Chapter title |
A Simplified Workflow for Protein Quantitation of Rat Brain Tissues Using Label-Free Proteomics and Spectral Counting.
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Chapter number | 36 |
Book title |
Injury Models of the Central Nervous System
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Published in |
Methods in molecular biology, January 2016
|
DOI | 10.1007/978-1-4939-3816-2_36 |
Pubmed ID | |
Book ISBNs |
978-1-4939-3814-8, 978-1-4939-3816-2
|
Authors |
Angela M. Boutté, Shonnette F. Grant, Jitendra R. Dave |
Editors |
Firas H. Kobeissy, C. Edward Dixon, Ronald L. Hayes, Stefania Mondello |
Abstract |
Mass spectrometry-based proteomics is an increasingly valuable tool for determining relative or quantitative protein abundance in brain tissues. A plethora of technical and analytical methods are available, but straightforward and practical approaches are often needed to facilitate reproducibility. This aspect is particularly important as an increasing number of studies focus on models of traumatic brain injury or brain trauma, for which brain tissue proteomes have not yet been fully described. This text provides suggested techniques for robust identification and quantitation of brain proteins by using molecular weight fractionation prior to mass spectrometry-based proteomics. Detailed sample preparation and generalized protocols for chromatography, mass spectrometry, spectral counting, and normalization are described. The rat cerebral cortex isolated from a model of blast-overpressure was used as an exemplary source of brain tissue. However, these techniques may be adapted for lysates generated from several types of cells or tissues and adapted by the end user. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 14 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 4 | 29% |
Student > Master | 2 | 14% |
Professor | 2 | 14% |
Unspecified | 1 | 7% |
Student > Bachelor | 1 | 7% |
Other | 1 | 7% |
Unknown | 3 | 21% |
Readers by discipline | Count | As % |
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Neuroscience | 2 | 14% |
Agricultural and Biological Sciences | 2 | 14% |
Chemical Engineering | 1 | 7% |
Unspecified | 1 | 7% |
Other | 2 | 14% |
Unknown | 4 | 29% |