Detailed description of the image analysis workflow, including machine learning model training dataset, for the article: "Phosphate starvation decouples cell differentiation from DNA replication control in the dimorphic bacterium Caulobacter crescentus", Hallgren et al. (2023; PLOS Genetics).

SND-ID: 2023-202. Version: 2. DOI: https://doi.org/10.58141/paxd-vr47

Citation

Alternative title

Ilastik image analysis pipeline for Caulobacter crescentus

Creator/Principal investigator(s)

Joel Hallgren - Stockholm University, Department of Molecular Biosciences orcid

Research principal

Stockholm University - Department of Molecular Biosciences, The Wenner-Gren Institute (MBW) rorId

Description

This dataset contains a detailed description of the image analysis procedure used in Hallgren et al. (2023; PLOS Genetics) to perform single-cell measurements of the bacterium Caulobacter crescentus. More specifically, the procedure identifies individual C. crescentus cells in phase-contrast microscopy pictures, annotates their cell type, as well as their size and basic morphological features. The procedure can for example be used to quantify the proportion of swarmer cells to stalked cells in a population, to measure the size of cells and their stalks, and to determine the fraction of constricted predivisional cells in a population.

The dataset includes: (1) ilastik project files, (2) custom Python scripts and ImageJ macros used for data processing, (3) settings for batch processing of images with the ImageJ plugin ‘MicrobeJ’, and (4) example data that can be used to run the image analysis pipeline from start to finish. The ilastik project files (.ilp) contain the random forest machine learning models used for their analysis, as well as the training dataset used to generate those models. The

... Show more..
This dataset contains a detailed description of the image analysis procedure used in Hallgren et al. (2023; PLOS Genetics) to perform single-cell measurements of the bacterium Caulobacter crescentus. More specifically, the procedure identifies individual C. crescentus cells in phase-contrast microscopy pictures, annotates their cell type, as well as their size and basic morphological features. The procedure can for example be used to quantify the proportion of swarmer cells to stalked cells in a population, to measure the size of cells and their stalks, and to determine the fraction of constricted predivisional cells in a population.

The dataset includes: (1) ilastik project files, (2) custom Python scripts and ImageJ macros used for data processing, (3) settings for batch processing of images with the ImageJ plugin ‘MicrobeJ’, and (4) example data that can be used to run the image analysis pipeline from start to finish. The ilastik project files (.ilp) contain the random forest machine learning models used for their analysis, as well as the training dataset used to generate those models. The README file contains instructions on how to run the image analysis pipeline from start to finish.

Although the machine learning models are trained specifically on images taken using our specific microscopy setup, the information and code present in this dataset can be used to easily set up a corresponding image analysis pipeline for a new laboratory, essentially by training new ilastik models and tweaking the MicrobeJ settings.

Additionally, underlying numerical data for all of graphs and summary statistics of the article (Hallgren et al., 2023) have been included in the form of tabular data in a zip archive. Show less..

Data contains personal data

No

Language

Data collection
Geographic coverage
Administrative information

Responsible department/unit

Department of Molecular Biosciences, The Wenner-Gren Institute (MBW)

Contributor(s)

Joel Hallgren - Stockholm University, Department of Molecular Biosciences, The Wenner-Gren Institute (MBW) orcid

Julien Mortier - Stockholm University, Department of Molecular Biosciences, The Wenner-Gren Institute (MBW) orcid

Topic and keywords

Research area

Natural sciences (Standard för svensk indelning av forskningsämnen 2011)

Biological sciences (Standard för svensk indelning av forskningsämnen 2011)

Cell biology (Standard för svensk indelning av forskningsämnen 2011)

Microbiology (Standard för svensk indelning av forskningsämnen 2011)

Cell and molecular biology (Standard för svensk indelning av forskningsämnen 2011)

Publications

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Joel Hallgren, Kira Koonce, Michele Felletti, Julien Mortier, Eloisa Turco, Kristina Jonas (2023) Phosphate starvation decouples cell differentiation from DNA replication control in the dimorphic bacterium Caulobacter crescentus. PLOS Genetics.

Joel Hallgren, Kira Koonce, Michele Felletti, Julien Mortier, Eloisa Turco, Kristina Jonas. Phosphate starvation decouples cell differentiation from DNA replication control in the dimorphic bacterium Caulobacter crescentus. bioRxiv 2023.07.26.550773 [preprint]
DOI: https://doi.org/10.1101/2023.07.26.550773

If you have published anything based on these data, please notify us with a reference to your publication(s). If you are responsible for the catalogue entry, you can update the metadata/data description in DORIS.

License

CC0 1.0

Versions

Version 2. 2023-11-20

Version 2: 2023-11-20

DOI: https://doi.org/10.58141/paxd-vr47

Data added: Underlying numerical data for all of graphs and summary statistics of the article (Hallgren et al., 2023) have been included as tabular data.

Version 1. 2023-11-13

Version 1: 2023-11-13

DOI: https://doi.org/10.58141/wfc6-qh32

Contact for questions about the data

Kristina Jonas

kristina.jonas@su.se

Published: 2023-11-20