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Guided Protocol for Fecal Microbial Characterization by 16S rRNA-Amplicon Sequencing
Published on: March 19, 2018
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Recovery of microbial community profile information hidden in chimeric sequence reads
Mengfei Ho1, Damee Moon1, Melissa Pires-Alves1
1Department of Microbiology, School of Molecular and Cellular Biology, University of Illinois at Urbana-Champaign, United States.
Computational and Structural Biotechnology Journal
|September 30, 2021
Summary
Comparing microbiome sequencing methods is crucial for accurate health assessments. This study found that sample complexity significantly impacts results, and a refined analysis approach improves data reliability.
Area of Science:
- Microbiome research
- Genomic sequencing technologies
- Vaginal microbiome studies
Background:
- Accurate microbiome profiling is essential for health and disease assessment.
- Current methods like 16S rRNA gene sequencing and metagenome shotgun sequencing have limitations.
- Discrepancies often exist between results from different sequencing approaches.
Purpose of the Study:
- To compare PCR-based 16S rRNA gene sequencing and metagenome shotgun sequencing.
- To evaluate these methods using vaginal samples from pregnant women.
- To identify factors influencing microbiome data interpretation.
Main Methods:
- Generated microbial community profiles from V3V4 and V4V5 regions of 16S rRNA gene sequencing.
- Performed metagenomic shotgun sequencing on a subset of samples.
- Utilized a chimera-counting program (BlastBin) for sequence analysis.
Main Results:
- Findings highlight sample composition and complexity as key factors in microbiome analysis.
- Discrepancies between 16S rRNA and shotgun sequencing were observed.
- The developed analysis approach improved the resemblance of PCR-based profiles to metagenomic data.
Conclusions:
- Microbiome data interpretation requires careful consideration of sample characteristics.
- Refined sequence analysis can enhance the accuracy of PCR-based microbiome profiling.
- Improved methods are needed for reliable microbiome assessments in clinical applications.
