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The Ubiquitin Proteasome System

Overview of attention for book
Cover of 'The Ubiquitin Proteasome System'

Table of Contents

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    Book Overview
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    Chapter 1 Characterization of RING-Between-RING E3 Ubiquitin Transfer Mechanisms
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    Chapter 2 Single-Turnover RING/U-Box E3-Mediated Lysine Discharge Assays
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    Chapter 3 Methods for NAD-Dependent Ubiquitination Catalyzed by Legionella pneumophila Effector Proteins
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    Chapter 4 Using In Vitro Ubiquitylation Assays to Estimate the Affinities of Ubiquitin-Conjugating Enzymes for Their Ubiquitin Ligase Partners
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    Chapter 5 Competition Assay for Measuring Deubiquitinating Enzyme Substrate Affinity
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    Chapter 6 Enzymatic Assembly of Ubiquitin Chains
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    Chapter 7 Ubiquitin-Activated Interaction Traps (UBAITs): Tools for Capturing Protein-Protein Interactions
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    Chapter 8 Generating Intracellular Modulators of E3 Ligases and Deubiquitinases from Phage-Displayed Ubiquitin Variant Libraries
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    Chapter 9 Integrated Proteogenomic Approach for Identifying Degradation Motifs in Eukaryotic Cells
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    Chapter 10 A Method to Monitor Protein Turnover by Flow Cytometry and to Screen for Factors that Control Degradation by Fluorescence-Activated Cell Sorting
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    Chapter 11 E. coli-Based Selection and Expression Systems for Discovery, Characterization, and Purification of Ubiquitylated Proteins
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    Chapter 12 Strategies to Trap Enzyme-Substrate Complexes that Mimic Michaelis Intermediates During E3-Mediated Ubiquitin-Like Protein Ligation
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    Chapter 13 Small-Angle X-Ray Scattering for the Study of Proteins in the Ubiquitin Pathway
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    Chapter 14 Methods for Preparing Cryo-EM Grids of Large Macromolecular Complexes
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    Chapter 15 Recombinant Expression, Unnatural Amino Acid Incorporation, and Site-Specific Labeling of 26S Proteasomal Subcomplexes
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    Chapter 16 Native Gel Approaches in Studying Proteasome Assembly and Chaperones
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    Chapter 17 Measuring the Overall Rate of Protein Breakdown in Cells and the Contributions of the Ubiquitin-Proteasome and Autophagy-Lysosomal Pathways
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    Chapter 18 Methods to Rapidly Prepare Mammalian 26S Proteasomes for Biochemical Analysis
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    Chapter 19 Measurement of the Multiple Activities of 26S Proteasomes
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    Chapter 20 Exploring the Regulation of Proteasome Function by Subunit Phosphorylation
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    Chapter 21 Scalable In Vitro Proteasome Activity Assay
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    Chapter 22 Exploring the Rampant Expansion of Ubiquitin Proteomics
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    Chapter 23 Ubiquitin diGLY Proteomics as an Approach to Identify and Quantify the Ubiquitin-Modified Proteome
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    Chapter 24 Interpreting the Language of Polyubiquitin with Linkage-Specific Antibodies and Mass Spectrometry
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    Chapter 25 Dissecting Dynamic and Heterogeneous Proteasome Complexes Using In Vivo Cross-Linking-Assisted Affinity Purification and Mass Spectrometry
Attention for Chapter 10: A Method to Monitor Protein Turnover by Flow Cytometry and to Screen for Factors that Control Degradation by Fluorescence-Activated Cell Sorting
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Chapter title
A Method to Monitor Protein Turnover by Flow Cytometry and to Screen for Factors that Control Degradation by Fluorescence-Activated Cell Sorting
Chapter number 10
Book title
The Ubiquitin Proteasome System
Published in
Methods in molecular biology, September 2018
DOI 10.1007/978-1-4939-8706-1_10
Pubmed ID
30242708
Book ISBNs
978-1-4939-8705-4, 978-1-4939-8706-1
Authors

Sophie A. Comyn, Thibault Mayor, Comyn, Sophie A., Mayor, Thibault

Abstract

The protein quality control network consists of multiple proteins or protein complexes that monitor proteome integrity by mediating protein folding and the removal of proteins that cannot be folded. An integral component of this network is the ubiquitin-proteasome system, which controls the degradation of thousands of cellular proteins. A number of questions remain unanswered regarding the degradation of misfolded proteins. For example, how are substrates recognized and triaged? What are the identities of the components involved? And finally, what substrates are targeted by any given component of the quality control network? Finding answers to these questions is what inspires our work in protein quality control. Further characterization of protein quality control mechanisms requires methods that can reliably quantify turnover rates of model substrates. One such method is based on flow cytometry. Here, we present protocols detailing how to assess protein stability with flow cytometry and how fluorescence-activated cell sorting (FACS) can be used to screen for factors important for protein quality control and protein turnover.

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 33%
Student > Bachelor 3 25%
Researcher 2 17%
Student > Doctoral Student 2 17%
Unknown 1 8%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 67%
Agricultural and Biological Sciences 1 8%
Chemistry 1 8%
Unknown 2 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 September 2018.
All research outputs
#18,649,666
of 23,103,903 outputs
Outputs from Methods in molecular biology
#7,996
of 13,222 outputs
Outputs of similar age
#261,042
of 340,695 outputs
Outputs of similar age from Methods in molecular biology
#150
of 235 outputs
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So far Altmetric has tracked 13,222 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
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