(1399-D) Workflow Development for Wastewater-Based-Epidemiology via Low-Cost Metagenomic Sequencing of Antimicrobial Resistance in Sub-Saharan Africa
Tuesday, February 6, 2024
2:00 PM – 3:00 PM EST
Location: Exhibit Halls AB
Abstract: Antimicrobial resistance (AMR) is an expanding threat that is under monitored in many areas of the world. Limited antimicrobial supply and diagnostic capability in parts of Sub-Saharan Africa pushes healthcare professionals to overprescribe a narrow range of antibiotics in response to non-specific infections. Poor antimicrobial stewardship has led to a global “silent pandemic” of drug resistant pathogens. We developed a wastewater-based sample preparation workflow that is capable of identifying clinically relevant AMR biomarkers from built wastewater infrastructure and open-air canals in Kamapala, Uganda. We have successfully simplified nucleic acid extraction techniques by utilizing exclusion-based sample preparations (ESP), a process where commercially available silica-coated paramagnetic nanoparticles are moved through surface tension-stabilized air/aqueous interface. This process does not require access to electricity and confers a significant decrease in plastic consumables when compared to more traditional nucleic acid extraction techniques. ESP is not only more logistically favorable in resource limited settings but may also reduce overall sample degradation by allowing local scientists to perform extraction in-situ rather than contracting it out. AMR infections may be exacerbated by a lag in diagnostic capability if improper antibiotics are prescribed. We set out to retain technology and expertise in Kampala by training local scientists on each step of our process. We collected three grab wastewater samples in Kampala, Uganda from two open-air canals near slums and one sample from a septic tank downstream of the Joint Clinical Research Centre (JCRC). Briefly, 250ml of wastewater was filtered through 0.22 µm filters and extracted using our adapted ESP workflow. After concentration and extraction, we prepared the wastewater sample for sequencing on the Oxford Nanopore Technologies platform using the Native Barcoding Kit V24 and MinION Mk1B as described by the manufacturer. After sequencing, we used open-source toolsets (Galaxy, Epi2Me) to assemble and identify AMR biomarkers within the data. Downstream of the JCRC, we were able to identify various AMR biomarkers for macrolide (msr(E), mph(E)) aminoglycoside (aph(3”)-lb aph(6)-id), and sulfonamide (sul2) resistance within Acinetobacter baumannii assemblies. Acinetobacter infections are especially difficult to treat in immunocompromised patients, such as those undergoing treatment for HIV. Additionally, this pathogen can rapidly acquire and spread AMR biomarkers, with some hospitals in the US only requiring a handful of A. baumannii infections to trigger enhanced surveillance and control measures. This data represents the first effort to our knowledge of ESP and nanopore sequencing in tandem within a resource limited setting to simplify metagenomic wastewater-based detection of AMR biomarkers.