Mobile laboratories (MLs), whether vehicle mounted or portable, provide a versatile platform for on site wastewater and environmental surveillance (WES) of pathogens, particularly in remote locations with limited laboratory infrastructure. However, molecular workflows intended for ML deployment require careful optimization to account for locally available equipment, consumables, infrastructure, workforce capacity, and operational constraints. In this study, we optimized an integrated ML workflow combining Oxford Nanopore Technologies (ONT) for shotgun metagenomics, multiplex metabarcoding for community level microbial analysis, and Biomeme based qPCR for targeted pathogen analysis. To further explore the potential of metagenomics for resistome assessment, we evaluated two whole metagenome enrichment approaches for their ability to improve detection of antimicrobial resistance genes. We introduce and validate a novel ONT based strategy for multiplexed sequencing small subunit (SSU) rRNA amplicon sequencing, enabling simultaneous profiling of bacteria, archaea, and microeukaryotes in complex microbial communities with multiplex metabarcoding. Sample pretreatment and nucleic acid (NA) extraction in this ML workflow were optimized using a combination chemical mechanical lysis approach followed by magnetic bead based NA purification. Workflow performance was verified using a mock community (ZymoBIOMICS Microbial Community Standard, Zymo Research, USA) and wastewater samples spiked with inactivated Mpox virus (MPXV), demonstrating accurate taxonomic representation and sensitive MPXV detection. Comparison with a commercial ZymoBIO bead beating kit for sediment sample showed ML NA extraction performed comparably. The time efficient multiplex metabarcoding workflow enabled simultaneous profiling of bacterial, archaeal, and eukaryotic diversity and produced results more concordant with qPCRbased pathogen detection than the REPLI g Cell Whole Genome Amplification (WGA) & Whole Transcriptome amplification (WTA). The protocol for Mpox virus genome characterization was successfully validated for whole genome sequencing (WES) based detection and incorporated into the standard ML workflow. Across both high and low biomass environmental matrices, the Multiple Displacement Amplification (MDA) based metagenomic workflow, combined with the ML NA extraction procedure, reliably reproduced the expected composition of the Microbial Community Standard. Collectively, the integration of ONT technology with MDA metagenomics and mobile qPCR workflows provides an effective One Health approach for pathogen surveillance and outbreak response across heterogeneous environmental settings, which was later further enhanced by an offline bioinformatic and visualization pipeline enabling near real time detection of pathogens and AMR thus early risk assessment.

The authors have declared no competing interest.

This study was supported by the European Commission through the ODIN project (grant no. 101103253, Strengthening Environmental Surveillance to Advance Public Health Action) and the ODIN Mpox project (grant no. 101195186, Implementing wastewater and environmental surveillance for Mpox in sub‑Saharan Africa). Additional support was provided by the SusOffAqua project (Research Council of Norway, project no. 328724) for all work involving sediment samples. Mpox virus material was supplied by the European Virus Archive Global (EVA GLOBAL), funded under the European Union Horizon 2020 research and innovation programme (grant agreement no. 871029).

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All data produced in the present study are available upon reasonable request to the authors