VDJdb in 2019: database extension, new analysis infrastructure and a T-cell receptor motif compendium

Abstract

Here, we report an update of the VDJdb database with a substantial increase in the number of T-cell receptor (TCR) sequences and their cognate antigens. The update further provides a new database infrastructure featuring two additional analysis modes that facilitate database querying and real-world data analysis. The increased yield of TCR specificity identification methods and the overall increase in the number of studies in the field has allowed us to expand the database more than 5-fold. Furthermore, several new analysis methods are included. For example, batch annotation of TCR repertoire sequencing samples allows for annotating large datasets on-line. Using recently developed bioinformatic methods for TCR motif mining, we have built a reduced set of high-quality TCR motifs that can be used for both training TCR specificity predictors and matching against TCRs of interest. These additions enhance the versatility of the VDJdb in the task of exploring T-cell antigen specificities. The database is available at https://vdjdb.cdr3.net.

SARS-CoV-2 reactive T cells in uninfected individuals are likely expanded by beta-coronaviruses

“…By focusing on the most frequent european HLAs, inaccuracies in the epitope prediction are reduced or even avoided. We did not utilize epitope databases like VDJDB (29) and IEDB (30) , the reason being that these databases have a natural bias towards laboratory model antigen. For instance, the most frequent epitopes in the Immune Epitope Database are human auto antigen and epitopes derived from Trypanosoma cruzi.…”

Current challenges for epitope-agnostic TCR interaction prediction and a new perspective derived from image classification

“…Data. The data used in this study was collected from the August 2019 release of VDJdb (8). It consists of 75,474 curated pairs of TCR CDR3 alpha/beta sequences and their epitope targets, covering both MHC classes and three species (Homo sapiens, Mus musculus and Macaca Mulatta).…”

“…However, understanding the molecular underpinnings of TCR-epitope recognition has proven to be more challenging. This can be explained in part by the lack of sufficient amounts of high quality data, although more and more experimental data is now being generated and being stored in public databases such as VDJdb and IEDB (8,9). In addition, the large diversity of TCR and epitope sequences leads to a large, highdimensional and likely non-homogeneous search space.…”

Comprehensive analysis of structural and sequencing data reveals almost unconstrained chain pairing in TCRαβ complex

“…As overall differences in pairing preferences in TCRαβ complex were relatively subtle, we hypothesized that the TCR repertoire can still show αβ pairing preferences when subject to perturbations, such as antigen-driven selection and expansion. We have therefore investigated pairing preferences in TCRs specific to certain epitopes extracted from the VDJdb database [12] (see Materials and Methods section).…”

“…The effective T-cell diversity is thus only limited by the total number of T-cells in human that is~10 11 [1] and potential pairing preferences between α and β chains. The size of foreign peptide pool to be recognized by T-cells can reach~10 12 variants for all possible 9-mers presented by HLA class I. So, as both TCR α and β chain is required to recognize an antigen [2] and a certain degree of cross-reactivity is needed to be able to form an efficient immune response [3], one would expect the immune system to aim at producing the highest possible number of α and β chain combinations across distinct T-cells in order to ensure optimal recognition of newly encountered pathogens.…”