Can We Predict and Prevent C difficile Colonization?

Sean Gibbons, PhD

Image credits: ISB

Asymptomatic colonization by Clostridioides difficile (C difficile) occurs in up to 40% of healthy adults, but predicting who might go on to develop infection remains a challenge. A new study led by Sean Gibbons, PhD, associate professor at the Institute for Systems Biology (ISB), introduces a powerful computational tool to do just that.

Using microbial community-scale metabolic models (MCMMs), Gibbons and colleagues analyzed gut microbiome data from over 15,000 individuals to predict colonization risk, and assess how targeted probiotics might help prevent infection before it starts.

In an email interview, we spoke with Gibbons about the implications of this research, and how MCMMs might change how we approach C difficile prevention in the future.

Contagion: Your study introduces MCMMs as a tool to predict individual-specific C difficile colonization risk. How do you envision this model being integrated into clinical workflows or screening protocols in the near future?

Gibbons: This study was pre-clinical. We were applying MCMMs retrospectively to existing data sets. We would want some additional validation of the predictions before integrating this workflow into clinical practice. For example, we would like to see whether or not our model could predict responders and non-responders to probiotic therapies designed to treat recurrent C diff. These kinds of data do exist, from clinical trials, but we haven't yet gotten access to them. If we see sufficient validation, then we would work towards an observational study, where we test our predictions prospectively in a clinical cohort. If that worked out, then we'd move towards an intervention framework, where we used the model to target high risk patients for intervention and prevention of infection. It's a long path towards translation into the clinic, and our current study represents the first step along that path.

You identified three distinct metabolic niches that allow C difficile to persist. What are the implications of this metabolic flexibility for treatment strategies, especially in patients without active infection?

Gibbons: The implication is that C diff can persist in the guts of many people as a commensal using different growth strategies. This means that interventions that may work for one person to help decolonize them of C diff may not work well in another person. The niche-flexibility of C diff shows us that personalized prebiotic, dietary, and/or probiotic interventions may be necessary to rescue non-responders to existing therapies. MCMMs are tools that enable this kind of personalization.

Your findings suggest that targeted probiotics may effectively suppress C difficile through metabolic competition. What are the next steps for translating this concept into a clinically viable alternative to fecal microbiota transplantation (FMT)?

Gibbons: We will need some additional validation data from retrospective trial diata or from prospective human observational cohorts, and possibly some animal studies (eg, interventions tested in mice) before we would move into human intervention trials. Even if the data look good, the regulatory landscape for personalized interventions is complex, so there may be some hurdles to overcome before we can routinely implement these kinds of therapies in the clinic. It's a long road, but we're committed to pushing these advances forward.

Given that colonization without symptoms is common, how might your research reshape how clinicians think about the line between colonization and infection—and the need for early intervention?

Gibbons: While hospital-acquired C diff infections are on the decline, community-acquired infections are rising. This is due, in part, to high rates of asymptomatic carriage of C diff. We actually think that it might be possible to prevent or reverse asymptomatic carriage of C diff across the population using precision prebiotic, dietary, and probiotic interventions. If we can prevent C diff carriage, we will stop these opportunistic infections before they have a chance to start. This kind of approach could be applied to other opportunistic pathogens as well.

As our understanding of the gut microbiome deepens, tools like MCMMs offer a promising path toward personalized prevention strategies for C difficile and other opportunistic infections. While clinical application is still on the horizon, this research marks an important first step in shifting the focus from treatment to early, targeted intervention.

Reference

Carr AV, Baliga NS, Diener C, Gibbons SM. Personalized Clostridioides difficile colonization risk prediction and probiotic therapy assessment in the human gut. Cell Syst. 2025;101367. doi:10.1016/j.cels.2025.101367