A Streamlined Hardware–Software Workflow for Real-Time Nanopore Sequencing on a GPU-Integrated Workstation

Abstract

Long-read sequencing technologies, particularly those developed by Oxford Nanopore Technologies (ONT), have transformed genome sequencing by enabling high-resolution analysis of complex microbial communities. Among ONT devices, the MinION remains affordable and scalable for low-resource settings. However, its limited onboard computing power constrains high-accuracy basecalling and limits its ability to address inherent sequencing errors effectively. To overcome these constraints, we assembled a streamlined in-house workflow that integrates at least five MinION devices with a GPU-powered workstation running Ubuntu 20 and MinKNOW. Rather than a new sequencing platform, this “home-made GridION” represents a practical integration of existing ONT devices with dedicated computing resources. At its core is a live basecalling pipeline capable of handling both FAST5 and POD5 file formats. The system supports high-throughput basecalling using Guppy on FAST5 files as well as Dorado on POD5 files, ensuring compatibility with both legacy and current ONT data standards. File monitoring is automated via inotifywait, enabling immediate detection of new files, real-time basecalling, and organized output of FASTQ batches. Beyond basecalling, we implemented an automated downstream pipeline for metagenomic analysis, enabling taxonomic profiling and detection of antimicrobial resistance genes (ARG). Tested on 10 hospital wastewater samples, the workflow generated at least 500,000 reads per sample within six hours, which were analysed for antimicrobial resistance gene abundance. This demonstrates its potential as an open, scalable hardware/software platform that extends the utility of MinION sequencing for microbial genomics in resource-limited environments. The setup can channel as many MinIONs as available USB ports, with a ratio of 1 MK1D for 1 TB of storage capacity on the associated computer.