Defining pluripotent stem cells through quantitative proteomic analysis

Sonja Reiland, Ghasem Hosseini Salekdeh, Jeroen Krijgsveld*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

26 Citations (Scopus)


Embryonic stem cells (ESCs) are at the center stage of intense research, inspired by their potential to give rise to all cell types of the adult individual. This property makes ESCs suitable candidates for generating specialized cells to replace damaged tissue lost after injury or disease. However, such clinical applications require a detailed insight of the molecular mechanisms underlying the self-renewal, expansion and differentiation of stem cells. This has gained further relevance since the introduction of induced pluripotent stem cells (iPSCs), which are functionally very similar to ESCs. The key property that iPSCs can be derived from somatic cells lifts some of the major ethical issues related to the need for embryos to generate ESCs. Yet, this has only increased the need to define the similarity of iPSCs and ESCs at the molecular level, both before and after they are induced to differentiate. In this article, we describe the proteomic approaches that have been used to characterize ESCs with regard to self-renewal and differentiation, with an emphasis on signaling cascades and histone modifications. We take this as a lead to discuss how quantitative proteomics can be deployed to study reprogramming and iPSC identity. In addition, we discuss how emerging proteomic technologies can become a useful tool to monitor the (de)differentiation status of ESCs and iPSCs.

Original languageEnglish
Pages (from-to)29-42
Number of pages14
JournalExpert Review of Proteomics
Issue number1
Publication statusPublished - 1 Feb 2011
Externally publishedYes


  • cell surface marker
  • chromatin dynamics
  • differentiation
  • embryonic stem cell
  • induced pluripotent stem cell
  • mass spectrometry
  • phosphoproteome
  • post-translational modifications
  • protein quantification
  • proteomics
  • regenerative medicine


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