********************* README Raw data and MATLAB code from Wang et al. "Natural Variation in Preparation for Nutrient Depletion Reveals a Cost-Benefit Tradeoff." Updated Jan 5, 2015 ********************* Each file is a ZIP archive of raw data from one set of experiments (see detailed list of datasets below). In addition to raw data, we provide a ZIP of the MATLAB code (R2013b or later) for processing the data and plotting figures. These scripts contain comments, metadata, and implementation details that supplement the analysis procedures described in Materials and Methods. Every figure in the paper can be generated using the files provided here (except for cartoons and cosmetic post-processing in Adobe Illustrator). The ZIP of MATLAB code is designed to be unzipped to the same folder as each of the Dataset ZIP files. Some scripts contain relative paths that assume this configuration, so they may need to be edited if your folder layout is different. Some general-purpose MATLAB functions used here also available separately, potentially in newer versions, as part of the Springer Lab codebase. For more information, see http://springerlab.org/resources/code/. For further questions, contact Jue Wang (juewang@post.harvard.edu) or Michael Springer (michael_springer@hms.harvard.edu). ------------------- INSTRUCTIONS ------------------- 1. Download and unzip the dataset you want. For example, download "Dataset 1.zip" and unzip it. It should leave a folder "Dataset 1" containing various files and subfolders. 2. Download "MATLAB analysis code.zip" and unzip it to the same base folder where you unzipped the dataset(s) (i.e. the folder containing "Dataset 1" above). This should leave a folder "MATLAB analysis code." 3. Add the folder "MATLAB analysis code/Common MATLAB Functions/" to your MATLAB path. This contains functions needed to run the analysis scripts. 4. Navigate to "MATLAB analysis code/Dataset 1 code/" and open, for example, "plot_fig1D.m" in MATLAB. Run the script, and it will display a figure corresponding to Figure 1 panel D from the paper. NOTES: Where possible, metadata needed to analyze the data is provided explicitly in .csv files. For example, "strains.csv" contains names of strains in each well of a 96-well plate, and "conditions.csv" or "media.csv" contains the growth conditions for those wells. If the experimental design is unclear, additional metadata may be found in the analysis code. Most of the plots are generated using pre-processed data loaded from .mat files at the beginning of each script. Where possible, scripts (usually prefixed by "calculate_" or "extract_") are provided to compute the .mat files from raw data. Some plots use data from more than one dataset. In these cases, the script to generate the figure is present in whichever dataset folder is more "natural" for that figure, and a copy of pre-processed data from the other dataset is deposited in the folder where it is needed. A note is made in the MATLAB script about which dataset contains the cross-referenced data. ---------------------- LIST OF DATASETS ---------------------- These are all contained in a folder named "Dataset X", inside a ZIP archive named "Dataset X.zip". Data for main figures and related supporting figures: Dataset 1. GROWTH CURVES (Figure 1, S1-3, S11A-B; Also used in figure 3, 4, 7C). Contains .csv files of raw OD600 readings from plate reader. Dataset 2. DIAUXIC GROWTH TIMECOURSE ON BC187 AND YJM978 (Figure 2, 5A-B, S4B-D, S5, S7C, S11C; Also used in figure 5C, S7B). Contains .fcs files of raw flow cytometry data and .csv files of sugar concentrations. Dataset 3. DIAUXIC GROWTH TIMECOURSE ON MULTIPLE STRAINS (Figure 3, S7A-B,D-F,I, S9A). Contains .fcs files of raw flow cytometry data. Dataset 4. MEDIUM SHIFT AND STEADY-STATE EXPRESSION (Figure 4, S6; Also used in figure S9A, S12). Contains .fcs files of raw flow cytometry data. Dataset 5. STEADY-STATE FITNESS OF BC187 AND YJM978 (Figure 5C, S12). Contains .fcs files of raw flow cytometry data. Dataset 6. SYNTHETIC INDUCTION (Figure 6). Contains .fcs files of raw flow cytometry data. Dataset 7. STEADY-STATE FITNESS OF MULTIPLE STRAINS (Figure 7, S14). Contains .fcs files of raw flow cytometry data. Data for other supporting figures: Dataset 8. ABSOLUTE COUNTING CONTROL (Figure S4A). Contains .fcs files of raw flow cytometry data. Dataset 9. LONG TIMECOURSE INDUCTION (Figure S8, S9B). Contains .fcs files of raw flow cytometry data. Dataset 10. PRE-CONDITION EFFECT ON INDUCTION KINETICS (Figure S10). Contains .fcs files of raw flow cytometry data. Dataset 11. TIMELAPSE MICROSCOPY (Figure S13). Contains .tiff files of raw microscopy data.