Abstract
Strong cation exchange (SCX) chromatography has been utilized as an excellent separation technique that can be combined with reversed-phase (RP) chromatography, which is frequently used in peptide mass spectrometry. Although SCX is valuable as the second component of such two-dimensional separation methods, its application goes far beyond efficient fractionation of complex peptide mixtures. Here I describe how SCX facilitates mapping of the protein posttranslational modifications (PTMs), specifically phosphorylation and N-terminal acetylation. The SCX chromatography has been mainly used for enrichment of these two PTMs, but it might also be beneficial for high-throughput analysis of other modifications that alter the net charge of a peptide.
Highlights
Posttranslational modifications (PTMs) regulate protein function, subcellular localization, and degradation
Current efforts are focused on optimizing the strong cation exchange (SCX) chromatography for analysis of phosphorylation as a key signaling modification, this HPLC method has a potential to be used in analysis of other PTMs that alter a net charge of the peptides
SCX could be possibly used in glycomics, based on the assumption that many extracellular N-glycans contain sialic acid residues, thereby reducing the net charge of glycopeptides in comparison with the unmodified peptides [42]
Summary
Posttranslational modifications (PTMs) regulate protein function, subcellular localization, and degradation. Detection of the modified residues is crucial for understanding of the physiological roles of proteins as well as their mechanisms and pathways, it still represents a challenge. It is especially true in case of global proteome studies, in which hundreds or thousands of modified sites are monitored at the same time, and such analyses are becoming more required due to an increasing popularity of the systems biology approaches. Mass-spectrometry-based proteomics offers highly sensitive tools for modification mapping (reviewed in [1, 2]), where thousands of proteins can be concurrently analyzed to construct and validate comprehensive physiological models.
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