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
|
Authors |
Nestor Solis, Stuart J. Cordwell |
Editors |
Hee-Jeon Hong |
Abstract |
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
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 11 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 2 | 18% |
Student > Ph. D. Student | 2 | 18% |
Student > Master | 2 | 18% |
Student > Doctoral Student | 2 | 18% |
Unspecified | 1 | 9% |
Other | 0 | 0% |
Unknown | 2 | 18% |
Readers by discipline | Count | As % |
---|---|---|
Immunology and Microbiology | 2 | 18% |
Veterinary Science and Veterinary Medicine | 1 | 9% |
Unspecified | 1 | 9% |
Nursing and Health Professions | 1 | 9% |
Pharmacology, Toxicology and Pharmaceutical Science | 1 | 9% |
Other | 2 | 18% |
Unknown | 3 | 27% |