Genomic insights into specialized and primary metabolism gene clusters in methicillin-resistant Staphylococcus aureus...

Community-acquired methicillin-resistant Staphylococcus aureus (CA-MRSA) remains a major public health concern. Beyond canonical virulence determinants, biosynthetic gene clusters (BGCs) for specialized metabolites (SMs) and primary metabolic adaptations may shape fitness in community settings. In this study, we analyzed 123 CA-MRSA isolates from Egypt (2020-2021) alongside three reference genomes using a combined genomics workflow: antiSMASH and PRISM for homology-based specialized BGCs and predicted structures, GECCO for de novo BGC detection, BiG-SCAPE for gene-cluster family (GCF) networks and gutSMASH for primary-metabolism clusters detection. Assemblies were generated from Illumina MiSeq data and annotated with Prokka; sequence types and clonal complexes were assigned with FastMLST. antiSMASH identified a total of 934 BGCs (median 8 per genome), dominated by the following BGC types: NRPS-independent siderophores (NIS) (n = 312; IucA/IucC-like siderophores), non-ribosomal peptide synthetase (NRPS) (n = 132), and opine-like metallophores (n = 123). GECCO detected 415 BGCs, including 287 unclassified and 101 NRPS-associated clusters. GutSMASH recovered 582 primary metabolism gene clusters (GCs), with fumarate-to-succinate (n = 96), arginine-to-bicarbonate (n = 89; ADI) and nitrate-reductase (n = 84) energy-capturing modules being the most frequent. NRPS and NIS content varied widely among isolates, exceeding reference genome diversity, and BiG-SCAPE networks suggested multiple isolate-specific GCFs lacking MIBiG matches. Egyptian CA-MRSA displays a rich repertoire of iron-acquisition, peptide, and metallophore BGCs alongside anaerobic/energy-efficiency primary metabolism GCs that may support survival and competitiveness in community niches. While experimental validation is needed, these pathways nominate tractable targets for anti-virulence or metabolism-directed interventions and provide a genomic baseline for CA-MRSA in the North African region.