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Guided Protocol for Fecal Microbial Characterization by 16S rRNA-Amplicon Sequencing
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Current challenges and best-practice protocols for microbiome analysis.

Richa Bharti1, Dominik G Grimm1

  • 1Weihenstephan-Triesdorf University of Applied Sciences and Technical University of Munich, TUM Campus Straubing for Biotechnology and Sustainability, Straubing, Germany.

Briefings in Bioinformatics
|December 19, 2019
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Summary
This summary is machine-generated.

This review simplifies microbiome analysis by standardizing workflows for 16S rRNA sequencing and metagenomics. It offers best-practice protocols to address challenges in experimental design and computational analysis for microbial community studies.

Keywords:
16S rRNA sequencingamplicon sequencingassemblyfunctional and taxonomic classificationmetagenomicsmicrobiome

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Genomics

Background:

  • Next-generation sequencing significantly advanced microbiome research, revealing microbial roles in metabolism, physiology, and ecology.
  • Microbiome analysis faces challenges from experimental variables, sequencing errors, and complex computational downstream processes.
  • Rapid evolution of sequencing technologies and methodologies complicates data interpretation and reproducibility.

Purpose of the Study:

  • To review key workflows for 16S rRNA sequencing, shotgun, and long-read metagenomics.
  • To establish best-practice protocols for experimental design, sample handling, sequencing, and data analysis.
  • To provide standardized computational workflows for 16S rRNA and metagenomic data analysis.

Main Methods:

  • Comprehensive literature review of existing microbiome analysis workflows.
  • Development and curation of standardized protocols for experimental and computational steps.
  • Creation of accessible best-practice workflows for 16S rRNA and metagenomic data.

Main Results:

  • Identified critical experimental and computational factors influencing microbiome analysis outcomes.
  • Established standardized protocols covering the entire analysis pipeline from design to visualization.
  • Developed and shared a set of best-practice computational workflows for common microbiome sequencing data types.

Conclusions:

  • Standardized best-practice workflows are essential for accurate and reproducible microbiome research.
  • The provided protocols and workflows aim to simplify and enhance the analysis of microbial communities.
  • Adoption of these best practices will improve the reliability and comparability of microbiome studies across different environments.