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.
Project description:The microbiome associated with an animal's gut and other organs is considered an integral part of its ecological functions and adaptive capacity. To better understand how microbial communities influence activities and capacities of the host, we need more information on the functions that are encoded in a microbiome. Until now, the information about soil invertebrate microbiomes is mostly based on taxonomic characterization, achieved through culturing and amplicon sequencing. Using shotgun sequencing and various bioinformatics approaches we explored functions in the bacterial metagenome associated with the soil invertebrate Folsomia candida, an established model organism in soil ecology with a fully sequenced, high-quality genome assembly. Our metagenome analysis revealed a remarkable diversity of genes associated with antimicrobial activity and carbohydrate metabolism. The microbiome also contains several homologs to F. candida genes that were previously identified as candidates for horizontal gene transfer (HGT). We suggest that the carbohydrate- and antimicrobial-related functions encoded by Folsomia's metagenome play a role in the digestion of recalcitrant soil-born polysaccharides and the defense against pathogens, thereby significantly contributing to the adaptation of these animals to life in the soil. Furthermore, the transfer of genes from the microbiome may constitute an important source of new functions for the springtail.
Project description:We use a unique set of terrestrial experiments to demonstrate how soil management practises result in emergence of distinct associations between physical structure and biological functions. These associations have a significant effect on the flux, resilience and efficiency of nutrient delivery to plants (including water). Physical structure, determining the air-water balance in soil as well as transport rates, is influenced by nutrient and physical interventions. Contrasting emergent soil structures exert selective pressures upon the microbiome metagenome. These selective pressures are associated with the quality of organic carbon inputs, the prevalence of anaerobic microsites and delivery of nutrients to microorganisms attached to soil surfaces. This variety results in distinctive gene assemblages characterising each state. The nature of the interactions provide evidence that soil behaves as an extended composite phenotype of the resident microbiome, responsive to the input and turnover of plant-derived organic carbon. We provide new evidence supporting the theory that soil-microbe systems are self-organising states with organic carbon acting as a critical determining parameter. This perspective leads us to propose carbon flux, rather than soil organic carbon content as the critical factor in soil systems, and we present evidence to support this view.
Project description:The Arecibo Observatory (AO) located in Arecibo, Puerto Rico, is the most sensitive, powerful and active planetary radar system in the world . One of its principal components is the 305 m-diameter spherical reflector dish (AORD), which is exposed to high frequency electromagnetic waves. To unravel the microbial communities that inhabit this environment, soil samples from underneath the AORD were collected, DNA extracted, and sequenced using Illumina MiSeq. Taxonomic and functional profiles were generated using the MG-RAST server. The most abundant domain was Bacteria (91%), followed by Virus (8%), Archaea (0.9%) and Eukaryota (0.9%). The most abundant phylum was Proteobacteria (54%), followed by Actinobacteria (8%), Bacteroidetes (5%) and Firmicutes (4%). In terms of functions, the most abundant among the metagenome corresponded to phages, transposable elements and plasmids (16%), followed by clustering-based subsystems (11%), carbohydrates (10%), and amino acids and derivatives (9%). This is the first soil metagenomic dataset from dish antennas and radar systems, specifically, underneath the AORD. Data can be used to explore the effect of high frequency electromagnetic waves in soil microbial composition, as well as the possibility of finding bioprospects with potential biomedical and biotechnological applications.
Project description:The soil ecosystem is critical for human health, affecting aspects of the environment from key agricultural and edaphic parameters to critical influence on climate change. Soil has more unknown biodiversity than any other ecosystem. We have applied diverse DNA extraction methods coupled with high throughput pyrosequencing to explore 4.88 × 10(9)?bp of metagenomic sequence data from the longest continually studied soil environment (Park Grass experiment at Rothamsted Research in the UK). Results emphasize important DNA extraction biases and unexpectedly low seasonal and vertical soil metagenomic functional class variations. Clustering-based subsystems and carbohydrate metabolism had the largest quantity of annotated reads assigned although <50% of reads were assigned at an E value cutoff of 10(-5). In addition, with the more detailed subsystems, cAMP signaling in bacteria (3.24±0.27% of the annotated reads) and the Ton and Tol transport systems (1.69±0.11%) were relatively highly represented. The most highly represented genome from the database was that for a Bradyrhizobium species. The metagenomic variance created by integrating natural and methodological fluctuations represents a global picture of the Rothamsted soil metagenome that can be used for specific questions and future inter-environmental metagenomic comparisons. However, only 1% of annotated sequences correspond to already sequenced genomes at 96% similarity and E values of <10(-5), thus, considerable genomic reconstructions efforts still have to be performed.
Project description:Mineral phosphate solubilization (MPS) microorganisms are important for their provision of orthophosphate anions for plant growth promotion activity in soil. In this study, we applied a functional metagenomic approach to identify this trait directly from the microbiome in barley rhizosphere soil that had not received P fertilizer over a 15-year period. A fosmid system was used to clone the metagenome of which 18,000 clones (~666 Mb of DNA) was screened for MPS. Functional assays and High Performance Liquid Chromatography analysis recognized gluconic acid production and MPS activity in the range 24.8-77.1 mmol/L and 27.6-38.16 μg/mL, respectively, when screened in an Escherichia coli host (at frequency of one MPS-positive clone hit per 114 Mb DNA tested). The MPS clones (with average insert size of ~37 kb) were analysed by 454 Roche sequencing and annotated. A number of genes/operons with homology to Phosphorous (P) uptake, regulatory and solubilization mechanisms were identified, linking the MPS function to the uncultivated microbiome present in barley rhizosphere soil.
Project description:Deforestation in the Brazilian Amazon occurs at an alarming rate, which has broad effects on global greenhouse gas emissions, carbon storage, and biogeochemical cycles. In this study, soil metagenomes and metagenome-assembled genomes (MAGs) were analyzed for alterations to microbial community composition, functional groups, and putative physiology as it related to land-use change and tropical soil. A total of 28 MAGs were assembled encompassing 10 phyla, including both dominant and rare biosphere lineages. Amazon Acidobacteria subdivision 3, Melainabacteria, Microgenomates, and Parcubacteria were found exclusively in pasture soil samples, while Candidatus Rokubacteria was predominant in the adjacent rainforest soil. These shifts in relative abundance between land-use types were supported by the different putative physiologies and life strategies employed by the taxa. This research provides unique biological insights into candidate phyla in tropical soil and how deforestation may impact the carbon cycle and affect climate change.
Project description:Areas within an agricultural field in the same season often differ in crop productivity despite having the same cropping history, crop genotype, and management practices. One hypothesis is that abiotic or biotic factors in the soils differ between areas resulting in these productivity differences. In this study, bulk soil samples collected from a high and a low productivity area from within six agronomic fields in Illinois were quantified for abiotic and biotic characteristics. Extracted DNA from these bulk soil samples were shotgun sequenced. While logistic regression analyses resulted in no significant association between crop productivity and the 26 soil characteristics, principal coordinate analysis and constrained correspondence analysis showed crop productivity explained a major proportion of the taxa variance in the bulk soil microbiome. Metagenome-wide association studies (MWAS) identified more Bradyrhizodium and Gammaproteobacteria in higher productivity areas and more Actinobacteria, Ascomycota, Planctomycetales, and Streptophyta in lower productivity areas. Machine learning using a random forest method successfully predicted productivity based on the microbiome composition with the best accuracy of 0.79 at the order level. Our study showed that crop productivity differences were associated with bulk soil microbiome composition and highlighted several nitrogen utility-related taxa. We demonstrated the merit of MWAS and machine learning for the first time in a plant-microbiome study.
Project description:This paper describes the discovery of novel ?-L-fucosidases and evaluation of their potential to catalyse the transglycosylation reaction leading to production of fucosylated human milk oligosaccharides. Seven novel ?-L-fucosidase-encoding genes were identified by functional screening of a soil-derived metagenome library and expressed in E. coli as recombinant 6xHis-tagged proteins. All seven fucosidases belong to glycosyl hydrolase family 29 (GH 29). Six of the seven ?-L-fucosidases were substrate-inhibited, moderately thermostable and most hydrolytically active in the pH range 6-7, when tested with para-nitrophenyl-?-L-fucopyranoside (pNP-Fuc) as the substrate. In contrast, one fucosidase (Mfuc6) exhibited a high pH optimum and an unusual sigmoidal kinetics towards pNP-Fuc substrate. When tested for trans-fucosylation activity using pNP-Fuc as donor, most of the enzymes were able to transfer fucose to pNP-Fuc (self-condensation) or to lactose. With the ?-L-fucosidase from Thermotoga maritima and the metagenome-derived Mfuc5, different fucosyllactose variants including the principal fucosylated HMO 2'-fucosyllactose were synthesised in yields of up to ~6.4%. Mfuc5 was able to release fucose from xyloglucan and could also use it as a fucosyl-donor for synthesis of fucosyllactose. This is the first study describing the use of glycosyl hydrolases for the synthesis of genuine fucosylated human milk oligosaccharides.
Project description:Using two forest soils, we previously constructed two fosmid libraries containing 113,700 members in total. The libraries were screened to select active antifungal clones using Saccharomyces cerevisiae as a target fungus. One clone from the Yuseong pine tree rhizosphere soil library, pEAF66, showed S. cerevisiae growth inhibition. Despite an intensive effort, active chemicals were not isolated. DNA sequence analysis and transposon mutagenesis of pEAF66 revealed 39 open reading frames (ORFs) and indicated that eight ORFs, probably in one transcriptional unit, might be directly involved in the expression of antifungal activity in Escherichia coli. The deduced amino acid sequences of eight ORFs were similar to those of the core genes encoding type II family polyketide synthases, such as the acyl carrier protein (ACP), ACP synthases, aminotransferase, and ACP reductase. The gene cluster involved in antifungal activity was similar in organization to the putative antibiotic production locus of Pseudomonas putida KT2440, although we could not select a similar active clone from the KT2440 genomic DNA library in E. coli. ORFs encoding ATP binding cassette transporters and membrane proteins were located at both ends of the antifungal gene cluster. Upstream ORFs encoding an IclR family response regulator and a LysR family response regulator were involved in the positive regulation of antifungal gene expression. Our results suggested the metagenomic approach as an alternative to search for novel antifungal antibiotics from unculturable soil bacteria. This is the first report of an antifungal gene cluster obtained from a soil metagenome using S. cerevisiae as a target fungus.