Benchmarking Denoising Strategies and Nucleic Acid Templates for ITS2 Amplicon Sequencing of Gut Microbiome

Background: The human gut mycobiome plays a critical role in host immunity, yet standardized workflows for fungal internal transcribed spacer (ITS) amplicon sequencing remain elusive. Unlike the bacterial 16S rRNA gene, where the impact of DNA versus RNA templates is well-documented, such comparative benchmarks are lacking for fungal studies. Furthermore, fungal ITS regions exhibit significant length heterogeneity, posing unique challenges for denoising algorithms that were originally designed for conserved bacterial amplicons.Methods: We performed ITS2 sequencing on paired DNA and RNA (cDNA) from fecal samples of healthy controls and patients with acute gastrointestinal injury (AGI). We systematically benchmarked three pipelines: DADA2 (ASV), Deblur (ASV), and VSEARCH (OTU). We then evaluated genomic (DNA) vs. transcriptomic (RNA) concordance and used ANCOM to compare disease-associated signatures within each template.Results: DADA2 outperformed VSEARCH and Deblur by resolving biological length heterogeneity without the artifacts introduced by rigid trimming. Direct comparison between DNA and RNA profiles revealed high concordance: Alpha and Beta diversity showed no significant differences, and ANCOM identified no differentially abundant taxa between the two nucleic acid templates. However, intra-template clinical analysis (AGI vs. Healthy) revealed distinct biomarker profiles. While DNA and RNA analyses both identified Glomeromycota as a key disease marker, they each detected unique sets of additional differentially abundant taxa.Conclusions: DADA2 is the optimal denoising strategy for ITS2 data due to its ability to handle length polymorphism. Regarding nucleic acid templates, we propose a tiered strategy: for routine community profiling, DNA sequencing is sufficient as it accurately captures the dominant, stable mycobiome structure. However, for in-depth clinical investigations targeting the active rare biosphere or specific metabolic shifts, RNA-based sequencing provides necessary complementary insight.