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University of Manchester Group Develops Freeware for Long-Term, Live-Cell Imaging

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A group led by scientists at the University of Manchester in the UK has developed software that can automatically measure the location and intensity of fluorescence in living cells, and is making the tool freely available to the biological imaging community.
 
The tool, called CellTracker, is the latest example of freeware for high-content imaging, a trend that complicates an already crowded market for commercial image-analysis software. In addition, CellTracker is one of the first tools for tracking living and moving cells, which may enable improved single-cell analysis.
 
CellTracker was developed in the laboratory of Douglas Kell, a professor of bioanalytical science in the department of chemistry at the University of Manchester and director of the Manchester Center for Integrative Systems Biology. Kell’s group recently published a paper in the Journal of the Royal Society Interface describing the software and its utility in a NF-κB signaling assay.
 
According to the JRSI paper, the researchers developed CellTracker because the scientific community has been showing increasing interest in quantifying the amount and spatial distribution of proteins in individual cells.
 
Kell and colleagues wrote that high-content imaging methods have helped to meet this demand, but as many of these methods use fixed cells they are not suitable for a more systems biology approach to understanding gene expression pathways.
 
“A number of commercial software systems offer general-purpose image-processing capabilities,” the scientists wrote. “However, as part of a program in understanding spatial signal transduction using live-cell imaging in single cells, it became clear that none of these was suitable for our needs, more specifically because living cells are motile and change shape throughout the course of time-lapse experiments.”
 
To remedy this, Kell and colleagues devised image-analysis algorithms for CellTracker that track not only the positions of cells, but also their boundaries. The JRSI paper describes, in detail, how the group developed these algorithms.
 
In addition, the University of Manchester scientists described an experiment in which they used CellTracker to follow NF-κB signaling in live cells. Specifically, they co-transfected cultured SK-N-AS cells with p65-DsRed and pEGFP-N1, which produced a red fluorescent p65 fusion protein and enhanced green fluorescent protein. They subsequently examined the cells using confocal laser scanning microscopy for eight hours.
 
Their results showed how CellTracker was able to capture the motion of cells and their size variations based on changes in fluorescence intensity and nucleus-to-cytoplasm ratios. Furthermore, the results obtained with CellTracker agreed with profiles obtained using manual analysis, but were obtained in only five minutes as opposed to approximately 120 minutes.
 
Lastly, the group obtained data that underscored a common shortcoming of high-content imaging for fixed or live cells.
 
“In high-content image analysis, it is often the case that populations of cells are analyzed as a whole,” the researchers wrote. “The cells in this example show clearly that the location of signaling proteins can oscillate in each cell but that they are out of phase with each other when comparing different cells. This causes them to be damped out if they are analyzed at the level of the population.”
 
The scientists also cited previous research that they had conducted showing that the functional consequences of NF-κB signaling “may in fact depend not only on the signal amplitude, but also on the number, period, and frequency of these oscillations … underscoring the importance of single-cell measurements.”
 
CellTracker is available for download on the Kell group website, as are various publications and application notes about the software. The software currently supports Carl Zeiss laser-scanning microscopy, and TIFF and MAT file formats. Users can also export cell properties, such as nuclear and cytoplasmic average intensities, into Microsoft Excel and to an XML file.
 
Tracking the Market
 
CellTracker is the latest example of free software for image analysis, following on the heels of CellProfiler, a free and open-source platform developed over the past two years by Anne Carpenter and colleagues at the Whitehead Institute for Biomedical Research.
 
While both software packages have similar goals – to offer imaging scientists in academia and pharma more flexibility in their software than can be found in commercial packages – CellTracker may be more useful for longer-term, live-cell imaging while CellProfiler is designed more for high-content screening.
 

“I think time-lapse imaging has actually been underdeveloped in the high-content screening world, in general, and certainly in the open-source world.”

Kell told CBA News this week that the major difference between CellTracker and CellProfiler is CellTracker’s ability to track living, moving cells. But according to Carpenter, who is currently the director of the Broad Institute Imaging Platform, CellProfiler is also able to track moving cells.
 
“Actually, CellProfiler also can process time-lapse movies, and identify cells and track them over time,” Carpenter said. “Right now the tracking algorithms that we’re using, in my view, are fairly rudimentary, but I think are pretty comparable to what are used in general in the field. But we haven’t done any specific work in that area – we’ve simply used some obvious and straightforward tracking algorithms.”
 
Carpenter added that her group has been less interested in developing these capabilities because “it’s pretty rare that people have the resources and image-acquisition instrumentation available to do a serious high-throughput experiment in time lapse. I think time-lapse imaging has actually been underdeveloped in the high-content screening world, in general; and certainly in the open-source world.”
 
In addition, CellTracker is not open-source, while CellProfiler is, meaning that researchers can use the basic template to drop in their own algorithms for specific high-content imaging applications, which then become available to the scientific community.
Regardless of the specific capabilities of each freeware package, commercial image-analysis software vendors face a growing challenge from scientists who are developing similar tools and giving them away for free. These vendors include Definiens, SVision, Vala Sciences, and Media Cybernetics; and to a lesser extent vendors who offer image-analysis software packaged with high-content imaging systems, such as Cellomics, Molecular Devices, GE Healthcare, Evotec Technologies (now part of PerkinElmer), and BD Biosciences.
 
And there may still be additional free image-analysis software on the way, particularly for long-term live-cell imaging. Researchers associated with the European Molecular Biology Laboratory and the MitoCheck Consortium have been developing software to track cellular functions such as microtubule growth (see CBA News, 12/22/2006). That software is not fully developed yet, but may eventually be freely available to scientists.

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