Just like any living organism, the soil has its own metabolism. Plants, worms, insects, and most importantly, microorganisms in the soil, break down organic matter, consume and generate nutrients, and process other materials to give the soil a life of its own. Soil microbiomes, which drive much of the metabolism in these ecosystems, are immensely complex – comprised of thousands of species with untold interactions and dynamics.
Given the complexity of the soil, however, it can be nearly impossible to understand how the communities of microbes living there respond to changes in the environment, such as temperature, moisture, acidity, and nutrient availability. Solving this problem is critical if we want to understand how soil microbiomes adapt to ever-changing environmental conditions and climate change.
New research from the University of Chicago shows that a deceptively simple mathematical model can describe how the soil responds to environmental change. Using just two variables, the model shows that changes in pH levels consistently result in three distinct metabolic states of the community.
The study, published this week in Nature, highlights how describing the collective behavior of complex systems mathematically can cut through the complexity, enabling predictions of how the soil and its metabolism will respond to change. Ultimately, this will help scientists design interventions for improving agriculture or restoring ecosystems.
"When people think about these ecosystems, they assume you have to write down a mathematical description of the entire system, which involves thousands of variables, interacting species, and the resources they're consuming," said Seppe Kuehn, PhD, Associate Professor of Ecology and Evolution at the University of Chicago, and the senior author of the paper. "So, the fact that we were able to describe this in a simple way was extremely intellectually satisfying."
A herculean effort to analyze the soil
The study is the result of a herculean effort by Kiseok Lee, a graduate student in Kuehn's lab. He sampled 20 natural soils across the pH gradient from Cook Agronomy Farm in Pullman, Washington, that have large natural variations in pH but few differences in other environmental factors. Then, he manipulated each native soil's pH by small increments in the lab, resulting in 1,500 microcosm experiments.
The pH level is a measure of the concentration of hydrogen ions in a solution. Lower pH means more acidic (more hydrogen ions), and higher pH means more basic or alkaline (fewer hydrogen ions).
Levels of pH in the soil are important because they affect the types of microorganisms living there, their metabolic activity, and the soil's chemistry. The researchers wanted to test the effects of changing pH on anaerobic nitrate respiration, which is the process by which anaerobic microbes (i.e. ones that don't require oxygen) use nitrate to generate energy. Nitrate respiration is a key metabolic process in agriculture and soil health.
Lee painstakingly placed samples onto plates, each with 48 wells for holding the soil, along with some water, nitrates, and acid or base solution to change the pH. Preparing and incubating the samples took months. After that, Lee took time-series measurements of nitrate in each microcosm—a total of 15,000 measurements, all by hand. "I was the machine," Lee said, when asked if he was able to automate any of the sampling and testing.
Deceptively simple modeling
Lee and Kuehn worked with Siqi Liu, PhD, co-first author and a former graduate student in the lab of study co-corresponding author Madhav Mani, PhD, Associate Professor of Engineering Sciences and Applied Mathematics at Northwestern University, along with co-corresponding author Mikhail Tikhonov, PhD, Associate Professor of Physics at Washington University in St. Louis.
The team created a model to describe the dynamics in each of the 1,500 samples as they metabolized the nitrate. They found that a simple model predicted the activity with just two parameters: indigenous biomass activity and the amount of growth-limiting nutrient available. Depending on how the pH was changed, they saw three consistent results:
- Regime I, or the "acidic death regime": Large changes toward acidity caused the death of functional biomass
- Regime II, "nutrient-limiting regime": During moderate changes, acidic or basic, the nitrate metabolism was limited by the availability of a limiting nutrient (carbon), resulting in linear nitrate dynamics
- Regime III, "resurgent growth regime": Large changes toward basic conditions caused dominant groups of microbes to become less active, while rare groups rapidly grew and metabolized nitrate exponentially
"No matter how you perturb the pH, there's just these three dynamic classes of behavior that the whole ecosystem can exhibit. Outside of that, it doesn't look like anything else is allowed," Kuehn said. "That's really quite striking, because you have all this complexity at the lower level giving rise to this relative simplicity at the higher level."
"This connects to an important theoretical question: when is it OK to summarize dozens of diverse species with a single coarse model?" Tikhonov said. "Here, Kiseok and Siqi managed to show that a coarsened description is not only an excellent approximation of the data but captures something general about community response to perturbations."
Putting the new model to use
Understanding how the soil microbiome responds to these changes is useful for designing interventions. For example, if nitrogen fertilizer runoff from farms contaminates nearby waterways, officials could take measures to increase pH and remove excess nitrate to prevent algae blooms.
"If you want to understand how these systems are going to respond to future perturbations, then delimiting the set of possible responses is obviously very useful," Kuehn said.
The researchers also think the same modeling approach can be applied to other environmental factors.
"Focusing on the resilience of the community, which is expressed by biomass activity and the limiting nutrient, shows us that different amounts of perturbations will elicit different effects," Lee said. "I think this means that we can apply it to elucidating functional responses in other microbial systems against different environmental changes, whether it be from temperature, pH, salinity, or something else."
The study, "Functional regimes define soil microbiome response to environmental change," was supported by the National Science Foundation, the National Institute for General Medical Sciences, the Center for Living Systems at UChicago, the National Institute for Mathematics and Theory in Biology, the Simons Foundation, and the Chan-Zuckerberg Initiative. Additional authors include Kyle Crocker and Jocelyn Wang from UChicago and David Huggins from the United States Department of Agriculture.
