GPSmatch: an R package for comparing Genomic-binding Profile Similarity among transcriptional regulators using customizable databases.

SUMMARY: Eukaryotic gene expression requires coordination among hundreds of transcriptional regulators. To characterize a specific transcriptional regulator, identifying how it shares genomic-binding sites with other regulators can generate important insights into its action. As genomic data such as chromatin immunoprecipitation assays with sequencing (ChIP-Seq) are being continously generated from individual labs, there is a demand for timely integration and analysis of these new data. We have developed an R package, GPSmatch (Genomic-binding Profile Similarity match), for calculating the Jaccard index to compare the ChIP-Seq peaks from one experiment to other experiments stored in a user-supplied customizable database. GPSmatch also evaluates the statistical significance of the calculated Jaccard index using a nonparametric Monte Carlo procedure. We show that GPSmatch is suitable for identifying and ranking transcriptional regulators with shared genomic-binding profiles, which may unravel potential mechanistic actions of gene regulation. AVAILABILITY AND IMPLEMENTATION: The software is freely available at https://github.com/Bao-Lab/GPSmatch. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Characterization of Vaginal Microbial Community Dynamics in the Pathogenesis of Incident Bacterial Vaginosis, a Pilot Study.

BACKGROUND: Despite more than 60 years of research, the etiology of bacterial vaginosis (BV) remains controversial. In this pilot study, we used shotgun metagenomic sequencing to characterize vaginal microbial community changes before the development of incident BV (iBV). METHODS: A cohort of African American women with a baseline healthy vaginal microbiome (no Amsel criteria, Nugent score 0-3 with no Gardnerella vaginalis morphotypes) were followed for 90 days with daily self-collected vaginal specimens for iBV (≥2 consecutive days of a Nugent score of 7-10). Shotgun metagenomic sequencing was performed on select vaginal specimens from 4 women, every other day for 12 days before iBV diagnosis. Sequencing data were analyzed through Kraken2 and bioBakery 3 workflows, and specimens were classified into community state types. Quantitative polymerase chain reaction was performed to compare the correlation of read counts with bacterial abundance. RESULTS: Common BV-associated bacteria such as G. vaginalis , Prevotella bivia , and Fannyhessea vaginae were increasingly identified in the participants before iBV. Linear modeling indicated significant increases in G. vaginalis and F . vaginae relative abundance before iBV, whereas the relative abundance of Lactobacillus species declined over time. The Lactobacillus species decline correlated with the presence of Lactobacillus phages. We observed enrichment in bacterial adhesion factor genes on days before iBV. There were also significant correlations between bacterial read counts and abundances measured by quantitative polymerase chain reaction. CONCLUSIONS: This pilot study characterizes vaginal community dynamics before iBV and identifies key bacterial taxa and mechanisms potentially involved in the pathogenesis of iBV.