Project description:Mycorrhizae, symbiotic interactions between soil fungi and tree roots, are ubiquitous in terrestrial ecosystems. The fungi contribute phosphorous, nitrogen and mobilized nutrients from organic matter in the soil and in return the fungus receives photosynthetically-derived carbohydrates. This union of plant and fungal metabolisms is the mycorrhizal metabolome. Understanding this symbiotic relationship at a molecular level provides important contributions to the understanding of forest ecosystems and global carbon cycling. We generated next generation short-read transcriptomic sequencing data from fully-formed ectomycorrhizae between Laccaria bicolor and aspen (Populus tremuloides) roots. The transcriptomic data was used to identify statistically significantly expressed gene models using a bootstrap-style approach, and these expressed genes were mapped to specific metabolic pathways. Integration of expressed genes that code for metabolic enzymes and the set of expressed membrane transporters generates a predictive model of the ectomycorrhizal metabolome. Results indicate the specific compounds glycine, glutamate, and allantoin are synthesized by L. bicolor and that these compounds or their metabolites may be used for the benefit of aspen in exchange for the photosynthetically-derived sugars fructose and glucose.The analysis illustrates an approach to generate testable biological hypotheses to investigate the complex molecular interactions that drive ectomycorrhizal symbiosis. These models are consistent with experimental environmental data and provide insight into the molecular exchange processes for organisms in this complex ecosystem. The method used here for predicting metabolomic models of mycorrhizal systems from deep RNA sequencing data can be generalized and is broadly applicable to transcriptomic data derived from complex systems. Fully formed L.bicolor::P.trichocapra mycorrhizae in duplicate
Project description:Many trees form ectomycorrhizal symbiosis with fungi. During symbiosis, the tree roots supply sugar to the fungi in exchange for nitrogen, and this process is critical for the nitrogen and carbon cycles in forest ecosystems. However, the extents to which ectomycorrhizal fungi can liberate nitrogen and modify the soil organic matter and the mechanisms by which they do so remain unclear since they have lost many enzymes for litter decomposition that were present in their free-living, saprotrophic ancestors. Using time-series spectroscopy and transcriptomics, we examined the ability of two ectomycorrhizal fungi from two independently evolved ectomycorrhizal lineages to mobilize soil organic nitrogen. Both species oxidized the organic matter and accessed the organic nitrogen. The expression of those events was controlled by the availability of glucose and inorganic nitrogen. Despite those similarities, the decomposition mechanisms, including the type of genes involved as well as the patterns of their expression, differed markedly between the two species. Our results suggest that in agreement with their diverse evolutionary origins, ectomycorrhizal fungi use different decomposition mechanisms to access organic nitrogen entrapped in soil organic matter. The timing and magnitude of the expression of the decomposition activity can be controlled by the below-ground nitrogen quality and the above-ground carbon supply.
2018-11-30 | GSE110485 | GEO
Project description:eDNA Captures Depth Partitioning in a Kelp Forest Ecosystem
Project description:Understanding biological diversity and distribution patterns at multiple spatial scales is a central issue in ecology. Here, we investigated the biogeographical patterns of functional genes in soil microbes from 24 arctic heath sites using GeoChip-based metagenomics and principal coordinates of neighbour matrices (PCNM)-based analysis. Functional gene richness varied considerably among sites, while the proportions of each major functional gene category were evenly distributed. Functional gene composition varied significantly at most medium and broad spatial scales, and the PCNM analyses indicated that 14-20% of the variation in total and major functional gene categories could be attributed primarily to relatively broad-scale spatial effects that were consistent with broad-scale variation in soil pH and total nitrogen. The combination of variance partitioning and multi-scales analysis indicated that spatial distance effects contributed 12% to variation in functional gene composition,whereas environmental factors contributed only 3%. This relatively strong influence of spatial as compared to environmental variation in determining functional gene distributions contrasts sharply with typical microbial phylotype/species-based biogeographical patterns in the Arctic and elsewhere. Our results suggest that the distributions of soil functional genes cannot be predicted from phylogenetic distributions because spatial factors associated with historical contingencies are relatively important determinants of their biogeography.
Project description:Soil microbial community is a complex blackbox that requires a multi-conceptual approach (Hultman et al., 2015; Bastida et al., 2016). Most methods focus on evaluating total microbial community and fail to determine its active fraction (Blagodatskaya & Kuzyakov 2013). This issue has ecological consequences since the behavior of the active community is more important (or even essential) and can be different to that of the total community. The sensitivity of the active microbial community can be considered as a biological mechanism that regulates the functional responses of soil against direct (i.e. forest management) and indirect (i.e. climate change) human-induced alterations. Indeed, it has been highglihted that the diversity of the active community (analyzed by metaproteomics) is more connected to soil functionality than the that of the total community (analyzed by 16S rRNA gene and ITS sequencing) (Bastida et al., 2016). Recently, the increasing application of soil metaproteomics is providing unprecedented, in-depth characterisation of the composition and functionality of active microbial communities and overall, allowing deeper insights into terrestrial microbial ecology (Chourey et al., 2012; Bastida et al., 2015, 2016; Keiblinger et al., 2016). Here, we predict the responsiveness of the soil microbial community to forest management in a climate change scenario. Particularly, we aim: i) to evaluate the impacts of 6-years of induced drought on the diversity, biomass and activity of the microbial community in a semiarid forest ecocosystem; and ii) to discriminate if forest management (thinning) influences the resistance of the microbial community against induced drought. Furthermore, we aim to ascertain if the functional diversity of each phylum is a trait that can be used to predict changes in microbial abundance and ecosystem functioning.
Project description:Identifying the genetic basis for natural selection is a fundamental research goal, and particularly significant for soil fungi because of their central role in ecosystem functioning. Here, we identify rapid evolutionary processes in the plant root colonizing insect pathogen Metarhizium robertsii. While adapting to a new soil community, expression of TATA box containing cell wall and stress response genes evolved at an accelerated rate, whereas virulence determinants, transposons and chromosome structure were unaltered. The survival of diversified field isolates was increased, confirming that the mutations were adaptive, and we further show that large populations of Metarhizium are principally maintained by associations with plant roots rather than insect populations. These results provide a mechanistic basis for understanding mutational and selective effects on soil microbes.
Project description:Mycorrhizae, symbiotic interactions between soil fungi and tree roots, are ubiquitous in terrestrial ecosystems. The fungi contribute phosphorous, nitrogen and mobilized nutrients from organic matter in the soil and in return the fungus receives photosynthetically-derived carbohydrates. This union of plant and fungal metabolisms is the mycorrhizal metabolome. Understanding this symbiotic relationship at a molecular level provides important contributions to the understanding of forest ecosystems and global carbon cycling. We generated next generation short-read transcriptomic sequencing data from fully-formed ectomycorrhizae between Laccaria bicolor and aspen (Populus tremuloides) roots. The transcriptomic data was used to identify statistically significantly expressed gene models using a bootstrap-style approach, and these expressed genes were mapped to specific metabolic pathways. Integration of expressed genes that code for metabolic enzymes and the set of expressed membrane transporters generates a predictive model of the ectomycorrhizal metabolome. Results indicate the specific compounds glycine, glutamate, and allantoin are synthesized by L. bicolor and that these compounds or their metabolites may be used for the benefit of aspen in exchange for the photosynthetically-derived sugars fructose and glucose.The analysis illustrates an approach to generate testable biological hypotheses to investigate the complex molecular interactions that drive ectomycorrhizal symbiosis. These models are consistent with experimental environmental data and provide insight into the molecular exchange processes for organisms in this complex ecosystem. The method used here for predicting metabolomic models of mycorrhizal systems from deep RNA sequencing data can be generalized and is broadly applicable to transcriptomic data derived from complex systems.
Project description:Decomposition of soil organic matter in forest soils is thought to be controlled by the activity of saprotrophic fungi, while biotrophic fungi including ectomycorrhizal fungi act as vectors for input of plant carbon. The limited decomposing ability of ectomycorrhizal fungi is supported by recent findings showing that they have lost many of the genes that encode hydrolytic plant cell-wall degrading enzymes in their saprophytic ancestors. Nevertheless, here we demonstrate that ectomycorrhizal fungi representing at least four origins of symbiosis have retained significant capacity to degrade humus-rich litter amended with glucose. Spectroscopy showed that this decomposition involves an oxidative mechanism and that the extent of oxidation varies with the phylogeny and ecology of the species. RNA-Seq analyses revealed that the genome-wide set of expressed transcripts during litter decomposition has diverged over evolutionary time. Each species expressed a unique set of enzymes that are involved in oxidative lignocellulose degradation by saprotrophic fungi. A comparison of closely related species within the Boletales showed that ectomycorrhizal fungi oxidized litter material as efficiently as brown-rot saprotrophs. The ectomycorrhizal species within this clade exhibited more similar decomposing mechanisms than expected from the species phylogeny in concordance with adaptive evolution occurring as a result of similar selection pressures. Our data shows that ectomycorrhizal fungi are potential organic matter decomposers, yet not saprotrophs. We suggest that the primary function of this decomposing activity is to mobilize nutrients embedded in organic matter complexes and that the activity is driven by host carbon supply. Comparative transcriptomics of ectomycorrhizal (ECM) versus brown-rot (BR) fungi while degrading soil-organic matter
Project description:To study whether and how soil nitrogen conditions affect the ecological effects of long-term elevated CO2 on microbial community and soil ecoprocess, here we investigated soil microbial community in a grassland ecosystem subjected to ambient CO2 (aCO2, 368 ppm), elevated CO2 (eCO2, 560 ppm), ambient nitrogen deposition (aN) or elevated nitrogen deposition (eN) treatments for a decade. Under the aN condition, a majority of microbial function genes, as measured by GeoChip 4.0, were increased in relative abundance or remained unchanged by eCO2. Under the eN condition, most of functional genes associated with carbon, nitrogen and sulfur cycling, energy processes, organic remediation and stress responses were decreased or remained unchanged by eCO2, while genes associated with antibiotics and metal resistance were increased. The eCO2 effects on fungi and archaea were largely similar under both nitrogen conditions, but differed substantially for bacteria. Coupling of microbial carbon or nitrogen cycling genes, represented by positive percentage and density of gene interaction in association networks, was higher under the aN condition. In accordance, changes of soil CO2 flux, net N mineralization, ammonification and nitrification was higher under the aN condition. Collectively, these results demonstrated that eCO2 effects are contingent on nitrogen conditions, underscoring the difficulty toward predictive modeling of soil ecosystem and ecoprocesses under future climate scenarios and necessitating more detailed studies. Fourty eight samples were collected for four different carbon and nitrogen treatment levels (aCaN,eCaN,aCeN and eCeN) ; Twelve replicates in every elevation