Ontology highlight
ABSTRACT:
PROVIDER: PRJNA507292 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR8252910_1.fastq.gz | Fastqsanger.gz | |||
| SRR8252910_2.fastq.gz | Fastqsanger.gz | |||
| SRR8252920_1.fastq.gz | Fastqsanger.gz | |||
| SRR8252920_2.fastq.gz | Fastqsanger.gz | |||
| SRR8252930_1.fastq.gz | Fastqsanger.gz |
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Project description:The spread of antibiotic resistance genes (ARG) into agricultural soils, products, and foods severely limits the use of organic fertilizers in agriculture. In this study, experimental land plots were fertilized, sown, and harvested for two consecutive agricultural cycles using either mineral or three types of organic fertilizers: sewage sludge, pig slurry, or composted organic fraction of municipal solid waste. The analysis of the relative abundances of more than 200,000 ASV (Amplicon Sequence Variants) allowed the identification of a small, but significant (<10%) overlap between soil and fertilizer microbiomes, particularly in soils sampled the same day of the harvest (post-harvest soils). Loads of clinically relevant ARG were significantly higher (up to 100 fold) in fertilized soils relative to the initial soil. The highest increases corresponded to post-harvest soils treated with organic fertilizers, and they correlated with the extend of the contribution of fertilizers to the soil microbiome. Edible products (lettuce and radish) showed low, but measurable loads of ARG (sul1 for lettuces and radish, tetM for lettuces). These loads were minimal in mineral fertilized soils, and strongly dependent on the type of fertilizer. We concluded that at least part of the observed increase on ARG loads in soils and foodstuffs were actual contributions from the fertilizer microbiomes. Thus, we propose that adequate waste management and good pharmacological and veterinarian practices may significantly reduce the potential health risk posed by the presence of ARG in agricultural soils and plant products.
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Project description:GCMS datasets for the soil depth manuscript
Abstract
Two factors that are well-known to influence soil microbiomes include the depth of the soil as well as the level of moisture. Previous works have demonstrated that climate change will increase the incidence of drought in soils, but it is unknown how fluctuations in moisture availability affect soil microbiome composition and functioning down the depth profile. Here, we investigated soil and wheatgrass rhizosphere microbiomes in a common field setting under four different irrigation regimes and three depths. We demonstrated that there is a significant interactive effect, where fluctuations in soil moisture more strongly influence soil microbiomes at the surface layer than in deeper layers, including for soil community composition, diversity, and for functional profiles. Meanwhile, in rhizosphere communities the influence of irrigation was similar across the different depths, although there were slight discrepancies between the two cultivars of wheatgrass used. The lessened response of deeper soil microbiomes to changes in irrigation may be due to higher incidence of slow-growing, stress-resistant microbes.
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Project description:Microarrays have become established tools for describing microbial systems, however the assessment of expression profiles for environmental microbial communities still presents unique challenges. Notably, the concentration of particular transcripts are likely very dilute relative to the pool of total RNA, and PCR-based amplification strategies are vulnerable to amplification biases and the appropriate primer selection. Thus, we apply a signal amplification approach, rather than template amplification, to analyze the expression of selected lignin-degrading enzymes in soil. Controls in the form of known amplicons and cDNA from Phanerochaete chrysosporium were included and mixed with the soil cDNA both before and after the signal amplification in order to assess the dynamic range of the microarray. We demonstrate that restored prairie soil expresses a diverse range of lignin-degrading enzymes following incubation with lignin substrate, while farmed agricultural soil does not. The mixed additions of control cDNA with soil cDNA indicate that the mixed biomass in the soil does interfere with low abundance transcript changes, nevertheless our microarray approach consistently reports the most robust signals. Keywords: comparative analysis, microbial ecology, soil microbial communities
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