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Interactions affected by arginine methylation in the yeast protein-protein interaction network.

ABSTRACT: Protein-protein interactions can be modulated by the methylation of arginine residues. As a means of testing this, we recently described a conditional two-hybrid system, based on the bacterial adenylate cyclase (BACTH) system. Here, we have used this conditional two-hybrid system to explore the effect of arginine methylation in modulating protein-protein interactions in a subset of the Saccharomyces cerevisiae arginine methylproteome network. Interactions between the yeast hub protein Npl3 and yeast proteins Air2, Ded1, Gbp2, Snp1, and Yra1 were first validated in the absence of methylation. The major yeast arginine methyltransferase Hmt1 was subsequently included in the conditional two-hybrid assay, initially to determine the degree of methylation that occurs. Proteins Snp1 and Yra1 were confirmed as Hmt1 substrates, with five and two novel arginine methylation sites mapped by ETD LC-MS/MS on these proteins, respectively. Proteins Ded1 and Gbp2, previously predicted but not confirmed as substrates of Hmt1, were also found to be methylated with five and seven sites mapped respectively. Air2 was found to be a novel substrate of Hmt1 with two sites mapped. Finally, we investigated the interactions of Npl3 with the five interaction partners in the presence of active Hmt1 and in the presence of Hmt1 with a G68R inactivation mutation. We found that the interaction between Npl3 and Air2, and Npl3 and Ded1, were significantly increased in the presence of active Hmt1; the interaction of Npl3 and Snp1 showed a similar degree of increase in interaction but this was not statistically significant. The interactions of Npl3 and Gbp2, along with Npl3 and Yra1, were not significantly increased or decreased by methylation. We conclude that methylarginine may be a widespread means by which the interactions of proteins are modulated.

SUBMITTER: Erce MA

PROVIDER: S-EPMC3820932 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe recently emerged protein interaction network paradigm can provide novel and important insights into the innerworkings of a cell. Yet, the heavy burden of both false positive and false negative protein-protein interaction data casts doubt on the broader usefulness of these interaction sets. Approaches focusing on one-protein-at-a-time have been powerfully employed to demonstrate the high degree of conservation of proteins participating in numerous interactions; here, we expand his 'node' focused paradigm to investigate the relative persistence of 'link' based evolutionary signals in a protein interaction network of S. cerevisiae and point out the value of this relatively untapped source of information.ResultsThe trend for highly connected proteins to be preferably conserved in evolution is stable, even in the context of tremendous noise in the underlying protein interactions as well as in the assignment of orthology among five higher eukaryotes. We find that local clustering around interactions correlates with preferred evolutionary conservation of the participating proteins; furthermore the correlation between high local clustering and evolutionary conservation is accompanied by a stable elevated degree of coexpression of the interacting proteins. We use this conserved interaction data, combined with P. falciparum/Yeast orthologs, as proof-of-principle that high-order network topology can be used comparatively to deduce local network structure in non-model organisms.ConclusionHigh local clustering is a criterion for the reliability of an interaction and coincides with preferred evolutionary conservation and significant coexpression. These strong and stable correlations indicate that evolutionary units go beyond a single protein to include the interactions among them. In particular, the stability of these signals in the face of extreme noise suggests that empirical protein interaction data can be integrated with orthologous clustering around these protein interactions to reliably infer local network structures in non-model organisms.

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Interactions affected by arginine methylation in the yeast protein-protein interaction network.

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