Circadian rhythms are a key survival mechanism that dictates biological activity according to the day-night cycle. In animals, cell-autonomous circadian clocks can be found in nearly every cell type and are subjected to multi-layered regulation. Although these peripheral clocks are remotely controlled by the master clock in the brain, they are also sensitive to their immediate physical microenvironment through mechanisms that are still unknown. Here we show that the circadian clock in fibroblasts is regulated mechanically through YAP/TAZ and TEAD. We use high-throughput analysis of single-cell circadian rhythms and apply controlled mechanical, biochemical, and genetic perturbations to study the expression of the core clock gene Rev-erbα. We observe that Rev-erbα circadian oscillations are disrupted concomitantly with the translocation of YAP/TAZ to the nucleus. By targeted mutations and tuning expression levels of YAP we identify TEAD as the transcriptional effector of this mechanosensitive regulatory pathway. Our findings establish a mechanism that links cell mechanobiology and the circadian clock, which could contribute to explain the circadian impairment observed in cancer and ageing, where the regulation of the mechanical environment and YAP/TAZ is lost.

Autonomous circadian clocks exist in nearly every mammalian cell type. These cellular clocks are subjected to a multilayered regulation sensitive to the mechanochemical cell microenvironment. Whereas the biochemical signaling that controls the cellular circadian clock is increasingly well understood, mechanisms underlying regulation by mechanical cues are largely unknown. Here we show that the fibroblast circadian clock is mechanically regulated through YAP/TAZ nuclear levels. We use high-throughput analysis of single-cell circadian rhythms and apply controlled mechanical, biochemical, and genetic perturbations to study the expression of the clock gene Rev-erbα. We observe that Rev-erbα circadian oscillations are disrupted with YAP/TAZ nuclear translocation. By targeted mutations and overexpression of YAP/TAZ, we show that this mechanobiological regulation, which also impacts core components of the clock such as Bmal1 and Cry1, depends on the binding of YAP/TAZ to the transcriptional effector TEAD. This mechanism could explain the impairment of circadian rhythms observed when YAP/TAZ activity is upregulated, as in cancer and aging.

Complex diseases such as Multiple Sclerosis (MS) cover a wide range of biological scales, from genes and proteins to cells and tissues, up to the full organism. We conducted a multilayer network analysis and deep phenotyping with multi-omics data (genomics, phosphoproteomics and cytomics), brain and retinal imaging, and clinical data, obtained from a multicenter prospective cohort of 328 patients and 90 healthy controls. Multilayer networks were constructed using mutual information, and Boolean simulations identified paths within and among all layers. The path more commonly found from the boolean simulations connects MP2K, with Th17 cells, the retinal nerve fiber layer (RNFL) thickness and the age related MS severity score (ARMSS). Combinations of several proteins (HSPB1, MP2K1, SR6, KS6B1, SRC, MK03, LCK and STAT6)) and immune cells (Th17, Th1 non-classic, CD8, CD8 Treg, CD56 neg, and B memory) were part of the paths explaining the clinical phenotype. Specific paths identified were subsequently analyzed by flow cytometry at the single-cell level.

Circadian rhythms are archetypical examples of nonlinear oscillations. While these oscillations are usually attributed to circuits of biochemical interactions among clock genes and proteins, recent experimental studies reveal that they are also affected by the cell's mechanical environment. Here we extend a standard biochemical model of circadian rhythmicity to include mechanical effects in a parametric manner. Using experimental observations to constrain the model, we suggest specific ways in which the mechanical signal might affect the clock. Additionally, a bifurcation analysis of the system predicts that these mechanical signals need to be within an optimal range for circadian oscillations to occur.