Co-occurring protein phosphorylation are functionally associated

Ying Li, Xueya Zhou, Zichao Zhai and Tingting Li

PLOS Computational Biology, 2017, vol. 13, issue 5, 1-23

Abstract: Post-translational modifications (PTMs) add a further layer of complexity to the proteome and regulate a wide range of cellular protein functions. With the increasing number of known PTM sites, it becomes imperative to understand their functional interplays. In this study, we proposed a novel analytical strategy to explore functional relationships between PTM sites by testing their tendency to be modified together (co-occurrence) under the same condition, and applied it to proteome-wide human phosphorylation data collected under 88 different laboratory or physiological conditions. Co-occurring phosphorylation occurs significantly more frequently than randomly expected and include many known examples of cross-talk or functional connections. Such pairs, either within the same phosphoprotein or between interacting partners, are more likely to be in sequence or structural proximity, be phosphorylated by the same kinases, participate in similar biological processes, and show residue co-evolution across vertebrates. In addition, we also found that their co-occurrence states tend to be conserved in orthologous phosphosites in the mouse proteome. Together, our results support that the co-occurring phosphorylation are functionally associated. Comparison with existing methods further suggests that co-occurrence analysis can be a useful complement to uncover novel functional associations between PTM sites.Author summary: In addition to gene expression and translation control, post-translational modifications (PTMs) represent another level to regulate proteins functions. Different PTM sites within a protein usually co-operate to fulfill their functional roles. Recent advances in high-throughput mass spectrometry (MS) technologies have facilitated the proteome-wide identification of PTM sites, giving rise to both challenge and opportunity to understand their functional relationships. Previously, several data mining approaches have been developed to explore the global PTM interplays. In this study, we proposed to infer functional associations between PTM sites from the correlation of their modification status across many biological conditions, which was not exploited before. In practice, we tested if a pair of sites are modified together under the same condition significantly more often than expected (co-occurrence). As a proof of principle, we applied this analytical strategy to human phosphorylation because we could collect data sets of proteome-wide coverage under 88 different conditions. We demonstrated that sites with co-occurring phosphorylation status are functionally associated from several lines of evidence. The co-occurrence analysis can also uncover functionally connected phosphosites with clear biological evidence which are missed by other approaches. With increasing proteome-wide data for other types of PTMs under different conditions, the co-occurrence analysis can be integrated with other methods to identify novel PTM associations.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1005502

DOI: 10.1371/journal.pcbi.1005502

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