Abstract
Background: Stenotrophomonas maltophilia is an increasingly important multidrug-resistant opportunistic pathogen frequently isolated from clinical, environmental, and plant-associated niches. Despite its medical relevance, the global population structure, species-complex boundaries, and genomic determinants of antimicrobial resistance (AMR) and ecological adaptation remain poorly resolved, partly due to inconsistent annotations and fragmented genomic datasets. Methods: Approximately 2400 genome assemblies annotated as Stenotrophomonas maltophilia were available in the NCBI Assembly database at the time of query. After pre-download filtering to exclude metagenome-assembled genomes and atypical lineages, 1750 isolate genomes were retrieved and subjected to stringent quality control (completeness ≥90%, contamination ≤5%, ≤500 contigs, N50 ≥ 10 kb, and ≤1% ambiguous bases), yielding a final curated dataset of 1518 high-quality genomes used for downstream analyses. Genomes were assessed using CheckM, annotated with Prokka, and compared using average nucleotide identity (ANI), pan-genome analysis, core-genome phylogenomics, and functional annotation. AMR genes, mobile genetic elements (MGEs), and metadata (source, host, and geographic origin) were integrated to assess lineage-specific genomic features and ecological distributions. Results: ANI-based clustering resolved the S. maltophilia complex into multiple distinct genomospecies and revealed extensive misidentification of publicly deposited genomes. The pan-genome was highly open, reflecting strong genomic plasticity driven by accessory gene acquisition. Core-genome phylogeny resolved well-supported clades associated with clinical, environmental, and plant-related niches. Resistome profiling showed widespread intrinsic MDR determinants, with certain lineages enriched for efflux pumps, β-lactamases, and trimethoprim–sulfamethoxazole resistance markers. MGE analysis identified lineage-specific integrative conjugative elements, prophages, and transposases that correlated with source and geographic distribution. Conclusions: This large-scale analysis provides the most comprehensive genomic overview of the S. maltophilia complex to date. Our findings clarify species boundaries, highlight substantial taxonomic misannotation in public databases, and reveal lineage-specific AMR and mobilome patterns linked to ecological and clinical origins. The curated dataset and evolutionary insights generated here establish a foundation for global genomic surveillance, epidemiological tracking, and future studies on the evolution of antimicrobial resistance in S. maltophilia.