scholarly journals GIANA allows computationally-efficient TCR clustering and multi-disease repertoire classification by isometric transformation

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Hongyi Zhang ◽  
Xiaowei Zhan ◽  
Bo Li

AbstractSimilarity in T-cell receptor (TCR) sequences implies shared antigen specificity between receptors, and could be used to discover novel therapeutic targets. However, existing methods that cluster T-cell receptor sequences by similarity are computationally inefficient, making them impractical to use on the ever-expanding datasets of the immune repertoire. Here, we developed GIANA (Geometric Isometry-based TCR AligNment Algorithm) a computationally efficient tool for this task that provides the same level of clustering specificity as TCRdist at 600 times its speed, and without sacrificing accuracy. GIANA also allows the rapid query of large reference cohorts within minutes. Using GIANA to cluster large-scale TCR datasets provides candidate disease-specific receptors, and provides a new solution to repertoire classification. Querying unseen TCR-seq samples against an existing reference differentiates samples from patients across various cohorts associated with cancer, infectious and autoimmune disease. Our results demonstrate how GIANA could be used as the basis for a TCR-based non-invasive multi-disease diagnostic platform.

2021 ◽  
Vol 7 (20) ◽  
pp. eabf5835
Author(s):  
Wen Zhang ◽  
Peter G. Hawkins ◽  
Jing He ◽  
Namita T. Gupta ◽  
Jinrui Liu ◽  
...  

T cell receptor (TCR) antigen–specific recognition is essential for the adaptive immune system. However, building a TCR-antigen interaction map has been challenging due to the staggering diversity of TCRs and antigens. Accordingly, highly multiplexed dextramer-TCR binding assays have been recently developed, but the utility of the ensuing large datasets is limited by the lack of robust computational methods for normalization and interpretation. Here, we present a computational framework comprising a novel method, ICON (Integrative COntext-specific Normalization), for identifying reliable TCR-pMHC (peptide–major histocompatibility complex) interactions and a neural network–based classifier TCRAI that outperforms other state-of-the-art methods for TCR-antigen specificity prediction. We further demonstrated that by combining ICON and TCRAI, we are able to discover novel subgroups of TCRs that bind to a given pMHC via different mechanisms. Our framework facilitates the identification and understanding of TCR-antigen–specific interactions for basic immunological research and clinical immune monitoring.


PROTEOMICS ◽  
2009 ◽  
Vol 9 (13) ◽  
pp. 3549-3563 ◽  
Author(s):  
Masaki Matsumoto ◽  
Koji Oyamada ◽  
Hidehisa Takahashi ◽  
Takamichi Sato ◽  
Shigetsugu Hatakeyama ◽  
...  

2001 ◽  
Vol 75 (2) ◽  
pp. 1065-1071 ◽  
Author(s):  
Mineki Saito ◽  
Graham P. Taylor ◽  
Akiko Saito ◽  
Yoshitaka Furukawa ◽  
Koichiro Usuku ◽  
...  

ABSTRACT Using HLA-peptide tetrameric complexes, we isolated human T-cell lymphotrophic virus type 1 Tax peptide-specific CD8+ T cells ex vivo. Antigen-specific amino acid motifs were identified in the T-cell receptor Vβ CDR3 region of clonally expanded CD8+ T cells. This result directly confirms the importance of the CDR3 region in determining the antigen specificity in vivo.


2021 ◽  
Vol 12 ◽  
Author(s):  
Valentina Ceglia ◽  
Erin J. Kelley ◽  
Annalee S. Boyle ◽  
Sandra Zurawski ◽  
Heather L. Mead ◽  
...  

Common approaches for monitoring T cell responses are limited in their multiplexity and sensitivity. In contrast, deep sequencing of the T Cell Receptor (TCR) repertoire provides a global view that is limited only in terms of theoretical sensitivity due to the depth of available sampling; however, the assignment of antigen specificities within TCR repertoires has become a bottleneck. This study combines antigen-driven expansion, deep TCR sequencing, and a novel analysis framework to show that homologous ‘Clusters of Expanded TCRs (CETs)’ can be confidently identified without cell isolation, and assigned to antigen against a background of non-specific clones. We show that clonotypes within each CET respond to the same epitope, and that protein antigens stimulate multiple CETs reactive to constituent peptides. Finally, we demonstrate the personalized assignment of antigen-specificity to rare clones within fully-diverse uncultured repertoires. The method presented here may be used to monitor T cell responses to vaccination and immunotherapy with high fidelity.


2014 ◽  
Vol 490-491 ◽  
pp. 757-762
Author(s):  
Guo Li Ji ◽  
Long Teng Chen ◽  
Liang Liang Chen

This paper proposed a way of two-level parallel alignment based on sequence parallel vectorization with GPU acceleration on the Fermi architecture, which integrates sequence parallel vectorization, parallel k-means clustering approximate alignment and parallel Smith-Waterman algorithm. The method converts sequence alignment into vector alignment by first. Then it uses k-means alignment to divide sequences into several groups and reduce the size of sequence data. The expected accurate alignment result is achieved using parallel Smith-Waterman algorithm. The high-throughput mouse T-cell receptor (TCR) sequences were used to validate the proposed method. Under the same hardware condition, comparing to serial Smith-Waterman algorithm and CUDASW++2.0 algorithm, our method is the most efficient alignment algorithm with high alignment accuracy.


1995 ◽  
Vol 181 (3) ◽  
pp. 845-855 ◽  
Author(s):  
A H Shankar ◽  
R G Titus

In experimental murine cutaneous leishmaniasis caused by Leishmania major (Lm), the cellular determinants governing development of protective or exacerbative T cells are not well understood. We, therefore, attempted to determine the influence of T cell and non-T cell compartments on disease outcome. To this end, T cell chimeric mice were constructed using adult thymectomized lethally irradiated, bone marrow-reconstituted (ATXBM) animals of genetically resistant, C57BL/6, or susceptible, BALB/c, backgrounds. These hosts were engrafted with naive T cell populations from H-2-congenic susceptible, BALB.B6-H-2b, or resistant, C57BL/6.C-H-2d, animals, respectively. Chimeric mice were then infected with Lm, and disease outcome was monitored. BALB/c T cell chimeric mice, BALB/c ATXBM hosts given naive C57BL/6.C-H-2d T cells, resolved their infections as indicated by reductions in both lesion size and parasite numbers. Furthermore, the mice developed typical Th1 (interferon[IFN]-gamma hiinterleukin[IL]-4lo) cytokine patterns. In contrast, both sham chimeric, BALB/c ATXBM hosts given naive BALB/c T cells, and control irradiated euthymic mice succumbed to infection, producing Th2 profiles (IFN-gamma loIL-4hiIL-10hi). C57BL/6 T cell chimeras, C57BL/6 ATXBM hosts given naive BALB.B6-H-2b T cells, resolved their infections as did C57BL/6 sham chimeras and euthymic controls. Interestingly, whereas C57BL/6 control animals produced Th1 cytokines, chimeric animals progressed from Th0 (IFN-gamma hiIL-4hiIL-10hi) to Th2 (IFN-gamma loIL-4hiIL-10hi) cytokine profiles as cure ensued. Both reconstitution and chimeric status of all mice were confirmed by flow cytometry. In addition, T cell receptor V beta usage of Lm-specific blasts was determined. In all cases, V beta use was multiclonal, involving primarily V beta 2, 4, 6, 8.1, 8.2, 8.3, 10, and 14, with relative V beta frequencies differing between H-2b and H-2d animals. Most importantly, however, these differences did not segregate between cure and noncure outcomes. These findings indicate that: (a) genetic traits determining cure in Lm infection can direct disease outcome from both T cell and non-T cell compartments; (b) the presence of the curing genotype in only one compartment is sufficient to confer cure; (c) curing genotype T cells autonomously assume a Th1 cytokine profile-mediating cure; (d) noncuring genotype T cells can mediate cure in a curing environment, despite the onset of Th2 cytokine production; and lastly, (e) antigen specificity of responding T cells, as assessed by V beta T cell receptor diversity, is not a critical determinant of disease outcome.


1987 ◽  
Vol 165 (2) ◽  
pp. 279-301 ◽  
Author(s):  
S B Sorger ◽  
S M Hedrick ◽  
P J Fink ◽  
M A Bookman ◽  
L A Matis

17 T cell clones and 3 T cell lines, specific for pigeon cytochrome c, were analyzed for fine specificity and rearranged T cell receptor (TCR) gene elements. Clones of similar fine specificities were grouped into one of four phenotypes, and correlations between phenotype differences and gene usage could be made. All the lines and clones rearranged a member of the V alpha 2B4 gene family to a limited number of J alpha regions. The beta chain was made up of one of three non-cross-hybridizing V beta regions, each rearranging to only one or two J beta s. The use of alternate V beta regions could be correlated with phenotype differences, which were manifested either as MHC- or MHC and antigen-specificity changes. In addition, the presence of alloreactivity, which defined a phenotype difference, could be correlated solely with the use of an alternate J alpha region. These observations were substantiated by prospective analyses of pigeon cytochrome c-specific T cell lines that were selected for alternate MHC specificity or alloreactivity and were found to express the correlated alpha and beta chain rearrangements. Previously, the TCR DNA sequences from two clones, each representing a variant of one phenotype, showed sequence differences only in the N regions of their TCR genes. Since only these two variants, using identical V alpha-J alpha and V beta-J beta gene elements, were repeatedly observed in this study, we would predict that the junctional diversity differences are selectable. In this T cell response, all the gene elements involved in the generation of diversity appear to be selected, and may therefore be important in the determination of TCR specificity. This high degree of receptor gene selection represents a fundamental difference from the diversity seen in several extensively analyzed antibody responses.


1999 ◽  
Vol 68 (1) ◽  
pp. 141-149 ◽  
Author(s):  
Bimalangshu Dey ◽  
Yong-Guang Yang ◽  
Frederic Preffer ◽  
Akira Shimizu ◽  
Kirsten Swenson ◽  
...  

2020 ◽  
Author(s):  
Shiyu Wang ◽  
Longlong Wang ◽  
Ya Liu

AbstractCD4+ T cells are key components of adaptive immunity. The cell differentiation equips CD4+ T cells with new functions. However, the effect of cell differentiation on T cell receptor (TCR) repertoire is not investigated. Here, we examined the features of TCR beta (TCRB) repertoire of the top clones within naïve, memory and regular T cell (Treg) subsets: repertoire structure, gene usage, length distribution and sequence composition. First, we found that memory subsets and Treg would be discriminated from naïve by the features of TCRB repertoire. Second, we found that the correlations between the features of memory subsets and naïve were positively related to differentiation levels of memory subsets. Third, we found that public clones presented a reduced proportion and a skewed sequence composition in differentiated subsets. Furthermore, we found that public clones led naïve to recognize a broader spectrum of antigens than other subsets. Our findings suggest that TCRB repertoire of CD4+ T cell subsets is skewed in a differentiation-depended manner. Our findings show that the variations of public clones contribute to these changes. Our findings indicate that the reduce of public clones in differentiation trim the antigen specificity of CD4+ T cells. The study unveils the physiological effect of memory formation and facilitates the selection of proper CD4+ subset for cellular therapy.


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