The pan-microbiome profiling system Taxa4Meta identifies clinical dysbiotic features and classifies diarrheal disease

Area of Science:

• Microbiology
• Bioinformatics
• Genomics

Background:

• Targeted metagenomic sequencing is crucial for identifying microbiome biomarkers in diseases.
• Existing methods often produce inconsistent results due to study power limitations and sequencing bias.

Purpose of the Study:

• To introduce Taxa4Meta, a bioinformatics pipeline designed to mitigate technical and demographic biases in microbiome data.
• To validate Taxa4Meta for accurate taxonomic profiling of 16S rRNA amplicon data across diverse sequencing strategies.

Main Methods:

• Development and validation of the Taxa4Meta bioinformatics pipeline.
• Application of Taxa4Meta for taxonomic profiling of 16S rRNA amplicon data.
• Reanalysis of individual patient 16S data sets to assess predictive capabilities.

Main Results:

• Taxa4Meta demonstrated accurate taxonomic profiling irrespective of sequencing strategy.
• The pipeline successfully identified clinical dysbiotic features predictive of human diseases.
• 16S-based classifiers generated by Taxa4Meta effectively stratified diarrheal patients with Clostridioides difficile infection, IBS, or IBD.

Conclusions:

• Taxa4Meta offers a robust solution to overcome bias in targeted metagenomic sequencing.
• The pipeline has significant potential for reliable prediction of human diseases through microbiome analysis.
• Taxa4Meta establishes a new standard for microbiome surveys, enabling population-scale definition of gut dysbiosis.