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

Proteomic analysis of stem cell differentiation and early development

Genomics methodologies have advanced to the extent that it is now possible to interrogate the gene expression in a single cell but proteomics has traditionally lagged behind and required much greater cellular input and was not quantitative. Coupling protein with gene expression data is essential for understanding how cell behavior is regulated. Advances primarily in mass spectrometry have, however, greatly improved the sensitivity of proteomics methods over the last decade and the outcome of proteomic analyses can now also be quantified. Nevertheless, it is still difficult to obtain sufficient tissue from staged mammalian embryos to combine proteomic and genomic analyses. Recent developments in pluripotent stem cell biology have in part addressed this issue by providing surrogate scalable cell systems in which early developmental events can be modeled. Here we present an overview of current proteomics methodologies and the kind of information this can provide on the biology of human and mouse pluripotent stem cells.

Quantitative proteomic analysis of membrane proteins involved in astroglial differentiation of neural stem cells by SILAC labeling coupled with LC-MS/MS

Membrane proteins play a critical role in the process of neural stem cell self-renewal and differentiation. Here, we apply the SILAC (stable isotope labeling by amino acids in cell culture) approach to quantitatively compare the membrane proteome of the self-renewing and the astroglial differentiating cells. High-resolution analysis on a linear ion trap-Orbitrap instrument (LTQ-Orbitrap) at sub-ppm mass accuracy resulted in confident identification and quantitation of more than 700 distinct membrane proteins during the astroglial differentiation. Of the 735 quantified proteins, seven cell surface proteins display significantly higher expression levels in the undifferentiated state membrane compared to astroglial differentiating membrane. One cell surface protein transferrin receptor protein 1 may serve as a new candidate for NSCs surface markers. Functional clustering of differentially expressed proteins by Ingenuity Pathway Analysis revealed that most of overexpressed membrane proteins in the astroglial differentiation neural stem cells are involved in cellular growth, nervous system development, and energy metabolic pathway. Taken together, this study increases our understanding of the underlying mechanisms that modulate complex biological processes of neural stem cell proliferation and differentiation.

In vivo quantitative proteome profiling: planning and evaluation of SILAC experiments

Mass spectrometry-based quantitative proteomics can identify and quantify thousands of proteins in complex biological samples. Improved instrumentation, quantification strategies and data analysis tools now enable protein analysis on a genome-wide scale. Particularly, quantification based on stable isotope labeling with amino acids (SILAC) has emerged as a robust, reliable and simple method for accurate large-scale protein quantification. The spectrum of applications ranges from bacteria and eukaryotic cell culture systems to multicellular organisms. Here, we provide a step-by-step protocol on how to plan and perform large-scale quantitative proteome analysis using SILAC, from sample preparation to final data analysis.

Stable isotope labelling with amino acids in cell culture for human embryonic stem cell proteomic analysis

The identification and quantitative measurements of proteins in human embryonic stem cells (hESC) is a fast growing interdisciplinary area with an enormous impact on understanding the biology of hESC and the mechanism controlling self-renewal and differentiation. Using a quantitative mass spectroscopic method of stable isotope labelling with amino acids during cell culture (SILAC), we are able to analyse differential expression of proteins from different cellular compartments and to identify intracellular signalling pathways involved in self-renewal and differentiation. In this chapter, we provide a detailed method for creating SILAC media suitable for use in hESC experiments, additionally we describe methods for the isolation of membrane fractions and cytosolic and nuclear/membrane fractions.

Quantitative proteomics of complex mixtures

Measurement of biologically important effector protein molecules has been a long-standing essential component of biological research. Advances in biotechnology, in the form of high-resolution mass spectrometers, and in bioinformatics, now allow the simultaneous quantitative analysis of thousands of proteins. While these techniques still do not allow definitive identification of the entire proteome of complex mixtures, such as cells, quantitative analyses of hundreds to thousands of proteins in such complex mixtures provides a means to elucidate molecular alterations that occur during perturbation of cellular systems. This article will outline considerations of reducing sample complexity, by strategies such as multidimensional separations (gel-based and chromatography-based, including multidimensional protein identification technology). In addition, some of the most common methods used to quantitatively measure proteins in complex mixtures (2D difference in-gel electrophoresis, isotope-coded affinity tags, isotope-coded protein labeling, tandem mass tags, isobaric tags for relative and absolute quantitation, stable isotope labeling of amino acids in cell culture and label-free), as well as recent examples of each strategy, are described.

Characterization of ubiquitination dependent dynamics in growth factor receptor signaling by quantitative proteomics

Protein ubiquitination is a dynamic reversible post-translational modification that plays a key role in the regulation of numerous cellular processes including signal transduction, endocytosis, cell cycle control, DNA repair and gene transcription. The conjugation of the small protein ubiquitin or chains of ubiquitin molecules of various types and lengths to targeted proteins is known to alter proteins' lifespan, localization and function and to modulate protein interactions. Despite its central importance in various aspects of cellular life and function there are only a limited number of reports investigating ubiquitination on a proteomic scale, mainly due to the inherited complexity and heterogeneity of ubiquitination. We describe here a quantitative proteomics strategy based on the specificity of ubiquitin binding domains (UBDs) and Stable Isotope Labeling by Amino acids in Cell culture (SILAC) for selectively decoding ubiquitination-driven processes involved in the regulation of cellular signaling networks. We applied this approach to characterize the temporal dynamics of ubiquitination events accompanying epidermal growth factor receptor (EGFR) signal transduction. We used recombinant UBDs derived from endocytic adaptor proteins for specific enrichment of ubiquitinated complexes from the EGFR network and subsequent quantitative analyses by high accuracy mass spectrometry. We show that the strategy is suitable for profiling the dynamics of ubiquitination occurring on individual proteins as well as ubiquitination-dependent events in signaling pathways. In addition to a detailed seven time-point profile of EGFR ubiquitination over 30 minutes of ligand stimulation, our data determined prominent involvement of Lysine-63 ubiquitin branching in EGF signaling. Furthermore, we found two centrosomal proteins, PCM1 and Azi1, to form a multi-protein complex with the ubiquitin E3 ligases MIB1 and WWP2 downstream of the EGFR, thereby revealing possible ubiquitination cross-talk between EGF signaling and centrosomal-dependent rearrangements of the microtubules. This is a general strategy that can be utilized to study the dynamics of other cellular systems and post-translational modifications.

Pluripotent stem cell heterogeneity and the evolving role of proteomic technologies in stem cell biology

Stem cells represent obvious choices for regenerative medicine and are invaluable for studies of human development and drug testing. The proteomic landscape of pluripotent stem cells (PSCs), in particular, is not yet clearly defined; consequently, this field of research would greatly benefit from concerted efforts designed to better characterize these cells. In this concise review, we provide an overview of stem cell potency, highlight the types and practical implications of heterogeneity in PSCs and provide a detailed analysis of the current view of the pluripotent proteome in a unique resource for this rapidly evolving field. Our goal in this review is to provide specific insights into the current status of the known proteome of both mouse and human PSCs. This has been accomplished by integrating published data into a unified PSC proteome to facilitate the identification of proteins, which may be informative for the stem cell state as well as to reveal areas where our current view is limited. These analyses provide insight into the challenges faced in the proteomic analysis of PSCs and reveal one area--the cell surface subproteome--that would especially benefit from enhanced research efforts.

An enhanced chemically defined SILAC culture system for quantitative proteomics study of human embryonic stem cells

Stable isotope labeling by SILAC-based quantitative proteomics analysis provides an unprecedented tool for the study of mechanisms underlying the self-renewal and differentiation of human embryonic stem cells (hESCs). While we recently reported a chemically defined SILAC culture system specific for a rare cell proteomic reactor (R. Tian et al., Mol. Cell. Proteomics 2011, 10, M110.000679), total hESC yield, prolonged self-renewal capacity (i.e.<12 days), and laborious procedure remain substantial hurdles for its conventional application in hESC studies. Here, we devised an enhanced SILAC culture system consisting of a new chemically defined SILAC-medium and a novel culture protocol. As a result, with much less culture maneuvers, approximately 40-fold greater hESCs were produced than the system reported previously. Moreover, the enhanced SILAC culture system was sufficient to support the self-renewal of hESCs for >60 days and was also highly reproducible. As such, it provides a new platform that can be readily adapted by general laboratory for further comprehensive SILAC-based proteomics analysis of hESCs and induced pluripotent stem cells.

Defining pluripotent stem cells through quantitative proteomic analysis

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.

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.

Quantitative neuroproteomics: classical and novel tools for studying neural differentiation and function

Mechanisms underlying neural stem cell proliferation, differentiation and maturation play a critical role in the formation and wiring of neuronal connections. This process involves the activation of multiple serial events, which guide the undifferentiated cells to different lineages via distinctive developmental programs, forming neuronal circuits and thus shaping the adult nervous system. Furthermore, alterations within these strictly regulated pathways can lead to severe neurological and psychiatric diseases. In this framework, the investigation of the high dynamic protein expression changes and other factors affecting protein functions, for example post-translational modifications, the alterations of protein interaction networks, is of pivotal importance for the understanding of the molecular mechanisms responsible for cell differentiation. More recently, proteomic studies in neuroscience ("neuroproteomics") are receiving increased interest for the primary understanding of the regulatory networks underlying neuronal differentiation processes. Besides the classical two-dimensional-based proteomic strategies, the emerging platforms for LC-MS shotgun proteomic analysis hold great promise in unraveling the molecular basis of neural stem cell differentiation. In this review, recent advancements in label-free LC-MS quantitative neuroproteomics are highlighted as a new tool for the study of neural differentiation and functions, in comparison to mass spectrometry-based labeling approaches. The more commonly used protein profiling strategies and model systems for the analysis of neural differentiation are also discussed, along with the challenging proteomic approaches aimed to analyze the nervous system-specific organelles, the neural cells secretome and the specific protein interaction networks.

Secretome Analysis of Skeletal Myogenesis Using SILAC and Shotgun Proteomics

Myogenesis, the formation of skeletal muscle, is a multistep event that commences with myoblast proliferation, followed by cell-cycle arrest, and finally the formation of multinucleated myotubes via fusion of mononucleated myoblasts. Each step is orchestrated by well-documented intracellular factors, such as cytoplasmic signalling molecules and nuclear transcription factors. Regardless, the key step in getting a more comprehensive understanding of the regulation of myogenesis is to explore the extracellular factors that are capable of eliciting the downstream intracellular factors. This could further provide valuable insight into the acute cellular response to extrinsic cues in maintaining normal muscle development. In this paper, we survey the intracellular factors that respond to extracellular cues that are responsible for the cascades of events during myogenesis: myoblast proliferation, cell-cycle arrest of myoblasts, and differentiation of myoblasts into myotubes. This focus on extracellular perspective of muscle development illustrates our mass spectrometry-based proteomic approaches to identify differentially expressed secreted factors during skeletal myogenesis.

Study of neurotrophin-3 signaling in primary cultured neurons using multiplex stable isotope labeling with amino acids in cell culture

Conventional stable isotope labeling with amino acids in cell culture (SILAC) requires extensive metabolic labeling of proteins and therefore is difficult to apply to cells that do not divide or are unstable in SILAC culture. Using two different sets of heavy amino acids for labeling allows for straightforward SILAC quantitation using partially labeled cells because the two cell populations are always equally labeled. Here we report the application of this labeling strategy to primary cultured neurons. We demonstrated that protein quantitation was not compromised by incomplete labeling of the neuronal proteins. We used this method to study neurotrophin-3 (NT-3) signaling in primary cultured neurons. Surprisingly our results indicate TrkB signaling is a major component of the signaling network induced by NT-3 in cortical neurons. In addition, involvement of proteins such as VAMP2, Scamp1, and Scamp3 suggests that NT-3 may lead to enhanced exocytosis of synaptic vesicles.

System-wide temporal characterization of the proteome and phosphoproteome of human embryonic stem cell 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.

Toward a complete in silico, multi-layered embryonic stem cell regulatory network

Recent efforts in systematically profiling embryonic stem (ES) cells have yielded a wealth of high-throughput data. Complementarily, emerging databases and computational tools facilitate ES cell studies and further pave the way toward the in silico reconstruction of regulatory networks encompassing multiple molecular layers. Here, we briefly survey databases, algorithms, and software tools used to organize and analyze high-throughput experimental data collected to study mammalian cellular systems with a focus on ES cells. The vision of using heterogeneous data to reconstruct a complete multi-layered ES cell regulatory network is discussed. This review also provides an accompanying manually extracted dataset of different types of regulatory interactions from low-throughput experimental ES cell studies available at http://amp.pharm.mssm.edu/iscmid/literature.

Glycoproteomic analysis of glioblastoma stem cell differentiation

Cancer stem cells are responsible for tumor formation through self-renewal and differentiation into multiple cell types and thus represent a new therapeutic target for tumors. Glycoproteins play a critical role in determining the fates of stem cells such as self-renewal, proliferation, and differentiation. Here we applied a multilectin affinity chromatography and quantitative glycoproteomics approach to analyze alterations of glycoproteins relevant to the differentiation of a glioblastoma-derived stem cell line HSR-GBM1. Three lectins including concanavalin A (Con A), wheat germ agglutinin (WGA), and peanut agglutinin (PNA) were used to capture glycoproteins, followed by LC-MS/MS analysis. A total of 73 and 79 high-confidence (FDR < 0.01) glycoproteins were identified from the undifferentiated and differentiated cells, respectively. Label-free quantitation resulted in the discovery of 18 differentially expressed glycoproteins, wherein 9 proteins are localized in the lysosome. All of these lysosomal glycoproteins were up-regulated after differentiation, where their principal function was hydrolysis of glycosyl residues. Protein-protein interaction and functional analyses revealed the active involvement of lysosomes during the process of glioblastoma stem cell differentiation. This work provides glycoprotein markers to characterize differentiation status of glioblastoma stem cells that may be useful in stem-cell therapy of glioblastoma.

Large scale phosphoproteome profiles comprehensive features of mouse embryonic stem cells

Embryonic stem cells are pluripotent and capable of unlimited self-renewal. Elucidation of the underlying molecular mechanism may contribute to the advancement of cell-based regenerative medicine. In the present work, we performed a large scale analysis of the phosphoproteome in mouse embryonic stem (mES) cells. Using multiplex strategies, we detected 4581 proteins and 3970 high confidence distinct phosphosites in 1642 phosphoproteins. Notably, 22 prominent phosphorylated stem cell marker proteins with 39 novel phosphosites were identified for the first time by mass spectrometry, including phosphorylation sites in NANOG (Ser-65) and RE1 silencing transcription factor (Ser-950 and Thr-953). Quantitative profiles of NANOG peptides obtained during the differentiation of mES cells revealed that the abundance of phosphopeptides and non-phosphopeptides decreased with different trends. To our knowledge, this study presents the largest global characterization of phosphorylation in mES cells. Compared with a study of ultimately differentiated tissue cells, a bioinformatics analysis of the phosphorylation data set revealed a consistent phosphorylation motif in human and mouse ES cells. Moreover, investigations into phosphorylation conservation suggested that phosphoproteins were more conserved in the undifferentiated ES cell state than in the ultimately differentiated tissue cell state. However, the opposite conclusion was drawn from this conservation comparison with phosphosites. Overall, this work provides an overview of phosphorylation in mES cells and is a valuable resource for the future understanding of basic biology in mES cells.

Quantitative proteomics for epigenetics

Mass spectrometry has made many contributions to the chromatin field through the mapping of histone modifications and the identification of protein complexes involved in gene regulation. MS-based proteomics has now evolved from the identification of single protein spots in gels to the identification and quantification of thousands of proteins in complex mixtures. Quantitative approaches also allow comparative and time-resolved analysis of post-translational modifications. An important emerging field is the unbiased interaction analysis of proteins with other proteins, defined protein modifications, specific DNA and RNA sequences, and small molecules. Quantitative proteomics can also accurately monitor whole proteome changes in response to perturbation of the gene expression machinery. We provide an up-to-date review of modern quantitative proteomic technology and its applications in the field of epigenetics.

Proteomics and the dynamic plasma membrane: Quo Vadis?

Quo Vadis: where are you going? Advances in MS-based proteomics have enabled research to move from obtaining the basic protein inventory of cells and organelles to the ability of monitoring their dynamics, including changes in abundance, location and various PTMs. In this respect, the cellular plasma membrane is of particular interest, by not only serving as a barrier between the "cell interior" and the external environment, but moreover by organizing and clustering essential components to enable dynamic responses to internal and external stimuli. Defining and characterizing the dynamic plasma membrane proteome is crucial for understanding fundamental biological processes, disease mechanisms and for finding drug targets. Protein identification, characterization of dynamic PTMs and protein-ligand interactions, and determination of transient changes in protein expression and composition are among the challenges in functional proteomic studies of the plasma membrane. We review the recent progress in MS-based plasma membrane proteomics by presenting key examples from eukaryotic systems, including mammals, yeast and plants. We highlight the importance of enrichment and quantification technologies required for detailed functional and comparative analysis of the dynamic plasma membrane proteome.

Advances in shotgun proteomics and the analysis of membrane proteomes

The emergence of shotgun proteomics has facilitated the numerous biological discoveries made by proteomic studies. However, comprehensive proteomic analysis remains challenging and shotgun proteomics is a continually changing field. This review details the recent developments in shotgun proteomics and describes emerging technologies that will influence shotgun proteomics going forward. In addition, proteomic studies of integral membrane proteins remain challenging due to the hydrophobic nature in integral membrane proteins and their general low abundance levels. However, there have been many strategies developed for enriching, isolating and separating membrane proteins for proteomic analysis that have moved this field forward. In summary, while shotgun proteomics is a widely used and mature technology, the continued pace of improvements in mass spectrometry and proteomic technology and methods indicate that future studies will have an even greater impact on biological discovery.

Identification of cell surface glycoprotein markers for glioblastoma-derived stem-like cells using a lectin microarray and LC-MS/MS approach

Despite progress in the treatment of glioblastoma, more than 95% of patients suffering from this disease still die within 2 years. Recent findings support the belief that cancer stem-like cells are responsible for tumor formation and ongoing growth. Here a method combining lectin microarray and LC-MS/MS was used to discover the cell surface glycoprotein markers of a glioblastoma-derived stem-like cell line. Lectin microarray analysis of cell surface glycans showed that two galactose-specific lectins Trichosanthes kirilowii agglutinin (TKA) and Peanut agglutinin (PNA) could distinguish the stem-like glioblastoma neurosphere culture from a traditional adherent glioblastoma cell line. Agarose-bound TKA and PNA were used to capture the glycoproteins from the two cell cultures, which were analyzed by LC-MS/MS. The glycoproteins were quantified by spectral counting, resulting in the identification of 12 and 11 potential glycoprotein markers from the TKA and PNA captured fractions respectively. Almost all of these proteins were membrane proteins. Differential expression was verified by Western blotting analysis of 6 interesting proteins, including the up-regulated Receptor-type tyrosine-protein phosphatase zeta, Tenascin-C, Chondroitin sulfate proteoglycan NG2, Podocalyxin-like protein 1 and CD90, and the down-regulated CD44. An improved understanding of these proteins may be important for earlier diagnosis and better therapeutic targeting of glioblastoma.

Quantitative proteomic analyses of influenza virus-infected cultured human lung cells

Because they are obligate intracellular parasites, all viruses are exclusively and intimately dependent upon host cells for replication. Viruses, in turn, induce profound changes within cells, including apoptosis, morphological changes, and activation of signaling pathways. Many of these alterations have been analyzed by gene arrays, which measure the cellular "transcriptome." Until recently, it has not been possible to extend comparable types of studies to globally examine all the host cellular proteins, which are the actual effector molecules. We have used stable isotope labeling by amino acids in cell culture (SILAC), combined with high-throughput two-dimensional (2-D) high-performance liquid chromatography (HPLC)/mass spectrometry, to determine quantitative differences in host proteins after infection of human lung A549 cells with human influenza virus A/PR/8/34 (H1N1) for 24 h. Of the 4,689 identified and measured cytosolic protein pairs, 127 were significantly upregulated at >95% confidence, 153 were significantly downregulated at >95% confidence, and a total of 87 proteins were upregulated or downregulated more than 5-fold at >99% confidence. Gene ontology and pathway analyses indicated differentially regulated proteins and included those involved in host cell immunity and antigen presentation, cell adhesion, metabolism, protein function, signal transduction, and transcription pathways.

Comparative proteomics of human embryonic stem cells and embryonal carcinoma cells

Pluripotent human embryonic stem cells (ESCs) can be differentiated in vitro into a variety of cells which hold promise for transplantation therapy. Human embryonal carcinoma cells (ECCs), stem cells of human teratocarcinomas, are considered a close but malignant counterpart to human ESCs. In this study, a comprehensive quantitative proteomic analysis of ESCs and ECCs was carried out using the iTRAQ method. Using two-dimensional LC and MS/MS analyses, we identified and quantitated approximately 1800 proteins. Among these are proteins associated with pluripotency and development as well as tight junction signaling and TGFbeta receptor pathway. Nearly approximately 200 proteins exhibit more than twofold difference in abundance between ESCs and ECCs. Examples of early developmental markers high in ESCs include beta-galactoside-binding lectin, undifferentiated embryonic cell transcription factor-1, DNA cytosine methyltransferase 3beta isoform-B, melanoma antigen family-A4, and interferon-induced transmembrane protein-1. In contrast, CD99-antigen (CD99), growth differentiation factor-3, cellular retinoic acid binding protein-2, and developmental pluripotency associated-4 were among the highly expressed proteins in ECCs. Several proteins that were highly expressed in ECCs such as heat shock 27 kDa protein-1, mitogen-activated protein kinase kinase-1, nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor like-2, and S100 calcium-binding protein-A4 have also been attributed to malignancy in other systems. Importantly, immunocytochemistry was used to validate the proteomic analyses for a subset of the proteins. In summary, this is the first large-scale quantitative proteomic study of human ESCs and ECCs, which provides critical information about the regulators of these two closely related, but developmentally distinct, stem cells.

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.

Rare cell proteomic reactor applied to stable isotope labeling by amino acids in cell culture (SILAC)-based quantitative proteomics study of human embryonic stem cell differentiation

The molecular basis governing the differentiation of human embryonic stem cells (hESCs) remains largely unknown. Systems-level analysis by proteomics provides a unique approach to tackle this question. However, the requirement of a large number of cells for proteomics analysis (i.e. 10(6)-10(7) cells) makes this assay challenging, especially for the study of rare events during hESCs lineage specification. Here, a fully integrated proteomics sample processing and analysis platform, termed rare cell proteomic reactor (RCPR), was developed for large scale quantitative proteomics analysis of hESCs with ∼50,000 cells. hESCs were completely extracted by a defined lysis buffer, and all of the proteomics sample processing procedures, including protein preconcentration, reduction, alkylation, and digestion, were integrated into one single capillary column with a strong cation exchange monolith matrix. Furthermore, on-line two-dimensional LC-MS/MS analysis was performed directly using RCPR as the first dimension strong cation exchange column. 2,281 unique proteins were identified on this system using only 50,000 hESCs. For stable isotope labeling by amino acids in cell culture (SILAC)-based quantitative study, a ready-to-use and chemically defined medium and an in situ differentiation procedure were developed for complete SILAC labeling of hESCs with well characterized self-renewal and differentiation properties. Mesoderm-enriched differentiation was studied by RCPR using 50,000 hESCs, and 1,086 proteins were quantified with a minimum of two peptides per protein. Of these, 56 proteins exhibited significant changes during mesoderm-enriched differentiation, and eight proteins were demonstrated for the first time to be overexpressed during early mesoderm development. This work provides a new platform for the study of rare cells and in particular for further elucidating proteins that govern the mesoderm lineage specification of human pluripotent stem cells.

Quantitative top-down proteomics of SILAC labeled human embryonic stem cells

Human embryonic stem cells (hESCs) are self-renewing pluripotent cells with relevance to treatment of numerous medical conditions. However, a global understanding of the role of the hESC proteome in maintaining pluripotency or triggering differentiation is still largely lacking. The emergence of top-down proteomics has facilitated the identification and characterization of intact protein forms that are not readily apparent in bottom-up studies. Combined with metabolic labeling techniques such as stable isotope labeling by amino acids in cell culture (SILAC), quantitative comparison of intact protein expression under differing experimental conditions is possible. Herein, quantitative top-down proteomics of hESCs is demonstrated using the SILAC method and nano-flow reverse phase chromatography directly coupled to a linear-ion-trap Fourier transform ion cyclotron resonance mass spectrometer (nLC-LTQ-FT-ICR-MS). In this study, which to the best of our knowledge represents the first top-down analysis of hESCs, we have confidently identified 11 proteins by accurate intact mass, MS/MS, and amino acid counting facilitated by SILAC labeling. Although quantification is challenging due to the incorporation of multiple labeled amino acids (i.e., lysine and arginine) and arginine to proline conversion, we are able to quantitatively account for these phenomena using a mathematical model.

Isolation of cell surface proteins for mass spectrometry-based proteomics

Defining the cell surface proteome has profound importance for understanding cell differentiation and cell-cell interactions, as well as numerous pathogenic abnormalities. Owing to their hydrophobic nature, plasma membrane proteins that reside on the cell surface pose analytical challenges and, despite efforts to overcome difficulties, remain under-represented in proteomic studies. Limitations in the classically employed ultracentrifugation-based approaches have led to the invention of more elaborate techniques for the purification of cell surface proteins. Three of these methods--cell surface coating with cationic colloidal silica beads, biotinylation and chemical capture of surface glycoproteins--allow for marked enrichment of this subcellular proteome, with each approach offering unique advantages and characteristics for different experiments. In this article, we introduce the principles of each purification method and discuss applications from the recent literature.

Decoding signalling networks by mass spectrometry-based proteomics

Signalling networks regulate essentially all of the biology of cells and organisms in normal and disease states. Signalling is often studied using antibody-based techniques such as western blots. Large-scale 'precision proteomics' based on mass spectrometry now enables the system-wide characterization of signalling events at the levels of post-translational modifications, protein-protein interactions and changes in protein expression. This technology delivers accurate and unbiased information about the quantitative changes of thousands of proteins and their modifications in response to any perturbation. Current studies focus on phosphorylation, but acetylation, methylation, glycosylation and ubiquitylation are also becoming amenable to investigation. Large-scale proteomics-based signalling research will fundamentally change our understanding of signalling networks.

A genetic engineering solution to the "arginine conversion problem" in stable isotope labeling by amino acids in cell culture (SILAC)

Stable isotope labeling by amino acids in cell culture (SILAC) provides a straightforward tool for quantitation in proteomics. However, one problem associated with SILAC is the in vivo conversion of labeled arginine to other amino acids, typically proline. We found that arginine conversion in the fission yeast Schizosaccharomyces pombe occurred at extremely high levels, such that labeling cells with heavy arginine led to undesired incorporation of label into essentially all of the proline pool as well as a substantial portion of glutamate, glutamine, and lysine pools. We found that this can be prevented by deleting genes involved in arginine catabolism using methods that are highly robust yet simple to implement. Deletion of both fission yeast arginase genes or of the single ornithine transaminase gene, together with a small modification to growth medium that improves arginine uptake in mutant strains, was sufficient to abolish essentially all arginine conversion. We demonstrated the usefulness of our approach in a large scale quantitative analysis of proteins before and after cell division; both up- and down-regulated proteins, including a novel protein involved in septation, were successfully identified. This strategy for addressing the “arginine conversion problem” may be more broadly applicable to organisms amenable to genetic manipulation.

GABAB receptor constituents revealed by tandem affinity purification from transgenic mice

GABA(B) receptors function as heterodimeric G-protein-coupled receptors for the neurotransmitter gamma-aminobutyric acid (GABA). Receptor subtypes, based on isoforms of the ligand-binding subunit GABA(B1), are thought to involve a differential set of associated proteins. Here, we describe two mouse lines that allow a straightforward biochemical isolation of GABA(B) receptors. The transgenic mice express GABA(B1) isoforms that contain sequences for a two-step affinity purification, in addition to their endogenous subunit repertoire. Comparative analyses of purified samples from the transgenic mice and wild-type control animals revealed two novel components of the GABA(B1) complex. One of the identified proteins, potassium channel tetramerization domain-containing protein 12, associates with heterodimeric GABA(B) receptors via the GABA(B2) subunit. In transfected hippocampal neurons, potassium channel tetramerization domain-containing protein 12 augmented axonal surface targeting of GABA(B2). The mice equipped with tags on GABA(B1) facilitate validation and identification of native binding partners of GABA(B) receptors, providing insight into the molecular mechanisms of synaptic modulation.

Multi-dimensional liquid chromatography in proteomics--a review

Proteomics is the large-scale study of proteins, particularly their expression, structures and functions. This still-emerging combination of technologies aims to describe and characterize all expressed proteins in a biological system. Because of upper limits on mass detection of mass spectrometers, proteins are usually digested into peptides and the peptides are then separated, identified and quantified from this complex enzymatic digest. The problem in digesting proteins first and then analyzing the peptide cleavage fragments by mass spectrometry is that huge numbers of peptides are generated that overwhelm direct mass spectral analyses. The objective in the liquid chromatography approach to proteomics is to fractionate peptide mixtures to enable and maximize identification and quantification of the component peptides by mass spectrometry. This review will focus on existing multidimensional liquid chromatographic (MDLC) platforms developed for proteomics and their application in combination with other techniques such as stable isotope labeling. We also provide some perspectives on likely future developments.

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 .

Proteome-wide quantitation by SILAC

Ongoing improvements in instrumentation, fractionation techniques, and enrichment procedures have dramatically increased the coverage of the proteome achievable via LC-MS/MS-based methodologies, opening the call for approaches to quantitatively assess differences at a proteome-wide scale. Stable isotope labeling by amino acids in cell culture (SILAC) has emerged as a powerful and versatile approach for proteome-wide quantitation by mass spectrometry. SILAC utilizes the cells' own metabolism to incorporate isotopically labeled amino acids into its proteome which can be mixed with the proteome of unlabeled cells and differences in protein expression can easily be read out by comparing the abundance of the labeled versus unlabeled proteins. SILAC has been applied to numerous different cell lines and the technique has been adapted for a wide range of experimental procedures. In this chapter we provide detailed procedure for performing SILAC-based experiment for proteome-wide quantitation, including a protocol for optimizing SILAC labeling. We also provide an update on the most recent developments of this technique.

Current trends in quantitative proteomics

It was inevitable that as soon as mass spectrometrists were able to tell biologists which proteins were in their samples, the next question would be how much of these proteins were present. This has turned out to be a much more challenging question. In this review, we describe the multiple ways that mass spectrometry has attempted to address this issue, both for relative quantitation and for absolute quantitation of proteins. There is no single method that will work for every problem or for every sample. What we present here is a variety of techniques, with guidelines that we hope will assist the researcher in selecting the most appropriate technique for the particular biological problem that needs to be addressed. We need to emphasize that this is a very active area of proteomics research-new quantitative methods are continuously being introduced and some 'pitfalls' of older methods are just being discovered. However, even though there is no perfect technique--and a better technique may be developed tomorrow--valuable information on biomarkers and pathways can be obtained using these currently available methods.