Interrogating the microbiome: experimental and computational considerations in support of study reproducibility

Area of Science:

• Microbiology
• Bioinformatics
• Genomics

Background:

• The human microbiome significantly impacts health and disease, driving interest in microbiome-based therapeutics.
• Metagenomics, using sequencing and computational analysis, identifies and quantifies microbial communities.
• The field of metagenomics faces challenges in standardization and reproducibility.

Purpose of the Study:

• To review experimental and computational factors influencing microbiome analysis.
• To guide the establishment of reproducible and robust metagenomics workflows.
• To address current limitations in metagenomic data quality, quantification, and interpretation.

Main Methods:

• Literature review of experimental protocols in microbiome research.
• Analysis of computational pipelines for metagenomic data processing.
• Synthesis of findings on sources of variability in metagenomics.

Main Results:

• Identification of critical experimental steps affecting data quality.
• Pinpointing computational factors influencing microbial quantification and interpretation.
• Highlighting the need for standardization across metagenomic studies.

Conclusions:

• Standardizing experimental and computational workflows is essential for reliable microbiome research.
• Addressing variability sources will enhance the quality and interpretability of metagenomic data.
• This review provides a framework for reproducible microbiome interrogations and therapeutic development.