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Single Cell Protein Analysis

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Cover of 'Single Cell Protein Analysis'

Table of Contents

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    Book Overview
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    Chapter 1 Single-Cell Western Blotting
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    Chapter 2 A Microfluidic Device for Immunoassay-Based Protein Analysis of Single E. coli Bacteria
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    Chapter 3 Enzyme-Linked ImmunoSpot (ELISpot) for Single-Cell Analysis
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    Chapter 4 Single Cell Protein Analysis
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    Chapter 5 Single Cell Protein Analysis
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    Chapter 6 Microfluidic Flow Cytometry for Single-Cell Protein Analysis
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    Chapter 7 Microfluidic Image Cytometry for Single-Cell Phenotyping of Human Pluripotent Stem Cells
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    Chapter 8 Characterizing Phenotypes and Signaling Networks of Single Human Cells by Mass Cytometry.
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    Chapter 9 Multiplexed Peptide-MHC Tetramer Staining with Mass Cytometry.
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    Chapter 10 Imaging and Mapping of Tissue Constituents at the Single-Cell Level Using MALDI MSI and Quantitative Laser Scanning Cytometry
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    Chapter 11 SPLIFF: A Single-Cell Method to Map Protein-Protein Interactions in Time and Space.
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    Chapter 12 Microfluidic Proximity Ligation Assay for Profiling Signaling Networks with Single-Cell Resolution
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    Chapter 13 Dynamics and Interactions of Individual Proteins in the Membrane of Single, Living Cells
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    Chapter 14 Microfluidics-Enabled Enzyme Activity Measurement in Single Cells
  16. Altmetric Badge
    Chapter 15 Microfluidic Chemical Cytometry for Enzyme Assays of Single Cells
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    Chapter 16 Quantitative Detection of Nucleocytoplasmic Transport of Native Proteins in Single Cells
Attention for Chapter 11: SPLIFF: A Single-Cell Method to Map Protein-Protein Interactions in Time and Space.
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Chapter title
SPLIFF: A Single-Cell Method to Map Protein-Protein Interactions in Time and Space.
Chapter number 11
Book title
Single Cell Protein Analysis
Published in
Methods in molecular biology, January 2015
DOI 10.1007/978-1-4939-2987-0_11
Pubmed ID
Book ISBNs
978-1-4939-2986-3, 978-1-4939-2987-0
Authors

Dünkler, Alexander, Rösler, Reinhild, Kestler, Hans A, Moreno-Andrés, Daniel, Johnsson, Nils, Alexander Dünkler, Reinhild Rösler, Hans A. Kestler, Daniel Moreno-Andrés, Nils Johnsson

Abstract

Protein interactions occur at certain times and at specific cellular places. The past years have seen a massive accumulation of binary protein-protein interaction data. The rapid increase of this context-free information necessitates robust methods to monitor protein interactions with temporal and spatial resolution in single cells. We have developed a simple split-ubiquitin-based method (SPLIFF) that uses the ratio of two fluorescent reporters as a signal for protein-protein interactions. One protein of the pair of interest is attached to the linear fusion of mCherry, the C-terminal half of ubiquitin, and GFP (mCherry-Cub-GFP). The other potential binding partner is expressed as a C-terminal fusion to the N-terminal half of ubiquitin (Nub). Upon co-expression the interaction between the two proteins of interest induces the reassociation of Nub and Cub to the native-like ubiquitin. GFP is subsequently cleaved from the C-terminus of Cub and degraded whereas the red-fluorescent mCherry stays attached to the Cub-fusion protein. We first implemented this method in the model yeast Saccharomyces cerevisiae. One fusion protein is expressed in cells of the a-mating type and the complementary fusion protein in cells of the α-mating type. Upon mixing, both cell types fuse and the Nub- and Cub-fusion proteins are free to interact. The red and green fluorescence is monitored by two-channel fluorescence time-lapse microcopy. The moment of cell fusion defines the start of the analysis. The calculated ratio of green to red fluorescence allows mapping the spatiotemporal interaction profiles of the investigated proteins in single cells.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 43%
Student > Ph. D. Student 5 36%
Student > Bachelor 3 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 8 57%
Biochemistry, Genetics and Molecular Biology 5 36%
Engineering 1 7%

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 07 November 2015.
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#5,575,303
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Outputs from Methods in molecular biology
#3,066
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#167,790
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Outputs of similar age from Methods in molecular biology
#232
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