Carl R. Woese Institute for Genomic Biology

Depending on others for something you need may feel like a risky proposition—and perhaps a human one. It is actually a survival strategy found in the microbial world, and far more frequently than one might expect. Discovering why is key to understanding how microbes form stable communities across medical, industrial, and ecological settings.

A new study by bioengineering professor Sergei Maslov (CAIM co-leader), computational scientist Ashish George, and biology professor Tong Wang explores why interdependence can be such a winning move for microbial communities. Their work, published this week in Cell Systems , demonstrated that a mathematical model of how bacteria produce and share resources accurately predicted the outcome of experiments with living E. coli strains.

The researchers’ collaboration began during their time as colleagues at the Carl R. Woese Institute for Genomic Biology at the University of Illinois Urbana-Champaign. George continued the collaboration in his position at the Broad Institute; Wang, in his appointment at Purdue University. Maslov, who led the study, remains at Illinois and is an affiliate member of the National Institute for Theory and Mathematics in Biology, which supported the research in part. The National Science Foundation and the Simons Foundation also provided support for the study.

“Microbes rarely live in isolation. They actually live in communities just like humans,” Wang said to explain their inspiration for embarking on the study. “We wanted to establish a mathematical model to try to capture how they trade essential nutrients, and eventually what kind of community they will be able to assemble due to their cooperative interactions.”

Maslov and Wang were focused in particular on auxotrophs—microbes that are missing the capability to make one or several essential nutrients, often amino acids, which they must instead absorb from their environment. Auxotrophy seems at first glance like a weakness. The cell’s survival is dependent upon its surroundings, and most often its neighbors. Yet auxotrophs are not a rare occurrence; they are commonly found in microbial communities.

“Previous studies seem to show that when a community has more auxotrophic species, it seems to be more stable, and these communities are actually pretty prevalent,” Wang said. "So another reason why we want to establish this type of model is to answer: why are there so many auxotrophic species, and what's their connection with ecological stability?”

Other research groups have explored, through laboratory experiments and a mathematical model only based on pairwise species-species interactions, how auxotrophs can remain a functioning part of communities by focusing on how two types of auxotrophs might pair up—each one supplying a resource the other needs. The experimental dynamic is intriguing, but the model can’t fully portray microbial cooperation accurately, failing to predict how interdependencies develop across a whole community of 14 members with many different nutrients to share or consume.

The research team wanted a mathematical model that could describe in numbers how the interplay across a whole community of multiple types of microbes might develop. Based on the established model, they derived two key ecological principles.

“One principle is that we have to balance all the fluxes. Let's make sure that everything that is being generated, all the amino acids being generated by the community, is consumed by somebody in the community, so nothing is left,” Maslov said. “The second one is, let's make sure that, for every species, there is actually something that limits its growth, because if nothing is limiting your growth, you will be growing exponentially and eventually you will take over . . . so we explored in this model how we can simultaneously balance fluxes, and make sure that all the species have their unique limiting resource and they can all coexist because they are fighting for different things.”

Their model’s results showed how the presence of auxotrophs can make a community more stable in the face of environmental fluctuations, because collectively, their network of interdependent production and consumption is more self-sufficient. In addition, once a group has formed, it is difficult for other microbes to “invade” unless their own nutrient requirements fit into the established group dynamic. 

To test their model, the researchers applied their model to predict the outcome of a past study from another group that combined 14 lab-created auxotroph strains of E. coli. In that study, four strains survived to form a stable community. The present model was able to correctly predict the identities of three of the four strains, a marked improvement over past modeling efforts. 

From here, Tong and Maslov plan to apply the new modeling approach to a variety of real-world conditions, such as understanding the communities of bacteria and other microbes that live in and on our bodies and impact our health. 

“We would like to study community assembly and try to explain some of the patterns of the human gut microbiome, why some species tend to sort of coexist together,” Tong said.  “Maybe they are complementary to each other regarding the generation of different amino acids, or even including other essential resources like vitamins. That's actually one of the applications we can imagine.”