Predictive Functional Profiling of Allergy-Associated Microbiota with PICRUSt2.

Functional profiling of host-associated microbiota is essential for elucidating its role in immune dysregulation, such as in allergic diseases. Predictive bioinformatics tools like PICRUSt2 (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States, version 2) enable the inference of microbial metabolic potential from 16 S rRNA gene amplicon data. This chapter describes the computational workflow for using PICRUSt2 to analyze allergy-associated microbiota. The protocol begins with a standardized amplicon sequence variant (ASV) table and its corresponding taxonomy and sequence files. Users execute the core PICRUSt2 pipeline to predict gene family abundances (EC numbers, KO categories) and reconstruct MetaCyc metabolic pathways. Predicted pathway abundances are then analyzed for differential abundance between sample groups using statistical methods in R, and metabolic interaction networks are constructed for visualization. The workflow is executed in a standard Unix command-line environment and is compatible with output from upstream pipelines such as QIIME 2. This protocol provides a standardized method to generate testable hypotheses about microbiome function in allergy research from widely available 16 S rRNA data.