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Neuroproteomics

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Cover of 'Neuroproteomics'

Table of Contents

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    Book Overview
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    Chapter 1 Neuroproteomics Studies: Challenges and Updates
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    Chapter 2 Progress and Potential of Imaging Mass Spectrometry Applied to Biomarker Discovery
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    Chapter 3 Biofluid Proteomics and Biomarkers in Traumatic Brain Injury
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    Chapter 4 Degradomics in Neurotrauma: Profiling Traumatic Brain Injury
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    Chapter 5 Evolving Relevance of Neuroproteomics in Alzheimer’s Disease
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    Chapter 6 Genome to Phenome: A Systems Biology Approach to PTSD Using an Animal Model
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    Chapter 7 Photoaffinity Labeling of Pentameric Ligand-Gated Ion Channels: A Proteomic Approach to Identify Allosteric Modulator Binding Sites
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    Chapter 8 Quantitative Phosphoproteomic Analysis of Brain Tissues
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    Chapter 9 Glycoproteins Enrichment and LC-MS/MS Glycoproteomics in Central Nervous System Applications
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    Chapter 10 A Novel 2-DE-Based Proteomic Analysis to Identify Multiple Substrates for Specific Protease in Neuronal Cells
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    Chapter 11 Neuroproteomic Profiling of Cerebrospinal Fluid (CSF) by Multiplexed Affinity Arrays
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    Chapter 12 Isolation and Proteomic Analysis of Microvesicles and Exosomes from HT22 Cells and Primary Neurons
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    Chapter 13 Combined MALDI Mass Spectrometry Imaging and Parafilm-Assisted Microdissection-Based LC-MS/MS Workflows in the Study of the Brain
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    Chapter 14 De Novo and Uninterrupted SILAC Labeling of Primary Microglia
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    Chapter 15 Spike-In SILAC Approach for Proteomic Analysis of Ex Vivo Microglia
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    Chapter 16 A Proteomic Evaluation of Sympathetic Activity Biomarkers of the Hypothalamus-Pituitary-Adrenal Axis by Western Blotting Technique Following Experimental Traumatic Brain Injury
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    Chapter 17 Efficient and Accurate Algorithm for Cleaved Fragments Prediction (CFPA) in Protein Sequences Dataset Based on Consensus and Its Variants: A Novel Degradomics Prediction Application
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    Chapter 18 Effect of Second-Hand Tobacco Smoke on the Nitration of Brain Proteins: A Systems Biology and Bioinformatics Approach
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    Chapter 19 An Advanced Omic Approach to Identify Co-Regulated Clusters and Transcription Regulation Network with AGCT and SHOE Methods
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    Chapter 20 AutoDock and AutoDockTools for Protein-Ligand Docking: Beta-Site Amyloid Precursor Protein Cleaving Enzyme 1(BACE1) as a Case Study
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    Chapter 21 An Integration of Decision Tree and Visual Analysis to Analyze Intracranial Pressure
Attention for Chapter 15: Spike-In SILAC Approach for Proteomic Analysis of Ex Vivo Microglia
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Chapter title
Spike-In SILAC Approach for Proteomic Analysis of Ex Vivo Microglia
Chapter number 15
Book title
Neuroproteomics
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-6952-4_15
Pubmed ID
Book ISBNs
978-1-4939-6950-0, 978-1-4939-6952-4
Authors

Joao Paulo Costa Pinho, Harris Bell-Temin, Bin Liu, Stanley M. Stevens Jr., Stanley M. Stevens

Editors

Firas H. Kobeissy, Stanley M. Stevens, Jr.

Abstract

Stable isotope labeling by amino acids in cell culture (SILAC) is a versatile mass spectrometry-based proteomic approach that can achieve accurate relative protein quantitation on a global scale. In this approach, proteins are labeled while being synthesized by the cell due to the presence of certain amino acids exclusively as heavier mass analogs than their regular (light) counterparts. This differential labeling allows for the identification of heavy and light forms of each peptide corresponding to two or more different experimental groups upon mass spectrometric analysis, the intensities of which reflect their abundance in the sample analyzed. Relative quantitation is straightforward when SILAC labeling efficiency is high (>99%) and the same cell proteome is used as the quantitation reference, which is typically the case for immortalized cell lines. However, the SILAC methodology for the proteomic analysis of primary cells isolated after in vivo experimentation is more challenging given the low labeling efficiency that would be achieved post-isolation. Alternatively, a stable-isotope-labeled cell line representing the cell type can be used as an internal standard (spike-in SILAC); however, adequate representation of the primary cell proteome with the stable-isotope-labeled internal standard may limit overall protein quantitation, especially for cell types that exhibit a broad range of phenotypes such as microglia, the resident immune cells in the brain. Here, we present a way to circumvent this limitation by combining multiple phenotypes of a single-cell type (the immortalized mouse BV2 microglial cell line) into a single spike-in standard using primary mouse microglia as our model system. We describe the preparation of media, incorporation of labels, induction of four different activation states (plus resting), isolation of primary microglia from adult mice brains, preparation of lysates for analysis, and general guidelines for data processing.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 57%
Researcher 1 14%
Student > Ph. D. Student 1 14%
Unknown 1 14%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 43%
Immunology and Microbiology 1 14%
Medicine and Dentistry 1 14%
Unknown 2 29%