Upon recognition of an antigen, activated T lymphocytes proliferate and differentiate, generating a heterogeneous progeny able to perform a vast array of functions. The phenotype of the initial naive repertoire, as well as the specificity between T cell receptors (TCR) for the antigen are critical components that determine the success of the immune response and establishment of protective immunity. Single cell technologies are now significantly improving the understanding of these highly dynamic and heterogeneous molecules. The rise of multi-omics approaches inevitably requires computational workflows to analyse and integrate large and multiple datasets together.
We have developed a computational pipeline to link the cell surface phenotype with the full transcriptome profile, including TCR. This model combines gene expression profile from scRNA-Seq with surface markers identified with flow cytometry index sorting on the same single cell. TCR were detected from scRNA-Seq reads using an updated version of the in-house developed tool to reconstruct VDJ sequence, called VDJPuzzle.
This pipeline has been applied to Ag-specific T cells derived from human peripheral blood mononuclear cells (PBMC) collected from a patient infected with Hepatitis C Virus and allowed us to identify surprisingly high heterogeneity. Our computational analysis contributes to the understanding of the evolution of lymphocytes during an immune response both at the population and molecular level providing insight into the interrelation and functioning of larger systems.