Computational Strategies for Dissecting the High-Dimensional Complexity of Adaptive Immune Repertoires

Abstract

The adaptive immune system recognizes antigens via an immense array of antigen-binding antibodies and T-cell receptors, the immune repertoire. The interrogation of immune repertoires is of high relevance for understanding the adaptive immune response in disease and infection (e.g., autoimmunity, cancer, HIV). Adaptive immune receptor repertoire sequencing (AIRR-seq) has driven the quantitative and molecular-level profiling of immune repertoires, thereby revealing the high-dimensional complexity of the immune receptor sequence landscape. Several methods for the computational and statistical analysis of large-scale AIRR-seq data have been developed to resolve immune repertoire complexity and to understand the dynamics of adaptive immunity. Here, we review the current research on (i) diversity, (ii) clustering and network, (iii) phylogenetic, and (iv) machine learning methods applied to dissect, quantify, and compare the architecture, evolution, and specificity of immune repertoires. We summarize outstanding questions in computational immunology and propose future directions for systems immunology toward coupling AIRR-seq with the computational discovery of immunotherapeutics, vaccines, and immunodiagnostics.

T‐cell receptor and B‐cell receptor repertoire profiling in adaptive immunity

“…Many computational approaches have been developed in the last decade to process and analyze HTS immune repertoire data , including software tools that can be used to extract TCR or BCR repertoires from raw sequencing reads (e.g., MiXCR, Vidjil, IMSEQ, IgReC ). This typically includes creating a list of clonotypes with determined CDR3, V, D, and J segments and their borders, as well as each clonotype's count and basic error correction, based on the collapsing of similar sequences.…”

Profiling virus-specific Tcf1+ T cell repertoires during acute and chronic viral infection

“…While multiple studies have recently investigated the transcriptional landscape of defined virus-specific Tcf1+ CD8 T cells in both acute and chronic infections (Utzschneider et al, 2016;Chen et al, 2019, 1), less attention has been devoted to studying the Tcf1+ and Tcf1-T cell receptor (TCR) repertoires under these two infection conditions. Advances in deep sequencing technologies enable the investigation of TCR (and antibody) repertoires at high-throughput and relatively inexpensive costs (Greiff, Miho, et al, 2015;Georgiou et al, 2014;Miho et al, 2018).…”

The expanding role of systems immunology in decoding the T cell receptor repertoire

“…data quality control, sequencing error prediction/correction, etc) and the analysis of specific “one-dimensional” immune repertoire characteristics. These immune repertoire characteristics, and the available computational tools, were neatly categorized in a recent review by Miho et al [8] as primarily relating to the assessment of diversity, similarity architecture, evolutionary relationships (antibody repertoires) and convergence or overlap between immune repertoires. While such tools have so far facilitated substantial progress in our understanding of TCR repertoires, there is a growing need for the development of more sophisticated computational approaches to provide higher-dimensional insights into TCR biology and to ensure statistically robust interpretation of data observations.…”