Dataset.

Supporting information for Gene regulation by a protein translation factor at the single-cell level

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/330891
Digital.CSIC. Repositorio Institucional del CSIC
  • Dolcemascolo, Roswitha
  • Goiriz Beltrán, Lucas
  • Montagud-Martínez, Roser
  • Rodrigo, Guillermo
S1 Fig. Reliability of the dose-response curve. a) Mean of eBFP2 expression as a function of IPTG. b) Mean of sfGFP expression as a function of IPTG. c) Noise of eBFP2 expression as a function of IPTG. d) Noise of sfGFP expression as a function of IPTG. Points correspond to the values of the population shown in the main figures. Error bars correspond to standard errors calculated from four different populations. Solid lines correspond to predictions with the mathematical model. S2 Fig. Numerical simulations of stochastic dynamics. a-d) Stochastic trajectories with time of eBFP2 and sfGFP for two different IPTG concentrations. In red, deterministic trajectories. The initial condition corresponds to the uninduced state in all cases. e-h) Histograms of protein expression computed from long trajectories. The Gamma distributions fitted against the experimental data (blue lines) were also represented. S3 Fig. Sensitivity analysis of the model parameters. Plots of mean and noise of expression as a function of IPTG, where solid lines correspond to the dynamics predicted with the adjusted parameter, dotted lines to the dynamics if the parameter increases 2-fold, and dashed lines to the dynamics if the parameter decreases 2-fold. S4 Fig. Stochastic gene expression described by a Gamma distribution. Histograms of experimental single-cell fluorescence for both a) eBFP2 and b) sfGFP for different induction conditions with IPTG, together with fitted Gamma distributions against the data (blue lines) and predicted Gamma distributions obtained by using the model values of mean and noise (red lines). S5 Fig. Growth curves. Three different populations (blue, red, and green) were monitored with time. Points correspond to absorbance values, while solid lines come from fitted exponential trends. S6 Fig. Relationship between cellular growth rate and volume. a) Schematics to show that as TC increases, cells grow slower and are bigger. b) Scatter plot between the cube of the forward scattering signal (proxy of cellular volume) and the growth rate for the 81 IPTG and TC conditions (colored by TC condition). An exponential trend was adjusted (solid line). S1 Appendix. Stochastic differential equations. Derivation of the mathematical expressions of noise in eBFP2 and sfGFP having followed a Langevin formalism and the mean-field approximation. S2 Appendix. Gamma distribution. Derivation of the Gamma distribution for protein expression from a general stochastic differential equation. S1 Data. Flow cytometry data. Single-cell fluorescence data of eBFP2 and sfGFP for different induction conditions with IPTG and TC after filtering events., Peer reviewed
 
DOI: http://hdl.handle.net/10261/330891
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/330891

HANDLE: http://hdl.handle.net/10261/330891
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/330891
 
Ver en: http://hdl.handle.net/10261/330891
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/330891

Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/330891
Dataset. 2022

SUPPORTING INFORMATION FOR GENE REGULATION BY A PROTEIN TRANSLATION FACTOR AT THE SINGLE-CELL LEVEL

Digital.CSIC. Repositorio Institucional del CSIC
  • Dolcemascolo, Roswitha
  • Goiriz Beltrán, Lucas
  • Montagud-Martínez, Roser
  • Rodrigo, Guillermo
S1 Fig. Reliability of the dose-response curve. a) Mean of eBFP2 expression as a function of IPTG. b) Mean of sfGFP expression as a function of IPTG. c) Noise of eBFP2 expression as a function of IPTG. d) Noise of sfGFP expression as a function of IPTG. Points correspond to the values of the population shown in the main figures. Error bars correspond to standard errors calculated from four different populations. Solid lines correspond to predictions with the mathematical model. S2 Fig. Numerical simulations of stochastic dynamics. a-d) Stochastic trajectories with time of eBFP2 and sfGFP for two different IPTG concentrations. In red, deterministic trajectories. The initial condition corresponds to the uninduced state in all cases. e-h) Histograms of protein expression computed from long trajectories. The Gamma distributions fitted against the experimental data (blue lines) were also represented. S3 Fig. Sensitivity analysis of the model parameters. Plots of mean and noise of expression as a function of IPTG, where solid lines correspond to the dynamics predicted with the adjusted parameter, dotted lines to the dynamics if the parameter increases 2-fold, and dashed lines to the dynamics if the parameter decreases 2-fold. S4 Fig. Stochastic gene expression described by a Gamma distribution. Histograms of experimental single-cell fluorescence for both a) eBFP2 and b) sfGFP for different induction conditions with IPTG, together with fitted Gamma distributions against the data (blue lines) and predicted Gamma distributions obtained by using the model values of mean and noise (red lines). S5 Fig. Growth curves. Three different populations (blue, red, and green) were monitored with time. Points correspond to absorbance values, while solid lines come from fitted exponential trends. S6 Fig. Relationship between cellular growth rate and volume. a) Schematics to show that as TC increases, cells grow slower and are bigger. b) Scatter plot between the cube of the forward scattering signal (proxy of cellular volume) and the growth rate for the 81 IPTG and TC conditions (colored by TC condition). An exponential trend was adjusted (solid line). S1 Appendix. Stochastic differential equations. Derivation of the mathematical expressions of noise in eBFP2 and sfGFP having followed a Langevin formalism and the mean-field approximation. S2 Appendix. Gamma distribution. Derivation of the Gamma distribution for protein expression from a general stochastic differential equation. S1 Data. Flow cytometry data. Single-cell fluorescence data of eBFP2 and sfGFP for different induction conditions with IPTG and TC after filtering events., Peer reviewed




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