TY - JOUR
T1 - CellShape
T2 - A user-friendly image analysis tool for quantitative visualization of bacterial cell factories inside
AU - Goñi-Moreno, Ángel
AU - Kim, Juhyun
AU - de Lorenzo, Víctor
N1 - Publisher Copyright:
Copyright © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
PY - 2017/2/1
Y1 - 2017/2/1
N2 - 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.
AB - 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.
KW - Cell segmentation
KW - Fluorescence microscopy
KW - Image analysis
KW - Pseudomonas putida
KW - Visualization software
UR - http://www.scopus.com/inward/record.url?scp=84992616349&partnerID=8YFLogxK
U2 - 10.1002/biot.201600323
DO - 10.1002/biot.201600323
M3 - Article
C2 - 27492366
AN - SCOPUS:84992616349
SN - 1860-6768
VL - 12
JO - Biotechnology Journal
JF - Biotechnology Journal
IS - 2
M1 - 1600323
ER -