Back

A high-resolution, unbiased analysis of the cellular immune response to Epstein-Barr virus

Garcia Jimenez, A. F.; Picozzi, A.; Sanchez de la Cruz, A.; Vazquez, E.; Benguria, A.; Dopazo, A.; Lougaris, V.; Gonzalez-Granado, L. I.; Chijioke, O.; Lopez-Granados, E.; Reyburn, H. T.

2025-10-10 immunology
10.1101/2025.10.09.681317 bioRxiv
Show abstract

More than 95% of humans are infected with Epstein-Barr virus (EBV), yet although EBV infection has been associated with inflammatory and autoimmune diseases, lymphoproliferative disorders, and several types of cancer, for the vast majority of infected people the infection is asymptomatic as EBV replication is controlled by the immune system. Immunity against this virus has been studied since the discovery of EBV in the 1960s, and although important insights have been made, no unbiased, global studies of immune responses to EBV in healthy seropositive subjects have been reported. Here we describe a novel protocol to study the cellular immune response to EBV, detecting lymphocytes that respond to EBV via analyses of proliferation or induced expression of activation markers and cytokines. Using this system we sequenced, for the first time at a single-cell level, the transcriptome of all cells capable of responding to EBV in healthy individuals and in patients with inborn errors of immunity (IEI) associated with susceptibility to EBV infection. Lymphocyte cytotoxicity appears to be crucial for the proper control of EBV-infection, while a proportionate T-regulatory cell response likely helps to avoid excessive immunity and immune pathology. We also show that {gamma}{delta} T cells expressing the TCR V{delta}1 chain use various activating natural killer (NK) cell receptors to recognise and kill EBV-infected lymphoblastoid cell lines (LCLs) and thus could be a promising candidate for allogeneic cell therapy for EBV-associated lymphoproliferative disorders in patients with either primary or secondary immunodeficiencies. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=186 HEIGHT=200 SRC="FIGDIR/small/681317v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@116ad85org.highwire.dtl.DTLVardef@1da33d7org.highwire.dtl.DTLVardef@81a2a6org.highwire.dtl.DTLVardef@dd571d_HPS_FORMAT_FIGEXP M_FIG C_FIG

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.