Deciphering the Energy Use Channels in Soil Organic Matter: Impacts of Long-term Manure Addition and Necromass Revealed by LC-FT-ICR-MS

Manuring of arable soils has been reported to increase soil organic matter (SOM) contents, microbial activity, and abundance of microbial metabolites, suggesting an increasing abundance of necromass markers in general. SOM’s chemical complexity hampers our understanding of mechanistic links between SOM transformation, necromass imprints, and energy storage. Non-targeted molecular-levels techniques can provide insight into SOM’s molecular composition, energetic fingerprint and effects of manuring. We compared water-extractable organic matter (WEOM) from long-term manured soils with a set of fresh plant, bacterial and fungal necromass extracts by liquid chromatography Fourier transform ion cyclotron resonance mass spectrometry (LC-FT-ICR-MS). Manuring increased WEOM complexity in polar, unsaturated, oxidised and energy-poor compounds. These changes were linked to a 2-3-fold increase in necromass markers. In comparison to unfertilized soil, manured WEOM was dominated by bacterial necromass markers over fungal ones, suggesting bacterial control of changes in WEOM’s energetic properties. Although unfertilized soils showed a smaller necromass imprint, fungal N-containing markers were present, suggesting a more dominant fungal energy use channel, and potential N mining. Despite the parallel shifts in necromass imprints and NOSC between soils, 83% of formulas were not assigned to any necromass, but explained most of the shift to a more bioavailable, oxidized and energy-poor WEOM via long-term manuring. This could suggest that manuring promotes the oxidation of pre-existing SOM not associated to fresh necromass (“priming”). Alternatively, this could point to a missing coverage of necromass compositional variability in our study. We demonstrate the potential of LC-FT-ICR-MS to complement classical necromass marker studies by reporting ∼600 novel, readily soluble microbial necromass markers, thereby providing an avenue to build comprehensive databases for a more robust annotation of SOM sources and transformation processes in the future.