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ABSTRACT: We have characterized the subcellular proteome of human embryonic stem cells (hESCs) through MS analysis of the membrane, cytosolic, and nuclear fractions, isolated from the same sample of undifferentiated hESCs. Strikingly, 74% of all proteins identified were detected in a single subcellular fraction; we also carried out immunofluorescence studies to validate the subcellular localization suggested by proteomic analysis, for a subset of proteins. Our approach resulted in deeper proteome coverage - peptides mapping to 893, 2475, and 1185 proteins were identified in the nuclear, cytosolic, and membrane fractions, respectively. Additionally, we used spectral counting to estimate the relative abundance of all cytosolic proteins. A large number of proteins relevant to hESC biology, including growth factor receptors, cell junction proteins, transcription factors, chromatin remodeling proteins, and histone modifying enzymes were identified. Our analysis shows that components of a large number of interacting signaling pathways are expressed in hESCs. Finally, we show that proteomic analysis of the endoplasmic reticulum (ER) and Golgi compartments is a powerful alternative approach to identify secreted proteins since these are synthesized in the ER and transit through the Golgi. Taken together, our results show that systematic subcellular proteomic analysis is a valuable tool for studying hESC biology.
Proteomics 12/2011; 12(3):421-30. · 4.43 Impact Factor
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ABSTRACT: Protein quantification is one of the principal goals of mass spectrometry (MS)-based proteomics, and many strategies exist to achieve it. Several approaches involve the incorporation of a stable-isotope label using either chemical derivatization, enzymatically catalyzed incorporation of (18)O, or metabolic labeling in a cell or tissue culture. These techniques can be cost or time prohibitive or not amenable to the biological system of interest. Label-free techniques including those utilizing integrated ion abundance and spectral counting offer an alternative to stable-isotope-based methodologies. Herein, we present the comparison of stable-isotope labeling of amino acids in cell culture (SILAC) with spectral counting for the quantification of human embryonic stem cells as they differentiate toward the trophectoderm at three time points. Our spectral counting experimental strategy resulted in the identification of 2641 protein groups across three time points with an average sequence coverage of 30.3%, of which 1837 could be quantified with more than five spectral counts. SILAC quantification was able to identify 1369 protein groups with an average coverage of 24.7%, of which 1027 could be quantified across all time points. Within this context we further explore the capacity of each strategy for proteome coverage, variation in quantification, and the relative sensitivity of each technique to the detection of change in relative protein expression.
Rapid Communications in Mass Spectrometry 09/2011; 25(17):2524-32. · 2.79 Impact Factor
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ABSTRACT: Numerous experimental strategies exist for relative protein quantification, one of the primary objectives of mass spectrometry based proteomics analysis. These strategies mostly involve the incorporation of a stable isotope label via either metabolic incorporation in cell or tissue culture (¹⁵N/¹⁴N metabolic labeling, stable isotope labeling by amino acids in cell culture (SILAC)), chemical derivatization (ICAT, iTRAQ, TMT), or enzymatically catalyzed incorporation (¹⁸O labeling). Also, these techniques can be cost or time prohibitive or not amenable to the biological system of interest (i.e., metabolic labeling of clinical samples, most animals, or fungi). This is the case with the quantification of fungal proteomes, which often require auxotroph mutants to fully metabolically label. Alternatively, label-free strategies for protein quantification such as using integrated ion abundance and spectral counting have been demonstrated for quantification affording over 2 orders of magnitude of dynamic range which is comparable to metabolic labeling strategies. Direct comparisons of these quantitative techniques are largely lacking in the literature but are highly warranted in order to evaluate the capabilities, limitations, and analytical variability of available quantitative strategies. Here, we present the direct comparison of SILAC to label-free quantification by spectral counting of an identical set of data from the bottom-up proteomic analysis of human embryonic stem cells, which are readily able to be quantified using both strategies, finding that both strategies result in a similar number of protein identifications. We also discuss necessary constraints for accurate quantification using spectral counting and assess the potential of this label-free strategy as a viable alternative for quantitative proteomics.
Analytical Chemistry 10/2010; 82(20):8696-702. · 5.86 Impact Factor
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ABSTRACT: 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.
Journal of the American Society for Mass Spectrometry 02/2010; 21(6):879-89. · 4.00 Impact Factor
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ABSTRACT: Age-related macular degeneration (AMD) is the leading cause of legal blindness among the elderly population in the industrialized world, affecting about 14 million people in the United States alone. Smoking is a major environmental risk factor for AMD, and hydroquinone is a major component in cigarette smoke. Hydroquinone induces the formation of cell membrane blebs in human retinal pigment epithelium (RPE). Blebs may accumulate and eventually contribute first to sub-RPE deposits and then drusen formation, which is a prominent histopathologic feature in eyes with AMD. As an attempt to better understand the mechanisms involved in early AMD, we sought to investigate the proteomic profile of RPE blebs. Isolated blebs were subjected to SDS-PAGE fractionation, and in-gel trypsin-digested peptides were analyzed by LC-MS/MS that lead to the identification of a total of 314 proteins. Identified proteins were predominantly involved in oxidative phosphorylation, cell junction, focal adhesion, cytoskeleton regulation, and immunogenic processes. Importantly basigin and matrix metalloproteinase-14, key proteins involved in extracellular matrix remodeling, were identified in RPE blebs and shown to be more prevalent in AMD patients. Altogether our findings suggest, for the first time, the potential involvement of RPE blebs in eye disease and shed light on the implication of cell-derived microvesicles in human pathology.
Molecular & Cellular Proteomics 07/2009; 8(10):2201-11. · 7.40 Impact Factor
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ABSTRACT: Online liquid chromatography-mass spectrometric (LC-MS) analysis of intact proteins (i.e., top-down proteomics) is a growing area of research in the mass spectrometry community. A major advantage of top-down MS characterization of proteins is that the information of the intact protein is retained over the vastly more common bottom-up approach that uses protease-generated peptides to search genomic databases for protein identification. Concurrent to the emergence of top-down MS characterization of proteins has been the development and implementation of the stable isotope labeling of amino acids in cell culture (SILAC) method for relative quantification of proteins by LC-MS. Herein we describe the qualitative and quantitative top-down characterization of proteins derived from SILAC-labeled Aspergillus flavus using nanoflow reversed-phase liquid chromatography directly coupled to a linear ion trap Fourier transform ion cyclotron resonance mass spectrometer (nLC-LTQ-FTICR-MS). A. flavus is a toxic filamentous fungus that significantly impacts the agricultural economy and human health. SILAC labeling improved the confidence of protein identification, and we observed 1318 unique protein masses corresponding to 659 SILAC pairs, of which 22 were confidently identified. However, we have observed some limiting issues with regard to protein quantification using top-down MS/MS analyses of SILAC-labeled proteins. The role of SILAC labeling in the presence of competing endogenously produced amino acid residues and its impact on quantification of intact species are discussed in detail.
Analytical Chemistry 08/2008; 80(13):4994-5001. · 5.86 Impact Factor
