These data were generated to analyze the human breast tissue microbiome composition and functional potential. We analyzed and compared the resident bacterial taxa of histologically normal breast tissue (healthy, H) with those of tissues donated prior to (pre-diagnostic, PD, ) and after (adjacent normal, AN, and tumor, T) breast cancer diagnosis to determine the role of the breast tissue microbiome in breast cancer. DNA was isolated from 165 tissue samples, 9 negative controls, and 1 positive control and submitted for Illumina Miseq paired-end sequencing of the V3 - V4 region of the 16S gene. 16S amplicons were pre-processed into amplicon sequence variants (ASVs) using DADA2. To infer bacterial function in breast cancer, we predicted the functional bacteriome from these ASVs using PICRUSt2 and the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. 

This data was collected via 16S ribosomal RNA gene sequencing of breast tissue from four different groups of women. Healthy (H) tissue is tissue donated to the Susan G. Komen Tissue Bank (KTB) by healthy women, Pre-diagnostic (PD) tissue is tissue donated to the KTB by healthy women who later were diagnosed with breast cancer. Adjacent normal (AN) tissue is tissue next to a malignant tumor donated by women with cancer. Tumor (T) tissue is breast tumor tissue. The AN and T tissues were selected from the Indiana University Simon Comprehensive Cancer Center Tissue Bank (IUSCCC). Specifically, the V3 - V4 region of the 16S gene was amplified and library prepped for Illumina MiSeq paired-end sequencing. Following sequencing, data was pre-processed into amplicon sequence variants (ASVs), which are represented in this file. These ASVs were further analyzed according to the methods outlined in the associated publication: DOI: 10.1128/msystems.01489-21. Additionally, we predicted the functional potential of the microbiota using PICRUSt2 and the Kyoto Encyclopedia of Genes and Genomes (KEGG) Database. This functional metagenome was predicted from the ASVs in this file and is represented in this file. Please reference the manuscript, DOI: 10.1128/msystems.01489-21, for additional analyses performed on these data.