Computational Analysis of the Predicted Evolutionary Conservation of Human Phosphorylation Sites

<div><p>Protein kinase-mediated phosphorylation is among the most important post-translational modifications. However, few phosphorylation sites have been experimentally identified for most species, making it difficult to determine the degree to which phosphorylation sites are conserved. The goal of this study was to use computational methods to characterize the conservation of human phosphorylation sites in a wide variety of eukaryotes. Using experimentally-determined human sites as input, homologous phosphorylation sites were predicted in all 432 eukaryotes for which complete proteomes were available. For each pair of species, we calculated phosphorylation site conservation as the number of phosphorylation sites found in both species divided by the number found in at least one of the two species. A clustering of the species based on this conservation measure was concordant with phylogenies based on traditional genomic measures. For a subset of the 432 species, phosphorylation site conservation was compared to conservation of both protein kinases and proteins in general. Protein kinases exhibited the highest degree of conservation, while general proteins were less conserved and phosphorylation sites were least conserved. Although preliminary, these data tentatively suggest that variation in phosphorylation sites may play a larger role in explaining phenotypic differences among organisms than differences in the complements of protein kinases or general proteins.</p></div

Comparison between the taxonomy of the 20 species described in the Materials and Methods section according to the National Center for Biotechnology Information (NCBI) Taxonomy Browser (panel A), and the dendrogram generated based on the phosphorylation site conservation of pairs of species (panel B).

<p>The scale applies to panel B only, with the branch lengths representing values of <i>C</i>(<i>S</i>_<i>A</i>, <i>S</i>_<i>B</i>). The species names are color-coded based on lineage: red, mammals; pink, insects; blue, fish; green, plants; purple, birds; orange, arachnids; yellow, nematodes; black, others (single-celled organisms of different lineages).</p

Comparison between the values of <i>C</i>(<i>S</i>_<i>A</i>, <i>S</i>_<i>B</i>) generated using Method 1 and those generated using the other three methods (<i>X</i> = 2, 3, and 4).

<p>Comparison between the values of <i>C</i>(<i>S</i>_<i>A</i>, <i>S</i>_<i>B</i>) generated using Method 1 and those generated using the other three methods (<i>X</i> = 2, 3, and 4).</p

Conservation of phosphorylation sites (upper triangle) and protein kinases (lower triangle) among 20 species from a diverse range of lineages.

<p>For a given pair of species, the values represent the percentage of phosphorylation sites or protein kinases found in at least one of the two species that were found in both species (the values <i>C</i>(<i>S</i>_<i>A</i>, <i>S</i>_<i>B</i>) described in the text). The cells are colored based on the value within; the closer the value is to 100, the brighter the shade of red.</p

Conservation of proteins among 20 species from a diverse range of lineages.

<p>For a given pair of species, the values represent the percentage of proteins found in at least one of the two species that were found in both species. The cells are colored based on the value within; the closer the value is to 100, the brighter the shade of red.</p

DAPPLE 2: a Tool for the Homology-Based Prediction of Post-Translational Modification Sites

The post-translational modification of proteins is critical for regulating their function. Although many post-translational modification sites have been experimentally determined, particularly in certain model organisms, experimental knowledge of these sites is severely lacking for many species. Thus, it is important to be able to predict sites of post-translational modification in such species. Previously, we described DAPPLE, a tool that facilitates the homology-based prediction of one particular post-translational modification, phosphorylation, in an organism of interest using known phosphorylation sites from other organisms. Here, we describe DAPPLE 2, which expands and improves upon DAPPLE in three major ways. First, it predicts sites for many post-translational modifications (20 different types) using data from several sources (15 online databases). Second, it has the ability to make predictions approximately 2–7 times faster than DAPPLE depending on the database size and the organism of interest. Third, it simplifies and accelerates the process of selecting predicted sites of interest by categorizing them based on gene ontology terms, keywords, and signaling pathways. We show that DAPPLE 2 can successfully predict known human post-translational modification sites using, as input, known sites from species that are either closely (e.g., mouse) or distantly (e.g., yeast) related to humans. DAPPLE 2 can be accessed at http://saphire.usask.ca/saphire/dapple2

Empirical distribution of random tree scores.

<p>Ten thousand random matrices were created from the matrix used to create the sample dendrogram in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080837#pone-0080837-g001" target="_blank">Figure 1</a> by randomly rearranging the peptide intensity values within each sample. For each score that was given to at least one random tree, the frequency of that score is indicated.</p

Heatmap and hierarchical clustering of kinome microarray profiles of samples from the example experiment using 17 peptides chosen according to a local search algorithm.

<p>The same distance metric and linkage method were used as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080837#pone-0080837-g001" target="_blank">Figure 1</a>. The sample names are the same as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080837#pone-0080837-g001" target="_blank">Figure 1</a>; the peptide names are also indicated on the right side of each row.</p

Screenshot of the user interface of the PIIKA 2 web server.

<p>Screenshot of the user interface of the PIIKA 2 web server.</p

Example of a PCA plot generated in VRML format by PIIKA 2.

<p>In this experiment, samples were taken from subjects labeled A, B, C, D, E, and F. Samples corresponding to subject A are in red, subject B are in yellow, and so on. The label near the top of the figure is the result of hovering the mouse over the leftmost red circle, and shows that the first, second, and third principal components for this sample had the values 2.46, 1.48, and 1.03, respectively. This image is an example of the visualization given using the VRML viewer Instant Player ( <a href="http://www.instantreality.org" target="_blank">http://www.instantreality.org</a> ).</p