Proteotyping: Tandem Mass Spectrometry Shotgun Proteomic Characterization and Typing of Pathogenic Microorganisms
Kapitel i bok, 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
Författare
Roger Karlsson
Sahlgrenska universitetssjukhuset
Nanoxis Consulting AB
Lucia Gonzales-Siles
Göteborgs universitet
Fredrik Boulund
Chalmers, Matematiska vetenskaper, Matematisk statistik
Åsa Lindgren
Sahlgrenska universitetssjukhuset
Göteborgs universitet
Liselott Svensson-Stadler
Sahlgrenska universitetssjukhuset
Göteborgs universitet
Anders Karlsson
Nanoxis Consulting AB
Erik Kristiansson
Chalmers, Matematiska vetenskaper, Tillämpad matematik och statistik
Edward R.B. Moore
Göteborgs universitet
Sahlgrenska universitetssjukhuset
MALDI‐TOF and Tandem MS for Clinical Microbiology
419-450
9781118960226 (ISBN)
Ämneskategorier
Bioinformatik (beräkningsbiologi)
Medicinsk genetik
Bioinformatik och systembiologi
DOI
10.1002/9781118960226.ch16