Aims

Specific Aim 1:

To conduct a comprehensive population survey of the foregut microbiome and demonstrate its association with GERD progression.

(1) Unsupervised microbiome typing. Samples of the foregut microbiome will be classified by unsupervised hierarchical clustering analysis. If distinct clusters are formed, we will test whether the clusters correlate with host phenotypes.
(2) Taxonomic typing of microbiome. The abundance-based 95% NRR will be calculated for each bacterial group and used to classify each of the samples to a normal or abnormal taxonomic type. Correlation between phenotype and taxonomic type will be performed.
(3) Normal reference range. Normal reference ranges for microbiomes in the foregut will be determined and used to relate samples of the microbiome with disease phenotypes.
(4) Core species in the foregut. Core species in the foregut that occupy all three major anatomic sites (the mouth, distal esophagus, and stomach) will be identified and changes in their abundance will be correlated with host phenotypes.
(5) Spatial relationship. Concordant changes in microbiome among the three foregut sites will be correlated with host phenotypes.
(6) Temporal stability. We will resample the BE patients one year after the first sampling to evaluate stability of the foregut microbiome.

Specific Aim 2:

To define the distal esophageal metagenome and demonstrate its association with progression of GERD

(1) Exploring associations between sample metagenomes and phenotypes by unsupervised metagenotyping. The metagenomes of the esophageal microbiome will be classified by unsupervised cluster analysis based on k-mer distance. If distinct clusters are formed, we will test whether the clusters correlate with host phenotypes.
(2 and 3) Gene-disease and pathway-disease association. Gene/pathway-disease associations will be evaluated both at the full sample metagenome level and at individual taxonomic levels within each sample, with the aim of discerning protein families and functional groups whose abundances strongly correlate with disease state.
(4-6) Archaea/fungus/virus-disease association. Although not the main goal of this project, metagenomic analysis also will reveal microbial DNA sequences beyond the bacterial domain and provide an opportunity to broaden the scope of microbe-disease association. In-depth metagenomic analysis may reveal the presence of archaea, fungus, or virus. If they are present in the distal esophagus, we will analyze their association with the disease phenotypes.