Project description:Quantitative taxonomic compositions of nematode communities help to assess soil environments due to their rich abundance and various feeding habitats. DNA metabarcoding by the 18S ribosomal RNA gene (SSU) regions were preferentially used for analyses of soil nematode communities, but the optimal regions for high-throughput amplicon sequencing have not previously been well investigated. In this work, we performed Illumina-based amplicon sequencing of four SSU regions (regions 1-4) to identify suitable regions for nematode metabarcoding using the taxonomic structures of nematodes from uncultivated field, copse, and cultivated house garden soils. The fewest nematode-derived sequence variants (SVs) were detected in region 3, and the total nematode-derived SVs were comparable in regions 1 and 4. The relative abundances of reads in regions 1 and 4 were consistent in both orders and feeding groups with prior studies, thus suggesting that region 4 is a suitable target for the DNA barcoding of nematode communities. Distinct community structures of nematodes were detected in the taxon, feeding habitat, and life-history strategy of each sample; i.e., Dorylamida- and Rhabditida-derived plant feeders were most abundant in the copse soil, Rhabditida-derived bacteria feeders in the house garden soil, and Mononchida- and Dorylamida-derived omnivores and predators and Rhabditida-derived bacteria feeders in the field soil. Additionally, low- and high-colonizer-persister (cp) groups of nematodes dominated in the house garden and copse soils, respectively, whereas both groups were found in the field soil, suggesting bacteria-rich garden soil, undisturbed and plant-rich copse soil, and a transient status of nematode communities in the field soil. These results were also supported by the maturity indices of the three sampling sites. Finally, the influence of the primer tail sequences was demonstrated to be insignificant on amplification. These findings will be useful for DNA metabarcoding of soil nematode communities by amplicon sequencing.
Project description:Soils are a sink for sulfidised-silver nanoparticles (Ag2S-NPs), yet there are limited ecotoxicity data for their effects on microbial communities. Conventional toxicity tests typically target a single test species or function, which does not reflect the broader community response. Using a combination of quantitative PCR, 16S rRNA amplicon sequencing and species sensitivity distribution (SSD) methods, we have developed a new approach to calculate silver-based NP toxicity thresholds (HCx, hazardous concentrations) that are protective of specific members (operational taxonomic units, OTUs) of the soil microbial community. At the HC20 (80% of species protected), soil OTUs were significantly less sensitive to Ag2S-NPs compared to AgNPs and Ag+ (5.9, 1.4 and 1.4 mg Ag kg-1, respectively). However at more conservative HC values, there were no significant differences. These trends in OTU responses matched with those seen in a specific microbial function (rate of nitrification) and amoA-bacteria gene abundance. This study provides a novel molecular-based framework for quantifying the effect of a toxicant on whole soil microbial communities while still determining sensitive genera/species. Methods and results described here provide a benchmark for microbial community ecotoxicological studies and we recommend that future revisions of Soil Quality Guidelines for AgNPs and other such toxicants consider this approach.
Project description:High-throughput amplicon sequencing technology has been widely used in soil microbiome studies. Here, we estimated the bias of amplicon sequencing data affected by DNA extraction methods in a saline soil, and a non-saline normal soil was used as a control. Compared with the normal soil, several unique points were observed in the saline soil. The soil washing pretreatment can improve not only DNA quantity and quality but also microbial diversities in the saline soil; therefore, we recommend the soil washing pretreatment for saline soils especially hypersaline soils that cannot be achieved with detectable DNA amounts without the pretreatment. Also, evenness indices were more easily affected by DNA extraction methods than richness indices in the saline soil. Moreover, proportions of Gram-positive bacteria had significant positive correlations with the achieved microbial diversities within replicates of the saline soil. Though DNA extraction methods can bias the microbial diversity or community and relative abundances of some phyla/classes can vary by a factor of more than five, soil types were still the most important factor of the whole community. We confirmed good comparability in the whole community, but more attention should be paid when concentrating on an exact diversity value or the exact relative abundance of a certain taxon. Our study can provide references for the DNA extraction from saline and non-saline soils and comparing sequencing data across studies who may employ different DNA extraction methods.
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:Common bottlenecks in environmental and crop microbiome studies are the consumable and personnel costs necessary for genomic DNA extraction and sequencing library construction. This is harder for challenging environmental samples such as soil, which is rich in Polymerase Chain Reaction (PCR) inhibitors. To address this, we have established a low-cost genomic DNA extraction method for soil samples. We also present an Illumina-compatible 16S and ITS rRNA gene amplicon library preparation workflow that uses common laboratory equipment. We evaluated the performance of our genomic DNA extraction method against two leading commercial soil genomic DNA kits (MoBio PowerSoil® and MP Biomedicals™ FastDNA™ SPIN) and a recently published non-commercial extraction method by Zou et al. (PLoS Biology, 15, e2003916, 2017). Our benchmarking experiment used four different soil types (coniferous, broad-leafed, and mixed forest plus a standardized cereal crop compost mix) assessing the quality and quantity of the extracted genomic DNA by analyzing sequence variants of 16S V4 and ITS rRNA amplicons. We found that our genomic DNA extraction method compares well to both commercially available genomic DNA extraction kits in DNA quality and quantity. The MoBio PowerSoil® kit, which relies on silica column-based DNA extraction with extensive washing, delivered the cleanest genomic DNA, for example, best A260:A280 and A260:A230 absorbance ratios. The MP Biomedicals™ FastDNA™ SPIN kit, which uses a large amount of binding material, yielded the most genomic DNA. Our method fits between the two commercial kits, producing both good yields and clean genomic DNA with fragment sizes of approximately 10 kb. Comparative analysis of detected amplicon sequence variants shows that our method correlates well with the two commercial kits. Here, we present a low-cost genomic DNA extraction method for soil samples that can be coupled to an Illumina-compatible simple two-step amplicon library construction workflow for 16S V4 and ITS marker genes. Our method delivers high-quality genomic DNA at a fraction of the cost of commercial kits and enables cost-effective, large-scale amplicon sequencing projects. Notably, our extracted gDNA molecules are long enough to be suitable for downstream techniques such as full gene sequencing or even metagenomics shotgun approaches using long reads (PacBio or Nanopore), 10x Genomics linked reads, and Dovetail genomics.
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: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:Recent advances in DNA sequencing technologies have allowed scientists to probe increasingly complex biological systems, including the diversity of bacteria in the environment. However, despite a multitude of recent studies incorporating these methods, many questions regarding how environmental samples should be collected and stored still persist. Here, we assess the impact of different soil storage conditions on microbial community composition using Illumina-based 16S rRNA V4 amplicon sequencing. Both storage time and temperature affected bacterial community composition and structure. Frozen samples maintained the highest alpha diversity and differed least in beta diversity, suggesting the utility of cold storage for maintaining consistent communities. Samples stored for intermediate times (three and seven days) had both the highest alpha diversity and the largest differences in overall beta diversity, showing the degree of community change after sample collection. These divergences notwithstanding, differences in neither storage time nor storage temperature substantially altered overall communities relative to more than 500 previously examined soil samples. These results systematically support previous studies and stress the importance of methodological consistency for accurate characterization and comparison of soil microbiological assemblages.
Project description:<h4>Background</h4>Advances in DNA sequencing technologies have transformed our capacity to perform life science research, decipher the dynamics of complex soil microbial communities and exploit them for plant disease management. However, soil is a complex conglomerate, which makes functional metagenomics studies very challenging.<h4>Results</h4>Metagenomes were assembled by long-read (PacBio, PB), short-read (Illumina, IL), and mixture of PB and IL (PI) sequencing of soil DNA samples were compared. Ortholog analyses and functional annotation revealed that the PI approach significantly increased the contig length of the metagenomic sequences compared to IL and enlarged the gene pool compared to PB. The PI approach also offered comparable or higher species abundance than either PB or IL alone, and showed significant advantages for studying natural product biosynthetic genes in the soil microbiomes.<h4>Conclusion</h4>Our results provide an effective strategy for combining long and short-read DNA sequencing data to explore and distill the maximum information out of soil metagenomics.
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.