T Cell Receptor Research Articles

TGIRT-seq of Inflammatory Breast Cancer Tumor and Blood Samples Reveals Widespread Enhanced Transcription Impacting RNA Splicing and Intronic RNAs in Plasma.

Inflammatory breast cancer (IBC) is the most aggressive and lethal breast cancer subtype but lacks unequivocal genomic differences or robust biomarkers that differentiate it from non-IBC. Here, Thermostable Group II intron Reverse Transcriptase RNA-sequencing (TGIRT-seq) revealed myriad differences in tumor samples, Peripheral Blood Mononuclear Cells (PBMCs), and plasma that distinguished IBC from non-IBC patients and healthy donors across all tested receptor-based subtypes. These included numerous differentially expressed protein-coding gene and non-coding RNAs in all three sample types, a granulocytic immune response in IBC PBMCs, and over- expression of antisense RNAs, suggesting wide-spread enhanced transcription in both IBC tumors and PBMCs. By using TGIRT-seq to quantitate Intron-exon Depth Ratios (IDRs) and mapping reads to both genome and transcriptome reference sequences, we developed methods for parallel analysis of transcriptional and post-transcriptional gene regulation. This analysis identified numerous differentially and non-differentially expressed protein-coding genes in IBC tumors and PBMCs with high IDRs, the latter reflecting rate-limiting RNA splicing that negatively impacts mRNA production. Mirroring gene expression differences in tumors and PBMCs, over-represented protein-coding gene RNAs in IBC patient plasma were largely intronic RNAs, while those in non- IBC patients and healthy donor plasma were largely mRNA fragments. Potential IBC biomarkers in plasma included T-cell receptor pre-mRNAs and intronic, LINE-1, and antisense RNAs. Our findings provide new insights into IBC and set the stage for monitoring disease progression and response to treatment by liquid biopsy. The methods developed for parallel transcriptional and post- transcriptional gene regulation analysis have potentially broad RNA-seq and clinical applications.

From TCR fundamental research to innovative chimeric antigen receptor design.

Engineered T cells that express chimeric antigen receptors (CARs) have transformed the treatment of haematological cancers. CARs combine the tumour-antigen-binding function of antibodies with the signalling functions of the T-=cell receptor (TCR) ζ chain and co-stimulatory receptors. The resulting constructs aim to mimic the TCR-based and co-receptor-based activation of T cells. Although these have been successful for some types of cancer, new CAR formats are needed, to limit side effects and broaden their use to solid cancers. Insights into the mechanisms of TCR signalling, including the identification of signalling motifs that are not present in the TCR ζ chain and mechanistic insights in TCR activation, have enabled the development of CAR formats that outcompete the current CARs in preclinical mouse models and clinical trials. In this Perspective, we explore the mechanistic rationale behind new CAR designs.

Ultrasensitive allele inference from immune repertoire sequencing data with MiXCR.

Allelic variability in the adaptive immune receptor loci, which harbor the gene segments that encode B cell and T cell receptors (BCR/TCR), is of critical importance for immune responses to pathogens and vaccines. Adaptive immune receptor repertoire sequencing (AIRR-seq) has become widespread in immunology research making it the most readily available source of information about allelic diversity in immunoglobulin (IG) and T cell receptor (TR) loci. Here we present a novel algorithm for extra-sensitive and specific variable (V) and joining (J) gene allele inference, allowing reconstruction of individual high-quality gene segment libraries. The approach can be applied for inferring allelic variants from peripheral blood lymphocyte BCR and TCR repertoire sequencing data, including hypermutated isotype-switched BCR sequences, thus allowing high-throughput novel allele discovery from a wide variety of existing datasets. The developed algorithm is a part of the MiXCR software. We demonstrate the accuracy of this approach using AIRR-seq paired with long-read genomic sequencing data, comparing it to a widely used algorithm, TIgGER. We applied the algorithm to a large set of IG heavy chain (IGH) AIRR-seq data from 450 donors of ancestrally diverse population groups, and to the largest reported full-length TCR alpha and beta chain (TRA; TRB) AIRR-seq dataset, representing 134 individuals. This allowed us to assess the genetic diversity within the IGH, TRA and TRB loci in different populations and to establish a database of alleles of V and J genes inferred from AIRR-seq data and their population frequencies with free public access through an online database.

Quantitative Analysis of Protein-Protein Equilibrium Constants in Cellular Environments Using Single-Molecule Localization Microscopy.

Current methods for determining equilibrium constants often operate in three-dimensional environments, which may not accurately reflect interactions with membrane-bound proteins. With our technique, based on single-molecule localization microscopy (SMLM), we directly determine protein-protein association (Ka) and dissociation (Kd) constants in cellular environments by quantifying associated and isolated molecules and their interaction area. We introduce Kernel Surface Density (ks-density,) a novel method for determining the accessible area for interacting molecules, eliminating the need for user-defined parameters. Simulation studies validate our method's accuracy across various density and affinity conditions. Applying this technique to T cell signaling proteins, we determine the 2D association constant of T cell receptors (TCRs) in resting cells and the pseudo-3D dissociation constant of pZAP70 molecules from phosphorylated intracellular tyrosine-based activation motifs on the TCR-CD3 complex. We address challenges of multiple detection and molecular labeling efficiency. This method enhances our understanding of protein interactions in cellular environments, advancing our knowledge of complex biological processes.

MicroRNAs are enriched at COVID-19 genomic risk regions, and their blood levels correlate with the COVID-19 prognosis of cancer patients infected by SARS-CoV-2

BackgroundCancer patients are more susceptible to an aggressive course of COVID-19. Developing biomarkers identifying cancer patients at high risk of COVID-19-related death could help determine who needs early clinical intervention. The miRNAs hosted in the genomic regions associated with the risk of aggressive COVID-19 could represent potential biomarkers for clinical outcomes.Patients and methodsPlasma samples were collected at The University of Texas MD Anderson Cancer Center from cancer patients (N = 128) affected by COVID-19. Serum samples were collected from vaccinated healthy individuals (n = 23) at the Municipal Clinical Emergency Teaching Hospital in Timisoara, Romania. An in silico positional cloning approach was used to identify the presence of miRNAs at COVID-19 risk-associated genomic regions: CORSAIRs (COvid-19 RiSk AssocIated genomic Regions). The miRNA levels were measured by RT-qPCR.ResultsWe found that miRNAs were enriched in CORSAIR. Low plasma levels of hsa-miR-150-5p and hsa-miR-93-5p were associated with higher COVID-19-related death. The levels of hsa-miR-92b-3p were associated with SARS-CoV-2 test positivity. Peripheral blood mononuclear cells (PBMC) increased secretion of hsa-miR-150-5p, hsa-miR-93-5p, and hsa-miR-92b-3p after in vitro TLR7/8- and T cell receptor (TCR)-mediated activation. Increased levels of these three miRNAs were measured in the serum samples of healthy individuals between one and nine months after the second dose of the Pfizer-BioNTech COVID-19 vaccine. SARS-CoV-2 infection of human airway epithelial cells influenced the miRNA levels inside their secreted extracellular vesicles.ConclusionsMiRNAs are enriched at CORSAIR. Plasma miRNA levels can represent a potential blood biomarker for predicting COVID-19-related death in cancer patients.

Downregulation of PIK3IP1/TrIP on T cells is controlled by TCR signal strength, PKC and metalloprotease-mediated cleavage.

The protein known as PI3K-interacting protein (PIK3IP1), or transmembrane inhibitor of PI3K (TrIP), is highly expressed by T cells and can modulate PI3K activity in these cells. Several studies have also revealed that TrIP is rapidly downregulated following T cell activation. However, it is unclear as to how this downregulation is controlled. Using a novel monoclonal antibody that robustly stains cell-surface TrIP, we demonstrate that TrIP is lost from the surface of activated T cells in a manner dependent on the strength of signaling through the T cell receptor (TCR) and specific downstream signaling pathways, in particular classical PKC isoforms. TrIP expression returns by 24 hours after stimulation, suggesting that it may play a role in resetting TCR signaling at later time points. We also provide evidence that ADAM family proteases are required for both constitutive and stimulation-induced downregulation of TrIP in T cells. Finally, by expressing truncated forms of TrIP in cells, we identify the region in the extracellular stalk domain of TrIP that is targeted for proteolytic cleavage.

Interpretable GWAS by linking clinical phenotypes to quantifiable immune repertoire components

Bridging the gap between genotype and phenotype in GWAS studies is challenging. A multitude of genetic variants have been associated with immune-related diseases, including cancer, yet the interpretability of most variants remains low. Here, we investigate the quantitative components in the T cell receptor (TCR) repertoire, the frequency of clusters of TCR sequences predicted to have common antigen specificity, to interpret the genetic associations of diverse human diseases. We first developed a statistical model to predict the TCR components using variants in the TRB and HLA loci. Applying this model to over 300,000 individuals in the UK Biobank data, we identified 2309 associations between TCR abundances and various immune diseases. TCR clusters predicted to be pathogenic for autoimmune diseases were significantly enriched for predicted autoantigen-specificity. Moreover, four TCR clusters were associated with better outcomes in distinct cancers, where conventional GWAS cannot identify any significant locus. Collectively, our results highlight the integral role of adaptive immune responses in explaining the associations between genotype and phenotype.

Investigation of Long-Term CD4+ T Cell Receptor Repertoire Changes Following SARS-CoV-2 Infection in Patients with Different Severities of Disease.

The difference in the immune response to severe acute respiratory syndrome coro-navirus 2 (SARS-CoV-2) in patients with mild versus severe disease remains poorly understood. Recent scientific advances have recognised the vital role of both B cells and T cells; however, many questions remain unanswered, particularly for T cell responses. T cells are essential for helping the generation of SARS-CoV-2 antibody responses but have also been recognised in their own right as a major factor influencing COVID-19 disease outcomes. The examination of T cell receptor (TCR) family differences over a 12-month period in patients with varying COVID-19 disease severity is crucial for understanding T cell responses to SARS-CoV-2. We applied a machine learning approach to analyse TCR vb family responses in COVID-19 patients (n = 151) across multiple timepoints and disease severities alongside SARS-CoV-2 infection-naïve (healthy control) individ-uals (n = 62). Blood samples from hospital in-patients with moderate, severe, or critical disease could be classified with an accuracy of 94%. Furthermore, we identified significant variances in TCR vb family specificities between disease and control subgroups. Our findings suggest advantageous and disadvantageous TCR repertoire patterns in relation to disease severity. Following validation in larger cohorts, our methodology may be useful in detecting protective immunity and the assessment of long-term outcomes, particularly as we begin to unravel the immunological mechanisms leading to post-COVID complications.

JunB is required for CD8+ T cell responses to acute infections.

Basic-leucine zipper transcription factor ATF-like (BATF) and interferon regulatory factor 4 (IRF4) are crucial transcription factors for generation of cytotoxic effector and memory CD8+ T cells. JunB is required for expression of genes controlled by BATF and IRF4 in CD4+ T cell responses, but the role of JunB in CD8+ T cells remains unknown. Here, we demonstrate that JunB is essential for cytotoxic CD8+ T cell responses. JunB expression is transiently induced, depending on T cell receptor (TCR) signal strength. JunB deficiency severely impairs clonal expansion of effector CD8+ T cells in response to acute infection with Listeria monocytogenes. Junb-deficient CD8+ T cells fail to control transcription and chromatin accessibility of a specific set of genes regulated by BATF and IRF4, resulting in impaired cell survival, glycolysis, and cytotoxic CD8+ T cell differentiation. Furthermore, JunB deficiency enhances expression of coinhibitory receptors, including programmed death receptor 1 (PD-1) and T-cell immunoglobulin mucin-3 (TIM3) upon activation of naïve CD8+ T cells. These results indicate that JunB, in collaboration with BATF and IRF4, promotes multiple key events in the early stage of cytotoxic CD8+ T cell responses.

PCR GeneScan Analysis of Rearranged Immunoglobulin or T-Cell Receptor Genes for Clonality Diagnostics in Suspect Lymphoproliferations.

Assessment of the presence of clonal lymphoproliferations via polymerase chain reaction (PCR)-based analysis of rearranged immunoglobulin (IG) or T-cell receptor (TR) genes is a valuable method in the diagnosis of suspect lymphoproliferative disorders. Additionally, this methodology can be used for evaluating dissemination of lymphoma cells and for studying the clonal relationship between multiple (different locations) and consecutive (over time) lymphomas. Here we describe an integrated approach to assess clonality via analysis of Ig heavy chain (IGH), Ig kappa (IGK), TCR beta (TRB), and TCR gamma (TRG) gene rearrangements, based on the standardized multiplex PCRs as originally developed by the European BIOMED-2 consortium (currently named EuroClonality). The described protocol covers the pre-analytical phase of DNA isolation (from formalin-fixed paraffin-embedded and fresh tissues, body fluids, peripheral blood, and bone marrow), the analytical phase of PCR GeneScan analysis, and the post-analytical interpretation of the obtained profiles, following established guidelines.

Load-based divergence in the dynamic allostery of two TCRs recognizing the same pMHC.

Increasing evidence suggests that mechanical load on the αβ T cell receptor (TCR) is crucial for recognizing the antigenic peptide-loaded major histocompatibility complex (pMHC) molecule. Our recent all-atom molecular dynamics (MD) simulations revealed that the inter-domain motion of the TCR is responsible for the load-induced catch bond behavior of the TCR-pMHC complex and peptide discrimination. To further examine the generality of the mechanism, we perform all-atom MD simulations of the B7 TCR under different conditions for comparison with our previous simulations of the A6 TCR. The two TCRs recognize the same pMHC and have similar interfaces with pMHC in crystal structures. We find that the B7 TCR-pMHC interface stabilizes under ∼15-pN load using a conserved dynamic allostery mechanism that involves the asymmetric motion of the TCR chassis. However, despite forming comparable contacts with pMHC as A6 in the crystal structure, B7 has fewer high-occupancy contacts with pMHC during the simulation. These results suggest that the dynamic allostery common to the TCR αβ chassis can amplify slight differences in interfacial contacts into distinctive mechanical responses and potentially nuanced biological outcomes.

Exploring the Key Pathogenesis and Potential Intervention Targets of Sulforaphane in Acute Kidney Injury in Sepsis Based on Bioinformatics.

The objective was to use bioinformatics to analyze the potential key genes involved in the mechanism of sulforaphane's protective effects in sepsis-associated acute kidney injury (SA-AKI) and to identify potential intervention targets. Gene Expression Omnibus (GEO) gene chip datasets containing gene expression profiles from kidney tissues of SA-AKI patients and normal controls were selected. Upregulated differentially expressed genes (DEGs) were identified using GEO2R. Protein-protein interaction (PPI), GO, and KEGG enrichment analyses were performed. Allyl isothiocyanate's target genes were analyzed in the ChEMBL database, and intersections with the above DEGs were presented in Venn diagrams. Rat tissues were examined for FKBP1A expression using qRT-PCR. A total of 17 DEGs related to SA-AKI were obtained (|log fold change| > 0 and P < .05). KEGG pathway analysis indicated that the primary pathways linked to the elevated DEGs were glycogen breakdown, leukocyte trans-endothelial migration, and T-cell receptor, TNF, and NF-κB signaling. The module and PPI network analysis of common DEGs revealed one cluster and four candidate genes, including OASL, TRRAP, FKBP1A, and BANF. ChEMBL database analysis identified 339 target genes for allyl isothiocyanate, and the intersection with upregulated DEGs related to SA-AKI injury yielded two co-expressed genes, FKBP1A and TRRAP. According to the findings of the qRT-PCR assay, the kidney tissues of the model cohort showed significantly higher expression levels of FKBP1A mRNA than the control cohort (P = .0142). Allyl isothiocyanate may alleviate SA-AKI injury by targeting FKBP1/NF-κB.

Antigen specificity of clonally-enriched CD8+ T cells in multiple sclerosis.

CD8+ T cells are the dominant lymphocyte population in multiple sclerosis (MS) lesions where they are highly clonally expanded. The clonal identity, function, and antigen specificity of CD8+ T cells in MS are not well understood. Here we report a comprehensive single-cell RNA-seq and T cell receptor (TCR)-seq analysis of the cerebrospinal fluid (CSF) and blood from a cohort of treatment-naïve MS patients and control participants. A small subset of highly expanded and activated CD8+ T cells were enriched in the CSF in MS that displayed high activation, cytotoxicity and tissue-homing transcriptional profiles. Using a combination of unbiased and targeted antigen discovery approaches, MS-derived CD8+ T cell clonotypes recognizing Epstein-Barr virus (EBV) antigens and multiple novel mimotopes were identified. These findings shed vital insight into the role of CD8+ T cells in MS and pave the way towards disease biomarkers and therapeutic targets.

Activation-Induced Marker Assay to Identify and Isolate HCV-Specific T Cells for Single-Cell RNA-Seq Analysis.

Identification and isolation of antigen-specific T cells for downstream transcriptomic analysis is key for various immunological studies. Traditional methods using major histocompatibility complex (MHC) multimers are limited by the number of predefined immunodominant epitopes and MHC matching of the study subjects. Activation-induced markers (AIM) enable highly sensitive detection of rare antigen-specific T cells irrespective of the availability of MHC multimers. Herein, we have developed an AIM assay for the detection, sorting and subsequent single-cell RNA sequencing (scRNA-seq) analysis of hepatitis C virus (HCV)-specific T cells. We examined different combinations of the activation markers CD69, CD40L, OX40, and 4-1BB at 6, 9, 18 and 24 h post stimulation with HCV peptide pools. AIM+ CD4 T cells exhibited upregulation of CD69 and CD40L as early as 6 h post-stimulation, while OX40 and 4-1BB expression was delayed until 18 h. AIM+ CD8 T cells were characterized by the coexpression of CD69 and 4-1BB at 18 h, while the expression of CD40L and OX40 remained low throughout the stimulation period. AIM+ CD4 and CD8 T cells were successfully sorted and processed for scRNA-seq analysis examining gene expression and T cell receptor (TCR) usage. scRNA-seq analysis from this one subject revealed that AIM+ CD4 T (CD69+ CD40L+) cells predominantly represented Tfh, Th1, and Th17 profiles, whereas AIM+ CD8 T (CD69+ 4-1BB+) cells primarily exhibited effector and effector memory profiles. TCR analysis identified 1023 and 160 unique clonotypes within AIM+ CD4 and CD8 T cells, respectively. In conclusion, this approach offers highly sensitive detection of HCV-specific T cells that can be applied for cohort studies, thus facilitating the identification of specific gene signatures associated with infection outcome and vaccination.

Investigating TCR-pMHC interactions for TCRs without identified epitopes by constructing a computational pipeline

The molecular mechanisms underlying epitope recognition by T cell receptors (TCRs) are critical for activating T cell immune responses and rationally designing TCR-based therapeutics. Single-cell sequencing techniques vastly boost the accumulation of TCR sequences, while the limitation of available TCR-pMHC structures hampers further investigations. In this study, we proposed a computational pipeline that incorporates structural information and single-cell sequencing data to investigate the epitope-recognition mechanisms for TCRs without identified epitopes. By antigen specificity clustering, we mapped the epitope sequences between epitope-known and epitope-unknown TCRs from COVID-19 patients. One reported SARS-CoV-2 epitope, NQKLIANQF (S919–927), was identified for a TCR expressed by 614 T cells (TCR-614). Epitope screening also identified a potential cross-reactive epitope, KLKTLVATA (NSP31790–1798), for a TCR expressed by 204 T cells (TCR-204). By molecular dynamics (MD) simulations, we revealed the detailed epitope-recognition mechanisms for both TCRs. The structural motifs responsible for epitope recognition revealed by the MD simulations are consistent with the sequential features recognized by the sequence-based clustering method. We hope that this strategy could facilitate the discovery and optimization of TCR-based therapeutics.

Single-cell transcriptomics reveal potent extrafollicular B cell response linked with granzyme K+ CD8 T cell activation in lupus kidney

ObjectivesB and T cells constitute the majority of infiltrating lymphocytes in the kidney and represent the local perpetrators in lupus nephritis (LN), but the underlying pathogenic mechanisms are not well...

Evolving Patterns in Inpatient Pediatric Consultations to Allergy/Immunology at an Academic Medical Center

Background: Consultations to pediatric allergy/immunology are of benefit to many hospitalized inpatients, but there is limited current information about how T-cell receptor excision circles (TREC) screening may have changed these patterns for pediatric populations. We aimed to determine the types of consults being requested and their relative frequencies for primary pediatric allergy/immunology consults under an academic fellowship program since the start of TREC screening in 2016. Information gained could help identify focal concepts for pediatric allergy inpatient training curricula for fellowship and graduate medical education programs. Methods: Under an IRB approved study of an academic allergy fellowship consultation log, we retrospectively reviewed electronic medical records of pediatric allergy and immunology consults and categorized consultations by their primary indication. Results: Three-hundred and eighty-three pediatric allergy/immunology consultations were seen between September 4, 2016 to November 24, 2022. In terms of frequency, the most common consultation was for immunodeficiency evaluation or treatment, n=205 (53.5%), followed by drug allergy n=55 (14.4%), general allergy concerns n=43 (11.2%), skin allergy n=35 (9.1%), and less commonly inflammatory syndromes, n=26 (6.8%) and food allergy, n=19 (5.0%). Questions related to TREC screening comprised 21% of all immunodeficiency consults, at n=43. Conclusion: At an academic allergy center where all allergy/immunology service lines are currently provided, the most common reason for pediatric consultations were for help with immunodeficiency evaluation/treatment and drug allergy. TREC screening is a new key indication for consultation. Fellowship programs may benefit from focusing on these content areas for the pediatric inpatient setting.

MA11.13 Peripheral T-Cell Receptor Repertoire Differentiates a Typical Progression in Non-Small Cell Lung Cancer Patients Treated with Immunotherapy

MA11.13 Peripheral T-Cell Receptor Repertoire Differentiates a Typical Progression in Non-Small Cell Lung Cancer Patients Treated with Immunotherapy

Single-Cell Antigen Receptor Sequencing in Pigs with Influenza.

Understanding the pulmonary adaptive immune system of pigs is important as respiratory pathogens present a major challenge for swine producers and pigs are increasingly used to model human pulmonary diseases. Single-cell RNA sequencing (scRNAseq) has accelerated the characterization of cellular phenotypes in the pig respiratory tract under both healthy and diseased conditions. However, combining scRNAseq with recovery of paired T cell receptor (TCR) α and β chains as well as B cell receptor (BCR) heavy and light chains to interrogate their repertoires has not to our knowledge been demonstrated for pigs. Here, we developed primers to enrich porcine TCR α and β chains along with BCR κ and λ light chains and IgM, IgA, and IgG heavy chains that are compatible with the 10x Genomics VDJ sequencing protocol. Using these pig-specific assays, we sequenced the T and B cell receptors of cryopreserved lung cells from CD1D -expressing and -deficient pigs after one or two infections with influenza A virus (IAV) to examine whether natural killer T (NKT) cells alter pulmonary TCR and BCR repertoire selection. We also performed paired single-cell RNA and receptor sequencing of FACS-sorted T cells longitudinally sampled from the lungs of IAV-vaccinated and -infected pigs to track clonal expansion in response to IAV exposure. All pigs presented highly diverse repertoires. Pigs re-exposed to influenza antigens from either vaccination or infection exhibited higher numbers of expanded CD4 and CD8 T cell clonotypes with activated phenotypes, suggesting potential IAV reactive T cell populations. Our results demonstrate the utility of high throughput single-cell TCR and BCR sequencing in pigs.

Computational insights in design of Crimean-Congo hemorrhagic fever virus conserved immunogenic nucleoprotein peptides containing multiple epitopes.

Crimean-Congo hemorrhagic fever virus (CCHFV) belongs to Nairoviridae family and has tripartite RNA genome. It is endemic in various countries of Asia, Africa, and Europe and is primarily transmitted by Hyalomma ticks but nosocomial transmission also been reported. Vaccines for CCHF are in early phase of clinical trial; therefore, this work is centered on identification of potential immunogenic peptide as vaccine candidates with application of different immunoinformatics approaches. Eleven conserved (>90%) peptides of CCHFV nucleoprotein were selected for CD8+ T-cell (NetMHCpan 4.1b and NetCTLpan 1.1 server) and CD4+ T-cell (NetMHCIIpan-4.0 server and Tepitool) epitope prediction. Three peptides containing multiple CD8+ and CD4+ T-cell and B-cell epitopes were identified on basis of consensus prediction approach. Peptides displayed good antigenicity score of 0.45-0.68 and predicted to bind with diverse human leukocyte antigen (HLA) alleles. Molecular docking was performed with epitopes to HLA and HLA-epitopes complex to T-cell receptor (TCR). In most of the cases, docked complex of HLA-epitope and HLA-epitopes-TCR have the binding energy close to respective natural bound peptide complex with HLA and TCR. Molecular dynamic simulation also revealed that HLA-peptide complexes have minimum fluctuation and deviation than HLA-peptide-TCR docked over 50ns simulation run. Considering these findings, identified peptides can serve as potential vaccine candidates for CCHFV disease.