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. 2013;9(1):e1002842.
doi: 10.1371/journal.pcbi.1002842. Epub 2013 Jan 10.

Phosphorylation variation during the cell cycle scales with structural propensities of proteins

Stefka Tyanova  1 , Jürgen Cox, Jesper Olsen, Matthias Mann, Dmitrij Frishman
Affiliations

Phosphorylation variation during the cell cycle scales with structural propensities of proteins

Stefka Tyanova et al. PLoS Comput Biol. 2013.

Abstract

Phosphorylation at specific residues can activate a protein, lead to its localization to particular compartments, be a trigger for protein degradation and fulfill many other biological functions. Protein phosphorylation is increasingly being studied at a large scale and in a quantitative manner that includes a temporal dimension. By contrast, structural properties of identified phosphorylation sites have so far been investigated in a static, non-quantitative way. Here we combine for the first time dynamic properties of the phosphoproteome with protein structural features. At six time points of the cell division cycle we investigate how the variation of the amount of phosphorylation correlates with the protein structure in the vicinity of the modified site. We find two distinct phosphorylation site groups: intrinsically disordered regions tend to contain sites with dynamically varying levels, whereas regions with predominantly regular secondary structures retain more constant phosphorylation levels. The two groups show preferences for different amino acids in their kinase recognition motifs - proline and other disorder-associated residues are enriched in the former group and charged residues in the latter. Furthermore, these preferences scale with the degree of disorderedness, from regular to irregular and to disordered structures. Our results suggest that the structural organization of the region in which a phosphorylation site resides may serve as an additional control mechanism. They also imply that phosphorylation sites are associated with different time scales that serve different functional needs.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Temporal phosphorylation patterns of phospho-sites with distinct structural properties.
Phosphorylation fold changes of three sites (UniProt accession number and residue identification number are given) during the six time points is shown together with their corresponding local structure. From left to right the phosphorylation variation over the six time points increases, together with the level of disorder: from (A) regular secondary structure (α-helix or β-sheet) through (B) irregular coils and loops to (C) disordered regions. Phospho-serine residues (pS) within regular regions and loops show small fluctuations in their phosphorylation levels, while larger changes occur in disordered regions.
Figure 2
Figure 2. Comparison of phosphorylation variation of sites within different structural categories.
A) Sites within ordered regions (blue) show smaller variation of the phosphorylation fold change over the cell cycle than those within disordered regions (red). The significance of the observation has been tested with Kolmogorov-Smirnov test (p-value 6.6E-13). (B) The variation of phosphorylation changes over the cell cycle scales with the structural propensities of the phosphorylated residues: from lowest in regular structures (blue) to highest in disordered regions (red). The observed differences were found to be significant by ANOVA test (p-value 3.02E-09).
Figure 3
Figure 3. Two sample logo of flanking regions of phosphorylation sites of low versus high phosphorylation variation.
Amino acids in the top and bottom parts (A) – central residue serine and B) – central residue threonine) represent residues, which are enriched or depleted correspondingly in the flanking regions of sites with small phosphorylation variation. Strong preferences are found for charged residues such as arginine, aspartate, and glutamate. In contrast, the majority of the amino acids that are more frequent in the negative set (i.e. variable phosphorylation set) are disorder-related e.g. proline, serine and glycine.
Figure 4
Figure 4. Conservation of phosphorylated sites versus conservation of control sites taking into account local structure.
Lower values correspond to slower evolutionary rate and higher conservation. Phosphorylation sites predicted to lie within regular structures (in blue, pS/pT/pY regular) appeared to be more conserved than their equivalent non-phosphorylated residues from the same proteins (p-value 2.24e-16). The same tendency was present for modified sites in disordered regions (in red, pS/pT/pY disordered), which were also subjected to a statistically significant slower evolutionary rate than their control set (p-value 3.4E-03). Phosphorylation sites in regular structures showed higher conservation than that of phosphorylation sites in irregular structures (p-value 3.23E-120).
Figure 5
Figure 5. Kinase motif decomposition based on phosphorylation variability and structural preferences.
The preferences of various kinases for sites with specific structural background and phosphorylation variation were calculated by the 2D Annotation Enrichment technique (see Methods). In general four classes can be distinguished: (i) tyrosine kinases (black squares), (ii) proline-directed kinases (red circles), (iii) non-proline directed kinases with charged residues in their substrate recognition motif (green and blue triangles corresponding to acidophilic and basophilic kinases respectively) and (iv) proline-oriented kinases, which contain a proline residue in their motif at position different from +1 relative to the modification site (red triangles and pentagons). The vertical axis separates the kinases according to their structural preferences. Tyrosine kinases favor sites within ordered regions with small phosphorylation variability. Serine/threonine kinases prefer more disordered regions, but span a larger space of phosphorylation variation. There is a tendency towards increasing disorderedness with higher phosphorylation variation, which clearly separates non proline-directed, proline-oriented and proline-directed kinases, the latter being characterized by the largest variation in phosphorylation. Examples for each class are shown and the data of all kinases can be found in Table 2.
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Grants and funding

This research was supported by the DFG International Research Training Group ‘Regulation and Evolution of Cellular Systems’ (GRK 1563). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.