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Proteomics

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Cover of 'Proteomics'

Table of Contents

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    Book Overview
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    Chapter 1 A Robust Protocol for Protein Extraction and Digestion
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    Chapter 2 Improving Proteome Coverage and Sample Recovery with Enhanced FASP (eFASP) for Quantitative Proteomic Experiments
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    Chapter 3 Proteome Characterization of a Chromatin Locus Using the Proteomics of Isolated Chromatin Segments Approach
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    Chapter 4 Profiling Cell Lines Nuclear Sub-proteome
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    Chapter 5 Optimized Enrichment of Phosphoproteomes by Fe-IMAC Column Chromatography
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    Chapter 6 Full Membrane Protein Coverage Digestion and Quantitative Bottom-Up Mass Spectrometry Proteomics
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    Chapter 7 Hydrophilic Strong Anion Exchange (hSAX) Chromatography Enables Deep Fractionation of Tissue Proteomes
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    Chapter 8 High pH Reversed-Phase Micro-Columns for Simple, Sensitive, and Efficient Fractionation of Proteome and (TMT labeled) Phosphoproteome Digests
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    Chapter 9 Multi-Lectin Affinity Chromatography for Separation, Identification, and Quantitation of Intact Protein Glycoforms in Complex Biological Mixtures
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    Chapter 10 Parallel Exploration of Interaction Space by BioID and Affinity Purification Coupled to Mass Spectrometry
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    Chapter 11 LUMIER: A Discovery Tool for Mammalian Protein Interaction Networks
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    Chapter 12 Dual-Color, Multiplex Analysis of Protein Microarrays for Precision Medicine
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    Chapter 13 Quantitative Proteomics Using SILAC
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    Chapter 14 Relative Protein Quantification Using Tandem Mass Tag Mass Spectrometry
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    Chapter 15 Pathway-Informed Discovery and Targeted Proteomic Workflows Using Mass Spectrometry
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    Chapter 16 Generation of High-Quality SWATH® Acquisition Data for Label-free Quantitative Proteomics Studies Using TripleTOF® Mass Spectrometers
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    Chapter 17 Annotating Mutational Effects on Proteins and Protein Interactions: Designing Novel and Revisiting Existing Protocols
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    Chapter 18 Protein Micropatterning Assay: Quantitative Analysis of Protein–Protein Interactions
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    Chapter 19 Designing Successful Proteomics Experiments
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    Chapter 20 Automated SWATH Data Analysis Using Targeted Extraction of Ion Chromatograms
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    Chapter 21 Virtualization of Legacy Instrumentation Control Computers for Improved Reliability, Operational Life, and Management
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    Chapter 22 Statistical Assessment of QC Metrics on Raw LC-MS/MS Data
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    Chapter 23 Data Conversion with ProteoWizard msConvert
Attention for Chapter 13: Quantitative Proteomics Using SILAC
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Chapter title
Quantitative Proteomics Using SILAC
Chapter number 13
Book title
Proteomics
Published in
Methods in molecular biology, February 2017
DOI 10.1007/978-1-4939-6747-6_13
Pubmed ID
Book ISBNs
978-1-4939-6745-2, 978-1-4939-6747-6
Authors

Kian Kani

Editors

Lucio Comai, Jonathan E. Katz, Parag Mallick

Abstract

The ability to enumerate all of the proteins in a cell is quickly becoming a reality. Quantitative proteomics adds an extra dimension to proteome-wide discovery experiments by enabling differential measurements of protein concentrations, characterization of protein turnover, increased stringency of co-immunoprecipitation reactions, as well as many other intriguing applications. One of the most widely used techniques that enable relative protein quantitation is stable isotope labeling by amino acids in cell culture (SILAC) (Ong et al., Mol Cell Proteomics 1(5):376-386, 2002). Over the past decade, SILAC has become the preferred approach for proteome-wide quantitation by mass spectrometry. This approach relies on the metabolic incorporation of isotopically enriched amino acids into the proteome of cells-the proteome of "light" ((1)H, (12)C, (14)N) cells can then be compared to "heavy" ((2)H, (13)C, (15)N) cells as the isotopically labeled proteins and peptides are easily distinguished in a mass spectrometer. Since cellular uptake and response to isotopically different amino acid(s) is naïve, it is without impact on cell physiology. We provide a detailed step-by-step procedure for performing SILAC-based experiment for proteome-wide quantitation in this chapter.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 33%
Student > Master 4 17%
Researcher 3 13%
Student > Bachelor 3 13%
Professor > Associate Professor 2 8%
Other 2 8%
Unknown 2 8%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 29%
Agricultural and Biological Sciences 4 17%
Medicine and Dentistry 3 13%
Chemistry 3 13%
Immunology and Microbiology 2 8%
Other 3 13%
Unknown 2 8%