Microbial Communities Influence Soil Dissolved Organic Carbon Concentration by Altering Metabolite Composition

Abstract

Rapid microbial growth in the early phase of plant litter decomposition is viewed as an important component of soil organic matter (SOM) formation. However, the microbial taxa and chemical substrates that correlate with carbon storage are not well resolved. The complexity of microbial communities and diverse substrate chemistries that occur in natural soils make it difficult to identify links between community membership and decomposition processes in the soil environment. To identify potential relationships between microbes, soil organic matter, and their impact on carbon storage, we used sand microcosms to control for external environmental factors such as changes in temperature and moisture as well as the variability in available carbon that exist in soil cores. Using Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) on microcosm samples from early phase litter decomposition, we found that protein- and tannin-like compounds exhibited the strongest correlation to dissolved organic carbon (DOC) concentration. Proteins correlated positively with DOC concentration, while tannins correlated negatively with DOC. Through random forest, neural network, and indicator species analyses, we identified 42 bacterial and 9 fungal taxa associated with DOC concentration. The majority of bacterial taxa (26 out of 42 taxa) belonged to the phylum Proteobacteria while all fungal taxa belonged to the phylum Ascomycota. Additionally, we identified significant connections between microorganisms and protein-like compounds and found that most taxa (12/14) correlated negatively with proteins indicating that microbial consumption of proteins is likely a significant driver of DOC concentration. This research links DOC concentration with microbial production and/or decomposition of specific metabolites to improve our understanding of microbial metabolism and carbon persistence.

Keywords: DOC; FTICR mass spectrometry; bacteria; fungi; metabolites; microbial communities.

FIGURE 1

Biplot analysis indicates that high and low DOC groups are enriched with different FTICR compound classes (PERMANOVA, F = 46.46, R² = 0.27, P = 0.001; ANOSIM, R = 0.45, P = 0.001). Ellipses indicate 95% confidence intervals (n = 125 samples).

FIGURE 2

The DOC pool is chemically diverse, and the high and low DOC groups contain distinct compounds. Van Krevelen plots of compounds found in all samples categorized by compound class (A) and compounds found in high DOC, low DOC, and both DOC groups (B).

FIGURE 3

Proteins and tannins are the compound classes most strongly correlated with DOC concentration. Spearman correlation coefficients (R), R²-values, and p-values are shown.

FIGURE 4

The majority of bacterial OTUs that are associated with high or low DOC are negatively correlated with protein. Stacked barplots indicate the number of bacterial OTUs that correlated negatively (left barplots) or positively with protein (right barplots) and their association with either high or low DOC based on indicator species analysis is shown at (A) phyla, (B) class, and (C) order levels.

FIGURE 5

Network diagram demonstrating that interactions between microbial taxa, proteins, and DOC are in accordance with the machine-learning assignments for microorganisms in terms of DOC concentration. Borders around taxa indicate whether they are associated with high DOC (red) or low DOC (blue). Bacterial taxa are indicated by rectangular borders and fungal taxa are indicated by oval borders. Black borders indicate DOC and protein compounds.