Spectral count

Reproducibility testing demonstrated that protein abundance measured using the spectral counting method exhibited a Pearson correlation R2 value >0.99 and a coefficient of variance of 14% (Fig. 20.6). 

Figure 20.8 Identifications of spectral counts, peptide sequences, and proteins in archival FFPE liver tissue across a time course of increasing fixation time. Reproduced with permission from Reference 20.

TABLE 20.1 Summary of IHC Staining Results and Comparison with Spectral Counts Measured by Shotgun Proteomics... 

Protein IHC Staining Intensity (Number of Spectral Counts) ... 

Balgley BM, Wang W, Song T, et al. Evaluation of confidence and reproducibility in quantitative proteomics performed by a capillary isoelectric focusing-based proteomic platform coupled with a spectral counting approach. Electrophoresis 2008 29 3047-3054. 

Another software program takes advantage of simultaneous spectral counting and a total ion chromatogram to enhance analysis quality (69). 

Figure 13.2-3. Yeast cell extract HPLC fractionation and LC-MS analysis. (A) Comparison of representative proteomic patterns recorded for two consecutive HPLC prefractionations. (B) Graphical comparison of HPLC prefractionation and straight analysis of the whole ceil extract (WCE) by LC-MS (a maximum protein spectral count was recorded for two successive HPLC runs and compared with the corresponding valne for the WCE). Black-to-red color shading indicates increasing spectral counts. (This fignre is available in full color at ftp //ftp.wiley.com/public/sci tech med/pharmaceutical biotech/.)...

Background Untreatable metastasis, rather than the primary tumor, is the cause of mortality in breast cancer. Myeloid-derived suppressor cells (MDSCs) are hema-topoetic cells that home specifically to the tumors and have a major role in tumor invasion and metastasis and the development of resistance to chemotherapy. MDSCs proliferate in response to tumors and accumulate in the spleen, from which they can be isolated using their Grl and CDllb surface markers. The objective was to use label-free mass spectrometry and shotgun proteomics to characterize MDSCs that associate with two mouse cell lines derived from the same tumor, one from the primary tumor (67NR) and the other from cells that have already metastasized to various organs (4T1). Spectral counting, for quantification, and protein network analysis were used to search for MDSC biomarkers characteristic to metastasis. 

Results and discussion Of 2,814 identified MDSC proteins 43 were exclusive to 67NR, 153 were exclusive to 4T1, and the rest (2,618) were shared. The shared (2,618) proteins were quantified by spectral counting and searched for up- and downregula-tion. Using one standard deviation as the threshold showed that 364 proteins were increased and 367 decreased in the 4T1 MDSCs, compared to the 67NR MDSCs. The proteins were primarily derived from the cytosol (34%) and nucleus (26%). Other substantial sources of the proteins were membranes, mitochondria, endoplasmic reticulum, and Golgi apparatus. 

One such method is based on ion intensities, assuming that there is a direct correlation between protein abundance and the area under the curve of the precursor ion spectra [75]. The other method is based on spectral counting, assuming a direct correlation between protein abundance and the number of MS/MS spectra obtained for the protein [76]. 

Pham, T.V., Piersma, S.R., Warmoes, M., and Jimenez, C.R. (2010) On the beta-binomial model for analysis of spectral count data in label-free tandem mass spectrometry-based proteomics. Bioinformatics. 26 (3), 363-369. 

Additional program(s) to validate the MS/MS-based peptide and protein identifications, to summarize results including MS/MS spectral counts (Scaffold, Proteome Software, Portland, OR), and to create aligned extracted-ion chromatograms (XICs, Sieve , Thermo), and so on. 

In order to profile proteins in the sample to confirm that changes occur in carbonylation stoichiometry rather than in the protein abundance. Scaffold allows for simultaneous comparison of multiple proteomic data sets in which the list of identified proteins can be sorted by various parameters. The spectral counting technique for relative protein quantitation utilizes the total number of MS/MS spectra identified for a particular protein as a measure of protein abundance, and consequently this parameter can be used to classify the abundance. Published protocols [14,15] can be used as methods for relative quantitation in which the change in abundance can be determined by the ratios as follows ... 

A 50% peptide probability can be used instead of the initial list of high-confidence identifications (99% protein confidence, 95% peptide confidence, and containing 2 unique peptides) in order to include peptides with lower Mascot scores that represent true positive identifications and would improve the overall spectral counting sensitivity. Ratios for proteins showing zero spectral counts in either control or treated groups should be tabulated as UC (unique in control) or UT (unique in treated). 

Spectral Count The total number of MS/MS spectra (usually corresponding to redundant and nonre-dundant peptides) used for identification of proteins. Spectral count increases with protein abundance, hence spectral counting is a useful approach in assessing relative protein abundance by a label-free quantitative strategy. 

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