Science Advances

Supplementary Materials

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  • Supplementary Materials and Methods
  • fig. S1. Design of a microfluidic platform and a typical experimental setup.
  • fig. S2. Growth of cell populations for cells grown in 2, 0.25, and 0.1% glucose.
  • fig. S3. Cumulative distribution function of budding intervals measured from individual cells grown in 2, 0.25, and 0.1% glucose.
  • fig. S4. Budding interval durations of spatially separate cells grown in 2, 0.25, and 0.1% glucose.
  • fig. S5. Example of erroneous approximation of Msn2 nuclear localization intensity.
  • fig. S6. Ratio of nuclear to cellular area as a function of the cell area.
  • fig. S7. Performance of algorithm in estimation of nuclear localization of Msn2 from whole cell, in the absence of a nuclear marker.
  • fig. S8. Estimation of nuclear localization of Msn2 using the algorithm is not sensitive to the variability in ratio of nuclear to cellular area at the single-cell level.
  • fig. S9. No photobleaching or significant drop in Msn2 signal was observed over the course of an experiment.
  • fig. S10. Proportion of cells having localization values below a given threshold k as a function of different thresholds k.
  • fig. S11. Quantification of Msn2 localization dynamics is robust to the choice of threshold used for localization quantification.
  • fig. S12. Heritability analysis of different localization features of Msn2 and analysis of inheritance of dynamical patterns of Msn2 localization is not sensitive to the choice of threshold used for Msn2 localization quantification.
  • fig. S13. Lack of correlation in localization amplitude between the first and second generation of the same cell.
  • fig. S14. Integral of Msn2 nuclear localization in different stress conditions.
  • fig. S15. Dissimilarity analysis of different localization features of Msn2 is not affected by spatial proximity between cell pairs.
  • fig. S16. Time dependent analysis of inheritance of Msn2 amplitude.
  • fig. S17. Similarity of Msn2 localization spikes as a function of time for M-D cell pairs in different glucose concentrations (related to Fig. 7B).
  • fig. S18. Correlation analysis between Msn2 localization features and cellular growth rate.
  • fig. S19. Mean squared error for Lasso solution as a function of different values of regularization or shrinkage parameter.
  • fig. S20. Lasso analysis is not sensitive to the choice of threshold used for Msn2 nuclear localization quantification.
  • fig. S21. System and measurement noise for different stress environments.
  • fig. S22. Block diagram of system identification and prediction steps.
  • fig. S23. Predicting CFP expression levels using cross-validation.
  • fig. S24. Sample polynomial fits for single-cell CFP trajectories.
  • table S1. Population doubling times of cells in different glucose concentrations obtained from fig. S2 (A to C).
  • table S2. Population doubling times calculated from OD600 measurements of cells grown in batch, using a shaker-incubator.
  • table S3. Values of parameters obtained from fitting data in fig. S6 to a sigmoidal function.
  • table S4. The P values comparing duration of Msn2 nuclear localization between 2 and 0.25% glucose, as well as 2 and 0.1% glucose across all threshold levels.
  • table S5. The P values comparing amplitude (A), frequency (B), and duration (C) of Msn2 nuclear localization between 2 and 0.25% glucose, as well as 2 and 0.1% glucose across different cell generations.
  • table S6. The P values obtained from Mann-Whitney U test.
  • table S7. The P values obtained from Mann-Whitney U test.
  • table S8. The P values obtained from Mann-Whitney U test.
  • table S9. Parameter values extracted from the linear state-space model’s application to the data obtained from 0.25 and 0.1% glucose experiments.
  • References (42–53)

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