Is the exquisite specificity of lymphocytes generated by thymic selection or due to evolution?

We have previously argued that the antigen receptors of T and B lymphocytes evolved to be sufficiently specific to avoid massive deletion of clonotypes by negative selection. Their optimal 'specificity' level, i.e., probability of binding any particular epitope, was shown to be inversely related to the number of self-antigens that the cells have to be tolerant to. Experiments have demonstrated that T lymphocytes also become more specific during negative selection in the thymus, because cells expressing the most crossreactive receptors have the highest likelihood of binding a self-antigen, and hence to be tolerized (i.e., deleted, anergized, or diverted into a regulatory T cell phenotype). Thus, there are two -not mutually exclusive- explanations for the exquisite specificity of T cells, one involving evolution and the other thymic selection. To better understand the impact of both, we extend a previously developed mathematical model by allowing for T cells with very different binding probabilities in the pre-selection repertoire. We confirm that negative selection tends to tolerize the most crossreactive clonotypes. As a result, the average level of specificity in the functional post-selection repertoire depends on the number of self-antigens, even if there is no evolutionary optimization of binding probabilities. However, the evolutionary optimal range of binding probabilities in the pre-selection repertoire also depends on the number of self-antigens. Species with more self antigens need more specific pre-selection repertoires to avoid excessive loss of T cells during thymic selection, and hence mount protective immune responses. We conclude that both evolution and negative selection are responsible for the high level of specificity of lymphocytes.

Role of T cells in severe COVID-19 disease, protection, and long term immunity.

Infection with SARS-CoV-2 causes wide range of disease severities from asymptomatic to life-threatening disease. Understanding the contribution of immunological traits in immunity against SARS-CoV-2 and in protection against severe COVID-19 could result in effective measures to prevent development of severe disease. While the role of cytokines and antibodies has been thoroughly studied, this is not the case for T cells. In this review, the association between T cells and COVID-19 disease severity and protection upon reexposure is discussed. While infiltration of overactivated cytotoxic T cells might be harmful in the infected tissue, fast responding T cells are important in the protection against severe COVID-19. This protection could even be viable in the long term as long-living memory T cells seem to be stabilized and mutations do not appear to have a large impact on T cell responses. Thus, after vaccination and infections, memory T cells should be able to help prevent onset of severe disease for most cases. Considering this, it would be useful to add N or M proteins in vaccinations, alongside the S protein which is currently used, as this results in a broader T cell response.

Evolution of SARS-CoV-2-specific CD4+ T cell epitopes.

Vaccination clearly decreases coronavirus disease 2019 (COVID-19) mortality; however, they also impose selection pressure on the virus, which promotes the evolution of immune escape variants. For example, despite the high vaccination level in especially Western countries, the Omicron variant caused millions of breakthrough infections, suggesting that the highly mutated spike protein in the Omicron variant can escape antibody immunity much more efficiently than the other variants of concern (VOCs). In this study, we investigated the resistance/susceptibility of T helper cell responses that are necessary for generating efficient long-lasting antibody immunity, in several VOCs. By predicting T helper cell epitopes on the spike protein for most common HLA-DRB1 alleles worldwide, we found that although most of high frequency HLA-DRB1 alleles have several potential T helper cell epitopes, few alleles like HLA-DRB1 13:01 and 11:01 are not predicted to have any significant T helper cell responses after vaccination. Using these predictions, a population based on realistic human leukocyte antigen-II (HLA-II) frequencies were simulated to visualize the T helper cell immunity on the population level. While a small fraction of this population had alarmingly little predicted CD4 T cell epitopes, the majority had several epitopes that should be enough to generate efficient B cell responses. Moreover, we show that VOC spike mutations hardly affect T helper epitopes and mainly occur in other residues of the spike protein. These results suggest that lack of long-lasting antibody responses is not likely due to loss of T helper cell epitopes in new VOCs.

CD200R1L is a functional evolutionary conserved activating receptor in human neutrophils.

Inhibitory and activating immune receptors play a key role in modulating the amplitude and duration of immune responses during infection and in maintaining immune balance in homeostatic conditions. The CD200 Receptor (CD200R) gene family in humans encodes one inhibitory receptor, CD200R1, and one putative activating member, CD200R1 Like (CD200R1L). It is demonstrated that CD200R1L is endogenously expressed by human neutrophils and activates cellular functions such as reactive oxygen species (ROS) production via Syk, PI3Kß, PI3Kδ, and Rac GTPase signaling. Phylogenetic analysis shows that CD200R1L is present in many species among vertebrates, ranging from birds to primates, suggesting that evolutionary conservation of this receptor is critical for protection against co-evolving pathogens. The duplication event that generated CD200R1L from CD200R occurred several times throughout evolution, supporting convergent evolution of CD200R1L. In our phylogenetic trees, CD200R1L has longer branch lengths than CD200R1 in most species, suggesting that CD200R1L is evolving faster than CD200R1. It is proposed that CD200R1L represents a hitherto uncharacterized activating receptor on human neutrophils.

Quantifying the Impact of Human Leukocyte Antigen on the Human Gut Microbiota.

The composition of the gut microbiota is affected by a number of factors, including the innate and adaptive immune system. The major histocompatibility complex (MHC), or the human leukocyte antigen (HLA) in humans, performs an essential role in vertebrate immunity and is very polymorphic in different populations. HLA determines the specificity of T lymphocyte and natural killer (NK) cell responses, including those against the commensal bacteria present in the human gut. Thus, it is likely that our HLA molecules, and thereby the adaptive immune response, can shape the composition of our microbiota. Here, we investigated the effect of HLA haplotype on the microbiota composition. We performed HLA typing and microbiota composition analyses on 3,002 public human gut microbiome data sets. We found that individuals with functionally similar HLA molecules are also similar in their microbiota composition. Our results show a statistical association between host HLA haplotype and gut microbiota composition. Because the HLA haplotype is a readily measurable parameter of the human immune system, these results open the door to incorporating the genetics of the immune system into predictive microbiome models. IMPORTANCE The microorganisms that live in the digestive tracts of humans, known as the gut microbiota, are essential for hosts' survival, as they support crucial functions. For example, they support the host in facilitating the uptake of nutrients and give colonization resistance against pathogens. The composition of the gut microbiota varies among humans. Studies have proposed multiple factors driving the observed variation, including diet, lifestyle, and health condition. Another major influence on the microbiota is the host's genetic background. We hypothesized the immune system to be one of the most important genetic factors driving the differences observed between gut microbiotas. Therefore, we searched for a link between the polymorphic molecules that shape human immune responses and the composition of the microbiota. HLA molecules are the most polymorphic molecules in our genome and therefore makes an excellent candidate to test such an association. To our knowledge for the first time, our results indicate a significant impact of the HLA on the human gut microbiota.

Identification of a novel conserved signaling motif in CD200 receptor required for its inhibitory function.

The inhibitory signaling of CD200 receptor 1 (CD200R) has been attributed to its NPxY signaling motif. However, NPxY-motifs are present in multiple protein families and are mostly known to mediate protein trafficking between subcellular locations rather than signaling. Therefore, we investigated whether additional motifs specify the inhibitory function of CD200R. We performed phylogenetic analysis of the intracellular domain of CD200R in mammals, birds, bony fish, amphibians and reptiles. Indeed, the tyrosine of the NPxY-motif is fully conserved across species, in line with its central role in CD200R signaling. In contrast, P295 of the NPxY-motif is not conserved. Instead, a conserved stretch of negatively charged amino acids, EEDE279, and two conserved residues P285 and K292 in the flanking region prior to the NPxY-motif are required for CD200R mediated inhibition of p-Erk, p-Akt308, p-Akt473, p-rpS6 and LPS-induced IL-8 secretion. Altogether, we show that instead of the more common NPxY-motif, CD200R signaling can be assigned to a unique signaling motif in mammals defined by: EEDExxPYxxYxxKxNxxY.

Is T Cell Negative Selection a Learning Algorithm?

Our immune system can destroy most cells in our body, an ability that needs to be tightly controlled. To prevent autoimmunity, the thymic medulla exposes developing T cells to normal "self" peptides and prevents any responders from entering the bloodstream. However, a substantial number of self-reactive T cells nevertheless reaches the periphery, implying that T cells do not encounter all self peptides during this negative selection process. It is unclear if T cells can still discriminate foreign peptides from self peptides they haven't encountered during negative selection. We use an "artificial immune system"-a machine learning model of the T cell repertoire-to investigate how negative selection could alter the recognition of self peptides that are absent from the thymus. Our model reveals a surprising new role for T cell cross-reactivity in this context: moderate T cell cross-reactivity should skew the post-selection repertoire towards peptides that differ systematically from self. Moreover, even some self-like foreign peptides can be distinguished provided that the peptides presented in the thymus are not too similar to each other. Thus, our model predicts that negative selection on a well-chosen subset of self peptides would generate a repertoire that tolerates even "unseen" self peptides better than foreign peptides. This effect would resemble a "generalization" process as it is found in learning systems. We discuss potential experimental approaches to test our theory.

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

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.

Revealing factors determining immunodominant responses against dominant epitopes.

Upon recognition of peptide-MHC complexes by T cell receptors (TCR), the cognate T cells expand and differentiate into effector T cells to generate protective immunity. Despite the fact that any immune response generates a diverse set of TCR clones against a particular epitope, only a few clones are highly expanded in any immune response. Previous studies observed that the highest frequency clones usually control viral infections better than subdominant clones, but the reasons for this dominance among T cell clones are still unclear. Here, we used publicly available TCR amino acid sequences to study which factors determine whether a response becomes immunodominance (ID) per donor; we classified the largest T cell clone as the epitope-specific dominant clone and all the other clones as subdominant responses (SD). We observed a distinctively hydrophobic CDR3 in ID responses against a dominant epitope from influenza A virus, compared to the SD responses. The common V-J combinations were shared between ID and SD responses, suggesting that the biased V-J recombination events are restricted by epitope specificity; thus, the immunodominance is not directly determined by a bias combination of V and J genetic segments. Our findings reveal a close similarity of global sequence properties between dominant and subdominant clones of epitope-specific responses but detectable distinctive amino acid enrichments in ID. Taken together, we believe this first comparative study of immunodominant and subdominant TCR sequences can guide further studies to resolve factors determining the immunodominance of antiviral as well as tumor-specific T cell responses.

Exploratory Study of Predicted Indirectly ReCognizable HLA Epitopes in Mismatched Hematopoietic Cell Transplantations.

HLA-mismatches in hematopoietic stem-cell transplantation are associated with an impaired overall survival (OS). The aim of this study is to explore whether the Predicted Indirectly ReCognizable HLA-Epitopes (PIRCHE) algorithm can be used to identify HLA-mismatches that are related to an impaired transplant outcome. PIRCHE are computationally predicted peptides derived from the patient's mismatched-HLA molecules that can be presented by donor-patient shared HLA. We retrospectively scored PIRCHE numbers either presented on HLA class-I (PIRCHE-I) or class-II (PIRCHE-II) for a Dutch multicenter cohort of 103 patients who received a single HLA-mismatched (9/10) unrelated donor transplant in an early phase of their disease. These patients were divided into low and high PIRCHE-I and PIRCHE-II groups, based on their PIRCHE scores, and compared using multivariate statistical analysis methods. The high PIRCHE-II group had a significantly impaired OS compared to the low PIRCHE-II group and the 10/10 reference group (HR: 1.86, 95%-CI: 1.02-3.40; and HR: 2.65, 95%-CI: 1.53-4.60, respectively). Overall, PIRCHE-II seem to have a more prominent effect on OS than PIRCHE-I. This impaired OS is probably due to an increased risk for severe acute graft-vs.-host disease. These data suggest that high PIRCHE-II scores may be used to identify non-permissible HLA mismatches within single HLA-mismatched hematopoietic stem-cell transplantations.

Immune biomarkers for predicting response to adoptive cell transfer as cancer treatment.

Adoptive cell transfer (ACT) is a form of personalised immunotherapy which has shown promising results in metastasised cancer. For this treatment, autologous T lymphocytes are selected and stimulated in vitro before re-administration in large numbers. However, only a fraction of patients benefit from ACT, and it is not yet known what biomarkers can predict treatment outcome. In this review, we describe what tumour characteristics are associated with response to ACT. Based on the current knowledge, the best candidate biomarker for a good anti-tumour response seems to be a large number of neoantigens with a homogeneous distribution across the tumour in combination with sufficient MHC-I expression level. Additionally, it is necessary to be able to isolate a diverse population of T cells reactive to these neoantigens from tumour tissue or peripheral blood. Additional promising candidate biomarkers shared with other cancer immunotherapies are a large number of tumour-infiltrating cytotoxic and memory T cells, normal levels of glycolysis, and a pro-inflammatory cytokine profile within the tumour. Intense research in this field will hopefully result in identification of more biomarkers for cancers with low mutational load.

Specificity of inhibitory KIRs enables NK cells to detect changes in an altered peptide environment.

The activity of natural killer (NK) cells is tightly regulated by inhibitory and activating receptors. Inhibitory killer immunoglobulin-like receptors (iKIRs) survey the surface of target cells by monitoring the expression of human leukocyte antigen (HLA) class I. The binding of iKIRs has been shown to be sensitive to the peptides presented by HLA class I, implying that iKIRs have the ability to detect the changes in the repertoire of peptide-HLA class I complexes (pHLA), a process occurring during viral infection and in tumor cells. To study how the pHLA repertoire changes upon infection, and whether an iKIR is able to detect these changes, we study peptides eluted from cells prior and after infection with measles virus (MV). Remarkably, most changes in the repertoire of potential iKIR ligands are predicted to be caused by the altered expression of self-peptides. We show that an iKIR can detect these changes in the presented peptides only if it is sufficiently specific, e.g., if iKIRs can distinguish between different amino acids in the contact residues (e.g., position 7 and 8). Our analysis further indicates that one single iKIR per host is not sufficient to detect changes in the peptide repertoire, suggesting that a multigene family encoding for different iKIRs is required for successful peptide recognition.

VDJdb: a curated database of T-cell receptor sequences with known antigen specificity.

The ability to decode antigen specificities encapsulated in the sequences of rearranged T-cell receptor (TCR) genes is critical for our understanding of the adaptive immune system and promises significant advances in the field of translational medicine. Recent developments in high-throughput sequencing methods (immune repertoire sequencing technology, or RepSeq) and single-cell RNA sequencing technology have allowed us to obtain huge numbers of TCR sequences from donor samples and link them to T-cell phenotypes. However, our ability to annotate these TCR sequences still lags behind, owing to the enormous diversity of the TCR repertoire and the scarcity of available data on T-cell specificities. In this paper, we present VDJdb, a database that stores and aggregates the results of published T-cell specificity assays and provides a universal platform that couples antigen specificities with TCR sequences. We demonstrate that VDJdb is a versatile instrument for the annotation of TCR repertoire data, enabling a concatenated view of antigen-specific TCR sequence motifs. VDJdb can be accessed at https://vdjdb.cdr3.net and https://github.com/antigenomics/vdjdb-db.

Long-term adaptation of the influenza A virus by escaping cytotoxic T-cell recognition.

The evolutionary adaptation of the influenza A virus (IAV) to human antibodies is well characterised. Much less is known about the long-term evolution of cytotoxic T lymphocyte (CTL) epitopes, which are important antigens for clearance of infection. We construct an antigenic map of IAVs of all human subtypes using a compendium of 142 confirmed CTL epitopes, and show that IAV evolved gradually in the period 1932-2015, with infrequent antigenic jumps in the H3N2 subtype. Intriguingly, the number of CTL epitopes per virus decreases with more than one epitope per three years in the H3N2 subtype (from 84 epitopes per virus in 1968 to 64 in 2015), mostly attributed to the loss of HLA-B epitopes. We confirm these observations with epitope predictions. Our findings indicate that selection pressures imposed by CTL immunity shape the long-term evolution of IAV.

The evolution of natural killer cell receptors.

Natural killer (NK) cells are immune cells that play a crucial role against viral infections and tumors. To be tolerant against healthy tissue and simultaneously attack infected cells, the activity of NK cells is tightly regulated by a sophisticated array of germline-encoded activating and inhibiting receptors. The best characterized mechanism of NK cell activation is "missing self" detection, i.e., the recognition of virally infected or transformed cells that reduce their MHC expression to evade cytotoxic T cells. To monitor the expression of MHC-I on target cells, NK cells have monomorphic inhibitory receptors which interact with conserved MHC molecules. However, there are other NK cell receptors (NKRs) encoded by gene families showing a remarkable genetic diversity. Thus, NKR haplotypes contain several genes encoding for receptors with activating and inhibiting signaling, and that vary in gene content and allelic polymorphism. But if missing-self detection can be achieved by a monomorphic NKR system why have these polygenic and polymorphic receptors evolved? Here, we review the expansion of NKR receptor families in different mammal species, and we discuss several hypotheses that possibly underlie the diversification of the NK cell receptor complex, including the evolution of viral decoys, peptide sensitivity, and selective MHC-downregulation.

Measles Virus Epitope Presentation by HLA: Novel Insights into Epitope Selection, Dominance, and Microvariation.

Immunity to infections with measles virus (MV) can involve vigorous human leukocyte antigen (HLA) class I-restricted CD8(+) cytotoxic T cell (CTL) responses. MV, albeit regarded monotypic, is known to undergo molecular evolution across its RNA genome. To address which regions of the MV proteome are eligible for recognition by CD8(+) CTLs and how different HLA class I loci contribute to the epitope display, we interrogated the naturally processed and presented MV peptidome extracted from cell lines expressing in total a broad panel of 16 different common HLA-A, -B, and -C molecules. The repertoire and abundance of MV peptides were bona fide identified by nanoHPLC-MS/MS. -Eighty-nine MV peptides were discovered and assignment to an HLA-A, -B, or -C allele, based on HLA-peptide affinity prediction, was in most cases successful. Length variation and presentation by multiple HLA class I molecules was common in the MV peptidome. More than twice as many unique MV epitopes were found to be restricted by HLA-B than by HLA-A, while MV peptides with supra-abundant expression rates (>5,000 cc) were rather associated with HLA-A and HLA-C. In total, 59 regions across the whole MV proteome were identified as targeted by HLA class I. Sequence coverage by epitopes was highest for internal proteins transcribed from the MV-P/V/C and -M genes and for hemagglutinin. At the genome level, the majority of the HLA class I-selected MV epitopes represented codons having a higher non-synonymous mutation rate than silent mutation rate, as established by comparison of a set of 58 unique full length MV genomes. Interestingly, more molecular variation was seen for the epitopes expressed at rates ≥1,000 cc. These data for the first time indicate that HLA class I broadly samples the MV proteome and that CTL pressure may contribute to the genomic evolution of MV.

HLA Preferences for Conserved Epitopes: A Potential Mechanism for Hepatitis C Clearance.

Hepatitis C virus (HCV) infections affect more than 170 million people worldwide. Most of these individuals are chronically infected, but some clear the infection rapidly. Host factors seem to play a key role in HCV clearance, among them are the human leukocyte antigen (HLA) class I molecules. Certain HLA molecules, e.g., B*27 and B*57, are associated with viral clearance. To identify potential mechanisms for these associations, we assess epitope distribution differences between HLA molecules using experimentally verified and in silico predicted HCV epitopes. Specifically, we show that the NS5B protein harbors the largest fraction of conserved regions among all HCV proteins. Such conserved regions could be good targets for cytotoxic T-cell (CTL) responses. We find that the protective HLA-B*27 molecule preferentially presents cytotoxic T-cell (CTL) epitopes from NS5B and, in general, presents the most strongly conserved epitopes among the 23 HLA molecules analyzed. In contrast, HLA molecules known to be associated with HCV persistence do not have similar preferences and appear to target the variable P7 protein. Overall, our analysis suggests that by targeting highly constrained - and thereby conserved - regions of HCV, the protective HLA molecule HLA-B*27 reduces the ability of HCV to escape the cytotoxic T-cell response of the host. For visualizing the distribution of both experimentally verified and predicted epitopes across the HCV genome, we created the HCV epitope browser, which is available at theory.bio.uu.nl/ucqi/hcv.

Comprehensive Analysis of the Naturally Processed Peptide Repertoire: Differences between HLA-A and B in the Immunopeptidome.

The cytotoxic T cell (CTL) response is determined by the peptide repertoire presented by the HLA class I molecules of an individual. We performed an in-depth analysis of the peptide repertoire presented by a broad panel of common HLA class I molecules on four B lymphoblastoid cell-lines (BLCL). Peptide elution and mass spectrometry analysis were utilised to investigate the number and abundance of self-peptides. Altogether, 7897 unique self-peptides, derived of 4344 proteins, were eluted. After viral infection, the number of unique self-peptides eluted significantly decreased compared to uninfected cells, paralleled by a decrease in the number of source proteins. In the overall dataset, the total number of unique self-peptides eluted from HLA-B molecules was larger than from HLA-A molecules, and they were derived from a larger number of source proteins. These results in B cells suggest that HLA-B molecules possibly present a more diverse repertoire compared to their HLA-A counterparts, which may contribute to their immunodominance. This study provides a unique data set giving new insights into the complex system of antigen presentation for a broad panel of HLA molecules, many of which were never studied this extensively before.