Microcosm flow5/16/2023 ![]() ![]() This limits analyses to sequential snapshots rather than more continuous time-series and results in important information loss. Capturing such microbial metabolic trajectories in heterogeneous systems like soils remains challenging due to problems associated with destructive sampling and low time resolution.Īlthough the characterization of soil microbial metabolism has become much more convenient and effective due to the development of sequence-based and mass spectrometry approaches to interrogate biomolecular processes, most approaches require destructive sample retrieval and processing. This response is rapid with turnover of microbial biomass, community composition, gene expression and metabolism being highly dynamic over a period of a few hours to days (e.g., Placella et al., 2012 Placella and Firestone, 2013 Barnard et al., 2020 Blazewicz et al., 2020). This response to snowmelt infiltration is similar to the Birch Effect that has been observed as the respiration response of a dry soil to wet-up ( Birch, 1958). During this critical phase of the water year in snow dominated systems, nitrogen retention and release by microbial biomass is dynamic and associated with snowmelt dynamics ( Brooks et al., 1998). Our prior work observed that snowmelt induced a significant shift in soil water potential, dynamic biomass growth and turnover that corresponded to a reassembly of the soil microbiome ( Sorensen et al., 2020). Snowpack dynamics for example are strongly influenced by climate driving forces such as atmospheric warming and precipitation patterns, and in turn regulate both plant and microbial activity ( Brooks et al., 1998 Lipson et al., 2002 Steltzer et al., 2009 Wipf, 2010 Sorensen et al., 2019). Accurate characterization of the activity of soil microbiomes is key to understanding how the soil compartment functions and responds to chronic and acute perturbations ( Bardgett and van der Putten, 2014 Delgado-Baquerizo et al., 2019). Soil is a major compartment of the Earth system and its constituent organisms are central contributors to global biogeochemical cycles. Overall, it appears that such mVC time-series from PTR-TOF-MS combined with causal inference represents an attractive approach to non-destructively observe soil microbial metabolism and its response to environmental perturbation. Increases in ammonia oxidation signatures (transformation of hydroxylamine to nitrite) were observed in parallel, and while the relative role of nitrifiers or methylotrophs cannot be confirmed, the inferred connection to TMA oxidation suggests either a direct or indirect coupling between these processes. ![]() Unique and synergistic connections between intermediates of methylotrophic pathways such as dimethylamine, formaldehyde and methanol were observed upon wet-up and indicate that the initial pulse of TMA was likely transformed into these intermediates by methylotrophs. Simulated snowmelt resulted in a rapid increase in the production of trimethylamine (TMA) suggesting that anaerobic degradation of quaternary amine osmo/cryoprotectants, such as glycine betaine, may be important contributors to this resource pulse. The biological context for these mVC interactions was evaluated by projecting the connections onto the Kyoto Encyclopedia of Genes and Genomes (KEGG) network of known metabolic pathways. ![]() Using an information theory approach based on the partitioning of mutual information, we identified mVC metabolite pairs with robust interactions, including those that were non-linear and with time lags. In this study, we used PTR-TOF-MS to investigate the metabolic trajectory of microbiomes from a subalpine forest soil, and their response to a simulated wet-up event akin to snowmelt. Microbial volatile compounds (mVCs) emitted from soil represent information-dense signatures and when assayed non-destructively using state-of-the-art instrumentation such as Proton Transfer Reaction-Time of Flight-Mass Spectrometry (PTR-TOF-MS) provide time resolved insights into the metabolism of active microbiomes. However, observing microbial metabolism and its dynamics non-destructively remains a major challenge for systems such as soil. With an increasing concern that climate change accelerates both snowmelt timing and rate, obtaining an accurate characterization of microbial response to snowmelt is important for understanding biogeochemical cycles intertwined with soil. Snowmelt dynamics are a significant determinant of microbial metabolism in soil and regulate global biogeochemical cycles of carbon and nutrients by creating seasonal variations in soil redox and nutrient pools. ![]()
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