Label-Free Real-Time Detection of DNA Methylation Based on Quartz

Jan 29, 2013 - DNA methylation plays an important role in the regulation of gene transcription, chromatin compaction, genome imprinting, and X-chromos...
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Label-Free Real-Time Detection of DNA Methylation Based on Quartz Crystal Microbalance Measurement Jie Wang,†,‡,§ Zhiqiang Zhu,† and Hongwei Ma*,† †

Division of Nanobiomedicine, Suzhou Institute of Nano-Tech and Nano-Bionics, Chinese Academy of Sciences, Suzhou, Jiangsu 215123, People’s Republic of China ‡ Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, People’s Republic of China § University of Chinese Academy of Sciences, Beijing, 100049, People’s Republic of China S Supporting Information *

ABSTRACT: DNA methylation plays an important role in the regulation of gene transcription, chromatin compaction, genome imprinting, and Xchromosome inactivation. DNA methyltransferase is considered a potential target for anticancer drug design. It is important to locate aberrantly methylated sequences on the human genome that are linked to specific diseases and to discover new low-toxic methylation inhibitors for medical treatments. We developed a DNA methylation detection method using a quartz crystal microbalance (QCM). We applied this method to assay genes p16 and GALR2 in two cell lines. Methylation of p16 was detected in both HT29 and HepG2 cell lines, whereas methylation of GALR2 was detected only in the HT29 cell line. We also used this method to evaluate the effect of 5-aza-2′-deoxycytidine (decitabine), a methyltransferase inhibitor used in clinical treatment. We found methylation of genes p16 and GALR2 to be strongly inhibited. The results show that this method is sensitive to DNA methylation and is fit for evaluation of methyltransferase inhibitors.

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PCR-assisted methods such as HpaII-PCR, combined bisulfite restriction analysis (COBRA), and methylationsensitive single-nucleotide primer extension (Ms-SNuPE) are more practical and advantageous in that they require very low DNA sample consumption. We developed a method that combined HpaII-PCR with quartz crystal microbalance (QCM) measurement for methylation detection. Specifically, we chose two suppressor genes, namely, cyclin-dependent kinase inhibitor 2A gene (p16) and galanin receptor 2 gene (GALR2), because many diseases have been found to be associated with aberrant methylation of suppressor genes.29−31 QCM is a mass sensor based on the piezoelectric properties of quartz crystals with many applications in both scientific research and industry.32−40 Recently, we proposed a “solidified liquid layer” (SLL) model that made feasible the quantitative analysis of QCM in liquid.41 To the best of our knowledge, we describe herein the first example of QCM-based DNA methylation detection.

he process of DNA methylation is a crucial part of DNA epigenetics, playing essential roles in the regulation of gene transcription, chromatin compaction, genome imprinting, and X-chromosome inactivation in all mammals.1−5 Because DNA aberrant methylation of tumor-linked genes is regarded as a hallmark of a number of diseases, including muscular dystrophy, some birth defects, cardiovascular diseases, and cancers, methyltransferase is considered a promising target for the development and implementation of new therapeutic approaches.6−13 For example, DNA methyltransferase inhibitors, such as 5-azacytidine and 5-aza-2′-deoxycytidine, have been approved for epigenetic therapy for DNA methylationrelated diseases.8−12 Existing methods that detect DNA methylation are based mainly on three techniques: methylation-sensitive restriction enzyme digestion, bisulfite treatment, and methylation antibody recognition.14,15 Methylation-specific polymerase chain reaction (MSP) analysis with bisulfite treatment16 is the most widely used method, but it carries a significant risk of false-positive/ negative results.17−19 Both bisulfite20 and chemical DNA sequencing21 require large amounts of purified polymerase chain reaction (PCR) products, labor-intensive procedures, and costly apparatuses.22−24 Other methods, such as radioactivelabel-based protocols,25,26 matrix-assisted laser desorption/ ionization mass spectrometry, and ion-pair reversed-phase high-performance liquid chromatography,27,28 are less popular because the skills of experienced technicians are required. Therefore, cheaper, faster, easily performed approaches are needed for detection of DNA methylation. © 2013 American Chemical Society

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MATERIAL AND METHODS Tropsin, Dulbecco’s modified Eagle’s medium (DMEM), and serum were obtained from Hyclone (Thermo Scientific, U.S.A.). TIANamp genomic DNA kit was purchased from Tiangen Biotech Co., Ltd. (Beijing, China), and 6-mercapto-1hexanol (MCH) was purchased from Sigma-Aldrich (St. Louis, U.S.A.). Received: September 14, 2012 Accepted: January 9, 2013 Published: January 29, 2013 2096

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HpaII enzyme, MspI enzyme, DNA marker, 25× dNTP mixture, 2× GC buffer I, and Hot Start Taq DNA polymerase (5 U μL−1) were obtained from Fermentas (Massachusetts, U.S.A.). The DNA probe functionalized with a thiol group was synthesized by Invitrogen Biotechnology Co., Ltd. (Shanghai, China). Synthetic target DNA and PCR primers were both purchased from Shanghai Sunny Biology Technology (Shanghai, China). The PCR primers were used to amplify gene promoter sequences located within CpG islands of the p16 and GALR2 genes. See the Supporting Information for sequences of the primers for nested PCR and probe. Probe Immobilization. The QCM chips were incubated with 1 μM DNA probe in PBS (0.1 M phosphate-buffered saline (PBS), 1 M NaCl, pH 7.4) for 2 h at room temperature (r.t.). After that, DNA-immobilized chips were immersed in 1 mM MCH PBS solution for 2 h at r.t. Finally, the QCM chips were rinsed with water and dried under nitrogen flow. DNA Methylation Detection. See the Supporting Information for genome extraction, digestion, PCR and primer design for nested PCR. The probe DNA-functionalized QCM chips were loaded into the QCM sensor chamber. The doublestranded PCR product was subjected to a denaturation step (5 min of incubation at 95 °C followed by 1 min on ice) to obtain single-stranded DNA (ssDNA).4 After establishing a baseline, the ssDNA was introduced into the flow channel of the QCM chamber at 37 °C, with PBS used as the running buffer at a flow rate of 30 μL/min. The DNA hybridization between probes and the target DNA, combined with the surrounding liquid, induced a QCM resonance frequency shift (Δf). Diluted solutions of negative control, mock sample, MspI-digested, and HpaII-PCR sample were similarly injected into the QCM sensor chamber for DNA methylation detection.

Scheme 1. Principle of QCM-Based Detection of DNA Methylationa

a (a) Methylated DNA survived HpaII digestion and served as a PCR template. PCR products were detected by QCM. (b) Unmethylated DNA was digested by HpaII and could not serve as a PCR template. There were no PCR products to be measured by QCM.

Methylation Measurement of p16 and GALR2 Genes. We first used synthetic double-stranded DNA as target DNA to obtain a linear dynamic range between the target DNA concentration and Δf. The synthetic DNA had 40 base pairs and was complementary to the DNA probe. After denaturing at 95 °C for 5 min, the synthetic target DNA was injected into the QCM flow channel. The tested concentration of target DNA (ranging from 20 nM to 1 μM) was able to principally cover the PCR product concentration. Figure 1b shows the hybridization process between the synthetic target DNA and the probe on the chip. We found a linear relationship between Δf and the DNA concentration with an R2 value of 0.978, as shown in Figure 1c, indicating that QCM was able to quantitatively assay double-stranded DNA over 3 orders of magnitude, with the limit of detection being less than 20 nM. We then applied this QCM-based method to measure real biological samples, i.e., to assay the methylation status of p16 and GALR2 in HT29 and HepG2 cell lines. Both p16 and GALR2 are tumor suppressor genes, regulating the cell cycle and encoding a G-protein-coupled receptor, respectively. Genomic DNAs of HT29 and HepG2 cells were extracted at 80% confluence, digested by HpaII, and amplified by PCR, denoted as the HpaII-PCR sample. We also prepared mock sample (to verify DNA integrity), by applying all treatments that were applied to the HpaII-PCR sample except digestion by HpaII, and negative control sample (equivalent PCR reagents were diluted with PBS buffer). In addition, MspI was used as an isoschizomer of HpaII because MspI is not sensitive to DNA methylation (at least not to CpG methylation). We used MspI to verify the accessibility of the DNA for an enzyme and to determine the background amplification for PCR. Genome DNAs were digested by MspI, and amplified by PCR, denoted as the Msp-PCR sample. These four samples induced different

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RESULTS QCM-Based Detection of DNA Methylation. The principle of QCM-based detection of DNA methylation is illustrated in Scheme 1. First, a small amount of genomic DNA is digested by HpaII, which is a methylation-sensitive restriction endonuclease. All unmethylated recognition sites are cleaved, while those that are methylated are conserved. Second, digested DNA is amplified by means of conventional nested PCR. PCR amplification succeeds only for methylated sequences; the methylated DNA is protected from the digestion of HpaII and retains intact to serve as DNA template in the PCR process. Finally, PCR products are injected into a QCM sensor chamber and hybridized with the probe at the surface, which induces a real-time QCM frequency shift (Δf). For methylated DNA, a large amount of PCR product hybridizes with the DNA probe on the chip surface, leading to a significant Δf. For unmethylated DNA, ineffective PCR amplification induces a negligible Δf. DNA Probe Immobilization. The immobilization of thiolfunctionalized DNA on gold surfaces is well-established.42,43 As shown in Figure 1a, the QCM frequency curve dropped sharply upon the introduction of DNA probe solution and then stabilized after 30 min. The immobilization of 35-mer probes caused a 31 ± 4 Hz frequency shift, which was calculated to represent 1.5 nm thickness of the immobilized DNA probe layer, close to the thickness of a densely packed oligonucleotide layer.41 In this study, the chip was incubated with DNA probe solution for 2 h. After that, the QCM chip was incubated with 1 mM MCH solution to improve the hybridization efficiency.44 2097

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Figure 1. Linear dynamic range between target DNA concentration and QCM frequency shift (Δf). (a) The immobilization of probe DNA was monitored by QCM. A 30 Hz frequency shift indicated the formation of a 1.5 nm thick layer, close to the thickness of a densely packed oligonucleotide layer. (b) QCM curves for synthetic target 40 bp DNA at five different concentrations. (c) Linear relation between Δf and concentration of synthetic target 40 bp DNA: y = ax + b, a = 49.6, b = 0, R2 = 0.978.

Figure 2. QCM-based method indicated different methylation statuses of p16 and GALR2 genes in HT29 and HepG2 cell lines: (a) the p16 gene in HT29 cells; (b) the GALR2 gene in HepG2 cells. The blue line denotes the HpaII-PCR sample: cell genome was first digested by HpaII enzyme and amplified by PCR. The PCR product flowed through the QCM, was captured by the probe on the chip, and induced Δf. The red line denotes the mock sample: genome DNA had not been digested by HpaII enzyme before PCR. The black line denotes the negative control: the addition of equivalent reagent mixtures. The magenta line denotes Msp-PCR: genome DNAs were digested by MspI enzyme before PCR.

Figure 3. Representative QCM curves for evaluation of methyltransferase inhibitor. (a) The p16 gene in HT29 cells. The blue line denotes the inhibitor sample: HT29 cells were cultured with decitabine for 48 h. The extracted DNA was digested by HpaII enzyme and amplified by PCR. The PCR product flowed through the QCM and was captured by the probe on the chip. The red line denotes mock sample, which is also the HpaII-PCR sample in Figure 2: cells had not been cultured with decitabine before genomes were extracted. The black line denotes the negative control: the addition of equivalent reagent mixtures for PCR. The magenta line denotes Msp-PCR: inhibitor-treated genome DNAs were digested by MspI enzyme before PCR. (b) GALR2 gene in HepG2 cell. HepG2 cells were cultured with decitabine for 48 h. Then extracted genome was digested by HpaII enzyme and amplified by PCR. The PCR product flowed through the QCM sensor chamber and was captured by the probe on the chip.

Δfs, as shown in Figure 2 and Supporting Information Figure S1, and were denoted as ΔHpa, ΔMock, ΔNega, and ΔMsp. For p16 in the HT29 cell line (Figure 2a), ΔHpa, ΔMock, ΔNega, and ΔMsp were Δf = 43 ± 1, 50 ± 2, 2 ± 1, and 4 ± 1 Hz, respectively (n = 3). For GALR2 in the HepG2 cell line (Figure 2b), ΔHpa, ΔMock, ΔNega, and ΔMsp were Δf = 2 ± 1, 65 ± 2, 2 ± 1, and 1 ± 1 Hz, respectively (n = 3). See also Supporting Information Figure S1 for the results of p16 in HepG2 cell line, and GALR2 in the HT29 cell line. Because these Δf values were within the linear dynamic range (Figure 1c), quantitative analysis of the methylation status of

the genes could be accomplished via the methylation index as defined below: methylation index =

ΔHpa − ΔMsp × 100% ΔMock − ΔMsp

where ΔHpa − ΔMsp is the quantity of methylated sequences measured by QCM following digestion by HpaII and PCR; ΔMock − ΔMsp is the quantity of all sequences measured by QCM after PCR without digestion. 2098

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Figure 4. (a) Methylation index of inhibitor-free samples (without inhibition by decitabine) and the inhibitor sample. The contrasts in the index between the black and red groups show that, except for GALR2 in the HepG2 group, gene promoter methylation was markedly repressed. (b) Induced Δf by p16 and GALR2 sequences from negative control, mock-PCR sample (without digestion by HpaII), HpaII-PCR (without inhibition by decitabine), and inhibitor-treated sample. With the exception of GALR2 in HepG2, the Δf of the inhibitor-treated sample is lower than that of the HpaII-PCR sample, and the latter is lower than that of the mock-PCR sample, which is in accordance with our anticipation. This result indicates that gene promoter sequences were differentially methylated in the samples. The inhibitor does repress methylation at these DNA sites.

For p16 in the HT29 cell line, the methylation index was 84.8% ± 4.3%. For GALR2 in the HepG2 cell line, the methylation index was 1.6% ± 2.2%. This means that for p16 in the HT29 cell line, 84.8% cells are methylated, and for GALR2 in the HepG2 cell line, 1.6% cells are methylated. Consistency between other method and QCM assay is indispensable for deciding whether the QCM assay truly reflects the methylation status of the target sequence. These QCM results were validated by MSP electrophoresis analysis, as shown in Supporting Information Figure S3. All of the above-mentioned results confirm that QCM can accurately assay DNA methylation. Evaluation of DNA Methylation Inhibitors. A cytidine analogue, 5-aza-2′-deoxycytidine (decitabine, Dacogen, DAC), was incorporated into the DNA of dividing cells and hypomethylated DNA by forming covalent complexes with the DNA methyltransferases (DNMTs). Decitabine is FDAapproved for the treatment of myelodysplastic syndrome (MDS). First, we used decitabine to inhibit methylation on the genome. Then, we applied QCM to detect the changes in methylation level on p16 and GALR2 to evaluate the inhibitor’s effect. Decitabine was diluted with sterilized water to yield a 10 μM solution. We cultured HT29 cells and HepG2 cells in DMEM medium. At 80% confluence, 400 μL of decitabine solution was added to 3.6 mL cell cultures for 48 h to inhibit DNA methylation on the genome.12 The cell growth and proliferation slowed down after the addition of decitabine solution, but no evident cell death or morphological rupture was observed. The inhibiting effect of decitabine on p16 and GALR2 promoters was evaluated by QCM, as shown in Figure 3. After treatment with decitabine, whole DNAs of HT29 and HepG2 cells were extracted, digested by HpaII, and amplified by PCR; these samples were denoted inhibitor samples. We also prepared mock samples (to check the original methylation level without the use of inhibitor, by including all treatments used for the inhibitor samples except treatment with decitabine) and a negative control sample (equivalent PCR reagents were diluted with PBS buffer). Genome DNAs were treated with inhibitor, later digested by MspI, and amplified by

PCR, denoted as the Msp-PCR sample. These four samples induced different changes, as shown in Figure 3, and were denoted as ΔInh, ΔMock, ΔNega, and ΔMsp, respectively. For p16 in HT29 cell line, ΔInh, ΔMock, ΔNega and ΔMsp were Δf = 26 ± 1, 43 ± 2, 2 ± 1, and 2 ± 1 Hz, respectively (n = 3). For GALR2 in HepG2 cell line, ΔInh, ΔMock, ΔNega, and ΔMsp were Δf = 2 ± 1, 2 ± 1, 2 ± 1, and 4 ± 1 Hz, respectively (n = 3). As shown in Figure 3 and Supporting Information Figure S2, for p16 in both HT29 and HepG2 cells and GALR2 in HT29 cells, Δf induced by inhibitor samples is lower than that induced by mock sample, which shows that the inhibition effect actually occurs. To quantify the inhibition effect, an inhibition effect index was derived as follows: ⎛ ΔInh − ΔMsp ⎞ inhibition effect index = ⎜1 − ⎟ × 100% ΔMock − ΔMsp ⎠ ⎝

where ΔInh − ΔMsp is the quantity of methylation after inhibition on the sequences and ΔMock − ΔMsp is the original methylation on the sequences. For p16 in HT29 and GALR2 in HepG2 cell lines, the inhibition effect indexes were 41.5% ± 3.9% and 0% ± 70.7%, respectively. For p16 in HT29 cells, 41.5% methylation was inhibited. For GALR2 in HepG2 cells, caution must be taken for the 0% inhibition effect because this site is only slightly methylated (original methylation index = 1.6%). Figure 4 shows the methylation level after inhibition was strongly repressed. These QCM results were validated by MSP electrophoresis analysis and bisulfite pyrosequencing, as shown in Supporting Information Figures S3 and S4. Thus, the effect of methylation inhibitors could be evaluated by QCM. The results of methylation detection and inhibitor evaluation are summarized in Figure 4b. We assayed the methylation status of genes p16 and GALR2 in HT29 and HepG2 cell lines. The p16 gene is 84.8% methylated in HT29 cells, and GALR2 is only 1.6% methylated in HepG2 cells. After being inhibited by decitabine, methylation of the p16 gene is inhibited 41.5% in HT29 cells, indicating that inhibition effect differs at different genome sites. All the data conform to data from previous studies.45−48 These experimental results proved the QCM2099

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appropriate specific primers under the low reaction temperature of PS (28 °C).15 Compared with sequencing techniques, the QCM-based method is much easier to use, and theoretically, there is no limitation on the target DNA sequence. Gel-based methods, for example, MSP, require preparation of the gel in advance, which can be labor-intensive and highly toxic, especially when a polyacrylamide gel is needed. In and after the electrophoresis, the fluorescence dye and imaging equipment are needed. For quantitative analysis, extra software is needed. Compared with gel-based detection, the QCM-based method only requires immobilization the probe DNA in advance in parallel and injecting PCR products in the process; the data could be acquired automatically. The QCM result has higher selectivity as referred before. This QCM-based strategy is not restricted to HpaII-PCRbased methylation detection. It can be adapted to other PCRbased methods by varying PCR conditions but using the same principle. For example, this strategy could be modified for bisulfite-treated DNA sample. Furthermore, this protocol can be adapted to a high-throughput system.51 Accordingly, a QCM-based strategy could be developed to be a label-free, lowcost, highly automatic protocol with adequate sensitivity and linear dynamic range that could be applied extensively in many fields. However, HpaII or any other restriction enzyme (RE) limits the CG loci that could be assessed for that HpaII only recognizes the CCGG loci on the genome. This might cause problems when analyzing particular sequences (e.g., TF binding sites) or clinically relevant positions which do not contain a restriction site. Also, analyses of nonpalindromic sites or nonCpG-methylation are a problem when using RE, which could not recognize these sites. In conclusion, we demonstrated a new DNA methylation detection method based on the combination of QCM and HpaII-PCR techniques. The QCM-based technique meets the requirements for most research purposes including early cancer diagnosis, screening for DNA markers, and designing inhibitors for cancer treatment, for which exact methylation fractions are not usually required.45 A trace amount of sample is required, and complicated bisulfite treatment or expensive methylationsensitive antibody is not required. Distinct from other strategies that use dual-labeled DNA primers or typical fluoresceinlabeled nucleotide triphosphate in PCR, this protocol consumes a small amount of thiol-functionalized DNA probe and is easily performed. Methylation status on CpG islands can be easily identified by a oligonucleotide-modified chip in a quantitative fashion. Quantitative Δf measurement eliminates environmental perturbance, thus increasing the repeatability and reliability of the results. This method can also be used to evaluate the inhibitor effect on specific DNA sequences. Given the demonstrated high-throughput capacity of QCM by Huang’s group,51 we believe we or other groups could further develop this QCM-based method to yield parallel detection of DNA methylation, which is particularly useful for screening appropriate methylation inhibitors that may replace the currently used highly toxic inhibitors.37

based method to be an appropriate method for methylation detection and inhibitor evaluation.

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DISCUSSION We first discuss the sensitivity and quantification issues. The linear dynamic range with synthetic DNA concentration and Δf was over 3 orders of magnitude (from 20 nM to 1 μM). Because it is easy for PCR to amplify the original DNA sample to the limit of detection (estimated to be less than 20 nM), this QCM-based method is adequately sensitive for assay of DNA methylation. The SLL model shows that a 1 Hz QCM signal in liquid corresponds to the 0.18 nm thickness change.49,50 If the hybridization of DNA forms a compact layer on the chip, a 100 nt oligonucleotide forms a rigid layer with a thickness of 100 × 0.34 = 34 nm (the distance or rise along the axis of the double DNA helix is 0.34 nm between two consecutive base pairs). This 34 nm thickness change would cause a 188 Hz frequency change. In our experiments, the QCM signal was not as great as the calculation, which is attributed to the fact that, with its long length, the DNA double helix is not completely rigid and a certain amount of bending along the DNA helix makes the layer thinner. By controlling the Δf within the linear dynamic range, quantitative results were obtained by converting the QCM signal into a methylation/inhibition index. We then discuss the specificity issue. The low stringency of primer mispriming in PCR is often overlooked or underestimated. Sometimes it may bring in some false-positive results and make the qualitative interpretation of gel-based data difficult, especially when the primers are spanning several CpG sites. The comparison between MSP and bisulfite pyrosequencing has shown that the methylation threshold for MSP detection is below 25%, explaining the occasional contradictious results of MSP and the other methods used for analysis.15 For QCM, the accuracy is improved by the hybridization between complementary probe and target DNA, which further bates the possibility of nonspecific signals and enhances the assay specificity. The complexity of real biological samples may seriously undermine DNA methylation assay’s quantitative precision. Therefore, data validation is our main focus on the p16 and GALR2 genes in HepG2 and HT29 cell lines. By matching the QCM data against that from MSP and bisulfite pyrosequencing, we could find that these two results correlate well with each other, indicating a reliable performance of the QCM method under real application conditions. We finally discuss the feasibility issue. Compared with another real-time method, methylated DNA immunoprecipitation real-time quantitative PCR (Medip-qPCR), which is needed to label the DNA, our QCM-based method is labelfree. Bisulfite sequencing (BS) and bisulfite pyrosequencing (PS) can locate and analyze every single CpG site of an assay separately under certain conditions. However, these techniques require amplification of DNA and purification of PCR products, and even the PCR products have to be cloned into an appropriate vector and transferred into bacteria for cloning the DNA to improve quality of the sequencing results. Therefore, they are very labor-intensive methods unsuitable for high throughput.15 Further, for BS, although numerous clones have to be sequenced for quantitative analysis, causing large analytical effort, BS data is not accurate less than 30% quantitatively. For PS, two system-based disadvantages exist: the low sequencing distance limited to 100−150 bp per run and sequence-dependent problems due to the need for designing

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ASSOCIATED CONTENT

S Supporting Information *

Figures S1−S4 and Tables S1−S3, as noted in the text. This material is available free of charge via the Internet at http:// pubs.acs.org. 2100

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AUTHOR INFORMATION

Corresponding Author

*Phone: 0086-512-62872539. Fax: 0086-512-62872562. E-mail: [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This work was supported by the National Natural Science Foundation of China (Grants 21074148 and 21105112) and the Special Foundation of the President of the Chinese Academy of Sciences. We thank Professor Hong Chen for generous support in the cell culture work. We thank the support from Shanghai Institute of Organic Chemistry, Chinese Academy of Science. We also thank Jinying Liu for useful technical suggestions and discussions.

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dx.doi.org/10.1021/ac3026724 | Anal. Chem. 2013, 85, 2096−2101