Direct Comparison of Stable Isotope Labeling by Amino Acids in Cell Culture and Spectral Counting for Quantitative Proteomics

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.

Mass spectrometry–based relative quantification of proteins in precatalytic and catalytically active spliceosomes by metabolic labeling (SILAC), chemical labeling (iTRAQ), and label-free spectral count

“…In agreement with previous comparative studies on MSbased quantification (Hendrickson et al 2006;Collier et al 2010;Li et al 2012), discrepancies between the isotope labeling and the spectral count techniques were seen, especially for small proteins (<20 kDa, e.g., Sm proteins) (Table 1), for which accurate quantification was not achieved by spectral count owing to the limited number of peptides that were generated. The spectral count was also a little less accurate than labeling in quantifying proteins present in equal amounts within the B and C complexes, such as U5-220K (B:C 1.68), U5-40K (B:C 1.50), and CBP20 (0.79) (see Supplemental Tables 2, 4, 6).…”

Integrated Proteomic Profiling of Cell Line Conditioned Media and Pancreatic Juice for the Identification of Pancreatic Cancer Biomarkers

“…Normalized spectral counts have been reported previously to be reliable indicators of protein abundance in studies comparing different label-free methods, and strong correlation between spectral counts and protein abundance have been shown (51). When restricting analysis to proteins identified with five or more spectra, results comparable to label-based approaches are obtainable (96). In the present study, this method was used for relative quantification between the cancer cell lines and the HPDE cell line.…”

Evaluation of Normalization Methods on GeLC-MS/MS Label-Free Spectral Counting Data to Correct for Variation during Proteomic Workflows

“…Here we defined very low SpC proteins as those with less than 1.67 SpC per replicate injection, or an average of five total spectral counts between two samples. Earlier studies by Old et al [11] and Collier et al [3] also proposed a cutoff of 5 or more total spectral counts across 2 samples, both having triplicate injections, to ensure accurate quantification. Gammulla et al [32] utilized even more stringent criteria, allowing for quantification of proteins having six or more spectral counts in each sample when triplicate injections were performed.…”

“…Advantages of label-free approaches compared to label incorporated methods (e.g., SILAC [1,2]) include simplicity of sample preparation and applicability to any organism. Additionally, reduced sample complexity allows for an increase in the number of peptides sequenced, which results in a greater dynamic range and more comprehensive proteome coverage [3,4]. Spectral counting [5] and ion abundance [6][7][8][9][10] have been used for label-free quantification and are known to correlate with protein abundance [11].…”