Tackling Misleading Peptide Regulation Fold Changes in Quantitative Proteomics
Relative quantification in proteomics is a common strategy to analyze differences in biological samples and time series experiments. However, the resulting fold changes can give a wrong picture of the peptide amounts contained in the compared samples.
Fold changes hide the actual amounts of peptides. In addition posttranslational modifications can redistribute over multiple peptides, covering the same protein sequence, detected by mass spectrometry.
To circumvent these effects, a method was established to estimate the involved peptide amounts. The estimation of the theoretical peptide amount is based on the behavior of the peptide fold changes, in which lower peptide amounts are more susceptible to quantitative changes in a given sequence segment.
This method was successfully applied to a time-resolved analysis of growth receptor signaling in human prostate cancer cells. The theoretical peptide amounts show that high peptide fold changes can easily be nullified by the effects stated above.
KeywordsFold Change Peptide Regulation Human Prostate Cancer Cell Quantitative Proteomics Peptide Group
Unable to display preview. Download preview PDF.
- 1.Adachi, J., Kumar, C., Zhang, Y., Olsen, J.V., Mann, M.: The human urinary proteome contains more than 1500 proteins, including a large proportion of membrane proteins. Genome Biol. 7, R80 (2006)Google Scholar
- 3.Bodenmiller, B., Aebersold, R.: Quantitative Analysis of Protein Phosphorylation on a System-Wide Scale by Mass Spectrometry-Based Proteomics, vol. 470, pp. 317–334. Elsevier (2010)Google Scholar
- 5.de Godoy, L., Olsen, J., de Souza, G., Li, G., Mortensen, P., Mann, M.: Status of complete proteome analysis by mass spectrometry: SILAC labeled yeast as a model system. Genome Biology 7(6), R50 (2006)Google Scholar
- 6.Grosse-Coosmann, F., Boehm, A.M., Sickmann, A.: Efficient analysis and extraction of MS/MS result data from mascot result files. BMC bioinformatics 6 (2005)Google Scholar
- 16.Webb-Robertson, B.J.M., Matzke, M.M., Jacobs, J.M., Pounds, J.G., Waters, K.M.: A statistical selection strategy for normalization procedures in lc-ms proteomics experiments through dataset-dependent ranking of normalization scaling factors. PROTEOMICS (2011)Google Scholar