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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
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    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 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 title
Imaging and Mapping of Tissue Constituents at the Single-Cell Level Using MALDI MSI and Quantitative Laser Scanning Cytometry
Chapter number 10
Book title
Single Cell Protein Analysis
Published in
Methods in molecular biology, January 2015
DOI 10.1007/978-1-4939-2987-0_10
Pubmed ID
Book ISBNs
978-1-4939-2986-3, 978-1-4939-2987-0

Catherine M. Rawlins, Joseph P. Salisbury, Daniel R. Feldman, Sinan Isim, Nathalie Y. R. Agar, Ed Luther, Jeffery N. Agar


For nearly a century, histopathology involved the laborious morphological analyses of tissues stained with broad-spectrum dyes (i.e., eosin to label proteins). With the advent of antibody-labeling, immunostaining (fluorescein and rhodamine for fluorescent labeling) and immunohistochemistry (DAB and hematoxylin), it became possible to identify specific immunological targets in cells and tissue preparations. Technical advances, including the development of monoclonal antibody technology, led to an ever-increasing palate of dyes, both fluorescent and chromatic. This provides an incredibly rich menu of molecular entities that can be visualized and quantified in cells-giving rise to the new discipline of Molecular Pathology. We describe the evolution of two analytical techniques, cytometry and mass spectrometry, which complement histopathological visual analysis by providing automated, cellular-resolution constituent maps. For the first time, laser scanning cytometry (LSC) and matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) are combined for the analysis of tissue sections. The utility of the marriage of these techniques is demonstrated by analyzing mouse brains with neuron-specific, genetically encoded, fluorescent proteins. We present a workflow that: (1) can be used with or without expensive matrix deposition methods, (2) uses LSC images to reveal the diverse landscape of neural tissue as well as the matrix, and (3) uses a tissue fixation method compatible with a DNA stain. The proposed workflow can be adapted for a variety of sample preparation and matrix deposition methods.

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 50%
Student > Ph. D. Student 1 13%
Student > Master 1 13%
Professor > Associate Professor 1 13%
Student > Postgraduate 1 13%
Other 0 0%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 2 25%
Agricultural and Biological Sciences 2 25%
Neuroscience 2 25%
Medicine and Dentistry 1 13%
Chemistry 1 13%
Other 0 0%