br Results br Discussion The

Results
Discussion The dataset allows a well-defined comparison of protein abundance and phosphorylation in pluripotent LDN193189 and the earliest definitive hNSCs. This contrasts with previous studies that used hESCs and heterogeneous mixtures of differentiated progeny (Brill et al., 2009; Rigbolt et al., 2011; Van Hoof et al., 2009), or hESCs only (Swaney et al., 2009). Another study compared hESCs and hiPSCs, reporting 6,761 proteins and 19,122 phosphorylation sites (Phanstiel et al., 2011). A proteomic analysis of the membrane fraction of hESCs and heterogeneous cells enriched for NSCs, derived by EB differentiation, yielded 5,105 proteins and 8,560 phosphorylation sites (Melo-Braga et al., 2014). In contrast, we used whole-cell lysates from hESCs and their hNSC derivatives at high purity under feeder-free conditions. Importantly, we did not passage the cells during hNSC induction, so as to capture unperturbed (phospho)proteomic profiles when pluripotent cells transition to the neural lineage. We report nearly 13,000 proteins (Figure 2A), most of which were phosphorylated at nearly 60,000 non-redundant sites (Table S1), revealing a striking depth of (phospho)proteomes and biological pathways. The dataset contains most previously published (phospho)proteins in hPSCs, plus more not reported in those studies (Figures S7E–S7H). In addition, our results suggest previously unknown reproducibility of the hPSC phosphoproteome via comparison with these datasets. Phosphorylated transcription factors are prominent in hESCs (Brill et al., 2009; Rigbolt et al., 2011; Van Hoof et al., 2009). Our current dataset represents progress toward comprehensive (phospho)proteomic mapping of transcription factors. Rigbolt et al. (2011) found that 83.8% of 216 detected transcription factors were phosphorylated. Similarly, 75.1% of the 487 transcription factors in our dataset were phosphorylated. OCT4 phosphorylation on pT234 and pS235 disrupts its binding to DNA (Brumbaugh et al., 2012). Phosphorylation sites pT225 and pY291 (Table S15A), to the best of our knowledge, have not been identified previously on OCT4. Our dataset also contains two phosphorylation sites on NANOG (pS10 and pS52). In addition, 12 phosphorylation sites were detected on SOX2, five of which were not reported previously (pY2, pT7, pT17 or pS18, pS257, and pS290). These and other examples suggest the importance of post-translational regulation of transcription factors, which is understudied. Dual SMAD inhibition and modulation of WNT signaling is important for neural conversion of hPSCs, as indicated previously (Chambers et al., 2009; Hasegawa et al., 2012) and by the present study (Figure 1A). NPTX1 plays a role in neural lineage specification from hESCs by reducing NODAL and BMP signaling (Boles et al., 2014), suggesting that NPTX1 further contributes to dual SMAD inhibition (Chambers et al., 2009). However, it remained unclear whether neural induction is regulated by other signals. The secreted protein MDK is an instructive component of neural lineage entry (Figure 7E). Blocking MDK by genetic knockdown and a monoclonal antibody provided independent evidence for a mechanism by which feedforward upregulation of MDK promotes neural induction, consistent with MDK resulting in specific upregulation of PAX6 (Figures 6 and 7). MDK may act through a receptor complex that can include ALK, PTPRZ1, LRP1, and SDC1 (Kadomatsu et al., 2013; Muramatsu, 2011). PTPRZ1 was more abundant in hESCs, whereas LRP1 was more abundant in hNSCs (Figure 7E). Although MDK was reported 26 years ago (Tomomura et al., 1990), MDK and its receptors remain understudied. Hence, the finding that MDK plays a role in PSC differentiation requires detailed follow-up studies. Collectively, our methods and dataset are resources to leverage diverse studies including further elucidation of pluripotency, differentiation, and reprogramming. The dataset may also prove useful for comparison with stem cells from non-mammalian models. For example, orthologs of all proteins in the COP9 complex in Drosophila germline stem cells (Pan et al., 2014) are in our dataset. We highlighted several analyses that the dataset enables and provided proof of principle for its predictive value. We make this resource freely available to the scientific community as curated tables, an interactive website (www.pluriprot.org), and raw data in the Peptide Atlas database (Institute for Systems Biology).