Gut microbiota and the host exist in a mutualistic relationship, with the functional composition of the microbiota strongly influencing the health and well-being of the host. In addition to the standard differential expression analysis of host genes to assess the complex cross-talk between environment (diet), microbiome, and host intestinal physiology, data-driven integrative approaches are needed to identify potential biomarkers of both host genes and microbial communities that characterize these interactions. Our findings demonstrate that the complementary application of univariate differential gene expression analysis and multivariate approaches such as sparse Canonical Correlation Analysis (sCCA) and sparse Principal Components Analysis (sPCA) can be used to integrate data from both the healthy infant gut microbial community and host transcriptome (exfoliome) using stool derived exfoliated cells shed from the gut. These approaches reveal host genes and microbial functional categories related to the feeding phenotype of the infants. Our findings also confirm that combinatorial noninvasive -omic approaches provide an integrative genomics-based perspective of neonatal host-gut microbiome interactions.
- Breast milk
- Sparse canonical correlation analysis
- Sparse principal components analysis
ASJC Scopus subject areas
- Microbiology (medical)