| Chapter title |
T Cell Response in the Lung Following Influenza Virus Infection
|
|---|---|
| Chapter number | 17 |
| Book title |
T-Cell Trafficking
|
| Published in |
Methods in molecular biology, March 2017
|
| DOI | 10.1007/978-1-4939-6931-9_17 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-6929-6, 978-1-4939-6931-9
|
| Authors |
Benson, Robert A., Lawton, Jennifer C., MacLeod, Megan K. L., Robert A. Benson Ph.D., Jennifer C. Lawton Ph.D., Megan K. L. MacLeod Ph.D., Robert A. Benson, Jennifer C. Lawton, Megan K. L. MacLeod |
| Editors |
George Edward Rainger, Helen M. Mcgettrick |
| Abstract |
Methods that enable the identification of virus-specific CD4 and CD8 T cells are key to our understanding of how the adaptive immune response controls viral infection. Here we describe two distinct methods to evaluate the T cell response to influenza A virus (IAV). The number and phenotype of T cells that respond to natural IAV epitopes can be assessed by flow cytometry using MHC class I and class II tetramers. Using this system, IAV-specific T cells can be tracked in various organs within the same animal, or, in different cohorts, the response can be evaluated at several time points following infection. While providing clear quantitative data, flow cytometry cannot provide any information about T cell location within the lung or interactions between responding T cells and other cell types. Here we also describe a method to examine activated CD4 T cells in the lungs of living animals using multiphoton intravital microscopy, thus providing real-time analysis of T cell behavior during an infection. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 5 | 83% |
| Unknown | 1 | 17% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 83% |
| Scientists | 1 | 17% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 10 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 2 | 20% |
| Researcher | 2 | 20% |
| Student > Master | 2 | 20% |
| Professor | 1 | 10% |
| Unspecified | 1 | 10% |
| Other | 2 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 3 | 30% |
| Engineering | 2 | 20% |
| Agricultural and Biological Sciences | 2 | 20% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 10% |
| Psychology | 1 | 10% |
| Other | 1 | 10% |