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Article

Identification of Radiation-Induced miRNA Biomarkers Using the CGL1 Cell Model System

1
School of Natural Sciences, Laurentian University, Sudbury, ON P3E 2C6, Canada
2
Medical Sciences Division, NOSM University, 935 Ramsey Lake Rd., Sudbury, ON P3E 2C6, Canada
3
Biomolecular Sciences Program, Laurentian University, Sudbury, ON P3E 2C6, Canada
4
Health Sciences North Research Institute, Sudbury, ON P3E 2H2, Canada
5
Medical Sciences Division, NOSM University, 955 Oliver Rd., Thunder Bay, ON P7B 5E1, Canada
6
Department of Biology, Lakehead University, Thunder Bay, ON P7B 5E1, Canada
*
Author to whom correspondence should be addressed.
Submission received: 3 May 2022 / Revised: 11 May 2022 / Accepted: 14 May 2022 / Published: 16 May 2022
(This article belongs to the Special Issue Molecular Diagnostics in Postgenomic Era)

Abstract

:
MicroRNAs (miRNAs) have emerged as a potential class of biomolecules for diagnostic biomarker applications. miRNAs are small non-coding RNA molecules, produced and released by cells in response to various stimuli, that demonstrate remarkable stability in a wide range of biological fluids, in extreme pH fluctuations, and after multiple freeze–thaw cycles. Given these advantages, identification of miRNA-based biomarkers for radiation exposures can contribute to the development of reliable biological dosimetry methods, especially for low-dose radiation (LDR) exposures. In this study, an miRNAome next-generation sequencing (NGS) approach was utilized to identify novel radiation-induced miRNA gene changes within the CGL1 human cell line. Here, irradiations of 10, 100, and 1000 mGy were performed and the samples were collected 1, 6, and 24 h post-irradiation. Corroboration of the miRNAome results with RT-qPCR verification confirmed the identification of numerous radiation-induced miRNA expression changes at all doses assessed. Further evaluation of select radiation-induced miRNAs, including miR-1228-3p and miR-758-5p, as well as their downstream mRNA targets, Ube2d2, Ppp2r2d, and Id2, demonstrated significantly dysregulated reciprocal expression patterns. Further evaluation is needed to determine whether the candidate miRNA biomarkers identified in this study can serve as suitable targets for radiation biodosimetry applications.

1. Introduction

Biodosimetry is the measurement of biological response to radiation. The gold standard in the field of biological dosimetry is the dicentric chromosome assay (DCA), which measures the incidence of dicentric chromosomes [1]. DCA has a predicting error of ±0.5 Gy which is adequate for high-dose radiation (HDR) exposures [2]. However, DCA is unreliable in the low-dose radiation (LDR) range (below 100 mGy) [2]. The cytokinesis-block micronucleus (CBMN) assay is also used for biodosimetry applications. The CBMN assay assesses the formation of micronuclei in binucleated cells derived from peripheral lymphocytes [3]. These micronuclei are formed when chromosomal structures are damaged, forming chromosome fragments that segregate separately during cell division. Unfortunately, both DCA and CBMN are low-throughput methodologies and are ineffective for estimating LDR exposures [4]. This emphasizes the need for new biodosimetry techniques that are reliable, sensitive, high-throughput, and minimally invasive.
microRNAs (miRNAs) are becoming more prevalent within the biomarker field as these biomolecules can be accurately analyzed to predict prognosis while being easily accessible due the fact of its abundance within patient serum [5]. miRNAs also demonstrate remarkable stability in a wide range of biological fluids [6]. In addition, miRNAs are resistant to multiple freeze–thaw cycles and extreme pH fluctuations; therefore, samples can be readily transported [7]. As such, these traits make miRNA key molecules when looking for specific biological markers for radiation exposures.
miRNAs are small non-protein coding RNA molecules approximately 20 nucleotides in length that act to post-transcriptionally modulate the gene expression profile of cells [8]. Two miRNAs with different cellular targets result per miRNA gene and are denoted with either 3p or 5p to indicate their origin. One of these two mature miRNA strands is then bound to Argonaute (AGO), forming a ribonucleoprotein complex known as the RNA-induced silencing complex (RISC) [9]. This complex uses the miRNA to bind to the complementary mRNA target and the AGO protein cleaves the mRNA strand. Despite having two viable miRNAs per gene, 3p and 5p, one of the species is usually more frequently integrated into the RISC complex than the other [10]. This more frequently integrated species is dependent on the particular gene itself and does not relate directly to the 3p or 5p end [11]. Taken together, complementary binding of miRNA to target mRNA prevents its translation and, therefore, reduces downstream protein expression.
Numerous studies have demonstrated that HDR exposure significantly alters miRNA profiles, resulting in downstream changes to various radiation-related molecular pathways including DNA damage repair, apoptosis, and cell cycle arrest [12,13,14]. Overall, the vast majority of the research on radiation and miRNA involves studies examining radiation therapy effects on cancer treatment and are thus HDR focused [15,16,17]. Another limitation of these studies is the lack of next-generation sequencing (NGS)-based miRNAome technology within the context of radiation-induced miRNA profiling [18,19,20]. While many articles investigated the interaction of one or more miRNAs, this selective approach can potentially introduce bias. NGS-based miRNAome profiling would ensure a more comprehensive investigation of the biological system and potentially lead to previously missed novel miRNA interactions resulting from the more focused approach. Taken together, further research is needed to comprehensively profile dose-dependent radiation-induced miRNA that can serve as candidate biomarkers for biodosimetry applications.
The primary aim of this study was to identify novel radiation-induced miRNA biomarkers at various dose ranges spanning LDR and HDR exposures. In this study, the entire miRNAome of the CGL1 cells were analyzed post-radiation exposure to identify dose-dependent radiation-induced miRNA expression changes. The CGL1 cell line is a preneoplastic nontumorigenic model resulting from the hybridization of a normal male skin GM0077 fibroblast cell with the malignant HeLa cervical cancer cell [21,22]. The CGL1 cells are nontumorigenic and demonstrate a normal fibroblast-like phenotype and transcriptome profile [23]. The CGL1 cell model system has been used extensively to investigate the effects of radiation-induced cellular transformation and tumorigenicity [24].

2. Materials and Methods

2.1. Cell Culture

The CGL1 cell line was grown in a humid environment at 37 °C with 5% CO2 [21]. The CGL1 cells were cultured using 1X Minimal Essential media (Corning, Manassas, VA, USA) with the addition of 50 U penicillin–streptomycin (GIBCO, Grand Island, NY, USA) and 5% calf serum (Hyclone, Logan, UT, USA).

2.2. Cell Irradiation

The CGL1 cells were exposed to X-rays in triplicate at 10, 100, or 1000 mGy and collected at 1, 6, and 24 h post-irradiation. Irradiations were performed on an X-RAD 320 irradiation cabinet (Precision X-ray, Madison, CT, USA) operated at 320 kV and 12.5 mA with a 2 mm Al filter. Briefly, cells were grown in a T25 flask (Life Technologies, Carlsbad, CA, USA) and plated to ensure 80% confluence at the desired endpoint. These sample sets consisted of three different timepoints post-irradiation (i.e., 1, 6, and 24 h) to assess the time-dependent expression of the various radiation-induced miRNA. These timepoints allowed for the analysis of acute (1 h), intermediate (6 h), and prolonged effects (24 h). At each of these timepoints, the cells were split into 4 different irradiation groups: the sham irradiation control and 10, 100, and 1000 mGy. This range of dose was selected to evaluate LDR effects (10 and 100 mGy) and a higher dose of radiation (1000 mGy), which is well known to induce DNA damage effects. These samples were irradiated on ice with cold PBS to ensure that no-dose rate effects were observed. The cells were irradiated using three different programs to ensure similar exposure times among the different doses. In short, the 10 mGy dose was irradiated at a dose rate of 5.6 mGy/min, the 100 mGy dose was irradiated at a dose rate of 138 mGy/min, and the 1000 mGy dose was irradiated at a dose rate of 1500 mGy/min. Following irradiation, the samples were re-incubated in media until the desired timepoint, at which point the cells were lysed and collected using 1 mL TRIzol per T-25 flask.

2.3. Total RNA Extraction

Total RNA was extracted using the TRIzol extraction method according to the manufacturer’s instructions. In brief, 0.2 mL of chloroform was added to 1 mL TRIZOL samples and vortexed prior to being centrifuged at 12,000× g for 20 min. The top aqueous layer containing the RNA was transferred into another tube, while the remaining DNA and protein layer were stored for future use. The RNA was precipitated out of the aqueous layer with the addition of 0.3 mL of isopropanol and centrifuged at 12,000× g for 15 min. Afterwards, the supernatant was decanted, and the remaining RNA pellet was washed with 1 mL of 70% ethanol and centrifuged at 7500× g for 5 min. Finally, the supernatant was removed, and the resulting RNA pellet was resuspended in 30 µL of DEPC water. The resulting total RNA samples were assessed to ensure both an adequate concentration and purity using a Nanodrop (Nanodrop One, Thermo Fisher Scientific, Madison, WI, USA), assuring the 260/280 nm absorbance ratio of the samples was greater than 1.8.

2.4. cDNA Synthesis

From the total RNA samples, one of two reverse transcription reactions were performed depending on whether mRNA or miRNA was to be analyzed. In brief, total RNA was first purified of DNA contaminants using a DNAse kit (MilliporeSigma, Oakville, ON, CA) before proceeding to reverse transcription reactions. The key difference between mRNA and miRNA cDNA preparation was that for the analysis of miRNAs, the samples were first subjected to a poly-A tail extension and annealed to an oligo-dT primer with a known sequence at the 3′ end (5′-GCATAGACCTGAATGGCGGTAAGGGTGTGGTAGGCGAGACATTTTTTTTTTTTTTTTTTTT-3′). This additional step before the cDNA synthesis serves to elongate the miRNA and produce a suitable nucleotide length for RT-qPCR analysis, without which RT-qPCR would have been otherwise impossible, as the miRNA are too similar in length to design RT-qPCR primers. For preparation of cDNA from mRNA, random hexamers were used. The resulting products were reverse transcribed using the Promega M-MLV Reverse Transcriptase kit (Madison, WI, USA).

2.5. miRNAome Profiling via Next-Generation Sequencing

An NGS analysis was conducted on the irradiated samples; however, based on various studies in the literature, 6 h post-stimulation was found to be an optimal timepoint, where most miRNA are expected to be expressed and, therefore, of most importance [25]. As such, the 6 h timepoint RNA samples were chosen for miRNAome analysis. The remaining two timepoints, 1 and 24 h, were analyzed subsequently using RT-qPCR and compared to the 6 h results. This allowed for the determination of the time-course for the expression of the dysregulated miRNA. For the sample preparation, the irradiated total RNA samples were treated with the QIAseq miRNA Library kit (QIAGEN Sciences, Germantown, MD, USA), which serves to select smaller RNA within a sample and prepare these RNA sequences for miRNAome profiling. In brief, following the collection of total RNA using the method described earlier, two ligation reactions were accomplished to add adapter sequences to the 5′ and 3′ end of the miRNA. A reverse transcription reaction integrating the UMI adaptors into the resulting cDNA was completed. Finally, a barcode index was added to the end of each of the sample conditions. Samples were then pooled together and sent out for sequencing at the Donnelly Sequencing Centre at the University of Toronto. The samples were sequenced on the NovoSeq6000 platform (Illumina) and consisted of a 75-base length read for a total of 10 million reads per sample. Previous reports have shown that 5 million sequencing reads per sample is adequate for total human miRNAome profiling [26].

2.6. RT-qPCR Primer Design and Validation

Despite the NGS methodology being an excellent technique capable of whole miRNAome profiling, false positives can occur based on statistical probability as well as other contributing factors such as library amplification and sequencing bias [27]. As such, a common practice to verify the integrity of the obtained sequencing results is to utilize a secondary confirmatory technique on randomly selected miRNA targets. Here, randomly selected miRNAs were cross-verified using RT-qPCR analysis.
RT-qPCR primers were designed in-house using the primer blast software offered by the National Center for Biotechnology Information (NCBI). For the design of the mRNA primers, the full-length mRNA transcript sequences were used [28]. However, for the miRNA primers, a modified input sequence was used consisting of the miRNA sequence appended to the oligodT adapter sequence.
The potential primers were screened for the combination of melting temperature, GC content, and lack of self-complementarity to obtain the optimal primer pairs for each gene. These primers were verified across a range of temperatures between 54 and 64 °C and run at various concentrations to ensure their amplification was optimal. The primers for the mRNA gene expression analysis were considered valid if their amplification reaction efficiency was uniform, had an R2 value of >0.99, and an amplification efficiency of 90–110%. For the miRNA, the amplification efficiency was relaxed to 70–130% in order to provide more flexibility than usual due to the limitations when designing miRNA primers; these miRNA primers usually correspond to the miRNA sequence itself with minimal design flexibility. The miRNA cDNA products were qPCR amplified using a universal reverse primer for the known end sequence (5′-GCATAGACCTGAATGGCGGTA-3) common to all of the modified miRNA and a forward primer specific to the miRNA in question. Validated primer information can be found in the appendix (Table A1 for miRNA and Table A2 for mRNA).

2.7. RT-qPCR

The RT-qPCR procedure was performed in 15 µL reaction volume ensuring a final volume of 1X qPCR master mix (LUNA, New England Biolabs, Ipswich, MA, USA) and 600 nM for both primers. The protocol was repeated for 40 cycles: 95 °C for 15 s and 60 °C for 30 s, after which the fluorescence was measured. A melt curve was performed at the end of the 40-cycle run to ensure that the resulting amplicon was unique. Once complete and the raw fluorescence data were obtained, the cycle threshold (Cq) data were analyzed using the QuantStudioTM Design and Analysis Software v1.5.1 (Applied Biosystems). Samples were normalized to the geometric mean of two control housekeeping genes: RPS18/GAPDH for mRNA and SNORD48/U6 for miRNA. The relative expression of the genes was calculated utilizing the ΔΔCT method with the following formula: 2ΔΔCT = 2(ΔCT gene − ΔCT housekeeping genes). The average 2ΔΔCT and standard error of the means (SEMs) were calculated [29].

2.8. Statistical Analysis

For the NGS data, the irradiated samples were first normalized with their sham control using the DEseq2 methodology package previously described [30]. Genes that had a p-value less than 0.05, a gene count greater than 50, and a fold change of at least 1.5 were considered significant.
For the RT-qPCR-based experiments, the different doses within a timepoint were compared to one another by performing a one-way ANOVA followed by Tukey’s post hoc analysis using Jamovi (p-values < 0.05 were considered significant).

3. Results

3.1. Identification of Dysregulated miRNA 6 h Post-Irradiation

The miRNAome analysis of CGL1 cells exposed to 10, 100, and 1000 mGy doses 6 h post-radiation is presented in Table 1. The miRNAome analysis identified a total of 2256 miRNAs within the CGL1 cells. Of these, 38 miRNAs were significantly dysregulated compared to the sham controls, demonstrating radiation-induced expression profiles.

3.2. Validation of the miRNAome Results Via RT-qPCR Analysis

To verify the validity of the significantly dysregulated miRNA identified from the miRNAome results, a secondary quantitative analysis was performed on the irradiated sample sets. Here, the validation of the miRNAome results were corroborated with RT-qPCR analysis. In addition, the 1 and 24 h timepoints were analyzed along with the 6 h timepoint to identify temporal expression patterns. As such, the adapted RT-qPCR technique for the quantification of miRNA described earlier was performed on the samples. The RT-qPCR primers were designed for all of the radiation-induced miRNAs identified in Table 1. However, only 19 of the total primers passed validation due to the limitations in designing primers for the short miRNA sequence (Table A1). From these validated primers, 11 miRNAs were found to be significantly dysregulated as identified via miRNAome and RT-qPCR methodologies across the different experimental conditions: miR-1228-3p, miR-758-5p, miR-502-3p, miR-491-5p, miR-362-5p, miR-3135b, miR-584-5p, miR-143-3p, miR-29a-5p, miR-1292-5p, and miR-370-3p (Figure 1). Of these miRNAs, miR-362-5p, miR-3135b, miR-584-5p, miR-143-3p, miR-29a-5p, and miR-370-3p shared the same temporal expression profile and were significantly upregulated at the 1000 mGy dose at the 1 h timepoint (Figure 1E–K). In fact, all 11 miRNAs, except for miR-1292-5p, were significantly upregulated at 1000 mGy 1 h post-irradiation. Moreover, miR-1292-5p demonstrated dysregulation uniquely at the 10 mGy dose, where it can be shown to be significantly increased at both the 1 and 24 h timepoints (Figure 1J). Another interesting trend was shown with miR-1228-3p, which demonstrated consistent upregulation at 1000 mGy between the 1 and 6 h timepoints (Figure 1A). The remaining miRNAs, miR-758-5p, miR-502-3p, miR-491-5p, shared a similar expression profile, wherein they showed a decrease in expression during the 6 h timepoint at 1000 mGy relative to the sham. Moreover, these miRNAs also demonstrated significant dose-dependent decreases compared to the sham: miR-758-5p showed a decrease at the 10 and 100 mGy doses (Figure 1B), miR-502-3p decreased at the 100 and 1000 mGy doses (Figure 1C), and miR-491-5p was reduced at the 10 and 1000 mGy doses (Figure 1D). Additionally, miR-491-5p also showed a significant increase at the 1000 mGy dose at the 24 h timepoint.

3.3. mRNA Gene Targets of miR-1228-3p and miR-758-5p Showed Reciprocal Expression

To better understand the underlying mechanism of action for these various significantly dysregulated miRNAs, their various downstream gene targets were identified based on the predicted interaction using the miRBD database and previously documented in the literature (Table 2) [31]. By examining all these mRNA targets, it can be determined if the change in miRNA expression demonstrates reciprocal effects on the expression of the mRNA targets. Here, reciprocal miRNA and mRNA expression demonstrated biologically relevant interactions [32]. However, for this analysis, it is important to note that miRNAs are typically induced much faster and last much longer than their mRNA counterparts; as such, the various timepoint expressions across mRNA and miRNA may not be a direct temporal relationship [33]. From the analysis of these mRNA targets, three significant miRNA/mRNA reciprocal interactions were identified. Here, miR-1228-3p was upregulated, whereas its mRNA targets, Ube2d2 and Ppp2r2d, were found to be significantly downregulated 6 h post-1000 mGy irradiation (Figure 2A,B). In addition, miR-758-5p was downregulated, while its mRNA target Id2 was found to be significantly upregulated at 24 h post-10/1000 mGy irradiation (Figure 2C).

4. Discussion

The overall miRNAome results showed 38 dysregulated genes across various radiation doses (Table 1). As predicted, an increasing number of genes were shown to be dysregulated when exposed to increasing levels of radiation [34]. To compare radiation dose-dependent expression patterns, 2 miRNAs were dysregulated at 10 mGy, 8 miRNAs were dysregulated at 100 mGy, and 29 miRNAs were dysregulated at 1000 mGy. Of those, 11 miRNAs were validated based on RT-qPCR analysis, and a further 2 miRNAs were shown to have reciprocal response to their predicted mRNA targets (Figure 2).
As mentioned, three mRNA/miRNA target sets were validated from the above results in terms of reciprocal expression patterns. In short, the expression of genes Ube2d2 and Ppp2r2d were inversely related to the expression of miR-1228-3p, whereas Id2 gene expression was inversely related to its target of miR-758-5p. To further explore the role of these radiation-induced mRNA changes within the CGL1 cells, their mechanism of action is discussed below based on the known literature.
Ube2d2 is a component of the protein ubiquitination pathway, a protein modification often associated with protein degradation [35]. The main function of Ube2d2 is to accept ubiquitin from the E1 complex and to catalyze the reaction between ubiquitin and other proteins [35]. Of special interest within our study was its role in the degradation of p53 via its interaction with MDM2 as illustrated in Figure 3 [35]. When paired with the knowledge that p53 is constitutively expressed and degraded via this system, it can be concluded that the levels of p53 within the cell may change in response to the expression of Ube2d2 [31,36]. In short, p53 levels should decrease when Ube2d2 is highly expressed and vice versa. Given that miR-1228-3p inhibits the translation of Ube2d2, radiation-induced expression of miR-1228-3p should therefore reduce Ube2d2-mediated degradation of p53. Therefore, increased expression of miR-1228-3p is expected to result in elevated p53 levels. In this specific case, where miR1228-3p was upregulated following 1 Gy irradiation, it can be inferred that the overall level of active p53 protein is likely elevated via a reduction in its degradation. Therefore, miR-1228-3p is potentially a radiation-induced master regulator of p53 activity and further investigation would be needed to conclude if p53 protein levels are increased in response to radiation-mediated upregulation of miR-1228-3p. Following that assumption, p53-related activities, including cell cycle arrest, DNA damage repair, and apoptosis, would likely be enhanced as a result of increased miR-1228-3p levels [37].
The second validated target of miR-1228-3p is a subunit of the protein phosphatase 2A (PP2A) complex, which is a ubiquitously expressed phosphatase that is generally associated with tumour suppressive activity [38]. The complex is a tri-heteromeric protein in which subunits A and C are responsible for its structural and enzymatic activity, whereas the many types of B subunits are responsible for its specificity and cellular localization [39]. PPP2R2D is a specific B subunit variant (B55 delta) of PP2A that serves to regulate its function and is associated with a key role within the cell cycle by controlling the exit of mitosis via its inhibitory effect on CDK1 [36]. In short, it is highly expressed when the cell is in interphase and found in lower quantities during mitosis [40]. However, a recent finding has also shown Ppp2r2d to have a potential oncogenic role within the cell, as it has repeatedly been shown to be upregulated in gastrointestinal cancer cells and its inhibition is deleterious to the cells [41]. This study demonstrated that the Ppp2r2d subunit was correlated with higher levels of p-mTOR protein, thus potentially affecting the cell proliferative state; however, a mechanism for this correlation could not be identified [41]. This discovery aligns with previous knowledge demonstrating that while PP2A acts primarily as a tumour suppressor, certain subunits, including Ppp2r2d, show the ability to positively regulate signalling pathways such as the MAPK signalling cascade [42]. These findings indicate that a reduction in Ppp2r2d via miR-1228-3p may lead to a decrease in proliferative signals after exposure to 1 Gy of radiation. This coincides with the expected radiation-induced stress response discussed with Ube2d2, where the cell initially undergoes cell cycle arrest post-radiation to allow progression of various repair pathways.
In addition to miR-1228-3p, this study identified reciprocal expression of miR-758-5p and Id2 (Inhibitor of DNA Binding 2). ID2 is a transcriptional regulator that is capable of binding to other transcription factors and preventing their binding to DNA, thus negatively regulating their activity [43]. As such, it can affect a diverse set of signalling pathways, which may be of interest in the context of radiation biology including proliferation, cell cycle arrest, and apoptosis pathways [44]. One such study showed results consistent with those presented here, where Id2 demonstrated an increase in expression following 24 h post-irradiation [45]. This study established that Id2 had the ability to reverse the cell cycle arrest induced by gamma irradiation, demonstrated a protective role when cells were exposed to irradiation, and promoted cell proliferation [45]. Taken together these finding may indicate that subsequent decreases in miR-758-5p at later timepoints post-irradiation trigger an increase in ID2, which promotes the return of the cell to normal functions following the irradiation-induced cell cycle arrest (Figure 4).
Taken together, miR-1228-3p and miR-758-5p appear to be the most promising radiation-induced miRNAs identified from this study. However, all of the radiation-induced miRNAs presented in Table 1 from the miRNAome analysis are potential targets to pursue further as possible biomarkers for LDR exposures. Other promising results include miR-4443, which was shown to be dysregulated at 10 and 100 mGy doses and may potentially show high sensitivity to radiation. In fact, all miRNAs found within the 10 and 100 mGy LDR range are novel radiation-induced miRNAs and should be further assessed for biodosimetry applications of LDR exposures.
The results from this study demonstrate that a single miRNA may not be sufficient to serve as a biomarker for a broad range of doses that spans LDR and HDR exposures. This study points to the use of dose-range specific miRNAs that can be assessed together to develop biodosimetry biomarkers to accurately identify a broad range of radiation dose exposures. In this scenario, a multiplex RT-qPCR design encompassing various dose-range specific primers for radiation-induced miRNAs may serve as a reliable approach for biodosimetry applications.
In addition, as shown in Figure 1, most of the miRNAs were dysregulated at the 1 h timepoint, whereas minimal lasting miRNA dysregulation was identified at the 24 h timepoint. This would potentially be a problem when determining the applicability of miRNA-based biodosimeter biomarkers, as the temporal window for detection should be as large as possible. Therefore, miRNAs, such as miR-1292-5p and miR-491-5p, that demonstrated prolonged dysregulation at 24 h post-irradiation may be of note. However, it is possible that the radiation-induced miRNAs may have been secreted as exosomes, contributing to the lack of elevated expression at 24 h post-irradiation with the cell.
Additionally, this study indicates that mRNA targets may also serve as potential radiation biomarkers. Here, we identified reduced expression of miR-758-5p and an upregulation of its mRNA target Id2 24 h post-radiation. Interestingly, Id2 expression has been previously identified in the literature as a radiation-induced biomarker [43].
This study provides a technical framework for identifying radiation-induced miRNA biomarkers using NGS-based miRNAome technology. Similar studies need to be performed in various cell types and in vivo models to elucidate reliable radiation-induced miRNA biomarkers. In addition, it is important to verify whether the radiation-induced miRNAs are also detectable in the extracellular environment in exosome fractions [47]. Given that serum and urine samples are likely the ideal choice for sampling radiation exposures, identification of released miRNA is crucial for developing reliable miRNA biomarkers for biodosimetry application.

5. Conclusions

In conclusion, this study identified numerous potential candidate radiation-induced miRNAs at various dose ranges. The results of the miRNAome study identified 38 radiation-induced miRNA that were dysregulated within the irradiated samples. From there, a total of 11 miRNA were further verified via RT-qPCR-based miRNA expression analysis. Here, two miRNAs demonstrated reciprocal gene expression with its predicted mRNA targets: miRNAs 1228-3p and 758-5p and their corresponding mRNA targets Ube2d2/Ppp2r2d and Id2, respectively. The most promising was the interaction of the miR-1228-3p target Ube2d2 and its role in p53 degradation. This finding suggests that radiation-induced expression of miR-1228-3p may promote higher levels of p53. Elevated p53 suggests a stress response typically expected after radiation exposures.
Altogether, the results discussed in this paper revealed novel potential miRNA biomarkers within the CGL1 cell line using miRNAome sequencing. Although this study requires additional investigation to validate its findings, the data presented here represents a good foundation for future investigations.

Author Contributions

Conceptualization, J.P., T.C.T. and S.T.; Formal analysis, J.P., C.D.M. and S.T.; Funding acquisition, C.T., N.K., S.J.L., D.R.B., T.C.T. and S.T.; Investigation, J.P. and S.T.; Methodology, J.P., C.D.M., T.C.T. and S.T.; Supervision, T.C.T. and S.T.; Writing—original draft, J.P. and S.T.; Writing—review and editing, J.P., C.D.M., C.T., N.K., S.J.L., D.R.B., T.C.T. and S.T. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Natural Sciences and Engineering Research Council of Canada (NSERC) Collaborative Research and Development (CRD) in partnership with Bruce Power and the Nuclear Innovation Institute. The research was also supported by a Northern Ontario School of Medicine Faculty Association Research Development Award.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon a reasonable request.

Conflicts of Interest

D.R.B. was previously employed by the company Bruce Power.

Appendix A

Table A1. RT-qPCR primers for miRNA gene expression profiling.
Table A1. RT-qPCR primers for miRNA gene expression profiling.
miRNAmiRNA forward PrimerTm
Oligo-dT adapterGCATAGACCTGAATGGCGGTAAGGGTGTGGTAGGCGAGACATTTTTTTTTTTTTTTTTTTT65
universal reverseGCATAGACCTGAATGGCGGTA60
SNORD48TGATGACCCCAGGTAACTCTGA60
miR-16-5pATTGAAACCTCTAAGAGTGGA60
U6GTG CTC GCT TCG GCA GCA CAT AT60
miR-423-3pAGCTCGGTCTGAGGCCC60
miR-191-5pCAACGGAATCCCAAAAGCAGC60
miR-6134UGA GGU GGU AGG AUG UAG A60
miR-6082GAATACGTCTGGTTGATCCAAAA57
miR-208a-5pAGCTTTTGGCCCGGGTTATAC61
miR-7112-3pCATCACAGCCTTTGGCCCTA60
miR-6762-3pUGGCUGCUUCCCUUGGUCUCCAG60
miR-6882-3pCTCTCCTCTTGCCTGCAGAA60
miR-200a-5pTCTTACCGGACAGTGCTGGA61
miR-604GCTGCGGAATTCAGGACAAAA60
miR-2355-5pTCCCCAGATACAATGGACAAAA57
miR-4692UCAGGCAGUGUGGGUAUCAGAU60
miR-378eACTGGACTTGGAGTCAGGAAA59
miR-4535GGACCTGGCTGGGACAAAA60
miR-1915-3pCGACGCGGCGGGAAA60
miR-1291CCTGACTGAAGACCAGCAGTAAA60
miR-19a-5pAGTTTTGCATAGTTGCACTACAAA58
miR-5008-3pTCCCAGGGCCTCGCAAA61
miR-4417TGGGCTTCCCGGAGGG60
miR-1537-3pAAAACCGUCUAGUUACAGUUGU60
miR-3168GAGUUCUACAGUCAGAC60
miR-5186AGAGAUUGGUAGAAAUCAGGU60
miR-4680-5pAGAACTCTTGCAGTCTTAGATGT57
miR-554AGTCCTGACTCAGCCAGTAAAAA60
miR-6845-3pCCUCUCCUCCCUGUGCCCCAG60
miR-6125GCGGAGCGGCGGAAAA61
miR-3616-3pCGAGGGCATTTCATGATGCAG60
miR-615-3pUCCGAGCCUGGGUCUCCCUCUU60
miR-3152-3pUGUGUUAGAAUAGGGGCAAUAA60
miR-4693-3pUGAGAGUGGAAUUCACAGUAUUU60
miR-4320GGGAUUCUGUAGCUUCCU60
miR-6783-5pGGAAAAGTCCTGATCCGGAAAAA59
miR-33b-5pGUGCAUUGCUGUUGCAUUGC60
miR-4662a-3pAAAGAUAGACAAUUGGCUAAAU60
miR-8082GATGGAGCTGGGAATACTCTGAA60
miR-4758-5pGCCGGTGGGGCTGAAAA60
miR-8071GGACTGGAGTGGGTGGAAAAA60
miR-4477bAUUAAGGACAUUUGUGAUUGAU60
miR-34a-5pTGGCAGTGTCTTAGCTGGTTG60
miR-182-5pTTTGGCAATGGTAGAACTCACACT60
miR-525-3pAAGGCGCTTCCCTTTAGAGC60
hsa-miR-492AGGACCTGCGGGACAAGA60
hsa-miR-4535GTGGACCTGGCTGGGAC60
miR-877-5pGTAGAGGAGATGGCGCAGG60
miR-133bTTTGGTCCCCTTCAACCAGC60
miR-205-3pGATTTCAGTGGAGTGAAGTTC60
miR-1ACATACTTCTTTATATGCCCAT60
miR-19bAGTTTTGCAGGTTTGCATCCAG60
miR-93-5pAAGTGCTGTTCGTGCAGGTAG60
miR-132-5pACCGTGGCTTTCGATTGTTAC59
miR-671-5pCTGGAGGGGCTGGAGAAAAA60
miR-628-3pTCTAGTAAGAGTGGCAGTCGAA58
miR-125b-1-3pACGGGTTAGGCTCTTGGGA60
miR-6797-5pGAAGGGGCTGAGAACAGGAAA60
miR-6739-5pTGGGAAAGAGAAAGAACAAGTAAAA57
miR-6823-3pGCCTCTCCTTCCCTCCAGAAA61
miR-449c-3pGCTAGTTGCACTCCTCTCTGT59
miR-328-3pCCTCTCTGCCCTTCCGTAAA59
miR-103a-3pCAGCATTGTACAGGGCTATGAA58
miR-4721CTCCAGGTGACGGTGGAAAAA60
miR-589-3pCAGAACAAATGCCGGTTCCC60
miR-769-3pGGATCTCCGGGGTCTTGGT61
miR-27a-3pCACAGTGGCTAAGTTCCGCA61
let-7g-5pTGAGGTAGTAGTTTGTACAGTT60
let-7a-5pTGAGGTAGTAGGTTGTATAGTT60
miR-296-5pAGGGCCCCCCCTCAATCCTGT60
miR-4443TTGGAGGCGTGGGTTTT60
miR-3120-3pACAGCAAGTGTAGACAGGCAA60
miR-423-3pAGCTCGGTCTGAGGCCCCTCAGT60
miR-362-5pCCTTGGAACCTAGGTGTGAGT60
miR-148b-5pAGTTCTGTTATACACTCAGGCAA60
miR-495-5pGAAGTTGCCCATGTTATTTTCG60
miR-6835-5pAGGGGGUAGAAAGUGGCUGAAG60
miR-4668-5pAGGGAAAAAAAAAAGGAUUUGUC60
miR-491-5pGTGGGGAACCCTTCCATGAG60
miR-4271GGGGGAAGAAAAGGTGGGG60
miR-665GGAGGCTGAGGCCCCTAAA60
miR-193a-5pTCTTTGCGGGCGAGATGAAA60
miR-22-3pAGCTGCCAGTTGAAGAACTGTA60
miR-1228-3pCACACCTGCCTCGCCC60
miR-181a-2-3pCACTGACCGTTGACTGTACCA60
miR-100-5pACCCGTAGATCCGAACTTGTG60
miR-143-3pTGAGATGAAGCACTGTAGCTC60
miR-10b-5pACCCTGTAGAACCGAATTTGTGA60
A total list of miRNA primers tested during the course of the secondary validation step of the obtained NGS results. The sequences and their optimal melting temperature can be found above.
Table A2. RT-qPCR primers for mRNA gene expression profiling.
Table A2. RT-qPCR primers for mRNA gene expression profiling.
mRNA PrimerSequence (5′→3′)LengthProduct (bp)Tm
PPP2R2D_F_Hu_1GTCAAGGACAGGGCAGACTTC2113660
PPP2R2D_R_Hu_2AGCTGTTCTCAGCTGTTCTATCA23
UBE2D2_F_Hu_1CGTTTTGCCCGATCCACAAG2014560
UBE2D2_R_Hu_1GTCCCGTGCCAGATCATTCA20
IRX2_F_Hu_1CACCAAGATGACCCTCACCC2011960
IRX2_R_Hu_1CGTCCTCGTCCTCATCTTCG20
ZNF554_F_Hu_1CTGCAGTACTGTGCTGATCCA2113760
ZNF554_R_Hu_1ACGTCTCTGTCCAGCCTTTG20
NFIA_F_Hu_1TGCCGAATCGATTGCAACTTC218360
NFIA_R_Hu_1GGCTGGTTCTCAGATTCGCT20
SOCS6_F_Hu_1GGCCGCCTCCGGAAAAT178160
SOCS6_R_Hu_1ACATCTGGAGAGGCTGCAAG20
RABGEF1_F_Hu_1GCGGTGACCTGGACCAC178260
RABGEF1_R_Hu_1TTCCCAAAGTGATCTCGCCC20
TJP1_F_Hu_1TGGTCTGTTTGCCCACTGTT2015060
TJP1_R_Hu_1TCTGTACATGCTGGCCAAGG20
TOR1AIP1_F_Hu_1AAGTCCTCTAGTGCAACGCC208260
TOR1AIP1_R_Hu_1ATCTTGGCTTGAGGCACTCC20
ZBTB44_F_Hu_1ACGAGTGCAAAACATGTGGC207260
ZBTB44_R_Hu_1GGTTCAGACTCCTCAGGTGC20
Moap1_F_Hu_1AGGCCCTTCTCCAGGCAATA207060
Moap1_R_Hu_1TGCCATATCCCTTCGTGGTT20
Csnk2a1_F_Hu_1ATCGCCGCCATATTGTCTGT2010960
Csnk2a1_R_Hu_1CAGCTGGGGGTAAGACCTTG20
PLAC8_F_Hu_1CAGAAGGAGAGCCATGCGTA207660
PLAC8_R_Hu_1AACCCACATGTTCTGAGAGGC21
SLC20A2_F_Hu_1TCTCGGCCTAATGTGGTAGGA2113860
SLC20A2_R_Hu_1CTCCCGATCTGGGAAAGCTG20
ID2_F_Hu_1ATCCTGTCCTTGCAGGCTTC208160
ID2_R_Hu_1ACCGCTTATTCAGCCACACA20
NUFIP2_F_Hu_1ATGTCCATTTTGCTTGCCTGG2114960
NUFIP2_R_Hu_1CCCAATTCAGGTGGGGTCTG20
PTP4A1_F_Hu_1CTGTGAGCTCTTAAGACTTGCTT237358
PTP4A1_R_Hu_1CACTGCTGCTGGGAATTATGA21
TOX4_F_Hu_1CTGACGATCACAGGGCCTTC2014260
TOX4_R_Hu_1GGCCAACCACATCTGAGACA20
SETD5_F_Hu_1CTGTGACAAGTGCAGGGGAA209560
SETD5_R_Hu_1CTGTTGCACTGCTATCCCCA20
PHACTR1_F_Hu_1TGTTCATTTGTGCTTGCGGG207460
PHACTR1_R_Hu_1CCCTTTCAACAGGACACGGT20
RTKN_F_Hu_1CGAGTGAAGTGTGACTCCGT209060
RTKN_R_Hu_1TTCCAGACAGGAAACCAGCC20
DSG3_F_Hu_1GACTCCTTCGGAAAGCAGCA2013860
DSG3_R_Hu_1GGGGAAGAGCCCCATCATTG20
CSNK1A1L_F_Hu_1CCCTGGGGTTTGCAAATTGT2013860
CSNK1A1L_R_Hu_1TCTTCACAGGTAAGCAGGCG20
CD36_F_Hu_1CCACACACTGGGATCTGACA2013260
CD36_R_Hu_1TCTGCAGGAAAGTCCTACACTG22
ZBTB20_F_Hu_1TCCTGACAAATGCTAGAACGGA228660
ZBTB20_R_Hu_1CCACCCGGCTGAGTAATCTC20
CBX5_F_Hu_1GGGAGGCCCCTCCTGTTAG197260
CBX5_R_Hu_1AAGACTAAGGCCACCAGGTC20
CTTN_F_Hu_1GACAAATGTGCCCTTGGCTG2011160
CTTN_R_Hu_1CTGCCTCTCCGACTGAACAC20
NCOA2_F_Hu_1CCCTCCCTCTACCACAGTCA208760
NCOA2_R_Hu_1CAGAGTCCTCTGAGAAGGCG20
ZNF281_F_Hu_1ATGACCACCATGGCACTGAG207060
ZNF281_R_Hu_1TCTGGCTTTGGCCTTTTTGC20
TNPO1_F_Hu_1TGCCCGGCCGTTTGAAG1712160
TNPO1_R_Hu_1GCTCGTCAGGTTTCCACTCA20
HNRNPD_F_Hu_1GCCATTCAAACTCCTCCCCA208960
HNRNPD_R_Hu_1GTCCCAGCTAAGGCCTCCTA20
SBNO1_F_Hu_1CAATGCCTACCCCGTCAGTT207260
SBNO1_R_Hu_1CTGCTTCGGTCTCCAAACCT20
DIPK2A_F_Hu_1GTGGGTGTGAGACATCCTAGC217460
DIPK2A_R_Hu_1CACGACAAGTGGGGTCTGC19
MCUB_F_Hu_1GGAGGATGCTCCAGAGGGG1911960
MCUB_R_Hu_1CTTCACACGCAAAACCTGGG20
NOL4L_F_Hu_1GCCAAAACCAAGACGGTGAC201246
NOL4L_R_Hu_1CCCAGAACTGGAACTTGCCT20
CAMTA1_F_Hu_1GAAAACAAGCCGGAAGAGCG208160
CAMTA1_R_Hu_1ATAGGTGGCACGGTGTTGAG202
cdk6_F_Hu_1CTGCAGGGAAAGAAAAGTGCAA229560
cdk6_R_Hu_1CTCCTCGAAGCGAAGTCCTC20
MTA3_F_Hu_1GTCCTCCCCCTCCGCTC1713160
MTA3_R_Hu_1CTGGGGACTGCCCAATTCAT20
TRIM50_F_Hu_1GGCATCTAACTGGAGCGACA208560
TRIM50_R_Hu_1CCAAGCCATCCACACTCACT20
SGIP1_F_Hu_1TGGAATTCCTTCAGGCGGAC207360
SGIP1_R_Hu_1ACGATTCCAGGTCCCAGCTA20
PLAGL2_F_Hu_1ACAATGCACCGCACAATGG1913860
PLAGL2_R_Hu_1CCTCCAACGCAGCTTTCAGA20
PRKACB_F_Hu_1GCTAGCAGTAAGAGCTGGTGT217560
PRKACB_R_Hu_1TGAACCTGGCAAGGAGCAAA20
LUC7L3_F_Hu_1GGTCAATGGGACCAGTGAAGA2114760
LUC7L3_R_Hu_1CGCTGCACTGTCAAACAGTAA21
EDEM1_F_Hu_1ACAACTACATGGCTCACGCC209160
EDEM1_R_Hu_1AGATTTGAAGGGTCCCCGC19
CYP1B1_F_Hu_1GCTGTGAGGAAACCTCGACT2012160
CYP1B1_R_Hu_1GAGTCTCTTGGCGTCGTCAG20
RMI1_F_Hu_1GCGGTTCCTGTCCTTACAGT198660
RMI1_R_Hu_1ACTGCTCAGAAATGGCCCTG20
MRPL35_F_Hu_1TGCAAAGAAATTGGGTCTGTGT2214160
MRPL35_R_Hu_1TGAAGGGCCACCCTTAAACC20
PIK3C2B_F_Hu_1CCACCATAGAGATGGCGTCC2013460
PIK3C2B_R_Hu_1TGGGCGCCTGATTCTTCTAC20
Cyld_F_Hu_1CCCCCTTTCTAGGGTGAGGA209860
Cyld_R_Hu_1TTCAGCAACGTGGTGTCCAT20
GAS7_F_Hu_1AGCCAACGAGTCTCTGCTTC207960
GAS7_R_Hu_1GCCGTCTCTGGGGTGC16
LRRC27_F_Hu_1CTCGCCAGCGCTTCAGT1710260
LRRC27_R_Hu_1TAGGAGCTGCTTCCCTCCAT20
FMNL3_F_Hu_1GAGTCGGGACTCGGGGAG1813060
FMNL3_R_Hu_1CTCTCCAGGTTGCCCATCG9
TTC21B_F_Hu_1TGCGTCTTCCTTTAGGCTGC208760
TTC21B_R_Hu_1TCTTCAATTCCTGCGAGTCCA21
CASTOR3_F_Hu_1AGCTTTTCCAGACCAGGCAT207660
CASTOR3_R_Hu_1CTAGGGGCTGATGTGCCAAA20
XPO7_F_Hu_1GCAATCACAGACGTCACAAGG2112660
XPO7_R_Hu_1TGCTTCAATGAGGAAGGCTGT21
PPM1A_F_Hu_1CTGCTCCGGACCTAGAGGAT2012460
PPM1A_R_Hu_1CAGCCTTGCATGCTGCTTAG20
DNM1L_F_Hu_1TCACCCGGAGACCTCTCATT209160
DNM1L_R_Hu_1TCTGCTTCCACCCCATTTTCT21
KDM3B_F_Hu_1CTGCGCACTCGAGCCTG1711460
KDM3B_R_Hu_1CCAGGAGTGTTGCTTCCAGT20
RBP1_F_Hu_1CCGCTACAATGGATCCTCCC209660
RBP1_R_Hu_1GGAAATGAGCGCCCTCCG18
FAAP20_F_Hu_1GGGTCCCCTTCTCCACTGTA207860
FAAP20_R_Hu_1CTGGCAGGAGCTGGAGATG20
PTEN_F_Hu_1CTGCAGAAAGACTTGAAGGCG217058
PTEN_R_Hu_1TGCTTTGAATCCAAAAACCTTACT24
GOLPH3_F_Hu_1TGTTTCCTCATGACTGCCCC208060
GOLPH3_R_Hu_1CGATCCGGGTTTCCGTGTTA20
ADAMTS3_F_Hu_1CAAGCATTCTCCGCGCTAAC2014760
ADAMTS3_R_Hu_1GGAGCGAGAAGGTGCTGTAA20
KCTD9_F_Hu_1CCCAAGAACGGAAAGGTGGT208860
KCTD9_R_Hu_1TGGTGGCTTTTATGCCGAGT20
FBN2_F_Hu_1GTTTTCTGCCAGTCATCCAGC2114260
FBN2_R_Hu_1AGCTGCTTTGGCTTCGATCT20
SEC63_F_Hu_1GGACATAAATAGGGCAATCCACT2311958
SEC63_R_Hu_1CCCTCTCACTCCTGGGTTTT20
ZFX_F_Hu_1ACCCTAGTGGAGTGTTGGCT2012360
ZFX_R_Hu_1TGAACCACTGAAGGGAGTCG20
DAPK1_F_Hu_1TTCGGAGTGTGAGGAGGACA2014960
DAPK1_R_Hu_1GGGAACACAGCTAGGGAGTG20
SMIM13_F_Hu_1AGTGGGTGAAAATTCCCGCT209460
SMIM13_R_Hu_1CCCTGGTAAACACTCAGCCC20
NAP1L5_F_Hu_1CTCCTAGACCTCTGCGGCTT2014762
NAP1L5_R_Hu_1GCTGTCACAGTCTCCACCCT20
CSDE1_F_Hu_1CGCTGAGCTGTTGGGTATGA207860
CSDE1_R_Hu_1ACGAGGTTTGTTCCTTGCCT20
set_F_Hu_1AGTCTCAGTGTTCAGCCTGC207860
set_R_Hu_1GGCCATGCTGTTAGGGAAGT20
OLFM4_F_Hu_1AAATGCTCGAGAGTTGCGGA2013360
OLFM4_R_Hu_1CACAGCAATCGTGTTGGTGG20
USP6NL_F_Hu_1TGGAAGGGAAACAATGGGGC2014460
USP6NL_R_Hu_1CATGTCCTCAGTACGGTCCC20
AVPR1A_F_Hu_1TGGGCGCCTTTCTTCATCAT207560
AVPR1A_R_Hu_1AGGGTTTTCCGATTCGGTCC20
HSD11B1_F_Hu_1TGCCTGCTTAGGAGGTTGTAG219060
HSD11B1_R_Hu_1AAAAGCCATCCGACAGGGAG20
GALNT15_F_Hu_1ACCCAGATGGCTTATTGCCT2012660
GALNT15_R_Hu_1TACCAGCCAGGGACTGAGTT20
GBP5_F_Hu_1AGTTCTGCTTGACACCGAGG2014960
GBP5_R_Hu_1GCAGTAGGTCGATAGCACCC20
CD200_F_Hu_1TCCAGGAGCAAGGATGGAGA207660
CD200_R_Hu_1GACCCAAACCAGGCTGTAGG20
PPM1A_F_Hu_1CTGCTCCGGACCTAGAGGAT2012460
PPM1A_R_Hu_1CAGCCTTGCATGCTGCTTAG20
NPHP1_F_Hu_1CCCACTTCTCCACTCCACAC207660
NPHP1_R_Hu_1AACTTTCCACCGTGCAGTCT20
Rock_F_Hu_1CCCTTTGCTTTCGCCTTTCC2015060
Rock1_R_Hu_1GAGGTGCTTCAGTCTAGCGG20
mmp14_F_Hu_1GGGTCTTCGTTGCTCAGTCA2014560
mmp14_R_Hu_1AACATTCGAGAGGCACAGGG20
kcne2_F_Hu_1ACGGGAACACTCCAATGACC2010560
kcne2_R_Hu_1TGGATGGTGGCCTTCGATTC20
WWP1_F_Hu_1TGCTACTTTTAGCAAACTGGGC2212858
WWP1_R_Hu_1TTAAGAAGTCAGTTCCATGGCT22
cdk16_F_Hu_1TTGGGCCGTTGGCTGTTC187060
cdk16_R_Hu_1GGCTCGCGGCACAGAG16
SEMA6A_F_Hu_1CTTACAACACAGTGTATGGGCA228160
SEMA6A_R_Hu_1CATACCCCTCTTGAGCCGTC20
CHRNB2_F_Hu_1GAAAGTTCGGCTCCCTTCCA2011560
CHRNB2_R_Hu_1GCCATCATAGGAGACCACGG20
POGK_F_Hu_1TGGGAAGTTTTGACGGAGCA2011360
POGK_R_Hu_1CGGGTGATCATGTCTGGCTT20
KSR2_F_Hu_1AAAGCACTCCAAACCGTGGA2013360
KSR2_R_Hu_1ACTCTTTACACACCGGCTCC20
SAMD4B_F_Hu_1CCTTCCTACTGGGCAGATGAG2110160
SAMD4B_R_Hu_1CCAGAAGTGGACATGGGGTA20
OPTC_F_Hu_1TGTCTTCAACCTGGCCTGTC207060
OPTC_R_Hu_1AGTACACAAGCCCATCCAGG20
CPNE5_F_Hu_1TGTGTCCAACGGTGGTGTC1911360
CPNE5_R_Hu_1CCAGCTTGTTGGCACAGAAC20
FOXP4_F_Hu_1AGCTGATTTGCTGCAGGGAT2010060
FOXP4_R_Hu_1GAAGGACACCTGGGAATGGG20
MSN_F_Hu_1GCCCAAAACGATCAGTGTGC208860
MSN_R_Hu_1AAATAGCTGCTTCCCGGTGG20
IGF2_F_Hu_1TCGCCGAACCAAAGTGGATTA2114860
IGF2_R_Hu_1GTGGGAGAGACAGAGTGAACG21
Smad3_F_Hu_1CCGGGGGTTGGACTTTCCT197060
Smad3_R_Hu_1CAGAAGTTTGGGTTTCCGCA20
Bcl2l1_F_Hu_1AGGCGGATTTGAATCTCTTTCTCT2412960
Bcl2l1_R_Hu_1GGGCTCAACCAGTCCATTGT20
Egfr_F_Hu_1GACAGGCCACCTCGTCG1710660
Egfr_R_Hu_1CCGGCTCTCCCGATCAATAC20
Notch3_F_Hu_1TCTAGGTAAGGTGGGGAGTGG217060
Notch3_R_Hu_1TGGGAGCTCAAGTTAGCCCT20
Mmp9 _F_Hu_1GTACTCGACCTGTACCAGCG209260
Mmp9 _R_Hu_1AGAAGCCCCACTTCTTGTCG20
Igf2bp1_F_Hu_1AGCTCCTTTATGCAGGCTCC2011160
lgf2bp1_R_Hu_1CCGGGAGAGCTGTTTGATGT20
Wnt3a_F_Hu_1CTCCTCCCTGGAGCTAGTGT2013860
Wnt3a_R_Hu_1AATCTGTAGCCCCGCCTCTG20
capns1_F_Hu_1CGGACGCTGCGGGAG157260
capns1_R_Hu_1TCACTGCGCCGCACAC16
A total list of mRNA primers tested, consisting of both predicted mRNA targets for the studied miRNA and the genes chosen for use in the DNA damage panel. The sequences of both primer pairs and their optimal melting temperature can be found above.

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Figure 1. Radiation-induced miRNA dysregulation in CGL1 cells. Various doses and timepoints were analyzed via RT-qPCR to obtain the temporal expression profile of the analyzed miRNAs in CGL1 cells. Cells were irradiated at 10, 100, and 1000 mGy and collected 1, 6, and 24 h post-irradiation. All irradiation doses were normalized to their own timepoint’s sham condition to obtain the relative fold change. All miRNA shown had at least one dose and timepoint that was considered significant; however, most of the significant findings were shown to be at the 1000 mGy dose. Significance is denoted by an asterisk, where * p < 0.05, ** p < 0.01, and *** p < 0.001.
Figure 1. Radiation-induced miRNA dysregulation in CGL1 cells. Various doses and timepoints were analyzed via RT-qPCR to obtain the temporal expression profile of the analyzed miRNAs in CGL1 cells. Cells were irradiated at 10, 100, and 1000 mGy and collected 1, 6, and 24 h post-irradiation. All irradiation doses were normalized to their own timepoint’s sham condition to obtain the relative fold change. All miRNA shown had at least one dose and timepoint that was considered significant; however, most of the significant findings were shown to be at the 1000 mGy dose. Significance is denoted by an asterisk, where * p < 0.05, ** p < 0.01, and *** p < 0.001.
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Figure 2. mRNA gene targets of miR-1228-3p and miR-758-5p showed reciprocal expression. Of the validated possible mRNA interaction shown in Table 2, three mRNA gene targets demonstrated a reciprocal gene expression pattern to their corresponding miRNA. In brief, (A) Ube2d2 and (B) Ppp2r2d demonstrated a reciprocal expression pattern to miR-1228-3p at 6 h, whereas (C) Id2 showed a reciprocal expression pattern to miR-758-5p at 24 h. Significance is denoted with asterisks, where * = p < 0.05, ** = p < 0.01, and *** = p < 0.001.
Figure 2. mRNA gene targets of miR-1228-3p and miR-758-5p showed reciprocal expression. Of the validated possible mRNA interaction shown in Table 2, three mRNA gene targets demonstrated a reciprocal gene expression pattern to their corresponding miRNA. In brief, (A) Ube2d2 and (B) Ppp2r2d demonstrated a reciprocal expression pattern to miR-1228-3p at 6 h, whereas (C) Id2 showed a reciprocal expression pattern to miR-758-5p at 24 h. Significance is denoted with asterisks, where * = p < 0.05, ** = p < 0.01, and *** = p < 0.001.
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Figure 3. Ube2d2’s role in p53 degradation, and the signaling pathway demonstrating the role of miR-1228-3p and its target Ube2d2 in regulating the degradation of p53. Here, Ube2d2 is shown transferring ubiquitin (ub) onto p53 via MDM2 and, thus, targeting p53 for degradation. miR-1228-3p inhibits the translation of Ube2d2. Therefore, radiation-induced expression of miR-1228-3p should reduce Ube2d2-mediated degradation of p53. Thus, increased expression of miR-1228-3p is expected to result in elevated p53 levels. The blue arrows represent pathway activation, whereas the red arrows illustrate pathway inhibition. E1 represents ubiquitin-activating enzymes that catalyze the first step in the ubiquitination reaction.
Figure 3. Ube2d2’s role in p53 degradation, and the signaling pathway demonstrating the role of miR-1228-3p and its target Ube2d2 in regulating the degradation of p53. Here, Ube2d2 is shown transferring ubiquitin (ub) onto p53 via MDM2 and, thus, targeting p53 for degradation. miR-1228-3p inhibits the translation of Ube2d2. Therefore, radiation-induced expression of miR-1228-3p should reduce Ube2d2-mediated degradation of p53. Thus, increased expression of miR-1228-3p is expected to result in elevated p53 levels. The blue arrows represent pathway activation, whereas the red arrows illustrate pathway inhibition. E1 represents ubiquitin-activating enzymes that catalyze the first step in the ubiquitination reaction.
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Figure 4. Id2’s role in reversing cell cycle arrest, illustrating the role of miR-758-5p in regulating Id2 and the consequence of upregulating Id2 via the activation of the MAPK signaling pathway. As part of the recovery process following radiation exposure, Id2 is expressed and binds to Rb. This interaction prevents binding to its other binding partner EF2, thus inducing cell proliferation [46]. The blue arrows in the figure represent pathway activation, whereas the red arrows illustrate pathway inhibition.
Figure 4. Id2’s role in reversing cell cycle arrest, illustrating the role of miR-758-5p in regulating Id2 and the consequence of upregulating Id2 via the activation of the MAPK signaling pathway. As part of the recovery process following radiation exposure, Id2 is expressed and binds to Rb. This interaction prevents binding to its other binding partner EF2, thus inducing cell proliferation [46]. The blue arrows in the figure represent pathway activation, whereas the red arrows illustrate pathway inhibition.
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Table 1. Dysregulated miRNA in CGL1 cells 6 h post-irradiation.
Table 1. Dysregulated miRNA in CGL1 cells 6 h post-irradiation.
Dose (mGy)miRNAFold Changep-Value
10miR-3120-3p11.30.042
miR-44431.90.048
100miR-44432.30.009
miR-362-5p2.10.034
miR-148b-5p2.00.043
miR-423-3p1.90.016
miR-500b-5p1.70.040
miR-502-3p1.60.040
miR-125b-1-3p1.60.041
miR-495-5p-1.70.040
1000miR-31688.80.0008
miR-671-5p5.30.003
miR-6835-5p4.20.001
miR-56944.10.009
miR-491-5p3.90.005
miR-20543.60.003
miR-4668-5p3.50.002
miR-60693.40.019
miR-23a-5p3.30.003
miR-3135b2.80.015
miR-22-3p2.70.022
miR-29a-5p2.70.045
miR-6652.50.007
miR-296-3p2.10.0004
miR-6813-3p2.10.008
miR-1292-5p2.00.011
miR-42711.90.006
miR-1228-3p1.80.043
miR-193a-5p1.70.007
miR-370-3p1.70.020
miR-758-5p1.70.044
miR-584-5p-2.10.021
miR-598-3p-2.20.050
miR-449c-3p-2.40.042
miR-181a-2-3p-2.50.022
miR-10b-5p-;2.70.035
miR-143-3p-2.80.034
miR-889-3p-2.80.041
miR-100-5p-2.90.028
A list of miRNAs from the miRNAome study that were found to be significant across all doses at the 6 h timepoint after three cut-offs were applied to the initial data: p-value < 0.05, fold change >1.5, and sequencing read count >50 reads in all three biological replicates.
Table 2. A list of top mRNA targets for selected radiation-induced miRNA.
Table 2. A list of top mRNA targets for selected radiation-induced miRNA.
miRNAmRNA Targets
miR-362-5pRbm27, Trim50, Sgip1, Plagl2, Prkacb, Luc7l3, Edem1, Cyp1b1, Rmi1, Mrpl35, Pik3c2b, Cyld, Gas7
miR-491-5pSema6a, Chrnb2, Pogk, Ksr2, Samd4b, Optc, Cpne5, Foxp4, Msn, Igf2, Smad3, Bcl2l1, Egfr, Notch3, Mmp9, Igf2bp1, Wnt3a, Capns1
miR-495-5pCttn, Ncoa2, Znf281, Tnpo1, Hnrnpd, Sbno1, Dipk2a, Mcub, Nol4l, Camta1, Cdk6, Mta3
miR-502-3pAdamts3, Kctd9, Fbn2, Sec63, Zfx, Dapk1, Smim13, Napil5, Csde1, Set, Olfm4
miR-584-5pUsp6nl, Avpr1a, Hsd11b1, Galnt15, Gbp5, Cd200, Ppm1a, Nphp1, Rock1, Mmp14, Kcne2, Wwp1, Cdk16
miR-758-5pSlc20a2, Id2, Nufip2, Ptp4a1, Tox4, Setd5, Phactr1, Rtkn, Dsg3, Csnk1a1l, Cd36, Zbtb20, Cbx5
miR-1228-3pPpp2r2d, Ube2d2, Irx2, Znf554, Nfia, Socs6, Rabgef1, Tjp1, Tor1aip1, Zbtb44, Moap1, Csnk2a1, Plac8
miR-3135bLrrc27, Fmnl3, Ttc21b, Castor3, Xpo7, Ppm1a, Dnm1l, Kdm3b, Rbp1, Faap20, Pten, Golph3
A list of potential miRNA gene targets was obtained from the miRBD database for each of the miRNA genes in Figure 1. The miRBD database presented a score denoting the likelihood of the miRNA interacting with various mRNA. From that scoring, the top dozen ranked mRNA gene targets for each miRNA were chosen for further analyses.
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Peterson, J.; McTiernan, C.D.; Thome, C.; Khaper, N.; Lees, S.J.; Boreham, D.R.; Tai, T.C.; Tharmalingam, S. Identification of Radiation-Induced miRNA Biomarkers Using the CGL1 Cell Model System. Bioengineering 2022, 9, 214. https://0-doi-org.brum.beds.ac.uk/10.3390/bioengineering9050214

AMA Style

Peterson J, McTiernan CD, Thome C, Khaper N, Lees SJ, Boreham DR, Tai TC, Tharmalingam S. Identification of Radiation-Induced miRNA Biomarkers Using the CGL1 Cell Model System. Bioengineering. 2022; 9(5):214. https://0-doi-org.brum.beds.ac.uk/10.3390/bioengineering9050214

Chicago/Turabian Style

Peterson, Jayden, Christopher D. McTiernan, Christopher Thome, Neelam Khaper, Simon J. Lees, Douglas R. Boreham, Tze Chun Tai, and Sujeenthar Tharmalingam. 2022. "Identification of Radiation-Induced miRNA Biomarkers Using the CGL1 Cell Model System" Bioengineering 9, no. 5: 214. https://0-doi-org.brum.beds.ac.uk/10.3390/bioengineering9050214

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