Abstract
BackgroundDeep immune receptor sequencing, RepSeq, provides unprecedented opportunities for identifying and studying condition-associated T-cell clonotypes, represented by T-cell receptor (TCR) CDR3 sequences. However, due to the immense diversity of the immune repertoire, identification of condition relevant TCR CDR3s from total repertoires has mostly been limited to either “public” CDR3 sequences or to comparisons of CDR3 frequencies observed in a single individual. A methodology for the identification of condition-associated TCR CDR3s by direct population level comparison of RepSeq samples is currently lacking.ResultsWe present a method for direct population level comparison of RepSeq samples using immune repertoire sub-units (or sub-repertoires) that are shared across individuals. The method first performs unsupervised clustering of CDR3s within each sample. It then finds matching clusters across samples, called immune sub-repertoires, and performs statistical differential abundance testing at the level of the identified sub-repertoires. It finally ranks CDR3s in differentially abundant sub-repertoires for relevance to the condition. We applied the method on total TCR CDR3β RepSeq datasets of celiac disease patients, as well as on public datasets of yellow fever vaccination. The method successfully identified celiac disease associated CDR3β sequences, as evidenced by considerable agreement of TRBV-gene and positional amino acid usage patterns in the detected CDR3β sequences with previously known CDR3βs specific to gluten in celiac disease. It also successfully recovered significantly high numbers of previously known CDR3β sequences relevant to each condition than would be expected by chance.ConclusionWe conclude that immune sub-repertoires of similar immuno-genomic features shared across unrelated individuals can serve as viable units of immune repertoire comparison, serving as proxy for identification of condition-associated CDR3s.
Highlights
Deep immune receptor sequencing, RepSeq, provides unprecedented opportunities for identifying and studying condition-associated T-cell clonotypes, represented by T-cell receptor (TCR) Complementarity-determining regions 3 (CDR3) sequences
We recently showed that over-represented amino acid motifs in CD-associated TCR Complementarity-determining regions 3 of the beta chain (CDR3β) sequences, originally identified from tetramer binding antigen-reactive T-cells [17, 18], were detectable from the unsorted total peripheral blood immune repertoires of celiac disease patients despite the immense repertoire diversity [9]
We hypothesized that clustering of CDR3s in the global repertoire reduces the enormous diversity of the immune repertoires into manageable units, and has the potential for allowing indirect detection of condition associated CDR3s by first comparing the abundance of CDR3 clusters between sample groups (Fig. 1)
Summary
RepSeq, provides unprecedented opportunities for identifying and studying condition-associated T-cell clonotypes, represented by T-cell receptor (TCR) CDR3 sequences. A frequently used approach to the identification of condition-specific clonotypes across sample groups is the investigation of the so called public clonotypes (represented typically by unique TCR CDR3 sequences), which are commonly observed across many individuals [4,5,6,7,8,9,10,11] Such shared clonotypes make up a small portion of the total immune response in each individual. Pogorelyy et al reported a Bayesian statistical method for comparing and detecting expanded/relevant clonotypes between repertoires of same individual at different time points [16] These methods allow the identification of interesting clones, which are private to individuals, but do not allow the direct investigation of differentially abundant clonotypes at the population level ad hoc combining of results from multiple samples is still possible. There is currently a need for methods that perform direct population level comparison of clonal differential abundance for the identification of condition-specific T-cell clonotypes in longitudinal or case–control RepSeq datasets
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
