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.
Project description:Dietary intake of fruits and vegetables (FV) has been inversely associated with lower risk of ulcerative colitis. A pig model was used to evaluate the impact of feeding FV on the host response to dextran sulfate sodium (DSS)-induced colitis. Methods: Six-week-old pigs were fed a grower diet alone or supplemented with lyophilized FV equivalent to the half (half-FV) or full (full-FV) daily levels recommended for humans by the Dietary Guidelines for Americans (DGA). Pigs were fed a 1) grower diet alone (negative control), 2) grower diet and orally treated with 4% DSS for 10 days to induce colitis (positive control), 3) half-FV diet treated with 4% DSS or 4) full-FV diet treated with 4% DSS. Pigs were monitored for the development of clinical signs of colitis. Proximal colon (PC) contents and mucosa (PCM) were collected for gut metagenome, tissue transcriptome and histopathological analysis. Results: Pigs fed the full-FV diet did not exhibit diarrhea, showed less fecal occult blood (FOB), PCM crypt hyperplasia but with no differential expressed genes (DEG) or changes in PC microbiome diversity (p < 0.05). Pigs within the half-FV group exhibited increased group FOB and DEG associated with tissue remodeling, crypt and goblet cell hyperplasia in the PCM and no changes in PC microbiome diversity and two pigs exhibiting diarrhea (p < 0.05). Pigs within the DSS positive control group exhibited a reduced DEG involved with intestinal immune response and PC microbiome diversity with altered metagenome, increased group PCM erosion and FOB with persistent diarrhea in one pig (p < 0.05) Conclusions: Overall, our results showed that pigs fed a three-week full-FV supplemented diet, were resistant to DSS-induced colitis with a differential dose-dependent protective effect on host intestinal tissue and gut metagenome when exposed to an inflammatory challenge.
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:We report raw bulk RNA sequencing data rice roots (X.kitaake) protoplasted for 2.5 hours and 3 hours to eliminate the effects of protoplasting duration on our scRNA-seq analysis, as well as rice roots grown in gel, non-compacted soil and compacted soil conditions to verify our findsing with scRNA-seq studies
Project description:Purpose: Deconstructing the soil microbiome into reduced-complexity functional modules represents a novel method of microbiome analysis. The goals of this study are to confirm differences in transcriptomic patterns among five functional module consortia. Methods: mRNA profiles of 3 replicates each of functional module enrichments of soil inoculum in M9 media with either 1) xylose, 2) n-acetylglucosamine, 3) glucose and gentamycin, 4) xylan, or 5) pectin were generated by sequencing using an Illumina platform (GENEWIZ performed sequencing). Sequence reads that passed quality filters were aligned to a soil metagenome using Burrows Wheeler Aligner. Resulting SAM files were converted to raw reads using HTSeq, and annotated using Uniref90 or EGGNOG databases. Results: To reduce the size of the RNA-Seq counts table and increase its computational tractability, transcripts containing a minimum of 75 total counts, but no more than 3 zero counts, across the 15 samples were removed. The subsequent dataset was normalized using DESeq2, resulting in a dataset consisting of 6947 unique transcripts across the 15 samples, and 185,920,068 reads. We identified gene categories that were enriched in a sample type relative to the overall dataset using Fisher’s exact test. Conclusions: our dataset confirms that the functional module consortia generated from targeted enrichments of a starting soil inoculum had distinct functional trends by enrichment type.
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.
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.
Project description:Soil transplant serves as a proxy to simulate climate change in realistic climate regimes. Here, we assessed the effects of climate warming and cooling on soil microbial communities, which are key drivers in Earth’s biogeochemical cycles, four years after soil transplant over large transects from northern (N site) to central (NC site) and southern China (NS site) and vice versa. Four years after soil transplant, soil nitrogen components, microbial biomass, community phylogenetic and functional structures were altered. Microbial functional diversity, measured by a metagenomic tool named GeoChip, and phylogenetic diversity are increased with temperature, while microbial biomass were similar or decreased. Nevertheless, the effects of climate change was overridden by maize cropping, underscoring the need to disentangle them in research. Mantel tests and canonical correspondence analysis (CCA) demonstrated that vegetation, climatic factors (e.g., temperature and precipitation), soil nitrogen components and CO2 efflux were significantly correlated to the microbial community composition. Further investigation unveiled strong correlations between carbon cycling genes and CO2 efflux in bare soil but not cropped soil, and between nitrogen cycling genes and nitrification, which provides mechanistic understanding of these microbe-mediated processes and empowers an interesting possibility of incorporating bacterial gene abundance in greenhouse gas emission modeling.