S01

Circadian rhythms—self-sustained, ~24-h oscillations in transcript and protein levels—are generated by a cell-autonomous molecular clock. These rhythms shape how individual cells respond to external signals, influencing key decisions such as differentiation and apoptosis. However, current tools for visualizing circadian rhythms at the single-cell level often rely on genomic engineering and clonal expansion, limiting their accessibility and applicability. We present fluorescent circadian reporters based on the murine REVERBα/Nr1d1 gene, delivered via lentiviral transduction and compatible with time-lapse single-cell microscopy. These reporters produce oscillatory signals that depend on a functional circadian clock and can be used to determine a cell’s circadian dynamics parameters, such as circadian phase. Their simple and efficient delivery should make them suitable for a wide variety of cell types, greatly expanding opportunities to study single-cell circadian dynamics and their impact across diverse biological processes and systems.

Circadian clocks govern daily physiological and behavioral processes and are crucial for health; disruptions can lead to various diseases. The circadian phase of entrainment—the phase of the internal circadian clock in relation to external environmental cycles—is influenced by both genetic and environmental factors, varies between individuals, and is reflected in daily behaviors such as sleep–wake patterns, cognitive performance, and physical activity. While circadian phase may also fluctuate within individuals, the dynamics and extent of such variation in daily life remain largely unexplored. The gold standard for circadian phase assessment, dim-light melatonin onset (DLMO), is impractical for large-scale studies, and blood-based molecular biomarkers, while promising, are limited in feasibility. To address these challenges, we developed HairTime, a noninvasive assay that estimates circadian phase from a single daytime hair sample. Developed and evaluated in two steps—a training and a validation study—HairTime demonstrated strong predictive power compared to DLMO. Suitable for large-scale studies, it was assessed using over 4,000 samples. Circadian phase estimations showed a normal distribution and were associated with age, sex, and notably, work schedules, with earlier timing on workdays, suggesting that societal factors can modulate internal rhythms. Together, these findings establish HairTime as a promising tool for assessing circadian phase in research and lay the foundation for future applications in personalized chronotherapy.