PTPN6 mediates positive feedbacks.

<p>(A to E) Model-predicted cumulative phosphorylation of the indicated pTyr sites in normal (WT) and PTPN6 KD cells. The cumulative phosphorylation of a site was calculated as the area under the corresponding time course of phosphorylation (0 to 60 s). Area is normalized to WT cells. (F to J) Simulation results (top) and immunoblots (bottom) showing the predicted and measured effects of PTPN6 KD on pTyr site dynamics. PTPN6 KD was modeled by setting the copy number of PTPN6 to 0. Simulated time courses are visualized as series of dots whose areas are proportional to relative phosphorylation levels. For each pTyr site, phosphorylation levels are normalized by the level of phosphorylation in unstimulated WT cells. Note that WT time courses present results shown previously in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0104240#pone-0104240-g002" target="_blank">Fig. 2</a>. IB, immunoblot; Quant., quantification; WCL, whole-cell lysate; Sim., simulation. (K) Hypothesized positive feedback loops involving PTPN6 incorporated in the model for TCR signaling. In these loops, LCK phosphorylates and activates PTPN6, and PTPN6 dephosphorylates sites that contribute to negative regulation of LCK. Thus, PTPN6 has a positive effect on phosphorylation events downstream of LCK, including LCK-mediated phosphorylation of ZAP70 and ZAP70-mediated phosphorylation of LAT. Blots are representative of the results from multiple (at least two) experiments. Each repeated immunoblot measurement is characterized by a coefficient of variation (CV) below 0.25, where CV is estimated as the ratio of the sample standard deviation to the sample mean.</p

Model for TCR signaling.

<p>Proteins considered in a rule-based model for TCR signaling are represented by rounded boxes. Separate boxes indicate the phosphosites considered in the model. Sites detected in phosphoproteomic experiments are each associated with a pair of heatmaps, in which the upper heatmap reflects averaged experimental measurements of relative pTyr abundance and the lower heatmap reflects simulated phosphorylation levels at matching time points. The color scale of each heatmap is unique: black represents the lowest and green represents the highest level of phosphorylation for that site. Interactions are represented by arrows according to the conventions illustrated at bottom. The number in the lower right corner of a protein box represents the number of components of the protein (domains, motifs, and/or pTyr sites) considered in the model.</p

Cell surface HLA expression of hHSC and lymphocytes derived from BM and peripheral blood.

<p>All allelic forms of HLA studied were highly expressed in all the cell types shown. However, HLA-A2 was expressed at significantly higher levels than HLA-B7 and -B8 on hHSC, BM CD4⁺ T cells, and BM CD8⁺ T cells. When BM lymphocytes and peripheral blood lymphocytes were compared, there was a marginal (but non-significant) difference in the expression of HLA-A2 and -B8 alleles which tended to have higher expression in peripheral blood than in BM. A significantly higher expression level of HLA-B7 was observed on peripheral blood CD4⁺ and CD8⁺ T lymphocytes. In peripheral blood, the expression of HLA-B8 was significantly lower than HLA-A2 and -B7 on CD4⁺ and CD8⁺ T lymphocytes. Peripheral CD19⁺ lymphocytes expressed similar amounts of HLA-A2, -B7 and -B8.</p

Expression of HLA-A and HLA-B in hESC and hMSC.

<p>Representative flow histograms showing HLA-A and -B expression in stem cell lines using allele-specific antibodies (anti-A2, -A3, -B7, and -B13). (A) In separate experiments, hESC lines (huES9 and KMEB2) showed a low expression of HLA-A alleles (A2 and A3, respectively) and no expression of the HLA-B alleles (B13 and B7, respectively). IFNγ stimulation up-regulated HLA-A alleles and induced of modest expression of HLA-B alleles. (B) Panel B shows representative flow histograms of an hMSC cell line (ToB11-13) both un-stimulated and IFNγ stimulated (72 hr) demonstrating a high constitutive expression of HLA-A2 and a relatively low expression of HLA-B7. Both antigens were up-regulated after stimulation with IFNγ. Panel (C) compares the expression of HLA-A and HLA-B between hESC (huES9) and hMSC (ToB11-13) during basal, un-induced conditions and after stimulation for 72 h with 25 ng/µl IFNγ. HLA expression was measured by flowcytometry as molecules of equivalent fluorochromes (MEF).</p

Description of cell lines.

§<p>the BM aspirates also used to establish the hMSC mentioned above.</p

Differentiation of hMSC to adipocytes and osteoblasts.

<p>Representative images for Oil O Red and Alizarin red staining demonstrating adipocyte and osteoblasts differentiation of hMSC cell lines cultured under adipogenic and osteogenic conditions, respectively. Non-differentiated cells were not stained (A and D), while the adipocyte differentiated cells were stained with Oil O red (B) and Alizarin red stained the matrix formed by osteoblasts (E). qPCR data shows marked up-regulation of PPAR gamma gene expression after adipocyte differentiation (C) and up-regulation of Collagen 1 gene expression in osteoblast differentiated cells (F).</p

Expression of HLA-A and HLA-B on hMSC and in their differentiated adipocyte and osteoblast progenies.

<p>Locus-specific HLA antigen expression before and after 13 days of differentiation of hMSC to adipocytes (A), or 16 days of differentiation to osteoblasts (B) in one hMSC-Tert4 cell line and three primary hMSC cell lines (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0054366#pone-0054366-t001" target="_blank">Table 1</a>). The analyzed HLA-A alleles were HLA-A2 (N = 3) and -A3 (N = 2). The analyzed HLA-B alleles were HLA-B7 (N = 3), -B27 (N = 1) and -B8 (N = 1) (data pooled according to locus, each data point represents mean value for 3 experiments for each cell line).</p

Cellular Proteome Dynamics during Differentiation of Human Primary Myoblasts

Muscle stem cells, or satellite cells, play an important role in the maintenance and repair of muscle tissue and have the capacity to proliferate and differentiate in response to physiological or environmental changes. Although they have been extensively studied, the key regulatory steps and the complex temporal protein dynamics accompanying the differentiation of primary human muscle cells remain poorly understood. Here, we demonstrate the advantages of applying a MS-based quantitative approach, stable isotope labeling by amino acids in cell culture (SILAC), for studying human myogenesis <i>in vitro</i> and characterize the fine-tuned changes in protein expression underlying the dramatic phenotypic conversion of primary mononucleated human muscle cells during <i>in vitro</i> differentiation to form multinucleated myotubes. Using an exclusively optimized triple encoding SILAC procedure, we generated dynamic expression profiles during the course of myogenic differentiation and quantified 2240 proteins, 243 of which were regulated. These changes in protein expression occurred in sequential waves and underlined vast reprogramming in key processes governing cell fate decisions, i.e., cell cycle withdrawal, RNA metabolism, cell adhesion, proteolysis, and cytoskeletal organization. <i>In silico</i> transcription factor target analysis demonstrated that the observed dynamic changes in the proteome could be attributed to a cascade of transcriptional events involving key myogenic regulatory factors as well as additional regulators not yet known to act on muscle differentiation. In addition, we created of a dynamic map of the developing myofibril, providing valuable insights into the formation and maturation of the contractile apparatus <i>in vitro</i>. Finally, our SILAC-based quantitative approach offered the possibility to follow the expression profiles of several muscle disease-associated proteins simultaneously and therefore could be a valuable resource for future studies investigating pathogenesis of degenerative muscle disorders as well as assessing new therapeutic strategies

Current model of IR activation and proposed binding mechanism for S961. A

<p>. Current model of IR activation. The four blue circles represent the receptor binding sites (sites 1 and 2) seen from a top view. Insulin is depicted as a yellow circle. For a detailed explanation of binding sites 1 and 2, see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0051972#pone.0051972-Whitesell1" target="_blank">[24]</a>. <b>B</b>. Proposed binding mechanism for S961. The four blue circles represent the receptor binding sites (sites 1 and 2) seen from a top view. For a detailed explanation of binding sites 1 and 2, see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0051972#pone.0051972-Whitesell1" target="_blank">[24]</a>. The S961 peptide (Site 1–2 peptide) is shown as two connected yellow circles. At concentrations of 1–10 nM, S961 crosslinks the receptor, leading to agonist activity. At concentrations of above 10 nM, the higher flexibility of S961 in comparison to the insulin molecule allows simultaneous crosslinking of both pairs of binding sites, leading to an inactive conformation and antagonism. The corresponding activation and inactivation sigmoids are also shown. <b>C</b>. Orientation of peptide binding sites. If site 1 is located N-terminally and site 2 C-terminally, a longer distance between the binding sites in S961 in comparison to S661 can be achieved.</p

StUbEx PLUSA Modified Stable Tagged Ubiquitin Exchange System for Peptide Level Purification and In-Depth Mapping of Ubiquitination Sites

Modulation of protein activities by reversible post-translational modifications (PTMs) is a major molecular mechanism involved in the control of virtually all cellular processes. One of these PTMs is ubiquitination, which regulates key processes including protein degradation, cell cycle, DNA damage repair, and signal transduction. Because of its importance for numerous cellular functions, ubiquitination has become an intense topic of research in recent years, and proteomics tools have greatly facilitated the identification of many ubiquitination targets. Taking advantage of the StUbEx strategy for exchanging the endogenous ubiquitin with an epitope-tagged version, we created a modified system, StUbEx PLUS, which allows precise mapping of ubiquitination sites by mass spectrometry. Application of StUbEx PLUS to U2OS cells treated with proteasomal inhibitors resulted in the identification of 41 589 sites on 7762 proteins, which thereby revealed the ubiquitous nature of this PTM and demonstrated the utility of the approach for comprehensive ubiquitination studies at site-specific resolution