High-resolution temporal profiling reveals synchronized dynamics of the mouse gut microbiome

Abstract

Background The gut microbiome undergoes diurnal oscillations entrained by host circadian rhythms and feeding behavior, and disruption of these oscillations has been linked to metabolic dysfunction. However, the temporal organization of microbial activity within these oscillatory cycles remains poorly understood, largely because conventional sampling approaches lack the temporal resolution needed to resolve rapid microbial dynamics. Results To address this gap, we developed a fully automated fecal collection system that enables continuous sampling from individual mice at minute- to hour-scale resolution without manual intervention. Using this platform, we collected fecal samples at hourly intervals over 14 consecutive days from individually housed mice. To reconstruct genome- and function-level trajectories from these data, we developed a cost-effective method (GORIN) that combines full-length 16S rRNA gene amplicon sequencing with long-read metagenomic references. Applying a newly developed phase-analytic method (NPPD) to determine the instantaneous phase of each genome and functional gene, we found that the gut microbiota is organized into two phase-coherent groups corresponding to the light and dark phases of the host circadian cycle. These two groups differed in gene content, suggesting distinct carbohydrate utilization strategies, with the light-phase community enriched in mucosal glycan-degrading enzymes, whereas the dark-phase community was enriched in carbon storage metabolism and motility-related functions. Within each phase, microbial taxa and functional genes displayed reproducible temporal succession across individual mice. Perturbations, including cage transfer and antibiotic treatment transiently disrupted phase synchronization, as measured by the phase order parameter, followed by gradual recovery of phase coherence. Conclusions These findings reveal reproducible phase-synchronized temporal organization in the mouse gut microbiome, with community-level phase relationships that can be quantified and tracked over time and following perturbation. The automated sampling platform, genome-resolved profiling framework, and phase-analytic metrics introduced here provide a scalable strategy for characterizing community-level temporal dynamics in host-associated microbial ecosystems, with potential applications for understanding how disruption of microbial temporal organization contributes to dysbiosis.