| Chapter title |
Skeletal Muscle Regeneration in the Mouse
|
|---|---|
| Chapter number | 12 |
| Book title |
Skeletal Muscle Regeneration in the Mouse
|
| Published in |
Methods in molecular biology, January 2016
|
| DOI | 10.1007/978-1-4939-3810-0_12 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-3808-7, 978-1-4939-3810-0
|
| Authors |
Arpke, Robert W, Kyba, Michael, Robert W. Arpke, Michael Kyba Ph.D., Michael Kyba |
| Editors |
Michael Kyba |
| Abstract |
In response to muscle damage, satellite cells proliferate and undertake both differentiation and self-renewal, generating new functional muscle tissue and repopulating this new muscle with stem cells for future injury responses. For many questions relating to the physiological regulation of satellite cells, quantitative readouts of self-renewal and differentiation can be very useful. There is a particular need for a quantitative assay for satellite cell self-renewal that does not rely solely upon sectioning, staining and counting cells in sections. In this chapter, we provide detailed methods for quantifying the self-renewal and differentiation potential of a given population of satellite cells using an assay involving transplantation into injured, regenerating muscle together with specific markers for donor cell identity and state of differentiation. In particular, using the Pax7-ZsGreen transgene as a marker of satellite cell state, self-renewal can be quantified by FACS on transplanted muscle to actually count the total number of resident satellite cells at time points following transplantation. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 19 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 21% |
| Other | 3 | 16% |
| Student > Bachelor | 3 | 16% |
| Student > Ph. D. Student | 3 | 16% |
| Professor | 1 | 5% |
| Other | 2 | 11% |
| Unknown | 3 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 9 | 47% |
| Computer Science | 2 | 11% |
| Unspecified | 1 | 5% |
| Psychology | 1 | 5% |
| Physics and Astronomy | 1 | 5% |
| Other | 2 | 11% |
| Unknown | 3 | 16% |