Figures and data in A robust and tunable mitotic oscillator in artificial cells

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10 figures, 3 tables and 5 additional files

Figures

Figure 1 with 1 supplement

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Reconstitution of an in vitro cell cycle clock and downstream mitotic events.

(A) Schematic view of a cell cycle oscillator that consists of coupled positive and negative feedback loops. The central regulator, cyclin B-Cdk1 complex activates its own activator, phosphatase Cdc25, forming a positive feedback loop, and inhibits its own inhibitor, kinase Wee1, forming a double negative feedback loop. Additionally, cyclinB-Cdk1 activates the E3 ubiquitin ligase APC/C, which targets cyclin B for degradation and completes a core negative feedback loop. Active APC/C also promotes the degradation of another substrate securin. Once cyclinB1-Cdk1 complex is activated, the circuit drives a set of mitotic events including chromosome condensation and nuclear envelope breakdown (NEB). (B) Experimental procedures. Cycling *Xenopus* extracts are supplemented with various combinations of recombinant proteins, mRNAs, and de-membraned sperm DNAs, which are encapsulated in 2% Perfluoropolyether-poly (ethylene glycol) (PFPE-PEG) oil microemulsions. Scale bar is 100 µm. (C) Snapshots of a droplet were taken periodically both in fluorescence channels (top three rows) and bright-field (the last row). The cyclic progression of the cell cycle clock and its downstream mitotic processes are simultaneously tracked by multiple fluorescence reporters. The clock regulator APC/C activity is reported by its substrate securin-mCherry, chromosomal morphology changes by the Hoechst stains, and NEB by GFP-NLS. Nuclear envelopes (red arrows) are also detectable on bright field images, matching the localization of GFP-NLS indicated nuclei. Scale bar is 30 µm. (D) Multi-channel measurements for the droplet in Figure 1C. The nucleus area (green circle) is calculated from the area of the nuclear envelope indicated by GFP-NLS, noting that the areas of the green circles are also scaled with the real areas calculated for the nuclei. DNA area curve (blue line) shows the chromosome area identified by Hoechst 33342 dye. Chromosome condensation happens almost at the same time as the nuclear envelope breaks down (black dashed line). The red dashed line represents the intensity of securin-mCherry over time, suggesting that degradation of the APC/C substrate lags behind NEB consistently at each cycle.

https://doi.org/10.7554/eLife.33549.002

Figure 1—video 1

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posterframe for video — Reconstitution of cell cycle clock and mitotic events.

This movie corresponds to Figure 1A. Green fluorescence channel shows alternations of nuclear envelope breakdown and reformation indicated by GFP-NLS protein. Green circles disappear when nuclear envelopes break down and reappear when nuclei assemble again. Blue channel (Hoechst) shows chromosome morphology changes over time. Securin-mCherry protein oscillations are shown in the red channel. The last channel is bright field, from which we can see nuclear envelope. Scale bar is 50 µm. The time stamp gives the real time in hour:minute format. The movie is shown at a rate of 10 frames per sec.

https://doi.org/10.7554/eLife.33549.003

Figure 2 with 2 supplements

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The minimal cell cycle oscillator is robust and tunable.

(A) Fluorescence image of securin-mCherry, a reporter for the cell cycle oscillator, in micro-emulsion droplets (scale bar, 100 µm). One example droplet (inside the white dotted framed square) is selected for time course analysis in Figure 2B. (B) The time course of securin-mCherry fluorescence intensity of the selected droplet from Figure 2A, indicating 32 undamped oscillations over a course of 100 hr. (C) Simultaneous measurements of fluorescence intensities of securin-mCherry (upper panel) and cyclin B-YFP (lower panel), showing sustained oscillations for about 58 hr. The mRNA concentrations of securin-mCherry and cyclin B-YFP are 10 ng/µL and 1 ng/µL. The series of mCherry and YFP images correspond to selected peaks and troughs in the time courses of fluorescence intensities. The two channels have coincident peaks and troughs for all cycles, suggesting that they both are reliable reporters for the cell cycle oscillator. (**D, E**) The oscillator is tunable in frequency (D) and number of cycles (E) as a function of the concentration of cyclin B mRNAs. Cyclin B not only functions as a substrate of APC/C but also binds to Cdk1 for its activation, functioning as an ‘input’ of the clock. In Figure 2D, the cell cycle periods are shortened by increasing the mRNA concentrations. In Figure 2E, the number of total cell cycles is reduced in response to increasing cyclin B mRNA concentrations. Each data point represents a single droplet that was collected from one of the loading replicates (see Materials and methods 7). Red dashed line connects medians at different conditions. Error bar indicates median absolute deviation (MAD). (**F, G**) Droplets with smaller diameters have larger periods on average and a wider distribution of periods (F), and exhibit smaller number of oscillations on average (G). Colored areas represent moving 25 percentiles to 75 percentiles and is smoothed using the LOWESS smoothing method (see Materials and methods 7). The equivalent diameter is defined as the diameter of a sphere that has an equal volume to that of a droplet, estimated by a volume formula in literature (Good et al., 2013). Note that these size effects are smaller for droplets with higher cyclin B mRNA concentrations.

https://doi.org/10.7554/eLife.33549.004

Figure 2—source data 1 Source data for generating Figure 2D-E.: https://doi.org/10.7554/eLife.33549.005
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Figure 2—source data 2 Source data for generating Figure 2F-G.: https://doi.org/10.7554/eLife.33549.006
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Figure 2—video 1

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Figure 2—video 2

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Figure 3 with 1 supplement

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Simulation of cell cycle model with energy depletion.

(A) Schematic view of the cyclin B-Cdk1 oscillation system. Note that ATP is taken into consideration. Activated molecules are marked in red, inactivated molecules in green and ATP or Pi in yellow. Black line indicates a reaction and blue dotted line a phosphorylation. (B) Relationship between ATP percentage and R value, showing that decreasing the ATP concentration leads to a higher R value. Error bars represent ranges from three simulations. Two inserts represent the dynamics of R value over time when the ATP percentage [ATP]/([ATP]+[ADP]) is set as 0.2 (left) and 0.5 (right). The model is simulated using Gillespie algorithm. (C) Phase plots of the two-ODE model. Parameters for the cyclin B nullcline (Ncyc) (Yang and Ferrell, 2013) and the Cdk1 nullclines with a variety of values of r (N1, r = 0.5; N2, r = 0.8; N3, r = 1.5; N4, r = 2.5) were chosen based on previous experimental work (Pomerening et al., 2003; Sha et al., 2003). Note that the r here is a parameter and is different from R in Figure 3B. Two sample traces of limit cycle oscillations are plotted for r = 0.8 (L1) and r = 1.5 (L2), showing that a larger r value leads to a higher amplitude and baseline. In addition, r = 0.5 (N1) generates a low stable steady-state of cyclin B (P1), while r = 2.5 (N4) a high stable steady-state of cyclin B (P4). These stable steady-states are indicated by the intersections of the nullclines (filled circles). The unstable steady states are labeled with open circles (P2 and P3). (D) Relationship between the oscillation baseline and amplitude values and ATP concentration (positively correlated with r). Error bars indicate the ranges of 3 replicates. Inserts show two example time courses of total cyclin B with different r values (L1, r = 0.8; L2, r = 1.5), colors of which match the ones in Figure 3C. Simulation is done using Gillespie algorithm. (E) Time series of total cyclin B molecules from the model without ATP (top panel, green line) and with ATP (bottom panel, yellow line).

https://doi.org/10.7554/eLife.33549.009

Figure 3—source data 1 Simulated data for generating Figure 3—figure supplement 1 using the energy depletion model.: https://doi.org/10.7554/eLife.33549.011
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Figure 3—figure supplement 1

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Analysis of the dependence of oscillations on the cyclin B synthesis and degradation rates.

(A) The period of the first cycle vs the last cycle in a droplet, showing that the period of the last cycle tends to be longer. Blue line indicates the same first and last periods. (B) Pearson correlation between the period of cycle and the index of cycle in a droplet. Positive correlation indicates that the cell cycle period tends to increase over time. (C) The period and number of oscillations decrease with an increasing cyclin B synthesis rate. Error bars represent standard deviations from 50 simulations. (D) Effects of synthesis and degradation rates of cyclin B as well as r on the baseline and amplitude of oscillations of total cyclin B. Color bar indicates baseline or amplitude of cyclin B (number of molecules per pL).

https://doi.org/10.7554/eLife.33549.010

Author response image 1

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A-C Statistics of droplets with sperm DNA (N=320) and without sperm DNA (N=373).

All droplets were prepared in the same day from the same batch of frog eggs. The figures show that adding sperm DNA may cause significant difference in number of oscillations (A), period (B) and oscillation sustaining time (C). D-E. Droplet-size dependence of period (D) and number of oscillations (E) with nucleus effect, showing that adding sperm DNAs has a more significant impact on larger droplets.

https://doi.org/10.7554/eLife.33549.020

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A thought experiment of a droplet of 200 µm in diameter undergoing ten divisions.

The cell cycle period is calculated for each division, with each corresponding diameter labeled on the figure. The error bar is showing 25^th and 75^th percentile as in Figure 2F in the main text.

https://doi.org/10.7554/eLife.33549.021

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Reproduction of Figure 3E bottom panel from the main text with different reaction volumes.
https://doi.org/10.7554/eLife.33549.022

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Size distribution for 1997 droplets obtained using a specific vortexing speed and duration.
https://doi.org/10.7554/eLife.33549.023

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Mitotic trigger waves in a large droplet.
https://doi.org/10.7554/eLife.33549.024

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Time traces of individual droplets with different concentrations of energy mix.

Each condition has two duplicate experiments and only one is shown. It is evident that the amplitude, baseline, and period decrease as the level of energy mix increases.

https://doi.org/10.7554/eLife.33549.025

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Amplitude (left panel) and period (right panel) decrease as energy mix concentration increases.
https://doi.org/10.7554/eLife.33549.026

Tables

Key resources table

Reagent type (species) or resource	Designation	Source or reference	Identifiers	Additional information
Biological sample (Xenopus laevis)	Xenopus eggs	Xenopus-I Inc.	RRID:NXR_0.0080
recombinant DNA reagent	securin-mCherry	this paper		Progentiors: PCR; Gateway vector pMTB2
recombinant DNA reagent	cyclin B1-YFP	this paper
recombinant DNA reagent	GST-GFP-NLS	PMID: 23863935		Dr. James Ferrell's lab
peptide, recombinant protein	GFP-NLS protein	this paper		BL21 (DE3)-T-1 competent cells
commercial assay or kit	QIAprep spin miniprep kit	QIAGEN	Cat No.: 27104
commercial assay or kit	mMESSAGE mMACHINE SP6 Transcription Kit	Ambion	Cat No.: AM1340
Strain, strain background	BL21 (DE3)-T-1 competent celss	Sigma-Aldrich	Cat No.: B2935
chemical compound, drug	calcium ionophore	Sigma-Aldrich	Cat No.: A23187
chemical compound, drug	Hoechst 33342	Sigma-Aldrich	Cat No.: B2261
chemical compound, drug	Trichloro (1H,1H,2H,2H- perfluorooctyl) silane	Sigma-Aldrich	Cat No.: 448931
chemical compound, drug	PFPE-PEG surfactant	Ran Biotechnologies	008-FluoroSurfactant- 2wtH-50G
other	GE Healthcare Glutathione Sepharose 4B beads	Sigma-Aldrich	Cat No.: GE17-0756-01
other	PD-10 column	Sigma-Aldrich	Cat No.: GE17-0851-01
other	VitroCom miniature hollow glass tubing	VitroCom	Cat No.: 5012

Table 1

Reaction rates and stoichiometry of the two-ODE model.

https://doi.org/10.7554/eLife.33549.012

Reaction	Rate	Stoichiometry
Active Cdk1 Synthesis	$ρ_{1} = k_{s y}$	$< C d k 1_{a} >=< C d k 1_{a} > + 1$
Active Cdk1 to Inactive Cdk1	$ρ_{2} = \sqrt{r} (a_{W e e 1} + \frac{b_{W e e 1} E C 50_{W e e 1}^{n_{W e e 1}}}{< C d k 1_{a} >^{n_{W e e 1}} + E C 50_{W e e 1}^{n_{W e e 1}}}) < C d k 1_{a} >$	$< C d k 1_{a} >=< C d k 1_{a} > - 1$ $< C d k 1_{i} >=< C d k 1_{i} > + 1$
Inactive Cdk1 to Active Cdk1	$ρ_{3} = \frac{1}{\sqrt{r}} (a_{C d c 25} + \frac{b_{C d c 25} < C d k 1_{a} >^{n_{C d c 25}}}{< C d k 1_{a} >^{n_{C d c 25}} + E C 50_{C d c 25}^{n_{C d c 25}}}) < C d k 1_{i} >$	$< C d k 1_{a} >=< C d k 1_{a} > + 1$ $< C d k 1_{i} >=< C d k 1_{i} > - 1$
Active Cdk1 Degradation	$ρ_{4} = (a_{d e g} + \frac{b_{d e g} < C d k 1_{a} >^{n_{d e g}}}{< C d k 1_{a} >^{n_{d e g}} + E C 50_{d e g}^{n_{d e g}}}) < C d k 1_{a} >$	$< C d k 1_{a} >=< C d k 1_{a} > - 1$
Inactive Cdk1 Degradation	$ρ_{5} = (a_{d e g} + \frac{b_{d e g} < C d k 1_{a} >^{n_{d e g}}}{< C d k 1_{a} >^{n_{d e g}} + E C 50_{d e g}^{n_{d e g}}}) < C d k 1_{i} >$	$< C d k 1_{i} >=< C d k 1_{i} > - 1$

Table 2

Reaction rates in the model considering ATP.

https://doi.org/10.7554/eLife.33549.013

Reaction	Rate
Active Cdk1 Synthesis	$ρ_{1} = k_{s y}$
Active Cdk1 to Inactive Cdk1	$ρ_{2} = 2 [A T P] < C d k 1_{a} > (a_{W e e 1} + \frac{b_{W e e 1} E C 50_{W e e 1}^{n_{W e e 1}}}{< C d k 1_{a} >^{n_{W e e 1}} + E C 50_{W e e 1}^{n_{W e e 1}}})$ $(\frac{1 - [A T P]}{[A T P] (1 - \frac{2 [W e e 1_{0}]}{[W e e 1_{t o t}]}) + \frac{[W e e 1_{0}]}{[W e e 1_{t o t}]}})$
Inactive Cdk1 to Active Cdk1	$ρ_{3} =< C d k 1_{i} > (a_{C d c 25} + \frac{b_{C d c 25} < C d k 1_{a} >^{n_{C d c 25}}}{< C d k 1_{a} >^{n_{C d c 25}} + E C 50_{C d c 25}^{n_{C d c 25}}})$ $(\frac{[A T P]}{1 - \frac{[C d c {25 - P i}_{0}]}{[C d c 25_{t o t}]} + (2 \frac{[C d c {25 - P i}_{0}]}{[C d c 25_{t o t}]} - 1) [A T P]})$
Active Cdk1 Degradation	$ρ_{4} = (a_{d e g} + \frac{b_{d e g} < C d k 1_{a} >^{n_{d e g}}}{< C d k 1_{a} >^{n_{d e g}} + E C 50_{d e g}^{n_{d e g}}})$ $< C d k 1_{a} >$
Inactive Cdk1 Degradation	$ρ_{5} = (a_{d e g} + \frac{b_{d e g} < C d k 1_{a} >^{n_{d e g}}}{< C d k 1_{a} >^{n_{d e g}} + E C 50_{d e g}^{n_{d e g}}})$ $< C d k 1_{i} >$

Additional files

Source code 1 Source code to generate Figure 1D based on raw image file.: https://doi.org/10.7554/eLife.33549.014
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Source code 2 Source code to generate Figure 2D–E and Figure 2F–G using Figure 2—source data 1 and Figure 2—source data 2 respectively.: https://doi.org/10.7554/eLife.33549.015
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Source code 3 Source code to generate Figure 3B–E.: https://doi.org/10.7554/eLife.33549.016
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Source code 4 Source code to generate Figure 3—figure supplement 1A–B using Figure 3—source data 1.: https://doi.org/10.7554/eLife.33549.017
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Transparent reporting form: https://doi.org/10.7554/eLife.33549.018
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Ye Guan
Zhengda Li
Shiyuan Wang
Patrick M Barnes
Xuwen Liu
Haotian Xu
Minjun Jin
Allen P Liu
Qiong Yang

(2018)

A robust and tunable mitotic oscillator in artificial cells

eLife 7:e33549.

https://doi.org/10.7554/eLife.33549

Figures

Reconstitution of an in vitro cell cycle clock and downstream mitotic events.

Reconstitution of cell cycle clock and mitotic events.

The minimal cell cycle oscillator is robust and tunable.

Figure 2—source data 1

Figure 2—source data 2

Free-running in vitro cell cycles detected by securin-mCherry reporter.

Tuning of the clock speed.

Simulation of cell cycle model with energy depletion.

Figure 3—source data 1

Analysis of the dependence of oscillations on the cyclin B synthesis and degradation rates.

A-C Statistics of droplets with sperm DNA (N=320) and without sperm DNA (N=373).

A thought experiment of a droplet of 200 µm in diameter undergoing ten divisions.

Reproduction of Figure 3E bottom panel from the main text with different reaction volumes.

Size distribution for 1997 droplets obtained using a specific vortexing speed and duration.

Mitotic trigger waves in a large droplet.

Time traces of individual droplets with different concentrations of energy mix.

Amplitude (left panel) and period (right panel) decrease as energy mix concentration increases.

Tables

Reaction rates and stoichiometry of the two-ODE model.

Reaction rates in the model considering ATP.

Additional files

Source code 1

Source code 2

Source code 3

Source code 4

Transparent reporting form

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Reconstitution of an in vitro cell cycle clock and downstream mitotic events.

Reconstitution of cell cycle clock and mitotic events.

The minimal cell cycle oscillator is robust and tunable.

Figure 2—source data 1

Figure 2—source data 2

Free-running in vitro cell cycles detected by securin-mCherry reporter.

Tuning of the clock speed.

Simulation of cell cycle model with energy depletion.

Figure 3—source data 1

Analysis of the dependence of oscillations on the cyclin B synthesis and degradation rates.

A-C Statistics of droplets with sperm DNA (N=320) and without sperm DNA (N=373).

A thought experiment of a droplet of 200 µm in diameter undergoing ten divisions.

Reproduction of Figure 3E bottom panel from the main text with different reaction volumes.

Size distribution for 1997 droplets obtained using a specific vortexing speed and duration.

Mitotic trigger waves in a large droplet.

Time traces of individual droplets with different concentrations of energy mix.

Amplitude (left panel) and period (right panel) decrease as energy mix concentration increases.

Reaction rates and stoichiometry of the two-ODE model.

Reaction rates in the model considering ATP.

Source code 1

Source code 2

Source code 3

Source code 4

Transparent reporting form

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)