2.45 GHz radiofrequency fields alter gene expression in cultured human cells
Radiofrequency (RF) refers to the electromagnetic waves ranging between 10 MHz and 300 GHz. RF have been widely used as a signal carrier in telecommunications. Recent advances in mobile phone technology have resulted in the exponential use of mobile phone communication around the world. The increasing exposure of humans to RF fields has raised wide concerns for potential adverse effects of RF fields on human health (http://www.fcc.gov/oet/rfsafety, http://www.fda.gov/cdrh/phones/index.html, http://www.who.int/emf, http://www.iegmp.org.uk/, http://www.verum-foundation.de/).
While it is clear that high energy-electromagnetic waves, such as X-rays have strong biological effects through ionizing damage, it is uncertain whether the low energy, non-ionizing RF fields could have effects on biological systems. Several epidemiological studies suggest a link between long-term RF exposures and pathological consequences such as cancer [1–7]. Molecular studies also suggest the possible influence of RF fields on various aspects of biological activities [8–13]. Although these studies have provided many clues to the issue of RF biological effects, the results are inconclusive and even controversial.
In this study, we used genome-wide gene expression as the indicator to address the issue of biological effects of RF. We used a 2.45 GHz waveguide system to expose human HL-60 cells. We used the serial analysis of gene expression (SAGE) technique to analyze the RF effect on gene expression at the genome level . Although gene expression has been used as an indicator in previous RF studies, those studies focused only on a handful number of genes pre-selected with defined functions. We aim to provide genome-wide coverage of the expressed genes regardless their functional categories in the RF treated cells to address if RF has biological effects [15,16]. We consider it particularly important to use this approach for the subject that there is limited biological information available. Our study shows that under the conditions used in our experimental system, the 2.45 GHz RF fields caused the expression changes of a number of genes.
2 Materials and methods
2.1 Cell culture
Human HL-60 cell line was purchased from ATCC. Cells were cultured in the RPMI 1640 medium + 10% fetal bovine serum (FBS) in an incubator at 37 °C with 5% CO2. Cells used for experiments were at the exponential growth phase. Prior to RF exposure, cells were spanned down and re-suspended in 10 ml of fresh medium at the density of 106/ml. The cells were then transferred to a 25 ml culture flask for RF exposure.
2.2 RF exposure system
The RF exposure system used for experiments was described in detail (Gerber et al. manuscript in preparation). Briefly, the RF source was a pulsed magnetron (Cober Muegge). It was pulsed at duration of 155 μs and a duty cycle of 7.5%, producing a peak power of 3 W into the waveguide. The measured average power was 225 mW, of which 100 mW was absorbed by the 10 ml cell suspension to provide the average SAR value of 10 W/kg. Using the measured 2.61 S/m conductivity of the medium at 2.45 GHz with the 133 W/kg SAR during the pulse, the calculated electric field is 320 V/m. A control waveguide, identical to the experimental waveguide was used for a sham exposure. Restricted by the cost of SAGE experiment, only the 2-h sham exposed cells were used as the control for the 2 and 6 h RF exposed cells. A flask containing a 10 ml HL-60 cell suspension at 106/ml was placed inside a WR340 brass waveguide having inside dimensions of 86.36 × 43.18 mm. The cells were allowed to settle down to the bottom of the flask to form a monolayer before exposure. The bottom of the flask is ground flat and coated with mineral oil to obtain good thermal conduction between the cell monolayer and brass waveguide. The bottom of the waveguide has an exterior plastic water channel glued to it such that the turbulent flowing water is in direct contact with the brass surface. A 5% air–CO2 mixture was introduced into the waveguide through a hole in its top surface. The brass surface was maintained at 37 °C through the use of a temperature-controlled water circulator. Two temperature probes (Luxtron) were inserted into the bottom surface of the flask to monitor the temperature. The temperature was maintained at 37.2 ± 0.2 °C during the exposure period.
2.3 SAGE process
The SAGE process followed the standard procedures [14,17]. Briefly, it includes the following steps: mRNA isolation from the cells, cDNA synthesis, NlaIII digestion of cDNAs, 3′cDNA collection, tag releasing from 3′ cDNA, ditags formation, ditag concatemerization, cloning, and DNA sequencing. SAGE tag sequences were extracted from the raw sequences using SAGE300 software. The SAGE data is deposited in NCBI with accession number GSE3025 (www.ncbi.nlm.nih.gov/projects/geo).
2.4 SAGE data analysis
To determine the gene origin of SAGE tags, the experimental SAGE tags were matched to the SAGEmap database (www.ncbi.nlm.nih/SAGEmap). A SAGE tag is assigned to a gene if it has a match in the reference database; and a SAGE tags is defined as a novel tag if it has no match in the SAGEmap database. To identify a specific gene for the SAGE tags shared by multiple genes in SAGEmap database, these tags were matched to a tissue-specific SAGE annotation database under the cell type “HL-60” (www.basic.northwestern.edu/SAGE/). By using the microarray expression data from the specific tissue type to annotate the SAGE tags collected from the same tissue type, this database provides high accuracy of gene prediction for SAGE tags shared by multiple genes (Ge et al., manuscript in preparation). To identify the differences in SAGE tags between the control and exposed cells, the method of Audic and Claverie (; http://telethon.bio.unipd.it/bioinfo/IDEG6_form/), a statistical method designed for SAGE analysis, was used for the comparison under P < 0.05 as the cut-off. Greater than 4-fold differences between samples was set as the second cut-off threshold to provide high confidence for the identification of alternatively expressed genes between different samples. To visualize the changes of gene expression, the “Cluster” and “Treeview” programs were used to generate the average linkage hierarchical clustering using Pearson’s correlation coefficient as a distance metrics . The Gene Ontology “biological process” terms were used to identify the functional categories of RF-response genes at P < 0.05 (; http://www.geneontology.org