Distinct responses of newly identified monocyte subsets to advanced gastrointestinal cancer and COVID-19.

Monocytes are critical cells of the immune system but their role as effectors is relatively poorly understood, as they have long been considered only as precursors of tissue macrophages or dendritic cells. Moreover, it is known that this cell type is heterogeneous, but our understanding of this aspect is limited to the broad classification in classical/intermediate/non-classical monocytes, commonly based on their expression of only two markers, i.e. CD14 and CD16. We deeply dissected the heterogeneity of human circulating monocytes in healthy donors by transcriptomic analysis at single-cell level and identified 9 distinct monocyte populations characterized each by a profile suggestive of specialized functions. The classical monocyte subset in fact included five distinct populations, each enriched for transcriptomic gene sets related to either inflammatory, neutrophil-like, interferon-related, and platelet-related pathways. Non-classical monocytes included two distinct populations, one of which marked specifically by elevated expression levels of complement components. Intermediate monocytes were not further divided in our analysis and were characterized by high levels of human leukocyte antigen (HLA) genes. Finally, we identified one cluster included in both classical and non-classical monocytes, characterized by a strong cytotoxic signature. These findings provided the rationale to exploit the relevance of newly identified monocyte populations in disease evolution. A machine learning approach was developed and applied to two single-cell transcriptome public datasets, from gastrointestinal cancer and Coronavirus disease 2019 (COVID-19) patients. The dissection of these datasets through our classification revealed that patients with advanced cancers showed a selective increase in monocytes enriched in platelet-related pathways. Of note, the signature associated with this population correlated with worse prognosis in gastric cancer patients. Conversely, after immunotherapy, the most activated population was composed of interferon-related monocytes, consistent with an upregulation in interferon-related genes in responder patients compared to non-responders. In COVID-19 patients we confirmed a global activated phenotype of the entire monocyte compartment, but our classification revealed that only cytotoxic monocytes are expanded during the disease progression. Collectively, this study unravels an unexpected complexity among human circulating monocytes and highlights the existence of specialized populations differently engaged depending on the pathological context.

COVID-19 Pandemic: Escape of Pathogenic Variants and MHC Evolution.

We propose a new hypothesis that explains the maintenance and evolution of MHC polymorphism. It is based on two phenomena: the constitution of the repertoire of naive T lymphocytes and the evolution of the pathogen and its impact on the immune memory of T lymphocytes. Concerning the latter, pathogen evolution will have a different impact on reinfection depending on the MHC allomorph. If a mutation occurs in a given region, in the case of MHC allotypes, which do not recognize the peptide in this region, the mutation will have no impact on the memory repertoire. In the case where the MHC allomorph binds to the ancestral peptides and not to the mutated peptide, that individual will have a higher chance of being reinfected. This difference in fitness will lead to a variation of the allele frequency in the next generation. Data from the SARS-CoV-2 pandemic already support a significant part of this hypothesis and following up on these data may enable it to be confirmed. This hypothesis could explain why some individuals after vaccination respond less well than others to variants and leads to predict the probability of reinfection after a first infection depending upon the variant and the HLA allomorph.

Identification of Unique Peptides for SARS-CoV-2 Diagnostics and Vaccine Development by an In Silico Proteomics Approach.

Ongoing evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus strains is posing new COVID-19 diagnosis and treatment challenges. To help efforts to meet these challenges we examined data acquired from proteomic analyses of human SARS-CoV-2-infected cell lines and samples from COVID-19 patients. Initially, 129 unique peptides were identified, which were rigorously evaluated for repeats, disorders, polymorphisms, antigenicity, immunogenicity, toxicity, allergens, sequence similarity to human proteins, and contributions from other potential cross-reacting pathogenic species or the human saliva microbiome. We also screened SARS-CoV-2-infected NBHE and A549 cell lines for presence of antigenic peptides, and identified paratope peptides from crystal structures of SARS-CoV-2 antigen-antibody complexes. We then selected four antigen peptides for docking with known viral unbound T-cell receptor (TCR), class I and II peptide major histocompatibility complex (pMHC), and identified paratope sequences. We also tested the paratope binding affinity of SARS-CoV T- and B-cell peptides that had been previously experimentally validated. The resultant antigenic peptides have high potential for generating SARS-CoV-2-specific antibodies, and the paratope peptides can be directly used to develop a COVID-19 diagnostics assay. The presented genomics and proteomics-based in-silico approaches have apparent utility for identifying new diagnostic peptides that could be used to fight SARS-CoV-2.

Generation of SARS-CoV-2 S1 Spike Glycoprotein Putative Antigenic Epitopes in Vitro by Intracellular Aminopeptidases.

Presentation of antigenic peptides by MHCI is central to cellular immune responses against viral pathogens. While adaptive immune responses versus SARS-CoV-2 can be of critical importance to both recovery and vaccine efficacy, how protein antigens from this pathogen are processed to generate antigenic peptides is largely unknown. Here, we analyzed the proteolytic processing of overlapping precursor peptides spanning the entire sequence of the S1 spike glycoprotein of SARS-CoV-2, by three key enzymes that generate antigenic peptides, aminopeptidases ERAP1, ERAP2, and IRAP. All enzymes generated shorter peptides with sequences suitable for binding onto HLA alleles, but with distinct specificity fingerprints. ERAP1 was the most efficient in generating peptides 8-11 residues long, the optimal length for HLA binding, while IRAP was the least efficient. The combination of ERAP1 with ERAP2 greatly limited the variability of peptide sequences produced. Less than 7% of computationally predicted epitopes were found to be produced experimentally, suggesting that aminopeptidase processing may constitute a significant filter to epitope presentation. These experimentally generated putative epitopes could be prioritized for SARS-CoV-2 immunogenicity studies and vaccine design. We furthermore propose that this in vitro trimming approach could constitute a general filtering method to enhance the prediction robustness for viral antigenic epitopes.

T-CoV: a comprehensive portal of HLA-peptide interactions affected by SARS-CoV-2 mutations.

Rapidly appearing SARS-CoV-2 mutations can affect T cell epitopes, which can help the virus to evade either CD8 or CD4 T-cell responses. We developed T-cell COVID-19 Atlas (T-CoV, https://t-cov.hse.ru) - the comprehensive web portal, which allows one to analyze how SARS-CoV-2 mutations alter the presentation of viral peptides by HLA molecules. The data are presented for common virus variants and the most frequent HLA class I and class II alleles. Binding affinities of HLA molecules and viral peptides were assessed with accurate in silico methods. The obtained results highlight the importance of taking HLA alleles diversity into account: mutation-mediated alterations in HLA-peptide interactions were highly dependent on HLA alleles. For example, we found that the essential number of peptides tightly bound to HLA-B*07:02 in the reference Wuhan variant ceased to be tight binders for the Indian (Delta) and the UK (Alpha) variants. In summary, we believe that T-CoV will help researchers and clinicians to predict the susceptibility of individuals with different HLA genotypes to infection with variants of SARS-CoV-2 and/or forecast its severity.

Activating Killer-Cell Immunoglobulin-Like Receptors Are Associated With the Severity of Coronavirus Disease 2019.

BACKGROUND: Etiopathogenesis of the clinical variability of the coronavirus disease 2019 (COVID-19) remains mostly unknown. In this study, we investigate the role of killer cell immunoglobulin-like receptor (KIR)/human leukocyte antigen class-I (HLA-I) interactions in the susceptibility and severity of COVID-19. METHODS: We performed KIR and HLA-I genotyping and natural killer cell (NKc) receptors immunophenotyping in 201 symptomatic patients and 210 noninfected controls. RESULTS: The NKcs with a distinctive immunophenotype, suggestive of recent activation (KIR2DS4low CD16low CD226low CD56high TIGIThigh NKG2Ahigh), expanded in patients with severe COVID-19. This was associated with a higher frequency of the functional A-telomeric activating KIR2DS4 in severe versus mild and/or moderate patients and controls (83.7%, 55.7% and 36.2%, P < 7.7 × 10-9). In patients with mild and/or moderate infection, HLA-B*15:01 was associated with higher frequencies of activating B-telomeric KIR3DS1 compared with patients with other HLA-B*15 subtypes and noninfected controls (90.9%, 42.9%, and 47.3%; P < .002; Pc = 0.022). This strongly suggests that HLA-B*15:01 specifically presenting severe acute respiratory syndrome coronavirus 2 peptides could form a neoligand interacting with KIR3DS1. Likewise, a putative neoligand for KIR2DS4 could arise from other HLA-I molecules presenting severe acute respiratory syndrome coronavirus 2 peptides expressed on infected an/or activated lung antigen-presenting cells. CONCLUSIONS: Our results support a crucial role of NKcs in the clinical variability of COVID-19 with specific KIR/ligand interactions associated with disease severity.

Does Genetic Predisposition Contribute to the Exacerbation of COVID-19 Symptoms in Individuals with Comorbidities and Explain the Huge Mortality Disparity between the East and the West?

The elderly and patients with several comorbidities experience more severe cases of coronavirus disease 2019 (COVID-19) than healthy patients without underlying medical conditions. However, it is unclear why these people are prone to developing alveolar pneumonia, rapid exacerbations, and death. Therefore, we hypothesized that people with comorbidities may have a genetic predisposition that makes them more vulnerable to various factors; for example, they are likely to become more severely ill when infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To test this hypothesis, we searched the literature extensively. Polymorphisms of genes, such as those that encode angiotensin-converting enzyme 1 (ACE1), have been associated with numerous comorbidities, such as cardiovascular disease, hypertension, diabetes, chronic kidney disease, and obesity, and there are potential mechanisms to explain these associations (e.g., DD-type carriers have greater ACE1 activity, and patients with a genetic alpha-1 anti-trypsin (AAT) deficiency lack control over inflammatory mediators). Since comorbidities are associated with chronic inflammation and are closely related to the renin-angiotensin-aldosterone system (RAAS), these individuals may already have a mild ACE1/ACE2 imbalance before viral infection, which increases their risk for developing severe cases of COVID-19. However, there is still much debate about the association between ACE1 D/I polymorphism and comorbidities. The best explanation for this discrepancy could be that the D allele and DD subtypes are associated with comorbidities, but the DD genotype alone does not have an exceptionally large effect. This is also expected since the ACE1 D/I polymorphism is only an intron marker. We also discuss how polymorphisms of AAT and other genes are involved in comorbidities and the severity of SARS-CoV-2 infection. Presumably, a combination of multiple genes and non-genetic factors is involved in the establishment of comorbidities and aggravation of COVID-19.

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.

Understanding the genetic contribution of the human leukocyte antigen system to common major psychiatric disorders in a world pandemic context.

The human leukocyte antigen (HLA) is a complex genetic system that encodes proteins which predominantly regulate immune/inflammatory processes. It can be involved in a variety of immuno-inflammatory disorders ranging from infections to autoimmunity and cancers. The HLA system is also suggested to be involved in neurodevelopment and neuroplasticity, especially through microglia regulation and synaptic pruning. Consequently, this highly polymorphic gene region has recently emerged as a major player in the etiology of several major psychiatric disorders, such as schizophrenia, autism spectrum disorder and bipolar disorder and with less evidence for major depressive disorders and attention deficit hyperactivity disorder. We thus review here the role of HLA genes in particular subgroups of psychiatric disorders and foresee their potential implication in future research. In particular, given the prominent role that the HLA system plays in the regulation of viral infection, this review is particularly timely in the context of the Covid-19 pandemic.

Respiratory viral infection in lung transplantation induces exosomes that trigger chronic rejection.

BACKGROUND: Respiratory viral infections can increase the risk of chronic lung allograft dysfunction after lung transplantation, but the mechanisms are unknown. In this study, we determined whether symptomatic respiratory viral infections after lung transplantation induce circulating exosomes that contain lung-associated self-antigens and assessed whether these exosomes activate immune responses to self-antigens. METHODS: Serum samples were collected from lung transplant recipients with symptomatic lower- and upper-tract respiratory viral infections and from non-symptomatic stable recipients. Exosomes were isolated via ultracentrifugation; purity was determined using sucrose cushion; and presence of lung self-antigens, 20S proteasome, and viral antigens for rhinovirus, coronavirus, and respiratory syncytial virus were determined using immunoblot. Mice were immunized with circulating exosomes from each group and resulting differential immune responses and lung histology were analyzed. RESULTS: Exosomes containing self-antigens, 20S proteasome, and viral antigens were detected at significantly higher levels (p < 0.05) in serum of recipients with symptomatic respiratory viral infections (n = 35) as compared with stable controls (n = 32). Mice immunized with exosomes from recipients with respiratory viral infections developed immune responses to self-antigens, fibrosis, small airway occlusion, and significant cellular infiltration; mice immunized with exosomes from controls did not (p < 0.05). CONCLUSIONS: Circulating exosomes isolated from lung transplant recipients diagnosed with respiratory viral infections contained lung self-antigens, viral antigens, and 20S proteasome and elicited immune responses to lung self-antigens that resulted in development of chronic lung allograft dysfunction in immunized mice.

The SPPL3-Defined Glycosphingolipid Repertoire Orchestrates HLA Class I-Mediated Immune Responses.

HLA class I (HLA-I) glycoproteins drive immune responses by presenting antigens to cognate CD8+ T cells. This process is often hijacked by tumors and pathogens for immune evasion. Because options for restoring HLA-I antigen presentation are limited, we aimed to identify druggable HLA-I pathway targets. Using iterative genome-wide screens, we uncovered that the cell surface glycosphingolipid (GSL) repertoire determines effective HLA-I antigen presentation. We show that absence of the protease SPPL3 augmented B3GNT5 enzyme activity, resulting in upregulation of surface neolacto-series GSLs. These GSLs sterically impeded antibody and receptor interactions with HLA-I and diminished CD8+ T cell activation. Furthermore, a disturbed SPPL3-B3GNT5 pathway in glioma correlated with decreased patient survival. We show that the immunomodulatory effect could be reversed through GSL synthesis inhibition using clinically approved drugs. Overall, our study identifies a GSL signature that inhibits immune recognition and represents a potential therapeutic target in cancer, infection, and autoimmunity.

COVID-19 in a lung transplant recipient: Exploring the diagnostic role of circulating exosomes and the clinical impact of advanced immunosuppression.

Exosomes isolated from plasma of lung transplant recipients with allograft injury contain donor-derived lung self-antigens (collagen V and Kα1 tubulin) and human leukocyte antigen (HLA) molecules. We present a case of a 76-year-old, female lung transplant recipient treated for acute cellular rejection with methylprednisolone and anti-thymocyte globulin, who subsequently contracted SARS-CoV-2 and developed a sharp increase in the mean fluorescent intensity of anti-HLA antibodies. Analysis of circulating exosomes during rejection, but before SARS-CoV-2 infection, revealed the presence of lung self-antigens and HLA class II molecules. After the patient contracted SARS-CoV-2, exosomes with the SARS-CoV-2 spike protein were also found. After resolution of infectious symptoms, exosomes with SARS-CoV-2 spike protein were no longer detected; however, exosomes with lung self-antigens and HLA class II molecules persisted, which coincided with a progressive decline in spirometric flows, suggesting chronic lung allograft dysfunction. We propose that the analysis of circulating exosomes may be used to detect allograft injury mediated by both rejection and infection. Furthermore, the detection of exosomes containing viral proteins may be helpful in identifying allograft injury driven by viral pathogens.

Analysis of the SARS-CoV-2 spike protein glycan shield reveals implications for immune recognition.

Here we have generated 3D structures of glycoforms of the spike (S) glycoprotein from SARS-CoV-2, based on reported 3D structures and glycomics data for the protein produced in HEK293 cells. We also analyze structures for glycoforms representing those present in the nascent glycoproteins (prior to enzymatic modifications in the Golgi), as well as those that are commonly observed on antigens present in other viruses. These models were subjected to molecular dynamics (MD) simulation to determine the extent to which glycan microheterogeneity impacts the antigenicity of the S glycoprotein. Lastly, we have identified peptides in the S glycoprotein that are likely to be presented in human leukocyte antigen (HLA) complexes, and discuss the role of S protein glycosylation in potentially modulating the innate and adaptive immune response to the SARS-CoV-2 virus or to a related vaccine. The 3D structures show that the protein surface is extensively shielded from antibody recognition by glycans, with the notable exception of the ACE2 receptor binding domain, and also that the degree of shielding is largely insensitive to the specific glycoform. Despite the relatively modest contribution of the glycans to the total molecular weight of the S trimer (17% for the HEK293 glycoform) they shield approximately 40% of the protein surface.

Conserved HLA binding peptides from five non-structural proteins of SARS-CoV-2-An in silico glance.

Coronavirus Disease 2019 (COVID-19) is a dangerous global threat that has no clinically approved treatment yet. Bioinformatics represent an outstanding approach to reveal key immunogenic regions in viral proteins. Here, five severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) non-structural proteins (NSPs) (NSP7, NSP8, NSP9, NSP12, and NSP13) were screened to identify potential human leukocyte antigen (HLA) binding peptides. These peptides showed robust viral antigenicity, immunogenicity, and a marked interaction with HLA alleles. Interestingly, several peptides showed affinity by HLA class I (HLA-I) alleles that commonly activates to natural killer (NK) cells. Notably, HLA biding peptides are conserved among SARS-CoV-2, severe acute respiratory syndrome coronavirus (SARS-CoV), and Middle Eastern respiratory syndrome coronavirus (MERS-CoV). Interestingly, HLA-I and HLA class II (HLA-II) binding peptides induced humoral and cell-mediated responses after in silico vaccination. These results may open further in vitro and in vivo investigations to develop novel therapeutic strategies against coronaviral infections.

Understanding the B and T cell epitopes of spike protein of severe acute respiratory syndrome coronavirus-2: A computational way to predict the immunogens.

The 2019 novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) outbreak has caused a large number of deaths, with thousands of confirmed cases worldwide. The present study followed computational approaches to identify B- and T-cell epitopes for the spike (S) glycoprotein of SARS-CoV-2 by its interactions with the human leukocyte antigen alleles. We identified 24 peptide stretches on the SARS-CoV-2 S protein that are well conserved among the reported strains. The S protein structure further validated the presence of predicted peptides on the surface, of which 20 are surface exposed and predicted to have reasonable epitope binding efficiency. The work could be useful for understanding the immunodominant regions in the surface protein of SARS-CoV-2 and could potentially help in designing some peptide-based diagnostics. Also, identified T-cell epitopes might be considered for incorporation in vaccine designs.