Sequence variability analysis of human class I and class II MHC molecules: functional and structural correlates of amino acid polymorphisms

The impact of micropolymorphism in Anpl-UAA on structural stability and peptide presentation

Micropolymorphism significantly shapes the peptide-binding characteristics of major histocompatibility complex class I (MHC-I) molecules, affecting the host's resistance to pathogens, which is particularly pronounced in avian species displaying the "minimal essential MHC" expression pattern. In this study, we compared two duck MHC-I alleles, Anpl-UAA*77 and Anpl-UAA*78, that exhibit markedly different peptide binding properties despite their high sequence homology. Through mutagenesis experiments and crystallographic analysis of complexes with the influenza virus-derived peptide AEAIIVAMV (AEV9), we identified a critical role for the residue at position 62 in regulating hydrogen-bonding interactions between the peptide backbone and the peptide-binding groove. This modulation affects the characteristics of the B pocket and the stability of the loop region between the 310 helix and the α1 helix, leading to significant changes in the structure and stability of the peptide-MHC-I complex (pMHC-I). Moreover, the proportion of different residues at position 62 among Anpl-UAAs may reflect the correlation between pAnpl-UAA stability and duck body temperature. This research not only advances our understanding of the Anpl-UAA structure but also deepens our insight into the impact of MHC-I micropolymorphism on peptide binding.

MHCpLogics: an interactive machine learning-based tool for unsupervised data visualization and cluster analysis of immunopeptidomes

The major histocompatibility complex (MHC) encodes a range of immune response genes, including the human leukocyte antigens (HLAs) in humans. These molecules bind peptide antigens and present them on the cell surface for T cell recognition. The repertoires of peptides presented by HLA molecules are termed immunopeptidomes. The highly polymorphic nature of the genres that encode the HLA molecules confers allotype-specific differences in the sequences of bound ligands. Allotype-specific ligand preferences are often defined by peptide-binding motifs. Individuals express up to six classical class I HLA allotypes, which likely present peptides displaying different binding motifs. Such complex datasets make the deconvolution of immunopeptidomic data into allotype-specific contributions and further dissection of binding-specificities challenging. Herein, we developed MHCpLogics as an interactive machine learning-based tool for mining peptide-binding sequence motifs and visualization of immunopeptidome data across complex datasets. We showcase the functionalities of MHCpLogics by analyzing both in-house and published mono- and multi-allelic immunopeptidomics data. The visualization modalities of MHCpLogics allow users to inspect clustered sequences down to individual peptide components and to examine broader sequence patterns within multiple immunopeptidome datasets. MHCpLogics can deconvolute large immunopeptidome datasets enabling the interrogation of clusters for the segregation of allotype-specific peptide sequence motifs, identification of sub-peptidome motifs, and the exportation of clustered peptide sequence lists. The tool facilitates rapid inspection of immunopeptidomes as a resource for the immunology and vaccine communities. MHCpLogics is a standalone application available via an executable installation at: https://github.com/PurcellLab/MHCpLogics.

Recent selection created distinctive variability patterns on MHC class II loci in three dolphin species from the Mediterranean Sea

The major histocompatibility complex (MHC) includes highly polymorphic genes involved in antigen presentation, which is crucial for adaptive immune response. They represent fitness related genetic markers particularly informative for populations exposed to environmental challenges. Here we analyse the diversity and evolutionary traits of MHC class II DQA and DQB genes in the dolphins Stenella coeruleoalba and Grampus griseus from the Mediterranean Sea. We found substantial nucleotide and functional diversity, as well as strong evidence of balancing selection indicated by allele and supertype frequencies, Tajima's D statistics and dN/dS tests. The Risso's dolphin, considered the least abundant in the region, showed the effect of divergent allele advantage at the nucleotide and functional-peptide levels. An outstanding polymorphism was found in the striped dolphin, particularly intriguing in the DQA gene where the Ewens-Watterson test detected a selection sweep that occurred in recent history. We hypothesize that morbillivirus, which has recurrently invaded Mediterranean populations over the last decades, exerted the detected selective pressure.

Genetic Diversity and Sequence Conservation of Peptide-Binding Regions of MHC Class I Genes in Pig, Cattle, Chimpanzee, and Human

Comparative analyses of MHC gene diversity and evolution across different species could offer valuable insights into the evolution of MHC genes. Intra- and inter-species sequence diversity and conservation of 12 classical major histocompatibility complex (MHC) class I genes from cattle, chimpanzees, pigs, and humans was analyzed using 20 representative allelic groups for each gene. The combined analysis of paralogous loci for each species revealed that intra-locus amino-acid sequence variations in the peptide-binding region (PBR) of MHC I genes did not differ significantly between species, ranging from 8.44% for SLA to 10.75% for BoLA class I genes. In contrast, intraspecies differences in the non-PBRs of these paralogous genes were more pronounced, varying from 4.59% for SLA to 16.89% for HLA. Interestingly, the Shannon diversity index and rate of nonsynonymous substitutions for PBR were significantly higher in SLA and BoLA than those in Patr and HLA. Analysis of peptide-binding pockets across all analyzed MHC class I genes of the four species indicated that pockets A and E showed the lowest and highest diversity, respectively. The estimated divergence times suggest that primate and artiodactyl MHC class I genes diverged 60.41 Mya, and BoLA and SLA genes diverged 35.34 Mya. These results offer new insights into the conservation and diversity of MHC class I genes in various mammalian species.

Diversity and evolution of the MHC class II DRB gene in the Capra sibirica experienced a demographic fluctuation in China

The major histocompatibility complex (MHC) genes are the most polymorphic genes in vertebrates, and their proteins play a critical role in adaptive immunity for defense against a variety of pathogens. MHC diversity was lost in many species after experiencing a decline in size. To understand the variation and evolution of MHC genes in the Siberian ibex, Capra sibirica, which has undergone a population decline, we analyzed the variation of the second exon of MHC class II DRB genes in samples collected from five geographic localities in Xinjiang, China, that belong to three diverged mitochondrial clades. Consequently, we identified a total of 26 putative functional alleles (PFAs) with 260 bp in length from 43 individuals, and found one (for 27 individuals) to three (for 5 individuals) PFAs per individual, indicating the presence of one or two DRB loci per haploid genome. The Casi-DRB1*16 was the most frequently occurring PFA, Casi-DRB1*22 was found in only seven individuals, 14 PFAs occurred once, 7 PFAs twice, implying high frequency of rare PFAs. Interestingly, more than half (15) of the PFAs were specific to clade I, only two and three PFAs were specific to clades II and III, respectively. So, we assume that the polygamy and sexual segregation nature of this species likely contributed to the allelic diversity of DRB genes. Genetic diversity indices showed that PFAs of clade II were lower in nucleotide, amino acid, and supertype diversity compared to those of the other two clades. The pattern of allele sharing and FST values between the three clades was to some extent in agreement with the pattern observed in mitochondrial DNA divergence. In addition, recombination analyses revealed no evidence for significant signatures of recombination events. Alleles shared by clades III and the other two clades diverged 6 million years ago, and systematic neighbor grids showed Trans-species polymorphism. Together with the PAML and MEME analyses, the results indicated that the DRB gene in C. sibirica evolved under balancing and positive selection. However, by comparison, it can be clearly seen that different populations were under different selective pressures. Our results are valuable in understanding the diversity and evolution of the DRB gene in a mountain living C. sibirica and in making decisions on future long-term protection strategies.

Identification and In Silico Characterization of a Conserved Peptide on Influenza Hemagglutinin Protein: A New Potential Antigen for Universal Influenza Vaccine Development

Antigenic changes in surface proteins of the influenza virus may cause the emergence of new variants that necessitate the reformulation of influenza vaccines every year. Universal influenza vaccine that relies on conserved regions can potentially be effective against all strains regardless of any antigenic changes and as a result, it can bring enormous public health impact and economic benefit worldwide. Here, a conserved peptide (HA288-107) on the stalk domain of hemagglutinin glycoprotein is identified among highly pathogenic influenza viruses. Five top-ranked B-cell and twelve T-cell epitopes were recognized by epitope mapping approaches and the corresponding Human Leukocyte Antigen alleles to T-cell epitopes showed high population coverage (>99%) worldwide. Moreover, molecular docking analysis indicated that VLMENERTL and WTYNAELLV epitopes have high binding affinity to the antigen-binding groove of the HLA-A*02:01 and HLA-A*68:02 molecules, respectively. Theoretical physicochemical properties of the peptide were assessed to ensure its thermostability and hydrophilicity. The results suggest that the HA288-107 peptide can be a promising antigen for universal influenza vaccine design. However, in vitro and in vivo analyses are needed to support and evaluate the effectiveness of the peptide as an immunogen for vaccine development.

Elucidation of binding mechanism, affinity, and complex structure between mWT1 tumor-associated antigen peptide and HLA-A*24:02

We have applied our advanced computational and experimental methodologies to investigate the complex structure and binding mechanism of a modified Wilms' Tumor 1 (mWT1) protein epitope to the understudied Asian-dominant allele HLA-A*24:02 (HLA-A24) in aqueous solution. We have applied our developed multicanonical molecular dynamics (McMD)-based dynamic docking method to analyze the binding pathway and mechanism, which we verified by comparing the highest probability structures from simulation with our experimentally solved x-ray crystal structure. Subsequent path sampling MD simulations elucidated the atomic details of the binding process and indicated that first an encounter complex is formed between the N-terminal's positive charge of the 9-residue mWT1 fragment peptide and a cluster of negative residues on the surface of HLA-A24, with the major histocompatibility complex (MHC) molecule preferring a predominantly closed conformation. The peptide first binds to this closed MHC conformation, forming an encounter complex, after which the binding site opens due to increased entropy of the binding site, allowing the peptide to bind to form the native complex structure. Further sequence and structure analyses also suggest that although the peptide loading complex would help with stabilizing the MHC molecule, the binding depends in a large part on the intrinsic affinity between the MHC molecule and the antigen peptide. Finally, our computational tools and analyses can be of great benefit to study the binding mechanism of different MHC types to their antigens, where it could also be useful in the development of higher affinity variant peptides and for personalized medicine.

Combining different bacteria in vaccine formulations enhances the chance for antiviral cross-reactive immunity: a detailed in silico analysis for influenza A virus

Bacteria are well known to provide heterologous immunity against viral infections through various mechanisms including the induction of innate trained immunity and adaptive cross-reactive immunity. Cross-reactive immunity from bacteria to viruses is responsible for long-term protection and yet its role has been downplayed due the difficulty of determining antigen-specific responses. Here, we carried out a systematic evaluation of the potential cross-reactive immunity from selected bacteria known to induce heterologous immunity against various viruses causing recurrent respiratory infections. The bacteria selected in this work were Bacillus Calmette Guerin and those included in the poly-bacterial preparation MV130: Streptococcus pneumoniae, Staphylococcus aureus, Staphylococcus epidermidis, Klebisella pneumoniae, Branhamella catarrhalis and Haemophilus influenzae. The virus included influenza A and B viruses, human rhinovirus A, B and C, respiratory syncytial virus A and B and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Through BLAST searches, we first identified the shared peptidome space (identity ≥ 80%, in at least 8 residues) between bacteria and viruses, and subsequently predicted T and B cell epitopes within shared peptides. Interestingly, the potential epitope spaces shared between bacteria in MV130 and viruses are non-overlapping. Hence, combining diverse bacteria can enhance cross-reactive immunity. We next analyzed in detail the cross-reactive T and B cell epitopes between MV130 and influenza A virus. We found that MV130 contains numerous cross-reactive T cell epitopes with high population protection coverage and potentially neutralizing B cell epitopes recognizing hemagglutinin and matrix protein 2. These results contribute to explain the immune enhancing properties of MV130 observed in the clinic against respiratory viral infections.

Designing of multi-epitope peptide vaccine against Acinetobacter baumannii through combined immunoinformatics and protein interaction-based approaches

Acinetobacter baumannii is one of the major pathogenic ESKAPE bacterium, which is responsible for about more than 722,000 cases in a year, globally. Despite the alarming increase in multidrug resistance, a safe and effective vaccine for Acinetobacter infections is still not available. Hence in the current study, a multiepitope vaccine construct was developed using linear B cell, cytotoxic T cell, and helper T cell epitopes from the antigenic and well-conserved lipopolysaccharide assembly proteins employing systematic immunoinformatics and structural vaccinology strategies. The multi-peptide vaccine was predicted to be highly antigenic, non-allergenic, non-toxic, and cover maximum population coverage worldwide. Further, the vaccine construct was modeled along with adjuvant and peptide linkers and validated to achieve a high-quality three-dimensional structure which was subsequently utilized for cytokine prediction, disulfide engineering, and docking analyses with Toll-like receptor (TLR4). Ramachandran plot showed 98.3% of the residues were located in the most favorable and permitted regions, thereby corroborating the feasibility of the modeled vaccine construct. Molecular dynamics simulation for a 100 ns timeframe further confirmed the stability of the binding vaccine-receptor complex. Finally, in silico cloning and codon adaptation were also performed with the pET28a (+) plasmid vector to determine the efficiency of expression and translation of the vaccine. Immune simulation studies demonstrated that the vaccine could trigger both B and T cell responses and can elicit strong primary, secondary, and tertiary immune responses. The designed multi-peptide subunit vaccine would certainly expedite the experimental approach for the development of a vaccine against A. baumannii infection.

High functional allelic diversity and copy number in both MHC classes in the common buzzard

BACKGROUND

The major histocompatibility complex (MHC), which encodes molecules that recognize various pathogens and parasites and initiates the adaptive immune response in vertebrates, is renowned for its exceptional polymorphism and is a model of adaptive gene evolution. In birds, the number of MHC genes and sequence diversity varies greatly among taxa, believed due to evolutionary history and differential selection pressures. Earlier characterization studies and recent comparative studies suggest that non-passerine species have relatively few MHC gene copies compared to passerines. Additionally, comparative studies that have looked at partial MHC sequences have speculated that non-passerines have opposite patterns of selection on MHC class I (MHC-I) and class II (MHC-II) loci than passerines: namely, greater sequence diversity and signals of selection on MHC-II than MHC-I. However, new sequencing technology is revealing much greater MHC variation than previously expected while also facilitating full sequence variant detection directly from genomic data. Our study aims to take advantage of high-throughput sequencing methods to fully characterize both classes and domains of MHC of a non-passerine bird of prey, the common buzzard (Buteo buteo), to test predictions of MHC variation and differential selection on MHC classes.

RESULTS

Using genetic, genomic, and transcriptomic high-throughput sequencing data, we established common buzzards have at least three loci that produce functional alleles at both MHC classes. In total, we characterize 91 alleles from 113 common buzzard chicks for MHC-I exon 3 and 41 alleles from 125 chicks for MHC-IIB exon 2. Among these alleles, we found greater sequence polymorphism and stronger diversifying selection at MHC-IIB exon 2 than MHC-I exon 3, suggesting differential selection pressures on MHC classes. However, upon further investigation of the entire peptide-binding groove by including genomic data from MHC-I exon 2 and MHC-IIA exon 2, this turned out to be false. MHC-I exon 2 was as polymorphic as MHC-IIB exon 2 and MHC-IIA exon 2 was essentially invariant. Thus, comparisons between MHC-I and MHC-II that included both domains of the peptide-binding groove showed no differences in polymorphism nor diversifying selection between the classes. Nevertheless, selection analysis indicates balancing selection has been acting on common buzzard MHC and phylogenetic inference revealed that trans-species polymorphism is present between common buzzards and species separated for over 33 million years for class I and class II.

CONCLUSIONS

We characterize and confirm the functionality of unexpectedly high copy number and allelic diversity in both MHC classes of a bird of prey. While balancing selection is acting on both classes, there is no evidence of differential selection pressure on MHC classes in common buzzards and this result may hold more generally once more data for understudied MHC exons becomes available.

HLA amino acid Mismatch-Based risk stratification of kidney allograft failure using a novel Machine learning algorithm

OBJECTIVE

While associations between HLA antigen-level mismatches (Ag-MM) and kidney allograft failure are well established, HLA amino acid-level mismatches (AA-MM) have been less explored. Ag-MM fails to consider the substantial variability in the number of MMs at polymorphic amino acid (AA) sites within any given Ag-MM category, which may conceal variable impact on allorecognition. In this study we aim to develop a novel Feature Inclusion Bin Evolver for Risk Stratification (FIBERS) and apply it to automatically discover bins of HLA amino acid mismatches that stratify donor-recipient pairs into low versus high graft survival risk groups.

METHODS

Using data from the Scientific Registry of Transplant Recipients, we applied FIBERS on a multiethnic population of 166,574 kidney transplants between 2000 and 2017. FIBERS was applied (1) across all HLA-A, B, C, DRB1, and DQB1 locus AA-MMs with comparison to 0-ABDR Ag-MM risk stratification, (2) on AA-MMs within each HLA locus individually, and (3) using cross validation to evaluate FIBERS generalizability. The predictive power of graft failure risk stratification was evaluated while adjusting for donor/recipient characteristics and HLA-A, B, C, DRB1, and DQB1 Ag-MMs as covariates.

RESULTS

FIBERS's best-performing bin (on AA-MMs across all loci) added significant predictive power (hazard ratio = 1.10, Bonferroni adj. p < 0.001) in stratifying graft failure risk (where low-risk is defined as zero AA-MMs and high-risk is one or more AA-MMs) even after adjusting for Ag-MMs and donor/recipient covariates. The best bin also categorized more than twice as many patients to the low-risk category, compared to traditional 0-ABDR Ag mismatching (∼24.4% vs ∼ 9.1%). When HLA loci were binned individually, the bin for DRB1 exhibited the strongest risk stratification; relative to zero AA-MM, one or more MMs in the bin yielded HR = 1.11, p < 0.005 in a fully adjusted Cox model. AA-MMs at HLA-DRB1 peptide contact sites contributed most to incremental risk of graft failure. Additionally, FIBERS points to possible risk associated with HLA-DQB1 AA-MMs at positions that determine specificity of peptide anchor residues and HLA-DQ heterodimer stability.

CONCLUSION

FIBERS's performance suggests potential for discovery of HLA immunogenetics-based risk stratification of kidney graft failure that outperforms traditional assessment.

The impact of HLA polymorphism on herpesvirus infection and disease

Human Leukocyte Antigens (HLA) are cell surface molecules, central in coordinating innate and adaptive immune responses, that are targets of strong diversifying natural selection by pathogens. Of these pathogens, human herpesviruses have a uniquely ancient relationship with our species, where coevolution likely has reciprocating impact on HLA and viral genomic diversity. Consistent with this notion, genetic variation at multiple HLA loci is strongly associated with modulating immunity to herpesvirus infection. Here, we synthesize published genetic associations of HLA with herpesvirus infection and disease, both from case/control and genome-wide association studies. We analyze genetic associations across the eight human herpesviruses and identify HLA alleles that are associated with diverse herpesvirus-related phenotypes. We find that whereas most HLA genetic associations are virus- or disease-specific, HLA-A*01 and HLA-A*02 allotypes may be more generally associated with immune susceptibility and control, respectively, across multiple herpesviruses. Connecting genetic association data with functional corroboration, we discuss mechanisms by which diverse HLA and cognate receptor allotypes direct variable immune responses during herpesvirus infection and pathogenesis. Together, this review examines the complexity of HLA-herpesvirus interactions driven by differential T cell and Natural Killer cell immune responses.

Both selection and drift drive the spatial pattern of adaptive genetic variation in a wild mammal

The major histocompatibility complex (MHC) has been intensively studied for the relative effects of different evolutionary forces in recent decades. Pathogen-mediated balancing selection is generally thought to explain the high polymorphism observed in MHC genes, but it is still unclear to what extent MHC diversity is shaped by selection relative to neutral drift. In this study, we genotyped MHC class II DRB genes and 15 neutral microsatellite loci across 26 geographic populations of European badgers (Meles meles) covering most of their geographic range. By comparing variation of microsatellite and diversity of MHC at different levels, we demonstrate that both balancing selection and drift have shaped the evolution of MHC genes. When only MHC allelic identity was investigated, the spatial pattern of MHC variation was similar to that of microsatellites. By contrast, when functional aspects of the MHC diversity (e.g., immunological supertypes) were considered, balancing selection appears to decrease genetic structuring across populations. Our comprehensive sampling and analytical approach enable us to conclude that the likely mechanisms of selection are heterozygote advantage and/or rare-allele advantage. This study is a clear demonstration of how both balancing selection and genetic drift simultaneously affect the evolution of MHC genes in a widely distributed wild mammal.

Whole Exome Sequencing Identified Two Single Nucleotide Polymorphisms of Human Leukocyte Antigen-DRB5 in Familial Sarcoidosis in China

BACKGROUND

Sarcoidosis is a multisystem granulomatous disorder whose etiology is related to genetic and immunological factors. Familial aggregation and ethnic prevalence suggest a genetic predisposition and inherited susceptibility to sarcoidosis.

OBJECTIVE

This study aimed to identify suspected risk loci for familial sarcoidosis patients.

METHODS

We conducted whole exome sequencing on two sarcoidosis patients and five healthy family members in a Chinese family for a case-control study. The two sarcoidosis patients were siblings who showed chronic disease.

RESULTS

The Gene Ontology results showed single nucleotide polymorphisms in three genes, including human leukocyte antigen (HLA)-DRB1, HLA-DRB5, and KIR2DL4, associated with both 'antigen processing and presentation' and 'regulation of immune response.' Sanger sequencing verified two nonsynonymous mutations in HLA-DRB5 (rs696318 and rs115817940) located on 6p21.3 in the major histocompatibility complex (MHC) class II beta 1 region. The structural model simulated on Prot- Param protein analysis by the Expert Protein Analysis System predicted that the hydropathy index changed at two mutation sites (rs696318: p.F96L, -1.844 to -1.656 and rs115817940: p.T106N, -0.322 to -0.633), which indicated the probability of changes in peptide-binding selectivity.

CONCLUSION

Our results indicated that two nonsynonymous mutations of HLA-DRB5 have been identified in two sarcoidosis siblings, while their healthy family members do not have the mutations. The two HLA-DRB5 alleles may influence genetic susceptibility and chronic disease progression through peptide mutations on the MHC class II molecule among the two affected family members.

Vaccine Design: An Introduction

Vaccines are the most successful and cost-effective medical interventions available to fight infectious diseases. They consist of biological preparations that are capable of stimulating the immune system to confer protective immunity against a particular harmful pathogen/agent. Vaccine design and development have evolved through the years. Early vaccines were obtained with little implementation of technology and in the absence of fundamental knowledge, representing a pure feat of human ingenuity. In contrast, modern vaccine development takes advantage of advances in technology and in our enhanced understanding of the immune system and host-pathogen interactions. Moreover, vaccine design has found novel applications beyond the prophylactic arena and there is an increasing interest in designing vaccines to treat human ailments like cancer and chronic inflammatory diseases. In this chapter, we focus on prophylactic vaccines against infectious diseases, providing an overview on immunology principles underlying immunization and on how vaccines work and are designed.

Evaluation of Genetic Diversity and Parasite-Mediated Selection of MHC Class I Genes in Emberiza godlewskii (Passeriformes: Emberizidae)

The major histocompatibility complex (MHC) is a multi-copy immune gene family in vertebrates. Its genes are highly variable and code for antigen-presenting molecules. Characterization of MHC genes in different species and investigating the mechanisms that shape MHC diversity is an important goal in understanding the evolution of biological diversity. Here we developed a next-generation sequencing (NGS) protocol to genotype the MHC class I genes of 326 Godlewski’s buntings (Emberiza godlewskii) sampled in the Western mountain area of Beijing from 2014 to 2016. A total of 184 functional alleles were identified, including both non-classical and classical alleles, clustering into nine supertypes. Compared with other passerine birds, the number of MHC class I alleles per individual in Godlewski’s buntings is high (mean 16.1 ± 3.3, median 16). In addition, we demonstrated signatures of historical and contemporary selection on MHC genes. Reflecting historical selection, ten amino acid sites in the antigen-binding domain showed signatures of balancing selection, eight of which exhibit high amino acid polymorphism. In terms of contemporary selection, we found that specific MHC supertypes were nominally associated with the infection of two malaria parasite lineages. These findings indicate the action of historical and possibly also contemporary balancing selection and suggest negative frequency-dependent or fluctuating selection as possible selection mechanisms.

Molecular Characterization of MHC Class I Alpha 1 and 2 Domains in Asian Seabass (Lates calcarifer)

The Asian seabass is of importance both as a farmed and wild animal. With the emergence of infectious diseases, there is a need to understand and characterize the immune system. In humans, the highly polymorphic MHC class I (MHC-I) molecules play an important role in antigen presentation for the adaptive immune system. In the present study, we characterized a single MHC-I gene in Asian seabass (Lates calcarifer) by amplifying and sequencing the MHC-I alpha 1 and alpha 2 domains, followed by multi-sequence alignment analyses. The results indicated that the Asian seabass MHC-I α1 and α2 domain sequences showed an overall similarity within Asian seabass and retained the majority of the conserved binding residues of human leukocyte antigen-A2 (HLA-A2). Phylogenetic tree analysis revealed that the sequences belonged to the U lineage. Mapping the conserved binding residue positions on human HLA-A2 and grass carp crystal structure showed a high degree of similarity. In conclusion, the availability of MHC-I α1 and α2 sequences enhances the quality of MHC class I genetic information in Asian seabass, providing new tools to analyze fish immune responses to pathogen infections, and will be applicable in the study of the phylogeny and the evolution of antigen-specific receptors.

Diversity of the MHC class II DRB gene in the wolverine (Carnivora: Mustelidae: Gulo gulo) in Finland

The wolverine (Gulo gulo) in Finland has undergone significant population declines in the past. Since major histocompatibility complex (MHC) genes encode proteins involved in pathogen recognition, the diversity of these genes provides insights into the immunological fitness of regional populations. We sequenced 862 amplicons (242 bp) of MHC class II DRB exon 2 from 32 Finnish wolverines and identified 11 functional alleles and three pseudogenes. A molecular phylogenetic analysis indicated trans-species polymorphism, and PAML and MEME analyses indicated positive selection, suggesting that the Finnish wolverine DRB genes have evolved under balancing and positive selection. In contrast to DRB gene analyses in other species, allele frequencies in the Finnish wolverines clearly indicated the existence of two regional subpopulations, congruent with previous studies based on neutral genetic markers. In the Finnish wolverine, rapid population declines in the past have promoted genetic drift, resulting in a lower genetic diversity of DRB loci, including fewer alleles and positively selected sites, than other mustelid species analyzed previously. Our data suggest that the MHC region in the Finnish wolverine population was likely affected by a recent bottleneck.

Identification of the novel HLA-C*08:243 allele in a Spanish bone marrow donor

HLA-C*08:243 differs from C*08:51 by a single nucleotide substitution in codon 156 (G>T). This article is protected by copyright. All rights reserved.

Resilience of Spike-Specific Immunity Induced by COVID-19 Vaccines against SARS-CoV-2 Variants

The outbreak of SARS-CoV-2 leading to the declaration of the COVID-19 global pandemic has led to the urgent development and deployment of several COVID-19 vaccines. Many of these new vaccines, including those based on mRNA and adenoviruses, are aimed to generate neutralizing antibodies against the spike glycoprotein, which is known to bind to the receptor angiotensin converting enzyme 2 (ACE2) in host cells via the receptor-binding domain (RBD). Antibodies binding to this domain can block the interaction with the receptor and prevent viral entry into the cells. Additionally, these vaccines can also induce spike-specific T cells which could contribute to providing protection against the virus. However, the emergence of new SARS-CoV-2 variants can impair the immunity generated by COVID-19 vaccines if mutations occur in cognate epitopes, precluding immune recognition. Here, we evaluated the chance of five SARS-CoV-2 variants of concern (VOCs), Alpha, Beta, Gamma, Delta and Omicron, to escape spike-specific immunity induced by vaccines. To that end, we examined the impact of the SARS-CoV-2 variant mutations on residues located on experimentally verified spike-specific epitopes, deposited at the Immune Epitope Database, that are targeted by neutralizing antibodies or recognized by T cells. We found about 300 of such B cell epitopes, which were largely overlapping, and could be grouped into 54 B cell epitope clusters sharing ≥ 7 residues. Most of the B cell epitope clusters map in the RBD domain (39 out of 54) and 20%, 50%, 37%, 44% and 57% of the total are mutated in SARS-CoV-2 Alpha, Beta, Gamma, Delta and Omicron variants, respectively. We also found 234 experimentally verified CD8 and CD4 T cell epitopes that were distributed evenly throughout the spike protein. Interestingly, in each SARS-CoV-2 VOC, over 87% and 79% of CD8 and CD4 T cell epitopes, respectively, are not mutated. These observations suggest that SARS-CoV-2 VOCs—particularly the Omicron variant—may be prone to escape spike-specific antibody immunity, but not cellular immunity, elicited by COVID-19 vaccines.

Selection and demography drive range-wide patterns of MHC-DRB variation in mule deer

BACKGROUND

Standing genetic variation is important especially in immune response-related genes because of threats to wild populations like the emergence of novel pathogens. Genetic variation at the major histocompatibility complex (MHC), which is crucial in activating the adaptive immune response, is influenced by both natural selection and historical population demography, and their relative roles can be difficult to disentangle. To provide insight into the influences of natural selection and demography on MHC evolution in large populations, we analyzed geographic patterns of variation at the MHC class II DRB exon 2 locus in mule deer (Odocoileus hemionus) using sequence data collected across their entire broad range.

RESULTS

We identified 31 new MHC-DRB alleles which were phylogenetically similar to other cervid MHC alleles, and one allele that was shared with white-tailed deer (Odocoileus virginianus). We found evidence for selection on the MHC including high dN/dS ratios, positive neutrality tests, deviations from Hardy-Weinberg Equilibrium (HWE) and a stronger pattern of isolation-by-distance (IBD) than expected under neutrality. Historical demography also shaped variation at the MHC, as indicated by similar spatial patterns of variation between MHC and microsatellite loci and a lack of association between genetic variation at either locus type and environmental variables.

CONCLUSIONS

Our results show that both natural selection and historical demography are important drivers in the evolution of the MHC in mule deer and work together to shape functional variation and the evolution of the adaptive immune response in large, well-connected populations.

Divergent and non-parallel evolution of MHC IIB in the Neotropical Midas cichlid species complex

Background

Ecological diversification is the result of divergent natural selection by contrasting habitat characteristics that favours the evolution of distinct phenotypes. This process can happen in sympatry and in allopatry. Habitat-specific parasite communities have the potential to drive diversification among host populations by imposing selective pressures on their host's immune system. In particular, the hyperdiverse genes of the major histocompatibility complex (MHC) are implicated in parasite-mediated host divergence. Here, we studied the extent of divergence at MHC, and discuss how it may have contributed to the Nicaraguan Midas cichlid species complex diversification, one of the most convincing examples of rapid sympatric parallel speciation.

Results

We genotyped the MHC IIB for individuals from six sympatric Midas cichlid assemblages, each containing species that have adapted to exploit similar habitats. We recovered large allelic and functional diversity within the species complex. While most alleles were rare, functional groups of alleles (supertypes) were common, suggesting that they are key to survival and that they were maintained during colonization and subsequent radiations. We identified lake-specific and habitat-specific signatures for both allelic and functional diversity, but no clear pattern of parallel divergence among ecomorphologically similar phenotypes.

Conclusions

Colonization and demographic effects of the fish could have contributed to MHC evolution in the Midas cichlid in conjunction with habitat-specific selective pressures, such as parasites associated to alternative preys or environmental features. Additional ecological data will help evaluating the role of host–parasite interactions in the Midas cichlid radiations and aid in elucidating the potential role of non-parallel features differentiating crater lake species assemblages.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12862-022-01997-9.

Repertoire analyses reveal T cell antigen receptor sequence features that influence T cell fate

T cells acquire a regulatory phenotype when their T cell receptors (TCRs) experience an intermediate-to-high affinity interaction with a self-peptide presented via the major histocompatibility complex (MHC). Using TCRβ sequences from flow-sorted human cells, we identified TCR features that promote regulatory T cell (T_reg) fate. From these results, we developed a scoring system to quantify TCR-intrinsic regulatory potential (TiRP). When applied to the tumor microenvironment, TiRP scoring helped to explain why only some T cell clones maintained the T_conv phenotype through expansion. To elucidate drivers of these predictive TCR features, we then examined the two elements of the T_reg TCR ligand separately: the self-peptide, and the human MHC II molecule. These analyses revealed that hydrophobicity in the third complementarity determining region (CDR3β) of the TCR promotes reactivity to self-peptides, while TCR variable gene (TRBV gene) usage shapes the TCR’s general propensity for human MHC II-restricted activation.

Reconstructing Macroevolutionary Patterns in Avian MHC Architecture With Genomic Data

The Major Histocompatibility Complex (MHC) is a hyper-polymorphic genomic region, which forms a part of the vertebrate adaptive immune system and is crucial for intra- and extra-cellular pathogen recognition (MHC-I and MHC-IIA/B, respectively). Although recent advancements in high-throughput sequencing methods sparked research on the MHC in non-model species, the evolutionary history of MHC gene structure is still poorly understood in birds. Here, to explore macroevolutionary patterns in the avian MHC architecture, we retrieved contigs with antigen-presenting MHC and MHC-related genes from available genomes based on third-generation sequencing. We identified: 1) an ancestral avian MHC architecture with compact size and tight linkage between MHC-I, MHC-IIA/IIB and MHC-related genes; 2) three major patterns of MHC-IIA/IIB unit organization in different avian lineages; and 3) lineage-specific gene translocation events (e.g., separation of the antigen-processing TAP genes from the MHC-I region in passerines), and 4) the presence of a single MHC-IIA gene copy in most taxa, showing evidence of strong purifying selection (low dN/dS ratio and low number of positively selected sites). Our study reveals long-term macroevolutionary patterns in the avian MHC architecture and provides the first evidence of important transitions in the genomic arrangement of the MHC region over the last 100 million years of bird evolution.

Machine Learning Techniques for the Prediction of B-Cell and T-Cell Epitopes as Potential Vaccine Targets with a Specific Focus on SARS-CoV-2 Pathogen: A Review

The only part of an antigen (a protein molecule found on the surface of a pathogen) that is composed of epitopes specific to T and B cells is recognized by the human immune system (HIS). Identification of epitopes is considered critical for designing an epitope-based peptide vaccine (EBPV). Although there are a number of vaccine types, EBPVs have received less attention thus far. It is important to mention that EBPVs have a great deal of untapped potential for boosting vaccination safety—they are less expensive and take a short time to produce. Thus, in order to quickly contain global pandemics such as the ongoing outbreak of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), as well as epidemics and endemics, EBPVs are considered promising vaccine types. The high mutation rate of SARS-CoV-2 has posed a great challenge to public health worldwide because either the composition of existing vaccines has to be changed or a new vaccine has to be developed to protect against its different variants. In such scenarios, time being the critical factor, EBPVs can be a promising alternative. To design an effective and viable EBPV against different strains of a pathogen, it is important to identify the putative T- and B-cell epitopes. Using the wet-lab experimental approach to identify these epitopes is time-consuming and costly because the experimental screening of a vast number of potential epitope candidates is required. Fortunately, various available machine learning (ML)-based prediction methods have reduced the burden related to the epitope mapping process by decreasing the potential epitope candidate list for experimental trials. Moreover, these methods are also cost-effective, scalable, and fast. This paper presents a systematic review of various state-of-the-art and relevant ML-based methods and tools for predicting T- and B-cell epitopes. Special emphasis is placed on highlighting and analyzing various models for predicting epitopes of SARS-CoV-2, the causative agent of COVID-19. Based on the various methods and tools discussed, future research directions for epitope prediction are presented.

Machine learning approaches for the genomic prediction of rheumatoid arthritis and systemic lupus erythematosus

BACKGROUND

Rheumatoid arthritis (RA) and systemic lupus erythematous (SLE) are autoimmune rheumatic diseases that share a complex genetic background and common clinical features. This study's purpose was to construct machine learning (ML) models for the genomic prediction of RA and SLE.

METHODS

A total of 2,094 patients with RA and 2,190 patients with SLE were enrolled from the Taichung Veterans General Hospital cohort of the Taiwan Precision Medicine Initiative. Genome-wide single nucleotide polymorphism (SNP) data were obtained using Taiwan Biobank version 2 array. The ML methods used were logistic regression (LR), random forest (RF), support vector machine (SVM), gradient tree boosting (GTB), and extreme gradient boosting (XGB). SHapley Additive exPlanation (SHAP) values were calculated to clarify the contribution of each SNPs. Human leukocyte antigen (HLA) imputation was performed using the HLA Genotype Imputation with Attribute Bagging package.

RESULTS

Compared with LR (area under the curve [AUC] = 0.8247), the RF approach (AUC = 0.9844), SVM (AUC = 0.9828), GTB (AUC = 0.9932), and XGB (AUC = 0.9919) exhibited significantly better prediction performance. The top 20 genes by feature importance and SHAP values included HLA class II alleles. We found that imputed HLA-DQA1*05:01, DQB1*0201 and DRB1*0301 were associated with SLE; HLA-DQA1*03:03, DQB1*0401, DRB1*0405 were more frequently observed in patients with RA.

CONCLUSIONS

We established ML methods for genomic prediction of RA and SLE. Genetic variations at HLA-DQA1, HLA-DQB1, and HLA-DRB1 were crucial for differentiating RA from SLE. Future studies are required to verify our results and explore their mechanistic explanation.

BCEPS: A Web Server to Predict Linear B Cell Epitopes with Enhanced Immunogenicity and Cross-Reactivity

Prediction of linear B cell epitopes is of interest for the production of antigen-specific antibodies and the design of peptide-based vaccines. Here, we present BCEPS, a web server for predicting linear B cell epitopes tailored to select epitopes that are immunogenic and capable of inducing cross-reactive antibodies with native antigens. BCEPS implements various machine learning models trained on a dataset including 555 linearized conformational B cell epitopes that were mined from antibody–antigen protein structures. The best performing model, based on a support vector machine, reached an accuracy of 75.38% ± 5.02. In an independent dataset consisting of B cell epitopes retrieved from the Immune Epitope Database (IEDB), this model achieved an accuracy of 67.05%. In BCEPS, predicted epitopes can be ranked according to properties such as flexibility, accessibility and hydrophilicity, and with regard to immunogenicity, as judged by their predicted presentation by MHC II molecules. BCEPS also detects if predicted epitopes are located in ectodomains of membrane proteins and if they possess N-glycosylation sites hindering antibody recognition. Finally, we exemplified the use of BCEPS in the SARS-CoV-2 Spike protein, showing that it can identify B cell epitopes targeted by neutralizing antibodies.

Inside the pocket: Critical elements of HLA-mediated susceptibility to cervical precancerous lesions

Human papillomavirus (HPV) infection is a necessary cause for cervical cancer (CC), but it also depends on genetic factors, such as HLA polymorphism. However, few reports addressed the role of amino acids residues at the HLA peptide-binding cleft in HPV-related cervical disease. Therefore, we aimed to investigate the association between HLA-B, HLA-C, and HLA-DRB1 polymorphism and amino acid residues composing the pockets of the peptide-binding cleft of the respective polypeptide chains with cervical intraepithelial neoplasia (CIN II/III). HLA typing was performed by PCR-SSOP in 184 women with CIN II/III and 174 controls from South Brazil. Associations were estimated by multivariate logistic regression. FDR test was performed to correct the p-value for multiple comparisons. HLA-DRB1*13:01 was associated with protection against CIN II/III, while HLA-C*03:04 was associated with susceptibility. The amino acid residues isoleucine, tyrosine, and leucine at positions 95, 116, and 163 of HLA-C, respectively, were associated with CIN II/III susceptibility. In contrast, serine at positions 11 and 13 of HLA-DRB1 was associated with protection against the disease. Our results confirm previously reported associations between HLA and cervical diseases caused by HPV and suggest a role for amino acid residues at different positions of HLA-C and HLA-DRB1 in CIN II/III. This finding may be further explored to better understand the genetic risk and the influence of immune response to CC development.

Characterization of Conserved and Promiscuous Human Rhinovirus CD4 T Cell Epitopes

Human rhinovirus (RV) is the most common cause of upper respiratory infections and exacerbations of asthma. In this work, we selected 14 peptides (6 from RV A and 8 from RV C) encompassing potential CD4 T cell epitopes. Peptides were selected for being highly conserved in RV A and C serotypes and predicted to bind to multiple human leukocyte antigen class II (HLA II) molecules. We found positive T cell recall responses by interferon gamma (IFNγ)-ELISPOT assays to eight peptides, validating seven of them (three from RV A and four from RV C) as CD4 T cell epitopes through intracellular cytokine staining assays. Additionally, we verified their promiscuous binding to multiple HLA II molecules by quantitative binding assays. According to their experimental HLA II binding profile, the combination of all these seven epitopes could be recognized by >95% of the world population. We actually determined IFNγ responses to a pool encompassing these CD4 T cell epitopes by intracellular cytokine staining, finding positive responses in 29 out of 30 donors. The CD4 T cell epitopes identified in this study could be key to monitor RV infections and to develop peptide-based vaccines against most RV A and C serotypes.

Major histocompatibility complex class II DR and DQ evolution and variation in wild capuchin monkey species (Cebinae)

The major histocompatibility complex (MHC) is an important gene complex contributing to adaptive immunity. Studies of platyrrhine MHC have focused on identifying experimental models of immune system function in the equivalent Human Leukocyte Antigen (HLA). These genes have thus been explored primarily in captive platyrrhine individuals from research colonies. However, investigations of standing MHC variation and evolution in wild populations are essential to understanding its role in immunity, sociality and ecology. Capuchins are a promising model group exhibiting the greatest habitat diversity, widest diet breadth and arguably the most social complexity among platyrrhines, together likely resulting in varied immunological challenges. We use high-throughput sequencing to characterize polymorphism in four Class II DR and DQ exons for the first time in seven capuchin species. We find evidence for at least three copies for DQ genes and at least five for DRB, with possible additional unrecovered diversity. Our data also reveal common genotypes that are inherited across our most widely sampled population, Cebus imitator in Sector Santa Rosa, Costa Rica. Notably, phylogenetic analyses reveal that platyrrhine DQA sequences form a monophyletic group to the exclusion of all Catarrhini sequences examined. This result is inconsistent with the trans-species hypothesis for MHC evolution across infraorders in Primates and provides further evidence for the independent origin of current MHC genetic diversity in Platyrrhini. Identical allele sharing across cebid species, and more rarely genera, however, does underscore the complexity of MHC gene evolution and the need for more comprehensive assessments of allelic diversity and genome structure.

HLA class II immunopeptidomics reveals that co-inherited HLA-allotypes within an extended haplotype can improve proteome coverage for immunosurveillance

Human leucocyte antigen (HLA) class II molecules in humans are encoded by three different loci, HLA-DR, -DQ, and -DP. These molecules share approximately 70% sequence similarity and all present peptide ligands to circulating T cells. While the peptide repertoires of numerous HLA-DR, -DQ, and -DP allotypes have been examined, there have been few reports on the combined repertoire of these co-inherited molecules expressed in a single cell as an extended HLA haplotype. Here we describe the endogenous peptide repertoire of a human B lymphoblastoid cell line (C1R) expressing the class II haplotype HLA-DR12/DQ7/DP4. We have identified 71350 unique naturally processed peptides presented collectively by HLA-DR12, HLA-DQ7, or HLA-DP4. The resulting "haplodome" is complemented by the cellular proteome defined by standard LC-MS/MS approaches. This large dataset has shed light on properties of these class II ligands especially the preference for membrane and extracellular source proteins. Our data also provides insights into the co-evolution of these conserved haplotypes of closely linked and co-inherited HLA molecules; which together increase sequence coverage of cellular proteins for immune surveillance with minimal overlap between each co-inherited HLA-class II allomorph.

A Highly Complex, MHC-Linked, 350 Million-Year-Old Shark Nonclassical Class I Lineage

Cartilaginous fish, or Chondrichthyes, are the oldest extant vertebrates to possess the MHC and the Ig superfamily-based Ag receptors, the defining genes of the gnathostome adaptive immune system. In this work, we have identified a novel MHC lineage, UEA, a complex multigene nonclassical class I family found in sharks (division Selachii) but not detected in chimaeras (subclass Holocephali) or rays (division Batoidea). This new lineage is distantly related to the previously reported nonclassical class I lineage UCA, which appears to be present only in dogfish sharks (order Squaliformes). UEA lacks conservation of the nine invariant residues in the peptide (ligand)-binding regions (PBR) that bind to the N and C termini of bound peptide in most vertebrate classical class I proteins, which are replaced by relatively hydrophobic residues compared with the classical UAA. In fact, UEA and UCA proteins have the most hydrophobic-predicted PBR of all identified chondrichthyan class I molecules. UEA genes detected in the whale shark and bamboo shark genome projects are MHC linked. Consistent with UEA comprising a very large gene family, we detected weak expression in different tissues of the nurse shark via Northern blotting and RNA sequencing. UEA genes fall into three sublineages with unique characteristics in the PBR. UEA shares structural and genetic features with certain nonclassical class I genes in other vertebrates, such as the highly complex XNC nonclassical class I genes in Xenopus, and we anticipate that each shark gene, or at least each sublineage, will have a unique function, perhaps in bacterial defense.

Characterization of novel HLA class I alleles: HLA-A*02:984, -B*18:205, -B*57:142N, -C*02:204, and -C*16:185

Five new HLA class I alleles were characterized by next-generation sequencing.

Encapsulation of Anguillicola crassus reduces the abundance of adult parasite stages in the European eel (Anguilla anguilla)

Encapsulation of the parasitic nematode Anguillicola crassus Kuwahara, Niimi & Hagaki is commonly observed in its native host, the Japanese eel (Anguilla japonica Temminck & Schlegel). Encapsulation has also been described in a novel host, the European eel (A. anguilla L.), and there is evidence that encapsulation frequency has increased since the introduction of A. crassus. We examined whether encapsulation of A. crassus provides an advantage to its novel host in Lake Müggelsee, NE Germany. We provide the first evidence that encapsulation was associated with reduced abundance of adult A. crassus. This pattern was consistent in samples taken 3 months apart. There was no influence of infection on the expression of the two metabolic genes studied, but the number of capsules was negatively correlated with the expression of two mhc II genes of the adaptive immune response, suggesting a reduced activation. Interestingly, eels that encapsulated A. crassus had higher abundances of two native parasites compared with non-encapsulating eels. We propose that the response of A. anguilla to infection by A. crassus may interfere with its reaction to other co-occurring parasites.

Population-Predicted MHC Class II Epitope Presentation of SARS-CoV-2 Structural Proteins Correlates to the Case Fatality Rates of COVID-19 in Different Countries

We observed substantial differences in predicted Major Histocompatibility Complex II (MHCII) epitope presentation of SARS-CoV-2 proteins for different populations but only minor differences in predicted MHCI epitope presentation. A comparison of this predicted epitope MHC-coverage revealed for the early phase of infection spread (till day 15 after reaching 128 observed infection cases) highly significant negative correlations with the case fatality rate. Specifically, this was observed in different populations for MHC class II presentation of the viral spike protein (p-value: 0.0733 for linear regression), the envelope protein (p-value: 0.023), and the membrane protein (p-value: 0.00053), indicating that the high case fatality rates of COVID-19 observed in some countries seem to be related with poor MHC class II presentation and hence weak adaptive immune response against these viral envelope proteins. Our results highlight the general importance of the SARS-CoV-2 structural proteins in immunological control in early infection spread looking at a global census in various countries and taking case fatality rate into account. Other factors such as health system and control measures become more important after the early spread. Our study should encourage further studies on MHCII alleles as potential risk factors in COVID-19 including assessment of local populations and specific allele distributions.

Peptidomes and Structures Illustrate Two Distinguishing Mechanisms of Alternating the Peptide Plasticity Caused by Swine MHC Class I Micropolymorphism

The micropolymorphism of major histocompatibility complex class I (MHC-I) can greatly alter the plasticity of peptide presentation, but elucidating the underlying mechanism remains a challenge. Here we investigated the impact of the micropolymorphism on peptide presentation of swine MHC-I (termed swine leukocyte antigen class I, SLA-I) molecules via immunopeptidomes that were determined by our newly developed random peptide library combined with the mass spectrometry (MS) de novo sequencing method (termed RPLD–MS) and the corresponding crystal structures. The immunopeptidomes of SLA-1*04:01, SLA-1*13:01, and their mutants showed that mutations of residues 156 and 99 could expand and narrow the ranges of peptides presented by SLA-I molecules, respectively. R156A mutation of SLA-1*04:01 altered the charge properties and enlarged the volume size of pocket D, which eliminated the harsh restriction to accommodate the third (P3) anchor residue of the peptide and expanded the peptide binding scope. Compared with 99^Tyr of SLA-1*0401, 99^Phe of SLA-1*13:01 could not form a conservative hydrogen bond with the backbone of the P3 residues, leading to fewer changes in the pocket properties but a significant decrease in quantitative of immunopeptidomes. This absent force could be compensated by the salt bridge formed by P1-E and 170^Arg. These data illustrate two distinguishing manners that show how micropolymorphism alters the peptide-binding plasticity of SLA-I alleles, verifying the sensitivity and accuracy of the RPLD-MS method for determining the peptide binding characteristics of MHC-I in vitro and helping to more accurately predict and identify MHC-I restricted epitopes.

A Proteome-Wide Immunoinformatics Tool to Accelerate T-Cell Epitope Discovery and Vaccine Design in the Context of Emerging Infectious Diseases: An Ethnicity-Oriented Approach

Emerging infectious diseases (EIDs) caused by viruses are increasing in frequency, causing a high disease burden and mortality world-wide. The COVID-19 pandemic caused by the novel SARS-like coronavirus (SARS-CoV-2) underscores the need to innovate and accelerate the development of effective vaccination strategies against EIDs. Human leukocyte antigen (HLA) molecules play a central role in the immune system by determining the peptide repertoire displayed to the T-cell compartment. Genetic polymorphisms of the HLA system thus confer a strong variability in vaccine-induced immune responses and may complicate the selection of vaccine candidates, because the distribution and frequencies of HLA alleles are highly variable among different ethnic groups. Herein, we build on the emerging paradigm of rational epitope-based vaccine design, by describing an immunoinformatics tool (Predivac-3.0) for proteome-wide T-cell epitope discovery that accounts for ethnic-level variations in immune responsiveness. Predivac-3.0 implements both CD8+ and CD4+ T-cell epitope predictions based on HLA allele frequencies retrieved from the Allele Frequency Net Database. The tool was thoroughly assessed, proving comparable performances (AUC ~0.9) against four state-of-the-art pan-specific immunoinformatics methods capable of population-level analysis (NetMHCPan-4.0, Pickpocket, PSSMHCPan and SMM), as well as a strong accuracy on proteome-wide T-cell epitope predictions for HIV-specific immune responses in the Japanese population. The utility of the method was investigated for the COVID-19 pandemic, by performing in silico T-cell epitope mapping of the SARS-CoV-2 spike glycoprotein according to the ethnic context of the countries where the ChAdOx1 vaccine is currently initiating phase III clinical trials. Potentially immunodominant CD8+ and CD4+ T-cell epitopes and population coverages were predicted for each population (the Epitope Discovery mode), along with optimized sets of broadly recognized (promiscuous) T-cell epitopes maximizing coverage in the target populations (the Epitope Optimization mode). Population-specific epitope-rich regions (T-cell epitope clusters) were further predicted in protein antigens based on combined criteria of epitope density and population coverage. Overall, we conclude that Predivac-3.0 holds potential to contribute in the understanding of ethnic-level variations of vaccine-induced immune responsiveness and to guide the development of epitope-based next-generation vaccines against emerging pathogens, whose geographic distributions and populations in need of vaccinations are often well-defined for regional epidemics.

Discordance Between the Predicted Versus the Actually Recognized CD8+ T Cell Epitopes of HCMV pp65 Antigen and Aleatory Epitope Dominance

CD8+ T cell immune monitoring aims at measuring the size and functions of antigen-specific CD8+ T cell populations, thereby providing insights into cell-mediated immunity operational in a test subject. The selection of peptides for ex vivo CD8+ T cell detection is critical because within a complex antigen exists a multitude of potential epitopes that can be presented by HLA class I molecules. Further complicating this task, there is HLA class I polygenism and polymorphism which predisposes CD8+ T cell responses towards individualized epitope recognition profiles. In this study, we compare the actual CD8+ T cell recognition of a well-characterized model antigen, human cytomegalovirus (HCMV) pp65 protein, with its anticipated epitope coverage. Due to the abundance of experimentally defined HLA-A*02:01-restricted pp65 epitopes, and because in silico epitope predictions are most advanced for HLA-A*02:01, we elected to focus on subjects expressing this allele. In each test subject, every possible CD8+ T cell epitope was systematically covered testing 553 individual peptides that walk the sequence of pp65 in steps of single amino acids. Highly individualized CD8+ T cell response profiles with aleatory epitope recognition patterns were observed. No correlation was found between epitopes' ranking on the prediction scale and their actual immune dominance. Collectively, these data suggest that accurate CD8+ T cell immune monitoring may necessitate reliance on agnostic mega peptide pools, or brute force mapping, rather than electing individual peptides as representative epitopes for tetramer and other multimer labeling of surface antigen receptors.

CERI, CEFX, and CPI: Largely Improved Positive Controls for Testing Antigen-Specific T Cell Function in PBMC Compared to CEF

Monitoring antigen-specific T cell immunity relies on functional tests that require T cells and antigen presenting cells to be uncompromised. Drawing of blood, its storage and shipment from the clinical site to the test laboratory, and the subsequent isolation, cryopreservation and thawing of peripheral blood mononuclear cells (PBMCs) before the actual test is performed can introduce numerous variables that may jeopardize the results. Therefore, no T cell test is valid without assessing the functional fitness of the PBMC being utilized. This can only be accomplished through the inclusion of positive controls that actually evaluate the performance of the antigen-specific T cell and antigen presenting cell (APC) compartments. For Caucasians, CEF peptides have been commonly used to this extent. Moreover, CEF peptides only measure CD8 cell functionality. We introduce here universal CD8+ T cell positive controls without any racial bias, as well as positive controls for the CD4+ T cell and APC compartments. In summary, we offer new tools and strategies for the assessment of PBMC functional fitness required for reliable T cell immune monitoring.

Human rhinovirus-specific CD8 T cell responses target conserved and unusual epitopes

Human Rhinovirus (HRV) is a major cause of common cold, bronchiolitis, and exacerbations of chronic pulmonary diseases such as asthma. CD8 T cell responses likely play an important role in the control of HRV infection but, surprisingly, HRV‐specific CD8 T cell epitopes remain yet to be identified. Here, we approached the discovery and characterization of conserved HRV‐specific CD8 T cell epitopes from species A (HRV A) and C (HRV C), the most frequent subtypes in the clinics of various pulmonary diseases. We found IFNγ‐ELISPOT positive responses to 23 conserved HRV‐specific peptides on peripheral blood mononuclear cells (PBMCs) from 14 HLA I typed subjects. Peptide‐specific IFNγ production by CD8 T cells and binding to the relevant HLA I were confirmed for six HRV A‐specific and three HRV C‐specific CD8 T cell epitopes. In addition, we validated A*02:01‐restricted epitopes by DimerX staining and found out that these peptides mediated cytotoxicity. All these A*02:01‐restricted epitopes were 9‐mers but, interestingly, we also identified and validated an unusually long 16‐mer epitope peptide restricted by A*02:01, HRVC_1791‐1806 (GLEPLDLNTSAGFPYV). HRV‐specific CD8 T cell epitopes describe here are expected to elicit CD8 T cell responses in up to 87% of the population and could be key for developing an HRV vaccine.

Pharmacogenomics for immunotherapy and immune-related cardiotoxicity

Immune checkpoint blockade (ICB) has become a standard of care in a subset of solid tumors. Although cancer survivorship has extended, rates of durable response of ICB remain poor; furthermore, cardiac adverse effects are emerging, which impact several mechanical aspects of the heart. Cardio-oncology programs implement a clinical assessment to curtail cardiovascular disease progression but are limited to the current clinical parameters used in cardiology. Pharmacogenomics provides the potential to unveil heritable and somatic genetic variations for guiding precision immunotherapy treatment to reduce the risk of immune-related cardiotoxicity. A better understanding of pharmacogenomics will optimize the current treatment selection and dosing of immunotherapy. Here, we summarize the recent pharmacogenomics studies in immunotherapy responsiveness and its related cardiotoxicity and highlight how patient genetics and epigenetics can facilitate researchers and clinicians in designing new approaches for precision immunotherapy. We highlight and discuss how single-cell technologies, human-induced pluripotent stem cells and systems pharmacogenomics accelerate future studies of precision cardio-oncology.

Genomics-based immuno-oncology: bridging the gap between immunology and tumor biology

The first hypotheses about how the immune system affects cancers were proposed in the early 20th century. These early concepts about cancer immunosurveillance were further developed in the decades that followed, but a detailed understanding of cancer immunity remained elusive. It was only recently, through the advent of high-throughput technologies, that scientists gained the ability to profile tumors with a resolution that allowed for granular assessment of both tumor cells and the tumor microenvironment. The advent of immune checkpoint inhibitors (ICIs), which have proven to be effective cancer therapies in many malignancies, has spawned great interest in developing biomarkers for efficacy, an endeavor that highlighted the value of dissecting tumor immunity using large-scale methods. Response to ICI therapy has been shown to be a highly complex process, where the dynamics of tumor and immune cells is key to success. The need to understand the biologic mechanisms at the tumor-immune interface has given rise to the field of cancer immunogenomics, a discipline that aims to bridge the gap between cancer genomics and classical immunology. We provide a broad overview of this emerging branch of translational science, summarizing common platforms used and recent discoveries in the field, which are having direct clinical implications. Our discussion will be centered around the genetic foundations governing tumor immunity and molecular determinants associated with clinical benefit from ICI therapy. We emphasize the importance of molecular diversity as a driver of anti-tumor immunity and discuss how these factors can be probed using genomic approaches.

Association of HLA-A, -B, -C, -DRB1 and -DQB1 alleles at amino acid level in individuals with schizophrenia: A study from South India

BACKGROUND

Schizophrenia, a chronic severe psychiatric illness of unknown aetiology, has been shown to be associated with HLA alleles but at varied degree in different population. The present study has focussed on analysing the frequency of HLA class I and class II alleles in persons with schizophrenia from South India.

METHODS

Ninety seven individuals with schizophrenia and 103 age- and gender-matched controls were typed for HLA- A, B, C, DRB1 and DQB1 loci by next-generation sequencing in Illumina MiniSeq using MIA FORA NGS FLEX HLA typing kit.

RESULTS

The results showed that HLA-A*01:01:01, B*37:01:01 and C*01:02:01 were positively associated with schizophrenia while HLA-B*35:03:01 and DRB1*04:03:01 were negatively associated. Gender-specific associations revealed that DRB1*10:01:01 and DQB1*05:01:01 were positively associated while DQB1*03:02:01 was negatively associated with female subjects with schizophrenia. A*24:02:01~B*37:01:01~C*06:02:01~DRB1*10:01:01~DQB1*05:01:01 is the predominant haplotype in schizophrenia population when compared to healthy controls. Amino acid association in susceptible and protective alleles has shown that the presence of peptide in the peptide-binding groves of mature HLA-A protein (K, M, V, R and V at 44th, 67th, 150th, 156th and 158th position), HLA-B protein (D and S at 77th and 99th position) and HLA-C protein (M at 99th position) confer susceptibility to the disease, only in the absence of E (Glutamic acid) at 74th position in mature HLA-DRB1 protein. Interaction of amino acids in protective alleles namely B*35:01:01 and DRB1*04:03:01 has revealed that aspartic acid at 114th (D) position in mature HLA-B protein and glutamic acid (E) at 74th position of mature HLA-DRB1 protein have a combined effect in protecting against the disease.

CONCLUSION

The study has revealed the HLA association with schizophrenia in south Indian population. The amino acid interaction with the disease needs to be confirmed in a larger population.

The combination of artificial intelligence and systems biology for intelligent vaccine design

INTRODUCTION

A new body of evidence depicts the applications of artificial intelligence and systems biology in vaccine design and development. The combination of both approaches shall revolutionize healthcare, accelerating clinical trial processes and reducing the costs and time involved in drug research and development.

AREAS COVERED

This review explores the basics of artificial intelligence and systems biology approaches in the vaccine development pipeline. The topics include a detailed description of epitope prediction tools for designing epitope-based vaccines and agent-based models for immune system response prediction, along with a focus on their potentiality to facilitate clinical trial phases.

EXPERT OPINION

Artificial intelligence and systems biology offer the opportunity to avoid the inefficiencies and failures that arise in the classical vaccine development pipeline. One promising solution is the combination of both methodologies in a multiscale perspective through an accurate pipeline. We are entering an 'in silico era' in which scientific partnerships, including a more and more increasing creation of an 'ecosystem' of collaboration and multidisciplinary approach, are relevant for addressing the long and risky road of vaccine discovery and development. In this context, regulatory guidance should be developed to qualify the in silico trials as evidence for intelligent vaccine development.

HLA Evolutionary Divergence as a Prognostic Marker for AML Patients Undergoing Allogeneic Stem Cell Transplantation

The diversity of human leukocyte antigens (HLAs) enables the presentation of immense repertoires of peptides, including tumor-associated antigens (TAAs). As a surrogate for immunopeptidome diversity, the HLA evolutionary divergence (HED) between individual HLA alleles might directly define the ability to present TAAs, a prerequisite for graft-versus-leukemia effects. We therefore analyzed the impact of HED on survival within a cohort of 171 acute myeloid leukemia (AML) patients after matched donor allogeneic hematopoietic stem cell transplantation (HSCT). Low HED (<25th percentile) of HLA class I (HED^{class I}) or HLA-DR antigens (HED^DR) was a strong determinant for adverse overall survival after allogeneic HSCT (OS), with a hazard ratio for death of 1.9 (95% CI 1.2–3.2) and 2.1 (95% CI 1.3–3.4), respectively. Defining a cutoff value for the combined HED^total (HED^{class I} and HED^DR), the respective 5 year OS was 29.7% and 64.9% in patients with low and high HED^total (p < 0.001), respectively. Furthermore, the risk of relapse was significantly higher in patients with low HED^total (hazard ratio (HR) 2.2, 95% CI 1.3–3.6) and event-free survival (EFS) was significantly reduced (5 year EFS 25.7% versus 54.4%, p < 0.001). We here introduce HED, a fundamental metric of immunopeptidome diversity, as a novel prognostic factor for AML patients undergoing allogeneic HSCT.

SynGAP isoforms differentially regulate synaptic plasticity and dendritic development

SynGAP is a synaptic Ras GTPase-activating protein (GAP) with four C-terminal splice variants: α1, α2, β, and γ. Although studies have implicated SYNGAP1 in several cognitive disorders, it is not clear which SynGAP isoforms contribute to disease. Here, we demonstrate that SynGAP isoforms exhibit unique spatiotemporal expression patterns and play distinct roles in neuronal and synaptic development in mouse neurons. SynGAP-α1, which undergoes liquid-liquid phase separation with PSD-95, is highly enriched in synapses and is required for LTP. In contrast, SynGAP-β, which does not bind PSD-95 PDZ domains, is less synaptically targeted and promotes dendritic arborization. A mutation in SynGAP-α1 that disrupts phase separation and synaptic targeting abolishes its ability to regulate plasticity and instead causes it to drive dendritic development like SynGAP-β. These results demonstrate that distinct intrinsic biochemical properties of SynGAP isoforms determine their function, and individual isoforms may differentially contribute to the pathogenesis of SYNGAP1-related cognitive disorders.