Project description:To understand the mechanism of breast cancer invasion and metastasis, we collected tumor tissue from a cohort of 120 breast cancer patients and performed a Nanostring gene profiling assay (26 cases were removed from further analysis during quality control). Differential gene expression (DGE) analysis was done by comparing patients with/without lymph node metastasis lymph nodes. To explore the role of RHAMM in breast cancer invasion and metastasis, we created an RHAMM Related Signature (RRS) by intersecting the top 50 genes with another DGE list generated from a murine model wherein overexpression of an oncogenic RHAMM isoform increased cell motility in vivo tumor engraftment, and metastasis to identify RHAMM-related transcriptome changes specifically.
Project description:We compared gene expression profiles between anciently and recently established populations of two major invading species, the black rat Rattus rattus and the house mouse Mus musculus musculus, in Senegal. Transcriptome analyses revealed respectively 364 and 83 differentially expressed genes along the mouse and rat invasion routes. Among them, 10 and 15% were annotated with functions related to immunity. All immune-related genes detected along the mouse invasion route were over-expressed at the invasion front. Genes of the complement activation pathway were over-represented. Results were less straightforward when considering the black rat. No particular immune pathway was over-represented. In conclusion, we revealed changes in transcriptomic profiles along invasion routes. Patterns differed between invaders. They could potentially be driven by increased infection risks at invasion front for the house mouse and trade-offs between immune responses for the black rat. Our results provide a first step in identifying the immune ecoevolutionary processes potentially involved in invasion success.
Project description:Gene expression patterns of the plant colonizing bacterium,Pseudomonas putida KT2440 were evaluated as a function of growth in the Arabidopsis thaliana rhizosphere. Gene expression in rhizosphere grown P. putida cells was compared to gene expression in non-rhizosphere grown cells. Keywords: Gene expression
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.
Project description:Increased root H+ secretion is known as a strategy of plant adaption to low phosphorus (P) stress by enhancing mobilization of sparingly soluble P-sources. However, it remains fragmentarywhether enhanced H+ exudation could reconstruct the plant rhizosphere microbial community under low P stress. The present study found that P deficiency led to enhanced H+ exudation from soybean (Glycine max) roots. Three out of all eleven soybean H+-pyrophosphatases (GmVP) geneswere up-regulated by Pi starvation in soybean roots. Among them, GmVP2 showed the highest expression level under low P conditions. Transient expression of a GmVP2-green fluorescent protein chimera in tobacco (Nicotiana tabacum) leaves, and functional characterization of GmVP2 in transgenic soybean hairy roots demonstrated that GmVP2 encoded a plasma membrane transporter that mediated H+ exudation. Meanwhile, GmVP2-overexpression in Arabidopsis thaliana resulted in enhanced root H+ exudation, promoted plant growth, and improved sparingly soluble Ca-P utilization. Overexpression of GmVP2 also changed the rhizospheric microbial community structures, as reflected by a preferential accumulation of acidobacteria in the rhizosphere soils. These results suggested that GmVP2 mediated Pi-starvation responsive H+ exudation,which is not only involved in plant growth and mobilization of sparingly soluble P-sources, but also affects microbial community structures in soils.
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. Triplicate samples were taken for both rhizosphere and bulk soil, in which each individual sample was a pool of four plants or soil cores. To determine the abundance of functional genes in the rhizosphere and bulk soils, GeoChip 3.0 was used.