Cytometric fingerprints of gut microbiota predict Crohn’s disease state

Abstract

Variations in the gut microbiome have been associated with changes in health state such as Crohns disease. Most surveys characterize the microbiome through analysis of the 16S rRNA gene. An alternative technology that can be used is flow cytometry. In this report we analyzed a disease cohort that has been characterized by both technologies. Changes in microbial community structure are reflected in both types of data. We demonstrate that cytometric fingerprints can be used as a diagnostic tool in order to classify samples according to Crohns disease state. These results highlight the potential of flow cytometry to perform rapid diagnostics of microbiome-associated diseases.