In vivo detection of antigen-specific CD8+ T cells by immuno-positron emission tomography.

The immune system's ability to recognize peptides on major histocompatibility molecules contributes to the eradication of cancers and pathogens. Tracking these responses in vivo could help evaluate the efficacy of immune interventions and improve mechanistic understanding of immune responses. For this purpose, we employ synTacs, which are dimeric major histocompatibility molecule scaffolds of defined composition. SynTacs, when labeled with positron-emitting isotopes, can noninvasively image antigen-specific CD8+ T cells in vivo. Using radiolabeled synTacs loaded with the appropriate peptides, we imaged human papillomavirus-specific CD8+ T cells by positron emission tomography in mice bearing human papillomavirus-positive tumors, as well as influenza A virus-specific CD8+ T cells in the lungs of influenza A virus-infected mice. It is thus possible to visualize antigen-specific CD8+ T-cell populations in vivo, which may serve prognostic and diagnostic roles.

Possible role of HLA class-I genotype in SARS-CoV-2 infection and progression: A pilot study in a cohort of Covid-19 Spanish patients.

Human Leukocyte Antigen (HLA) includes a large set of genes with important actions in immune response against viral infection. Numerous studies have revealed the existence of significant associations between certain HLA alleles and the susceptibility and prognosis of different infectious diseases. In this pilot study we analyse the binding affinity between 66 class I HLA alleles and SARS-CoV-2 viral peptides, and its association with the severity of the disease. A total of 45 Spanish patients with mild, moderate and severe SARS-CoV-2 infection were typed for HLA class I; after that, we analysed if an in silico model of HLA I-viral peptide binding affinity and classical HLA supertypes could be correlated to the severity of the disease. Our results suggest that patients with mild disease present Class I HLA molecules with a higher theoretical capacity for binding SARS-Cov-2 peptides and showed greater heterozygosity when comparing them with moderate and severe groups. In this regard, identifying HLA-SARS-CoV-2 peptides binding differences between individuals would help to clarify the heterogeneity of clinical responses to the disease and will also be useful to guide a personalized treatment according to its particular risk.

Targeting the coding sequence: opposing roles in regulating classical and non-classical MHC class I molecules by miR-16 and miR-744.

BACKGROUND: To control gene expression, microRNAs (miRNAs) are of key importance and their deregulation is associated with the development and progression of various cancer types. In this context, a discordant messenger RNA/protein expression pointing to extensive post-transcriptional regulation of major histocompatibility complex (MHC) class I molecules was already shown. However, only a very limited number of miRNAs targeting these molecules have yet been identified. Despite an increasing evidence of coding sequence (CDS)-located miRNA binding sites, there exists so far, no detailed study of the interaction of miRNAs with the CDS of MHC class I molecules. METHODS: Using an MS2-tethering approach in combination with small RNA sequencing, a number of putative miRNAs binding to the CDS of human leukocyte antigen (HLA)-G were identified. These candidate miRNAs were extensively screened for their effects in the HLA-G-positive JEG3 cell line. Due to the high sequence similarity between HLA-G and classical MHC class I molecules, the impact of HLA-G candidate miRNAs on HLA class I surface expression was also analyzed. The Cancer Genome Atlas data were used to correlate candidate miRNAs and HLA class I gene expression. RESULTS: Transfection of candidate miRNAs revealed that miR-744 significantly downregulates HLA-G protein levels. In contrast, overexpression of the candidate miRNAs miR-15, miR-16, and miR-424 sharing the same seed sequence resulted in an unexpected upregulation of HLA-G. Comparable results were obtained for classical MHC class I members after transfection of miRNA mimics into HEK293T cells. Analyses of The Cancer Genome Atlas data sets for miRNA and MHC class I expression further validated the results. CONCLUSIONS: Our data expand the knowledge about MHC class I regulation and showed for the first time an miRNA-dependent control of MHC class I antigens mediated by the CDS. CDS-located miRNA binding sites could improve the general use of miRNA-based therapeutic approaches as these sites are highly independent of structural variations (e.g. mutations) in the gene body. Surprisingly, miR-16 family members promoted MHC class I expression potentially in a gene activation-like mechanism.

arcasHLA: high-resolution HLA typing from RNAseq.

MOTIVATION: The human leukocyte antigen (HLA) locus plays a critical role in tissue compatibility and regulates the host response to many diseases, including cancers and autoimmune di3orders. Recent improvements in the quality and accessibility of next-generation sequencing have made HLA typing from standard short-read data practical. However, this task remains challenging given the high level of polymorphism and homology between HLA genes. HLA typing from RNA sequencing is further complicated by post-transcriptional modifications and bias due to amplification. RESULTS: Here, we present arcasHLA: a fast and accurate in silico tool that infers HLA genotypes from RNA-sequencing data. Our tool outperforms established tools on the gold-standard benchmark dataset for HLA typing in terms of both accuracy and speed, with an accuracy rate of 100% at two-field resolution for Class I genes, and over 99.7% for Class II. Furthermore, we evaluate the performance of our tool on a new biological dataset of 447 single-end total RNA samples from nasopharyngeal swabs, and establish the applicability of arcasHLA in metatranscriptome studies. AVAILABILITY AND IMPLEMENTATION: arcasHLA is available at https://github.com/RabadanLab/arcasHLA. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

ELM-MHC: An Improved MHC Identification Method with Extreme Learning Machine Algorithm.

The major histocompatibility complex (MHC) is a term for all gene groups of a major histocompatibility antigen. It binds to peptide chains derived from pathogens and displays pathogens on the cell surface to facilitate T-cell recognition and perform a series of immune functions. MHC molecules are critical in transplantation, autoimmunity, infection, and tumor immunotherapy. Combining machine learning algorithms and making full use of bioinformatics analysis technology, more accurate recognition of MHC is an important task. The paper proposed a new MHC recognition method compared with traditional biological methods and used the built classifier to classify and identify MHC I and MHC II. The classifier used the SVMProt 188D, bag-of-ngrams (BonG), and information theory (IT) mixed feature representation methods and used the extreme learning machine (ELM), which selects lin-kernel as the activation function and used 10-fold cross-validation and the independent test set validation to verify the accuracy of the constructed classifier and simultaneously identify the MHC and identify the MHC I and MHC II, respectively. Through the 10-fold cross-validation, the proposed algorithm obtained 91.66% accuracy when identifying MHC and 94.442% accuracy when identifying MHC categories. Furthermore, an online identification Web site named ELM-MHC was constructed with the following URL: http://server.malab.cn/ELM-MHC/ .

Diversity and characterisation of polymorphic 3' untranslated region haplotypes of MICA and MICB genes.

MICA and MICB genes encode ligands that interact with the natural killer (NK) cell activating receptor, NKG2D. These ligands display a highly polymorphic allelic repertoire, although the true functional significance of this polymorphism remains elusive. We previously reported additional polymorphism in the 5' untranslated region (UTR) proximal promoter region of these genes by sequencing international histocompatibility workshop (IHW) cell line DNA promoter and coding regions. The present study extends this analysis by further characterising the 3'UTR region of the same IHW reference panel to achieve a more complete understanding of MICA and MICB haplotype diversity and possible functional relevance. We found 17 extended MICA haplotypes encompassing the coding region and 3'UTR, including four novel haplotypes identified in IHW cell line DNA. This increased to 21 when also considering the 5'UTR proximal promoter region. Analysis of the MICB 3'UTR revealed two novel sequences in cell lines KLO and WIN designated MICB-UTR8 and UTR9, respectively. A total of 11 MICB haplotypes were identified in this study and five were unique. The present study, characterising MICA/B 3'UTR polymorphism utilising IHW reference cell lines, could be useful for future studies investigating the role of microRNA in post-transcriptional repression of gene expression and for immunotherapy strategies to combat cancer progression.

Combining one-step Sanger sequencing with phasing probe hybridization for HLA class I typing yields rapid, G-group resolution predicting 99% of unique full length protein sequences.

BACKGROUND: Sanger-based DNA sequencing of exons 2+3 of HLA class I alleles from a heterozygote frequently results in two or more alternative genotypes. This study was undertaken to reduce the time and effort required to produce a single high resolution HLA genotype. MATERIALS AND METHODS: Samples were typed in parallel by Sanger sequencing and oligonucleotide probe hybridization. This workflow, together with optimization of analysis software, was tested and refined during the typing of over 42,000 volunteers for an unrelated hematopoietic progenitor cell donor registry. Next generation DNA sequencing (NGS) was applied to over 1000 of these samples to identify the alleles present within the G group designations. RESULTS: Single genotypes at G level resolution were obtained for over 95% of the loci without additional assays. The vast majority of alleles identified (>99%) were the primary allele giving the G groups their name. Only 0.7% of the alleles identified encoded protein variants that were not detected by a focus on the antigen recognition domain (ARD)-encoding exons. CONCLUSION: Our combined method routinely provides biologically relevant typing resolution at the level of the ARD. It can be applied to both single samples or to large volume typing supporting either bone marrow or solid organ transplantation using technologies currently available in many HLA laboratories.

Comparison of exome-based HLA class I genotyping tools: identification of platform-specific genotyping errors.

Accurate human leukocyte antigen (HLA) genotyping is critical in studies involving the immune system. Several algorithms to estimate HLA genotypes from whole-exome data were developed. We compared the accuracy of seven algorithms, including Optitype, Polysolver and PHLAT, as well as investigated patterns and possible causes of miscalls using 12 clinical samples and 961 individuals from the 1000 Genomes Project. Optitype showed the highest accuracy of 97.2% for HLA class I alleles at the second field resolution, followed by 94.0% in Polysolver and 85.6% in PHLAT. In Optitype, 34 (21.1%) of 161 miscalls were across different serological types, and common miscalls were HLA-A*26:01 to HLA-A*25:01, HLA-B*45:01 to HLA-B*44:15 and HLA-C*08:02 to HLA-C*05:01 with error rates of 4.1%, 10.0% and 4.1%, respectively. In Polysolver, 193 (55.9%) of 345 miscalls occurred across different serological alleles, and a specific pattern of genotyping error from HLA-A*25:01 to HLA-A*26:01 was observed in 93.3% of HLA-A*25:01 carriers, due to dropping of HLA-A*25:01 sequence reads during the extraction process of HLA reads. In PHLAT, 147 (59.8%) of 246 miscalls in HLA-A were due to erroneous assignment of multiple alleles to either HLA-A*01:22 or HLA-A*01:81. These results suggest that careful considerations needed to be taken when using exome-based HLA class I genotyping data and applying these results in clinical settings.

Alternative haplotypes of antigen processing genes in zebrafish diverged early in vertebrate evolution.

Antigen processing and presentation genes found within the MHC are among the most highly polymorphic genes of vertebrate genomes, providing populations with diverse immune responses to a wide array of pathogens. Here, we describe transcriptome, exome, and whole-genome sequencing of clonal zebrafish, uncovering the most extensive diversity within the antigen processing and presentation genes of any species yet examined. Our CG2 clonal zebrafish assembly provides genomic context within a remarkably divergent haplotype of the core MHC region on chromosome 19 for six expressed genes not found in the zebrafish reference genome: mhc1uga, proteasome-ß 9b (psmb9b), psmb8f, and previously unknown genes psmb13b, tap2d, and tap2e We identify ancient lineages for Psmb13 within a proteasome branch previously thought to be monomorphic and provide evidence of substantial lineage diversity within each of three major trifurcations of catalytic-type proteasome subunits in vertebrates: Psmb5/Psmb8/Psmb11, Psmb6/Psmb9/Psmb12, and Psmb7/Psmb10/Psmb13. Strikingly, nearby tap2 and MHC class I genes also retain ancient sequence lineages, indicating that alternative lineages may have been preserved throughout the entire MHC pathway since early diversification of the adaptive immune system ∼500 Mya. Furthermore, polymorphisms within the three MHC pathway steps (antigen cleavage, transport, and presentation) are each predicted to alter peptide specificity. Lastly, comparative analysis shows that antigen processing gene diversity is far more extensive than previously realized (with ancient coelacanth psmb8 lineages, shark psmb13, and tap2t and psmb10 outside the teleost MHC), implying distinct immune functions and conserved roles in shaping MHC pathway evolution throughout vertebrates.

Deciphering complex patterns of class-I HLA-peptide cross-reactivity via hierarchical grouping.

T-cell responses in humans are initiated by the binding of a peptide antigen to a human leukocyte antigen (HLA) molecule. The peptide-HLA complex then recruits an appropriate T cell, leading to cell-mediated immunity. More than 2000 HLA class-I alleles are known in humans, and they vary only in their peptide-binding grooves. The polymorphism they exhibit enables them to bind a wide range of peptide antigens from diverse sources. HLA molecules and peptides present a complex molecular recognition pattern, as many peptides bind to a given allele and a given peptide can be recognized by many alleles. A powerful grouping scheme that not only provides an insightful classification, but is also capable of dissecting the physicochemical basis of recognition specificity is necessary to address this complexity. We present a hierarchical classification of 2010 class-I alleles by using a systematic divisive clustering method. All-pair distances of alleles were obtained by comparing binding pockets in the structural models. By varying the similarity thresholds, a multilevel classification was obtained, with 7 supergroups, each further subclassifying to yield 72 groups. An independent clustering performed based only on similarities in their epitope pools correlated highly with pocket-based clustering. Physicochemical feature combinations that best explain the basis of clustering are identified. Mutual information calculated for the set of peptide ligands enables identification of binding site residues contributing to peptide specificity. The grouping of HLA molecules achieved here will be useful for rational vaccine design, understanding disease susceptibilities and predicting risk of organ transplants.

Identification of novel epitopes from human papillomavirus type 18 E7 that can sensitize PBMCs of multiple HLA class I against human cervical cancer.

BACKGROUND: To identify the novel epitopes from the human papillomavirus type 18 E7 which can sensitize PBMCs of four different major HLA class I A allele. METHODS: Twenty-four synthetic overlapping 15-amino acid peptides were screened by measuring the frequency of CD8+ cytotoxic T lymphocytes (CTLs)-producing interferon-γ (IFN-γ) by using flow cytometry and ELISpot assays and selected peptides were validated for cytolytic activity by using the 51Cr release assay. Truncated peptides in the selected epitopes were tested to determine the important residues using ELISpot and 51Cr release assay. RESULTS: Among 24 peptides, E781-95DDLRAFQQLFLNTLS (#21) and E789-103LFLNTLSFVCPWCAS (#23) induced significantly higher Th 1 response including IFN-γ production and in vitro cytotoxicity of PBMCs of four different HLA-A alleles against cervical cancer cells than that of other peptides and the negative control (no peptide sensitization). In E781-95 (#21), amino acid position 81, 82 (N-terminus) and 92, 94, 95 (C-terminus) for HLA-A*02:02 and 24:02, and 81, 82 (N-terminus) and 92, 95 (C-terminus) for HLA-A*11:01 and 33:03 were important to elicit Th1 response of PBMCS. In E789-103 (#23), residue 100 and103 (C-terminus) were important to elicit the CD8+ CTL response in HLA-A*02:01, 11:01 and 33:03 and 100, 101, and 103 (C-terminus) were important to elicit the CD8+ CTL response in HLA-A*24:02. CONCLUSIONS: E781-95 (#21) and E789-103 (#23) were identified as novel epitopes from HPV18 E7 which could sensitized PBMCs of four different HLA class I (HLA-A*02:01, 24:02, 11:01 and 33:03). These epitopes could be useful for immune monitoring and immunotherapy for HPV 18+ cervical cancer.

Classification of human leukocyte antigen (HLA) supertypes.

Identification of new antigenic peptides, derived from infectious agents or cancer cells, which bind to human leukocyte antigen (HLA) class I and II molecules, is of importance for the development of new effective vaccines capable of activating the cellular arm of the immune response. However, the barrier to the development of peptide-based vaccines with maximum population coverage is that the restricting HLA genes are extremely polymorphic resulting in a vast diversity of peptide-binding HLA specificities and a low population coverage for any given peptide-HLA specificity. One way to reduce this complexity is to group thousands of different HLA molecules into several so-called HLA supertypes: a classification that refers to a group of HLA alleles with largely overlapping peptide binding specificities. In this chapter, we focus on the state-of-the-art classification of HLA supertypes including HLA-I supertypes and HLA-II supertypes and their application in development of peptide-based vaccines.

Improving the prediction of HLA class I-binding peptides using a supertype-based method.

The computational prediction of peptides that bind to major histocompatibility complex (MHC) molecules has practical importance for the development of epitope-based vaccines. The performance of the prediction methods depends on the verified peptides. However, the available peptide datasets of most alleles contain significant biases. An investigation to the effect of the peptides in the training dataset on the performance of the generated model indicated that there was a discrepancy between the classification of binders from biological data and classification of binders from super-motif-sharing peptides, which was induced by the non-motif-containing peptides. Most human MHC (called HLA) class I molecules could be assigned to supertypes based on their overlapping peptide-binding specificities, therefore, we proposed a supertype-based method for the modeling of the HLA class I-peptide binding: candidates of peptides binding to alleles in a given supertypes were screened using the super-motifs, and then the peptides binding to specific allele in the supertype were predicted by the model trained on the super-motif-sharing peptides. The efficacy of this supertype-based method was examined in two matrix-based methods and one machine learning method for 20 alleles in HLA supertypes A1, A2, A3, A24, B44 and B7. Evaluations on several benchmark datasets indicated that the supertype-based method achieved remarkable success in improving the prediction of HLA-binding peptides.

Allelic and haplotypic diversity of 5'promoter region of the MICA gene.

In this study, the 5'promoter region of MHC class I chain-related gene A (MICA) was investigated in 104 healthy, unrelated Han individuals recruited from northern China, using PCR-sequencing method. Twelve variable sites were detected, which were in very strong linkage disequilibrium with each other. Twelve different MICA 5'promoter haplotypes were identified, among which Promoter-7 predominated (0.5529). Twenty-six extended haplotypes incorporating MICA 5'promoter and MICA exons 2-5 were observed in this population, 9 of which were in significant linkage disequilibrium (LD). Phylogenetic analysis of 5'promoter refined MICA sub-lineage structure previously constructed according to MICA coding and 3'untranslated regions. Ewens-Watterson homozygosity statistics at MICA 5'promoter region were consistent with neutral expectations. None of the five variable sites detected within the minimal promoter of MICA gene was located in the putative binding sites for transcription factor. Our study provided for the first time the sequence information about 5'promoter of MICA gene at a human population level. The data will facilitate the understanding of regulation of MICA gene expression, which represents a promising pathway for immune intervention against cancer, autoimmune disorders and infections.

Canine DLA-79 gene: an improved typing method, identification of new alleles and its role in graft rejection and graft-versus-host disease.

Developing a preclinical canine model that predicts outcomes for hematopoietic cell transplantation in humans requires a model that mimics the degree of matching between human donor and recipient major histocompatibility complex (MHC) genes. The polymorphic class I and class II genes in mammals are typically located in a single chromosome as part of the MHC complex. However, a divergent class I gene in dogs, designated dog leukocyte antigen-79 (DLA-79), is located on chromosome 18 while other MHC genes are on chromosome 12. This gene is not taken into account while DLA matching for transplantation. Though divergent, this gene shares significant similarity in sequence and exon-intron architecture with other class I genes, and is transcribed. Little is known about the polymorphisms of DLA-79 and their potential role in transplantation. This study was aimed at exploring the reason for high rate of rejection seen in DLA-matched dogs given reduced intensity conditioning, in particular, the possibility that DLA-79 allele mismatches may be the cause. We found that about 82% of 407 dogs typed were homozygous for a single, reference allele. Owing to the high prevalence of a single allele, 87 of the 108 dogs (∼80%) transplanted were matched for DLA-79 with their donor. In conclusion, we have developed an efficient method to type alleles of a divergent MHC gene in dogs and identified two new alleles. We did not find any statistical correlation between DLA-79 allele disparity and graft rejection or graft-versus-host disease, among our transplant dogs.

Microarrays for high-throughput genotyping of MICA alleles using allele-specific primer extension.

The role of major histocompatibility complex (MHC) class I chain-related gene A (MICA), a ligand of NKG2D, has been defined in human diseases by its allele associations with various autoimmune diseases, hematopoietic stem cell transplantation (HSCT) and cancer. This study describes a practical system to develop MICA genotyping by allele-specific primer extension (ASPE) on microarrays. From the results of 20 control primers, strict and reliable cut-off values of more than 30,000 mean fluorescence intensity (MFI) as positive and less than 3000 MFI as negative, were applied to select high-quality specific extension primers. Among 55 allele-specific primers, 44 primers could be initially selected as optimal primer. Through adjusting the length, six primers were improved. The other failed five primers were corrected by refractory modification. MICA genotypes by ASPE on microarrays showed the same results as those by nucleotide sequencing. On the basis of these results, ASPE on microarrays may provide high-throughput genotyping for MICA alleles for population studies, disease-gene associations and HSCT.

Immunogenetics of the NKG2D ligand gene family.

NKG2D ligands (NKG2DLs) are a group of major histocompatibility complex (MHC) class I-like molecules, the expression of which is induced by cellular stresses such as infection, tumorigenesis, heat shock, tissue damage, and DNA damage. They act as a molecular danger signal alerting the immune system for infected or neoplastic cells. Mammals have two families of NKG2DL genes: the MHC-encoded MIC gene family and the ULBP gene family encoded outside the MHC region in most mammals. Rodents such as mice and rats lack the MIC family of ligands. Interestingly, some mammals have NKG2DL-like molecules named MILL that are phylogenetically related to MIC, but do not function as NKG2DLs. In this paper, we review our current knowledge of the MIC, ULBP, and MILL gene families in representative mammalian species and discuss the origin and evolution of the NKG2DL gene family.

MICA polymorphism: biology and importance in immunity and disease.

The human major histocompatibility complex class I chain-related gene A (MICA) is one of the genes in the HLA class I region of chromosome 6. Unlike HLA classical class I gene products, MICA does not present any antigen but acts as a ligand for several immune cells including natural killer (NK) cells bearing NKG2D receptors. MICA is the member of the non-classical class I family that displays the greatest degree of polymorphism. MICA alleles can be divided into two large groups with the polymorphisms found in alpha3 domains. This division could be explained by a possible polyphyletic origin that is in line with recent findings from evolutionary, population and functional studies of this gene. MICA polymorphisms are associated with a number of diseases related to NK activity, such as viral infection, cancer and allograft rejection or graft-versus-host disease (GVHD). The mechanisms underlying these associations include NK cell-mediated cytotoxicity and MICA shedding to produce immunosuppressive soluble MICA particles. The MICA-induced humoral response has attracted interest recently because of its possible role in graft rejection in solid organ transplantation. Here, we discuss the genetics and biology of the MICA gene and its products, and their importance in disease.

The varicellovirus-encoded TAP inhibitor UL49.5 regulates the presentation of CTL epitopes by Qa-1b1.

Impairment of MHC class I Ag processing is a commonly observed mechanism that allows viruses and tumors to escape immune destruction by CTL. The peptide transporter TAP that is responsible for the delivery of MHC class I-binding peptides into the endoplasmic reticulum is a pivotal target of viral-immune evasion molecules, and expression of this transporter is frequently lost in advanced cancers. We recently described a novel population of CTL that intriguingly exhibits reactivity against such tumor-immune escape variants and that recognizes self-peptides emerging at the cell surface due to defects in the processing machinery. Investigations of this new type of CTL epitopes are hampered by the lack of an efficient inhibitor for peptide transport in mouse cells. In this article, we demonstrate that the varicellovirus protein UL49.5, in contrast to ICP47 and US6, strongly impairs the activity of the mouse transporter and mediates degradation of mouse TAP1 and TAP2. Inhibition of TAP was witnessed by a strong reduction of surface MHC class I display and a decrease in recognition of conventional tumor-specific CTL. Analysis of CTL reactivity through the nonclassical molecule Qa-1(b) revealed that the presentation of the predominant leader peptide was inhibited. Interestingly, expression of UL49.5 in processing competent tumor cells induced the presentation of the new category of peptides. Our data show that the varicellovirus UL49.5 protein is a universal TAP inhibitor that can be exploited for preclinical studies on CTL-based immune intervention.