No abstract

Plant-microbe interactions in the rhizosphere have important roles in biogeochemical cycling, and maintenance of plant health and productivity, yet remain poorly understood. Using RNA-based metatranscriptomics, the global active microbiomes were analysed in soil and rhizospheres of wheat, oat, pea and an oat mutant (sad1) deficient in production of anti-fungal avenacins. Rhizosphere microbiomes differed from bulk soil and between plant species. Pea (a legume) had a much stronger effect on the rhizosphere than wheat and oat (cereals), resulting in a dramatically different rhizosphere community. The relative abundance of eukaryotes in the oat and pea rhizospheres was more than fivefold higher than in the wheat rhizosphere or bulk soil. Nematodes and bacterivorous protozoa were enriched in all rhizospheres, whereas the pea rhizosphere was highly enriched for fungi. Metabolic capabilities for rhizosphere colonisation were selected, including cellulose degradation (cereals), H 2 oxidation (pea) and methylotrophy (all plants). Avenacins had little effect on the prokaryotic community of oat, but the eukaryotic community was strongly altered in the sad1 mutant, suggesting that avenacins have a broader role than protecting from fungal pathogens. Profiling microbial communities with metatranscriptomics allows comparison of relative abundance, from multiple samples, across all domains of life, without polymerase chain reaction bias. This revealed profound differences in the rhizosphere microbiome, particularly at the kingdom level between plants.

The multicellular nature of plants requires that cells should communicate in order to coordinate essential functions. This is achieved in part by molecular flux through pores in the cell wall, called plasmodesmata. We describe the proteomic analysis of plasmodesmata purified from the walls of Arabidopsis suspension cells. Isolated plasmodesmata were seen as membrane-rich structures largely devoid of immunoreactive markers for the plasma membrane, endoplasmic reticulum and cytoplasmic components. Using nano-liquid chromatography and an Orbitrap ion-trap tandem mass spectrometer, 1341 proteins were identified. We refer to this list as the plasmodesmata- or PD-proteome. Relative to other cell wall proteomes, the PD-proteome is depleted in wall proteins and enriched for membrane proteins, but still has a significant number (35%) of putative cytoplasmic contaminants, probably reflecting the sensitivity of the proteomic detection system. To validate the PD-proteome we searched for known plasmodesmal proteins and used molecular and cell biological techniques to identify novel putative plasmodesmal proteins from a small subset of candidates. The PD-proteome contained known plasmodesmal proteins and some inferred plasmodesmal proteins, based upon sequence or functional homology with examples identified in different plant systems. Many of these had a membrane association reflecting the membranous nature of isolated structures. Exploiting this connection we analysed a sample of the abundant receptor-like class of membrane proteins and a small random selection of other membrane proteins for their ability to target plasmodesmata as fluorescently-tagged fusion proteins. From 15 candidates we identified three receptor-like kinases, a tetraspanin and a protein of unknown function as novel potential plasmodesmal proteins. Together with published work, these data suggest that the membranous elements in plasmodesmata may be rich in receptor-like functions, and they validate the content of the PD-proteome as a valuable resource for the further uncovering of the structure and function of plasmodesmata as key components in cell-to-cell communication in plants.

With the completion of the sequencing of the Arabidopsis genome and the recent advances in proteomic technology, the identification of proteins from highly complex mixtures is now possible. Rather than using gel electrophoresis and peptide mass fingerprinting, we have used multidimensional protein identification technology (MudPIT) to analyse the "tightly-bound" proteome for purified cell walls from Arabidopsis cell suspension cultures. Using bioinformatics for the prediction of signal peptides for targeting to the secretory pathway and for the absence of ER retention signal, 89 proteins were selected as potential extracellular proteins. Only 33% of these were identified in previous proteomic analyses of Arabidopsis cell walls. A functional classification revealed that a large proportion of the proteins were enzymes, notably carbohydrate active enzymes, peroxidases and proteases. Comparison of all the published proteomic analyses for the Arabidopsis cell wall identified 268 non-redundant genes encoding wall proteins. Sixty of these (22%) were derived from our analysis of tightly-bound wall proteins.