The Regional Landscape of the Human Colon Culturome in Health and Cystic Fibrosis

Abstract

Cystic fibrosis (CF) alters gut physiology, yet its impact on microbial communities across colonic regions (ascending, transverse, descending colon) and microhabitats (lumen, mucosa) remains incompletely understood. Here, we applied culturomics to characterize gut microbiota in 32 individuals (22 nonCF, 10 CF). Persons with CF (pwCF) exhibited significantly higher viable bacterial loads than nonCF individuals, particularly in mucosal samples. Anaerobes predominated overall, with relative enrichment of aerobes in the mucosa of pwCF. Alpha diversity was reduced in mucosal samples and aerobic cultures for pwCF, whereas beta diversity was influenced by all the tested variables except the colonic region. Phylum-level analyses revealed enrichment of Proteobacteria and depletion of Actinobacteria, Bacteroidota, and Firmicutes in samples from pwCF, consistent with stool analysis. Random forest models identified selected oral-associated microbes as key predictive taxa and accurately classified polyp status with very high accuracy. Whole-genome sequencing of Bacteroides fragilis (n=21) and Escherichia coli (n=15) isolates, representing a subset of 109 gut bacterial genomes sequenced from this cohort, revealed minimal genomic variation across colonic regions and sample types, indicating intra-individual strain stability. The understandings from this pilot culturome study may help in developing targeted microbial therapeutic approaches to address the gut dysbiosis of CF. ImportanceThis pilot study represents the first culturome analysis of the cystic fibrosis colon. Our preliminary findings demonstrate that CF-associated gut dysbiosis is spatially specific, with mucosal bacterial communities showing pronounced alterations while luminal communities remain unchanged. This spatial specificity suggests the mucosal microenvironment as a potential therapeutic target and indicates that interventions focused solely on luminal bacteria may be insufficient. The promising predictive accuracy of culturome-based machine learning models in this small cohort suggests these viable bacterial signatures could serve as biomarkers for CF management pending larger validation studies. Additionally, our initial observations of complex CFTR modulator effects on gut microbial communities provide insights for future studies optimizing combination therapies.