Human leukocyte Antigen-DM polymorphisms in autoimmune diseases

HLA-DM and HLA-DO interplay for the peptide editing of HLA class II in healthy tissues and leukemia

HLA class II antigen presentation is modulated by the activity of the peptide editor HLA-DM and its antagonist HLA-DO, with their interplay controlling the peptide repertoires presented by normal and malignant cells. The role of these molecules in allogeneic hematopoietic cell transplantation (alloHCT) is poorly investigated. Balanced expression of HLA-DM and HLA-DO can influence the presentation of leukemia-associated antigens and peptides targeted by alloreactive T cells, therefore affecting both anti-leukemia immunity and the potential onset of Graft versus Host Disease. We leveraged on a large collection of bulk and single cell RNA sequencing data, available at different repositories, to comprehensively review the level and distribution of HLA-DM and HLA-DO in different cell types and tissues of the human body. The resulting expression atlas will help future investigations aiming to dissect the dual role of HLA class II peptide editing in alloHCT, and their potential impact on its clinical outcome.

DeepHLAPred: a deep learning-based method for non-classical HLA binder prediction

Human leukocyte antigen (HLA) is closely involved in regulating the human immune system. Despite great advance in detecting classical HLA Class I binders, there are few methods or toolkits for recognizing non-classical HLA Class I binders. To fill in this gap, we have developed a deep learning-based tool called DeepHLAPred. The DeepHLAPred used electron-ion interaction pseudo potential, integer numerical mapping and accumulated amino acid frequency as initial representation of non-classical HLA binder sequence. The deep learning module was used to further refine high-level representations. The deep learning module comprised two parallel convolutional neural networks, each followed by maximum pooling layer, dropout layer, and bi-directional long short-term memory network. The experimental results showed that the DeepHLAPred reached the state-of-the-art performanceson the cross-validation test and the independent test. The extensive test demonstrated the rationality of the DeepHLAPred. We further analyzed sequence pattern of non-classical HLA class I binders by information entropy. The information entropy of non-classical HLA binder sequence implied sequence pattern to a certain extent. In addition, we have developed a user-friendly webserver for convenient use, which is available at http://www.biolscience.cn/DeepHLApred/ . The tool and the analysis is helpful to detect non-classical HLA Class I binder. The source code and data is available at https://github.com/tangxingyu0/DeepHLApred .

MHC-II dynamics are maintained in HLA-DR allotypes to ensure catalyzed peptide exchange

Presentation of antigenic peptides by major histocompatibility complex class II (MHC-II) proteins determines T helper cell reactivity. The MHC-II genetic locus displays a large degree of allelic polymorphism influencing the peptide repertoire presented by the resulting MHC-II protein allotypes. During antigen processing, the human leukocyte antigen (HLA) molecule HLA-DM (DM) encounters these distinct allotypes and catalyzes exchange of the placeholder peptide CLIP by exploiting dynamic features of MHC-II. Here, we investigate 12 highly abundant CLIP-bound HLA-DRB1 allotypes and correlate dynamics to catalysis by DM. Despite large differences in thermodynamic stability, peptide exchange rates fall into a target range that maintains DM responsiveness. A DM-susceptible conformation is conserved in MHC-II molecules, and allosteric coupling between polymorphic sites affects dynamic states that influence DM catalysis. As exemplified for rheumatoid arthritis, we postulate that intrinsic dynamic features of peptide-MHC-II complexes contribute to the association of individual MHC-II allotypes with autoimmune disease.

Identification of novel prognostic targets in glioblastoma using bioinformatics analysis

Background

Glioblastoma (GBM) is the most malignant grade of glioma. Highly aggressive characteristics of GBM and poor prognosis cause GBM-related deaths. The potential prognostic biomarkers remain to be demonstrated. This research builds up predictive gene targets of expression alterations in GBM utilizing bioinformatics analysis.

Methods and results

The microarray datasets (GSE15824 and GSE16011) associated with GBM were obtained from Gene Expression Omnibus (GEO) database to identify the differentially expressed genes (DEGs) between GBM and non-tumor tissues. In total, 719 DEGs were obtained and subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) for function enrichment analysis. Furthermore, we constructed protein–protein Interaction (PPI) network among DEGs utilizing Search Tool for the Retrieval of Interacting Genes (STRING) online tool and Cytoscape software. The DEGs of degree > 10 was selected as hub genes, including 73 upregulated genes and 21 downregulated genes. Moreover, MCODE application in Cytoscape software was employed to identify three key modules involved in GBM development and prognosis. Additionally, we used the Gene expression profiling and interactive analyses (GEPIA) online tool to further confirm four genes involving in poor prognosis of GBM patients, including interferon-gamma-inducible protein 30 (IFI30), major histocompatibility complex class II-DM alpha (HLA-DMA), Prolyl 4-hydroxylase beta polypeptide (P4HB) and reticulocalbin-1 (RCN1). Furthermore, the correlation analysis indicated that the expression of IFI30, an acknowledged biomarker in glioma, was positively correlated with HLA-DMA, P4HB and RCN1. RCN1 expression was positively correlated with P4HB and HLA-DMA. Moreover, qRT-PCR and immunohistochemistry analysis further validated the upregulation of four prognostic markers in GBM tissues.

Conclusions

Analysis of multiple datasets combined with global network information and experimental verification presents a successful approach to uncover the risk hub genes and prognostic markers of GBM. Our study identified four risk- and prognostic-related gene signatures, including IFI30, HLA-DMA, P4HB and RCN1. This gene sets contribute a new perspective to improve the diagnostic, prognostic, and therapeutic outcomes of GBM.

Sortase-Mediated Multi-Fragment Assemblies by Ligation Site Switching

Sortase-mediated ligation (SML) is a powerful tool of protein chemistry allowing the ligation of peptides containing LPxTG sorting motifs and N-terminal glycine nucleophiles. The installation of a sorting motif into the product prohibits the assembly of multiple fragments by SML. Here we report multi-fragment SML based on switchable sortase substrates. Substitution of the Leu residue by disulfide-containing Cys(StBu) results in active sorting motifs, which are inactivatable by reduction. In combination with a photo-protected N-Gly nucleophile, multi-fragment SML is enabled by repetitive cycles of SML and ligation site switching. The feasibility of this approach was demonstrated by a proof-of-concept four-fragment ligation, the assembly of peptide probes for bivalent chromatin binding proteins and oligomerization of peptide antigens. Biochemical and immuno-assays demonstrated functionality of these probes rendering them promising tools for immunology and chromatin biochemistry.

HLA class II peptide-binding-region analysis reveals funneling of polymorphism in action

BACKGROUND

HLA-class II proteins hold important roles in key physiological processes. The purpose of this study was to compile all class II alleles reported in human population and investigate patterns in pocket variants and their combinations, focusing on the peptide-binding region (PBR).

METHODS

For this purpose, all protein sequences of DPA1, DQA1, DPB1, DQB1 and DRB1 were selected and filtered, in order to have full PBR sequences. Proportional representation was used for pocket variants while population data were also used.

RESULTS

All pocket variants and PBR sequences were retrieved and analyzed based on the preference of amino acids and their properties in all pocket positions. The observed number of pocket variants combinations was much lower than the possible inferred, suggesting that PBR formation is under strict funneling. Also, although class II proteins are very polymorphic, in the majority of the reported alleles in all populations, a significantly less polymorphic pocket core was found.

CONCLUSIONS

Pocket variability of five HLA class II proteins was studied revealing favorable properties of each protein. The actual PBR sequences of HLA class II proteins appear to be governed by restrictions that lead to the establishment of only a fraction of the possible combinations and the polymorphism recorded is the result of intense funneling based on function.

Subacute combined degeneration of the spinal cord with concomitant autoimmune disease: report of 2 cases

The etiology of subacute combined degeneration (SCD) of the spinal cord is closely associated with vitamin B12 (VitB12) deficiency. The clinical manifestations of SCD are complex and vary substantially. Due to some SCD patients with atypical manifestations and concomitant autoimmune disorders, the probability of misdiagnosis and missed diagnosis is still relatively high in the early stage. We report the cases of two patients who were missed or misdiagnosed at another hospital because of the normal initial VitB12 level and partial overlap of clinical manifestations, finally diagnosed as SCD with atypical manifestations and concomitant autoimmune disorders, pharyngeal-cervical-brachial Guillain-Barre syndrome in Case 1 and SCD with autoimmune thyroiditis in Case 2. After undergoing corresponding treatment, death was reported in Case 1 and improvement in Case 2. Analysis of the clinical manifestations and investigation of the underlying pathogenesis in such patients could help improve the rate of early diagnosis and allow timely treatment of SCD, thereby preventing disease progression and poor clinical outcomes.

Partnering for the major histocompatibility complex class II and antigenic determinant requires flexibility and chaperons

Cytotoxic, or helper T cells recognize antigen via T cell receptors (TCRs) that can see their target antigen as short sequences of peptides bound to the groove of proteins of major histocompatibility complex (MHC) class I, and class II respectively. For MHC class II epitope selection from exogenous pathogens or self-antigens, participation of several accessory proteins, molecular chaperons, processing enzymes within multiple vesicular compartments is necessary. A major contributing factor is the MHC class II structure itself that uniquely offers a dynamic and flexible groove essential for epitope selection. In this review, I have taken a historical perspective focusing on the flexibility of the MHC II molecules as the driving force in determinant selection and interactions with the accessory molecules in antigen processing, HLA-DM and HLA-DO.

Type 1 Diabetes and the HLA Region: Genetic Association Besides Classical HLA Class II Genes

Type 1 diabetes is an autoimmune disease with rising incidence in high-income countries. Genetic and environmental predisposing factors contribute to the etiology of the disease, although their interaction is not sufficiently understood to allow for preventive action. Strongest known associations with genetic variation map to classical HLA class II genes. Because of its genetic complexity, the HLA region has been under-represented in genome-wide association studies, having potentially hindered the identification of relevant associations underlying the etiology of the disease. Here, we performed a comprehensive HLA-wide genetic association analysis of type 1 diabetes including multi-allelic and rare variants. We used high-density whole-exome sequencing data of the HLA region in the large UK Biobank dataset to apply gene-based association tests with a carefully defined type 1 diabetes phenotype (97 cases and 48,700 controls). Exon-based and single-variant association tests were used to complement the analysis. We replicated the known association of type 1 diabetes with the classical HLA-DQ gene. Tailoring the analysis toward rare variants, we additionally identified the lysine methyl transferase EHMT2 as associated. Deeper insight into genetic variation associated with disease as presented and discussed in detail here can help unraveling mechanistic details of the etiology of type 1 diabetes. More specifically, we hypothesize that genetic variation in EHMT2 could impact autoimmunity in type 1 diabetes development.

Blunted nutrient-response pathways in adipose tissue following high fat meals in men with metabolic syndrome: A randomized postprandial transcriptomic study

BACKGROUND

Excessive adipose tissue is central to disease burden posed by the Metabolic Syndrome (MetS). Whilst much is known of the altered transcriptomic regulation of adipose tissue under fasting conditions, little is known of the responses to high-fat meals.

METHODS

Nineteen middle-aged males (mean ± SD 52.0 ± 4.6 years), consumed two isocaloric high-fat, predominately dairy-based or soy-based, breakfast meals. Abdominal subcutaneous adipose biopsies were collected after overnight fast (0 h) and 4 h following each meal. Global gene expression profiling was performed by microarray (Illumina Human WG-6 v3).

RESULTS

In the fasted state, 13 genes were differently expressed between control and MetS adipose tissue (≥1.2 fold-difference, p < 0.05). In response to the meals, the control participants had widespread increases in genes related to cellular nutrient responses (≥1.2 fold-change, p < 0.05; 2444 & 2367 genes; dairy & soy, respectively). There was blunted response in the MetS group (≥1.2 fold-change, p < 0.05; 332 & 336 genes; dairy & soy, respectively).

CONCLUSIONS

In middle-aged males with MetS, a widespread suppression of the subcutaneous adipose tissue nutrient responsive gene expression suggests an inflexibility in the transcriptomic responsiveness to both high-fat meals.

Revisiting nonclassical HLA II functions in antigen presentation: Peptide editing and its modulation

The nonclassical major histocompatibility complex of class II molecules (ncMHCII) HLA-DM (DM) and HLA-DO (DO) feature essential functions for the selection of the peptides that are displayed by classical MHCII proteins (MHCII) for CD4⁺ T_h cell surveillance. Thus, although the binding groove of classical MHCII dictates the main features of the peptides displayed, ncMHCII function defines the preferential loading of peptides from specific cellular compartments and the extent to which they are presented. DM acts as a chaperone for classical MHCII molecules facilitating peptide exchange and thereby favoring the binding of peptide-MHCII complexes of high kinetic stability mostly in late endosomal compartments. DO on the other hand binds to DM blocking its peptide-editing function in B cells and thymic epithelial cells, limiting DM activity in these cellular subsets. DM and DO distinct expression patterns therefore define specific antigen presentation profiles that select unique peptide pools for each set of antigen presenting cell. We have come a long way understanding the mechanistic underpinnings of such distinct editing profiles and start to grasp the implications for ncMHCII biological function. DM acts as filter for the selection of immunodominant, pathogen-derived epitopes while DO blocks DM activity under certain physiological conditions to promote tolerance to self. Interestingly, recent findings have shown that the unexplored and neglected ncMHCII genetic diversity modulates retroviral infection in mouse, and affects human ncMHCII function. This review aims at highlighting the importance of ncMHCII function for CD4⁺ T_h cell responses while integrating and evaluating what could be the impact of distinct editing profiles because of natural genetic variations.

Human Hepatitis B Viral Infection Outcomes Are Linked to Naturally Occurring Variants of HLA-DOA That Have Altered Function

HLA molecules of the MHC class II (MHCII) bind and present pathogen-derived peptides for CD4 T cell activation. Peptide loading of MHCII in the endosomes of cells is controlled by the interplay of the nonclassical MHCII molecules, HLA-DM (DM) and HLA-DO (DO). DM catalyzes peptide loading, whereas DO, an MHCII substrate mimic, prevents DM from interacting with MHCII, resulting in an altered MHCII-peptide repertoire and increased MHCII-CLIP. Although the two genes encoding DO (DOA and DOB) are considered nonpolymorphic, there are rare natural variants. Our previous work identified DOB variants that altered DO function. In this study, we show that natural variation in the DOA gene also impacts DO function. Using the 1000 Genomes Project database, we show that ∼98% of individuals express the canonical DOA*0101 allele, and the remaining individuals mostly express DOA*0102, which we found was a gain-of-function allele. Analysis of 25 natural occurring DOα variants, which included the common alleles, identified three null variants and one variant with reduced and nine with increased ability to modulate DM activity. Unexpectedly, several of the variants produced reduced DO protein levels yet efficiently inhibited DM activity. Finally, analysis of associated single-nucleotide polymorphisms genetically linked the DOA*0102 common allele, a gain-of-function variant, with human hepatitis B viral persistence. In contrast, we found that the DOα F114L null allele was linked with viral clearance. Collectively, these studies show that natural variation occurring in the human DOA gene impacts DO function and can be linked to specific outcomes of viral infections.

Distinct editing functions of natural HLA-DM allotypes impact antigen presentation and CD4+ T cell activation

Classical human leukocyte antigen (HLA) molecules of the major histocompatibility class II (MHCII) complex present peptides for the development, surveillance and activation of CD4+ T cells. The nonclassical MHCII-like protein HLA-DM (DM) catalyzes the exchange and loading of peptides onto MHCII molecules, thereby shaping MHCII immunopeptidomes. Natural variations of DM in both chains of the protein (DMA and DMB) have been hypothesized to impact peptide presentation, but no evidence for altered function has been reported. Here we define the presence of DM allotypes in human populations covered by the 1000 Genomes Project and probe their activity. The functional properties of several allotypes are investigated and show strong enhancement of peptide-induced T cell activation for a particular combination of DMA and DMB. Biochemical evidence suggests a broader pH activity profile for the new variant relative to that of the most commonly expressed DM allotype. Immunopeptidome analysis indicates that the compartmental activity of the new DM heterodimer extends beyond the late endosome and suggests that the natural variation of DM has profound effects on adaptive immunity when antigens bypass the canonical processing pathway.

Immunoglobulin Binding Protein 1 as a Potential Urine Biomarker in Patients with Lupus Nephritis

We evaluated the role of immunoglobulin binding protein 1 (IGBP1), a phosphoprotein associated with the B cell receptor (BCR) complex, as a urine biomarker in lupus nephritis (LN). The IGBP1 concentrations in plasma and urine of patients with LN, systemic lupus erythematosus (SLE) without nephritis and healthy controls were estimated by ELISA. IGBP1 expression in the kidneys of LN patients and transplantation donors was detected by immunohistochemistry. Microarray-based global gene expression profile of HK-2 cells with IGBP1 knock-down and fluorescence-activated cell sorting (FACS) for intracellular IGBP1 expression in human peripheral blood mononuclear cells (PBMCs) was performed. Urine IGBP1 levels were elevated significantly in LN patients, and it correlated with the clinical activity indices (complement 3 (C3) level, anti-dsDNA antibodies titer, SLE Disease Activity Index-2000 (SLEDAI-2K) and histological activity index. IGBP1 expression was increased in LN patients as compared to the donors and was detected mainly in the tubules by histopathology. In microarray analysis, several genes related to SLE pathogenesis (PPME1, ROCK2, VTCN1, IL-17R, NEU1, HLA-DM, and PTX3) responded to siRNA-mediated IGBP1 silencing. In FACS, IGBP1 was expressed mainly in the CD14⁺ cells. The overall expression of IGBP1 in PBMCs was higher in LN patients as compared with that in SLE patients without nephritis. Conclusively, urinary IGBP1 may be a novel biomarker reflecting the clinical and histological activities in LN.

Quantification of HLA-DM-Dependent Major Histocompatibility Complex of Class II Immunopeptidomes by the Peptide Landscape Antigenic Epitope Alignment Utility

The major histocompatibility complex of class II (MHCII) immunopeptidome represents the repertoire of antigenic peptides with the potential to activate CD4⁺ T cells. An understanding of how the relative abundance of specific antigenic epitopes affects the outcome of T cell responses is an important aspect of adaptive immunity and offers a venue to more rationally tailor T cell activation in the context of disease. Recent advances in mass spectrometric instrumentation, computational power, labeling strategies, and software analysis have enabled an increasing number of stratified studies on HLA ligandomes, in the context of both basic and translational research. A key challenge in the case of MHCII immunopeptidomes, often determined for different samples at distinct conditions, is to derive quantitative information on consensus epitopes from antigenic peptides of variable lengths. Here, we present the design and benchmarking of a new algorithm [peptide landscape antigenic epitope alignment utility (PLAtEAU)] allowing the identification and label-free quantification (LFQ) of shared consensus epitopes arising from series of nested peptides. The algorithm simplifies the complexity of the dataset while allowing the identification of nested peptides within relatively short segments of protein sequences. Moreover, we apply this algorithm to the comparison of the ligandomes of cell lines with two different expression levels of the peptide-exchange catalyst HLA-DM. Direct comparison of LFQ intensities determined at the peptide level is inconclusive, as most of the peptides are not significantly enriched due to poor sampling. Applying the PLAtEAU algorithm for grouping of the peptides into consensus epitopes shows that more than half of the total number of epitopes is preferentially and significantly enriched for each condition. This simplification and deconvolution of the complex and ambiguous peptide-level dataset highlights the value of the PLAtEAU algorithm in facilitating robust and accessible quantitative analysis of immunopeptidomes across cellular contexts. In silico analysis of the peptides enriched for each HLA-DM expression conditions suggests a higher affinity of the pool of peptides isolated from the high DM expression samples. Interestingly, our analysis reveals that while for certain autoimmune-relevant epitopes their presentation increases upon DM expression others are clearly edited out from the peptidome.