1 Introduction

Oxford Nanopore Technologies (ONT) has revolutionized microbial genomics by offering accessible third-generation sequencing. However, for researchers without specialized bioinformatics training, the steep learning curve of command-line tools and the complexities involved in selecting appropriate software and optimizing analysis parameters remain significant hurdles.

Commercial cloud-based solutions, while simplifying the analytical process, often necessitate high-bandwidth internet connectivity, incur additional operational costs, and present concerns regarding data privacy and security. Currently, only a limited number of bioinformatics workflows specifically tailored for Nanopore 16S amplicon analysis have been published, such as NanoCLUST and SituSeq (Santos et al. 2020, Rodríguez-Pérez et al. 2021, Zorz et al. 2023). In terms of user-friendly graphical interfaces, the primary option available is the official EPI2ME platform (https://epi2me.nanoporetech.com/). However, while EPI2ME streamlines the analytical process, it affords limited adaptability for optimizing specific parameters (e.g. minimum Q-score thresholds) or deploying custom, primer-specific reference databases. Furthermore, EPI2ME relies on a read-by-read classification strategy that is often insufficient to mitigate the inherent error rates of the underlying technology, leading to a high percentage of misclassified reads and increased uncertainty in taxonomic assignments.

To democratize access to these powerful tools, we present microbiONT. Unlike traditional pipelines that require intricate configuration, microbiONT prioritizes ease of deployment and usage. It is a local, privacy-focused platform that combines a user-friendly Streamlit interface with a local AI assistant. This hybrid approach allows users to perform basecalling, filtering, demultiplexing, and quality control via a standardized workflow. Uniquely, the integrated AI copilot transforms the analysis into an interactive learning opportunity by explaining parameters and logic. By removing technical barriers from installation to interpretation, microbiONT empowers wet-lab biologists to independently analyze genomic data on their local machines with confidence.