Evolution of cell size control is canalized towards adders or sizers by cell cycle structure and selective pressures

  1. Felix Proulx-Giraldeau
  2. Jan M Skotheim
  3. Paul François  Is a corresponding author
  1. Department of Physics, McGill University, Canada
  2. Department of Biology, Stanford University, United States
  3. Chan Zuckerberg Biohub, San Francisco, United States
17 figures, 8 tables and 1 additional file

Figures

Implementation of the cell cycle seed network and evolution algorithm.

(A) Schematic representation of the coupling between cell size and cell cycle progression. The transition between G1 (red) and S phases of the cell cycle at the G1/S transition (orange) can evolve …

Evolution of feedback-based size control.

(A) Typical 2D fitness trajectory for an evolutionary run. Individual networks are dots color coded by their epoch within the evolutionary trajectory. Fitness function of the number of divisions of …

Characterizing and comparing evolved size control mechanisms.

(A) Average period T(VC) of the oscillator of Model A1 as a function of the control volume VC at the G1/S transition. Period is normalized by τ the doubling time of the cell, and volume is rescaled by …

Distinct network constraints and selection pressures bias size control evolution towards adders or sizers.

Summary statistics for evolutionary simulations each having 500 epochs. Model A1 shown in Figure 2A-G was used as the initial seed network. 60 simulations were performed using Pareto optimization of …

System and evolutionary dynamics of cell size control networks.

Snapshots of an evolutionary simulation of 2500 epochs initialized with the Model A1 network topology along with an S. pombe-like cell cycle structure with a timer in G1 followed by a sizer in …

An evolved concentration fluctuation sensing size control model exhibits self-organized criticality.

(A) Size-dependent molecular noise arises due to Poissonian fluctuations in molecule number. Consider a protein production-degradation scheme for protein quantity X with production rate ρ and …

Appendix 1—figure 1
Probability of the G1/S transition occurring at the next time step.

X-coordinate is the quantity of the transcriptional regulator I. Y-coordinate is the probability of the G1/S transition occurring at the next time step Δt. Parameters θ=0.8 and nθ=8.

Appendix 1—figure 2
Control volume and archetype response curves.

(A) Schematic representation of the way we break the feedback in the system and impose a control volume VC (red arrow) at the G1/S transition in order to record the induced cell cycle period T(VC). (B) …

Appendix 1—figure 3
Response curves for the initial seed networks.

Columns indicate the size scaling assumption of the protein production rates as indicated above the figure. Rows indicate quantity or concentration sensing of inhibitor I at the G1/S transition …

Appendix 1—figure 4
Schematic representation of the φ-evo algorithm.

We begin with a user-defined initial seed network as starting point of the evolutionary process. The seed network is cloned to give a first population of networks. Individuals are then mutated …

Appendix 1—figure 5
S/G2/M noise analysis.

Summary statistics for evolutionary simulations each having 500 epochs. Model A1 was used as the initial seed network. 30 simulations were performed using Pareto optimization of the number of …

Appendix 1—figure 6
Growth rate noise analysis.

Summary statistics for evolutionary simulations each having 500 epochs. Model A1 was used as the initial seed network. Only 30 simulations were performed using Pareto optimization of the number of …

Appendix 1—figure 7
Division fraction noise analysis.

Summary statistics for evolutionary simulations each having 500 epochs. Model A1 was used as the initial seed network. Only 30 simulations were performed using Pareto optimization of the number of …

Appendix 1—figure 8
Model A3’s behavior.

(A) Network topology of the evolved Model A3. S3 is as a size sensor and titrates I in a size-dependent manner. (B) Size distributions at birth (red), G1/S (orange), and division (purple). (C) …

Appendix 1—figure 9
Model A4’s behavior.

(A) Network topology of the evolved Model A4. S4 is the size sensor and represses the production of I in a size-dependent manner. (B) Size distributions at birth (red), G1/S (orange) and division …

Appendix 1—figure 10
Model A5’s behavior.

(A) Network topology of the evolved Model A5. S3 is the size sensor and represses the production of I in a size-dependent manner. (B) Size distributions at birth (red), G1/S (orange) and division …

Appendix 1—figure 11
Model A6’s behavior.

(A) Network topology of the evolved Model A6. S3 is the size sensor and represses the production of I in a size-dependent manner. (B) Size distributions at birth (red), G1/S (orange) and division …

Tables

Appendix 1—table 1
Coefficients of variation: models and experiments.
ModelsData
NameCVBirthCell typeTime of size measureCV
A10.098Haploid budding yeastBudding0.17
A20.095Haploid fission yeastFission0.06
B0.235Mouse epidermal stem cellBirth0.17
Appendix 1—table 2
Model A1 parameter values.
ParameterValueParameterValue
p20.369408δ30.4574764
t1:21.104619kf16.783001
n1:23.215727kb10.195168
δ20.083827δ44.244007
p30.703658kf20.021174
t2:30.044938kb21.075146
n2:33.266732δ51.1010876
Appendix 1—table 3
Model A2 parameter values.
ParameterValueParameterValue
p21.915601n1:32.751652
t1:20.17872t2:30.441106
n1:22.09054n2:32.780297
t3:20.962612δ30.045051
t3:22.144666kf10.839879
δ20.019495kb10.381067
p31.944803δ40.913992
t1:30.4229390
Appendix 1—table 4
Model B parameter values.
ParameterValueParameterValue
p24.968896n3:33.189190
t1:22.569361δ30.246561
n1:20.952178p44.674459
t3:20.131057δ41.010978
n3:29.219961kf3.194116
δ20.521437kb4.634009
p30.113586δ51.165439
t3:32.183079C01
Appendix 1—table 5
Model A3 parameter values.
ParameterValueParameterValue
p25.606156t2:31.410420
t1:20.066136n2:33.434213
n1:28.177965kf1.930909
b20.911279kb3.871610
δ20.257920δ30.013294
p35.887584δ41.803926
Appendix 1—table 6
Model A4 parameter values.
ParameterValueParameterValue
p25.6604334δ20.001059
t1:20.408208kf0.843408
n1:21.769233kb1.680321
t3:20.887392δ30.825150
n3:26.437683p44.674459
t4:20.197495t2:40.744119
n4:23.238633n2:43.451469
b20.800255δ41.929584
Appendix 1—table 7
Model A5 parameter values.
ParameterValueParameterValue
p22.379635b42.624939
t1:20.142770δ41.499653
n1:20.383384δ50.006318
t3:20.714386δ60.983140
n3:28.642875δ70.481592
t4:21.754776kf10.226150
n4:27.783080kb13.793388
b20.195855kf21.608325
δ20.576282kb23.322565
b30.582449kf32.999118
δ30.318466kb30.906997
Appendix 1—table 8
Model A6 parameter values.
ParameterValueParameterValue
p20.369408δ20.093159
t1:20.748731kf10.533415
n1:23.850889kb13.141514
p33.868044δ30.626507
t2:30.082081kf23.911233
n2:33.638939kb21.885120
t3:30.599375δ40.821609
n3:36.300643δ51.882484

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