The authors have declared that no competing interests exist.
Conceived and designed the experiments: CCR BLI. Performed the experiments: CCR LEE EKM IE. Analyzed the data: CCR RDG GPT EKM IE RAB. Contributed reagents/materials/analysis tools: RDG GPT IE BLI. Wrote the paper: CCR RDG GPT HTB BLI RAB.
Nanosecond electrical pulse (nsEP) exposure activates signaling pathways, produces oxidative stress, stimulates hormone secretion, causes cell swelling and induces apoptotic and necrotic death. The underlying biophysical connection(s) between these diverse cellular reactions and nsEP has yet to be elucidated. Using global genetic analysis, we evaluated how two commonly studied cell types, U937 and Jurkat, respond to nsEP exposure. We hypothesized that by studying the genetic response of the cells following exposure, we would gain direct insight into the stresses experienced by the cell and in turn better understand the biophysical interaction taking place during the exposure. Using Ingenuity Systems software, we found genes associated with cell growth, movement and development to be significantly up-regulated in both cell types 4 h post exposure to nsEP. In agreement with our hypothesis, we also found that both cell lines exhibit significant biological changes consistent with mechanical stress induction. These results advance nsEP research by providing strong evidence that the interaction of nsEPs with cells involves mechanical stress.
Cell exposure to high intensity millisecond and microsecond electrical pulses (electroporation) is theorized to cause the formation of membrane pores. These “electro-pores” allow for the transfer of genetic and proteomic material, drugs and chemicals into a cell, for the purpose of inducing a biochemical change [
Events associated with nsEP exposure that can cause changes in gene expression have been identified. Using high speed imaging, Beier et al. observed a rapid increase in intracellular calcium originating from membrane regions closest to the electrodes, illustrating a unique directionality to the nsEP response [
To better characterize and understand this stress, and hopefully shed light on the biophysical mechanisms responsible for nanoporation, we performed a microarray analysis of both U937 and Jurkat cells exposed to 100 nsEPs at a duration of 10 ns and an electric field of 150kV/cm. Real-time quantitative PCR and luminex multiplexing assays were used to confirm the microarray data. The genomics and proteomic data presented in this paper provide the genetic evidence necessary to characterize the nature of the stress endured by both cells types when exposed to nsEP. This is the first time global genetic analysis has been applied to the cells exposed to nsEP.
The 10-ns exposure system used in this study has been previously described in great detail [
A) Drawing of the complete 10-ns set up, including the Tektronix ocilloscope, Glassman high voltage power supply and custom contol module for regulating the pressure of SF6 in the spark gap chamber. B) This is an enhanced view of the cuvette and its placement/orientation in regards to the pulser.
Both Jurkat (ATCC-TIB-152) and U937 (ATCC-CRL-1593.2) cells were acquired from ATCC (Manassas, VA) and sub-cultured according to supplier’s protocol. All cells were maintained at 37°C/5% CO2/95% humidity. Cells were grown and exposed in complete growth medium (ATCC, RPMI-1640 supplemented with 10% FBS, 1% Penicillin/Streptamycin). All cells were counted using the Countess® Cell Counter from Life Technologies (Grand Island, NY) and the final concentration was adjusted to 1200 cells/μL. The cells were then aliquoted into electroporation cuvettes with a 1mm gap between plates (150 μL volume). The cuvettes were exposed to either 100, 10 ns electrical pulses at 150kV/cm or they were sham exposed. nsEP and sham exposures occurred in a random fashion. The sham control samples were treated identically to the nsEP exposed samples except, when they were placed on the pulser, zero power was applied. Following either sham or nsEP exposure, the cells were transferred into a well plate in triplicate and incubated in the appropriate cell culture conditions for the allotted time necessary for each assay. In order to induce heat shock stress, cells were placed in identical electroporation cuvettes and incubated in a circulating water bath at 44°C for 40 minutes [
Cellular viability was evaluated 0.5, 4 and 24 h post-exposure using MTT (3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assays, as per manufacturer’s instructions (ATCC). In brief, cells were exposed to nsEP and incubated at 37°C/5% CO2/95% humidity for a predetermined amount of time. 10 μL of MTT reagent was then added to each well and incubated for 2 h. After incubation, 100 μL of detergent was added to each well, the plate was covered in foil, placed on an orbital shaker at 100 rpm and incubated at room temperature overnight. The absorbance was measured at 570 nm with a Synergy HT Plate Reader (BioTek, Winooski, VT). A ladder of serial dilutions of cells (103 to 106 cells) in culture medium was prepared and absorbance measurements were conducted. The absorbance values were plotted versus the cell number and curves were generated and used to determine the number of viable cells in each well. A two-tailed unpaired t-test was performed using GraphPad Prism (GraphPad Software, Inc, La Jolla, CA).
Cells were prepared and exposed identically as in cell viability experiments (section 2.3). FITC-Annexin V and propidium iodide were added to each sample at 10μL/mL and 2μL/mL respectively. Both reagents were added to the cells within 5 minutes of nsEP exposure and then were allowed to incubate in the exposure media at room temperature (26°C) for 10 minutes to insure proper fluorescent staining. The effects of 10-ns exposures were analyzed using an Accuri Flow Cytometer from BD Biosciences (San Jose, California). A total volume of 75 μL of media was analyzed resulting in typical cellular counts of ~40,000 cells. Cellular expression was measured for each individual channel using sham exposure and digitonin (0.4%) exposures as positive and negative controls. A single threshold was determined and percent of cells expressing each dye was measured. A two-tailed unpaired t-test was performed using GraphPad Prism. Digitonin (Sigma-Aldrich, St. Louis, MO), a non-ionic detergent that is routinely used to permeablize cells, was used as a positive control in this assay.
Total RNA was isolated from exposed cells and harvested 4 h after exposure. RNA was isolated with the Qiagen RNeasy Mini Kit and subjected to DNase digestion by the Qiagen RNase-free DNase Kit (QIAGEN Inc. Valencia, CA). RNA quantity was assessed by UV spectrometry at 260 nm / 280 nm absorbance on a NanoDrop Spectrophotometer (NanoDrop Technologies, Wilmington, DE). RNA quality was assessed on a Agilent Bioanalyzer using the Agilent RNA Nano Chips (Agilent Technologies, Waldbronn Germany).
Gene expression analysis was performed in triplicate (three sham, three nsEP exposed and three heat-shock treated) using the Affymetrix GeneChip® Human Genome U133 (HG-U133) plus 2.0 Array that contains 54,675 probe sets. Briefly, two micrograms of RNA were used for preparation of biotin-labeled targets (cRNA) using MessageAmp™-based protocols (Ambion, Inc., Austin, TX). Labeled cRNA was fragmented (0.5 μg/μL per reaction) and used for array hybridization and washing. The cRNA was mixed with a hybridization cocktail, heated to 99°C for 5 min and then incubated at 45°C for 5 min. Hybridization arrays were conducted for 16 h in an Affymetrix Model 640 hybridization oven (45°C, and 60 rpm). Arrays were washed and stained on an FS450 Fluidics station and were scanned on a GeneChip® Scanner 3000 7G. Image signal data, detection calls and annotations were generated for every gene using the Affymetrix Statistical Algorithm MAS 5.0 (GeneChip® Operating Software v1.3). A log2 transformation was conducted and a Student’s t-test was performed for comparison of the nsEP exposed samples to the two control groups (sham and heat-shocked). We conducted multiple testing correction—Benjamini and Hochberg—to determine the false discovery rate, and statistically significant genes were identified using Bonferroni correction procedures.
For interpretation of the results, the Ingenuity Pathways Analysis tool (IPA version 8.7, Ingenuity® Systems Inc., Redwood City, CA) was used. IPA is a web-based software application, which enables filtering and dataset comparisons, to identify biological mechanisms, pathways and functions most relevant to experimental datasets or differentially expressed genes. The cut-off criteria for our IPA analysis were: an absolute value of log ratio ≥2 or ≤-2 and a p-value ≤0.05. Other web-based resources, such as the GeneCards® Human Gene Database, the HUGO Gene Nomenclature Committee (HGNC,) and the Gene Ontology Consortium were also used to further supplement the analysis.
Each gene selected for validation was validated by quantitative real time polymerase chain reaction (qRT-PCR) using the Applied Biosystems StepOne™ Plus PCR system from ThermoFisher Scientific (Carlsbad, CA). Pre-made, validated TaqMan® Gene Expression Assays were selected for each gene to be validated (ThermoFisher Scientific). Samples were run in triplicate with all reagents from ThermoFisher Scientific including the TaqMan® One-Step RT-PCR Master Mix. Relative quantification (RQ) values were computed using the StepOne™ Plus software.
Cells were exposed to 10-ns pulse trains, then seeded into three different 12-well plates, and were allowed to incubate for up to twelve hours. One well plate of cells was processed at each time point: 4, 8 and 12 hours post-exposure. The harvested cells were aliquotted in triplicate into microcentrifuge tubes and placed on ice. The tubes were centrifuged at 1,400 rpm for five minutes to pellet the cells. The supernatant fluid was removed and this process was repeated one time using ice-cold PBS to ensure all foreign matter was removed before the cells were lysed by adding Complete Cell Extraction buffer from ThermoFisher Scientific (1% Triton X-100, 20 mM Tris-HCL, pH 7.4, 100 mM NaCl, 0.1 M EDTA, 0.2% SDS, 0.2 mM PMSF and 0.1 mM Leupepsin). The cell lysates were vortexed for two minutes. The lysate was clarified by centrifugation at 10,000 × g for 20 minutes at 4°C. The supernatant was collected and analyzed for protein content using a bicinchoninic acid (BCA) protein assay kit (Pierce™, Rockford, IL) and the analysis of the individual proteins was carried out via Luminex’s bead-based multiplexing immunoassay (EMD Millipore, Billerica, MA) following the manufacturer’s protocol. Briefly, the cell lysates were diluted 1:1 in assay buffer and 5 μg of total protein (25 μl/well) was loaded into the 96-well immunoassay plate along with lysate from positive controls (unstimulated HepG2 cells). Antibody-immobilized beads were added to each well and incubated for 2 h at room temperature (RT) followed by a 1 h incubation with detection antibodies. A streptavidin substrate was then added to each well and incubated for 30 minutes at RT after which the plate was run on a Luminex 200TM. The MILLIPLEX® multiplex detection assay is a rapid alternative to Western blotting and immunoprecipitation. Assays such as this, have the capacity for multiple, conjugated beads to be added to each sample resulting in the ability to obtain multiplexed results from every sample. Two different MILLIPLEX® multiplex detection assay were used, one testing proteins identified in the MAPK/SAPK pathway (MILLIPLEX MAP MAPK/SAPK Signaling 10-Plex Kit—Cell Signaling Multiplex Assay) and the other identifying proteins connected to the oxidative stress response pathway (MILLIPLEX MAP Human Oxidative Stress Magnetic Bead Panel—Cellular Metabolism Multiplex Assay).
We assessed the viability of both Jurkat and U937 cells at 0, 4 and 24 hours post nsEP exposure.
A) Viability of U937 cells exposed to 100 x 10 ns pulses at 150 kV/cm. The lowest level of viability occurred 24 h post exposure. B) Viability of Jurkat cells exposed to 100 x 10 ns pulses at 150 kV/cm. The lowest level of viability occurred 4 h post exposure. C) Phosphatidylserine (PS) and propidium iodide (PI) expression in U937 cells exposed to 100 x 10 ns pulses at 150 kV/cm. D) Phosphatidylserine (PS) and propidium iodide (PI) expression in Jurkat cells exposed to 100 x 10 ns pulses at 150 kV/cm. Heat shock (exposure of cells to 44°C for 40 min) is a stress (apoptosis) control. Digitonin was the positive (necrotic) control.
FITC-Annexin V and propidium iodide (PI) dyes were used to measure the structure and permeability of the plasma membranes for each cell line exposed to nsEP. FITC-Annexin V dye is used to detect externalization of phosphatidylserine (PS), possibly indicating plasma membrane disruption. We used propidium iodide to detect the formation of nanopores.
The mRNA from Jurkat and U937 cells exposed to either thermal or nsEP stress was analyzed using standard microarray data analysis techniques. The nsEP exposed samples were compared to sham exposed samples and the log ratio for each gene was plotted with respect to their respective p-values. The resultant volcano plots are displayed in
UniGene ID | Gene name | Symbol | Fold change 150kVnsEP vs. sham | p-Value 150kv nsEP vs. sham |
---|---|---|---|---|
Hs.446125 | male germ cell-associated kinase | MAK | 4.483 | 0.00081 |
Hs.155111 | hepatitis A virus cellular receptor 2 | HAVCR2 | 4.453 | 0.00479 |
Hs.351316 | transmembrane 4 L six family member 1 | TM4SF1 | 4.417 | 0.01954 |
Hs.154057 | matrix metalloproteinase 19 | MMP19 | 4.122 | 0.00389 |
Hs.370036 | chemokine (C-C motif) receptor 7 | CCR7 | 4.022 | 0.00779 |
Hs.551526 | Brain-specific protein p25 alpha | TPPP | 3.991 | 0.00274 |
Hs.267038 | premature ovarian failure, 1B | POF1B | 3.974 | 0.00078 |
Hs.369063 | Zic family member 2 | ZIC2 | 3.944 | 0.00019 |
Hs.351316 | transmembrane 4 L six family member 1 | TM4SF1 | 3.896 | 0.00504 |
Hs.315369 | aquaporin 4 | AQP4 | 3.886 | 0.00755 |
Hs.129794 | spermatogenesis associated 12 | SPATA12 | 3.745 | 0.00410 |
Hs.414795 | serine (or cysteine) proteinase inhibitor, clade E | SERPINE1 | 3.692 | 0.00591 |
Hs.362807 | interleukin 7 receptor /// interleukin 7 receptor | IL7R | 3.652 | 0.02727 |
Hs.436298 | epithelial membrane protein 1 | EMP1 | 3.638 | 0.00018 |
Hs.436550 | Na2+ channel, voltage gated, type VIII, alpha subunit | SCN8A | 3.606 | 0.02903 |
Hs.504908 | LIM domain only 3 (rhombotin-like 2) | LMO3 | 3.551 | 0.00110 |
Hs.91791 | Transmembrane protein 16C | TMEM16C | 3.468 | 0.00232 |
Hs.249718 | eukaryotic translation initiation factor 4E | EIF4E | 3.417 | 0.01264 |
Hs.514665 | DLGAP1 antisense RNA 2 | DLGAP1-AS2 | 3.404 | 0.00187 |
Hs.2258 | matrix metallopeptidase 10 (stromelysin 2) | MMP10 | 3.331 | 0.02632 |
Hs.388715 | small leucine-rich protein 1 | SMLR1 | -3.009 | 0.02216 |
Hs.433586 | PPP5 tetratricopeptide repeat domain containing 1 | PPP5D1 | -3.032 | 0.00243 |
Hs.534859 | Kazal-type serine peptidase inhibitor domain 1 | KAZALD1 | -3.066 | 0.00610 |
Hs.177193 | synaptotagmin IX | SYT9 | -3.082 | 0.00727 |
Hs.195298 | sarcoglycan, zeta | SGCZ | -3.114 | 0.00341 |
Hs.549092 | suppression of tumorigenicity 18, zinc finger | ST18 | -3.199 | 0.00272 |
Hs.322444 | RAMP2 antisense RNA 1 | RAMP2-AS1 | -3.224 | 0.00613 |
Hs.4290 | RAB3C, member RAS oncogene family | RAB3C | -3.255 | 0.00912 |
Hs.208544 | potassium channel, subfamily K, member 1 | KCNK1 | -3.273 | 0.00093 |
Hs.537383 | olfactory receptor, family 5, subfamily H, member 1 | OR5H1 | -3.290 | 0.00431 |
Hs.549149 | catenin (cadherin-associated protein), alpha 3 | CTNNA3 | -3.323 | 0.03010 |
Hs.131152 | long intergenic non-protein coding RNA 643 | LINC00643 | -3.372 | 0.02482 |
Hs.408453 | Wilms tumor 1 | WT1 | -3.440 | 0.00425 |
Hs.471162 | Ras association (RalGDS/AF-6) and pleckstrin homology domains 1 | RAPH1 | -3.563 | 0.00105 |
Hs.274264 | visual system homeobox 1 | VSX1 | -3.633 | 0.00772 |
Hs.27043 | K+ voltage-gated channel, subfamily H member 5 | KCNH5 | -3.687 | 0.00549 |
Hs.387367 | cytochrome P450, family 39, subfamily A, polypeptide 1 | CYP39A1 | -3.693 | 0.01892 |
Hs.147471 | zinc finger protein 749 | ZNF749 | -3.713 | 0.00114 |
Hs.173536 | protein kinase D3 | PRKD3 | -3.882 | 0.00010 |
Hs.440722 | zinc finger protein 587 | ZNF417 | -3.996 | 0.00115 |
Hs.146040 | chromosome 14 open reading frame 105 | C14orf105 | -4.364 | 0.00018 |
UniGene ID | Gene name | Symbol | Fold change 150kVnsEP vs. sham | p-Value 150kv nsEP vs. sham |
---|---|---|---|---|
Hs.25647 | v-fos FBJ murine osteosarcoma viral oncogene homolog | FOS | 7.269 | 0.00031 |
Hs.326035 | Early growth response 1 | EGR1 | 5.213 | 0.00031 |
Hs.326035 | early growth response 1 | EGR1 | 4.941 | 0.00029 |
Hs.549031 | early growth response 4 | EGR4 | 4.472 | 0.00244 |
Hs.326035 | early growth response 1 | EGR1 | 4.349 | 0.00009 |
Hs.494326 | basic leucine zipper nuclear factor 1 (JEM-1) | BLZF1 | 4.106 | 0.00281 |
Hs.1395 | early growth response 2 | EGR2 | 3.981 | 0.02375 |
Hs.536535 | dual specificity phosphatase 16 | DUSP16 | 3.832 | 0.00036 |
Hs.529512 | zinc finger protein 167 | ZNF167 | 3.700 | 0.01073 |
Hs.525704 | v-jun sarcoma virus 17 oncogene homolog | JUN | 3.606 | 0.00257 |
Hs.195398 | oligodendrocyte transcription factor 3 | OLIG3 | 3.604 | 0.01432 |
Hs.413099 | glycine receptor, alpha 3 | GLRA3 | 3.579 | 0.03397 |
Hs.75678 | FBJ murine osteosarcoma viral oncogene homolog B | FOSB | 3.577 | 0.00137 |
Hs.549086 | discs, large (Drosophila) homolog-associated protein 1 | DLGAP1 | 3.523 | 0.00130 |
Hs.532933 | purinergic receptor P2Y, G-protein coupled, 12 | P2RY12 | 3.499 | 0.00649 |
Hs.525704 | v-jun sarcoma virus 17 oncogene homolog | JUN | 3.466 | 0.00004 |
Hs.519601 | Inhibitor of DNA binding 4, dominant negative helix-loop-helix | ID4 | 3.400 | 0.00024 |
Hs.56247 | inducible T-cell co-stimulator | ICOS | 3.390 | 0.00468 |
Hs.162246 | transmembrane protein 171 | TMEM171 | 3.265 | 0.01988 |
Hs.498513 | aldo-keto reductase family 1, member C2 | AKR1C1/AKR1C2 | 3.232 | 0.00894 |
Hs.369263 | PDS5, regulator of cohesion maintenance, homolog B (S. cerevisiae) | PDS5B | -3.059 | 0.03108 |
Hs.24115 | miR-17-92 cluster host gene (non-protein coding) | MIR17HG | -3.098 | 0.04827 |
Hs.510093 | Abelson helper integration site 1 | AHI1 | -3.113 | 0.00354 |
Hs.551839 | uncharacterized LOC284600 | LOC284600 | -3.155 | 0.04887 |
Hs.159234 | forkhead box E1 (thyroid transcription factor 2) | FOXE1 | -3.184 | 0.01954 |
Hs.271791 | ATR serine/threonine kinase | ATR | -3.186 | 0.00019 |
Hs.525700 | small nuclear ribonucleoprotein polypeptide N | SNRPN | -3.377 | 0.00003 |
Hs.371903 | glycophorin E (MNS blood group) | GYPE | -3.398 | 0.01643 |
Hs.72901 | cyclin-dependent kinase inhibitor 2B (p15, inhibits CDK4) | CDKN2B | -3.451 | 0.00363 |
Hs.2799 | hyaluronan and proteoglycan link protein 1 | HAPLN1 | -3.471 | 0.00454 |
Hs.44685 | ring finger protein 141 | RNF141 | -3.474 | 0.04947 |
Hs.549172 | calmodulin-like 4 | CALML4 | -3.495 | 0.00665 |
Hs.54973 | cadherin 26 | CDH26 | -3.551 | 0.03073 |
Hs.519523 | serpin peptidase inhibitor, clade B (ovalbumin), member 6 | SERPINB6 | -3.560 | 0.00003 |
--- | long intergenic non-protein coding RNA 644 | LINC00644 | -3.568 | 0.00450 |
Hs.76561 | zinc finger protein 404 | ZNF404 | -3.603 | 0.00177 |
Hs.170849 | coiled-coil domain containing 122 | CCDC122 | -3.614 | 0.00129 |
Hs.389945 | WD repeat domain 60 | WDR60 | -3.641 | 0.00213 |
Hs.242520 | uromodulin-like 1 | UMODL1 | -3.680 | 0.01025 |
Hs.436380 | MAM domain containing glycosylphosphatidylinositol anchor 2 | MDGA2 | -3.703 | 0.02430 |
Hs.72307 | G protein-coupled receptor 110 | GPR110 | -3.720 | 0.01181 |
A) U937 cells exposed to nsEP had 327 genes significantly up-regulated as compared to sham (≥2 log ratio and p-value ≤ 0.05). 225 genes were significantly down regulated (≤-2 log ratio and p-value ≤ 0.05). B) Jurkat cells exposed to nsEP had 215 genes significantly up-regulated as compared to sham (≥2 log ratio and p-value ≤ 0.05). 206 genes were significantly down regulated (≤-2 log ratio and p-value ≤ 0.05).
The microarray data for each cell line was loaded into Ingenuity Systems IPA pathway analysis software and a core analysis was performed for the top 5000 genes from each set of microarray data. A summary table for each cell line can be found in Tables
Molecular and Cellular Functions | ||
---|---|---|
Function | p-values | # of Molecules |
Cellular Movement | 5.48E-13–1.32E-03 | 455 |
Cell-To-Cell Signaling and Interaction | 1.95E-11–1.28E-03 | 533 |
Cellular Development | 4.35E-08–1.28E-03 | 593 |
Cellular Growth and Proliferation | 9.37E-08–1.28E-03 | 751 |
Cell Death and Survival | 2.65E-07–1.36E-03 | 734 |
Cellular Movement | 1.52E-14–1.10E-03 | 429 |
Cell-To-Cell Signaling and Interaction | 8.03E-08–1.17E-03 | 508 |
Nucleic Acid Metabolism | 1.23E-07–5.33E-05 | 70 |
Small Molecule Biochemistry | 1.23E-07–1.10E-03 | 283 |
Cellular Development | 1.50E-07–1.11E-03 | 575 |
Canonical Pathway | ||
---|---|---|
Function | p-values | # of Molecules |
VDR/RXR Activation | 4.86E-06 | 33/77 (0.429) |
B Cell Development | 9.09E-05 | 15/28 (0.536) |
ILK Signaling | 1.03E-04 | 58/181 (0.32) |
tRNA Splicing | 1.54E-04 | 17/35 (0.486) |
Hepatic Fibrosis / Hepatic Stellate Cell Activation | 1.74E-04 | 61/196 (0.311) |
Hepatic Fibrosis / Hepatic Stellate Cell Activation | 2.9E-06 | 63/196 (0.321) |
G-Protein Coupled Receptor Signaling | 1.17E-05 | 75/254 (0.295) |
LPS/IL-1 Mediated Inhibition of RXR Function | 1.2E-05 | 64/208 (0.308) |
cAMP-mediated signaling | 8.37E-05 | 63/216 (0.292) |
Atherosclerosis Signaling | 1.62E-04 | 39/120 (0.325) |
Canonical pathways are “idealized or generalized pathways”; they are considered to be pathways that have previously been well established and classically characterized. The core analysis function in the IPA software identified the top 5 canonical pathways affected by nsEP exposure (
Comparative analysis of the top 5000 genes changing within in each cell line due to nsEP exposure was conducted. Both cell lines shared 1624 common genes changing due to nsEP exposure. However, only 890 of the shared genes had changed in the same manner, i.e. both up-or both down-regulated. Of these 890 genes, only 59 genes had a log ratio ≥1.0 (fold change = 2) and a p-value of ≤0.05 (
Gene Symbol | Gene name | Jurkat Fold Change | p-Value | U937 Fold Change | p-Value |
---|---|---|---|---|---|
JUN | jun proto-oncogene | 3.606 | 0.0026 | 2.444 | 0.0001 |
VEGFA | vascular endothelial growth factor A | 2.594 | 0.0396 | 1.32 | 0.0146 |
RORA | RAR-related orphan receptor A | 2.569 | 0.0471 | 1.949 | 0.0072 |
MXD1 | MAX dimerization protein 1 | 2.354 | 0.0095 | 1.635 | 0.0072 |
ATF3 | activating transcription factor 3 | 2.301 | 0.0005 | 1.216 | 0.0014 |
PPP1R15A | protein phosphatase 1, regulatory subunit 15A | 2.298 | 0.0032 | 2.21 | 0.0002 |
NDUFA10 | NADH dehydrogenase (ubiquinone) 1 alpha, 10, 42kDa | 2.286 | 0.0018 | 1.83 | 0.0424 |
BHLHE40 | basic helix-loop-helix family, member e40 | 2.235 | 0.0338 | 1.253 | 0.0013 |
LDLR | low density lipoprotein receptor | 2.218 | 0.0096 | 2.463 | 0.0386 |
NRP2 | neuropilin 2 | 2.082 | 0.0295 | 3.022 | 0.0031 |
SASH1 | SAM and SH3 domain containing 1 | 2.081 | 0.0000 | 1.768 | 0.0204 |
TBX3 | T-box 3 | 2.024 | 0.0420 | 2.052 | 0.0060 |
DOCK4 | dedicator of cytokinesis 4 | 1.942 | 0.0134 | 1.307 | 0.0303 |
SLC7A11 | solute carrier family 7 member 11 | 1.875 | 0.0041 | 2.309 | 0.0040 |
ULK2 | unc-51 like autophagy activating kinase 2 | 1.848 | 0.0293 | 1.38 | 0.0177 |
S1PR3 | sphingosine-1-phosphate receptor 3 | 1.824 | 0.0463 | 1.18 | 0.0047 |
DUSP10 | dual specificity phosphatase 10 | 1.821 | 0.0046 | 1.571 | 0.0108 |
CHD2 | chromodomain helicase DNA binding protein 2 | 1.75 | 0.0034 | 1.511 | 0.0231 |
TSC22D3 | TSC22 domain family, member 3 | 1.729 | 0.0370 | 1.807 | 0.0408 |
CACNB2 | calcium channel, voltage-dependent, beta 2 subunit | 1.718 | 0.0290 | 2.412 | 0.0409 |
EYA3 | EYA transcriptional coactivator and phosphatase 3 | 1.613 | 0.0322 | 2.8 | 0.0480 |
RNA45S5 | RNA, 45S pre-ribosomal 5 | 1.599 | 0.0003 | 2.887 | 0.0009 |
CREBRF | CREB3 regulatory factor | 1.578 | 0.0267 | 1.092 | 0.0232 |
RNF31 | ring finger protein 31 | 1.545 | 0.0488 | 1.72 | 0.0123 |
CAMK2B | calcium/calmodulin-dependent protein kinase II beta | 1.529 | 0.0252 | 1.706 | 0.0387 |
KLF6 | Kruppel-like factor 6 | 1.473 | 0.0016 | 1.939 | 0.0029 |
SESN2 | sestrin 2 | 1.463 | 0.0123 | 1.606 | 0.0000 |
MASP2 | mannan-binding lectin serine peptidase 2 | 1.448 | 0.0179 | 2.265 | 0.0283 |
ARG1 | arginase 1 | 1.382 | 0.0441 | 1.386 | 0.0430 |
NPR1 | natriuretic peptide receptor 1 | 1.362 | 0.0080 | 2.291 | 0.0118 |
TM4SF1 | transmembrane 4 L six family member 1 | 1.349 | 0.0249 | 4.417 | 0.0195 |
FAM122C | family with sequence similarity 122C | 1.31 | 0.0341 | 1.058 | 0.0162 |
JUND | jun D proto-oncogene | 1.308 | 0.0042 | 1.733 | 0.0057 |
SPATA6 | spermatogenesis associated 6 | 1.27 | 0.0237 | 1.924 | 0.0105 |
PHLDA1 | pleckstrin homology-like domain, family A, member 1 | 1.142 | 0.0074 | 2.861 | 0.0002 |
NEU1 | sialidase 1 (lysosomal sialidase) | 1.134 | 0.0296 | 1.201 | 0.0014 |
CD55 | CD55 molecule, decay accelerating factor for complement | 1.11 | 0.0324 | 1.321 | 0.0062 |
ABL2 | ABL proto-oncogene 2, non-receptor tyrosine kinase | 1.079 | 0.0455 | 1.267 | 0.0052 |
SKIL | SKI-like proto-oncogene | 1.073 | 0.0026 | 1.554 | 0.0302 |
HAO2 | hydroxyacid oxidase 2 (long chain) | 1.042 | 0.0494 | 1.618 | 0.0393 |
MAFF | v-maf avian musculoaponeurotic fibrosarcoma oncogene F | 1.007 | 0.0170 | 1.653 | 0.0022 |
MEX3D | mex-3 RNA binding family member D | -1.045 | 0.0318 | -2.098 | 0.0012 |
EBF3 | early B-cell factor 3 | -1.082 | 0.0122 | -1.047 | 0.0403 |
ZNF205 | zinc finger protein 205 | -1.083 | 0.0039 | -2.33 | 0.0060 |
PPIL2 | peptidylprolyl isomerase (cyclophilin)-like 2 | -1.123 | 0.0417 | -2.111 | 0.0041 |
XIRP2 | xin actin-binding repeat containing 2 | -1.19 | 0.0204 | -2.27 | 0.0255 |
TEX14 | testis expressed 14 | -1.22 | 0.0002 | -1.113 | 0.0242 |
CLECL1 | C-type lectin-like 1 | -1.23 | 0.0407 | -2.337 | 0.0097 |
HNRNPD | heterogeneous nuclear ribonucleoprotein D | -1.307 | 0.0083 | -1.545 | 0.0113 |
GABBR2 | gamma-aminobutyric acid (GABA) B receptor, 2 | -1.32 | 0.0411 | -1.784 | 0.0319 |
PPP2R5A | protein phosphatase 2, regulatory subunit B', alpha | -1.38 | 0.0121 | -1.722 | 0.0199 |
GPR98 | G protein-coupled receptor 98 | -1.515 | 0.0408 | -1.46 | 0.0232 |
SATB1 | SATB homeobox 1 | -1.97 | 0.0350 | -1.548 | 0.0003 |
RERE | arginine-glutamic acid dipeptide (RE) repeats | -2.105 | 0.0373 | -2.224 | 0.0488 |
FERMT1 | fermitin family member 1 | -2.548 | 0.0123 | -1.4 | 0.0182 |
TSEN54 | TSEN54 tRNA splicing endonuclease subunit | -2.707 | 0.0058 | -1.638 | 0.0389 |
PHLPP1 | PH domain and leucine rich repeat protein phosphatase 1 | -2.862 | 0.0066 | -1.037 | 0.0132 |
HAPLN1 | hyaluronan and proteoglycan link protein 1 | -3.471 | 0.0045 | -2.922 | 0.0221 |
We validated microarray expression for 3 common genes in both U937 and Jurkat cells. qRT-PCR was performed for the putative transforming gene of avian sarcoma virus 17, commonly known as
A) Comparison of the expression levels of JUN for U937 cells exposed to nsEP. B) Comparison of the expression levels of JUN for Jurkat cells exposed to nsEP. C) Comparison of the expression levels of DUSP10 for U937 cells exposed to nsEP. D) Comparison of the expression levels of DUSP10 for Jurkat cells exposed to nsEP. E) Comparison of the expression levels of HPRT1 for U937 cells exposed to nsEP. F) Comparison of the expression levels of HPRT1 for Jurkat cells exposed to nsEP. Mean and standard deviation are plotted as the green and black lines respectively.
In an effort to link genetic and proteomic data, we performed a bead based multiplexing assay for the MAPK pathway. The bead based kit was used to look for changes in
A) Levels of MAPK proteins for U937 at 4 h post exposure. B) Levels of MAPK proteins for Jurkat at 4 h post exposure. C) Levels of MAPK proteins for U937 at 8 h post exposure. D) Levels of MAPK proteins for Jurkat at 8 h post exposure. E) Levels of MAPK proteins for U937 at 12 h post exposure. F) Levels of MAPK proteins for Jurkat at 12 h post exposure. Error bars represent standard deviation (SD).
Proteins associated with oxidative stress were also surveyed via Luminex multiplexing bead assay. The human oxidative stress magnetic bead panel was used to measure the amount of
A) Levels of oxidative stress proteins for U937 at 4 h post exposure. B) Levels of oxidative stress proteins for Jurkat at 4 h post exposure. C) Levels of oxidative stress proteins for U937 at 8 h post exposure. D) Levels of oxidative stress proteins for Jurkat at 8 h post exposure. E) Levels of oxidative stress proteins for U937 at 12 h post exposure. F) Levels of oxidative stress proteins for Jurkat at 12 h post exposure. Error bars represent standard deviation (SD).
The viability (MTT) and cell flow data clearly show that both cells lines are affected by the nsEP exposure parameters used in this paper. Jurkat cells have been used extensively in nsEP research [
The microarray data presented here is a mere snapshot of the molecular changes that occurred within these cells 4 h post exposure. Both the Jurkat and U937 cells have approximately the same number of genes changing (400–500 genes each) despite their different responses to nsEP exposure (viability and PS expression). This number of genes is low in comparison to a heat shock stress which causes approximately 1200 genes to have a significant response (
The most striking finding of this entire study is the indication by the IPA software (based on the gene profiles) that the major cellular/molecular function affected by nsEP exposure is cellular growth/development/movement. This is in stark contrast to the MTT data. The viability data suggests the Jurkat cells are quite susceptible to the effects of nsEP with only 23% of the cells surviving at 4 h post exposure. Based on the loss of viability, we expected the genetic profile to indicate possibly necrotic or apoptotic gene pathway up-regulation, but instead, cellular growth development/movement functions are indicated as the top functions up-regulated in each cell line following nsEP exposure.
Despite these findings, identification of a dominant pathway was not possible. The increase in cellular growth development/movement functions is not the result of an individual pathway, but rather is the result of an intricate network of many pathways. Therefore, given this level of complexity, we analyzed individual genes, their response to stress and their associated pathways. Analysis of the top 20 genes changing in both cell lines indicated many of these genes play important roles in the cellular response to mechanical stress (
Gene Name | Symbol | Function (from NCBI Resources: Gene) | Cell |
---|---|---|---|
male germ cell-associated kinase | MAK | serine/threonine protein kinase related to kinases involved in cell cycle regulation | U937 |
v-jun sarcoma virus 17 oncogene homolog | JUN | interacts directly with specific target DNA sequences to regulate gene expression, part of the JNK pathway | U937/ Jurkat |
FBJ murine osteosarcoma viral oncogene homolog | FOS | regulator of cell proliferation, differentiation, and transformation. | Jurkat |
Early Growth Response 1 | EGR1 | induces the expression of growth factors, growth factor receptors, extracellular matrix proteins, proteins involved in the regulation of cell growth or differentiation, and proteins involved in apoptosis, growth arrest, and stress responses | Jurkat |
Early Growth Response 4 | EGR4 | cell proliferation by increased expression of potassium chloride cotransporter 2b (KCC2b) | Jurkat |
basic leucine zipper nuclear factor 1 | BLZF1 | regulation of cell growth | Jurkat |
Early Growth Response 2 | EGR2 | mediates NFκB and MAPK signaling | Jurkat |
dual specificity phosphatase 10 | DUSP10 | regulates the c-Jun amino-terminal kinase (JNK) and extracellular signal-regulated kinase (ERK) pathways | U937 Jurkat |
dual specificity phosphatase 16 | DUSP16 | regulates the c-Jun amino-terminal kinase (JNK) and extracellular signal-regulated kinase (ERK) pathways | Jurkat |
flavin containing monooxygenase 3 | FMO3 | transmembrane protein localizes to the endoplasmic reticulum | U937 |
transmembrane 4 L six family member 1 | TM4SF1 | molecular organizer that interacts with membrane and cytoskeleton-associated proteins | U937 |
matrix metalloproteinase 19 | MMP19 | breakdown of extracellular matrix | U937 |
premature ovarian failure, 1B | POF1B | binds non-muscle actin filaments | U937 |
Brain-specific protein p25 alpha | TPPP | binds to tubulin and microtubules and induces aberrant microtubule assemblies | U937 |
aquaporin 4 | AQP4 | function as water-selective channels in the plasma membranes | U937 |
Anoctamins | TMEM16C | phospholipid scrambling | U937 |
matrix metalloproteinase 10 (stromelysin 2) | MMP10 | breakdown of extracellular matrix | U937 |
Annexin A1 | ANXA1 | membrane-localized protein that binds phospholipids | U937 |
glycine receptor, alpha 3 | GLRA3 | encodes a member of the ligand-gated ion channel protein family | Jurkat |
chemokine (C-C motif) receptor 7 | CCR7 | member of the G protein-coupled receptor family | U937 |
regulator of G-protein signaling 1 | RGS1 | attenuates the signaling activity of G-proteins by binding to activated, GTP-bound G alpha subunit | U937 |
polycystic kidney disease 1 like 1 | PKD1L1 | novel G-protein-binding protein. Ca2+-permeable pore-forming subunits and receptor-like integral membrane proteins | U937 |
purinergic receptor P2Y, G-protein coupled, 12 | P2RY12 | belongs to the family of G-protein coupled receptor | Jurkat |
Given the level of gene expression associated with cellular growth and the apparent activation of the MAPK pathway, we correlated gene expression with protein levels using a quantitative Luminex assay. The MAPK pathway can be activated by mitogens or through certain stress pathways. Activation of the MAPK pathway in response to nsEP has been shown before, however, it was not linked to a specific genetic response [
Of the top 10 significantly changing genes in response to nsEP, EGR1 appears 3 times, with EGR4 and EGR2 appearing once each. ERG genes have been associated with MAPK pathway activation, but also, they have also been found to be up-regulated as part of the antioxidative response [
Based on the genetic response of both cell lines, it appears that these cells respond to nsEP as a mechanical stress. It has been reported in other studies that osteoblasts undergoing mechanical stretch, preferentially up-regulated FOS, JUN, and EGR1, 2, and 3 genes [
Although circumstantial, other data suggests that nsEP exposure can induce mechanical stress on cells. Biomarkers of mechanical stress and the observed bioeffects of nsEP exposure are strikingly similar. Markers of mechanical stress include calcium release from the endoplasmic reticulum [
The findings presented in this paper provide strong evidence that cells exposed to nsEP experience a stress that is interpreted as being mechanical in nature. It is important to note that we did not control for swelling in these experiments. However, it is unlikely that colloid osmotic swelling of these cells is responsible for the specific changes in mechanical stress associated gene expression. These exposures were performed in full growth medium, and analysis of the forward scattering (FSC-H) data collected from the flow cytometry analysis indicated that swelling did not occur (
We feel that these findings are important in the field of bioelectrics, because it suggests for the first time that the cells exposed to nsEP experience a mechanical stress of significant amplitude to elicit a specific genetic response. Although it is not explicitly mentioned by or accounted for by other nsEP researchers, mechanical stress, whether caused by electrodeformation [
Further work is underway to identify the source of the mechanical stress and quantify the amount of force generated by each of the previously identified sources of mechanical stress. The overall goal of future work will be to determine how and to what degree each source of mechanical stress contributes to the nanoporation phenomena or to other cellular reactions. Understanding the mechanisms responsible for the bioeffects associated with nsEP exposure is critical to the continued development and application of this technology.
U937 cells exposed to thermal stress had 1058 genes significantly up-regulated as compared to sham (≥2 log ratio and p-value ≤ 0.05). 101 genes were significantly down regulated (≤-2 log ratio and p-value ≤ 0.05).
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Jurkat cells exposed to thermal stress had 1004 genes significantly up-regulated as compared to sham (≥2 log ratio and p-value ≤ 0.05). 158 genes were significantly down regulated (≤-2 log ratio and p-value ≤ 0.05).
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Genes were selected based on log ratio (≥2, or ≤ -2) and with a p-value of ≤ 0.05.
(DOCX)
Genes were selected based on log ratio (≥2, or ≤ -2) and with a p-value of ≤ 0.05.
(DOCX)
Genes were selected based on log ratio (≥2, or ≤ -2) and with a p-value of ≤ 0.05.
(DOCX)
Genes were selected based on log ratio (≥2, or ≤ -2) and with a p-value of ≤ 0.05.
(DOCX)
Mr. Roth is a SMART Scholar and is supported by the OSD-T&E (Office of Secretary Defense-Test and Evaluation), Defense–Wide / PE0601120D8Z National Defense Education Program (NDEP) / BA-1, Basic Research.