Metabolic responses of two pioneer wood decay fungi to diurnally cycling temperature

This dataset contains pre-processed untargeted GC-MS metabolomics and direct shotgun proteomics from a microcosm woodblock experiment described in the paper "Rawlings et al (2021) Metabolic responses of two pioneer wood decay fungi to diurnally cycling temperature. Ecology."

The experiment investigates the effect of diurnal cycling of temperature on the metabolism of two wood decay species, Mucidula mucida and Exidia glandulosa. We colonised beech woodblocks with the two species (separate microcosms) and exposed them to either a diurnally cycling (mean 15 ± 10°C) or constant (15°C) temperature, in a fully factorial design. After 8 weeks we extracted the full complement of metabolites and proteins in the wood to examine the extent to which the abundances of metabolic products were altered.

The main results of the experiment were that products 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 which may be linked with its preference for habitats exhibiting abiotic stress. 

Methods
Data were collected through mass spectrometry after extracting all proteins and metabolites from wood block chips.

Gas chromatography mass spectrometry data were pre-processed using AMDIS for peak deconvolution, NIST 2017 and the GOLM Metabolome Database mass spectral reference libraries for metabolite identification and SpectConnect to produce the data matricies for analysis.

Liquid chromatography tandem mass spectrometry data were compared with the predicted protein databases of E. glandulosa HHB12029 (Nagy et al., 2016) and M. mucida CBS55879 (Barrasa, 2014; Ruiz-Dueñas et al., 2020) using MaxQuant with integrated Andromeda for database searching. Perseus was used to remove irrelevant protein groups and log2 transform LFQ intensity data.