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.

No 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.

Background: Specification of terminal fate in trophoblasts derived from human embryonic stem cells is not understood. Results: Inhibition of activin/nodal signaling triggers extravillous fate, but loss of inhibition causes syncytial fate. Conclusion: Activin/nodal signaling switches the terminal fate of trophoblasts. Significance: We provide a model system that allows for targeted derivation of extravillous trophoblasts and syncytiotrophoblasts.

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.