Project description:Decomposition of lignin-rich wood by fungi drives nutrient recycling in woodland ecosystems. Fluctuating abiotic conditions are known to promote the functioning of ecological communities and ecosystems. In the context of wood decay, fluctuating temperature increases decomposition rates. Metabolomics, in tandem with other ‘omics tools, can highlight the metabolic processes affected by experimental treatments, even in the absence of genome sequences and annotations. Globally, natural wood decay communities are dominated by the phylum Basidiomycota. We examined the metabolic responses of Mucidula mucida, a dominant constituent of pioneer communities in beech branches in British woodlands, and Exidia glandulosa, a stress-selected constituent of the same communities, in response to constant and diurnally cycling temperature. We applied untargeted metabolomics and proteomics to beech wood blocks, colonised by M. mucida or E. glandulosa and exposed to either diurnally cycling (mean 15 ± 10°C) or constant (15°C) temperature, in a fully factorial design. Metabolites and proteins linked to lignin breakdown, the citric acid cycle, pentose phosphate pathway, carbohydrate metabolism, fatty acid metabolism and protein biosynthesis and turnover were under-enriched in fluctuating, compared to stable temperatures, in the generalist M. mucida. Conversely E. glandulosa showed little differential response to the experimental treatments. By demonstrating temperature dependant metabolic signatures related to nutrient acquisition in a generalist wood decay fungus, we provide new insights into how abiotic conditions can affect community-mediated decomposition and carbon turnover in forests. We show that mechanisms underpinning important biogeochemical processes can be highlighted using untargeted metabolomics and proteomics in the absence of well-annotated genomes.
Project description:Co-expression networks and gene regulatory networks (GRNs) are emerging as important tools for predicting the functional roles of individual genes at a system-wide scale. To enable network reconstructions we built a large-scale gene expression atlas comprised of 62,547 mRNAs, 17,862 non-modified proteins, and 6,227 phosphoproteins harboring 31,595 phosphorylation sites quantified across maize development. There was little edge conservation in co-expression and GRNs reconstructed using transcriptome versus proteome data yet networks from either data type were enriched in ontological categories and effective in predicting known regulatory relationships. This integrated gene expression atlas provides a valuable community resource. The networks should facilitate plant biology research and they provide a conceptual framework for future systems biology studies highlighting the importance of studying gene regulation at several levels.
