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Bacterial Pathogenesis

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Cover of 'Bacterial Pathogenesis'

Table of Contents

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    Book Overview
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    Chapter 1 Protein-Based Strategies to Identify and Isolate Bacterial Virulence Factors.
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    Chapter 2 Analysis of Bacterial Surface Interactions with Mass Spectrometry-Based Proteomics.
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    Chapter 3 Differential Radial Capillary Action of Ligand Assay (DRaCALA) for High-Throughput Detection of Protein-Metabolite Interactions in Bacteria.
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    Chapter 4 Identifying Bacterial Immune Evasion Proteins Using Phage Display.
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    Chapter 5 Competition for Iron Between Host and Pathogen: A Structural Case Study on Helicobacter pylori.
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    Chapter 6 Common Challenges in Studying the Structure and Function of Bacterial Proteins: Case Studies from Helicobacter pylori.
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    Chapter 7 Development of a Single Locus Sequence Typing (SLST) Scheme for Typing Bacterial Species Directly from Complex Communities.
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    Chapter 8 Reconstructing the Ancestral Relationships Between Bacterial Pathogen Genomes.
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    Chapter 9 Making Fluorescent Streptococci and Enterococci for Live Imaging.
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    Chapter 10 Computer Vision-Based Image Analysis of Bacteria.
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    Chapter 11 Assessing Vacuolar Escape of Listeria Monocytogenes.
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    Chapter 12 Immobilization Techniques of Bacteria for Live Super-resolution Imaging Using Structured Illumination Microscopy.
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    Chapter 13 Negative Staining and Transmission Electron Microscopy of Bacterial Surface Structures.
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    Chapter 14 Detection of Intracellular Proteins by High-Resolution Immunofluorescence Microscopy in Streptococcus pyogenes.
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    Chapter 15 Antibody Guided Molecular Imaging of Infective Endocarditis.
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    Chapter 16 The Zebrafish as a Model for Human Bacterial Infections.
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    Chapter 17 Determining Platelet Activation and Aggregation in Response to Bacteria.
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    Chapter 18 Killing Bacteria with Cytotoxic Effector Proteins of Human Killer Immune Cells: Granzymes, Granulysin, and Perforin.
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    Chapter 19 In Vitro and In Vivo Biofilm Formation by Pathogenic Streptococci.
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    Chapter 20 Murine Mycobacterium marinum Infection as a Model for Tuberculosis.
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    Chapter 21 Generating and Purifying Fab Fragments from Human and Mouse IgG Using the Bacterial Enzymes IdeS, SpeB and Kgp.
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    Chapter 22 Measuring Antibody Orientation at the Bacterial Surface.
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    Chapter 23 Toward Clinical use of the IgG Specific Enzymes IdeS and EndoS against Antibody-Mediated Diseases.
Attention for Chapter 4: Identifying Bacterial Immune Evasion Proteins Using Phage Display.
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Chapter title
Identifying Bacterial Immune Evasion Proteins Using Phage Display.
Chapter number 4
Book title
Bacterial Pathogenesis
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-6673-8_4
Pubmed ID
Book ISBNs
978-1-4939-6671-4, 978-1-4939-6673-8
Authors

Cindy Fevre, Lisette Scheepmaker, Pieter-Jan Haas

Editors

Pontus Nordenfelt, Mattias Collin

Abstract

Methods aimed at identification of immune evasion proteins are mainly rely on in silico prediction of sequence, structural homology to known evasion proteins or use a proteomics driven approach. Although proven successful these methods are limited by a low efficiency and or lack of functional identification. Here we describe a high-throughput genomic strategy to functionally identify bacterial immune evasion proteins using phage display technology. Genomic bacterial DNA is randomly fragmented and ligated into a phage display vector that is used to create a phage display library expressing bacterial secreted and membrane bound proteins. This library is used to select displayed bacterial secretome proteins that interact with host immune components.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 20%
Researcher 2 20%
Student > Master 2 20%
Student > Bachelor 1 10%
Librarian 1 10%
Other 0 0%
Unknown 2 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 20%
Veterinary Science and Veterinary Medicine 1 10%
Arts and Humanities 1 10%
Computer Science 1 10%
Immunology and Microbiology 1 10%
Other 1 10%
Unknown 3 30%