Data set and data processing software of: Bacterial cell size modulation along the growth curve across nutrient conditions

In Repository.zip it is possible to find the following folders:

 

ImageProcess: Shows an example of the studied phtos, the segmentation mask obtained using Ilastik and the scripts used to estimate the cell dimensions.

 

DataProcessing: Includes the raw data for cells size in all the studied conditions, a script showing the filtering and the data processing for plotting most of the figures of the article.

 

CFUod: Includes the dataset of CFU and OD measurements studied in the article. The inered trends over different biological replica and the data processing for plotting the Figures in the main text. 

 

 

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ImageProces:

 

This folder contains:

 

* IMAGES folder: Contains a 10 arbitrary folders of images, one for different OD conditions for the experiment of M9 + 0.25% CAS. Each image is a .tif file. The pixel size is 0.07 micrometers per pixel and they were obtained using bright field microscopy imaging. 

 

* SEG folder: Contains the masks for the same number of folders and photos equivalent photos in the IMAGES folder. Masks are also in .tif format.

 

* "Dataset.csv": Is a typical dataset obtained from the images using the script of image processing. The data consists on the following columns:

a. OD: Label of the OD measurement. Following experimental arbitrary notation, this number was the time in hours times 10. 

b. Photo: The label of the segmented photo.

c. Area: Area of the segmenteated contour (squared micrometers).

d. Len: Cell size length (Micrometers).

 

* "ImageProcesing.ipynb": Jupyter notebook for procesing the images and their masks. The output is "Dataset.csv"

 

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DataProcessing:

 

This folder contains:

 

* RawData.csv: comma separated values file with the dimensions of different cells in for the studied conditions. The data consists on the following columns:

a. Strain: Represents the experimental condition. It has the following values:

M9= E.coli Growth in minimal M9

M9cas25= E.coli in M9 + 0.25% Casaminoacids

LBSS= E.coli in LB in steady growth

SalLB= S. enterica in LB.

SalM9=S. enterica in M9

M9cas50= E.coli in M9 + 0.5% Casaminoacids

LB2= E. coli in LB

b. Photo: label for the studied photo.

c. Time: Time in hours after resuspension.

d. OD: Optical density of the studied population.

e. Len: Cell length of the situdied contour (micrometers).

f. Area: Projected area of the cell contour (squared micrometers).

g. Area: Volume of the cell (cubic micrometers).

h. SAV surface/volume ratio.

i. Width: Cell width 

j. Aspect; Aspect ratio length/width

 

*Stats.csv: Results of the statistical moments of cell size dimensions calculated from "Rawdata.csv" using "Plotter.ipynb". These data consists on the following columns:

 

a. Time: Time (hours)

b. OD: Optical density 

c. MnVol: Mean cell volume (cubic micrometers)

d. MnVolErr: 95% confidence interval of the mean volume.

e. CV2Vol: squared coefficient of variation of the volume.

f. CV2VolErr: 95% confidence interval squared coefficient of variation of the volume.

g. Mnw: Mean cell width (micrometers)

h. MnwErr: 95% confidence interval of the mean width.

i. CV2w: squared coefficient of variation of the cell width.

j. CV2wErr: 95% confidence interval squared coefficient of variation of the width.

k. MnLen: Mean cell length (micrometers)

l. MnLenErr: 95% confidence interval of the mean length.

m. CV2Len: squared coefficient of variation of the cell length.

n. CV2LenErr: 95% confidence interval of the squared coefficient of variation of the cell length.

o. Strain: Nutrient conditions

 

*Ploter.ipnyb: Jupyter notebook which using "RawData.csv" calculates the moments in "Stats.csv" and plots most of the figures of the main article. 

 

 

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CFUod: 

 

This folder contains:

 

* resultsOD.csv: OD values for different biology replicas. The columns are as follows:

a. t: Time (hours)

b. log(OD): Natural logarithm of the bets fit for the  optical density

c. log(OD) error: 95% confidence interval for the best fit of the natural logarithm of the optical density.

d. gr: best fit growth rate in units of 1/hours.

e. gr error: 95% confidence interval of the growth rate.

f. three columns called "od": each represents the optical density for each experimental replica.

 

 

* resultscfu.csv: cfu values for different biology replicas. The columns are as follows:

a. t: Time (hours)

b. log(OD): Natural logarithm of the bets fit for the cfu

c. log(OD) error: 95% confidence interval for the best fit of the natural logarithm of the cfu.

d. gr: best fit growth rate in units of 1/hours.

e. gr error: 95% confidence interval of the growth rate.

f. three columns called "od": each represents the cfu for each experimental replica.

 

 

*ODGrowthRate.ipynb: jupyter notebook that uses "resultsOD.csv" and "resultscfu.csv" for plotting the ratio OD/cfu.

 

 

Any question please ask cnieto@udel.edu

 

Cesar Augusto Nieto Acuna

 

Newark, Delaware, USA

 

08/05/2024