Human fecal metabolomic profiling could inform Clostridioides difficile infection diagnosis and treatment

Abstract

Clostridioides difficile is a significant public health threat, and diagnosis of this infection is challenging due to a lack of sensitivity in current diagnostic testing. In this issue of the JCI, Robinson et al. use a logistic regression model based on the fecal metabolome that is able to distinguish between patients with non-C. difficile diarrhea and C. difficile infection, and to some degree, patients who are asymptomatically colonized with C. difficile. The authors construct a metabolic definition of human C. difficile infection, which could improve diagnostic accuracy and aid in the development of targeted therapeutics against this pathogen.