| Chapter title |
Genetically encoded fluorescent reporters to visualize protein kinase C activation in live cells.
|
|---|---|
| Chapter number | 17 |
| Book title |
Signal Transduction Protocols
|
| Published in |
Methods in molecular biology, January 2011
|
| DOI | 10.1007/978-1-61779-160-4_17 |
| Pubmed ID | |
| Book ISBNs |
978-1-61779-159-8, 978-1-61779-160-4
|
| Authors |
Lisa L. Gallegos, Alexandra C. Newton, Gallegos, Lisa L., Newton, Alexandra C. |
| Abstract |
Protein kinase C (PKC) signaling drives many important cellular processes and its dysregulation results in pathophysiologies such as cancer (Gokmen-Polar et al., Cancer Res 61:1375-1381, 2001). Because PKC is activated acutely and allosterically, it is difficult to monitor the cellular activity of endogenous PKC by conventional methodologies (Newton, Methods Enzymol 345:499-506, 2002). Rather, PKC signaling is best studied in situ using biosensors such as FRET-based reporters. We have generated several FRET-based reporters for studying PKC signaling in real time in live cells (Violin and Newton, IUBMB Life 55:653-660, 2003). Using these reporters, we have demonstrated phase-locked oscillations in Ca2+ release and membrane-localized endogenous PKC activity in response to histamine (Violin et al., J Cell Biol 161:899-909, 2003), as well as distinct signatures of endogenous PKC signaling at specific organelles in response to uridine-5'-triphosphate (UTP; Gallegos et al., J Biol Chem 281:30947-30956, 2006). Here we describe methods to image cells expressing the reporters and elaborate on data analyses, control experiments, and variations for imaging the activity of expressed PKC. |
X Demographics
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| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 26 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 27% |
| Student > Bachelor | 4 | 15% |
| Professor | 3 | 12% |
| Student > Doctoral Student | 2 | 8% |
| Researcher | 2 | 8% |
| Other | 3 | 12% |
| Unknown | 5 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
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| Neuroscience | 5 | 19% |
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| Medicine and Dentistry | 2 | 8% |
| Chemical Engineering | 1 | 4% |
| Other | 3 | 12% |
| Unknown | 5 | 19% |