Published on: Sep 29, 2013
Systems approach to study cellular responses to non-ionizing electro-magnetic fields
Arnold Kuzniar1, Berina Eppink, Charlie Laffeber, David Schuermann, Manuel Murbach, Mascha Schoonakker, Alex Zelensky, Jeroen Demmers, Primo Schär & Roland Kanaar
1Department of Genetics, Erasmus Medical Center, Rotterdam, the Netherlands, 3000 CA
Arnold Kuzniar graduated in bioinformatics, and recently joined the laboratory of Prof. Roland Kanaar at Erasmus Medical Center in Rotterdam, The Netherlands, to investigate the potential effects of non-ionizing electromagnetic (EM) fields on cells. The research project has a truly interdisciplinary character integrating cell biology, biochemistry and bioinformatics. The work presented at the BioEM2013 meeting in Thessaloniki, Greece, focused on computational proteomics approach to study cellular responses to ELF/RF EM fields by identifying molecular changes in the entire sets of the cells’ proteins (proteome).
There is a public health concern about the influence of non-ionizing EM fields, such as those produced by power-lines, mobile or wireless devices, on the development of cancer. We hypothesize that for detecting any biological effect of EM fields, a living cell first must receive a stimulus, process it and then respond by changing its molecular state i.e., cellular protein levels and/or protein modifications (e.g., by phosphorylation). In this quest two approaches were followed: i) the targeted approach with a primary focus on DNA damage response pathways, since cancer is promoted and driven by DNA damage and ii) the whole proteome or unbiased approach using semi-quantitative proteomics to investigate all known cellular processes and signaling pathways. We implemented three key technologies that allow us to conduct highly controlled experiments and sensitive detection of molecular changes in exposed cells. First, we use a standardized in vitro exposure apparatus developed by IT'IS to expose different mammalian cell lines to a 50 Hz power-line signal. The second technology is a highly sensitive and accurate mass spectrometer that can determine protein identities. Using this technology we can also measure relative protein abundance between different conditions, an approach known as semi-quantitative proteomics with SILAC. Using differential SILAC labeling one can compare the entire proteomes of treated (exposed) versus untreated (sham) cells. To do this, however, a third technology is pivotal; a bioinformatics infrastructure for the management, analysis and interpretation of large data sets. Specifically, I developed a bioinformatics workflow consisting of MS/protein library search algorithm and an integrated proteomics database. The database stores processed experimental data such as protein identifications and quantitations, as well as other relevant biological information from public repositories on the molecular functions of the proteins, their interaction with other proteins, the biological processes they are known to be involved in and their sub-cellular localization. Importantly, the database is more than a data store: it could be compared to a sophisticated "microscope" that can be interrogated to find answers to relevant biological questions such as: i) Which proteins are differentially regulated in the cells upon ELF/RF exposure? ii) Where do the candidate proteins localize in a cell? iii) Which biological processes or signaling pathways are perturbed upon exposure? Our preliminary experiments suggest that a small fraction of the proteome responds to ELF EM fields. Using bioinformatics approaches we are now identifying which cellular processes may be perturbed in order to find biological implications.
It was a pleasure to participate at the BioEM2013 meeting and to discuss interesting research with many of you. I am humbled to be recognized with an award for my poster presentation. I look forward to the next meeting.
This work was supported by ZonMw (The Netherlands Organisation for Health Research and Development).