Identification of immunologic factors associated with allograft rejection using NGS T cell receptor repertoire data

Abstract

T and B cells are known to play an important role in transplant rejection. Nevertheless, the factors that lead to rejection are not yet fully understood. We have developed a general bioinformatics pipeline for processing T cell receptor (TCR) and immunoglobulin (IG) repertoire next-generation sequencing (NGS) data for comparing immune repertoire properties between multiple groups of samples. Using such a pipeline can help to identify properties of the immune repertoire increasing the risk of allograft rejection after transplantation.

Our pipeline is implemented in Python 3.7. Various methods for processing, analyzing and comparing multiple immune repertoire NGS samples are provided. The pipeline returns detailed information about the sequencing quality and provides calculations and visualizations in regard of clonality, diversity, clonotype overlap as well as V(D)J gene analysis and similarity analysis of TCR and IG repertoires.

The functionality of the pipeline will be demonstrated on immune repertoire sequencing data from eight kidney transplant patients with sequential samples. For all patients mixed lymphocyte reactions (MLRs) have been performed to identify alloreactive T cells. With our clonotype overlap analysis module we were able to identify alloreactive clonotypes and to subsequently track changes in the alloreactive repertoire after transplantation.