Proteome biology of stem cells: a new joint HUPO and ISSCR initiative.

Department of Biomolecular Mass Spectrometry, Utrecht University, Sorbonnelaan 16, 3584 CA Utrecht, The Netherlands.
Molecular &amp Cellular Proteomics (Impact Factor: 7.25). 02/2008; 7(1):204-5. DOI: 10.1074/mcp.H800001-MCP200
Source: PubMed
  • Source
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Stem cell research has been widely studied over the last few years and has attracted increasing attention from researchers in all fields of medicine due to its potential to treat many previously incurable diseases by replacing damaged cells or tissues. As illustrated by hematopoietic stem research, understanding stem cell differentiation at molecular levels is essential for both basic research and for clinical applications of stem cells. Although multiple integrative analyses, such as genomics, epigenomics, transcriptomics and proteomics, are required to understand stem cell biology, proteomics has a unique position in stem cell research. For example, several major breakthroughs in HSC research were due to the identification of proteins such as colony-stimulating factors (CSFs) and cell-surface CD molecules. In 2007, the Human Proteome Organization (HUPO) and the International Society for Stem Cell Research (ISSCR) launched the joint Proteome Biology of Stem Cells Initiative. A systematic proteomics approach to understanding stem cell differentiation will shed new light on stem cell biology and accelerate clinical applications of stem cells.
    Anatomy & cell biology 03/2010; 43(1):1-14. DOI:10.5115/acb.2010.43.1.1
  • [Show abstract] [Hide abstract]
    ABSTRACT: Protein biomarkers are fundamental tools for the characterization of stem cells and for tracking their differentiation and maturation down developmental lineages. Technology development allowing increased coverage of difficult cellular proteomes should allow for the discovery of new and novel membrane protein biomarkers for use by the stem cell research community. The amphipathic and highly hydrophobic nature and relative low abundance of many membrane proteins present significant analytical challenges. These difficulties are amplified when the source material (tissue or cells) is only available in limited quantities (e.g., embryonic stem cells). Recent advances in enrichment for purer membrane fractions, the enzymatic and chemical digestion of membrane proteins in the presence of solvents or chaotropes, and the use of "shotgun" proteomics methodologies have gradually resulted in increased membrane proteome coverage with numbers of predicted integral membrane proteins now in excess of 1000 being routinely reported. We have recently demonstrated the advantages of using peptide isoelectric focusing in the first dimension on immobilized pH gradients (peptide IPG-IEF) followed by reversed phase chromatography and tandem MS to increase membrane proteome coverage. This study looked at achieving a similar level of membrane proteome coverage using modifications to reported methodologies while restricting the number of characterized human embryonic stem cells to 10(7) cells. Two-thousand two-hundred and ninety-two (2292) nonredundant proteins were identified with two or more high accuracy peptide matches from 260 mug of a human embryonic stem cell membrane enriched fraction with a false discovery rate of 0.32%. Gene Ontology (GO) mapping predicted 1279 (44.9%) of this list to be membrane proteins of which 395 proteins were predicted to be derived from the plasma membrane compartment. The TMHMM algorithm predicted 904 integral membrane proteins with up to 16 transmembrane helices. Collectively, we assert that the substantial membrane proteome coverage achieved using these procedures will enable rapid advances in the identification and quantitation of novel membrane proteins as markers of differentiation status and/or genetic mutation from relatively low numbers of cultured embryonic stem cells.
    Journal of Proteome Research 11/2009; 8(12):5642-9. DOI:10.1021/pr900597s · 5.00 Impact Factor