations and metadata (strain, day, replicate, regimen). Gene Ontology and KEGG enrichment analyses describing functional pathways recurrently targeted under CRO or CRO–AZT pressure. Resistance‑associated mutation sets, including changes in penA, mtr loci, PBPs, porins, and envelope biogenesis pathways. Temporal MIC measurements, comparing theoretical sampling concentrations with empirical susceptibility assays. Baseline polymorphism profiles for all parental strains used in the evolution experiments. Fractional inhibitory concentration (FIC) indices quantifying CRO–AZT pharmacodynamic interactions across strains. Cross‑resistance matrices covering multiple antibiotic classes. Mutation burden quantification and hypermutation signatures, including mismatch‑repair disruptions and genome maintenance defects. Temporal dynamics of functional mutation classes, efflux determinants, envelope remodeling markers, and genome‑maintenance pathways. Population‑level mutation frequency assays, including rifampicin‑based mutational load quantification. Recombination‑filtering rationale for phylogenetic reconstruction (Gubbins). Together, these supplementary tables and captions provide the complete quantitative and methodological foundation for reconstructing evolutionary trajectories, identifying hypermutator emergence, and characterizing genomic background–dependent outcomes under ceftriaxone–azithromycin combination therapy.