DOI: 10.5061/dryad.ksn02v7fd
title: Non-genetic adaptation by collective migration

description: Cell populations must adjust their phenotypic composition to adapt to
 changing environments. One adaptation strategy is to maintain distinct
 phenotypic subsets within the population and to modulate their relative
 abundances via gene regulation. Another strategy involves genetic
 mutations, which can be augmented by stress-response pathways. Here, we
 studied how a migrating bacterial population regulates its phenotypic
 distribution to traverse diverse environments. We generated isogenic
 Escherichia coli populations with varying distributions of swimming
 behaviors and observed their phenotype distributions during migration in
 liquid and porous environments. We found that the migrating populations
 became enriched with high-performing swimming phenotypes in each
 environment, allowing the populations to adapt without requiring mutations
 or gene regulation. This adaptation is dynamic and rapid, reversing in a
 few doubling times when migration ceases. By measuring the chemoreceptor
 abundance distributions during migration towards different attractants, we
 demonstrated that adaptation acts on multiple chemotaxis-related traits
 simultaneously. These measurements are consistent with a general mechanism
 in which adaptation results from a balance between cell growth generating
 diversity and collective migration eliminating under-performing
 phenotypes. Thus, collective migration enables cell populations with
 continuous, multi-dimensional phenotypes to flexibly and rapidly adapt
 their phenotypic composition to diverse environmental conditions.
description: <strong>Growth rates measurements</strong>
 Growth measurements were done using a microplate reader (BioTek
 Epoch 2 microplate spectrophotometer). Overnight cultures were diluted by
 100-fold into fresh media supplemented with appropriate inducer
 concentrations. 200 μL of diluted cells were aliquoted into each well of
 polystyrene 96-well plates (Falcon 96-wells REF 353072), and the plates
 were loaded into the plate reader. The plates were incubated at
 30<sup>o</sup>C while continuously shaking linearly at 567
 cpm. The OD<sub>600</sub> of each well was measured every 7
 minutes for 36 hours. To extract the growth rates of each sample, the
 slopes of the linear region (at the mid-exponential growth phases) of the
 natural log of OD<sub>600</sub> versus time (hours) curves
 were calculated.  
 <strong>Formation of propagating waves and expansion speed
 measurements using swim plate and capillary tube assays
 </strong> For the swim plate assay, 3 µL of cells
 in exponential phase were inoculated at the center of semi-solid agarose
 plates for RP437-derived strains or 10  of cells in exponential phase for
 MG1655-derived strains. For RP437-derived strains, the semi-solid agarose
 plates were made using M9-based media, as described above, supplemented
 with 0.14% agarose (American Bioanalytical Agarose GPG/LE) and appropriate
 concentrations of aTc. Similarly, for MG1655-derived strains, the
 semi-solid agarose plates were made using H1 minimal media, as described
 above, supplemented with 0.14% agarose. The plates were incubated at
 30<sup>o</sup>C for 15 hours (RP437-derived strains) or at
 33.5<sup>o</sup>C for 48 hours (MG1655-derived strains). The
 edges of the migrating colonies were picked using pipette tips and diluted
 into chemotaxis buffer (for RP437-derived strains) or minimal chemotaxis
 buffer (for MG1655-derived strains) for subsequent tracking and imaging
 analyses. To measure the expansion speeds of bacterial populations in swim
 plates, images were taken with a Canon DS126291 camera every 30 minutes.
 The diameters of the expansion rings as a function of time and expansion
 speeds were extracted from the images using a customized MATLAB
 code. Overnight cultures were inoculated 100-fold into
 5 mL of media with appropriate inducers and grown at
 30<sup>o</sup>C until OD<sub>600 </sub>= 0.2.
 Cells were concentrated to an OD<sub>600</sub> = 6. A 12-inch
 capillary tube was filled with growth media (M9 glycerol with casamino
 acids, MgSO<sub>4</sub>, and PVP-40) and 6-hours aged aTc, and
 one side of the tube was plugged by stabbing the tube into a plate filled
 with solidified agar (1.5% agar in distilled water). The concentrated cell
 mixture was filled on the other side of the tube using a 1 mL syringe, and
 another agar plug was added into that side. Both sides of the tube were
 then plugged with clay. The tubes are incubated horizontally at
 30<sup>o</sup>C for 9 hours. To isolate the wave, a 3-cm
 section of the tube that contained the wave was fractionated, and the
 mixture inside the 3-cm section was diluted into chemotaxis buffer for
 subsequent tracking analysis. To measure the expansion speeds of bacterial
 populations in capillary tubes, images were taken with a Canon DS126291
 camera every 10 minutes. Positions of the populations as a function of
 time and expansion speeds were extracted from images using
 ImageJ. <strong>Tracking single cells and tumble
 detection</strong> Washed cells were diluted with
 chemotaxis buffer to an OD<sub>600</sub> = 0.0005. The diluted
 mixture was injected inside the microfluidic device using a 1 mL syringe.
 To prevent evaporation, holes on both sides of the microfluidic device
 were taped. The device was placed on an inverted microscope (Nikon Eclipse
 Ti-U) equipped with a custom environmental chamber (50% humidity and
 30<sup>o</sup>C). A custom MATLAB script was used to record
 3-minute phase contrast videos at 4X magnification and 20
 frames-per-second. Data from video recordings were stored as .bin
 files. A customized MATLAB code was used to detect
 tumble and extract tumble bias of single cells, as previously
 described<sup>58</sup>. Only trajectories longer than 10
 seconds were considered for analysis. Each tumble bias distribution was
 generated using 4 3-minute videos that contained ~1000 total
 trajectories.  
 <strong>Measuring the time scales of relaxation of TB
 distribution to the standing batch distribution</strong>
 <em>E. coli </em>RP437 or HE205 were grown to
 mid-exponential phases and let to migrate in capillary assays for 9 hours,
 as mentioned above. The sections of the capillary tubes containing the
 migrating bacterial populations were fractioned, and the cells were added
 into 1 mL of growth media.  For every 15- or 30-minutes during growth in
 the batch cultures, the TB distributions of the populations were measured.
 The mean of TB distributions normalized by the trajectory lengths were
 determined for each time points. The equation to model
 for the relaxation of mean TB is:
                        where  is the mean TB
 over time,  is the mean TB of the batch culture,  is the mean TB during
 collective migration in the capillary tubes, and  is the relaxation
 timescale. To estimate , we fitted the means of the mean TBs across
 replicates and the standard error of the means across replicates to the
 equation using maximum likelihood estimation. To estimate the error of ,
 we sampled the posterior distribution using Markov Chain Monte Carlo
 simulation to get 100 simulated parameter values and calculate the
 standard deviation of those values.  
 <strong>Protein expression measurements in swim
 plates</strong> Non-motile MG1655-derived cells
 expressing labeled Tsr or non-motile RP437-derived cells expressing
 labeled CheY and CheZ used as biosensors for gene expression were grown as
 described above. Subsequently, cells were mixed with the appropriate media
 and 0.14% liquified agarose to a final OD<sub>600</sub> =
 0.01. Swim plates were left to solidify at room temperature for 2-3 hours,
 and afterward, 10 μL of OD<sub>600</sub> = 0.01 motile WT
 MG1655 (labeled Tsr experiments) or motile WT RP437 (labeled CheY and CheZ
 experiments) cells were inoculated in the center of the plate. The motile
 population of cells shapes the gradient of the plate and ensures that the
 non-motile biosensor strain experiences the same local environment as
 motile cells. After a colony of migrating cells has formed, cells from the
 center and the edge of the colony are picked and diluted into minimal
 chemotaxis buffer for subsequent imaging.  
 <strong>Single-cell protein copy number quantification
 using fluorescent microscopy</strong> Washed
 cells were diluted 10-fold and plated on agarose pads (3% agarose in
 minimal chemotaxis buffer). The cell suspension was left to dry for 10
 minutes, and cells were immediately imaged afterward. Imaging was
 performed using an inverted microscope (Nikon Eclipse Ti-E) equipped with
 an oil immersion 100x phase-contrast objective lens. To measure the
 fluorescence intensity of the strain expressing cheY-mRFP and cheZ-mYFP,
 fluorescent proteins were excited using a light-emitting diode
 illumination system (pE-4000, CoolLED). The RFP and YFP channels were
 imaged consecutively using a multi-band filter (Semrock), and the
 fluorescence emissions were led into a 2-camera image splitter (TwinCam,
 Cairn), leading to two identical sCMOS cameras (ORCA-Flash4.0 V2,
 Hamamatsu). The same setup was used to measure the fluorescence intensity
 of the strain expressing Tsr-mYFP. In a typical experiment, 20 fields of
 view, containing approximately 1000 cells in total, are imaged.
   <strong>Fluorescent image analysis for
 protein copy number quantification</strong> For
 each field of view, one phase contrast, one YFP, and one RFP channel
 images were acquired. Using a custom MATLAB script, images from the two
 cameras were aligned using an affine transformation, and cells were
 segmented on the phase-contrast channel using a modified Otsu algorithm.
 Then, the image background was subtracted from each image, and the
 fluorescent intensity of every cell was extracted. Finally, the area of
 each cell was calculated by fitting an ellipsoid. The fluorescent
 intensity of each cell was divided by the cell area as a measure of
 protein concentration.
description: # Non-genetic adaptation by collective migration
 [https://doi.org/10.5061/dryad.ksn02v7fd](https://doi.org/10.5061/dryad.ksn02v7fd) ## Description of the data and file structure The dataset is a collection of .mat files, which each contain MATLAB struct variables with processed single-cell trajectories or Tsr/CheYZ measurements. For the measurement of the relaxation of mean TB, the .mat files are structs that contain a table which contains the mean TB values of each trajectories and other information such as the replicate number, timepoint, and trajectory duration of that trajectory. For the measurement of tumble bias vs. OD600, the .mat file provided contains three variables that contains information about the TB for each trajectory, the OD600, and timepoints of measurements. The dataset also contains .xlsx files that reports the growth rates and expansion speeds of various conditions and strains. **The description of each provided files** 1. **datalabel.xlsx**: This file outlines all of the strains, conditions, descriptions, and replicate number of all the data provided. Please refer to this file for specific details about each file. 2. **tracking_measurement.zip**: This .zip file contains all of the tracking files in the paper. The tracking filenames are in the format of "...rad_swimtracker.mat" 3. **inheritance_measurement.zip**: the .mat file contains a variable called TE1_data_comb (for RP437) or HE205_data_comb (for HE205), which is a N x 5 matrix (N is the total number of trajectories). 4. **receptor_tsr_measurement.zip**: this .zip contains the .mat files that have a struct variable called "all_segmented_cells" that has 7 fields to report receptor abundances in single cell. 5. **cheychez_measurement.zip**: this .zip contains the .mat files that have a struct variable called "all_segmented_cells" that has 7 fields to report CheY and CheZ abundances in single cell. 6. **FigureS7_TE1_data_steadystategrowth_trackingdata.mat**: This .mat file contains data for cell tracking TB measurements of RP437 WT during steady, exponential growth. 7. **FigureS5_expansionradiusvstime_RP437_WTvscheZmutants_agarose.xlsx**: This is an excel file contains the measured expansion radius vs. time on agarose swim plates of RP437 WT and CheZ mutants. 8. **Figure6b_expansionspeed_MG1655_serinevsasp.xlsx**: This is an excel file contains the measured expansion speed vs. time of MG1655 on agarose swim plates supplemented with serine or aspartate. 9. **FigureS6_growthrate_RP437_WTvscheZmutants.xlsx**: This is an excel file contains the measured growth rate on of RP437 WT and CheZ mutants. 10. **FigureS10_expansionpositionvstime_RP437_WTvscheZmutants_liquid.xlsx:** This is an excel file contains the measured expansion position vs. time in capillary tubes of RP437 WT and CheZ mutants. 11. **Figure4b_expansionspeed_RP437_WTvscheZmutants_liquid.xlsx:** This is an excel file contains the measured expansion speed vs. time of RP437 and the CheZ mutants in capillary tubes. 12. **Figure2b_expansionspeed_RP437_WTvscheZmutants_agarose.xlsx:** This is an excel file contains the measured expansion speed vs. time of RP437 and the CheZ mutants on agarose swim plates. **The description of the variables** 1. **rad_swimtracker.mat files in tracking_measurement.zip:** The "swimtracker" .mat file contains several fields: 1. file_info: A RadFileInfo variable that contains the metadata about the file's properties.  2. metadata:  A Metadata variable that contains information about microscope settings used to record the tracking videos .  3. movie_name: A string about the name of the movie. 4. params: A struct containing 9 fields containing information of the parameters used to detect cells, track cells, and detect tumbles.  5. tracks: A Nx1 struct containing 68 fields about the x-coordinate (um), y-coordinate (um), trajectory time (sec), tumble bias, etc... The length unit is in microns, time unit is in seconds, and the angle unit is in radian. 2. **TE1_data_comb.mat and HE205_data_comb:** the .mat file contains a variable called TE1_data_comb (for RP437) or HE205_data_comb (for HE205), which is a N x 5 matrix (N is the total number of trajectories). Column 1 is the time points in minutes, column 2 is the replicate number, column 3 is the mean TB, column 4 is the weight by trajectory duration, and column 5 is the trajectory duration. 3. **.mat files in receptor_tsr_measurement.zip and cheychez_measurement.zip:** the .mat files contain a struct variable called "all_segmented_cells" that has 7 fields 1. centroid_x: the x location of the center of the cell (microns) 2. centroid_y: the y location of the center of the cell (microns) 3. area: the cell area (microns^2) 4. length: the length of the cell (micron) 5. width: the width of the cell (micron) 6. mcherry: mCherry intensity (AU) 7. YFP: YFP intensity (AU) 4. **FigureS7_TE1_data_steadystategrowth_trackingdata.mat:** The .mat file contains a variable called TE1_data_steadystategrowth_comb, which is a N x 8 matrix (N is the total number of trajectories). Column 1 is the time points of measurement in minutes, column 2 is the replicate number, column 3 is the mean TB, column 4 is the weight, column 5 is the speed (microns/seconds), column 6 is the run speed (microns/seconds), column 7 is the length of tracks (duration in seconds), and column 8 is the run time (seconds). It also contains a variable OD600, which is the OD600 measurements of the 5 replicates, and timepoint, which is the time of each measurement taken. 5. **FigureS5_expansionradiusvstime_RP437_WTvscheZmutants_agarose.xlsx:** The first column contains the timepoint in minutes. Columns B-L is the expansion radius (cm) of WT RP437. Columns N-S is the expansion radius of CheZ mutant supplemented with 2 ng/mL aTc. Columns T-Y is the expansion radius of CheZ mutant supplemented with 16 ng/mL aTc. 6. **Figure6b_expansionspeed_MG1655_serinevsasp.xlsx:** The first column contains the expansion speed of MG1655 supplemented with Serine in mm/hours, and the second column contains the expansion speed of MG1655 supplemented with Aspartate. 7. **FigureS6_growthrate_RP437_WTvscheZmutants.xlsx:** The first column contains the growth rates (1/hr) of RP437 WT, the second column contains the growth rates of RP437 CheZ mutants supplemented with 2 ng/mL aTc, and the third column contains the growth rates of RP437 CheZ mutants supplemented with 16 ng/mL aTc. 8. **FigureS10_expansionpositionvstime_RP437_WTvscheZmutants_liquid.xlsx:** The first sheet contains the time point in the first column and position in mm of WT RP437 in capillary tubes, the second sheet contains the time point in the first column and position in mm of RP437 CheZ mutant supplemented with 2 ng/mL aTc in capillary tubes, and the third sheet contains the time point in the first column and position in mm of RP437 CheZ mutant supplemented with 16 ng/mL aTc in capillary tubes. 9. **Figure4b_expansionspeed_RP437_WTvscheZmutants_liquid.xlsx:** The first column contains the expansion speed (mm/min) of RP437 WT, the second column contains the expansion speed of RP437 CheZ mutants supplemented with 2 ng/mL aTc, and the third column contains the expansion speed of RP437 CheZ mutants supplemented with 16 ng/mL aTc. 10. **Figure2b_expansionspeed_RP437_WTvscheZmutants_agarose.xlsx:** The first column contains the expansion speed (mm/min) of RP437 WT, the second column contains the expansion speed of RP437 CheZ mutants supplemented with 2 ng/mL aTc, and the third column contains the expansion speed of RP437 CheZ mutants supplemented with 16 ng/mL aTc. ## Code/software The GITHUB repository ([https://github.com/emonetlab/nongenetic-adaptation-wave](https://github.com/emonetlab/nongenetic-adaptation-wave)) provides the scripts to reproduce figures in our manuscript. To load the datasets, MATLAB 2020b and Microsoft Excel should be used. ## Access information Other publicly accessible locations of the data: * None Data was derived from the following sources: * For raw datasets, please contact [thierry.emonet@yale.edu](mailto:thierry.emonet@yale.edu).