BactImAS: a platform for processing and analysis of bacterial time-lapse microscopy movies

Background The software available to date for analyzing image sequences from time-lapse microscopy works only for certain bacteria and under limited conditions. These programs, mostly MATLAB-based, fail for microbes with irregular shape, indistinct cell division sites, or that grow in closely packed...

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Vydané v:BMC bioinformatics Ročník 15; číslo 1; s. 251
Hlavní autori: Mekterovic, Igor, Mekterovic, Darko, Maglica, zeljka
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: London BioMed Central 25.07.2014
BioMed Central Ltd
Springer Nature B.V
Predmet:
Algorithms
Automation
Bacteria
Bacterial Proteins - metabolism
Bioinformatics
Biomedical and Life Sciences
Cell division
Cell Proliferation
Computational Biology/Bioinformatics
Computer Appl. in Life Sciences
Computer programs
Data analysis
Databases, Factual
Drug resistance
Gene expression
Gene Expression Regulation, Bacterial
Heterogeneity
image analysis and data visualization
Image Processing, Computer-Assisted - methods
Imaging
Isocitrate Lyase - metabolism
Java
Life Sciences
Linux
Manuals
Microarrays
Microscope and microscopy
Microscopy
Microscopy - methods
Mycobacterium smegmatis
Mycobacterium smegmatis - cytology
Mycobacterium smegmatis - genetics
Operating systems
Programming languages
Software
Structured Query Language-SQL
Studies
ImageJ
Image analysis
Time-lapse microscopy
Mycobacteria
Data visualization
Database
Icy
ISSN:1471-2105, 1471-2105
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Shrnutí:Background The software available to date for analyzing image sequences from time-lapse microscopy works only for certain bacteria and under limited conditions. These programs, mostly MATLAB-based, fail for microbes with irregular shape, indistinct cell division sites, or that grow in closely packed microcolonies. Unfortunately, many organisms of interest have these characteristics, and analyzing their image sequences has been limited to time consuming manual processing. Results Here we describe BactImAS – a modular, multi-platform, open-source, Java-based software delivered both as a standalone program and as a plugin for Icy. The software is designed for extracting and visualizing quantitative data from bacterial time-lapse movies. BactImAS uses a semi-automated approach where the user defines initial cells, identifies cell division events, and, if necessary, manually corrects cell segmentation with the help of user-friendly GUI and incorporated ImageJ application. The program segments and tracks cells using a newly-developed algorithm designed for movies with difficult-to-segment cells that exhibit small frame-to-frame differences. Measurements are extracted from images in a configurable, automated fashion and an SQLite database is used to store, retrieve, and exchange all acquired data. Finally, the BactImAS can generate configurable lineage tree visualizations and export data as CSV files. We tested BactImAS on time-lapse movies of Mycobacterium smegmatis and achieved at least 10-fold reduction of processing time compared to manual analysis. We illustrate the power of the visualization tool by showing heterogeneity of both icl expression and cell growth atop of a lineage tree. Conclusions The presented software simplifies quantitative analysis of time-lapse movies overall and is currently the only available software for the analysis of mycobacteria-like cells. It will be of interest to the community of both end-users and developers of time-lapse microscopy software.
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ISSN:1471-2105
1471-2105
DOI:10.1186/1471-2105-15-251