Project description:The transcriptome of Leptosphaeria maculans was analyzed in mycelium and during oilseed rape (Brassica napus) leaf infection. The array probes were designed from gene models from the L. maculans whole genome annotation. One aim of this study was to verify the expression of the automatically annotated gene models in various conditions. Another goal was to monitor gene expression profiles during oilseed rape leaf infection and to highlight tissue-specific transcripts, e.g. in plant up-regulated transcripts, for further analyses. We performed 9 hybridizations (NimbleGen) with samples derived from mycelium and infected oilseed rape leaves. Samples from infected oilseed rape leaves were harvested 7 and 14 days post infection. Three replicates each. All samples were labeled with Cy3.
Project description:<p>Biological nitrogen fixation by free-living bacteria and rhizobial symbiosis with legumes plays a key role in sustainable crop production. Here, we study how different crop combinations influence the interaction between peanut plants and their rhizosphere microbiota via metabolite deposition and functional responses of free-living and symbiotic nitrogen-fixing bacteria. Based on a long-term (8 year) diversified cropping field experiment, we find that peanut co-cultured with maize and oilseed rape lead to specific changes in peanut rhizosphere metabolite profiles and bacterial functions and nodulation. Flavonoids and coumarins accumulate due to the activation of phenylpropanoid biosynthesis pathways in peanuts. These changes enhance the growth and nitrogen fixation activity of free-living bacterial isolates, and root nodulation by symbiotic Bradyrhizobium isolates. Peanut plant root metabolites interact with Bradyrhizobium isolates contributing to initiate nodulation. Our findings demonstrate that tailored intercropping could be used to improve soil nitrogen availability through changes in the rhizosphere microbiome and its functions.</p>
Project description:Advances in DNA sequencing technologies has drastically changed our perception of the structure and complexity of the plant microbiome. By comparison, our ability to accurately identify the metabolically active fraction of soil microbiota and its specific functional role in augmenting plant health is relatively limited. Here, we combined our recently developed protein extraction method and an iterative bioinformatics pipeline to enable the capture and identification of extracellular proteins (metaexoproteomics) synthesised in the rhizosphere of Brassica spp. We first validated our method in the laboratory by successfully identifying proteins related to a host plant (Brassica rapa) and its bacterial inoculant, Pseudomonas putida BIRD-1. This identified numerous rhizosphere specific proteins linked to the acquisition of plant-derived nutrients in P. putida. Next, we analysed natural field-soil microbial communities associated with Brassica napus L. (oilseed rape). By combining metagenomics with metaexoproteomics, 1882 proteins were identified across bulk and rhizosphere samples. Meta-exoproteomics identified a clear shift (p<0.001) in the metabolically active fraction of the soil microbiota responding to the presence of B. napus roots that was not apparent in the composition of the total microbial community (metagenome). This metabolic shift was associated with the stimulation of rhizosphere-specialised bacteria, such as Gammaproteobacteria, Betaproteobacteria and Flavobacteriia and the upregulation of plant beneficial functions related to phosphorus and nitrogen mineralisation. Together, our metaproteomic assessment of the ‘active’ plant microbiome at the field-scale demonstrates the importance of moving past a genomic assessment of the plant microbiome in order to determine ecologically important plant-microbe interactions underpinning plant health.
Project description:Advances in DNA sequencing technologies has drastically changed our perception of the structure and complexity of the plant microbiome. By comparison, our ability to accurately identify the metabolically active fraction of soil microbiota and its specific functional role in augmenting plant health is relatively limited. Here, we combined our recently developed protein extraction method and an iterative bioinformatics pipeline to enable the capture and identification of extracellular proteins (metaexoproteomics) synthesised in the rhizosphere of Brassica spp. We first validated our method in the laboratory by successfully identifying proteins related to a host plant (Brassica rapa) and its bacterial inoculant, Pseudomonas putida BIRD-1. This identified numerous rhizosphere specific proteins linked to the acquisition of plant-derived nutrients in P. putida. Next, we analysed natural field-soil microbial communities associated with Brassica napus L. (oilseed rape). By combining metagenomics with metaexoproteomics, 1882 proteins were identified across bulk and rhizosphere samples. Meta-exoproteomics identified a clear shift (p<0.001) in the metabolically active fraction of the soil microbiota responding to the presence of B. napus roots that was not apparent in the composition of the total microbial community (metagenome). This metabolic shift was associated with the stimulation of rhizosphere-specialised bacteria, such as Gammaproteobacteria, Betaproteobacteria and Flavobacteriia and the upregulation of plant beneficial functions related to phosphorus and nitrogen mineralisation. Together, our metaproteomic assessment of the ‘active’ plant microbiome at the field-scale demonstrates the importance of moving past a genomic assessment of the plant microbiome in order to determine ecologically important plant-microbe interactions underpinning plant health.
Project description:Advances in DNA sequencing technologies has drastically changed our perception of the structure and complexity of the plant microbiome. By comparison, our ability to accurately identify the metabolically active fraction of soil microbiota and its specific functional role in augmenting plant health is relatively limited. Here, we combined our recently developed protein extraction method and an iterative bioinformatics pipeline to enable the capture and identification of extracellular proteins (metaexoproteomics) synthesised in the rhizosphere of Brassica spp. We first validated our method in the laboratory by successfully identifying proteins related to a host plant (Brassica rapa) and its bacterial inoculant, Pseudomonas putida BIRD-1. This identified numerous rhizosphere specific proteins linked to the acquisition of plant-derived nutrients in P. putida. Next, we analysed natural field-soil microbial communities associated with Brassica napus L. (oilseed rape). By combining metagenomics with metaexoproteomics, 1882 proteins were identified across bulk and rhizosphere samples. Meta-exoproteomics identified a clear shift (p<0.001) in the metabolically active fraction of the soil microbiota responding to the presence of B. napus roots that was not apparent in the composition of the total microbial community (metagenome). This metabolic shift was associated with the stimulation of rhizosphere-specialised bacteria, such as Gammaproteobacteria, Betaproteobacteria and Flavobacteriia and the upregulation of plant beneficial functions related to phosphorus and nitrogen mineralisation. Together, our metaproteomic assessment of the ‘active’ plant microbiome at the field-scale demonstrates the importance of moving past a genomic assessment of the plant microbiome in order to determine ecologically important plant-microbe interactions underpinning plant health.
Project description:The transcriptome of Leptosphaeria maculans was analyzed in mycelium and during oilseed rape (Brassica napus) leaf infection. The array probes were designed from gene models from the L. maculans whole genome annotation. One aim of this study was to verify the expression of the automatically annotated gene models in various conditions. Another goal was to monitor gene expression profiles during oilseed rape leaf infection and to highlight tissue-specific transcripts, e.g. in plant up-regulated transcripts, for further analyses.