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Amazon deforestation enriches antibiotic resistance genes

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Abstract

The expansion of livestock production and agriculture is responsible for the increase of deforestation rates in the Amazon rainforest, with consequences to climate and micro and macro biodiversity. Although many studies have evaluated the effects of deforestation on the microbiome, its effect on the soil resistome remains unknown. Considering that antibiotic resistance genes (ARGs) are a threat to global health and food security, here we evaluated how land-use change in the Amazon region impacts the soil resistome. Our analysis revealed that several antibiotic resistance mechanisms and genes are common to both the native forest and the altered areas; however, deforestation and subsequent conversion to other land-use systems increased the diversity and abundance of these genes. The enrichment of ARGs is correlated to increased microbial diversity in response to deforestation, along with changes in soil chemical properties, such as pH and aluminum. Our findings demonstrated that Amazon deforestation enriched ARGs in soil and how anthropogenic disturbances may exert selective pressure on the microbial communities expanding the soil resistome. Further investigation is still needed to understand if the ARGs can be transferred via the food chains (e.g. agricultural soils) to humans, jeopardizing antibiotic treatment effectiveness and compromising public health.

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Slash‐and‐burn clearing of forest typically results in increase in soil nutrient availability. However, the impact of these nutrients on the soil microbiome is not known. Using next generation sequencing of 16S rRNA gene and shotgun metagenomic DNA, we compared the structure and the potential functions of bacterial community in forest soils to deforested soils in the Amazon region and related the differences to soil chemical factors. Deforestation decreased soil organic matter content and factors linked to soil acidity and raised soil pH, base saturation and exchangeable bases. Concomitant to expected changes in soil chemical factors, we observed an increase in the alpha diversity of the bacterial microbiota and relative abundances of putative copiotrophic bacteria such as Actinomycetales and a decrease in the relative abundances of bacterial taxa such as Chlamydiae, Planctomycetes and Verrucomicrobia in the deforested soils. We did not observe an increase in genes related to microbial nutrient metabolism in deforested soils. However, we did observe changes in community functions such as increases in DNA repair, protein processing, modification, degradation and folding functions, and these functions might reflect adaptation to changes in soil characteristics due to forest clear‐cutting and burning. In addition, there were changes in the composition of the bacterial groups associated with metabolism‐related functions. Co‐occurrence microbial network analysis identified distinct phylogenetic patterns for forest and deforested soils and suggested relationships between Planctomycetes and aluminium content, and Actinobacteria and nitrogen sources in Amazon soils. The results support taxonomic and functional adaptations in the soil bacterial community following deforestation. We hypothesize that these microbial adaptations may serve as a buffer to drastic changes in soil fertility after slash‐and‐burning deforestation in the Amazon region.
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Soil microorganisms are sensitive to environment disturbances, and such alterations have consequences on microbial diversity and functions. Our hypothesis is that alpha diversity of microbial communities and functional diversity decrease from undisturbed to disturbed soils, with consequences for functional redundancy in the soil ecosystem. To test this hypothesis, we used soil DNA shotgun metagenomics approach to assess the soil microbiome in a chronosequence of land-use from a native tropical forest, followed by deforestation and cultivation of soybean croplands and pasture in different seasons. Agriculture and pasture soils were among the most diverse and presented higher functional redundancy, which is important to maintain the ecosystem functioning after the forest conversion. On the other hand, the ecosystem equilibrium in forest is maintained based on a lower alpha diversity but higher abundance of microorganisms. Our results indicate that land-use change alters the structure and composition of microbial communities; however, ecosystem functionality is overcome by different strategies based on the abundance and diversity of the communities.
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STAMP is a graphical software package that provides statistical hypothesis tests and exploratory plots for analysing taxonomic and functional profiles. It supports tests for comparing pairs of samples or samples organized into two or more treatment groups. Effect sizes and confidence intervals are provided to allow critical assessment of the biological relevancy of test results. A user-friendly graphical interface permits easy exploration of statistical results and generation of publication-quality plots. Availability and implementation: STAMP is licensed under the GNU GPL. Python source code and binaries are available from our website at: http://kiwi.cs.dal.ca/Software/STAMP Contact: donovan.parks{at}gmail.com Supplementary information: Supplementary data are available at Bioinformatics online.
Article
Hypothesis-testing methods for multivariate data are needed to make rigorous probability statements about the effects of factors and their interactions in experiments. Analysis of variance is particularly powerful for the analysis of univariate data. The traditional multivariate analogues, however, are too stringent in their assumptions for most ecological multivariate data sets. Non-parametric methods, based on permutation tests, are preferable. This paper describes a new non-parametric method for multivariate analysis of variance, after McArdle and Anderson (in press). It is given here, with several applications in ecology, to provide an alternative and perhaps more intuitive formulation for ANOVA (based on sums of squared distances) to complement the description provided by McArdle and Anderson (in press) for the analysis of any linear model. It is an improvement on previous non-parametric methods because it allows a direct additive partitioning of variation for complex models. It does this while maintaining the flexibility and lack of formal assumptions of other non-parametric methods. The test-statistic is a multivariate analogue to Fisher’s F-ratio and is calculated directly from any symmetric distance or dissimilarity matrix. P-values are then obtained using permutations. Some examples of the method are given for tests involving several factors, including factorial and hierarchical (nested) designs and tests of interactions.
Article
Mass production and use of antibiotics and antimicrobials in medicine and agriculture have existed for over 60 years, and has substantially benefited public health and agricultural productivity throughout the world. However, there is growing evidence that resistance to antibiotics (AR) is increasing both in benign and pathogenic bacteria, posing an emerging threat to public and environmental health in the future. Although evidence has existed for years from clinical data of increasing AR, almost no quantitative environmental data exist that span increased industrial antibiotic production in the 1950s to the present; i.e., data that might delineate trends in AR potentially valuable for epidemiological studies. To address this critical knowledge gap, we speculated that AR levels might be apparent in historic soil archives as evidenced by antibiotic resistance gene (ARG) abundances over time. Accordingly, DNA was extracted from five long-term soil-series from different locations in The Netherlands that spanned 1940 to 2008, and 16S rRNA gene and 18 ARG abundances from different major antibiotic classes were quantified. Results show that ARG from all classes of antibiotics tested have significantly increased since 1940, but especially within the tetracyclines, with some individual ARG being >15 times more abundant now than in the 1970s. This is noteworthy because waste management procedures have broadly improved and stricter rules on nontherapeutic antibiotic use in agriculture are being promulgated. Although these data are local to The Netherlands, they suggest basal environmental levels of ARG still might be increasing, which has implications to similar locations around the world.
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Animal production has changed from subsistence to an industrial model, lowering production costs but giving rise to higher potential environmental impact. When the effluents are not correctly managed, serious pollution events can occur. In Brazil liquid manure is commonly stored in reception pits or covered lagoons (biodigestors), followed by land application as a biofertilizer. In some regions there is an excess of manure due to low soil support capacities, and in these cases new technologies have to be adopted to export or treat the excess effluent. Manure storage time in pits/covered lagoons and new polymers to separate the solid fraction have been studied in Brazil. Treatment technologies, like swine manure treatment systems (SMTS), have been developed from a technical and economical point of view to optimize the processes and give a technological alternative to pork producers increasing production while reducing environmental impact.
Article
Over the millennia, microorganisms have evolved evasion strategies to overcome a myriad of chemical and environmental challenges, including antimicrobial drugs. Even before the first clinical use of antibiotics more than 60 years ago, resistant organisms had been isolated. Moreover, the potential problem of the widespread distribution of antibiotic resistant bacteria was recognized by scientists and healthcare specialists from the initial use of these drugs. Why is resistance inevitable and where does it come from? Understanding the molecular diversity that underlies resistance will inform our use of these drugs and guide efforts to develop new efficacious antibiotics.
Advanced swine manure treatment and utilization in Brazil. Bioresource technology, OECD workshop: livestock waste treatment systems of the future: a challenge to environmental quality
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