Engineering transkingdom signalling in plants to control gene expression in rhizosphere bacteria

Abstract: The root microbiota is critical for agricultural yield, with growth-promoting bacteria able to solubilise phosphate, produce plant growth hormones, antagonise pathogens and fix N2. Plants control the microorganisms in their immediate environment and this is at least in part through direct selection, the immune system, and interactions with other microorganisms. Considering the importance of the root microbiota for crop yields it is attractive to artificially regulate this environment to optimise agricultural productivity. Towards this aim we express a synthetic pathway for the production of the rhizopine scyllo-inosamine in plants. We demonstrate the production of this bacterial derived signal in both Medicago truncatula and barley and show its perception by rhizosphere bacteria, containing bioluminescent and fluorescent biosensors. This study lays the groundwork for synthetic signalling networks between plants and bacteria, allowing the targeted regulation of bacterial gene expression in the rhizosphere for delivery of useful functions to plants

PPDB, the Plant Proteomics Database at Cornell

The Plant Proteomics Database (PPDB; http://ppdb.tc.cornell.edu), launched in 2004, provides an integrated resource for experimentally identified proteins in Arabidopsis and maize (Zea mays). Internal BLAST alignments link maize and Arabidopsis information. Experimental identification is based on in-house mass spectrometry (MS) of cell type-specific proteomes (maize), or specific subcellular proteomes (e.g. chloroplasts, thylakoids, nucleoids) and total leaf proteome samples (maize and Arabidopsis). So far more than 5000 accessions both in maize and Arabidopsis have been identified. In addition, more than 80 published Arabidopsis proteome datasets from subcellular compartments or organs are stored in PPDB and linked to each locus. Using MS-derived information and literature, more than 1500 Arabidopsis proteins have a manually assigned subcellular location, with a strong emphasis on plastid proteins. Additional new features of PPDB include searchable posttranslational modifications and searchable experimental proteotypic peptides and spectral count information for each identified accession based on in-house experiments. Various search methods are provided to extract more than 40 data types for each accession and to extract accessions for different functional categories or curated subcellular localizations. Protein report pages for each accession provide comprehensive overviews, including predicted protein properties, with hyperlinks to the most relevant databases

Defining the Rhizobium leguminosarum Species Complex

Bacteria currently included in Rhizobium leguminosarum are too diverse to be considered a single species, so we can refer to this as a species complex (the Rlc). We have found 429 publicly available genome sequences that fall within the Rlc and these show that the Rlc is a distinct entity, well separated from other species in the genus. Its sister taxon is R. anhuiense. We constructed a phylogeny based on concatenated sequences of 120 universal (core) genes, and calculated pairwise average nucleotide identity (ANI) between all genomes. From these analyses, we concluded that the Rlc includes 18 distinct genospecies, plus 7 unique strains that are not placed in these genospecies. Each genospecies is separated by a distinct gap in ANI values, usually at approximately 96% ANI, implying that it is a ‘natural’ unit. Five of the genospecies include the type strains of named species: R. laguerreae, R. sophorae, R. ruizarguesonis, “R. indicum” and R. leguminosarum itself. The 16S ribosomal RNA sequence is remarkably diverse within the Rlc, but does not distinguish the genospecies. Partial sequences of housekeeping genes, which have frequently been used to characterize isolate collections, can mostly be assigned unambiguously to a genospecies, but alleles within a genospecies do not always form a clade, so single genes are not a reliable guide to the true phylogeny of the strains. We conclude that access to a large number of genome sequences is a powerful tool for characterizing the diversity of bacteria, and that taxonomic conclusions should be based on all available genome sequences, not just those of type strains

Defining the Rhizobium leguminosarum Species Complex

Bacteria currently included in Rhizobium leguminosarum are too diverse to be considered a single species, so we can refer to this as a species complex (the Rlc). We have found 429 publicly available genome sequences that fall within the Rlc and these show that the Rlc is a distinct entity, well separated from other species in the genus. Its sister taxon is R. anhuiense. We constructed a phylogeny based on concatenated sequences of 120 universal (core) genes, and calculated pairwise average nucleotide identity (ANI) between all genomes. From these analyses, we concluded that the Rlc includes 18 distinct genospecies, plus 7 unique strains that are not placed in these genospecies. Each genospecies is separated by a distinct gap in ANI values, usually at approximately 96% ANI, implying that it is a ‘natural’ unit. Five of the genospecies include the type strains of named species: R. laguerreae, R. sophorae, R. ruizarguesonis, “R. indicum” and R. leguminosarum itself. The 16S ribosomal RNA sequence is remarkably diverse within the Rlc, but does not distinguish the genospecies. Partial sequences of housekeeping genes, which have frequently been used to characterize isolate collections, can mostly be assigned unambiguously to a genospecies, but alleles within a genospecies do not always form a clade, so single genes are not a reliable guide to the true phylogeny of the strains. We conclude that access to a large number of genome sequences is a powerful tool for characterizing the diversity of bacteria, and that taxonomic conclusions should be based on all available genome sequences, not just those of type strains

Evaluation of chloroform/methanol extraction to facilitate the study of membrane proteins of non-model plants

Membrane proteins are of great interest to plant physiologists because of their important function in many physiological processes. However, their study is hampered by their low abundance and poor solubility in aqueous buffers. Proteomics studies of non-model plants are generally restricted to gel-based methods. Unfortunately, all gel-based techniques for membrane proteomics lack resolving power. Therefore, a very stringent enrichment method is needed before protein separation. In this study, protein extraction in a mixture of chloroform and methanol in combination with gel electrophoresis is evaluated as a method to study membrane proteins in non-model plants. Benefits as well as disadvantages of the method are discussed. To demonstrate the pitfalls of working with non-model plants and to give a proof of principle, the method was first applied to whole leaves of the model plant Arabidopsis. Subsequently, a comparison with proteins extracted from leaves of the non-model plant, banana, was made. To estimate the tissue and organelle specificity of the method, it was also applied on banana meristems. Abundant membrane or lipid-associated proteins could be identified in both tissues, with the leaf extract yielding a higher number of membrane proteins

Proteomic analysis of pollination-induced corolla senescence in petunia

Senescence represents the last phase of petal development during which macromolecules and organelles are degraded and nutrients are recycled to developing tissues. To understand better the post-transcriptional changes regulating petal senescence, a proteomic approach was used to profile protein changes during the senescence of Petunia×hybrida ‘Mitchell Diploid’ corollas. Total soluble proteins were extracted from unpollinated petunia corollas at 0, 24, 48, and 72 h after flower opening and at 24, 48, and 72 h after pollination. Two-dimensional gel electrophoresis (2-DE) was used to identify proteins that were differentially expressed in non-senescing (unpollinated) and senescing (pollinated) corollas, and image analysis was used to determine which proteins were up- or down-regulated by the experimentally determined cut-off of 2.1-fold for P <0.05. One hundred and thirty-three differentially expressed protein spots were selected for sequencing. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to determine the identity of these proteins. Searching translated EST databases and the NCBI non-redundant protein database, it was possible to assign a putative identification to greater than 90% of these proteins. Many of the senescence up-regulated proteins were putatively involved in defence and stress responses or macromolecule catabolism. Some proteins, not previously characterized during flower senescence, were identified, including an orthologue of the tomato abscisic acid stress ripening protein 4 (ASR4). Gene expression patterns did not always correlate with protein expression, confirming that both proteomic and genomic approaches will be required to obtain a detailed understanding of the regulation of petal senescence