Low-dimensional dynamics of two coupled biological oscillators

The circadian clock and the cell cycle are two biological oscillatory processes that coexist within individual cells. These two oscillators were found to interact, which can lead to their synchronization. Here, we develop a method to identify a low-dimensional stochastic model of the coupled system directly from time-lapse imaging in single cells. In particular, we infer the coupling and nonlinear dynamics of the two oscillators from thousands of mouse and human single-cell fluorescence microscopy traces. This coupling predicts multiple phase-locked states showing different degrees of robustness against molecular fluctuations inherent to cellular-scale biological oscillators. For the 1:1 state, the predicted phase-shifts following period perturbations were validated experimentally. Moreover, the phase-locked states are temperature-independent and evolutionarily conserved from mouse to human, hinting at a common underlying dynamical mechanism. Finally, we detect a signature of the coupled dynamics in a physiological context, explaining why tissues with different proliferation states exhibited shifted circadian clock phases.

Spatio-temporal synchronization of biological oscillators

Jonathan Bieler

The circadian clock is a cell-autonomous and self-sustained oscillator with a period of about 24 hours that controls many aspects of cellular physiology. The cell cycle is also a fundamental periodic process, with a period in the range of one day in mammals. A large number of studies showed that these two cycles interact at the molecular level. Mathematical theory of coupled oscillators predicts that in the presence of coupling, two cycles with similar periods can synchronize. Consequently, the molecular interactions between the cell cycle and the circadian clock could lead to their synchronization. Such synchrony is consistent with a number of studies showing that cells divide more at specific circadian times. Moreover, a few works also report effects of cell divisions on the circadian oscillator. More detailed mathematical models of the molecular networks involved also predict that the two cycles can synchronize. To better characterize this potential synchronization in mammalian cells, we monitored the mutual interactions between the two oscillators by time-lapse imaging of single NIH3T3 fibroblasts during several days. To do so, we used a fluorescent reporter under the control of a circadian promoter and monitored the cell cycle progression by detecting the time of mitosis. The analysis of thousands of circadian cycles in dividing cells clearly indicated that both oscillators tick in a 1:1 mode-locked state, with cell divisions occurring tightly 5 hours before the peak in circadian Rev-Erbα -YFP reporter expression. In principle, such synchrony may be caused by coupling from one oscillator onto the other, or in both directions. While gating of cell division by the circadian cycle has been most studied, our data combined with stochastic modeling strongly suggest that reverse coupling is predominant in NIH3T3 cells. In order to further test the direction of the coupling, we performed several perturbation experiments; we changed the cell cycle period by acquiring recordings at different temperatures, we analyzed cell lines containing genetic knock-down of circadian genes and used drugs that target specific proteins of the cell cycle and the circadian clock. These experiments showed that the two interacting cellular oscillators adopt a synchronized state that is highly robust over a wide range of parameters. Moreover, the set of perturbations on the periods of either oscillator induced shifts in the relative phases of circadian and cell cycles that were consistent with a scenario in which the circadian cycle resonates to the cell cycle. These findings have implications for circadian function in proliferative tissues, including epidermis, immune cells, and cancer.

EPFL2014

Robust synchronization of coupled circadian and cell cycle oscillators in single mammalian cells

Jonathan Bieler, Rosamaria Cannavo, Cédric Gobet, Kyle Gustafson, Felix Naef

Circadian cycles and cell cycles are two fundamental periodic processes with a period in the range of 1 day. Consequently, coupling between such cycles can lead to synchronization. Here, we estimated the mutual interactions between the two oscillators by time-lapse imaging of single mammalian NIH3T3 fibroblasts during several days. The analysis of thousands of circadian cycles in dividing cells clearly indicated that both oscillators tick in a 1: 1 mode-locked state, with cell divisions occurring tightly 5 h before the peak in circadian Rev-Erba-YFP reporter expression. In principle, such synchrony may be caused by either unidirectional or bidirectional coupling. While gating of cell division by the circadian cycle has been most studied, our data combined with stochastic modeling unambiguously show that the reverse coupling is predominant in NIH3T3 cells. Moreover, temperature, genetic, and pharmacological perturbations showed that the two interacting cellular oscillators adopt a synchronized state that is highly robust over a wide range of parameters. These findings have implications for circadian function in proliferative tissues, including epidermis, immune cells, and cancer.

Nature / European Molecular Biology Organization2014

CAST: An automated segmentation and tracking tool for the analysis of transcriptional kinetics from single-cell time-lapse recordings

Simon Blanchoud, Felix Naef, Damien Lionel Nicolas, Onur Tidin, Benjamin Zoller

Fluorescence and bioluminescence time-lapse imaging allows to investigate a vast range of cellular processes at single-cell or even subcellular resolution. In particular, time-lapse imaging can provide uniquely detailed information on the fine kinetics of transcription, as well as on biological oscillations such as the circadian and cell cycles. However, we face a paucity of automated methods to quantify time-lapse imaging data with single-cell precision, notably throughout multiple cell cycles. We developed CAST (Cell Automated Segmentation and Tracking platform) to automatically and robustly detect the position and size of cells or nuclei, quantify the corresponding light signals, while taking into account both cell divisions (lineage tracking) and migration events. We present here how CAST analyzes bioluminescence data from a short-lived transcriptional luciferase reporter. However, our flexible and modular implementation makes it easily adaptable to a wide variety of time-lapse recordings. We exemplify how CAST efficiently quantifies single-cell gene expression over multiple cell cycles using mouse NIH3T3 culture cells with a luminescence expression driven by the Bmal1 promoter, a central gene of the circadian oscillator. We further illustrate how such data can be used to quantify transcriptional bursting in conditions of lengthened circadian period, revealing thereby remarkably similar bursting signature compared to the endogenous circadian condition despite marked period lengthening. In summary, we establish CAST as novel tool for the efficient segmentation, signal quantification, and tracking of time-lapse images from mammalian cell culture.

Academic Press Inc Elsevier Science2015

Spatio-temporal synchronization of biological oscillators

Jonathan Bieler

EPFL2014