SUMMARY: The Pathogen-Host Analysis Tool (PHAT) is an application for processing and analyzing next-generation sequencing (NGS) data as it relates to relationships between pathogens and their hosts. Unlike custom scripts and tedious pipeline programming, PHAT provides an integrative platform encompassing raw and aligned sequence and reference file input, quality control (QC) reporting, alignment and variant calling, linear and circular alignment viewing, and graphical and tabular output. This novel tool aims to be user-friendly for life scientists studying diverse pathogen-host relationships. AVAILABILITY AND IMPLEMENTATION: The project is available on GitHub (https://github.com/chgibb/PHAT) and includes convenient installers, as well as portable and source versions, for both Windows and Linux (Debian and RedHat). Up-to-date documentation for PHAT, including user guides and development notes, can be found at https://chgibb.github.io/PHATDocs/. We encourage users and developers to provide feedback (error reporting, suggestions and comments).

Infections of stratified epithelia contribute to a large group of common diseases, such as dermatological conditions and sexually transmitted diseases. To investigate how epithelial structure affects infection dynamics, we develop a general ecology-inspired model for stratified epithelia. Our model allows us to simulate infections, explore new hypotheses and estimate parameters that are difficult to measure with tissue cell cultures. We focus on two contrasting pathogens: Chlamydia trachomatis and Human papillomaviruses (HPV). Using cervicovaginal parameter estimates, we find that key infection symptoms can be explained by differential interactions with the layers, while clearance and pathogen burden appear to be bottom-up processes. Cell protective responses to infections (e.g. mucus trapping) generally lowered pathogen load but there were specific effects based on infection strategies. Our modeling approach opens new perspectives for 3D tissue culture experimental systems of infections and, more generally, for developing and testing hypotheses related to infections of stratified epithelia.