The microRNAs (miRNAs) function as global negative regulators of gene expression and have been associated with a multitude of biological processes. The dysfunction of the microRNAome has been linked to various diseases including cancer. Our laboratory recently reported modulation in the expression of miRNA in a variety of cell types exposed to ionizing radiation (IR). To further understand miRNA role in IR-induced stress pathways, we catalogued a set of common miRNAs modulated in various irradiated cell lines and generated a list of predicted target genes. Using advanced bioinformatics tools we identified cellular pathways where miRNA predicted target genes function. The miRNA-targeted genes were found to play key roles in previously identified IR stress pathways such as cell cycle, p53 pathway, TGF-beta pathway, ubiquitin-mediated proteolysis, focal adhesion pathway, MAPK signaling, thyroid cancer pathway, adherens junction, insulin signaling pathway, oocyte meiosis, regulation of actin cytoskeleton, and renal cell carcinoma pathway. Interestingly, we were able to identify novel targeted pathways that have not been identified in cellular radiation response, such as aldosterone-regulated sodium reabsorption, long-term potentiation, and neutrotrophin signaling pathways. Our analysis indicates that the miRNA interactome in irradiated cells provides a platform for comprehensive modeling of the cellular stress response to IR exposure.
MicroRNAs (miRNAs) are approximately 21 nucleotides in length that do not code for proteins. miRNAs were discovered in 1993 but their significance was not realized until 2000 [
Cellular stress pathways protect cells from the deleterious effects of genotoxic insult. Ionizing radiation disrupts cellular homeostasis through multiple mechanisms. The cells respond to stress induced by ionizing radiation exposure through complex processes by activating many pathways ranging from DNA damage processing, signal transduction, altered gene expression, cell-cycle arrest, and genomic instability to cell death [
Alterations in the miRNA expression levels occur following exposure to ionizing radiation [
We were interested to examine the role of miRNAs in ionizing radiation- (IR-) induced stress pathways. Although miRNAs have been implicated as crucial posttranscriptional gene regulators, their role in the cellular response to IR is not comprehensively examined. We asked the question: can we use microRNAome and their target genes to corroborate previously identified IR responsive pathways? We also argued if the miRNAome would allow us to discover new perspective to radiation exposure. This study was undertaken (1) to assemble miRNA species that are modulated after radiation exposure in many human cell lines, (2) to identify the genes that are targeted by these miRNA using bioinformatics approaches, and (3) to determine the role of miRNA target genes in radiation-induced cellular pathways.
We collected the data from our published work on radiation-induced miRNA and also searched the PubMed database to collect articles that investigated the modulation of miRNA after IR exposure. The keywords miRNA, microRNA, ionizing radiation and radiation were used in performing the literature search. This search retrieved 236 research articles. PubMed was a preferred choice over the other available article databases such as Web of Science, BIOSIS Previews (
The miRNA expression data extracted from the published research articles was used to assemble a database. Over 1000 records were generated from the data extraction procedure. Microsoft Excel was utilized to tabulate the information from various articles. This “mastersheet” formed the platform for the subsequent analysis. The data was organized in the Excel “mastersheet” with the following headings: cell type, cell line, radiation type, radiation dose (Gy), dose rate (Gy/min), analysis time (hours) after treatment, miRNA species, qualitative miRNA expression from base, qualitative miRNA expression from base (numerical), quantitative miRNA expression (fold change), and data source. The Pivot Table tool of Microsoft Excel was employed to reorganize the master dataset. This “pivot table” was referenced to the original unchanged mastersheet. The pivot table allowed to generate a list of miRNA that were observed to show altered expression in 5 or more cell lines after exposure to ionizing radiation.
The miRNAs of interest were assembled in Microsoft Access database then searched against the mirDB dataset (
The output dataset queried through the Access database provided the predicted target genes for the miRNA species of interest. The Entrez ID list was imported in DAVID (Database for Annotation, Visualization andIntegrated Discovery) (
Exposure to ionizing radiation induces various physiological responses including DNA repair, cell cycle arrest, signal transduction, cell death, and cell differentiation [
A variety of cell lines have been exploited to examine the miRNA expression profile after radiation exposure. The lymphoblast TK6 cell line has normal p53 and was used as a base to compare IR-induced miRNA from p53 negative WTK1 cell line [
Radiation-induced miRNA expression analysis in various cell lines.
Cell line | Cell type | Radiation type | Radiation dose (Gy) | Characterized miRNA | Reference |
---|---|---|---|---|---|
A549 | Basal Epithelial | N/A | 2.5 | 8 |
[ |
HBE135-E6E7 | Squamous | N/A | 2.5 | 8 |
[ |
TK6 | Lymphoblast | X-radiation | 0.5 | 21 |
[ |
TK6 | Lymphoblast | X-radiation | 2 | 21 |
[ |
WTK1 | Lymphoblast | X-radiation | 0.5 | 21 |
[ |
WTK1 | Lymphoblast | X-radiation | 2 | 21 |
[ |
HDMEC | Endothelial | X-radiation | 2 | 11 |
[ |
AG1522 | Fibroblast | X-radiation | 0.1 | 7 |
[ |
AG1522 | Fibroblast | X-radiation | 2 | 22 |
[ |
M059J | Glial | X-radiation | 3 | 19 |
[ |
M059K | Glial | X-radiation | 3 | 19 |
[ |
IM9 | B Lymphoblast | Gamma | 1 | 36 |
[ |
IM9 | B Lymphoblast | Gamma | 10 | 26 |
[ |
IM9 | B Lymphoblast | Gamma | 0.5 | 22 |
[ |
IM9 | B Lymphoblast | Gamma | 10 | 22 |
[ |
TK6 | Lymphoblast | Gamma | 2 | 20 |
[ |
Jurkat | T- cell | Gamma | 2 | 20 |
[ |
A549 | Basal epithelial | Gamma | 20 | 12 |
[ |
A549 | Basal epithelial | Gamma | 40 | 18 |
[ |
LNCaP | Epithelial | X-radiation | 6 | 15 |
[ |
C4-2 | Epithelial | X-radiation | 6 | 11 |
[ |
HCT116 (Null) | Epithelial | Gamma | 10 | 36 |
[ |
HCT116 (WT) | Epithelial | Gamma | 10 | 36 |
[ |
We built an miRNA database to warehouse the IR-induced miRNA expression data extracted from various published studies. All of these studies employed low LET radiation and the doses ranged from 0.1 to 40 Gy. The analysis methodology ranged from real-time PCR to microarray techniques. The number of radiation modulated miRNA ranged from 8 to 36 in individual cell lines. The Microsoft Excel’s pivot table from the original “mastersheet” permitted to create a list of miRNA that were modulated in 5 or more cell lines. 20 miRNA species were identified that were modulated in 5 or more cell lines after treatment with IR. The pivot table feature was further exploited to build a heat map of the IR-modulated miRNAs. This heat map displays 3 dimensional information which accounts for cell line, analysis time after IR treatment and the miRNA species (Figure
The modulation of
We next determined the expression status of another twelve miRNA hsa-miR-142-3p, hsa-miR-142-5p, hsa-miR-143, hsa-miR-155, hsa-miR-15a, hsa-miR-16, hsa-miR-17-3p, hsa-miR-17-5p, hsa-miR-18, hsa-miR-19a, hsa-miR-19b, and hsa-miR-21 in irradiated IM9, Jurkat, M059J, M059K, TK6, and WTK1 cells (Figure
The modulation of various miRNAs in different cell lines. The analysis time indicates the period of time that had elapsed after exposure to ionizing radiation. The green color indicates upregulation and red color shows downregulation of a miRNA. The yellow color signifies no change, and the gray color indicates that the miRNAs during those time points were not examined. The orange color signified some conflicting data where it was either reported a no change or downregulation in two or more studies. Similarly the light green color indicates data where it was either reported a no change or upregulation in two or more studies.
The list of miRNAs studied among a group of cell types was further examined to identify the target mRNAs affected by these miRNA. We utilized the miRDB for predicting the miRNA target genes. The miRDB uses a support vector machine (SVM), which is a type of algorithm based on statistical learning theory. This program uses statistics and employs artificial intelligence strategy such as neural networks to assign a prediction score for a miRNA’s target gene. This process of predicting miRNA target genes is accomplished through a machine-learning algorithm, which places a target score on a miRNA-gene association. This miRDB database was chosen to identify miRNA target genes because for the simplicity of the database structure and agreed upon thresholds for the prediction target score. The prediction target score of 50–95 was used to filter the target genes. We constructed association networks between miRNAs and the target mRNAs and visualized the target genes controlled by various IR responsive miRNA with Cytoscape. The complexity associated with miRNA interactome is shown in Figure
miRNA and the predicted target genes identified in biological pathways.
miRNA | Target genes identified in biological pathways |
---|---|
miR-15a, miR-16 | AP2A1, PHKA1, CDC25A, SMAD7, CCNE1, SMURF1, PIK3R1, INSR, SESN1, ARHGAP5, UBE4B, YWHAH, SIAH1, BTRC, RELN, UBE2Q1, FGF2, FASN, WEE1, SGK1, TGFBR1 |
miR-202 | SMAP1, DUSP1, LAMA1 |
miR-155 | VAV3, DET1, RAB11FIP, IGF2 |
miR-197 | IL1RAP, ARHGEF12 |
miR-142-5p | DIAPH2, CUL4A, CCNH, STAG1, RAP1A, UBE2K, TPR, ACTN4, VHL, ATP1B1, ITGAV, CCNG2, UBE2D1, CUL2, HIF1A |
miR-142-3p | WASL, MYLK, TAB2 |
miR-575 | GRIA2, TSG101, MYH10 |
miR-609 | PRKC1, PDPK1, PPP1R3A |
miR-34A | WASF1, PVRL1, FLOT2, VSP37B, COL4A4, DNM1L, PPM1A, CCNE2, RRAS |
miR-34b | YWHAG, DNM3, PDK1, NCKAP1, PRKAR2E |
miR-18a | ATM |
miR-21 | PPP1R3B, NTF3, FRS2, VCL, PPP1R3D, PITX2, UBE2D3, WWP1 |
miR-let 7a, b, c, d, e, f, g, i | IGF1R, ADRB2, MAP4K3, NRAS, E2F5, GDF6 |
miR-143 | CACNA1A, PRKX, UBE2E1, KRAS, LMO7, UBE2E3, ARFGAP3 |
miR-376a | TP53AIP1, G8PC2, PRKAC8 |
miR-19a, miR-19b | RPS6KA5, RAPGEF2, CASP8, VPS37A, CACNA1C, CLTC, ITGB8, LDLR, BMPR2, NCOA4, RAP1B |
miR- 145 | DAB2, AP2B1, TPM3, SMAD2, DUSP6, PPP3CA, PHHKB, SKP1ITGB8, PPP3R2, CRKL, UBA6, PXN |
Visualization of miRNAs and their associated target genes network with Cytoscape. The interaction network shows nodes and connections between miRNAs and the target genes. The yellow nodes represent the miRNA and the pink/red nodes represent its targeted gene. The opacity of the blue edge links signifies the target score between the miRNA and the target gene. The opacity of red nodes represents genes that have been identified to play roles in biological pathways.
We also identified the genes that were controlled by multiple miRNA after exposure to IR. Figure
The regulation of genes with various miRNA. The genes that are controlled by two or more different miRNAs are shown. The green shade identifies the miRNA predicted to regulate that particular gene. The red shade identifies the miRNA that are not predicted to control the expression of the listed gene.
Using the KEGG database we searched for pathways where the miRNA target genes function in order to gain insight into the processes that could be affected by miRNA modulation in irradiated cells. First the mirDB was linked to the Gene Database from the NCBI (National Center for Biotechnology Information) to identify the functions of the specific genes. The Gene Database from the NCBI was retrieved for offline purposes. This database provided descriptive information regarding the functions of miRNA target gene. Second, the Entrez Gene ID was linked to the KEGG pathways database to identify the genes associated with biological pathways. The miRNA target gene dataset was imported into DAVID, a bioinformatics tool that provides functional gene-annotation. The genes associated with various biological pathways were determined with DAVID and the interactions were visualized with Cytoscape (Figure
Mapping of miRNA targets genes to biological pathways. This network depicts the miRNA target genes and the associated biological pathways. The landscape of genes to pathway interactions was visualized with Cytoscape. Pink or red nodes represent the genes and the blue nodes indicate biological pathways.
The functional pathways highlighted by Cytoscape are shown in Table
Biological pathways controlled by IR-modulated miRNAs and their association with ionizing radiation response.
Identified pathways | Number of miRNA target genes | Association with IR response | Reference |
---|---|---|---|
Adherens junction | 10 | Yes |
[ |
Aldosterone-regulated sodium reabsorption | 7 | Unknown | N/A |
Apoptosis | 9 | Yes |
[ |
Cell cycle | 12 | Yes |
[ |
Endocytosis | 20 | Yes |
[ |
Focal adhesion | 17 | Yes |
[ |
Insulin signaling | 19 | Yes |
[ |
Long-term potentiation | 11 | Unknown | N/A |
MAPK signaling | 22 | Yes |
[ |
Neutrotrophin signaling | 12 | Unknown | N/A |
Oocyte meiosis | 13 | Yes |
[ |
p53 signaling | 8 | Yes |
[ |
Regulation of actin cytoskeleton | 20 | Yes |
[ |
Renal cell carcinoma | 9 | Yes |
[ |
TGF- |
10 | Yes |
[ |
Thyroid cancer | 6 | Yes |
[ |
Ubiquitin-mediated proteolysis | 17 | Yes |
[ |
Interestingly, the interactome analysis reported in the present study permitted us to discover novel pathways that have not been previously associated with ionizing radiation response. We discovered that radiation-induced miRNA control the expression of a number of genes that function in aldosterone-regulated sodium reabsorption, long-term potentiation, and neurotrophin signaling pathways.
The mineralocorticoid hormone, aldosterone is a key regulator of sodium homeostasis. The aldosterone controls sodium reabsorption by regulating the cell-surface expression and function of the epithelial sodium channel (ENaC). The stimulatory effect of aldosterone on ENaC is mediated by the induction of serum- and glucocorticoid-regulated kinase 1 (SGK1) [
The neurotrophin-signaling pathway is involved in differentiation and survival of neural cells. The insulin/insulin-like growth factor 1 receptor-signaling (IGF1-R) pathway is linked to the neurogenic capacities of the aging brain, to neurotrophin signaling, and to the molecular pathogenesis of Alzheimer’s disease [
The long-term potentiation pathway is associated with long-lasting enhancement in signal transmission between two neurons. The plastic changes at synapses between neurons are partly associated with the memory. The long-term potentiation (LTP) is a major form of synaptic plasticity [
Our findings suggest that the miRNA target gene interactome can help identify novel cellular functions that could be altered as a result of stress induced by radiation exposure. The ability to discover previously uncharacterized new novel pathways through understanding the interactome of miRNA-predicted target genes and -associated pathways offers a new platform for future investigations. A deeper understanding of the miRNA expression signatures in different cell types subjected to IR exposure will not only lead to identify common biological pathways affected in all cell types but will also permit to discover pathways that are only affected in certain cell types.
It is apparent that miRNAs are involved in controlling the biological pathways associated with ionizing radiation induced stress responses. The miRNA expression alterations in irradiated cells explains the observed biological effects and provides a broader perspective on understanding cellular defense mechanisms against radiation-induced insult. This investigation has provided a starting point where the role of miRNAs in ionizing radiation can be explored. The pathways affected by IR-induced miRNA provide vital information to understand the regulation of the biological processes in cells exposed to IR. It has always been assumed that only transcriptional factors affect the gene expression and control biological pathways. However, the participation of miRNAs adds another set of rules dictating control of the biological pathways. miRNAs may act as “hub” regulators of specific cellular responses, immediately downregulated so as to stimulate DNA repair mechanisms, followed by upregulation involved in suppressing apoptosis for cell survival. Taken together, miRNAs may mediate signaling pathways in sequential fashion in response to radiation. Future studies will be aimed to understand the effect of miRNA perturbation on the disruption of biological pathways. Though the genes that are associated with the pathways have been determined, it is still unclear whether an activation or inhibition of the pathway takes place in the cells exposed to radiation.
The authors declare that they have no conflict of interests.
M. A. Chaudhry conceived the idea and planned the study. T. W. Lhakang performed the experiments and the informatics analysis. M. A. Chaudhry and T. W. Lhakang wrote the paper.
M. A. Chaudhry is supported by an endowment fund, College of Nursing and Health Sciences, University of Vermont, VT, USA.