Stability of peptide-HLA-I complexes and tapasin folding facilitation - tools to define immunogenic peptides

Impact of peptide:HLA complex stability for the identification of SARS-CoV-2-specific CD8+T cells

Induction of a lasting protective immune response is dependent on presentation of epitopes to patrolling T cells through the HLA complex. While peptide:HLA (pHLA) complex affinity alone is widely exploited for epitope selection, we demonstrate that including the pHLA complex stability as a selection parameter can significantly reduce the high false discovery rate observed with predicted affinity. In this study, pHLA complex stability was measured on three common class I alleles and 1286 overlapping 9-mer peptides derived from the SARS-CoV-2 Spike protein. Peptides were pooled based on measured stability and predicted affinity. Strikingly, stability of the pHLA complex was shown to strongly select for immunogenic epitopes able to activate functional CD8⁺T cells. This result was observed across the three studied alleles and in both vaccinated and convalescent COVID-19 donors. Deconvolution of peptide pools showed that specific CD8⁺T cells recognized one or two dominant epitopes. Moreover, SARS-CoV-2 specific CD8⁺T cells were detected by tetramer-staining across multiple donors. In conclusion, we show that stability analysis of pHLA is a key factor for identifying immunogenic epitopes.

Structure-guided stabilization of pathogen-derived peptide-HLA-E complexes using non-natural amino acids conserves native TCR recognition

The nonpolymorphic class Ib molecule, HLA-E, primarily presents peptides from HLA class Ia leader peptides, providing an inhibitory signal to NK cells via CD94/NKG2 interactions. Although peptides of pathogenic origin can also be presented by HLA-E to T cells, the molecular basis underpinning their role in antigen surveillance is largely unknown. Here, we solved a co-complex crystal structure of a TCR with an HLA-E presented peptide (pHLA-E) from bacterial (Mycobacterium tuberculosis) origin, and the first TCR-pHLA-E complex with a noncanonically presented peptide from viral (HIV) origin. The structures provided a molecular foundation to develop a novel method to introduce cysteine traps using non-natural amino acid chemistry that stabilized pHLA-E complexes while maintaining native interface contacts between the TCRs and different pHLA-E complexes. These pHLA-E monomers could be used to isolate pHLA-E-specific T cells, with obvious utility for studying pHLA-E restricted T cells, and for the identification of putative therapeutic TCRs.

HLA class I is most tightly linked to levels of tapasin compared with other antigen-processing proteins in glioblastoma

Background:

Tumour cells can evade the immune system by dysregulation of human leukocyte antigens (HLA-I). Low quantity and/or altered quality of HLA-I cell surface expression is the result of either HLA-I alterations or dysregulations of proteins of the antigen-processing machinery (APM). Tapasin is an APM protein dedicated to the maturation of HLA-I and dysregulation of tapasin has been linked to higher malignancy in several different tumours.

Methods:

We studied the expression of APM components and HLA-I, as well as HLA-I tapasin-dependency profiles in glioblastoma tissues and corresponding cell lines.

Results:

Tapasin displayed the strongest correlation to HLA-I heavy chain but also clustered with β₂-microglobulin, transporter associated with antigen processing (TAP) and LMP. Moreover, tapasin also correlated to survival of glioblastoma patients. Some APM components, for example, TAP1/TAP2 and LMP2/LMP7, showed variable but coordinated expression, whereas ERAP1/ERAP2 displayed an imbalanced expression pattern. Furthermore, analysis of HLA-I profiles revealed variable tapasin dependence of HLA-I allomorphs in glioblastoma patients.

Conclusions:

Expression of APM proteins is highly variable between glioblastomas. Tapasin stands out as the APM component strongest correlated to HLA-I expression and we proved that HLA-I profiles in glioblastoma patients include tapasin-dependent allomorphs. The level of tapasin was also correlated with patient survival time. Our results support the need for individualisation of immunotherapy protocols.

Tapasin facilitation of natural HLA-A and -B allomorphs is strongly influenced by peptide length, depends on stability, and separates closely related allomorphs

Despite an abundance of peptides inside a cell, only a small fraction is ultimately presented by HLA-I on the cell surface. The presented peptides have HLA-I allomorph-specific motifs and are restricted in length. So far, detailed length studies have been limited to few allomorphs. Peptide-HLA-I (pHLA-I) complexes of different allomorphs are qualitatively and quantitatively influenced by tapasin to different degrees, but again, its effect has only been investigated for a small number of HLA-I allomorphs. Although both peptide length and tapasin dependence are known to be important for HLA-I peptide presentation, the relationship between them has never been studied. In this study, we used random peptide libraries from 7- to 13-mers and studied binding in the presence and absence of a recombinant truncated form of tapasin. The data show that HLA-I allomorphs are differentially affected by tapasin, different lengths of peptides generated different amounts of pHLA-I complexes, and HLA-A allomorphs are generally less restricted than HLA-B allomorphs to peptides of the classical length of 8-10 aa. We also demonstrate that tapasin facilitation varies for different peptide lengths, and that the correlation between high degree of tapasin facilitation and low stability is valid for different random peptide mixes of specific lengths. In conclusion, these data show that tapasin has specificity for the combination of peptide length and HLA-I allomorph, and suggest that tapasin promotes formation of pHLA-I complexes with high on and off rates, an important intermediary step in the HLA-I maturation process.

Simultaneous alignment and clustering of peptide data using a Gibbs sampling approach

MOTIVATION

Proteins recognizing short peptide fragments play a central role in cellular signaling. As a result of high-throughput technologies, peptide-binding protein specificities can be studied using large peptide libraries at dramatically lower cost and time. Interpretation of such large peptide datasets, however, is a complex task, especially when the data contain multiple receptor binding motifs, and/or the motifs are found at different locations within distinct peptides.

RESULTS

The algorithm presented in this article, based on Gibbs sampling, identifies multiple specificities in peptide data by performing two essential tasks simultaneously: alignment and clustering of peptide data. We apply the method to de-convolute binding motifs in a panel of peptide datasets with different degrees of complexity spanning from the simplest case of pre-aligned fixed-length peptides to cases of unaligned peptide datasets of variable length. Example applications described in this article include mixtures of binders to different MHC class I and class II alleles, distinct classes of ligands for SH3 domains and sub-specificities of the HLA-A*02:01 molecule.

AVAILABILITY

The Gibbs clustering method is available online as a web server at http://www.cbs.dtu.dk/services/GibbsCluster.