Genomic Science Program
U.S. Department of Energy | Office of Science | Biological and Environmental Research Program

Model Communities of Soil Microbiomes Reveal Details of Carbon-Use Efficiencies and Interkingdom Interactions Across Scales

Authors:

Ryan McClure1* (Ryan.mcclure@pnnl.gov), Marci Garcia1, Erin Bredeweg1, Josue Rodriguez- Ramos1, Natalie Sadler1, Sneha Couvillion1, Daisy Herrera1, Sharon Zhao1, Robert Danczak1, Yuliya Farris1, Kirsten S. Hofmockel1,2

Institutions:

1Biological Sciences Division, Pacific Northwest National Laboratory; 2Department of Agronomy, Iowa State University–Ames

URLs:

Goals

Pacific Northwest National Laboratory’s Phenotypic Response of Soil Microbiomes Science Focus Area aims to achieve a systems-level understanding of the soil microbiome’s phenotypic response to changing moisture. Researchers perform multiscale examinations of molecular and ecological interactions occurring within and between members of microbial consortia during organic carbon (C) decomposition, using chitin as a model compound. Integrated experiments address spatial and interkingdom interactions among bacteria, fungi, viruses, and plants that regulate community functions throughout the soil profile. Data are used to parametrize individual- and population-based models for predicting interspecies and interkingdom interactions. Lab and field experiments test predictions to reveal individual and community microbial phenotypes. Knowledge gained provides a fundamental understanding of how soil microbes interact to decompose and sequester organic C and enables prediction of how biochemical reaction networks shift in response to changing moisture regimes.

Abstract

The fate of soil organic C depends in part on how efficiently bacteria and fungi incorporate C into biomass. Higher fungal: bacterial ratios in soil microbiomes have been associated with lower C-use efficiencies (CUE), and CUE is also sensitive to environmental factors, including C source (Soares 2019; Ullah et al. 2021). Therefore, understanding both CUE and interkingdom interactions, and how they affect one another, is key to a complete understanding of the soil ecosystem. However, as these systems are incredibly complex, direct analysis is often difficult. In this project, researchers use a model community of bacterial species, Model Soil Consortium – 2 (MSC-2) to explore how CUE is affected by different experimental growth conditions under four different C sources (N-acetylglucosamine, trehalose, chitin and carboxymethylcellulose; McClure et al. 2022). Researchers show that faster growth (determined via cell counting) does not always reflect high CUE, and that, in certain cases, CUE values are the highest in conditions causing slower or stagnant growth. The team also found that under growth conditions with shaking, vitamin and mineral deficiency led to slower growth and lower CUE that was dependent on the specific C sources. This suggests that factors that can limit growth (such as lack of key vitamins) are not always the rate-limiting step if another factor (complex C) is present. Identifying a rate-limiting factor can be difficult but the use of model communities helps by discovering paradigms that can be applied to more complex systems.

Researchers extended the successful model community analysis by increasing the complexity to the interkingdom level through the addition of a fungal partner, Fusarium oxysporum, and the structural complexity by using glass beads in a spatially structured soil habitat. The team found that the respiration of bacterial and fungal partners is greatly increased when cultured together vs. separately, revealing interkingdom interactions that can positively affect community metabolism. Researchers are expanding this work through the development of a Microbial Rhizosphere Community (MRC-1), a community of cocultured bacteria and fungi that will be key to future analysis of how CUE is affected by fungal: bacterial ratios and interactions.

In parallel, researchers are evaluating soils from the Tall Wheatgrass Irrigation Field Trials in Prosser, WA. The team generated 13 metagenome samples from fungal floats of field soil from which 333 metagenome-assembled genomes (MAGs) have been derived. These MAGs represent microorganisms, predominantly bacteria, associated with the fungal hyphosphere. Several novel genera were identified, some containing metabolic pathways for the degradation of complex C substances like chitin, cellulose, and starches, which may aid survival in the hyphosphere ecosystem.

The work presented here illuminates several potential crosskingdom interaction events across scales of complexity (soil analogous laboratory systems and field experiments). Future experiments in this area will explore how interactions between species, an approach made simpler with the defined MSC-2 community where species can be removed or added easily, drive CUE. Researchers also propose to use these findings to design and implement experiments that test hypotheses generated in controlled laboratory systems in native field environments so that it can be determined whether and to what degree CUE findings scale across systems.

References

McClure, R., et al. 2022. “Interaction Networks are Driven by Community-Responsive Phenotypes in a Chitin-Degrading Consortium of Soil Microbes,” Msystems 7, e00372-00322.

Soares, M., and J. Rousk. 2019. “Microbial Growth and Carbon Use Efficiency in Soil: Links to Fungal-Bacterial Dominance, SOC-Quality and Stoichiometry,” Soil Biology and Biochemistry 131,195–205.

Ullah, M. R., et al. 2021. “Drought-Induced and Seasonal Variation in Carbon Use Efficiency is Associated with Fungi: Bacteria Ratio and Enzyme Production in a Grassland Ecosystem,” Soil Biology and Biochemistry 155,108159.

Funding Information

Pacific Northwest National Laboratory is a multiprogram national laboratory operated by Battelle for the DOE under contract no. DE-AC05-76RLO 1830. This program is supported by the DOE, Office of Science, through the Genomic Science Program, BER program, under FWP 70880. A portion of the metagenomic data was provided by the DOE Joint Genome Institute through project BERSS 508623.