A Galaxy Workflow for Taxonomic Profiling of Host-Contaminated Microbiomes Using Nanopore Sequencing: Validation with Public Ena Datasets

Host-contaminated microbiomes, such as those found in mouse fecal samples, pose challenges for taxonomic profiling due to the high abundance of host DNA. Nanopore sequencing, with its long-read capabilities, enhances resolution but suffers from higher error rates and host contamination. This study presents a reproducible Galaxy workflow for taxonomic profiling of host-contaminated microbiomes using Nanopore sequencing data. The workflow integrates preprocessing (FastQC, Porechop, fastp), taxonomic classification (Kraken2 with a custom GTDB + mouse gut taxa database), and visualization (Krona pie charts) to provide a scalable and user-friendly analysis pipeline. Using the public ENA dataset PRJNA559386, the workflow processed 365,314 raw reads, yielding 267,615 high-quality reads. Taxonomic profiling identified Acetobacterium sp. KB-1 (13%) and Acetivibrio clariflavus DSM 19732 (12%) as dominant taxa, consistent with their roles as acetogenic and cellulolytic bacteria. Rare taxa, such as Acetobacter senegalensis (0.8%), were also detected, demonstrating the workflow’s sensitivity. The proposed workflow provides a robust, reproducible, and scalable framework for taxonomic profiling of host-contaminated microbiomes, addressing key challenges in Nanopore- based microbiome analysis. This approach has significant implications for clinical and environmental studies where host contamination is inevitable, enabling more accurate microbial community assessments.