Language

English

Publication Date

1-16-2024

Journal

Journal of Clinical Investigation

DOI

10.1172/JCI170859

PMID

37962956

PMCID

PMC10786686

PubMedCentral® Posted Date

1-16-2024

PubMedCentral® Full Text Version

Post-print

Abstract

Targeted metagenomic sequencing is an emerging strategy to survey disease-specific microbiome biomarkers for clinical diagnosis and prognosis. However, this approach often yields inconsistent or conflicting results owing to inadequate study power and sequencing bias. We introduce Taxa4Meta, a bioinformatics pipeline explicitly designed to compensate for technical and demographic bias. We designed and validated Taxa4Meta for accurate taxonomic profiling of 16S rRNA amplicon data acquired from different sequencing strategies. Taxa4Meta offers significant potential in identifying clinical dysbiotic features that can reliably predict human disease, validated comprehensively via reanalysis of individual patient 16S data sets. We leveraged the power of Taxa4Meta's pan-microbiome profiling to generate 16S-based classifiers that exhibited excellent utility for stratification of diarrheal patients with Clostridioides difficile infection, irritable bowel syndrome, or inflammatory bowel diseases, which represent common misdiagnoses and pose significant challenges for clinical management. We believe that Taxa4Meta represents a new "best practices" approach to individual microbiome surveys that can be used to define gut dysbiosis at a population-scale level.

Keywords

Humans, Dysbiosis, Gastrointestinal Microbiome, RNA, Ribosomal, 16S, Microbiota, Diarrhea, Gastroenterology, Infectious disease, Bacterial infections

Published Open-Access

yes

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