Dataset Information

Compartmentalized metabolic network reconstruction of microbial communities to determine the effect of agricultural intervention on soils.

ABSTRACT: Soil microbial communities are responsible for a wide range of ecological processes and have an important economic impact in agriculture. Determining the metabolic processes performed by microbial communities is crucial for understanding and managing ecosystem properties. Metagenomic approaches allow the elucidation of the main metabolic processes that determine the performance of microbial communities under different environmental conditions and perturbations. Here we present the first compartmentalized metabolic reconstruction at a metagenomics scale of a microbial ecosystem. This systematic approach conceives a meta-organism without boundaries between individual organisms and allows the in silico evaluation of the effect of agricultural intervention on soils at a metagenomics level. To characterize the microbial ecosystems, topological properties, taxonomic and metabolic profiles, as well as a Flux Balance Analysis (FBA) were considered. Furthermore, topological and optimization algorithms were implemented to carry out the curation of the models, to ensure the continuity of the fluxes between the metabolic pathways, and to confirm the metabolite exchange between subcellular compartments. The proposed models provide specific information about ecosystems that are generally overlooked in non-compartmentalized or non-curated networks, like the influence of transport reactions in the metabolic processes, especially the important effect on mitochondrial processes, as well as provide more accurate results of the fluxes used to optimize the metabolic processes within the microbial community.

SUBMITTER: Alvarez-Silva MC

PROVIDER: S-EPMC5540551 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Compartmentalized metabolic network reconstruction of microbial communities to determine the effect of agricultural intervention on soils.

Alvarez-Silva María Camila MC Álvarez-Yela Astrid Catalina AC Gómez-Cano Fabio F Zambrano María Mercedes MM Husserl Johana J Danies Giovanna G Restrepo Silvia S González-Barrios Andrés Fernando AF

PloS one 20170802 8

Soil microbial communities are responsible for a wide range of ecological processes and have an important economic impact in agriculture. Determining the metabolic processes performed by microbial communities is crucial for understanding and managing ecosystem properties. Metagenomic approaches allow the elucidation of the main metabolic processes that determine the performance of microbial communities under different environmental conditions and perturbations. Here we present the first compartm ...[more]

PMID: 28767679

Similar Datasets

Project description:This study investigated the differences in microbial community abundance, composition and diversity throughout the depth profiles in soils collected from corn and soybean fields in lowa, USA using 16S rRNA amplicon sequencing. The results revealed decreased richness and diversity in microbial communities at increasing soil depth. Soil microbial community composition differed due to crop type only in the top 60 cm and due to location only in the top 90 cm. While the relative abundance of most phyla decreased in deep soils, the relative abundance of the phylum Proteobacteria increased and dominated agricultural soils below the depth of 90 cm. Although soil depth was the most important factor shaping microbial communities, edaphic factors including soil organic matter, soil bulk density and the length of time that deep soils were saturated with water were all significant factors explaining the variation in soil microbial community composition. Soil organic matter showed the highest correlation with the exponential decrease in bacterial abundance with depth. A greater understanding of how soil depth influences the diversity and composition of soil microbial communities is vital for guiding sampling approaches in agricultural soils where plant roots extend beyond the upper soil profile. In the long term a greater knowledge of the influence of depth on microbial communities should contribute to new strategies that enhance the sustainability of soil which is a precious resource for food security.IMPORTANCE Determining how microbial properties change across different soils and within the soil depth profile, will be potentially beneficial to understanding the long-term processes that are involved in the health of agricultural ecosystems. Most literature on soil microbes has been restricted to the easily accessible surface soils. However, deep soils are important in soil formation, carbon sequestration, and in providing nutrients and water for plants. In the most productive agricultural systems in the USA where soybean and corn are grown, crop plant roots extend into the deeper regions of soils (> 100 cm), but little is known about the taxonomic diversity or the factors that shape deep soil microbial communities. The findings reported here highlight the importance of soil depth in shaping microbial communities, provide new information about edaphic factors that influence the deep soil communities and reveal more detailed information on taxa that exist in deep agricultural soils.

Project description:The dynamics of individual microbial populations and their gene functions in agricultural soils, especially after major activities such as nitrogen (N) fertilization, remain elusive but are important for a better understanding of nutrient cycling. Here, we analyzed 20 short-read metagenomes collected at four time points during 1 year from two depths (0 to 5 and 20 to 30 cm) in two Midwestern agricultural sites representing contrasting soil textures (sandy versus silty loam) with similar cropping histories. Although the microbial community taxonomic and functional compositions differed between the two locations and depths, they were more stable within a depth/site throughout the year than communities in natural aquatic ecosystems. For example, among the 69 population genomes assembled from the metagenomes, 75% showed a less than 2-fold change in abundance between any two sampling points. Interestingly, six deep-branching Thaumarchaeota and three complete ammonia oxidizer (comammox) Nitrospira populations increased up to 5-fold in abundance upon the addition of N fertilizer. These results indicated that indigenous archaeal ammonia oxidizers may respond faster (are more copiotrophic) to N fertilization than previously thought. None of 29 recovered putative denitrifier genomes encoded the complete denitrification pathway, suggesting that denitrification is carried out by a collection of different populations. Altogether, our study identified novel microbial populations and genes responding to seasonal and human-induced perturbations in agricultural soils that should facilitate future monitoring efforts and N-related studies.IMPORTANCE Even though the impact of agricultural management on the microbial community structure has been recognized, an understanding of the dynamics of individual microbial populations and what functions each population carries are limited. Yet, this information is important for a better understanding of nutrient cycling, with potentially important implications for preserving nitrogen in soils and sustainability. Here, we show that reconstructed metagenome-assembled genomes (MAGs) are relatively stable in their abundance and functional gene content year round, and seasonal nitrogen fertilization has selected for novel Thaumarchaeota and comammox Nitrospira nitrifiers that are potentially less oligotrophic than their marine counterparts previously studied.

Dataset Information

Compartmentalized metabolic network reconstruction of microbial communities to determine the effect of agricultural intervention on soils.

Publications

Compartmentalized metabolic network reconstruction of microbial communities to determine the effect of agricultural intervention on soils.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets