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Updated: Jun 15, 2026

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
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Benchmarking MicrobIEM - a user-friendly tool for decontamination of microbiome sequencing data.

Claudia Hülpüsch1,2,3, Luise Rauer1,2,4, Thomas Nussbaumer4

  • 1Environmental Medicine, Faculty of Medicine, University of Augsburg, Stenglinstr. 2, 86156, Augsburg, Germany.

BMC Biology
|November 23, 2023
PubMed
Summary

Microbiome analysis requires quality control to remove contaminants from 16S rRNA gene sequencing data. MicrobIEM is a new tool that effectively removes contaminants, especially in low-biomass samples like human skin.

Keywords:
16S rRNA gene sequencingBioinformatic decontaminationDecontamLow-biomass microbiomeNegative controlSourceTrackerYouden’s index

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Genetics

Background:

  • Microbiome analysis using 16S rRNA gene sequencing is common in research.
  • Contaminants in sequencing data can distort results, particularly in low-biomass environments like human skin.
  • Bioinformatic removal of contaminants is crucial for accurate microbiome analysis.

Purpose of the Study:

  • Introduce MicrobIEM, a novel tool for bioinformatically removing contaminants from 16S rRNA gene sequencing data using negative controls.
  • Evaluate MicrobIEM's performance against existing decontamination methods.
  • Provide a user-friendly tool for microbiome quality control.

Main Methods:

  • Benchmarking MicrobIEM against five established decontamination approaches.
  • Utilizing four 16S rRNA amplicon sequencing datasets: three mock communities with varying contamination levels and compositions, and one skin microbiome dataset.
  • Employing evaluation measures such as Youden's index for unbiased assessment.

Main Results:

  • Decontamination performance varied based on algorithm parameters and dataset type.
  • Control-based algorithms, including MicrobIEM's ratio filter, were effective in staggered mock communities and low-biomass samples.
  • MicrobIEM and Decontam's prevalence filter successfully reduced contaminants in the skin microbiome dataset while preserving relevant genera.

Conclusions:

  • MicrobIEM's ratio filter is a highly effective decontamination method, comparable to established tools.
  • MicrobIEM offers a user-friendly graphical interface with interactive plots for parameter selection.
  • MicrobIEM is the first quality control tool designed for microbiome researchers without coding expertise.