Institute for Systems Biology (ISB) researchers are using personalized models to forecast gut colonization risk and test targeted probiotic therapies. Pathogen Clostridioides difficile (C. diff) infects more than 500,000 people in the United States each year and kills up to 30,000. It is a leading cause of health care-associated infections, particularly in hospitals and long term care facilities. But not everyone who harbors C. diff gets sick—as many as 30% to 40% of the population are carrying this bug right now in their gastrointestinal tract.
C. diff is what scientists call an opportunistic pathogen—capable of causing life-threatening illness, but also capable of existing quietly as a commensal organism in the gut—waiting for the right moment, like after a round of antibiotics, to wreak havoc.
What if we could identify the risk before infection takes hold?
In a new study published in Cell Systems, researchers from ISB have developed a powerful, personalized modeling framework to predict whether C diff is likely to colonize an individual’s gut, and to test whether specific probiotic therapies might prevent and/or reverse that colonization.
“C diff is an opportunist. It can lie in wait in the gut, living benignly, ready to cause disease when conditions allow. If we remove the opportunity, we neutralize the threat,” said Dr. Sean Gibbons, senior author and associate professor at ISB. “Instead of reacting to disease, this gives us a path to prevent it before it starts.”
The team used microbial community–scale metabolic models, developed at ISB by cosenior author Christian Diener, PhD (now an assistant professor at the Medical University of Graz), to simulate how C. diff might behave in more than 15,000 human gut microbiome samples. The models identified three colonization states—high growth, moderate growth, and no growth—based on the unique microbial and metabolic composition of each gut environment.
Using C. diff invasion experiments in synthetic lab-based communities of human gut bacteria, the researchers found that they could accurately predict which communities were susceptible and which were resistant. In addition, they showed that they could accurately predict C. diff colonization in human time series with known C. diff colonization dynamics and in recurrent C. diff infection patients before and after receiving fecal transplants.
To better understand the mechanisms of C. diff suppression, they showed that a defined probiotic cocktail (known to resolve recurrent C. diff infections) suppresses C. diff growth by outcompeting it for key metabolites—such as succinate (a dicarboxylic acid), trehalose (a sugar), and ornithine (an amino acid byproduct)—that fuel C. diff’s expansion.
They also found that the probiotic cocktail was better at suppressing model-predicted C. diff growth in the context of certain microbiota, but not in others, revealing responders and nonresponders. By looking at model outputs from naturally resistant microbiota, the authors found that including dominant gram-negative anaerobic genera, like Phocaecola, in the simulated probiotic cocktail further improved model-predicted C. diff growth suppression. These results suggest that personalized, model-predicted probiotics could improve C. diff suppression and reduce the rate of nonresponders.
“This work moves us closer to precision probiotics and tailored interventions that account for each person’s gut ecosystem,” says Alex Carr, PhD, lead author of the paper and a postdoctoral fellow in ISB’s Gibbons Lab. “The ultimate goal is to decolonize opportunists like C. diff before they cause harm.”
The findings have immediate implications for reducing C. diff infections and longer-term potential for proactively managing other opportunistic pathogens. They also offer a blueprint for designing smarter, more targeted probiotic therapies that are personalized to each patient’s gut microbiome, although these model-guided interventions will need to be tested in human trials.
“Rather than just flooding the gut with microbes and hoping for the best, we can now use models to match the right probiotic to the right person,” Gibbons says. “It’s a systems biology approach to rationally engineering gut microbiome function, and we think that it has enormous promise for improving the efficacy of microbiome-mediated therapies.”
— Source: Institute for Systems Biology