CellShape: A user-friendly image analysis tool for quantitative visualization of bacterial cell factories inside

Area of Science:

• Microbiology
• Biotechnology
• Bioinformatics

Background:

• Fluorescence microscopy allows visualization of intracellular bacterial components.
• Quantifying microscopy data requires advanced bioinformatic tools, often with licensing restrictions.
• There is a need for accessible, open-source software for bacterial image analysis.

Purpose of the Study:

• To develop CellShape, a user-friendly platform for precise quantification of bacterial intracellular components from fluorescence microscopy images.
• To provide an open-source, extensible software solution for single-cell analysis.
• To analyze the spatial distribution of gene expression machinery in Pseudomonas putida.

Main Methods:

• Developed CellShape using Python, featuring subpixel precision and double-threshold segmentation.
• Created standalone executable files for easy end-user access without installation.
• Applied CellShape to analyze the 3D distribution of DNA, RNA polymerase, mRNA, and ribosomal proteins in Pseudomonas putida KT2440.

Main Results:

• CellShape offers high-precision image analysis for bacterial single-cell quantification.
• The platform facilitates detailed examination of intracellular component distribution.
• Analysis of Pseudomonas putida revealed unprecedented detail on gene expression flow constituents.

Conclusions:

• CellShape provides a powerful, accessible tool for quantitative bacterial cell biology.
• The open-source nature of CellShape promotes community development and wider adoption.
• This platform enables deeper understanding of cellular processes in industrial microbial strains.