DECODING THE INTERACTIONS BETWEEN T CELL RECEPTORS AND PEPTIDE-MHC

解码 T 细胞受体和肽-MHC 之间的相互作用

• 批准号: 10682160
• 负责人: Paul G. Thomas
• 金额: $ 89.07万
• 依托单位: ST. JUDE CHILDREN'S RESEARCH HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-06-20 至 2028-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10682160
• 关键词: 3-Dimensional; Address; Antigens; Award; Binding; Biological; Cells; Collaborations; Collection; Complex; Data; Data Set; Databases; Diagnostic; Epitopes; Gene Expression; Genetic Transcription; Goals; Human; Immune; Immunologist; Individual; Infection; Libraries; Major Histocompatibility Complex; Methods; Modeling; Nature; Pathologic; Peptide Receptor; Peptide/MHC Complex; Peptides; Peripheral Blood Mononuclear Cell; Productivity; Proteins; Protocols documentation; Recording of previous events; Reporting; Sampling; Source; Specificity; Structure; T Chain; T-Cell Antigen Receptor Specificity; T-Cell Receptor; TCR Activation; Therapeutic; Training; Work; cohort; combinatorial; complex data; computer framework; experimental study; improved; innovation; novel; novel strategies; pathogen; prediction algorithm; predictive modeling; programs; protein protein interaction; receptor; tool

Summary Conventional ɑβ T cell receptor (TCR) recognition of a cognate peptide-Major Histocompatibility Complex (pMHC) is central to adaptive immune recognition of pathogens and pathologically associated self-proteins. Despite substantial progress in structural prediction of protein-protein interactions with tools such as AlphaFold and RoseTTAFold, de novo prediction of TCR specificity (target pMHC) from TCR sequence has not yet been realized. Indeed, within the largest databases of curated TCR specificities, only ~105 unique TCR:pMHC assignments have been curated, and these are focused on <100 unique pMHC epitopes. In our previous work, we established that >200 unique receptors recognizing the same epitope are required to confidently predict whether a previously unobserved receptor belongs to the same specificity group. This work demonstrates that once data are sufficiently dense, local prediction of specificity becomes feasible. It follows that the current sparse nature of the available data is the major restriction to advancing the field. Thus, our central hypothesis is that advancing predictive models for TCR specificity requires a dramatic increase in the magnitude and diversity of curated TCR-pMHC data, which in turn requires new approaches for generating such useful data sets. In three Aims, we will address major limitations of the current epitope discovery and TCR characterization pipelines. In Aim 1, we will improve methods for relating single chain TCR sequences to specific peptides for generating large libraries of well-curated TCRα or TCRβ associations with individual epitopes. In addition to supporting our central goal, these data will have significant independent utility for immune profiling and diagnostics. In Aim 2, we will establish methods for assigning paired chain TCRɑβ data from single cell experiments to epitope pools, extending our recently reported reverse epitope discovery pipeline. Aim 3 will integrate public data and the data generated in Aims 1 and 2, with novel structural and computational approaches to generate improved de novo specificity prediction algorithms. These Aims will be accomplished by accessing our collection of longitudinally sampled PBMCs from >4000 humans across well-curated cohorts from diverse ancestries and infection histories.

总结

项目成果

The expanding role of systems immunology in decoding the T cell receptor repertoire.

• DOI: 10.1016/j.coisb.2018.09.005
• 发表时间: 2018-09
• 期刊: Current opinion in systems biology
• 影响因子: 3.7
• 作者: Vanessa Venturi;P. Thomas

A Cell for the Ages: Human γδ T Cells across the Lifespan.

• DOI: 10.3390/ijms21238903
• 发表时间: 2020-11-24
• 期刊: International journal of molecular sciences
• 影响因子: 5.6
• 作者: Clark BL;Thomas PG
• 通讯作者: Thomas PG

Immune responses in COVID-19 respiratory tract and blood reveal mechanisms of disease severity.

COVID-19 呼吸道和血液中的免疫反应揭示了疾病严重程度的机制。

• DOI: 10.21203/rs.3.rs-802084/v1
• 发表时间: 2021
• 期刊: Research square
• 作者: Zhang,Wuji;Chua,Brendon;Selva,Kevin;Kedzierski,Lukasz;Ashhurst,Thomas;Haycroft,Ebene;Shoffner,Suzanne;Hensen,Luca;Boyd,David;James,Fiona;Mouhtouris,Effie;Kwong,Jason;Chua,Kyra;Drewett,George;Copaescu,Ana;Dobson,Julie;Rowntr
• 通讯作者: Rowntr

Integrating T cell receptor sequences and transcriptional profiles by clonotype neighbor graph analysis (CoNGA).

• DOI: 10.1038/s41587-021-00989-2
• 发表时间: 2022-01
• 期刊: Nature biotechnology
• 影响因子: 46.9
• 作者: Schattgen SA;Guion K;Crawford JC;Souquette A;Barrio AM;Stubbington MJT;Thomas PG;Bradley P
• 通讯作者: Bradley P

Immune cellular networks underlying recovery from influenza virus infection in acute hospitalized patients.

• DOI: 10.1038/s41467-021-23018-x
• 发表时间: 2021-05-11
• 期刊: Nature communications
• 影响因子: 16.6
• 作者: Nguyen THO;Koutsakos M;van de Sandt CE;Crawford JC;Loh L;Sant S;Grzelak L;Allen EK;Brahm T;Clemens EB;Auladell M;Hensen L;Wang Z;Nüssing S;Jia X;Günther P;Wheatley AK;Kent SJ;Aban M;Deng YM;Laurie KL;Hurt AC;Gras S;Rossjohn J;Crowe J;Xu J;Jackson D;Brown LE;La Gruta N;Chen W;Doherty PC;Turner SJ;Kotsimbos TC;Thomas PG;Cheng AC;Kedzierska K
• 通讯作者: Kedzierska K