Proteotyping: Tandem Mass Spectrometry Shotgun Proteomic Characterization and Typing of Pathogenic Microorganisms
Book chapter, 2016
Proteotyping provides the means to identify and quantify the actual expression patterns of proteins and their associated pathways, which provides a more accurate picture of infectious agents and their pathogenic potential. Proteotyping, as an analytical method, is intimately correlated with genotypic or genomic data and offers an approach for a holistic characterization of microorganisms. Bioinformatics is vital for the analysis of the data generated by shotgun proteomics. This chapter describes the complete bioinformatics workflow necessary for proteotyping. Mass spectrometry (MS)-based shotgun proteomics analyses offer more detailed and comprehensive analyses of microorganisms. Two approaches may be applied: the so-called top-down and bottom-up proteomics. A major driver for the development and use of tandem MS and proteotyping in clinical settings will be the rapidly growing databases of whole genome reference sequences, which will refine microbial phylogeny and provide a foundation for proteomics-based identification.
Proteomics-based identification
Microbial phylogeny
Pathogenic microorganisms
Shotgun proteomic characterization
Wholegenome reference sequences
Bioinformatics workflow
Proteotyping
Tandem mass spectrometry
Author
Roger Karlsson
Sahlgrenska University Hospital
Nanoxis Consulting AB
Lucia Gonzales-Siles
University of Gothenburg
Fredrik Boulund
Chalmers, Mathematical Sciences, Mathematical Statistics
Åsa Lindgren
Sahlgrenska University Hospital
University of Gothenburg
Liselott Svensson-Stadler
Sahlgrenska University Hospital
University of Gothenburg
Anders Karlsson
Nanoxis Consulting AB
Erik Kristiansson
Chalmers, Mathematical Sciences, Applied Mathematics and Statistics
Edward R.B. Moore
University of Gothenburg
Sahlgrenska University Hospital
MALDI‐TOF and Tandem MS for Clinical Microbiology
419-450
9781118960226 (ISBN)
Subject Categories
Bioinformatics (Computational Biology)
Medical Genetics
Bioinformatics and Systems Biology
DOI
10.1002/9781118960226.ch16