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Metagenomic surveillance identifies a high-risk antibiotic resistance profile in community wastewater: a pilot study from Pakistan
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DOI：10.1007/s00210-026-05471-x.png)
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Abstract
En 中文
Environmental antimicrobial resistance surveillance in low- and middle-income countries (LMICs) faces critical data gaps, particularly in Pakistan, where approximately 90% of municipal wastewater is discharged untreated. In the absence of systematic monitoring in regions like Khyber Pakhtunkhwa, we conducted a pilot shotgun metagenomic sequencing study on two strategically selected community wastewater sites in Mardan. To translate complex metagenomic data into actionable public health intelligence, we developed the Antibiotic Resistance Risk Index (ARRI), a novel framework integrating antibiotic resistance gene (ARG) proportional abundance, pathogen taxonomic expansion, and WHO priority weighting. Our analysis revealed that the urban site (MCW2) exhibited a “critical” resistance profile, characterized by a 54% increase in ARG allelic richness (628 unique variants) despite a 19.9% decline in total relative ARG abundance. Taxonomic compositional changes consistent with an aerobic shift, including a 34-fold decline in Thermodesulfobacteria and a 46% increase in Pseudomonadota, were observed alongside an increased proportion of WHO priority pathogens, including Acinetobacter baumannii, Pseudomonas aeruginosa, and Escherichia coli. This site served as a reservoir for last-resort resistance determinants, including blaNDM, blaIMP, blaCTX-M, and mcr, which emerged exclusively in the urban drainage environment. The resistome contained 159 ARG families and 26 MGE types. Network analysis showed that 90.8% of ARG-MGE pairs exhibited coordinated increase in relative abundance, with all carbapenemase-linked pairs showing parallel trends. Consequently, ARRI scores escalated from 8.7 (moderate risk) to 34.2 (critical risk) at the urban site. These findings reveal the environmental circulation of hospital-associated resistance through decentralized sanitation infrastructure, representing a convergence of hospital-associated and community resistance profiles in LMIC settings. This study demonstrates that risk-weighted surveillance enables high-resolution, actionable AMR monitoring, providing a baseline methodology for environmental AMR surveillance in resource-limited settings.
Keywords:
Metagenomics
Wastewater surveillance
Antimicrobial resistance
LMIC
ARRI
One health
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6.9K
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