BpresenT is a framework for the discovery and verification of ACPA-specific BCR-derived neoepitopes as candidates for therapeutic vaccination in Rheumatoid Arthritis. It was developed for the Rheumatology Lab of the Leiden University Medical Centre by Mila van Rooij as an internship project for their B.Sc. Bio-Informatics.
Docker is the most convenient way to use BpresenT and it's GUI. A docker image is available at docker/bpresent.tar.
Once downloaded, the image is installed using the following command.
docker load bpresent.tarA one-click launcher for windows is available at docker/launcher.bat. This does require docker and the image to be installed.
Due to constraints of NetMHCpan, BpresenT only runs on Linux-based systems. Download the source, and run the following commands to deploy locally.
apt-get update -y && apt-get upgrade -y
apt-get install python3.10 python3-pip tcsh -y
pip3 install -r requirements.txt
pip3 install https://github.com/openvax/mhctools/tarball/441a650
python3 manage.py migrate
python3 manage.py updategenedb && python3 manage.py initadmin && python3 manage.py populatedbNetMHCpan4.1 needs to be downloaded and installed separately. NetMHCpan-4.1.
After installation, BpresenT can be launched with
python3 manage.py runserverThe BpresenT framework consists of multiple flexible Python modules encapsulated in a Django project. It incorporates two publicly available tools: The IMGT V-Quest tool for B- and T-cell receptor sequence analysis and alignment, and the NetMHCpan4.1 tool for HLA Class I-peptide presentation predictions.
The integration of these tools and modules into BpresenT allows users to locate and analyze potential HLA class I presenting peptides. This information is enhanced by the custom analytics modules that provide information like a sequence’s isotype, glycosylation sites, and gene and allele usage per patient. BpresenT’s built-in abstraction modules allow accessible database interaction, including functions like filtering and exporting.
On top of the BpresenT framework, the BpresenT Graphical User Interface (GUI) is built. The GUI applies the framework’s modules in a streamlined fashion, accessible to those without any programming knowledge. It provides an overview of the data supplied by the user and the accompanying data generated by NetMHCpan and the framework’s modules. By progressing through the GUI, B-cell receptors with promising in-silico peptide predictions can be selected for in-vitro testing. The mass-spectrometry results from in-vitro testing can be imported and compared to the in-silico results for validation.
The GUI applies the framework’s functions to deliver a summarizing overview of a given sequence’s predicted peptides, found peptides, nucleotide mutations, amino-acid changes, glycosylation sites, and V-Quest determined germlines through an interactive sequence alignment viewer.