How Soils Work
Authors:
Peter F. Chuckran4* ([email protected]), Paul Dijkstra1, Steven J. Blazewicz2, Bruce A. Hungate1, Egbert Schwartz1, Hannah S. Butler Robbins1, Rebecca Mau1, Alicia M. Purcell1,3, Natasja van Gestel3, Linnea K. Honeker2, Rina Estera-Molina2, Megan Foley1, Noah Sokol2, Erin Nuccio2, Mary Firestone4, Mike Allen2, Jennifer Pett-Ridge2,5
Institutions:
1Center for Ecosystem Science and Society, Northern Arizona University; 2Physical and Life Sciences Directorate, Lawrence Livermore National Laboratory; 3Department of Biological Sciences, Texas Tech University; 4Department of Environmental Science, Policy, and Management, University of California–Berkeley; 5Life and Environmental Sciences Department, University of California–Merced
URLs:
Goals
Microorganisms play key roles in soil carbon (C) turnover and stabilization of persistent organic matter via their metabolic activities, cellular biochemistry, and extracellular products. Microbial residues are the primary ingredients in soil organic matter, a pool critical to Earth’s soil health and climate. The project hypothesizes that microbial cellular chemistry, functional potential, and ecophysiology fundamentally shape soil C persistence, and the team is characterizing this via stable isotope probing of genome-resolved metagenomes and viromes. The project focuses on soil moisture as a “master controller” of microbial activity and mortality, since altered precipitation regimes are predicted across the temperate United States. The Science Focus Area’s (SFA) ultimate goal is to determine how microbial soil ecophysiology, population dynamics, and microbe-mineral-organic matter interactions regulate the persistence of microbial residues under changing moisture regimes.
Abstract
Ecophysiology and community ecology are natural stops on the road from genes to ecosystems, are central to understanding how microbes function, respond to substrate availability and environmental changes, release carbon dioxide, consume and produce soil organic matter, and are essential to develop a molecular and mechanistic understanding of microbes’ roles in soil C cycling.
Metatranscriptomics is a powerful and relatively new tool to study soil communities. However, the vast number of genes and transcripts and the complexity of their functions and regulation often limit a straightforward interpretation, making it difficult to draw clear conclusions from experiments conducted in natural soils. Instead of a whole transcriptome analysis, the project advocates a modular approach to study ecophysiology and community ecology of wild soil microbial communities. Each module consists of sets of genes related to specific ecophysiological (e.g., starvation responses) or community ecological (e.g., trophic dynamics) functions, founded on expert knowledge, applied, criticized, improved, and expanded by researchers using cross-ecosystem comparisons.
As an illustration, the team has analyzed four metatranscriptome datasets to answer the following research questions.
- It is often assumed that soil microbes spend most of their existence in a state of starvation with high-maintenance energy demand, where substrate is used only for energy production (Hagerty et al. 2018). Is there evidence that transcription of energy production and biosynthesis varies?
- Although microbes are mostly C-limited, low availability of inorganic nutrients may restrict microbial activity when excess organic C is available. In response to nutrient limitations, microbial cells increase transcription of transporters for the most limiting nutrient (Ishige et al. 2003; Silberbach et al. 2005). Do researchers see signs of inorganic nutrient limitations in metatranscriptome datasets?
- Bacteria form biofilms, consisting of extracellular polysaccharides mixed with lipids, proteins, and DNA. These biofilms protect the encapsulated cells, facilitate their survival, and may have an important role in soil organic matter formation. Can researchers use metatranscriptomes to study when and where biofilms are being produced?
- Using metatranscriptomes, can researchers detect the influence of carbohydrates on microbial metabolism by looking at gene expression associated with glycolysis versus gluconeogenesis?
In addition to being waystations towards a mechanistic perspective of ecosystems, ecophysiology can be a research target by itself.
- Can researchers use metatranscriptomes to study the molecular mechanisms of regulation of growth and starvation in soil microbial communities?
The experiments compared consist of a glucose addition; a water addition after a seasonal drought; a warming by time-since-deglaciation experiment in Antarctica; and a comparison between bulk, detritosphere, and rhizosphere communities.
Results show that transcript abundances for biosynthesis are mostly proportional to transcript abundances for energy production; high transcript abundances for nitrogen and phosphate transporters indicate short periods of nutrient limitations; and temporally and spatially explicit patterns of growth and biofilm production suggest that progress can be made to resolve questions relating soil organic matter formation and microbial activities.
Overall, the project signals a growing need for biochemical and cell physiological expertise within soil ecology.
References
Hagerty, S. B., et al. 2018. “Evaluating Soil Microbial Carbon Use Efficiency Explicitly as a Function of Cellular Processes: Implications for Measurements and Models,” Biogeochemistry 140, 269–83.
Ishige, T., et al. 2003. “The Phosphate Starvation Stimulon of Corynebacterium glutamicum Determined by DNA Microarray Analyses,” Journal of Bacteriology 185, 4519–29.
Silberbach, M., et al. 2005. “DNA Microarray Analysis of the Nitrogen Starvation Response of Corynebacterium glutamicum,” Journal of Bacteriology 119, 357–67.
Funding Information
This research is based upon work of the Lawrence Livermore National Laboratory (LLNL) “Microbes Persist” Soil Microbiome SFA, supported by the U.S. DOE Office of Science, BER program’s GSP under Award Number SCW1632 to LLNL and subcontracts to the Northern Arizona University. Work at LLNL was performed under U.S. DOE Contract DE-AC52-07NA27344. Work associated with the glucose addition experiment was partly funded by the U.S. Department of Agriculture National Institute of Food and Agriculture Foundational Program (award number 2017-67019-26396), while the Antarctic experiment was funded by National Science Foundation Office of Polar Programs award number 1947562. All sequencing was conducted by the U.S. DOE Joint Genome Institute, a DOE Office of Science User Facility and supported under contract DE-AC02-05CH11231.