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Bacterial phylogeny structures soil resistomes across habitats.

ABSTRACT: Ancient and diverse antibiotic resistance genes (ARGs) have previously been identified from soil, including genes identical to those in human pathogens. Despite the apparent overlap between soil and clinical resistomes, factors influencing ARG composition in soil and their movement between genomes and habitats remain largely unknown. General metagenome functions often correlate with the underlying structure of bacterial communities. However, ARGs are proposed to be highly mobile, prompting speculation that resistomes may not correlate with phylogenetic signatures or ecological divisions. To investigate these relationships, we performed functional metagenomic selections for resistance to 18 antibiotics from 18 agricultural and grassland soils. The 2,895 ARGs we discovered were mostly new, and represent all major resistance mechanisms. We demonstrate that distinct soil types harbour distinct resistomes, and that the addition of nitrogen fertilizer strongly influenced soil ARG content. Resistome composition also correlated with microbial phylogenetic and taxonomic structure, both across and within soil types. Consistent with this strong correlation, mobility elements (genes responsible for horizontal gene transfer between bacteria such as transposases and integrases) syntenic with ARGs were rare in soil by comparison with sequenced pathogens, suggesting that ARGs may not transfer between soil bacteria as readily as is observed between human pathogens. Together, our results indicate that bacterial community composition is the primary determinant of soil ARG content, challenging previous hypotheses that horizontal gene transfer effectively decouples resistomes from phylogeny.

SUBMITTER: Forsberg KJ

PROVIDER: S-EPMC4079543 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature

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Bacterial phylogeny structures soil resistomes across habitats.

Forsberg Kevin J KJ Patel Sanket S Gibson Molly K MK Lauber Christian L CL Knight Rob R Fierer Noah N Dantas Gautam G

Nature 20140521 7502

Ancient and diverse antibiotic resistance genes (ARGs) have previously been identified from soil, including genes identical to those in human pathogens. Despite the apparent overlap between soil and clinical resistomes, factors influencing ARG composition in soil and their movement between genomes and habitats remain largely unknown. General metagenome functions often correlate with the underlying structure of bacterial communities. However, ARGs are proposed to be highly mobile, prompting specu ...[more]

PMID: 24847883

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Project description:Natural soil is characterized as a complex habitat with patchy hydrated islands and spatially variable nutrients that is in a constant state of change due to wetting-drying dynamics. Soil microbial activity is often concentrated in sparsely distributed hotspots that contribute disproportionally to macroscopic biogeochemical nutrient cycling and greenhouse gas emissions. The mechanistic representation of such dynamic hotspots requires new modeling approaches capable of representing the interplay between dynamic local conditions and the versatile microbial metabolic adaptations. We have developed IndiMeSH (Individual-based Metabolic network model for Soil Habitats) as a spatially explicit model for the physical and chemical microenvironments of soil, combined with an individual-based representation of bacterial motility and growth using adaptive metabolic networks. The model uses angular pore networks and a physically based description of the aqueous phase as a backbone for nutrient diffusion and bacterial dispersal combined with dynamic flux balance analysis to calculate growth rates depending on local nutrient conditions. To maximize computational efficiency, reduced scale metabolic networks are used for the simulation scenarios and evaluated strategically to the genome scale model. IndiMeSH was compared to a well-established population-based spatiotemporal metabolic network model (COMETS) and to experimental data of bacterial spatial organization in pore networks mimicking soil aggregates. IndiMeSH was then used to strategically study dynamic response of a bacterial community to abrupt environmental perturbations and the influence of habitat geometry and hydration conditions. Results illustrate that IndiMeSH is capable of representing trophic interactions among bacterial species, predicting the spatial organization and segregation of bacterial populations due to oxygen and carbon gradients, and provides insights into dynamic community responses as a consequence of environmental changes. The modular design of IndiMeSH and its implementation are adaptable, allowing it to represent a wide variety of experimental and in silico microbial systems.

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Bacterial phylogeny structures soil resistomes across habitats.

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Bacterial phylogeny structures soil resistomes across habitats.

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