Chapter title |
Pull-Down with a c-di-GMP-Specific Capture Compound Coupled to Mass Spectrometry as a Powerful Tool to Identify Novel Effector Proteins.
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Chapter number | 28 |
Book title |
c-di-GMP Signaling
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Published in |
Methods in molecular biology, January 2017
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DOI | 10.1007/978-1-4939-7240-1_28 |
Pubmed ID | |
Book ISBNs |
978-1-4939-7239-5, 978-1-4939-7240-1
|
Authors |
Laventie, Benoît-Joseph, Glatter, Timo, Jenal, Urs, Benoît-Joseph Laventie, Timo Glatter, Urs Jenal |
Abstract |
Capture compound technology coupled to mass spectrometry (CCMS) allows to biochemically identify ligand receptors. Using a c-di-GMP-specific Capture Compound, we adapted this method for the identification and characterization of c-di-GMP binding proteins in any bacterial species. Because in silico analysis often fails to predict novel c-di-GMP effectors, this universal method aims at better defining the cellular c-di-GMP network in a wide range of bacteria. CCMS was successfully applied in several bacterial species (Nesper et al., J Proteom 75:4874-4878, 2012; Steiner et al., EMBO J 32:354-368, 2013; Tschowri et al., Cell 158:1136-1147, 2014; Trampari et al., J Biol Chem 290:24470-24483, 2015; Rotem et al., J Bacteriol 198:127-137, 2015). To outline the detailed protocol and to illustrate its power, we use Pseudomonas aeruginosa, an opportunistic pathogen in which c-di-GMP plays a critical role in virulence and biofilm control, as an example. CCMS identified 74% (38/51) of the known or predicted components of the c-di-GMP network. |
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Unknown | 3 | 75% |
Demographic breakdown
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Members of the public | 3 | 75% |
Scientists | 1 | 25% |
Mendeley readers
Geographical breakdown
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Unknown | 20 | 100% |
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Student > Doctoral Student | 3 | 15% |
Student > Bachelor | 3 | 15% |
Student > Master | 3 | 15% |
Student > Ph. D. Student | 3 | 15% |
Researcher | 3 | 15% |
Other | 2 | 10% |
Unknown | 3 | 15% |
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Agricultural and Biological Sciences | 4 | 20% |
Chemistry | 4 | 20% |
Immunology and Microbiology | 1 | 5% |
Unspecified | 1 | 5% |
Other | 0 | 0% |
Unknown | 4 | 20% |