Oscillations of the circadian clock protein, BMAL-1, align to daily cycles of mechanical stimuli: a novel means to integrate biological time within predictive in vitro model systems.

Purpose: In vivo, the circadian clock drives 24-h rhythms in human physiology. Isolated cells in vitro retain a functional clockwork but lack necessary timing cues resulting in the rapid loss of tissue-level circadian rhythms. This study tests the hypothesis that repeated daily mechanical stimulation acts as a timing cue for the circadian clockwork. The delineation and integration of circadian timing cues into predictive in vitro model systems, including organ-on-a-chip (OOAC) devices, represent a novel concept that introduces a key component of in vivo physiology into predictive in vitro model systems.

Methods: Quiescent bovine chondrocytes were entrained for 3 days by daily 12-h bouts of cyclic biaxial tensile strain (10%, 0.33 Hz, Flexcell) before sampling during free-running conditions. The core clock protein, BMAL-1, was quantified from normalised Western Blot signal intensity and the temporal oscillations characterised by Cosinor linear fit with 24-h period.

Results: Following entrainment, the cell-autonomous oscillations of the molecular clock protein, BMAL-1, exhibited circadian (24 h) periodicity ( < 0.001) which aligned to the diurnal mechanical stimuli. A 6-h phase shift in the mechanical entrainment protocol resulted in an equivalent shift of the circadian clockwork. Thus, repeated daily mechanical stimuli synchronised circadian rhythmicity of chondrocytes in vitro.

Conclusion: This work demonstrates that daily mechanical stimulation can act as a timing cue that is sufficient to entrain the peripheral circadian clock in vitro. This discovery may be exploited to induce and sustain circadian physiology within into predictive in vitro model systems, including OOAC systems. Integration of the circadian clock within these systems will enhance their potential to accurately recapitulate human diurnal physiology and hence augment their predictive value as drug testing platforms and as realistic models of human (patho)physiology.

Supplementary Information: The online version contains supplementary material available at 10.1007/s44164-022-00032-x.