Antigen Identification for Orphan T Cell Receptors Expressed on Tumor-Infiltrating Lymphocytes DOI Creative Commons
Marvin H. Gee, Arnold Han,

Shane Lofgren

et al.

Cell, Journal Year: 2017, Volume and Issue: 172(3), P. 549 - 563.e16

Published: Dec. 21, 2017

Highlights•Development of a human leukocyte antigen library for TCR ligand identification•Single-cell sequencing and phenotyping T cells infiltrating colon cancer•Ligand discovery four tumor-derived cell receptors•Identification shared non-mutated tumor between two patientsSummaryThe immune system can mount responses against tumors; however, the specificities tumor-infiltrating lymphocytes (TILs) are not well understood. We used yeast-display libraries peptide-human (pHLA) to screen antigens "orphan" receptors (TCRs) expressed on TILs from colorectal adenocarcinoma. Four TIL-derived TCRs exhibited strong selection peptides presented in highly diverse pHLA-A∗02:01 library. Three TIL were specific self-antigens, which present separate patient tumors, specificity self-antigen derived U2AF2. These results show that exposed recognition surface MHC-bound accessible contains sufficient structural information enable reconstruction sequences peptide targets pathogenic unknown specificity. This finding underscores surprising their cognate enables facile indentification through unbiased screening.Graphical abstract

Language: Английский

Harnessing the plasticity of CD4+ T cells to treat immune-mediated disease DOI
Michel DuPage, Jeffrey A. Bluestone

Nature reviews. Immunology, Journal Year: 2016, Volume and Issue: 16(3), P. 149 - 163

Published: Feb. 15, 2016

Language: Английский

Citations

449
Single-cell analysis reveals T cell infiltration in old neurogenic niches DOI
Ben W. Dulken,

Matthew T. Buckley,

Paloma Navarro Negredo

et al.

Nature, Journal Year: 2019, Volume and Issue: 571(7764), P. 205 - 210

Published: July 3, 2019

Language: Английский

Citations

442
Combinatorial labeling of single cells for gene expression cytometry DOI
H. Christina Fan,

Glenn K. Fu,

Stephen P. A. Fodor

et al.

Science, Journal Year: 2015, Volume and Issue: 347(6222)

Published: Feb. 5, 2015

We present a technically simple approach for gene expression cytometry combining next-generation sequencing with stochastic barcoding of single cells. A combinatorial library beads bearing cell- and molecular-barcoding capture probes is used to uniquely label transcripts reconstruct the digital profile thousands individual cells in experiment without need robotics or automation. applied technology dissect human hematopoietic system characterize heterogeneous response vitro stimulation. High sensitivity demonstrated by detection low-abundance rare Under current implementation, technique can analyze few thousand simultaneously readily scale 10,000s 100,000s

Language: Английский

Citations

440
Microbiotas from Humans with Inflammatory Bowel Disease Alter the Balance of Gut Th17 and RORγt+ Regulatory T Cells and Exacerbate Colitis in Mice DOI Creative Commons
Graham J. Britton, Eduardo J. Contijoch, Ilaria Mogno

et al.

Immunity, Journal Year: 2019, Volume and Issue: 50(1), P. 212 - 224.e4

Published: Jan. 1, 2019

Language: Английский

Citations

428
T cell fate and clonality inference from single-cell transcriptomes DOI
Michael J. T. Stubbington, Tapio Lönnberg, Valentina Proserpio

et al.

Nature Methods, Journal Year: 2016, Volume and Issue: 13(4), P. 329 - 332

Published: March 7, 2016

Language: Английский

Citations

422
Analyzing the Mycobacterium tuberculosis immune response by T-cell receptor clustering with GLIPH2 and genome-wide antigen screening DOI
Huang Huang, Chunlin Wang,

Florian Rubelt

et al.

Nature Biotechnology, Journal Year: 2020, Volume and Issue: 38(10), P. 1194 - 1202

Published: April 27, 2020

Language: Английский

Citations

369
Heterogeneity of Human CD4+T Cells Against Microbes DOI
Federica Sallusto

Annual Review of Immunology, Journal Year: 2016, Volume and Issue: 34(1), P. 317 - 334

Published: May 11, 2016

CD4 + T helper (Th) cells play a central role in the adaptive immune response by providing help to B and cytotoxic releasing different types of cytokines tissues mediate protection against wide range pathogenic microorganisms. These functions are performed Th endowed with distinct migratory capacities effector functions. Here we discuss how studies human cell microbes have advanced our understanding functional heterogeneity, particular discovery Th1 subset involved Mycobacteria characterization two Th17 specific for extracellular bacteria or fungi. We also review new approaches dissect at clonal level induced pathogens vaccines that revealed an unexpected degree intraclonal diversification propose progressive selective model differentiation.

Language: Английский

Citations

310
Large-scale detection of antigen-specific T cells using peptide-MHC-I multimers labeled with DNA barcodes DOI
Amalie Kai Bentzen, Andrea Marion Marquard, Rikke Lyngaa

et al.

Nature Biotechnology, Journal Year: 2016, Volume and Issue: 34(10), P. 1037 - 1045

Published: Aug. 29, 2016

Language: Английский

Citations

298
Circulating and Tissue-Resident CD4+ T Cells With Reactivity to Intestinal Microbiota Are Abundant in Healthy Individuals and Function Is Altered During Inflammation DOI Creative Commons
Ahmed N. Hegazy, Nathaniel R. West, Michael J. T. Stubbington

et al.

Gastroenterology, Journal Year: 2017, Volume and Issue: 153(5), P. 1320 - 1337.e16

Published: Aug. 4, 2017

Interactions between commensal microbes and the immune system are tightly regulated maintain intestinal homeostasis, but little is known about these interactions in humans. We investigated responses of human CD4

Language: Английский

Citations

291
scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses DOI Creative Commons
Juexin Wang, Anjun Ma, Yuzhou Chang

et al.

Nature Communications, Journal Year: 2021, Volume and Issue: 12(1)

Published: March 25, 2021

Abstract Single-cell RNA-sequencing (scRNA-Seq) is widely used to reveal the heterogeneity and dynamics of tissues, organisms, complex diseases, but its analyses still suffer from multiple grand challenges, including sequencing sparsity differential patterns in gene expression. We introduce scGNN (single-cell graph neural network) provide a hypothesis-free deep learning framework for scRNA-Seq analyses. This formulates aggregates cell–cell relationships with networks models heterogeneous expression using left-truncated mixture Gaussian model. integrates three iterative multi-modal autoencoders outperforms existing tools imputation cell clustering on four benchmark datasets. In an Alzheimer’s disease study 13,214 single nuclei postmortem brain successfully illustrated disease-related development mechanism. provides effective representation relationships. It also powerful that can be applied general

Language: Английский

Citations

291