Large-scale phosphoprotein analysis in Medicago truncatula roots provides insight into in vivo kinase activity in legumes

对蒺藜苜蓿根系中磷蛋白的大规模分析揭示了豆科植物体内激酶活性的机制

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Abstract

Nitrogen fixation in legumes requires the development of root organs called nodules and their infection by symbiotic rhizobia. Over the last decade, Medicago truncatula has emerged as a major model plant for the analysis of plant-microbe symbioses and for addressing questions pertaining to legume biology. While the initiation of symbiosis and the development of nitrogen-fixing root nodules depend on the activation of a protein phosphorylation-mediated signal transduction cascade in response to symbiotic signals produced by the rhizobia, few sites of in vivo phosphorylation have previously been identified in M. truncatula. We have characterized sites of phosphorylation on proteins from M. truncatula roots, from both whole cell lysates and membrane-enriched fractions, using immobilized metal affinity chromatography and tandem mass spectrometry. Here, we report 3,457 unique phosphopeptides spanning 3,404 nonredundant sites of in vivo phosphorylation on 829 proteins in M. truncatula Jemalong A17 roots, identified using the complementary tandem mass spectrometry fragmentation methods electron transfer dissociation and collision-activated dissociation. With this being, to our knowledge, the first large-scale plant phosphoproteomic study to utilize electron transfer dissociation, analysis of the identified phosphorylation sites revealed phosphorylation motifs not previously observed in plants. Furthermore, several of the phosphorylation motifs, including LxKxxs and RxxSxxxs, have yet to be reported as kinase specificities for in vivo substrates in any species, to our knowledge. Multiple sites of phosphorylation were identified on several key proteins involved in initiating rhizobial symbiosis, including SICKLE, NUCLEOPORIN133, and INTERACTING PROTEIN OF DMI3. Finally, we used these data to create an open-access online database for M. truncatula phosphoproteomic data.

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