Genotypes can persist in unpredictable environments by ‘hedging their bets’ and producing diverse phenotypes. Theoretical studies have shown that the phenotypic variability needed for a bet-hedging strategy can be generated by factors either inside or outside an organism. However, sensing the environment and bet hedging are frequently treated as distinct evolutionary strategies. Furthermore, nearly all empirical studies of the molecular underpinnings of bet-hedging strategies to date have focused on internal sources of variability. We took a synthetic approach and constructed an experimental system where a phenotypic trade-off is mediated by actively sensing a cue present in the environment. We show that active sensing can generate a diversified bet-hedging strategy. Mutations affecting the norm of reaction to the cue alter the diversification strategy, indicating that bet hedging by active sensing is evolvable. Our results indicate that a broader class of biological systems should be considered as potential examples of bet-hedging strategies, and that research into the structure of environmental variability is needed to distinguish bet-hedging strategies from adaptive plasticity.
JPEGs of scans of plate images for Figures 2 and 6
These are JPEG files of the original TIFF files used to produce Figs. 2 and 6. Note that Figure 2 was produced from replicate 1 and Figure 6B was produced with files from replicate 2. See README for metadata.
jpeg-scans.zip
Code used in the analysis of the data
R code files used to process the raw data to generate the data files in this submission as well as the code used to generate figures and datasets used for the statistics. These files must be in the same directory as the CSV files in this submission in order to run. HTML links in the README file to R code will also only work if these files are in the same folder as the HTML file.
R-code.zip
2017-Maxwell-Magwene-when-sensing-is-gambling-fig3
This is a file that gives the data used to generate Figure 3. The goal of this set of experiments was to determine the ability of different genotypes to grow in SC+5FOA and SC-ura media in different concentrations of estradiol. Each culture was measured at the beginning and end of a 24hr growth period. This file was generated by process-tradeoffs-fig3.R.
2017-Maxwell-Magwene-when-sensing-is-gambling-fig4
This is a file that gives the data used to generate Figure 4. The goal of this set of experiments was to determine if strain that was plastic to the concentration of estradiol was pursuing a bet-hedging strategy in an environment with estradiol gradients and that alternated between SC-ura and SC+5FOA selection. This file was generated by process-competitions-fig4.R.
2017-Maxwell-Magwene-when-sensing-is-gambling-fig5-and-figS2
This is a file that gives the data used to generate Figure 5 and Supplementary Figure 2. The goal of this experiment was to determine if the plastic strain had a lower fitness than specialist strains. This file was generated by process-liquid-competitions-fig5.R.
2017-Maxwell-Magwene-when-sensing-is-gambling-fig6
This is a file that gives the data used to generate Figure 6. The goal of this experiment was to determine if mutation altered the diversification strategies of the plastic strain. This file was generated by process-images-fig6.R, which collates the cropped image data into a csv file.
2017-Maxwell-Magwene-when-sensing-is-gambling-figS1a
These data are optical density readings for cultures of yeast grown in different concentrations of SC+5FOA media and different concentrations of estradiol. The goal was to determine which degron tag on URA3 would allow for conditional growth on both SC-ura and SC+5FOA. This file was generated by process-degron-tag-figS1.R.
2017-Maxwell-Magwene-when-sensing-is-gambling-figS1b
These data are optical density readings for cultures of yeast grown in SC-ura media and different concentrations of estradiol. The goal was to determine which degron tag on URA3 would allow for conditional growth on both SC-ura and SC+5FOA. This file was generated by process-degron-tag-figS1.R.
README in org-mode format
README.html was exported from org-mode format. Code embedded in this document can be executed natively using emacs. For code blocks to run and for links to work, all data in this submission, and all R files in the R-code folder should be placed in the same directory.