hrvatski jezikClear Cookie - decide language by browser settings

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

Mekterović, Igor; Mekterović, Darko; Maglica, Željka (2014) BactImAS: a platform for processing and analysis of bacterial time-lapse microscopy movies. BMC Bioinformatics, 15 (251). pp. 1-10. ISSN 1471-2105

[img]
Preview
PDF - Published Version - article
Available under License Creative Commons Attribution.

Download (1MB) | Preview

Abstract

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.

Item Type: Article
Uncontrolled Keywords: time-lapse microscopy; mycobacteria; image analysis; ImageJ; icy; data visualization; database
Subjects: NATURAL SCIENCES > Biology
TECHNICAL SCIENCES > Computing
Divisions: Division of Experimental Physics
Projects:
Project titleProject leaderProject codeProject type
Semantic Integration of Heterogeneous Data Sources (Semantička integracija heterogenih izvorišta podataka)Mirta Baranović036-0361983-2012MZOS
Depositing User: Darko Mekterović
Date Deposited: 24 May 2016 13:16
Last Modified: 24 May 2016 13:16
URI: http://fulir.irb.hr/id/eprint/2824
DOI: 10.1186/1471-2105-15-251

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year