A platform that sheds light on how the microbiome is formed, how it changes over time, and how it is affected by disturbances like antibiotics has been developed by Ophelia Venturelli, a biochemistry professor at the University of Wisconsin-Madison. Details on the model were published last week in Molecular Systems Biology.
"We know very little about the ecological interactions of the gut microbiome," Venturelli says. "Many studies have focused on cataloging all of the microbes present, which is very useful, but we wanted to try to understand the rules governing their assembly into communities, how stability is achieved, and how they respond to perturbations as well."
By learning these rules, researchers say they can better predict interactions between microbes using computational tools instead of performing laborious and time-consuming laboratory experiments. The data can also start to answer questions about how pathogens cause damage when they invade communities, and how to prevent it.
For the study, the researchers chose 12 bacterial types present in the human gut. The researchers fed data about the pairwise interactions, along with data on each individual species, into a dynamic model to decipher how all of the bacteria would likely interact when combined. They found the pairwise data alone was sufficient to predict how the larger community assembles.
"This model allows us to better understand and make predictions about the gut microbiome with fewer measurements," Venturelli explains. "We don't need to measure every single possible community of, say, three, four or five of a set of species. We just need to measure all the pairs, which still represents a very large number, to be able to predict the dynamics of the whole gut."
"Without a model, we are basically just blindly testing things without really knowing what we are doing and what the consequences are when we are, for example, trying to design an intervention," she says. "Having a model is a first step toward being able to manipulate the gut ecosystem in a way that can benefit human health."