Protocol for identifying Mycobacterium tuberculosis infection status through airway microbiome profiling

Area of Science:

• Microbiology
• Infectious Diseases
• Bioinformatics

Background:

• Tuberculosis remains a global health challenge, necessitating improved diagnostic methods.
• The airway microbiome offers potential as a non-invasive biomarker for respiratory infections.
• Accurate identification of Mycobacterium tuberculosis infection status is crucial for effective treatment and control.

Purpose of the Study:

• To provide a standardized protocol for analyzing airway microbiome data.
• To establish a microbiome signature for identifying Mycobacterium tuberculosis infection.
• To guide the identification of potential biomarkers for tuberculosis diagnosis.

Main Methods:

• Standardized procedures for processing raw microbiome sequencing data.
• Calculation of alpha and beta diversity metrics to assess microbial community structure.
• Application of Dirichlet multinomial mixture models for microbiome profiling.
• Analysis of taxonomic relative and differential abundances.
• Identification of specific microbial taxa or patterns associated with M. tuberculosis infection.

Main Results:

• The protocol enables the generation of an airway microbiome signature.
• The signature can differentiate between M. tuberculosis infection status.
• Identified potential microbial biomarkers correlated with infection status.

Conclusions:

• Airway microbiome analysis is a viable approach for M. tuberculosis detection.
• This protocol facilitates reproducible research in respiratory microbiome diagnostics.
• Further validation may lead to novel diagnostic tools for tuberculosis.