Researchers develop new method for analyzing cell function

 Researchers in Finland and Germany have developed an open-source software that will make it significantly easier to process bioimaging data. The software, named BioImageXD, will help in analysing cell and tissue functions.

BioImageXD is a free open-source multi-purpose post-processing tool for bioimaging. The software can be used for simple visualization of multi-channel temporal image stacks to complex 3D rendering of multiple channels at once. Animations of 3D renderings can be created using flying paths or keyframes.

The work to develop the software has been funded by the Academy of Finland (through the FinNano Research Programme), the European Union and Tekes – the Finnish Funding Agency for Technology and Innovation. Version 1.0 of BioImageXD has been accepted for publication in Nature Methods, the top journal in the field.

Among other things, the BioImageXD software is a tool for analysing how molecules move on cell surfaces and how they bond together. With the software, scientists can analyse the composition of cell surfaces, study how cancer cells spread in a three-dimensional environment, or measure how effectively viruses and targeted drugs enter cells. Such calculations have not been possible before.

In recent years, cell and tissue imaging with new, specialised microscopes has considerably advanced research in bioscience and biomedicine. The new methods also allow for studies on living cells. However, the microscopic images are not displayable as such and need to be rendered into three-dimensional models. These 3D renderings carry significant weight as evidence already by themselves, but reliable scientific data also requires numerical values, which can then be used in mathematical calculations. In addition, these calculations must be feasible with extremely large datasets.

So far, the lack of suitable software has clogged up this development. To solve the problem, researchers in Turku, Jyväskylä and Dresden drew up precise specifications for software for processing of imaging data. A key criterion was that the software would be based on the principles of open source, freely available to all researchers.

The work resulted in BioImageXD, a software program that thanks to its versatile and open-source nature has received much positive feedback from hundreds of researchers around the world.

From extensive development to test success 

One of the unique features of BioImageXD is that it can be used to create completely new analysis methods (and users do not even need programming skills), process thousands of images at the same time and analyse millions of molecules. Comparison tests have shown that BioImageXD is faster and more sensitive than other similar programs.

The development of the BioImageXD software began ten years ago in a University of Jyväskylä research team led by Jyrki Heino. Since then, the work has continued through active collaboration between Heino’s team, Varpu Marjomäki’s team and Daniel White from Max Planck Institute of Molecular Cell Biology and Genetics.

The main development has been led by Pasi Kankaanpää, who now works at Turku Centre for Biotechnology as Coordinator of the Cell Imaging Core.

The BioImageXD software will be featured in a special issue of Nature Methods, focusing on the processing of biomedical images.

__________

Courtesy Academy of Finland

For model images and videos on the BioImageXD software, and its use in visualising intracellular molecules, for instance, please contact Pasi Kankaanpää.

More information:

• Coordinator Pasi Kankaanpää (University of Turku), tel. +358 40 522 1090, pkanka@utu.fi
• Professor Jyrki Heino (University of Turku), tel. +358 50 523 8351,jyrki.heino@utu.fi
• Adjunct Professor Varpu Marjomäki (University of Jyväskylä), tel. +358 40 563 4422, varpu.s.marjomaki@jyu.fi

Article: P. Kankaanpää, L. Paavolainen, S. Tiitta, M. Karjalainen, J. Päivärinne, J. Nieminen, V. Marjomäki, J. Heino and D. White (2012). “BioImageXD: an open, general-purpose and high-throughput image-processing platform”. Nature Methods 9: 683-689.