A comparative meta-proteomic pipeline for the identification of plasmodesmata proteins and regulatory conditions in diverse plant species.

Background: A major route for cell-to-cell signalling in plants is mediated by cell wall-embedded pores termed plasmodesmata forming the symplasm. Plasmodesmata regulate the plant development and responses to the environment; however, our understanding of what factors or regulatory cues affect their structure and permeability is still limited. In this paper, a meta-analysis was carried out for the identification of conditions affecting plasmodesmata transport and for the in silico prediction of plasmodesmata proteins in species for which the plasmodesmata proteome has not been experimentally determined.

Results: Using the information obtained from experimental proteomes, an analysis pipeline (named plasmodesmata in silico proteome 1 or PIP1) was developed to rapidly generate candidate plasmodesmata proteomes for 22 plant species. Using the in silico proteomes to interrogate published transcriptomes, gene interaction networks were identified pointing to conditions likely affecting plasmodesmata transport capacity. High salinity, drought and osmotic stress regulate the expression of clusters enriched in genes encoding plasmodesmata proteins, including those involved in the metabolism of the cell wall polysaccharide callose. Experimental determinations showed restriction in the intercellular transport of the symplasmic reporter GFP and enhanced callose deposition in Arabidopsis roots exposed to 75-mM NaCl and 3% PEG (polyethylene glycol). Using PIP1 and transcriptome meta-analyses, candidate plasmodesmata proteins for the legume Medicago truncatula were generated, leading to the identification of Medtr1g073320, a novel receptor-like protein that localises at plasmodesmata. Expression of Medtr1g073320 affects callose deposition and the root response to infection with the soil-borne bacteria rhizobia in the presence of nitrate.

Conclusions: Our study shows that combining proteomic meta-analysis and transcriptomic data can be a valuable tool for the identification of new proteins and regulatory mechanisms affecting plasmodesmata function. We have created the freely accessible pipeline PIP1 as a resource for the screening of experimental proteomes and for the in silico prediction of PD proteins in diverse plant species.