Project description:We used wheat as rotational crop to assess the influence of continuous cropping on microbiome in Pinellia ternata rhizosphere and the remediation of rotational cropping to the impacted microbiota. Illumina high-throughput sequencing technology was utilized for this method to explore the rhizosphere microbial structure and diversity based on continuous and rotational cropping.
Project description:In this study, we used transcriptomic and hormonomic approaches to examine drought-induced changes in barley roots and leaves and its rhizosphere. By studying hormonal responses, alternative splicing events in barley, and changes in the rhizosphere microbiome, we aimed to provide a comprehensive view of barley drought-adaptive mechanisms and potential plant-microbe interactions under drought stress. This approach improved our understanding of barley adaptive strategies and highlighted the importance of considering plant-microbe interactions in the context of climate change.
Project description:Arsenic (As) bioavailability in the rice rhizosphere is influenced by many microbial interactions, particularly by metal-transforming functional groups at the root-soil interface. This study was conducted to examine As-transforming microbes and As-speciation in the rice rhizosphere compartments, in response to two different water management practices (continuous and intermittently flooded), established on fields with high to low soil-As concentration. Microbial functional gene composition in the rhizosphere and root-plaque compartments were characterized using the GeoChip 4.0 microarray. Arsenic speciation and concentrations were analyzed in the rhizosphere soil, root-plaque, porewater and grain samples. Results indicated that intermittent flooding significantly altered As-speciation in the rhizosphere, and reduced methyl-As and AsIII concentrations in the pore water, root-plaque and rice grain. Ordination and taxonomic analysis of detected gene-probes indicated that root-plaque and rhizosphere assembled significantly different metal-transforming functional groups. Taxonomic non-redundancy was evident, suggesting that As-reduction, -oxidation and -methylation processes were performed by different microbial groups. As-transformation was coupled to different biogeochemical cycling processes establishing functional non-redundancy of rice-rhizosphere microbiome in response to both rhizosphere compartmentalization and experimental treatments. This study confirmed diverse As-biotransformation at root-soil interface and provided novel insights on their responses to water management, which can be applied for mitigating As-bioavailability and accumulation in rice grains.
2021-07-12 | GSE179671 | GEO
Project description:Ginkgo root and rhizosphere fungi
| PRJNA889982 | ENA
Project description:Ginkgo root and rhizosphere bacteria
Project description:Root exudates contain specialised metabolites that affect the plant’s root microbiome. How host-specific microbes cope with these bioactive compounds, and how this ability shapes root microbiomes, remains largely unknown. We investigated how maize root bacteria metabolise benzoxazinoids, the main specialised metabolites of maize. Diverse and abundant bacteria metabolised the major compound in the maize rhizosphere MBOA and formed AMPO. AMPO forming bacteria are enriched in the rhizosphere of benzoxazinoid-producing maize and can use MBOA as carbon source. We identified a novel gene cluster associated with AMPO formation in microbacteria. The first gene in this cluster, bxdA encodes a lactonase that converts MBOA to AMPO in vitro. A deletion mutant of the homologous bxdA genes in the genus Sphingobium, does not form AMPO nor is it able to use MBOA as a carbon source. BxdA was identified in different genera of maize root bacteria. Here we show that plant-specialised metabolites select for metabolisation-competent root bacteria. BxdA represents a novel benzoxazinoid metabolisation gene whose carriers successfully colonize the maize rhizosphere and thereby shape the plant’s chemical environmental footprint
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:Microbial communities in the rhizosphere make significant contributions to crop health and nutrient cycling. However, their ability to perform important biogeochemical processes remains uncharacterized. Important functional genes, which characterize the rhizosphere microbial community, were identified to understand metabolic capabilities in the maize rhizosphere using GeoChip 3.0-based functional gene array method.