Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

High-throughput determination of the antigen specificities of T cell receptors in single cells

ABSTRACT: High-throughput determination of the antigen specificities of T cell receptors in single cells

PROVIDER: PRJNA488855 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

High-throughput determination of the antigen specificities of T cell receptors in single cells

Project description:High-throughput determination of the antigen specificities of T cell receptors in single cells

| PRJNA488856 | ENA

High-Throughput Determination of the Antigen Specificities of T cell Receptors in Single Cells

Project description:<p>High-throughput linking of T cell receptor (TCR) sequences to their binding antigens is vital for immune profiling, yet challenging. We present Tetramer associated TCR Sequencing (TetTCR-Seq) to address this challenge. Binding is determined using a library of DNA-barcoded antigen tetramers that are rapidly and inexpensively generated using an in vitro transcription/translation platform. We included CMV+ donors (CMV seropositive donors who are infected with Cytomegalovirus) to screen for CMV specific TCRs.</p>

| phs001678 | dbGaP

High-throughput determination of the antigen specificities of T cell receptors in single cells.

Project description: Not available

| S-EPMC6728224 | biostudies-literature

Clinical study on diagnosis of colorectal cancer based on high-throughput tumor antigen polypeptides screening

Project description:Interventions: Gold Standard:Pathological diagnosis;Index test:high-throughput tumor antigen polypeptides screening Primary outcome(s): Diagnostic accuracy Study Design: Factorial

| 2704426 | ecrin-mdr-crc

Clinical study on individualized and precise immunotherapy for colorectal cancer based on high-throughput tumor antigen polypeptides screening

Project description:Interventions: therapy group:Individualized and precise immunotherapy for colorectal cancer based on high-throughput tumor antigen polypeptides screening Primary outcome(s): Incidence of adverse events;Progression free survival Study Design: Single arm

| 2705817 | ecrin-mdr-crc

High-throughput profiling of antigen-specific antibody secreting cells using an antibody secretion trap (TRAPnSeq)

Project description:Following activation by cognate antigen, B cells undergo fine-tuning of their antigen receptors and may ultimately differentiate into antibody-secreting cells (ASCs). While antigen-specific antibodies from B cell receptor (BCR) expressing B cells can be readily cloned and sequenced following flow sorting, antigen-specific plasma cells that lack surface BCR cannot be easily profiled in a high-throughput way. Here, we report an approach, TRAPnSeq (antigen specificity mapping through Ig secretionTRAPandSequencing), that allows capture of secreted antibodies on the surface of ASCs, which in turn enables high-throughput screening of single ASCs against large antigen panels and recovery of paired VH:VL antibody sequences. This approach incorporates flow cytometry, standard microfluidic platforms and DNA barcoding technologies to isolate and characterize antigen-specific ASCs through single cell V(D)J, RNA and antigen barcode sequencing. We show the utility of TRAPnSeq by profiling antigen-specific IgG and IgE plasma cells from mouse and humans and validate antigen binding by ELISA. TRAPnSeq can easily be combined with existing B cell platforms to accelerate antibody discovery from ASCs and can further be expanded to any protein secreting-cells.

2023-07-07 | GSE233507 | GEO

Identification of heptanal receptors in mouse olfactory epithelium by a high-throughput in vivo method

Project description:We present heptanal receptors identified using a high-throughput in vivo method (Jiang et al., 2015)

2017-06-12 | GSE87695 | GEO

Optimizing High-Throughput Shotgun Immunoproteomics for Antigen Identification

Project description:Identification of individual proteins (i.e., antigens) which initiate and/or perpetuate adaptive immune responses has potential to greatly impact pre-clinical and clinical work across numerous fields. To date, however, the methodologies available to identify antigens responsible for driving adaptive immune responses have been plagued by numerous issues which have drastically limited their widespread adoption. Therefore, in this study, we sought to optimize a shotgun immunoproteomics approach to alleviate these persistent issues and create a high-throughput, quantitative methodology for antigen identification. Three individual components of a previously published approach, namely the protein extraction, antigen elution, and LC-MS/MS analysis steps, were optimized in a systematic manner. These studies determined that preparation of protein extracts using a one-step tissue disruption method in immunoprecipitation (IP) buffer, eluting antigens from affinity chromatography columns with 1% trifluoroacetic acid (TFA), and TMT-labeling & multiplexing equal volumes of eluted samples for LC-MS/MS analysis, resulted in quantitative longitudinal antigen identification, with reduced variability between replicates and increased total number of antigens identified. This optimized pipeline provides a multiplexed, highly reproducible, and fully quantitative approach to antigen identification which is broadly applicable to determine the role of antigenic proteins in inciting (i.e. primary antigens) and perpetuating (i.e., secondary antigens) a wide range of diseases.

2023-04-18 | PXD038761 | Pride

Quantitative modeling of transcription factor binding specificities using DNA shape

Project description:Accurate predictions of the DNA binding specificities of transcription factors (TFs) are necessary for understanding gene regulatory mechanisms. Traditionally, predictive models are built based on nucleotide sequence features. Here, we employed three- dimensional DNA shape information obtained on a high-throughput basis to integrate intuitive DNA structural features into the modeling of TF binding specificities using support vector regression. We performed quantitative predictions of DNA binding specificities, using the DREAM5 dataset for 65 mouse TFs and genomic-context protein binding microarray data for three human basic helix-loop-helix TFs. DNA shape-augmented models compared favorably with sequence-based models for these predictions. Although both k-mer and DNA shape features encoded the interdependencies between nucleotide positions of the binding site, using DNA shape features reduced the dimensionality of the feature space compared to k-mer use. Finally, analyzing the weights of DNA shape-augmented models uncovered TF family- specific structural readout mechanisms that were not obvious from the nucleotide sequence.

2014-11-04 | GSE59845 | GEO

Human coronary plaque T cells are clonally expanded and display cross-reacting viral/self-antigen specificities

Project description:Human coronary plaque T cells are clonally expanded and display cross-reacting viral/self-antigen specificities

| PRJNA807924 | ENA