Dataset Information

Response of Soil Properties and Microbial Communities to Agriculture: Implications for Primary Productivity and Soil Health Indicators.

ABSTRACT: Agricultural intensification is placing tremendous pressure on the soil's capacity to maintain its functions leading to large-scale ecosystem degradation and loss of productivity in the long term. Therefore, there is an urgent need to find early indicators of soil health degradation in response to agricultural management. In recent years, major advances in soil meta-genomic and spatial studies on microbial communities and community-level molecular characteristics can now be exploited as 'biomarker' indicators of ecosystem processes for monitoring and managing sustainable soil health under global change. However, a continental scale, cross biome approach assessing soil microbial communities and their functional potential to identify the unifying principles governing the susceptibility of soil biodiversity to land conversion is lacking. We conducted a meta-analysis from a dataset generated from 102 peer-reviewed publications as well as unpublished data to explore how properties directly linked to soil nutritional health (total C and N; C:N ratio), primary productivity (NPP) and microbial diversity and composition (relative abundance of major bacterial phyla determined by next generation sequencing techniques) are affected in response to agricultural management across the main biomes of Earth (arid, continental, temperate and tropical). In our analysis, we found strong statistical trends in the relative abundance of several bacterial phyla in agricultural (e.g., Actinobacteria and Chloroflexi) and natural (Acidobacteria, Proteobacteria, and Cyanobacteria) systems across all regions and these trends correlated well with many soil properties. However, main effects of agriculture on soil properties and productivity were biome-dependent. Our meta-analysis provides evidence on the predictable nature of the microbial community responses to vegetation type. This knowledge can be exploited in future for developing a new set of indicators for primary productivity and soil health.

SUBMITTER: Trivedi P

PROVIDER: S-EPMC4940416 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Response of Soil Properties and Microbial Communities to Agriculture: Implications for Primary Productivity and Soil Health Indicators.

Trivedi Pankaj P Delgado-Baquerizo Manuel M Anderson Ian C IC Singh Brajesh K BK

Frontiers in plant science 20160712

Agricultural intensification is placing tremendous pressure on the soil's capacity to maintain its functions leading to large-scale ecosystem degradation and loss of productivity in the long term. Therefore, there is an urgent need to find early indicators of soil health degradation in response to agricultural management. In recent years, major advances in soil meta-genomic and spatial studies on microbial communities and community-level molecular characteristics can now be exploited as 'biomark ...[more]

PMID: 27462326

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Project description:BackgroundStudying expression of genes by direct sequencing and analysis of metatranscriptomes at a particular time and space can disclose structural and functional insights about microbial communities. The present study reports comparative analysis of metatranscriptome from two distinct soil ecosystems referred as M1 (agriculture soil) and O1 (organic soil).ResultsAnalysis of sequencing reads revealed Proteobacteria as major dominant phyla in both soil types. The order of the top 3 abundant phyla in M1 sample was Proteobacteria > Ascomycota > Firmicutes, whereas in sample O1, the order was Proteobacteria > Cyanobacteria > Actinobacteria. Analysis of differentially expressed genes demonstrated high expression of transcripts related to copper-binding proteins, proteins involved in electron carrier activity, DNA integration, endonuclease activity, MFS transportation, and other uncharacterized proteins in M1 compared to O1. Of the particular interests, several transcripts related to nitrification, ammonification, stress response, and alternate carbon fixation pathways were highly expressed in M1. In-depth analysis of the sequencing data revealed that transcripts of archaeal origin had high expression in M1 compared to O1 indicating the active role of Archaea in metal- and pesticide-contaminated environment. In addition, transcripts encoding 4-hydroxyphenylpyruvate dioxygenase, glyoxalase/bleomycin resistance protein/dioxygenase, metapyrocatechase, and ring hydroxylating dioxygenases of aromatic hydrocarbon degradation pathways had high expression in M1. Altogether, this study provided important insights about the transcripts and pathways upregulating in the presence of pesticides and herbicides.ConclusionAltogether, this study claims a high expression of microbial transcripts in two ecosystems with a wide range of functions. It further provided clue about several molecular markers which could be a strong indicator of metal and pesticide contamination in soils. Interestingly, our study revealed that Archaea are playing a significant role in nitrification process as compared to bacteria in metal- and pesticide-contaminated soil. In particular, high expression of transcripts related to aromatic hydrocarbon degradation in M1 soil indicates their important role in biodegradation of pollutants, and therefore, further investigation is needed.

Project description:UNLABELLED: Understanding the interactions among different species and their responses to environmental changes, such as elevated atmospheric concentrations of CO(2), is a central goal in ecology but is poorly understood in microbial ecology. Here we describe a novel random matrix theory (RMT)-based conceptual framework to discern phylogenetic molecular ecological networks using metagenomic sequencing data of 16S rRNA genes from grassland soil microbial communities, which were sampled from a long-term free-air CO(2) enrichment experimental facility at the Cedar Creek Ecosystem Science Reserve in Minnesota. Our experimental results demonstrated that an RMT-based network approach is very useful in delineating phylogenetic molecular ecological networks of microbial communities based on high-throughput metagenomic sequencing data. The structure of the identified networks under ambient and elevated CO(2) levels was substantially different in terms of overall network topology, network composition, node overlap, module preservation, module-based higher-order organization, topological roles of individual nodes, and network hubs, suggesting that the network interactions among different phylogenetic groups/populations were markedly changed. Also, the changes in network structure were significantly correlated with soil carbon and nitrogen contents, indicating the potential importance of network interactions in ecosystem functioning. In addition, based on network topology, microbial populations potentially most important to community structure and ecosystem functioning can be discerned. The novel approach described in this study is important not only for research on biodiversity, microbial ecology, and systems microbiology but also for microbial community studies in human health, global change, and environmental management. IMPORTANCE: The interactions among different microbial populations in a community play critical roles in determining ecosystem functioning, but very little is known about the network interactions in a microbial community, owing to the lack of appropriate experimental data and computational analytic tools. High-throughput metagenomic technologies can rapidly produce a massive amount of data, but one of the greatest difficulties is deciding how to extract, analyze, synthesize, and transform such a vast amount of information into biological knowledge. This study provides a novel conceptual framework to identify microbial interactions and key populations based on high-throughput metagenomic sequencing data. This study is among the first to document that the network interactions among different phylogenetic populations in soil microbial communities were substantially changed by a global change such as an elevated CO(2) level. The framework developed will allow microbiologists to address research questions which could not be approached previously, and hence, it could represent a new direction in microbial ecology research.

Project description:Substrate quality and the availability of nutrients are major factors controlling microbial decomposition processes in soils. Seasonal alteration in resource availability, which is driven by plants via belowground C allocation, nutrient uptake and litter fall, also exerts effects on soil microbial community composition. Here we investigate if seasonal and experimentally induced changes in microbial community composition lead to alterations in functional properties of microbial communities and thus microbial processes. Beech forest soils characterized by three distinct microbial communities (winter and summer community, and summer community from a tree girdling plot, in which belowground carbon allocation was interrupted) were incubated with different 13C-labeled substrates with or without inorganic N supply and analyzed for substrate use and various microbial processes. Our results clearly demonstrate that the three investigated microbial communities differed in their functional response to addition of various substrates. The winter communities revealed a higher capacity for degradation of complex C substrates (cellulose, plant cell walls) than the summer communities, indicated by enhanced cellulase activities and reduced mineralization of soil organic matter. In contrast, utilization of labile C sources (glucose) was lower in winter than in summer, demonstrating that summer and winter community were adapted to the availability of different substrates. The saprotrophic community established in girdled plots exhibited a significantly higher utilization of complex C substrates than the more plant root associated community in control plots if additional nitrogen was provided. In this study we were able to demonstrate experimentally that variation in resource availability as well as seasonality in temperate forest soils cause a seasonal variation in functional properties of soil microorganisms, which is due to shifts in community structure and physiological adaptations of microbial communities to altered resource supply.

Dataset Information

Response of Soil Properties and Microbial Communities to Agriculture: Implications for Primary Productivity and Soil Health Indicators.

Publications

Response of Soil Properties and Microbial Communities to Agriculture: Implications for Primary Productivity and Soil Health Indicators.

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