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Quantitative proteomics of microbes: Principles and applications to virulence

Malmstroem, Lars; Malmström, Johan LU and Aebersold, Ruedi (2011) In Proteomics 11(15). p.2947-2956
Abstract
The rapidly increasing ability to sequence complete genomes of different microbial species and strains provides us with information regarding their genetic variability. Genetic variability is a mechanism for human pathogens to adapt to and avoid the immune system and to also develop resistance to antibiotics. However, the assessment of the contributions of individual genetic differences to resistance or other phenotypes is not a priori apparent from the genomic variability. Quantitative proteomics can provide accurate molecular phenotypes of microbes that are difficult to determine using alternative technologies. Over the recent few years we and others have developed a range of proteomic technologies for the quantitative analysis of... (More)
The rapidly increasing ability to sequence complete genomes of different microbial species and strains provides us with information regarding their genetic variability. Genetic variability is a mechanism for human pathogens to adapt to and avoid the immune system and to also develop resistance to antibiotics. However, the assessment of the contributions of individual genetic differences to resistance or other phenotypes is not a priori apparent from the genomic variability. Quantitative proteomics can provide accurate molecular phenotypes of microbes that are difficult to determine using alternative technologies. Over the recent few years we and others have developed a range of proteomic technologies for the quantitative analysis of microbial proteomes. Here, we describe the most commonly used techniques and discuss their strengths and weaknesses and illustrate their respective performance for the identification of virulence factors in Streptococcus pyogenes. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Label-free quantification, Microbes, Microbiology, MS, Selected, reaction monitoring, Targeted proteomics
in
Proteomics
volume
11
issue
15
pages
2947 - 2956
publisher
John Wiley & Sons
external identifiers
  • wos:000293269100003
  • scopus:79960419835
ISSN
1615-9861
DOI
10.1002/pmic.201100088
language
English
LU publication?
yes
id
51d76520-52c6-4f48-b04b-5704920b8bc7 (old id 2071719)
date added to LUP
2011-08-29 12:41:32
date last changed
2017-04-23 03:21:38
@article{51d76520-52c6-4f48-b04b-5704920b8bc7,
  abstract     = {The rapidly increasing ability to sequence complete genomes of different microbial species and strains provides us with information regarding their genetic variability. Genetic variability is a mechanism for human pathogens to adapt to and avoid the immune system and to also develop resistance to antibiotics. However, the assessment of the contributions of individual genetic differences to resistance or other phenotypes is not a priori apparent from the genomic variability. Quantitative proteomics can provide accurate molecular phenotypes of microbes that are difficult to determine using alternative technologies. Over the recent few years we and others have developed a range of proteomic technologies for the quantitative analysis of microbial proteomes. Here, we describe the most commonly used techniques and discuss their strengths and weaknesses and illustrate their respective performance for the identification of virulence factors in Streptococcus pyogenes.},
  author       = {Malmstroem, Lars and Malmström, Johan and Aebersold, Ruedi},
  issn         = {1615-9861},
  keyword      = {Label-free quantification,Microbes,Microbiology,MS,Selected,reaction monitoring,Targeted proteomics},
  language     = {eng},
  number       = {15},
  pages        = {2947--2956},
  publisher    = {John Wiley & Sons},
  series       = {Proteomics},
  title        = {Quantitative proteomics of microbes: Principles and applications to virulence},
  url          = {http://dx.doi.org/10.1002/pmic.201100088},
  volume       = {11},
  year         = {2011},
}