Microbial Diversity of Temperate Pine and Native Forest Soils Profiled by 16S rRNA Gene Amplicon Sequencing.
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ABSTRACT:
SUBMITTER: Amoo AE
PROVIDER: S-EPMC8188351 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Data on the 16S rRNA gene amplicon sequences from Pteris vittata rhizosphere soils are reported. The following phyla were recorded in arsenic-rich soils: Actinobacteria (59%), Proteobacteria (26%), Chloroflexi (17%), and Acidobacteria (9%). Actinobacteria (45%), Proteobacteria (22%), Chloroflexi (10%), and Acidobacteria (11%) were in natural-mineral soils.
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Project description:Microbial amplicon sequencing studies are an important tool in biological and biomedical research. Widespread 16S rRNA gene microbial surveys have shed light on the structure of many ecosystems inhabited by bacteria, including the human body. However, specialized software and algorithms are needed to convert raw sequencing data into biologically meaningful information (i.e. tables of bacterial counts). While different bioinformatic pipelines are available in a rapidly changing and improving field, users are often unaware of limitations and biases associated with individual pipelines and there is a lack of agreement regarding best practices. Here, we compared six bioinformatic pipelines for the analysis of amplicon sequence data: three OTU-level flows (QIIME-uclust, MOTHUR, and USEARCH-UPARSE) and three ASV-level (DADA2, Qiime2-Deblur, and USEARCH-UNOISE3). We tested workflows with different quality control options, clustering algorithms, and cutoff parameters on a mock community as well as on a large (N = 2170) recently published fecal sample dataset from the multi-ethnic HELIUS study. We assessed the sensitivity, specificity, and degree of consensus of the different outputs. DADA2 offered the best sensitivity, at the expense of decreased specificity compared to USEARCH-UNOISE3 and Qiime2-Deblur. USEARCH-UNOISE3 showed the best balance between resolution and specificity. OTU-level USEARCH-UPARSE and MOTHUR performed well, but with lower specificity than ASV-level pipelines. QIIME-uclust produced large number of spurious OTUs as well as inflated alpha-diversity measures and should be avoided in future studies. This study provides guidance for researchers using amplicon sequencing to gain biological insights.
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Project description:Soil microbes are major drivers of soil carbon cycling, yet we lack an understanding of how climate warming will affect microbial communities. Three ongoing field studies at the Harvard Forest Long-term Ecological Research (LTER) site (Petersham, MA) have warmed soils 5°C above ambient temperatures for 5, 8, and 20 years. We used this chronosequence to test the hypothesis that soil microbial communities have changed in response to chronic warming. Bacterial community composition was studied using Illumina sequencing of the 16S ribosomal RNA gene, and bacterial and fungal abundance were assessed using quantitative PCR. Only the 20-year warmed site exhibited significant change in bacterial community structure in the organic soil horizon, with no significant changes in the mineral soil. The dominant taxa, abundant at 0.1% or greater, represented 0.3% of the richness but nearly 50% of the observations (sequences). Individual members of the Actinobacteria, Alphaproteobacteria and Acidobacteria showed strong warming responses, with one Actinomycete decreasing from 4.5 to 1% relative abundance with warming. Ribosomal RNA copy number can obfuscate community profiles, but is also correlated with maximum growth rate or trophic strategy among bacteria. Ribosomal RNA copy number correction did not affect community profiles, but rRNA copy number was significantly decreased in warming plots compared to controls. Increased bacterial evenness, shifting beta diversity, decreased fungal abundance and increased abundance of bacteria with low rRNA operon copy number, including Alphaproteobacteria and Acidobacteria, together suggest that more or alternative niche space is being created over the course of long-term warming.
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Project description:The volcanic soils of Chiloé Island, Chile, have physical and chemical characteristics that affect their productivity. We report here a 16S rRNA gene analysis that characterizes the predominant microbial communities in volcanic soils of Chiloé either in the presence or absence of fertilization. The major phyla identified were Proteobacteria, Acidobacteria, and Actinobacteria.
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Project description:IntroductionBiological communities present in soil are essential to sustainable and productive agricultural practices; however, an accurate determination of the ecological status of agricultural soils remains to date an elusive task. An ideal indicator should be pervasive, play a relevant role in the ecosystem, show a rapid and proportional answer to external perturbations and be easily and economically measurable. Rhizobacteria play a major role in determining soil properties, becoming an attractive candidate for the detection of ecological indicators. The application of massive sequencing technologies to metagenomic analysis is providing an increasingly more precise view of the structure and composition of soil communities. In this work, we analyse soil rhizobacterial composition under various stress levels to search for potential ecological indicators.General biodiversity indicatorsOur results suggest that the Shannon index requires observation of a relatively large number of individuals to be representative of the true population diversity, and that the Simpson index may underestimate rare taxa in rhizobacterial environments.Taxonomical classification methodsDetection of indicator taxa requires comparison of taxonomical classification of sequences. We have compared RDP classifier, RTAX and similarity-based taxonomical classification and selected the latter for taxonomical assignment because it provides larger detail.Taxonomy-based ecological indicatorsThe study of significant variations in common, clearly identified, taxa, using paired datasets allows minimization of non-treatment effects and avoidance of false positives. We have identified taxa associated to specific perturbations as well as taxa generally affected in treated soils. Changes in these taxa, or combinations of them, may be used as ecological indicators of soil health. The overall number and magnitude of changes detected in taxonomic groups does also increase with stress. These changes constitute an alternative indicator to measuring specific taxa, although their determination requires large sample sizes, better obtained by massive sequencing.SummaryThe main ecological indicators available are the Shannon index, OTU counts and estimators, overall detection of the number and proportion of changes, and changes of specific indicator taxa. Massive sequencing remains the most accurate tool to measure rhizobacterial ecological indicators. When massive sequencing is not an option, various cultivable taxonomic groups, such as specific groups in the Actinobacteria tree, are attractive as potential indicators of large disruptions to the rhizobiome.
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Project description:The 16S rRNA amplicons from biofilms inhabiting rocks near various water bodies of Marsberg Copper Mine (Rhenish Massif, Germany) reveal the diversity of their microbial communities. The abundance of Chloroflexi and Cyanobacteria taxa in the biofilms near leachate streams indicated the selective enrichment of Ktedonobacteria and Oxyphotobacteria members.
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Project description:Two consortia (Consortium A and Consortium B) that can use 1,4-dioxane (a groundwater contaminant of emerging concern) as the sole carbon source were enriched from Rice University (Houston, TX, USA) campus soil. Phylogenetic analysis by 16S rRNA sequencing revealed the dominant genus in both of the consortia is Mycobacterium (56% in Consortium A and 49% in Consortium B). The predominance of Mycobacterium spp, in these consortia support the notion that this is an important and commonly encountered genus of dioxane degraders. Among other genera present that make at least 2% of these consortia, only Afipia encompasses a strain (i.e., Afipia sp. D1) that was reported to degrade dioxane as sole carbon and energy source. A nested PCR analysis using two degenerate primers to target the hydroxylase alpha subunit of groups 3 to 6 SDIMOs was performed to gain insights into which enzymes were responsible for dioxane degradation by these consortia. The purified products obtained from the second PCR run were sequenced and compared to genes databases (NCBI) encompassing all of the currently reported SDIMOs. The dominant SDIMO genes in Consortium A corresponded to a group-6 putative propane monooxygenase-like SDIMO (98.8%); while in Consortium B, SDIMO genes from both groups 5 (47.3%) and 6 (51.9%) were observed. In both consortia, the relative abundance of thmA/dxmA gene was negligible (0.03%), which is consistent with the negative amplification of these genes as verified in qPCR. Overall, the high relative abundance of group-6 putative propane monooxygenases in our two consortia suggests the novel finding that group 6-SDIMOs could also play an important role in dioxane degradation. This underscores the need for further research on genes and enzymes involved in dioxane biodegradation to develop novel biomarkers that can be useful for forensic analysis and performance assessment of bioremediation and natural attenuation at dioxane-impacted sites. DNA was extracted from bacteria biomass harvested in exponential growth phase, when half or more of the added dioxane (100 mg/L) was consumed. Total DNA extractions were performed using the UltraClean® Microbial DNA Isolation Kit (MO BIO, Carlsbad, CA, USA) according to the manufacturer’s protocol. The V4 region of the 16S rRNA gene was amplified by PCR using the forward 515F and reverse 806R primers. Sequencing was performed at MR DNA (www.mrdnalab.com, Shallowater, TX, USA) by Illumina MiSeq paired-end sequencing (approximately 2×300 bp as the read length). Sequence data were processed using MR DNA analysis pipeline. Operational taxonomic units (OTUs) were defined by clustering at 3% divergence (97% similarity). Final OTUs were taxonomically classified using BLASTn against the RDPII (http://rdp.cme.msu.edu) and NCBI (www.ncbi.nlm.nih.gov) databases.Previously designed degenerate primers NVC57, NVC58, NVC65 and NVC66 to target conserved regions in the soluble di-iron monooxygenases (SDIMO) alpha subunit gene (groups 3 to 6) were used to examine the presence and diversity of SDIMO genes in these two consortia. A nested PCR strategy was used to increase the PCR product yield. In the first run, the PCR mixture contained 1 µL of NVC65 and NVC58 primer mixture (10 µM), 20 ng of the extracted genomic DNA, 12.5 µL of KAPA HiFi HotStart ReadyMix (2X) (KAPA Biosystems, Wilmington, MA, USA), and nuclease-free water to yield a total volume of 25 µL. PCR was performed in a Bio-Rad Thermal Cycler (Bio-Rad, Hercules, CA, USA) with the following temperature profile: initial denaturation (94°C, 5 min), then 29 amplification cycles (94°C for 30 s, 55°C for 30 s, 72°C for 1 min per kb) and a final extension (72°C for 5 min). The length of the PCR products in the first run was checked by 1% agarose gel and DNA bands of the correct size (1100 bp) were excised and purified. 20 ng of the purified PCR product was used as the DNA template in the second run, with the second set of primers (NVC57 and NVC66). The purified product (420 bp) from the second PCR was sent to MR DNA (www.mrdnalab.com, Shallowater, TX, USA) for Illumina MiSeq paired-end sequencing (approximately 2×300 bp as the read length). Sequence data were processed using MR DNA analysis pipeline. Operational taxonomic units (OTUs) were defined by clustering at 3% divergence (97% similarity). A database including all of the currently reported SDIMO genes on NCBI was created and used to taxonomically classify the final OTUs.
2018-05-01 | GSE97756 | GEO
Project description:The global expansion of tree plantations is often claimed to have positive effects for mitigating global warming, preventing soil erosion, and reducing biodiversity loss. However, questions remain unanswered about the impacts of plantations on belowground diversity and soil properties. Here, we examine how forestry plantations of exotic trees affect critical soil functions and the composition of invertebrate assemblages, by comparing invertebrate diversity and soil physico-chemical properties between non-native Pinus radiata plantations, and nearby native forests in a region of extensive plantation activity in south-central Chile. We quantified differences in diversity, abundance, and community composition of soil invertebrates, as well as fundamental soil properties such as soil water content, water infiltration, nutrient status, and pH. We show that in this landscape mosaic of native forest and plantations, both soil invertebrate communities and physical soil properties differed significantly between systems, despite similar soil origins and topographies. We found a significant loss of soil carbon and a major reduction in taxonomic and functional diversity of soil invertebrates in pine plantation sites. Soil biotic and abiotic characteristics of plantations differed significantly from native forests in plantation-dominated south-central Chile, with profound consequences for ecosystem processes and resilience to future climate change.
| S-EPMC7210289 | biostudies-literature
Project description:Analysis of 16S ribosomal RNA (rRNA) gene amplification data for microbial barcoding can be inaccurate across complex environmental samples. A method, ANCHOR, is presented and designed for improved species-level microbial identification using paired-end sequences directly, multiple high-complexity samples and multiple reference databases. A standard operating procedure (SOP) is reported alongside benchmarking against artificial, single sample and replicated mock data sets. The method is then directly tested using a real-world data set from surface swabs of the International Space Station (ISS). Simple mock community analysis identified 100% of the expected species and 99% of expected gene copy variants (100% identical). A replicated mock community revealed similar or better numbers of expected species than MetaAmp, DADA2, Mothur and QIIME1. Analysis of the ISS microbiome identified 714 putative unique species/strains and differential abundance analysis distinguished significant differences between the Destiny module (U.S. laboratory) and Harmony module (sleeping quarters). Harmony was remarkably dominated by human gastrointestinal tract bacteria, similar to enclosed environments on earth; however, Destiny module bacteria also derived from nonhuman microbiome carriers present on the ISS, the laboratory's research animals. ANCHOR can help substantially improve sequence resolution of 16S rRNA gene amplification data within biologically replicated environmental experiments and integrated multidatabase annotation enhances interpretation of complex, nonreference microbiomes.
| S-EPMC6851558 | biostudies-literature
Project description:Autotrophic ammonia oxidizer (AAO) populations in soils from native, tilled, and successional treatments at the Kellogg Biological Station Long-Term Ecological Research site in southwestern Michigan were compared to assess effects of disturbance on these bacteria. N fertilization effects on AAO populations were also evaluated with soils from fertilized microplots within the successional treatments. Population structures were characterized by PCR amplification of microbial community DNA with group-specific 16S rRNA gene (rDNA) primers, cloning of PCR products and clone hybridizations with group-specific probes, phylogenetic analysis of partial 16S rDNA sequences, and denaturing gradient gel electrophoresis (DGGE) analysis. Population sizes were estimated by using most-probable-number (MPN) media containing varied concentrations of ammonium sulfate. Tilled soils contained higher numbers than did native soils of culturable AAOs that were less sensitive to different ammonium concentrations in MPN media. Compared to sequences from native soils, partial 16S rDNA sequences from tilled soils were less diverse and grouped exclusively within Nitrosospira cluster 3. Native soils yielded sequences representing three different AAO clusters. Probes for Nitrosospira cluster 3 hybridized with DGGE blots from tilled and fertilized successional soils but not with blots from native or unfertilized successional soils. Hybridization results thus suggested a positive association between the Nitrosospira cluster 3 subgroup and soils amended with inorganic N. DGGE patterns for soils sampled from replicated plots of each treatment were nearly identical for tilled and native soils in both sampling years, indicating spatial and temporal reproducibility based on treatment.
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