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The Human Leukocyte Antigen Class II Immunopeptidome of the SARS-CoV-2 Spike Glycoprotein.

ABSTRACT: Precise elucidation of the antigen sequences for T cell immunosurveillance greatly enhances our ability to understand and modulate humoral responses to viral infection or active immunization. Mass spectrometry is used to identify 526 unique sequences from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike glycoprotein extracellular domain in a complex with human leukocyte antigen class II molecules on antigen-presenting cells from a panel of healthy donors selected to represent a majority of allele usage from this highly polymorphic molecule. The identified sequences span the entire spike protein, and several sequences are isolated from a majority of the sampled donors, indicating promiscuous binding. Importantly, many peptides derived from the receptor binding domain used for cell entry are identified. This work represents a precise and comprehensive immunopeptidomic investigation with the SARS-CoV-2 spike glycoprotein and allows detailed analysis of features that may aid vaccine development to end the current coronavirus disease 2019 (COVID-19) pandemic.

SUBMITTER: Knierman MD

PROVIDER: S-EPMC7664343 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Class II human leukocyte antigens (HLA II) are proteins involved in the human immunological adaptive response by binding and exposing some pre-processed, non-self peptides in the extracellular domain in order to make them recognizable by the CD4+ T lymphocytes. However, the understanding of HLA-peptide binding interaction is a crucial step for designing a peptide-based vaccine because the high rate of polymorphisms in HLA class II molecules creates a big challenge, even though the HLA II proteins can be grouped into supertypes, where members of different class bind a similar pool of peptides. Hence, first we performed the supertype classification of 27 HLA II proteins using their binding affinities and structural-based linear motifs to create a stable group of supertypes. For this purpose, a well-known clustering method was used, and then, a consensus was built to find the stable groups and to show the functional and structural correlation of HLA II proteins. Thus, the overlap of the binding events was measured, confirming a large promiscuity within the HLA II-peptide interactions. Moreover, a very low rate of locus-specific binding events was observed for the HLA-DP genetic locus, suggesting a different binding selectivity of these proteins with respect to HLA-DR and HLA-DQ proteins. Secondly, a predictor based on a support vector machine (SVM) classifier was designed to recognize HLA II-binding peptides. The efficiency of prediction was estimated using precision, recall (sensitivity), specificity, accuracy, F-measure, and area under the ROC curve values of random subsampled dataset in comparison with other supervised classifiers. Also the leave-one-out cross-validation was performed to establish the efficiency of the predictor. The availability of HLA II-peptide interaction dataset, HLA II-binding motifs, high-quality amino acid indices, peptide dataset for SVM training, and MATLAB code of the predictor is available at http://sysbio.icm.edu.pl/HLA .

Project description:BackgroundAssociations between human leukocyte antigens (HLA) alleles and cervical cancer are largely representative of squamous cell carcinoma (SCC), the major histologic subtype. We evaluated the association between HLA class I (A, B, and C) and class II (DRB1 and DQB1) loci and risk of cervical adenocarcinoma (ADC), a less common but aggressive histologic subtype.MethodsWe pooled data from the Eastern and Western US Cervical Cancer studies, and evaluated the association between individual alleles and allele combinations and ADC (n = 630 ADC; n = 775 controls). Risk estimates were calculated for 11 a priori (based on known associations with cervical cancer regardless of histologic type) and 38 non a priori common alleles, as odds ratios (OR) and 95% confidence intervals (CI), adjusted for age and study. In exploratory analysis, we compared the risk associations between subgroups with HPV16 or HPV18 DNA in ADC tumor tissues in the Western US study cases and controls.ResultsThree of the a priori alleles were significantly associated with decreased risk of ADC [DRB1*13:01 (OR = 0.61; 95% CI: 0.41-0.93), DRB1*13:02 (OR = 0.49; 95% CI: 0.31-0.77), and DQB1*06:03 (OR = 0.64; 95% CI: 0.42-0.95)]; one was associated with increased risk [B*07:02 (OR = 1.39; 95% CI: 1.07-1.79)]. Among alleles not previously reported, DQB1*06:04 (OR = 0.46; 95% CI: 0.27-0.78) was associated with decreased risk of ADC and remained significant after correction for multiple comparisons, and C*07:02 (OR = 1.41; 95% CI: 1.09-1.81) was associated with increased risk. We did not observe a difference by histologic subtype. ADC was most strongly associated with increased risk with B*07:02/C*07:02 alleles (OR = 1.33; 95% CI: 1.01-1.76) and decreased risk with DRB1*13:02/DQB1*06:04 (OR = 0.41; 95% CI: 0.21-0.80).ConclusionRESULTS suggest that HLA allele associations with cervical ADC are similar to those for cervical SCC. An intriguing finding was the difference in risk associated with several alleles restricted to HPV16 or HPV18-related tumors, consistent with the hypothesis that HLA recognition is HPV type-specific.

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The Human Leukocyte Antigen Class II Immunopeptidome of the SARS-CoV-2 Spike Glycoprotein.

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