System-Wide Temporal Characterization of the Proteome and Phosphoproteome of Human Embryonic Stem Cell Differentiation

Kristoffer T. G. Rigbolt, Tatyana A. Prokhorova, Vyacheslav Akimov, Jeanette Henningsen, Pia T. Johansen, Irina Kratchmarova, Moustapha Kassem, Matthias Mann, Jesper V. Olsen,* Blagoy Blagoev*

*To whom correspondence should be addressed. E-mail: bab{at}bmb.sdu.dk (B.B.); jesper.olsen{at}cpr.ku.dk (J.V.O.)

This PDF file includes:

• Materials and Methods
• Fig. S1. Cells treated with NCM or PMA differentiate in a nondirected manner.
• Fig. S2. General properties of the data sets.
• Fig. S3. Frequency of protein and phosphorylation site identifications with selected GO Molecular Function and Cellular Component terms.
• Fig. S4. Dynamic changes in phosphorylation organized by phosphorylation motif.
• Fig. S5. Double-phosphorylation motifs.
• Fig. S6. The S-score algorithm.
• Fig. S7. Quantitative proteomics approach for identification of DNMT3A- and DNMT3B-interacting proteins.
• Table S8. Primers used for real-time QPCR.
• References
  

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Other Supplementary Material for this manuscript includes the following:

• Table S1 (Microsoft Excel format). Protein identifications.
• Table S2 (Microsoft Excel format). Phosphorylation site identifications.
• Table S3 (Microsoft Excel format). Protein and phosphorylation site identifications for 30-min and 6-hour biological replicas.
• Table S4 (Microsoft Excel format). Identified transcription factors and transcription factor phosphorylation sites.
• Table S5 (Microsoft Excel format). Linear phosphorylation motifs.
• Table S6 (Microsoft Excel format). Identified kinases and kinase phosphorylation sites.
• Table S7 (Microsoft Excel format). Protein identifications from DNMT3A and DNMT3B immunoprecipitations.

[Download Tables S1 to S7 (Compressed)]

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© 2011 American Association for the Advancement of Science