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Background <p>High-throughput 16S rRNA gene amplicon sequencing is essential for characterizing gut dysbiosis in translational research. However, microbiome profiles vary widely across sequencing platforms, library preparation protocols, targeted hypervariable regions (HVRs), and bioinformatics workflows. For users of the Ion Torrent S5 platform, there is currently no consensus methodology for performing open-source analyses as an alternative to proprietary frameworks. This study evaluates the proprietary Ion Reporter™ software against eight open-source pipelines based on QIIME2 and the SILVA database, accounting for data compositionality. Benchmarking was performed using a commercial human fecal reference material (ZymoBIOMICS™ D6323) characterized via DNA-shotgun sequencing (the ZB-Shotgun profile), as the reference standard.</p> Results <p>Poisson regression modeling showed that using two primer sets for library preparation yielded a 30 % lower expected read count than a single primer set (IRR = 0.6986, <i>p</i> &lt; 0.001). Across all configurations, the choice of denoising algorithm (DADA2 vs. Deblur) significantly affected alpha diversity calculations. At the phylum level, hierarchical clustering of Bayes factors (BFs) indicated that multi-region Ion Reporter workflows produced stable consensus predictions. Conversely, at the species level, single-HVR open-source pipelines significantly outperformed multi-region approaches.</p> Conclusions <p>Open-source pipelines that combine targeted HVR2 or HVR4 inputs with state-of-the-art denoisers outperform proprietary Ion Reporter options, providing superior taxonomic resolution and precision for species-level microbiome profiling. This study establishes a traceable, reproducible, and cost-effective framework that empowers independent researchers to maximize the utility of Ion Torrent 16S rRNA data in healthcare and gastrointestinal research without relying on restrictive software ecosystems.</p>

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Evaluating 16S metagenomics data analysis pipelines using an Ion Torrent sequencer for human gut microbiome research

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月28日

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  • Roddy Jorquera,
  • Troy Ejsmentewicz,
  • Rodrigo Lagos,
  • Nicolas Bravo,
  • Francisco Issotta,
  • Andrés Hernández-Oliveras,
  • Franz Villarroel-Espíndola,
  • Roxana González-Stegmaier

摘要

Background

High-throughput 16S rRNA gene amplicon sequencing is essential for characterizing gut dysbiosis in translational research. However, microbiome profiles vary widely across sequencing platforms, library preparation protocols, targeted hypervariable regions (HVRs), and bioinformatics workflows. For users of the Ion Torrent S5 platform, there is currently no consensus methodology for performing open-source analyses as an alternative to proprietary frameworks. This study evaluates the proprietary Ion Reporter™ software against eight open-source pipelines based on QIIME2 and the SILVA database, accounting for data compositionality. Benchmarking was performed using a commercial human fecal reference material (ZymoBIOMICS™ D6323) characterized via DNA-shotgun sequencing (the ZB-Shotgun profile), as the reference standard.

Results

Poisson regression modeling showed that using two primer sets for library preparation yielded a 30 % lower expected read count than a single primer set (IRR = 0.6986, p < 0.001). Across all configurations, the choice of denoising algorithm (DADA2 vs. Deblur) significantly affected alpha diversity calculations. At the phylum level, hierarchical clustering of Bayes factors (BFs) indicated that multi-region Ion Reporter workflows produced stable consensus predictions. Conversely, at the species level, single-HVR open-source pipelines significantly outperformed multi-region approaches.

Conclusions

Open-source pipelines that combine targeted HVR2 or HVR4 inputs with state-of-the-art denoisers outperform proprietary Ion Reporter options, providing superior taxonomic resolution and precision for species-level microbiome profiling. This study establishes a traceable, reproducible, and cost-effective framework that empowers independent researchers to maximize the utility of Ion Torrent 16S rRNA data in healthcare and gastrointestinal research without relying on restrictive software ecosystems.