Brancaccio, M. | bioRxiv Science

bioRxiv2023

The circadian clock is a pacemaker of the axonal regenerative ability

Peripheral nervous system injuries lead to long-term neurological disability due to limited axonal regenerative ability. Injury-dependent and -independent physiological mechanisms have provided important molecular insight into neuronal regeneration. However, whether common molecular denominators underpin both injury-dependent and independent biological processes remain unclear. Here, we performed a comparative analysis of recently generated transcriptomic datasets associated with the regenerative ability of sciatic dorsal root ganglia (DRG). Surprisingly, circadian rhythms were identified as a the most significantly enriched biological process associated with regenerative capability. We demonstrate that DRG neurons possess an endogenous circadian clock with a 24h oscillations of circadian genes and that their regenerative ability displays a diurnal oscillation in a mouse model of sciatic nerve injury. Consistently, transcriptomic analysis of DRG neurons showed a significant time-of-day dependent enrichment for processes associated with axonal regeneration, development and growth, as well as circadian associated genes, including the core clock genes Bmal1 and Clock. Indeed, DRG-specific ablation of the non-redundant clock gene Bmal1 showed that it is required for regenerative gene expression, neuronal intrinsic circadian regeneration and target reinnervation. Lastly, lithium, a chrono-active compound, enhanced nerve regeneration, in wildtype but not in Bmal1 and Cry1/2-deficient mice. Together, these data demonstrate that daily rhythms and the molecular clock fine-tune the regenerative response of DRG neurons, and that chrono-active drugs, such as lithium, are a novel potential approach to nerve repair.

neuroscience↗

bioRxiv2021

A spatio-temporal model to reveal oscillatorphenotypes in molecular clocks: Parameterestimation elucidates circadian gene transcriptiondynamics in single-cells

We propose a stochastic distributed delay model together with a Markov random field prior and a measurement model for bioluminescence-reporting to analyse spatiotemporal gene expression in intact networks of cells. The model describes the oscillating time evolution of molecular mRNA counts through a negative transcriptional-translational feedback loop encoded in a chemical Langevin equation with a probabilistic delay distribution. The model is extended spatially by means of a multiplicative random effects model with a first order Markov random field prior distribution. Our methodology effectively separates intrinsic molecular noise, measurement noise, and extrinsic noise and phenotypic variation driving cell heterogeneity, while being amenable to parameter identification and inference. Based on the single-cell model we propose a novel computational stability analysis that allows us to infer two key characteristics, namely the robustness of the oscillations, i.e. whether the reaction network exhibits sustained or damped oscillations, and the profile of the regulation, i.e. whether the inhibition occurs over time in a more distributed versus a more direct manner, which affects the cells ability to phase-shift to new schedules. We show how insight into the spatio-temporal characteristics of the circadian feedback loop in the suprachiasmatic nucleus (SCN) can be gained by applying the methodology to bioluminescence-reported expression of the circadian core clock gene Cry1 across mouse SCN tissue. We find that while (almost) all SCN neurons exhibit robust cell-autonomous oscillations, the parameters that are associated with the regulatory transcription profile give rise to a spatial division of the tissue between the central region whose oscillations are resilient to perturbation in the sense that they maintain a high degree of synchronicity, and the dorsal region which appears to phase shift in a more diversified way as a response to large perturbations and thus could be more amenable to entrainment.

systems biology↗