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:Here, we report 17 metagenome-assembled genomes (MAGs) recovered from microbial consortia of forest and pasture soils in the Brazilian Eastern Amazon. The bacterial MAGs have the potential to act in important ecological processes, including carbohydrate degradation and sulfur and nitrogen cycling.
Project description:The metagenomes of complex microbial communities are rich sources of novel biocatalysts. We exploited the metagenome of a mixed microbial population for isolation of more than 15 different genes encoding novel biocatalysts by using a combined cultivation and direct cloning strategy. A 16S rRNA sequence analysis revealed the presence of hitherto uncultured microbes closely related to the genera Pseudomonas, Agrobacterium, Xanthomonas, Microbulbifer, and Janthinobacterium. Total genomic DNA from this bacterial community was used to construct cosmid DNA libraries, which were functionally searched for novel enzymes of biotechnological value. Our searches in combination with cosmid sequencing resulted in identification of four clones encoding 12 putative agarase genes, most of which were organized in clusters consisting of two or three genes. Interestingly, nine of these agarase genes probably originated from gene duplications. Furthermore, we identified by DNA sequencing several other biocatalyst-encoding genes, including genes encoding a putative stereoselective amidase (amiA), two cellulases (gnuB and uvs080), an alpha-amylase (amyA), a 1,4-alpha-glucan branching enzyme (amyB), and two pectate lyases (pelA and uvs119). Also, a conserved cluster of two lipase genes was identified, which was linked to genes encoding a type I secretion system. The novel gene aguB was overexpressed in Escherichia coli, and the enzyme activities were determined. Finally, we describe more than 162 kb of DNA sequence that provides a strong platform for further characterization of this microbial consortium.
Project description:Sensitive models of climate change impacts would require a better integration of multi-omics approaches that connect the abundance and activity of microbial populations. Here, we show that climate is a fundamental driver of the protein abundance of microbial populations (metaproteomics), yet not their genomic abundance (16S rRNA gene amplicon sequencing), supporting the hypothesis that metabolic activity may be more closely linked to climate than community composition.
Project description:Soil microbial communities contain the highest level of prokaryotic diversity of any environment, and metagenomic approaches involving the extraction of DNA from soil can improve our access to these communities. Most analyses of soil biodiversity and function assume that the DNA extracted represents the microbial community in the soil, but subsequent interpretations are limited by the DNA recovered from the soil. Unfortunately, extraction methods do not provide a uniform and unbiased subsample of metagenomic DNA, and as a consequence, accurate species distributions cannot be determined. Moreover, any bias will propagate errors in estimations of overall microbial diversity and may exclude some microbial classes from study and exploitation. To improve metagenomic approaches, investigate DNA extraction biases, and provide tools for assessing the relative abundances of different groups, we explored the biodiversity of the accessible community DNA by fractioning the metagenomic DNA as a function of (i) vertical soil sampling, (ii) density gradients (cell separation), (iii) cell lysis stringency, and (iv) DNA fragment size distribution. Each fraction had a unique genetic diversity, with different predominant and rare species (based on ribosomal intergenic spacer analysis [RISA] fingerprinting and phylochips). All fractions contributed to the number of bacterial groups uncovered in the metagenome, thus increasing the DNA pool for further applications. Indeed, we were able to access a more genetically diverse proportion of the metagenome (a gain of more than 80% compared to the best single extraction method), limit the predominance of a few genomes, and increase the species richness per sequencing effort. This work stresses the difference between extracted DNA pools and the currently inaccessible complete soil metagenome.