| Chapter title |
Single-Cell Analysis of T-Cell Receptor αβ Repertoire.
|
|---|---|
| Chapter number | 15 |
| Book title |
Immunosenescence
|
| Published in |
Methods in molecular biology, January 2015
|
| DOI | 10.1007/978-1-4939-2963-4_15 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-2962-7, 978-1-4939-2963-4
|
| Authors |
Dash, Pradyot, Wang, George C, Thomas, Paul G, Pradyot Dash, George C. Wang, Paul G. Thomas, Wang, George C., Thomas, Paul G. |
| Abstract |
The unbiased, paired analysis of T-cell receptor (TCR) α- and β-chain usage at the single-cell level provides a valuable window of understanding into the TCR repertoire and the nature of the immune response. Earlier technologies for TCR repertoire analysis were often limited to examining TCR complementarity-determining region 3 (CDR3) β expression or required in vitro cloning procedures that can artificially skew the TCR repertoire from its in vivo state. We describe here a direct ex vivo, single-cell-based strategy for the clonotypic analysis of TCRαβ repertoires that utilizes multiplexed panels of TCRα and TCRβ-specific primers in a nested PCR to amplify expressed transcripts from individual, epitope-specific T cells. This strategy yields the paired TCRαβ sequences of any given population of αβ T cells of interest. |
X Demographics
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| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 25% |
| Germany | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 30 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 17% |
| Student > Ph. D. Student | 5 | 17% |
| Student > Bachelor | 3 | 10% |
| Student > Postgraduate | 2 | 7% |
| Other | 2 | 7% |
| Other | 3 | 10% |
| Unknown | 10 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Immunology and Microbiology | 13 | 43% |
| Agricultural and Biological Sciences | 3 | 10% |
| Medicine and Dentistry | 2 | 7% |
| Chemistry | 1 | 3% |
| Engineering | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 10 | 33% |