skip to main content

Title: Light entrainment of single cell circadian oscillator measured by a high-throughput microfluidic droplet platform.
This paper reports the measurement on light entrainment of single cell circadian oscillator of a model fungal system, Neurospora crassa (N. crassa), through a high-throughput microfluidic droplet platform [1]. The results demonstrated for the first time that single cell circadian oscillators could be entrained by light.
Award ID(s):
Publication Date:
Journal Name:
Proc. of the 21st International Conference on Miniaturized Systems for Chemistry and Life Sciences (MicroTAS). Savannah, GA October 22-26, 2017.
Sponsoring Org:
National Science Foundation
More Like this
  1. Most eukaryotes and cyanobacterial species have a biological clock that allows adaptation to the daily light/dark cycle of the planet. A central problem in the study of the biological clock is understanding the synchro-nization of the stochastic oscillators in different cells and tissues, but this problem is largely unstudied, particularly in the context of circadian rhythms. We developed a novel microfluidic platform to make high-throughput and high-precision measurements of biological clocks on a controlled number of Neurospora crassa (N. crassa) cells. Single cell measurements in this platform enabled us to test whether clocks of individual cells are able to communicate.
  2. Four inter-related measures of phase are described to study the phase synchronization of cellular oscillators, and computation of these measures is described and illustrated on single cell fluorescence data from the model filamentous fungus, Neurospora crassa. One of these four measures is the phase shift ϕ in a sinusoid of the form x(t) = A(cos(ωt + ϕ), where t is time. The other measures arise by creating a replica of the periodic process x(t) called the Hilbert transform x̃(t), which is 90 degrees out of phase with the original process x(t). The second phase measure is the phase angle FH(t) between the replica x̃(t) and X(t), taking values between -π and π. At extreme values the Hilbert Phase is discontinuous, and a continuous form FC(t) of the Hilbert Phase is used, measuring time on the nonnegative real axis (t). The continuous Hilbert Phase FC(t) is used to define the phase MC(t1,t0) for an experiment beginning at time t0 and ending at time t1. In that phase differences at time t0 are often of ancillary interest, the Hilbert Phase FC(t0) is subtracted from FC(t1). This difference is divided by 2π to obtain the phase MC(t1,t0) in cycles. Both the Hilbert Phasemore »FC(t) and the phase MC(t1,t0) are functions of time and useful in studying when oscillators phase-synchronize in time in signal processing and circadian rhythms in particular. The phase of cellular clocks is fundamentally different from circadian clocks at the macroscopic scale because there is an hourly cycle superimposed on the circadian cycle.« less
  3. Abstract

    Stochastic networks for the clock were identified by ensemble methods using genetic algorithms that captured the amplitude and period variation in single cell oscillators ofNeurosporacrassa. The genetic algorithms were at least an order of magnitude faster than ensemble methods using parallel tempering and appeared to provide a globally optimum solution from a random start in the initial guess of model parameters (i.e., rate constants and initial counts of molecules in a cell). The resulting goodness of fit$${x}^{2}$$x2was roughly halved versus solutions produced by ensemble methods using parallel tempering, and the resulting$${x}^{2}$$x2per data point was only$${\chi }^{2}/n$$χ2/n= 2,708.05/953 = 2.84. The fitted model ensemble was robust to variation in proxies for “cell size”. The fitted neutral models without cellular communication between single cells isolated by microfluidics provided evidence for onlyoneStochastic Resonance at one common level of stochastic intracellular noise across days from 6 to 36 h of light/dark (L/D) or in a D/D experiment. When the light-driven phase synchronization was strong as measured by the Kuramoto (K), there was degradation in the single cell oscillations away from the stochastic resonance. The rate constants for the stochastic clock network are consistent with those determined on a macroscopic scale of 107cells.

  4. The Neurospora crassa GUL-1 is part of the COT-1 pathway, which plays key roles in regulating polar hyphal growth and cell wall remodeling. We show that GUL-1 is a bona fide RNA-binding protein (RBP) that can associate with 828 “core” mRNA species. When cell wall integrity (CWI) is challenged, expression of over 25% of genomic RNA species are modulated (2,628 mRNAs, including the GUL-1 mRNA). GUL-1 binds mRNAs of genes related to translation, cell wall remodeling, circadian clock, endoplasmic reticulum (ER), as well as CWI and MAPK pathway components. GUL-1 interacts with over 100 different proteins, including stress-granule and P-body proteins, ER components and components of the MAPK, COT-1, and STRIPAK complexes. Several additional RBPs were also shown to physically interact with GUL-1. Under stress conditions, GUL-1 can localize to the ER and affect the CWI pathway—evident via altered phosphorylation levels of MAK-1, interaction with mak-1 transcript, and involvement in the expression level of the transcription factor adv-1 . We conclude that GUL-1 functions in multiple cellular processes, including the regulation of cell wall remodeling, via a mechanism associated with the MAK-1 pathway and stress-response.
  5. Mathematical models have a long and influential history in the study of human circadian rhythms. Accurate predictive models for the human circadian light response have been used to study the impact of a host of light exposures on the circadian system. However, generally, these models do not account for the physiological basis of these rhythms. We illustrate a new paradigm for deriving models of the human circadian light response. Beginning from a high-dimensional model of the circadian neural network, we systematically derive low-dimensional models using an approach motivated by experimental measurements of circadian neurons. This systematic reduction allows for the variables and parameters of the derived model to be interpreted in a physiological context. We fit and validate the resulting models to a library of experimental measurements. Finally, we compare model predictions for experimental measurements of light levels and discuss the differences between our model’s predictions and previous models. Our modeling paradigm allows for the integration of experimental measurements across the single-cell, tissue, and behavioral scales, thereby enabling the development of accurate low-dimensional models for human circadian rhythms.