Assessing the Multivariate Relationship between the Human Infant Intestinal Exfoliated Cell Transcriptome (Exfoliome)...

Area of Science:

• Microbiome Research
• Genomics
• Host-Microbe Interactions

Background:

• The gut microbiota and host share a mutualistic relationship, significantly impacting host health.
• Understanding host-microbiome cross-talk requires integrative approaches beyond standard gene expression analysis.
• Identifying biomarkers for host genes and microbial communities is crucial for characterizing these interactions.

Purpose of the Study:

• To develop and apply integrative data-driven approaches for analyzing host-gut microbiome interactions.
• To identify potential biomarkers of host genes and microbial communities in infants.
• To link host transcriptome and gut microbiome data to infant feeding phenotypes.

Main Methods:

• Utilized univariate differential gene expression analysis.
• Employed multivariate approaches: sparse Canonical Correlation Analysis (sCCA) and sparse Principal Components Analysis (sPCA).
• Integrated data from healthy infant gut microbial communities and host transcriptome (exfoliome) from stool-derived exfoliated cells.

Main Results:

• Revealed specific host genes and microbial functional categories associated with infant feeding phenotypes.
• Demonstrated the complementary application of univariate and multivariate analyses for data integration.
• Confirmed the utility of combinatorial noninvasive -omic approaches.

Conclusions:

• Integrative genomics approaches provide a comprehensive perspective on neonatal host-gut microbiome interactions.
• Noninvasive -omic strategies can effectively characterize the complex interplay between the host and gut microbiome.
• Findings highlight the potential for identifying biomarkers related to host-microbiome dynamics and feeding behaviors.