Metagenomics-Enabled Phylogeographic Mapping of Multidrug-Resistant Organisms and Resistance Genes in an Urban Subway System
Background: The microbiome of urban subway system mirrors the broader microbial landscape of a metropolitan city and may serve as potential hubs for pathogen and antimicrobial resistance (AMR) dissemination. However, existing microbiological investigations often lack focus on public health insights, limiting our understanding of multidrug-resistant organisms (MDROs) and antibiotic resistance genes (ARGs) in these high-traffic built environments.Results: In 2.5 years, we surveilled MDROs and ARGs in the Hong Kong (HK) subway network using a three-tier framework integrating quantitative PCR, culture-dependent methods, and metagenomics. Bacterial (n = 730) and viral (n = 296) surface swabs were collected from high-contact surfaces across subway stations in five consecutive summers and winters. SARS-CoV-2 (13.2 percent) and Influenza A virus (12.5 percent) predominated the subway surfaces. Viable MDROs were recovered from 4.11 percent of samples, including the first report of a clinically significant methicillin-resistant Staphylococcus aureus (MRSA) ST8 SCCmecIVl, and multidrug-resistant Acinetobacter baumannii (MDRA), and carbapenem-resistant Pseudomonas aeruginosa (CRPA). Shotgun metagenomics revealed five ESKAPE-E organisms and mecA, a hallmark of MRSA resistance, among dominant taxa and ARGs. Targeted probe capture enrichment (TC) enhanced detection of clinically relevant targets at lower sequencing depths, by increasing the read assignment to microbial taxa and ARGs of public health importance by 5.3- and 349.1-fold, respectively.Conclusions: This study unravels the role of subways as modest reservoirs for MDROs and ARGs, notably MRSA, and demonstrates the utility of TC in public health surveillance by enabling a sensitive detection of low-abundance but high-risk targets achievable with less resources. The actionable multi-tier framework developed here will further advance the robustness and scalability of prospective environmental surveillance.