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

Andrew K Sewell,Dmitriy M Chudakov,Dmitry V Bagaev,Meriem Attaf,Fabio Luciani,David K Cole,Ivan V Zvyagin,Jerome Samir,Can Kesmir,Garry Dolton,Cristina Rius,Mikhail Shugay,Alexander Greenshields-Watson,Nina Babel,Evgeny S Egorov,Ulrik Stervbo,Andrew J Godkin,Renske M A Vroomans

doi:10.1093/nar/gkz874

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.

Highlights

Knowing the exact antigen specificity of a given T-cell is key to solving numerous problems of both basic and ap* To plied immunology research: from discovering the specificity profile of T-cell receptor (TCR) repertoire sequencing samples [1,2], to finding associations between autoimmunity and foreign mimics of self-antigens [3], and designing of personalized tumor immunotherapies [4]
VDJdb database is substantially expanded compared to the previous report [6]: since the establishment of the database a total of 155 published studies were processed and added resulting in 61 049 TCR specificity records in 2019 compared to only 5491 in 2017
We used the publication dates of papers added to VDJdb to calculate the rate of accumulation of TCR specificity knowledge (Figure 1)

Summary

Introduction

Knowing the exact antigen specificity of a given T-cell is key to solving numerous problems of both basic and ap* To plied immunology research: from discovering the specificity profile of TCR repertoire sequencing samples [1,2], to finding associations between autoimmunity and foreign mimics of self-antigens [3], and designing of personalized tumor immunotherapies [4]. The field of molecular methods designed for studying antigen-specific T-cells is developing at a high pace: novel methodologies based on single-cell T-cell sequencing allow simultaneous detection of TCR sequence, T-cell phenotype and a vast array of antigen specificities [5]. A number of methods for TCR specificity prediction were reported recently, many of which rely on VDJdb data for training and validating classifiers [9,10,11,12]. The latter demonstrates the overall potential of the VDJdb database for developing better bioinformatic methods for TCR sequence analysis

Methods

Results

Conclusion