t cell receptors
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2022 ◽  
Author(s):  
Jorge Mansilla-Soto ◽  
Justin Eyquem ◽  
Sascha Haubner ◽  
Mohamad Hamieh ◽  
Judith Feucht ◽  
...  

2022 ◽  
Vol 13 (1) ◽  
Author(s):  
Daichao Wu ◽  
Alexander Kolesnikov ◽  
Rui Yin ◽  
Johnathan D. Guest ◽  
Ragul Gowthaman ◽  
...  

AbstractT cells play a vital role in combatting SARS-CoV-2 and forming long-term memory responses. Whereas extensive structural information is available on neutralizing antibodies against SARS-CoV-2, such information on SARS-CoV-2-specific T-cell receptors (TCRs) bound to their peptide–MHC targets is lacking. Here we determine the structures of a public and a private TCR from COVID-19 convalescent patients in complex with HLA-A2 and two SARS-CoV-2 spike protein epitopes (YLQ and RLQ). The structures reveal the basis for selection of particular TRAV and TRBV germline genes by the public but not the private TCR, and for the ability of the TCRs to recognize natural variants of RLQ but not YLQ. Neither TCR recognizes homologous epitopes from human seasonal coronaviruses. By elucidating the mechanism for TCR recognition of an immunodominant yet variable epitope (YLQ) and a conserved but less commonly targeted epitope (RLQ), this study can inform prospective efforts to design vaccines to elicit pan-coronavirus immunity.


2022 ◽  
Vol 82 ◽  
Author(s):  
A. Cortés ◽  
J. Coral ◽  
C. McLachlan ◽  
J. A. G. Corredor ◽  
R. Benítez

Abstract The coupling of a ligand with a molecular receptor induces a signal that travels through the receptor, reaching the internal domain and triggering a response cascade. In previous work on T-cell receptors and their coupling with foreign antigens, we observed the presence of planar molecular patterns able to generate electromagnetic fields within the proteins. These planes showed a coherent (synchronized) behavior, replicating immediately in the intracellular domain that which occurred in the extracellular domain as the ligand was coupled. In the present study, we examined this molecular transduction - the capacity of the coupling signal to penetrate deep inside the receptor molecule and induce a response. We verified the presence of synchronized behavior in diverse receptor-ligand systems. To appreciate this diversity, we present four biochemically different systems - TCR-peptide, calcium pump-ADP, haemoglobin-oxygen, and gp120-CD4 viral coupling. The confirmation of synchronized molecular transduction in each of these systems suggests that the proposed mechanism would occur in all biochemical receptor-ligand systems.


2021 ◽  
Author(s):  
Xian Xian Liu ◽  
Gloria Li ◽  
Wei Lou ◽  
Juntao Gao ◽  
Simon Fong

[Background]: An emerging type of cancer treatment, known as cell immunotherapy, is gaining popularity over chemotherapy or other radia-tion therapy that causes mass destruction to our body. One favourable ap-proach in cell immunotherapy is the use of neoantigens as targets that help our body immune system identify the cancer cells from healthy cells. Neoan-tigens, which are non-autologous proteins with individual specificity, are generated by non-synonymous mutations in the tumor cell genome. Owing to its strong immunogenicity and lack of expression in normal tissues, it is now an important target for tumor immunotherapy. Neoantigens are some form of special protein fragments excreted as a by-product on the surface of cancer cells during the DNA mutation at the tumour. In cancer immunotherapies, certain neoantigens which exist only on cancer cells elicit our white blood cells (body's defender, anti-cancer T-cell) responses that fight the cancer cells while leaving healthy cells alone. Personalized cancer vaccines there-fore can be designed de novo for each individual patient, when the specific neoantigens are found to be relevant to his/her tumour. The vaccine which is usually coded in synthetic long peptides, RNA or DNA representing the neo-antigens trigger an immune response in the body to destroy the cancer cells (tumour). The specific neoantigens can be found by a complex process of biopsy and genome sequencing. Alternatively, modern technologies nowa-days tap on AI to predict the right neoantigen candidates using algorithms. However, determining the binding and non-binding of neoantigens on T-cell receptors (TCR) is a challenging computational task due to its very large search space. [Objective]: To enhance the efficiency and accuracy of traditional deep learning tools, for serving the same purpose of finding potential responsive-ness to immunotherapy through correctly predicted neoantigens. It is known that deep learning is possible to explore which novel neoantigens bind to T-cell receptors and which ones don't. The exploration may be technically ex-pensive and time-consuming since deep learning is an inherently computa-tional method. one can use putative neoantigen peptide sequences to guide personalized cancer vaccines design. [Methods]: These models all proceed through complex feature engineering, including feature extraction, dimension reduction and so on. In this study, we derived 4 features to facilitate prediction and classification of 4 HLA-peptide binding namely AAC and DC from the global sequence, and the LAAC and LDC from the local sequence information. Based on the patterns of sequence formation, a nested structure of bidirectional long-short term memory neural network called local information module is used to extract context-based features around every residue. Another bilstm network layer called global information module is introduced above local information module layer to integrate context-based features of all residues in the same HLA-peptide binding chain, thereby involving inter-residue relationships in the training process. introduced. [Results]: Finally, a more effective model is obtained by fusing the above two modules and 4 features matric, the method performs significantly better than previous prediction schemes, whose overall r-square increased to 0.0125 and 0.1064 on train and increased to 0.0782 and 0.2926 on test da-tasets. The RMSE for our proposed models trained decreased to approxi-mately 0.0745 and 1.1034, respectively, and decreased to 0.6712 and 1.6506 on test dataset. [Conclusion]: Our work has been actively refining a machine-learning model to improve neoantigen identification and predictions with the determinants for Neoantigen identification. The final experimental results show that our method is more effective than existing methods for predicting peptide types, which can help laboratory researchers to identify the type of novel HLA-peptide binding. Keywords: machine learning; Cancer Cell Immunology; HLA-peptide binding Neoantigen Prediction; HLA; Data Visualization; Novel Neoanti-gen and TCR Pairing Discovery; Vector representation


Pharmaceutics ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 26
Author(s):  
Seth-Frerich Fobian ◽  
Ziyun Cheng ◽  
Timo L. M. ten Hagen

Cancer immunotherapy, a promising and widely applied mode of oncotherapy, makes use of immune stimulants and modulators to overcome the immune dysregulation present in cancer, and leverage the host’s immune capacity to eliminate tumors. Although some success has been seen in this field, toxicity and weak immune induction remain challenges. Liposomal nanosystems, previously used as targeting agents, are increasingly functioning as immunotherapeutic vehicles, with potential for delivery of contents, immune induction, and synergistic drug packaging. These systems are tailorable, multifunctional, and smart. Liposomes may deliver various immune reagents including cytokines, specific T-cell receptors, antibody fragments, and immune checkpoint inhibitors, and also present a promising platform upon which personalized medicine approaches can be built, especially with preclinical and clinical potentials of liposomes often being frustrated by inter- and intrapatient variation. In this review, we show the potential of liposomes in cancer immunotherapy, as well as the methods for synthesis and in vivo progression thereof. Both preclinical and clinical studies are included to comprehensively illuminate prospects and challenges for future research and application.


2021 ◽  
Author(s):  
James M Heather ◽  
Matthew J Spindler ◽  
Marta Herrero Alonso ◽  
Yifang Ivana Shui ◽  
David G Millar ◽  
...  

The study and manipulation of T cell receptors (TCRs) is central to multiple fields across basic and translational immunology research. Produced by V(D)J recombination, TCRs are often only recorded in the literature and data repositories as a combination of their V and J gene symbols, plus their hypervariable CDR3 amino acid sequence. However, numerous applications require full-length coding nucleotide sequences. Here we present Stitchr, a software tool developed to specifically address this limitation. Given minimal V/J/CDR3 information, Stitchr produces complete coding sequences representing a fully spliced TCR cDNA. Due to its modular design, Stitchr can be used for TCR engineering using either published germline or novel/modified variable and constant region sequences. Sequences produced by Stitchr were validated by synthesizing and transducing TCR sequences into Jurkat cells, recapitulating the expected antigen specificity of the parental TCR. Using a companion script, Thimble, we demonstrate that Stitchr can process a million TCRs in under ten minutes using a standard desktop personal computer. By systemizing the production and modification of TCR sequences, we propose that Stitchr will increase the speed, repeatability, and reproducibility of TCR research. Stitchr is available on GitHub.


eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Amado Carreras-Sureda ◽  
Laurence Abrami ◽  
Kim Ji-Hee ◽  
Wen-An Wang ◽  
Christopher Henry ◽  
...  

Efficient immune responses require Ca2+ fluxes across ORAI1 channels during engagement of T cell receptors (TCR) at the immune synapse (IS) between T cells and antigen presenting cells. Here, we show that ZDHHC20-mediated S-acylation of the ORAI1 channel at residue Cys143 promotes TCR recruitment and signaling at the IS. Cys143 mutations reduced ORAI1 currents and store-operated Ca2+ entry in HEK-293 cells and nearly abrogated long-lasting Ca2+ elevations, NFATC1 translocation, and IL-2 secretion evoked by TCR engagement in Jurkat T cells. The acylation-deficient channel remained in cholesterol-poor domains upon enforced ZDHHC20 expression and was recruited less efficiently to the IS along with actin and TCR. Our results establish S-acylation as a critical regulator of ORAI1 channel trafficking and function at the IS and reveal that ORAI1 S-acylation enhances TCR recruitment to the synapse.


2021 ◽  
Vol 15 (12) ◽  
pp. e0010018
Author(s):  
Angela X. Zhou ◽  
Thomas J. Scriba ◽  
Cheryl L. Day ◽  
Deanna A. Hagge ◽  
Chetan Seshadri

T cell receptors (TCRs) encode the history of antigenic challenge within an individual and have the potential to serve as molecular markers of infection. In addition to peptide antigens bound to highly polymorphic MHC molecules, T cells have also evolved to recognize bacterial lipids when bound to non-polymorphic CD1 molecules. One such subset, germline-encoded, mycolyl lipid-reactive (GEM) T cells, recognizes mycobacterial cell wall lipids and expresses a conserved TCR-ɑ chain that is shared among genetically unrelated individuals. We developed a quantitative PCR assay to determine expression of the GEM TCR-ɑ nucleotide sequence in human tissues and blood. This assay was validated on plasmids and T cell lines. We tested blood samples from South African subjects with or without tuberculin reactivity or with active tuberculosis disease. We were able to detect GEM TCR-ɑ above the limit of detection in 92% of donors but found no difference in GEM TCR-ɑ expression among the three groups after normalizing for total TCR-ɑ expression. In a cohort of leprosy patients from Nepal, we successfully detected GEM TCR-ɑ in 100% of skin biopsies with histologically confirmed tuberculoid and lepromatous leprosy. However, GEM TCR-ɑ expression was not different between leprosy patients and control subjects after normalization. Thus, GEM T cells constitute part of the T cell repertoire in the skin. Further, these results reveal the feasibility of developing a simple, field deployable molecular diagnostic based on mycobacterial lipid antigen-specific TCR sequences that are readily detectable in human tissues and blood independent of genetic background.


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