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Bacterial Cell Wall Homeostasis

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Cover of 'Bacterial Cell Wall Homeostasis'

Table of Contents

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    Book Overview
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    Chapter 1 Bacterial Cell Wall Homeostasis
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    Chapter 2 Ultra-Sensitive, High-Resolution Liquid Chromatography Methods for the High-Throughput Quantitative Analysis of Bacterial Cell Wall Chemistry and Structure.
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    Chapter 3 Bacterial Cell Wall Homeostasis
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    Chapter 4 Cell Shaving and False-Positive Control Strategies Coupled to Novel Statistical Tools to Profile Gram-Positive Bacterial Surface Proteomes.
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    Chapter 5 Differential Proteomics Based on Multidimensional Protein Identification Technology to Understand the Biogenesis of Outer Membrane of Escherichia coli.
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    Chapter 6 Bacterial Cell Wall Homeostasis
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    Chapter 7 Zymographic Techniques for the Analysis of Bacterial Cell Wall in Bacillus.
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    Chapter 8 Liquid Chromatography-Tandem Mass Spectrometry to Define Sortase Cleavage Products.
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    Chapter 9 Genetics and Cell Morphology Analyses of the Actinomyces oris srtA Mutant.
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    Chapter 10 Bacterial Cell Wall Homeostasis
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    Chapter 11 Luciferase Reporter Gene System to Detect Cell Wall Stress Stimulon Induction in Staphylococcus aureus.
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    Chapter 12 Bacterial Cell Wall Homeostasis
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    Chapter 13 Continuous Fluorescence Assay for Peptidoglycan Glycosyltransferases.
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    Chapter 14 Analysis of Peptidoglycan Fragment Release.
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    Chapter 15 Bacterial Cell Wall Homeostasis
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    Chapter 16 Analysis of Bacterial Cell Surface Chemical Composition Using Cryogenic X-Ray Photoelectron Spectroscopy.
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    Chapter 17 Biophysical Measurements of Bacterial Cell Shape.
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    Chapter 18 Bacterial Cell Wall Homeostasis
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    Chapter 19 Structural Comparison and Simulation of Pneumococcal Peptidoglycan Hydrolase LytB.
Attention for Chapter 4: Cell Shaving and False-Positive Control Strategies Coupled to Novel Statistical Tools to Profile Gram-Positive Bacterial Surface Proteomes.
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Chapter title
Cell Shaving and False-Positive Control Strategies Coupled to Novel Statistical Tools to Profile Gram-Positive Bacterial Surface Proteomes.
Chapter number 4
Book title
Bacterial Cell Wall Homeostasis
Published in
Methods in molecular biology, January 2016
DOI 10.1007/978-1-4939-3676-2_4
Pubmed ID
Book ISBNs
978-1-4939-3674-8, 978-1-4939-3676-2

Nestor Solis, Stuart J. Cordwell


Hee-Jeon Hong


A powerful start to the discovery and design of novel vaccines, and for better understanding of host-pathogen interactions, is to profile bacterial surfaces using the proteolytic digestion of surface-exposed proteins under mild conditions. This "cell shaving" approach has the benefit of both identifying surface proteins and their surface-exposed epitopes, which are those most likely to interact with host cells and/or the immune system, providing a comprehensive overview of bacterial cell topography. An essential requirement for successful cell shaving is to account for (or minimize) cellular lysis that can occur during the shaving procedure and thus generate data that is biased towards non-surface (e.g., cytoplasmic) proteins. This is further complicated by the presence of "moonlighting" proteins, which are proteins predicted to be intracellular but with validated surface or extracellular functions. Here, we describe an optimized cell shaving protocol for Gram-positive bacteria that uses proteolytic digestion and a "false-positive" control to reduce the number of intracellular contaminants in these datasets. Released surface-exposed peptides are analyzed by liquid chromatography (LC) coupled to high-resolution tandem mass spectrometry (MS/MS). Additionally, the probabilities of proteins being surface exposed can be further calculated by applying novel statistical tools.

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 22%
Student > Doctoral Student 2 22%
Researcher 2 22%
Student > Ph. D. Student 1 11%
Unknown 2 22%
Readers by discipline Count As %
Immunology and Microbiology 2 22%
Agricultural and Biological Sciences 1 11%
Nursing and Health Professions 1 11%
Pharmacology, Toxicology and Pharmaceutical Science 1 11%
Medicine and Dentistry 1 11%
Other 0 0%
Unknown 3 33%