Chapter title |
High Dimensional Cytometry of Central Nervous System Leukocytes During Neuroinflammation
|
---|---|
Chapter number | 22 |
Book title |
Inflammation
|
Published in |
Methods in molecular biology, January 2017
|
DOI | 10.1007/978-1-4939-6786-5_22 |
Pubmed ID | |
Book ISBNs |
978-1-4939-6784-1, 978-1-4939-6786-5
|
Authors |
Dunja Mrdjen, Felix J. Hartmann, Burkhard Becher |
Editors |
Björn E. Clausen, Jon D. Laman |
Abstract |
Autoimmune diseases like multiple sclerosis (MS) develop from the activation and complex interactions of a wide network of immune cells, which penetrate the central nervous system (CNS) and cause tissue damage and neurological deficits. Experimental autoimmune encephalomyelitis (EAE) is a model used to study various aspects of MS, including the infiltration of autoaggressive T cells and pathogenic, inflammatory myeloid cells into the CNS. Various signature landscapes of immune cell infiltrates have proven useful in shedding light on the causes of specific EAE symptoms in transgenic mice. However, single cell analysis of these infiltrates has thus far been limited in conventional fluorescent flow cytometry methods by 14-16 parameter staining panels. With the advent of mass cytometry and metal-tagged antibodies, a staining panel of 35-45 parameters is now possible. With the aid of dimensionality reducing and clustering algorithms to visualize and analyze this high dimensional data, this allows for a more comprehensive picture of the different cell populations in an inflamed CNS, at a single cell resolution level. Here, we describe the induction of active EAE in C56BL/6 mice and, in particular, the staining of microglia and CNS invading immune cells for mass cytometry with subsequent data visualization and analysis. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | 2% |
Unknown | 45 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 12 | 26% |
Researcher | 8 | 17% |
Student > Master | 7 | 15% |
Student > Postgraduate | 4 | 9% |
Professor | 4 | 9% |
Other | 5 | 11% |
Unknown | 6 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Immunology and Microbiology | 11 | 24% |
Neuroscience | 7 | 15% |
Agricultural and Biological Sciences | 6 | 13% |
Medicine and Dentistry | 4 | 9% |
Biochemistry, Genetics and Molecular Biology | 3 | 7% |
Other | 6 | 13% |
Unknown | 9 | 20% |