OLGA: fast computation of generation probabilities of B- and T-cell receptor amino acid sequences and motifs

Abstract

Motivation: High-throughput sequencing of large immune repertoires has enabled the development of methods to predict the probability of generation by V(D)J recombination of Tand B-cell receptors of any specific nucleotide sequence. These generation probabilities are very non-homogeneous, ranging over 20 orders of magnitude in real repertoires. Since the function of a receptor really depends on its protein sequence, it is important to be able to predict this probability of generation at the amino acid level. However, brute-force summation over all the nucleotide sequences with the correct amino acid translation is computationally intractable. The purpose of this paper is to present a solution to this problem. Results: We use dynamic programming to construct an efficient and flexible algorithm, called OLGA (Optimized Likelihood estimate of immunoGlobulin Amino-acid sequences), for calculating the probability of generating a given CDR3 amino acid sequence or motif, with or without V/J restriction, as a result of V(D)J recombination in B or T cells. We apply it to databases of epitope-specific T-cell receptors to evaluate the probability that a typical human subject will possess T cells responsive to specific disease-associated epitopes. The model prediction shows an excellent agreement with published data. We suggest that OLGA may be a useful tool to guide vaccine design. Availability: Source code is available at https://github.com/zsethna/OLGA

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

“…The V (D)J recombination mechanism generates some antigen receptor sequences much more frequently than others. There are efficient algorithms that can calculate the probability of generation for a given antigen receptor sequence [52, 85,86], and these could theoretically estimate the number of donors sharing such sequence [87]. Thus, there is no sharp border between public and private clonotypes, but rather a continuous spectrum of publicness defined by the probability of an antigen receptor being produced by the recombination machinery.…”

How many different clonotypes do immune repertoires contain?

“…The two corresponding clones would be indistinguishable, and form a single clonotype in the repertoire. This effect can be corrected for by using models of recombination [43,44]. These models, which are inferred from data, can predict the distribution of generation probabilities of full receptors, or of single chains, both at the level of nucletoide or amino acid sequences, as shown in Fig.…”

“…Clones ×10 [44]. Most clonotypes have very low probability and are therefore unlikely to occur in two clones independently.…”

Quantitative Immunology for Physicists

“…. Entropy estimates for both nucleotide and amino acid sequences are reported in [176]. Human nucletoide TCR β diversity is H 1 ∼ 44 bits (bits refer to ln(2) units) for nucletoides and 30 bits for amino-acids, TCR α divesity is ∼ 30 bits for nucleotides and 25 bits for amino acids.…”