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

Ángel Goñi-Moreno, Juhyun Kim, Víctor de Lorenzo

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Visualization of the intracellular constituents of individual bacteria while performing as live biocatalysts is in principle doable through more or less sophisticated fluorescence microscopy. Unfortunately, rigorous quantitation of the wealth of data embodied in the resulting images requires bioinformatic tools that are not widely extended within the community-let alone that they are often subject to licensing that impedes software reuse. In this context we have developed CellShape, a user-friendly platform for image analysis with subpixel precision and double-threshold segmentation system for quantification of fluorescent signals stemming from single-cells. CellShape is entirely coded in Python, a free, open-source programming language with widespread community support. For a developer, CellShape enhances extensibility (ease of software improvements) by acting as an interface to access and use existing Python modules; for an end-user, CellShape presents standalone executable files ready to open without installation. We have adopted this platform to analyse with an unprecedented detail the tridimensional distribution of the constituents of the gene expression flow (DNA, RNA polymerase, mRNA and ribosomal proteins) in individual cells of the industrial platform strain Pseudomonas putida KT2440. While the CellShape first release version (v0.8) is readily operational, users and/or developers are enabled to expand the platform further.

Original languageEnglish
Article number1600323
JournalBiotechnology Journal
Volume12
Issue number2
DOIs
StatePublished - 1 Feb 2017

Keywords

  • Cell segmentation
  • Fluorescence microscopy
  • Image analysis
  • Pseudomonas putida
  • Visualization software

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