模拟轮班作息扰乱小鼠昼夜节律与行为

Shift work has become a major cause of circadian rhythm disruption in modern society. This study investigated the systemic consequences of shift schedules by subjecting mice to different light-dark (LD) cycles: non-24-h cycles (rapidly rotating groups A and B ) and 24-h cycles ( group C and control group). We performed behavioral tests, serum hormone measurements, transcriptomic analysis of suprachiasmatic nucleus (SCN) genes, and gut microbiome analysis. The results showed that the mice exhibited significant body weight gain after altering LD cycle compared with the control group. In groups exposed to non-24-h cycles, the circadian expression rhythms of core clock genes ( Per , Cry , and Bmal1 ) in the SCN were lost. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses revealed that genes in the SCN losing rhythmicity were significantly enriched in metabolic and regulatory pathways, disrupting endocrine and metabolic rhythms and ultimately compromising health. The circadian rhythms of key hormones like melatonin and dopamine were also lost. Concurrently, these central disruptions drove peripheral pathology, including gut microbiota dysbiosis (altered Firmicutes/Bacteroidota ratio, reduced Verrucomicrobia) and a profound loss of gut microbial diurnal oscillations. Behaviorally, this multisystem discord manifested as significantly increased anxiety-like and depression-like behaviors and fatigue ( P NEW & NOTEWORTHY Systematic comparison of multiple simulated shift schedules in mice reveals that non-24-h light-dark cycles, but not fixed 24-h shifted cycles, abolish suprachiasmatic nucleus core clock gene ( Per , Cry , Bmal1 ) rhythms, disrupt melatonin and dopamine, and desynchronize gut microbiota at the phylum level. These central and peripheral disruptions selectively exacerbate anxiety- and depression-like behaviors without impairing spatial memory, revealing a hierarchical disintegration of circadian organization. The findings provide a physiological framework for evidence-based shift scheduling.