A combined dataset of human cerebrospinal fluid proteins identified by multi-dimensional chromatography and tandem mass spectrometry

Sheng Pan, David Zhu, Joseph F. Quinn, Elaine R. Peskind, Thomas J. Montjne, Biaoyang Lin, David R. Goodlett, Greg Taylor, Jimmy Eng, Jing Zhang

Research output: Contribution to journalArticle

101 Scopus citations

Abstract

Human cerebrospinal fluid (CSF) is an important source for studying protein biomarkers of age-related neurodegenerative diseases. Before characterizing biomarkers unique to each disease, it is necessary to categorize CSF proteins systematically and extensively. However, the enormous complexity, great dynamic range of protein concentrations, and tremendous protein heterogeneity due to post-translational modification of CSF create significant challenges to the existing proteomics technologies for an in-depth, nonbiased profiling of the human CSF proteome. To circumvent these difficulties, in the last few years, we have utilized several different separation methodologies and mass spectrometric platforms that greatly enhanced the identification coverage and the depth of protein profiling of CSF to characterize CSF proteome. In total, 2594 proteins were identified in well-characterized pooled human CSF samples using stringent proteomics criteria. This report summarizes our efforts to comprehensively characterize the human CSF proteome to date.

Original languageEnglish (US)
Pages (from-to)469-473
Number of pages5
JournalProteomics
Volume7
Issue number3
DOIs
StatePublished - Feb 1 2007

Keywords

  • Alzheimer's disease
  • Human cerebrospinal fluid
  • Mass spectrometry
  • Parkinson's disease

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology

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    Pan, S., Zhu, D., Quinn, J. F., Peskind, E. R., Montjne, T. J., Lin, B., Goodlett, D. R., Taylor, G., Eng, J., & Zhang, J. (2007). A combined dataset of human cerebrospinal fluid proteins identified by multi-dimensional chromatography and tandem mass spectrometry. Proteomics, 7(3), 469-473. https://doi.org/10.1002/pmic.200600756