Project description:Background: The soil environment is responsible for sustaining most terrestrial plant life on earth, yet we know surprisingly little about the important functions carried out by diverse microbial communities in soil. Soil microbes that inhabit the channels of decaying root systems, the detritusphere, are likely to be essential for plant growth and health, as these channels are the preferred locations of new root growth. Understanding the microbial metagenome of the detritusphere and how it responds to agricultural management such as crop rotations and soil tillage will be vital for improving global food production. Methods: The rhizosphere soils of wheat and chickpea growing under + and - decaying root were collected for metagenomics sequencing. A gene catalogue was established by de novo assembling metagenomic sequencing. Genes abundance was compared between bulk soil and rhizosphere soils under different treatments. Conclusions: The study describes the diversity and functional capacity of a high-quality soil microbial metagenome. The results demonstrate the contribution of the microbiome from decaying root in determining the metagenome of developing root systems, which is fundamental to plant growth, since roots preferentially inhabit previous root channels. Modifications in root microbial function through soil management, can ultimately govern plant health, productivity and food security.
Project description:On going efforts are directed at understanding the mutualism between the gut microbiota and the host in breast-fed versus formula-fed infants. Due to the lack of tissue biopsies, no investigators have performed a global transcriptional (gene expression) analysis of the developing human intestine in healthy infants. As a result, the crosstalk between the microbiome and the host transcriptome in the developing mucosal-commensal environment has not been determined. In this study, we examined the host intestinal mRNA gene expression and microbial DNA profiles in full term 3 month-old infants exclusively formula fed (FF) (n=6) or breast fed (BF) (n=6) from birth to 3 months. Host mRNA microarray measurements were performed using isolated intact sloughed epithelial cells in stool samples collected at 3 months. Microbial composition from the same stool samples was assessed by metagenomic pyrosequencing. Both the host mRNA expression and bacterial microbiome phylogenetic profiles provided strong feature sets that clearly classified the two groups of babies (FF and BF). To determine the relationship between host epithelial cell gene expression and the bacterial colony profiles, the host transcriptome and functionally profiled microbiome data were analyzed in a multivariate manner. From a functional perspective, analysis of the gut microbiota's metagenome revealed that characteristics associated with virulence differed between the FF and BF babies. Using canonical correlation analysis, evidence of multivariate structure relating eleven host immunity / mucosal defense-related genes and microbiome virulence characteristics was observed. These results, for the first time, provide insight into the integrated responses of the host and microbiome to dietary substrates in the early neonatal period. Our data suggest that systems biology and computational modeling approaches that integrate “-omic” information from the host and the microbiome can identify important mechanistic pathways of intestinal development affecting the gut microbiome in the first few months of life. KEYWORDS: infant, breast-feeding, infant formula, exfoliated cells, transcriptome, metagenome, multivariate analysis, canonical correlation analysis 12 samples, 2 groups
Project description:Earthworms enhance plant growth but the precise mechanism by which this occurs is not known. An understanding of the mechanism could potentially support changes in agricultural management reducing fertiliser usage and therefore costs and the carbon footprint of agriculture. We conducted a factorial experiment in which 5 strains of wheat were grown in the presence and absence of earthworms under regular watering and droughted conditions. The different wheat strains all responded in a similar fashion. Plant biomass was greater in the presence of earthworms and under regular watering. The presence of earthworms reduced the impact of drought on plant biomass and also slowed down the rate of drying of the droughted soils. Plant nutrient content (N, P, Si) showed no consistent pattern with treatments but total N, P and Si mirrored plant biomass and decreased in the order earthworm-present watered > earthworm-present droughted > earthworm-absent watered > earthworm-absent droughted. Nutrient availability in the soil, as assessed by chemical extractions showed no consistent pattern with treatments. Differential gene expression of plants was greater between watering treatments than between earthworm treatments. Genes that were differentially expressed between the earthworm treatments predominantly related to plant defences, abiotic stress and control of plant growth though a couple were linked to both nitrogen cycling and stress responses. The soil microbiome of the earthworm-present treatments was more associated with nutrient-rich environments, the promotion of plant growth and the suppression of plant pathogens. Our data suggest that enhanced plant growth was due to changes in the microbiome due to earthworm processing of the soil rather than changes in nutrient availability due to the presence of earthworms.
Project description:The experiment was designed to test the interactions of Spartina alterniflora, its microbiome, and the interaction of the plant-microbe relationship with oil from the Deepwater Horizon oil spill (DWH). Total RNA was extracted from leaf and root microbiome of S. alterniflora in soils that were oiled in DWH oil spill with or without added oil, as well as those grown in unoiled soil with or without added oil. The work in its entirety characterizes the transport, fate and catabolic activities of bacterial communities in petroleum-polluted soils and within plant tissues.
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:On going efforts are directed at understanding the mutualism between the gut microbiota and the host in breast-fed versus formula-fed infants. Due to the lack of tissue biopsies, no investigators have performed a global transcriptional (gene expression) analysis of the developing human intestine in healthy infants. As a result, the crosstalk between the microbiome and the host transcriptome in the developing mucosal-commensal environment has not been determined. In this study, we examined the host intestinal mRNA gene expression and microbial DNA profiles in full term 3 month-old infants exclusively formula fed (FF) (n=6) or breast fed (BF) (n=6) from birth to 3 months. Host mRNA microarray measurements were performed using isolated intact sloughed epithelial cells in stool samples collected at 3 months. Microbial composition from the same stool samples was assessed by metagenomic pyrosequencing. Both the host mRNA expression and bacterial microbiome phylogenetic profiles provided strong feature sets that clearly classified the two groups of babies (FF and BF). To determine the relationship between host epithelial cell gene expression and the bacterial colony profiles, the host transcriptome and functionally profiled microbiome data were analyzed in a multivariate manner. From a functional perspective, analysis of the gut microbiota's metagenome revealed that characteristics associated with virulence differed between the FF and BF babies. Using canonical correlation analysis, evidence of multivariate structure relating eleven host immunity / mucosal defense-related genes and microbiome virulence characteristics was observed. These results, for the first time, provide insight into the integrated responses of the host and microbiome to dietary substrates in the early neonatal period. Our data suggest that systems biology and computational modeling approaches that integrate “-omic” information from the host and the microbiome can identify important mechanistic pathways of intestinal development affecting the gut microbiome in the first few months of life. KEYWORDS: infant, breast-feeding, infant formula, exfoliated cells, transcriptome, metagenome, multivariate analysis, canonical correlation analysis
Project description:Metagenome data from soil samples were collected at 0 to 10cm deep from 2 avocado orchards in Channybearup, Western Australia, in 2024. Amplicon sequence variant (ASV) tables were constructed based on the DADA2 pipeline with default parameters.