Mastering ectomycorrhizal symbiosis: the impact of carbohydrates.
ABSTRACT Mycorrhiza formation is the consequence of a mutualistic interaction between certain soil fungi and plant roots that helps to overcome nutritional limitations faced by the respective partners. In symbiosis, fungi contribute to tree nutrition by means of mineral weathering and mobilization of nutrients from organic matter, and obtain plant-derived carbohydrates as a response. Support with easily degradable carbohydrates seems to be the driving force for fungi to undergo this type of interaction. As a consequence, the fungal hexose uptake capacity is strongly increased in Hartig net hyphae of the model fungi Amanita muscaria and Laccaria bicolor. Next to fast carbohydrate uptake and metabolism, storage carbohydrates are of special interest. In functional A. muscaria ectomycorrhizas, expression and activity of proteins involved in trehalose biosynthesis is mainly localized in hyphae of the Hartig net, indicating an important function of trehalose in generation of a strong carbon sink by fungal hyphae. In symbiosis, fungal partners receive up to approximately 19 times more carbohydrates from their hosts than normal leakage of the root system would cause, resulting in a strong carbohydrate demand of infected roots and, as a consequence, a more efficient plant photosynthesis. To avoid fungal parasitism, the plant seems to have developed mechanisms to control carbohydrate drain towards the fungal partner and link it to the fungus-derived mineral nutrition. In this contribution, current knowledge on fungal strategies to obtain carbohydrates from its host and plant strategies to enable, but also to control and restrict (under certain conditions), carbon transfer are summarized.
Article: Using deep RNA sequencing for the structural annotation of the Laccaria bicolor mycorrhizal transcriptome.[show abstract] [hide abstract]
ABSTRACT: Accurate structural annotation is important for prediction of function and required for in vitro approaches to characterize or validate the gene expression products. Despite significant efforts in the field, determination of the gene structure from genomic data alone is a challenging and inaccurate process. The ease of acquisition of transcriptomic sequence provides a direct route to identify expressed sequences and determine the correct gene structure. We developed methods to utilize RNA-seq data to correct errors in the structural annotation and extend the boundaries of current gene models using assembly approaches. The methods were validated with a transcriptomic data set derived from the fungus Laccaria bicolor, which develops a mycorrhizal symbiotic association with the roots of many tree species. Our analysis focused on the subset of 1501 gene models that are differentially expressed in the free living vs. mycorrhizal transcriptome and are expected to be important elements related to carbon metabolism, membrane permeability and transport, and intracellular signaling. Of the set of 1501 gene models, 1439 (96%) successfully generated modified gene models in which all error flags were successfully resolved and the sequences aligned to the genomic sequence. The remaining 4% (62 gene models) either had deviations from transcriptomic data that could not be spanned or generated sequence that did not align to genomic sequence. The outcome of this process is a set of high confidence gene models that can be reliably used for experimental characterization of protein function. 69% of expressed mycorrhizal JGI "best" gene models deviated from the transcript sequence derived by this method. The transcriptomic sequence enabled correction of a majority of the structural inconsistencies and resulted in a set of validated models for 96% of the mycorrhizal genes. The method described here can be applied to improve gene structural annotation in other species, provided that there is a sequenced genome and a set of gene models.PLoS ONE 01/2010; 5(7):e9780. · 4.09 Impact Factor
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ABSTRACT: 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. The generated model of mycorrhizal metabolome predicts that 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.BMC Systems Biology 01/2011; 5:70. · 3.15 Impact Factor