Circadian rhythms govern glucose homeostasis, and their dysregulation leads to complex metabolic diseases. Gut microbes exhibit diurnal rhythms that influence host circadian networks and metabolic processes, yet underlying mechanisms remain elusive. Here, we showed hierarchical, bidirectional communication among the liver circadian clock, gut microbes, and glucose homeostasis in mice. To assess this relationship, we utilized mice with liver-specific deletion of the core circadian clock gene Bmal1 via Albumin-cre maintained in either conventional or germ-free housing conditions. The liver clock, but not the forebrain clock, required gut microbes to drive glucose clearance and gluconeogenesis. Liver clock dysfunctionality expanded proportions and abundances of oscillating microbial features by 2-fold relative to that in controls. The liver clock was the primary driver of differential and rhythmic hepatic expression of glucose and fatty acid metabolic pathways. Absent the liver clock, gut microbes provided secondary cues that dampened these rhythms, resulting in reduced lipid fuel utilization relative to carbohydrates. All together, the liver clock transduced signals from gut microbes that were necessary for regulating glucose and lipid metabolism and meeting energy demands over 24 hours.
Katya Frazier, Sumeed Manzoor, Katherine Carroll, Orlando DeLeon, Sawako Miyoshi, Jun Miyoshi, Marissa St. George, Alan Tan, Evan A. Chrisler, Mariko Izumo, Joseph S. Takahashi, Mrinalini C. Rao, Vanessa A. Leone, Eugene B. Chang
Usage data is cumulative from December 2023 through December 2024.
Usage | JCI | PMC |
---|---|---|
Text version | 1,723 | 792 |
277 | 242 | |
Figure | 692 | 9 |
Table | 42 | 0 |
Supplemental data | 127 | 15 |
Citation downloads | 94 | 0 |
Totals | 2,955 | 1,058 |
Total Views | 4,013 |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.