Kristoffer T.G. Rigbolt

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

Dynamic phosphorylation during stem cell differentiation may control recruitment of DNA methyltransferases to silence genes that maintain pluripotency. Dynamics of the Stem Cell Phosphoproteome Understanding the signaling events that control stem cell pluripotency and self-renewal and those governing differentiation should improve our ability to develop stem cell–based therapies. Rigbolt et al. performed global quantitative proteomic and phosphoproteomic analysis of human embryonic stem cells at five time points over 24 hours of nondirected (lineage-independent) differentiation initiated by two different paradigms. They identified a common core phosphoproteome associated with both differentiation protocols, discovered several temporal patterns of phosphorylation, and made predictions about changes in the activities of kinases during the differentiation period. DNA methyltransferases (DNMTs) exhibited dynamic changes in phosphorylation status that may influence their interaction with a promoter-bound protein complex, suggesting that the phosphorylation state of DNMTs may govern their recruitment to and thus silencing of target genes, such as those that promote pluripotency, during differentiation. To elucidate cellular events underlying the pluripotency of human embryonic stem cells (hESCs), we performed parallel quantitative proteomic and phosphoproteomic analyses of hESCs during differentiation initiated by a diacylglycerol analog or transfer to media that had not been conditioned by feeder cells. We profiled 6521 proteins and 23,522 phosphorylation sites, of which almost 50% displayed dynamic changes in phosphorylation status during 24 hours of differentiation. These data are a resource for studies of the events associated with the maintenance of hESC pluripotency and those accompanying their differentiation. From these data, we identified a core hESC phosphoproteome of sites with similar robust changes in response to the two distinct treatments. These sites exhibited distinct dynamic phosphorylation patterns, which were linked to known or predicted kinases on the basis of the matching sequence motif. In addition to identifying previously unknown phosphorylation sites on factors associated with differentiation, such as kinases and transcription factors, we observed dynamic phosphorylation of DNA methyltransferases (DNMTs). We found a specific interaction of DNMTs during early differentiation with the PAF1 (polymerase-associated factor 1) transcriptional elongation complex, which binds to promoters of the pluripotency and known DNMT target genes encoding OCT4 and NANOG, thereby providing a possible molecular link for the silencing of these genes during differentiation.

MSQuant, an Open Source Platform for Mass Spectrometry-Based Quantitative Proteomics

Mass spectrometry-based proteomics critically depends on algorithms for data interpretation. A current bottleneck in the rapid advance of proteomics technology is the closed nature and slow development cycle of vendor-supplied software solutions. We have created an open source software environment, called MSQuant, which allows visualization and validation of peptide identification results directly on the raw mass spectrometric data. MSQuant iteratively recalibrates MS data thereby significantly increasing mass accuracy leading to fewer false positive peptide identifications. Algorithms to increase data quality include an MS(3) score for peptide identification and a post-translational modification (PTM) score that determines the probability that a modification such as phosphorylation is placed at a specific residue in an identified peptide. MSQuant supports relative protein quantitation based on precursor ion intensities, including element labels (e.g., (15)N), residue labels (e.g., SILAC and ICAT), termini labels (e.g., (18)O), functional group labels (e.g., mTRAQ), and label-free ion intensity approaches. MSQuant is available, including an installer and supporting scripts, at http://msquant.sourceforge.net .

Dynamics of the Skeletal Muscle Secretome during Myoblast Differentiation

During recent years, increased efforts have focused on elucidating the secretory function of skeletal muscle. Through secreted molecules, skeletal muscle affects local muscle biology in an auto/paracrine manner as well as having systemic effects on other tissues. Here we used a quantitative proteomics platform to investigate the factors secreted during the differentiation of murine C2C12 skeletal muscle cells. Using triple encoding stable isotope labeling by amino acids in cell culture, we compared the secretomes at three different time points of muscle differentiation and followed the dynamics of protein secretion. We identified and quantitatively analyzed 635 secreted proteins, including 35 growth factors, 40 cytokines, and 36 metallopeptidases. The extensive presence of these proteins that can act as potent signaling mediators to other cells and tissues strongly highlights the important role of the skeletal muscle as a prominent secretory organ. In addition to previously reported molecules, we identified many secreted proteins that have not previously been shown to be released from skeletal muscle cells nor shown to be differentially released during the process of myogenesis. We found 188 of these secreted proteins to be significantly regulated during the process of myogenesis. Comparative analyses of selected secreted proteins revealed little correlation between their mRNA and protein levels, indicating pronounced regulation by posttranscriptional mechanisms. Furthermore, analyses of the intracellular levels of members of the semaphorin family and their corresponding secretion dynamics demonstrated that the release of secreted proteins is tightly regulated by the secretory pathway, the stability of the protein, and/or the processing of secreted proteins. Finally, we provide 299 unique hydroxyproline sites mapping to 48 distinct secreted proteins and have discovered a novel hydroxyproline motif.

GProX, a User-Friendly Platform for Bioinformatics Analysis and Visualization of Quantitative Proteomics Data

Recent technological advances have made it possible to identify and quantify thousands of proteins in a single proteomics experiment. As a result of these developments, the analysis of data has become the bottleneck of proteomics experiment. To provide the proteomics community with a user-friendly platform for comprehensive analysis, inspection and visualization of quantitative proteomics data we developed the Graphical Proteomics Data Explorer (GProX)1. The program requires no special bioinformatics training, as all functions of GProX are accessible within its graphical user-friendly interface which will be intuitive to most users. Basic features facilitate the uncomplicated management and organization of large data sets and complex experimental setups as well as the inspection and graphical plotting of quantitative data. These are complemented by readily available high-level analysis options such as database querying, clustering based on abundance ratios, feature enrichment tests for e.g. GO terms and pathway analysis tools. A number of plotting options for visualization of quantitative proteomics data is available and most analysis functions in GProX create customizable high quality graphical displays in both vector and bitmap formats. The generic import requirements allow data originating from essentially all mass spectrometry platforms, quantitation strategies and software to be analyzed in the program. GProX represents a powerful approach to proteomics data analysis providing proteomics experimenters with a toolbox for bioinformatics analysis of quantitative proteomics data. The program is released as open-source and can be freely downloaded from the project webpage at http://gprox.sourceforge.net.

Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) and Quantitative Comparison of the Membrane Proteomes of Self-renewing and Differentiating Human Embryonic Stem Cells

Stable isotope labeling by amino acids in cell culture (SILAC) is a powerful quantitative proteomics platform for comprehensive characterization of complex biological systems. However, the potential of SILAC-based approaches has not been fully utilized in human embryonic stem cell (hESC) research mainly because of the complex nature of hESC culture conditions. Here we describe complete SILAC labeling of hESCs with fully preserved pluripotency, self-renewal capabilities, and overall proteome status that was quantitatively analyzed to a depth of 1556 proteins and 527 phosphorylation events. SILAC-labeled hESCs appear to be perfectly suitable for functional studies, and we exploited a SILAC-based proteomics strategy for discovery of hESC-specific surface markers. We determined and quantitatively compared the membrane proteomes of the self-renewing versus differentiating cells of two distinct human embryonic stem cell lines. Of the 811 identified membrane proteins, six displayed significantly higher expression levels in the undifferentiated state compared with differentiating cells. This group includes the established marker CD133/Prominin-1 as well as novel candidates for hESC surface markers: Glypican-4, Neuroligin-4, ErbB2, receptor-type tyrosine-protein phosphatase ζ (PTPRZ), and Glycoprotein M6B. Our study also revealed 17 potential markers of hESC differentiation as their corresponding protein expression levels displayed a dramatic increase in differentiated embryonic stem cell populations.

Functional Proteomics Defines the Molecular Switch Underlying FGF Receptor Trafficking and Cellular Outputs

The stimulation of fibroblast growth factor receptors (FGFRs) with distinct FGF ligands generates specific cellular responses. However, the mechanisms underlying this paradigm have remained elusive. Here, we show that FGF-7 stimulation leads to FGFR2b degradation and, ultimately, cell proliferation, whereas FGF-10 promotes receptor recycling and cell migration. By combining mass-spectrometry-based quantitative proteomics with fluorescence microscopy and biochemical methods, we find that FGF-10 specifically induces the rapid phosphorylation of tyrosine (Y) 734 on FGFR2b, which leads to PI3K and SH3BP4 recruitment. This complex is crucial for FGFR2b recycling and responses, given that FGF-10 stimulation of either FGFR2b_Y734F mutant- or SH3BP4-depleted cells switches the receptor endocytic route to degradation, resulting in decreased breast cancer cell migration and the inhibition of epithelial branching in mouse lung explants. Altogether, these results identify an intriguing ligand-dependent mechanism for the control of receptor fate and cellular outputs that may explain the pathogenic role of deregulated FGFR2b, thus offering therapeutic opportunities.

Systematic In Vivo RNAi Analysis Identifies IAPs as NEDD8-E3 Ligases

The intimate relationship between mediators of the ubiquitin (Ub)-signaling system and human diseases has sparked profound interest in how Ub influences cell death and survival. While the consequence of Ub attachment is intensely studied, little is known with regards to the effects of other Ub-like proteins (UBLs), and deconjugating enzymes that remove the Ub or UBL adduct. Systematic in vivo RNAi analysis identified three NEDD8-specific isopeptidases that, when knocked down, suppress apoptosis. Consistent with the notion that attachment of NEDD8 prevents cell death, genetic ablation of deneddylase 1 (DEN1) suppresses apoptosis. Unexpectedly, we find that Drosophila and human inhibitor of apoptosis (IAP) proteins can function as E3 ligases of the NEDD8 conjugation pathway, targeting effector caspases for neddylation and inactivation. Finally, we demonstrate that DEN1 reverses this effect by removing the NEDD8 modification. Altogether, our findings indicate that IAPs not only modulate cellular processes via ubiquitylation but also through attachment of NEDD8, thereby extending the complexity of IAP-mediated signaling.

Global remodelling of cellular microenvironment due to loss of collagen VII

The mammalian cellular microenvironment is shaped by soluble factors and structural components, the extracellular matrix, providing physical support, regulating adhesion and signalling. A global, quantitative mass spectrometry strategy, combined with bioinformatics data processing, was developed to assess proteome differences in the microenvironment of primary human fibroblasts. We studied secreted proteins of fibroblasts from normal and pathologically altered skin and their post‐translational modifications. The influence of collagen VII, an important structural component, which is lost in genetic skin fragility, was used as model. Loss of collagen VII had a global impact on the cellular microenvironment and was associated with proteome alterations highly relevant for disease pathogenesis including decrease in basement membrane components, increase in dermal matrix proteins, TGF‐β and metalloproteases, but not higher protease activity. The definition of the proteome of fibroblast microenvironment and its plasticity in health and disease identified novel disease mechanisms and potential targets of intervention.

Involvement of mitochondrial dynamics in the segregation of mitochondrial matrix proteins during stationary phase mitophagy

Mitophagy, the autophagic degradation of mitochondria, is an important housekeeping function in eukaryotic cells and defects in mitophagy correlate with ageing phenomena and with several neurodegenerative disorders. A central mechanistic question regarding mitophagy is whether mitochondria are consumed en masse, or whether an active process segregates defective molecules from functional ones within the mitochondrial network, thus allowing a more efficient culling mechanism. Here, we combine a proteomic study with a molecular genetic and cell biology approach to determine whether such a segregation process occurs in yeast mitochondria. We find that different mitochondrial matrix proteins undergo mitophagic degradation at distinctly different rates, supporting the active segregation hypothesis. These differential degradation rates depend on mitochondrial dynamics, suggesting a mechanism coupling weak physical segregation with mitochondrial dynamics to achieve a distillation-like effect. In agreement, the rates of mitophagic degradation strongly correlate with the degree of physical segregation of specific matrix proteins.

Quantitative phosphoproteomics to characterize signaling networks

Reversible protein phosphorylation is involved in the regulation of most, if not all, major cellular processes via dynamic signal transduction pathways. During the last decade quantitative phosphoproteomics have evolved from a highly specialized area to a powerful and versatile platform for analyzing protein phosphorylation at a system-wide scale and has become the intuitive strategy for comprehensive characterization of signaling networks. Contemporary phosphoproteomics use highly optimized procedures for sample preparation, mass spectrometry and data analysis algorithms to identify and quantify thousands of phosphorylations, thus providing extensive overviews of the cellular signaling networks. As a result of these developments quantitative phosphoproteomics have been applied to study processes as diverse as immunology, stem cell biology and DNA damage. Here we review the developments in phosphoproteomics technology that have facilitated the application of phosphoproteomics to signaling networks and introduce examples of recent system-wide applications of quantitative phosphoproteomics. Despite the great advances in phosphoproteomics technology there are still several outstanding issues and we provide here our outlook on the current limitations and challenges in the field.