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Implementing Wastewater-Based Epidemiology for Long-Read Metagenomic Sequencing of Antimicrobial Resistance in
William Strike1, Temitope O C Faleye2, Brian Lubega3
1Department of Biomedical Engineering, University of Kentucky, 522 Robotics and Manufacturing Building, Lexington, KY 40506, USA.
Abstract:
Antimicrobial resistance (AMR) is an emerging global threat that is expanding in many areas of the world. Wastewater-based epidemiology (WBE) is uniquely suited for use in areas of the world where clinical surveillance is limited or logistically slow to identify emerging threats, such as in Sub-Saharan Africa (SSA). Wastewater was analyzed from three urban areas of Kampala, including a local HIV research clinic and two informal settlements. Wastewater extraction was performed using a low-cost, magnetic bead-based protocol that minimizes consumable plastic consumption followed by sequencing on the Oxford Nanopore Technology MinION platform. The majority of the analysis was performed using cloud-based services to identify AMR biomarkers and bacterial pathogens. Assemblies containing AMR pathogens were isolated from all locations. As one example, clinically relevant AMR biomarkers for multiple drug classes were found within Acinetobacter baumannii genomic fragments. This work presents a metagenomic WBE workflow that is compatible with areas of the world without robust water treatment infrastructure. This study was able to identify various bacterial pathogens and AMR biomarkers without shipping water samples internationally or relying on complex concentration methods. Due to the time-dependent nature of wastewater surveillance data, this work involved cross-training researchers in Uganda to collect and analyze wastewater for future efforts in public health development.
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