An Integrated Mobile Laboratory Workflow for Wastewater and Environmental Pathogen Surveillance: Performance Evaluation and Field Application in Sub-Saharan Africa

Abstract Mobile laboratories (MLs) offer a practical solution for decentralized wastewater and environmental surveillance in settings with limited laboratory infrastructure, cold-chain logistics, and trained personnel. However, field-deployable molecular workflows suitable for diverse environmental matrices have not been systematically evaluated. Here, we present an integrated ML workflow combining Oxford Nanopore Technologies (ONT) sequencing for shotgun metagenomics, multiplex small-subunit (SSU) rRNA metabarcoding, and portable qPCR for targeted pathogen detection. Nucleic acid extraction was optimized and evaluated across wastewater and sediment matrices. Workflow performance was assessed using the ZymoBIOMICS Microbial Community Standard and wastewater spiked with inactivated mpox virus (MPXV), demonstrating comparable taxonomic recovery and consistent MPXV detection across spike concentrations. Multiplex SSU rRNA metabarcoding enabled simultaneous profiling of bacteria, archaea, and microeukaryotes, while 16S rRNA-derived community composition showed strong agreement with ONT-based 16S rRNA amplicon sequencing. Multiple displacement amplification combined with rapid barcoding reliably reproduced mock community composition across environmental matrices. As a proof-of-concept, the workflow was applied to environmental samples from sub-Saharan Africa, detecting priority pathogens and antimicrobial resistance genes consistent with the local epidemiological context. These findings demonstrate the feasibility and field adaptability of the workflow for One Health pathogen and antimicrobial resistance surveillance in resource-limited settings.