Development of a body fluid identification multiplex via DNA methylation analysis

The goal of this study is to develop an epigenetic multiplex for body fluid identification based on tissue specific DNA methylation. A series of genetic loci capable of discerning the origin of DNA as coming from saliva, blood, vaginal epithelia, or semen were used for this application. The markers – BCAS4, CG06379435, VE_8, and ZC3H12D – were amplified together and then sequenced via pyrosequencing. Methylation values for cytosine guanine dinucleotide (CpG) sites at each locus were then measured across the four markers. In total, 124 samples were collected, and bisulfite modified to convert unmethylated DNA to uracil. This converted DNA was then amplified via multiplex PCR with reverse primers containing a biotin molecule. Biotinylated PCR products were then analyzed using pyrosequencing to generate a series of pyrograms containing 18 CpG sites. The percent methylation at each CpG site was determined, and then agglomerative hierarchical cluster analysis was used to create a model to indicate sample origin. Further analysis reduced the number of CpG sites required for optimal determination of body fluid type to five. This study demonstrates an efficient multiplexed body fluid identification process utilizing DNA methylation that can be easily implemented in forensic laboratories.     

A data-driven,high-throughput methodology to determine tissue-specific differentially methylated regions able to discriminate body fluids

Tissue-specific differentially methylated regions (tDMRs) are regions of the genome with methylation patterns that modulate gene expression in those tissue types. The detection of tDMRs in forensic evidence can permit the identification of body fluids at trace levels. In this report, we have performed a bioinformatic analysis of an existing array dataset to determine if new tDMRs could be identified for use in body fluid identification from forensic evidence. Once these sites were identified, primers were designed and bisulfite modification was performed. The relative methylation level for each body fluid at a given locus was then determined using qPCR with high-resolution melt analysis (HRM). After screening 127 tDMR's in multiple body fluids, we were able to identify four new markers able to discriminate blood (2 markers), vaginal epithelia (1 marker) and buccal cells (1 marker). One marker for each target body fluid was also tested with pyrosequencing showing results consistent with those obtained by HRM. This work successfully demonstrates the ability of in silico analysis to develop a novel set of tDMRs capable of being differentiated by real time PCR/HRM. The method can rapidly determine the body fluids left at crime scenes, assisting the triers of fact in forensic casework.     

p16基因甲基化的芯片定量检测

p16基因的失活与多种肿瘤相关,但p16基因缺失率较低,突变更为罕见,p16基因启动子区CpG岛甲基化与其蛋白表达密切相关．DNA甲基化已成为目前研究的热点,现有的技术包括：Southernblot法、限制性内切酶-PCR法、DNA测序法、甲基化特异性PCR(MSP)、     

High-resolution melt analysis for the detection of skin/sweat via DNA methylation

The determination of tissue type is important when reconstructing a crime scene as skin cells may indicate innocent contact, whereas other types of cells, such as blood and semen, may indicate foul play. Up to now, there has been no specific DNA methylation-based marker to distinguish skin cell DNA from other body fluids. The goal of this study is to develop a DNA methylation-based assay to detect and identify skin cells collected at forensic crime scenes for use in DNA typing. For this reason, we have utilized a DNA methylation chip array-based genome-wide association study to identify skin-specific DNA methylation markers. DNA obtained from skin along with other body fluids, such as semen, saliva, blood, and vaginal epithelia, were tested using five genes that were identified as sites for potential new epigenetic skin markers. Samples were collected, bisulfite converted, and subjected to real-time polymerase chain reaction (PCR) with high-resolution melt analysis. In our studies, when using WDR11, PON2, and NHSL1 assays with bisulfite-modified PCR, skin/sweat amplicons melted at lower temperatures compared to blood, saliva, semen, and vaginal epithelia. One-way analysis of variance demonstrates that these three skin/sweat markers are significantly different when compared with other body fluids (p < 0.05). These results demonstrate that high-resolution melt analysis is a promising technology to detect and identify skin/sweat DNA from other body fluids.     

Determining the global DNA methylation status of rat according to the identifier repetitive elements

A large portion of the genome represents repetitive elements. Identifier (ID) elements, the major elements of short interspersed repetitive elements, are widespread with about 150 000 copies in the rat genome. Each ID element contains six CpG dinucleotides, which might account for the global methylation status of rat. We validated the CpG methylation of the ID elements by various methods. The methylation of one CpG site (CpG-3) of the ID element was investigated by performing pyrosequencing. The methylation percentage of the CpG-3 site was 53.6% (SD = 2.2) on average from six rat tissues with blood, but 24.6% (SD = 1.0) in rat pheochromocytoma, PC-12, cell line. This CpG-3 methylation was further verified by whole genome amplification (WGA), 5-azacytidine treatment, and proportional mixing of rat WGA genomic DNA (gDNA) with liver gDNA. Methylation-sensitive restriction enzyme PCR method showed that three other CpG sites (CpG-1, CpG-4, and CpG-5) within the ID element were also methylated (about 60%) in rat gDNA, but not in WGA gDNA. The ID elements may be good candidates for routine analysis of the global DNA methylation changes of rat for pharmaceutical treatment and their use can make basic epigenetic research possible with high accuracy.     

Predicting human age by detecting DNA methylation status in hair

Age prediction is of great importance for criminal investigation and judicial expertise. DNA methylation status is considered a promising method to infer tissue age by virtue of age-dependent changes on methylation sites. In recent years, forensic scientists have established various models to predict the chronological age of blood, saliva, and semen based on DNA methylation status. However, hair-inferred age has not been studied in the field of forensic science. In this study, we measured the methylation statuses of potential age-related CpG sites by using the multiplex methylation SNaPshot method. A total of 10 CpG sites from the LAG3, SCGN, ELOVL2, KLF14, C1orf132, SLC12A5, GRIA2, and PDE4C genes were found to be tightly associated with age in hair follicles. A correlation coefficient above 0.7 was found for four CpG sites (cg24724428 and Chr6:11044628 in ELOVL2, cg25148589 in GRIA2, and cg07547549 in SLC12A5). Among four age-prediction models, the multiple linear regression model consisting of 10 CpG sites provided the best-fitting results, with a median absolute deviation of 3.68 years. It is feasible to obtain both human identification and age information from a single scalp hair follicle. No significant differences in methylation degree were found between different sexes, hair types, or hair colors. In conclusion, we established a method to evaluate chronological age by assessing DNA methylation status in hair follicles.     

Quantitative analysis of DNA methylation in the promoter region of the methylguanine‐O6‐DNA‐methyltransferase gene by COBRA and subsequent native capillary gel electrophoresis

Along with histone modifications, RNA interference and delayed replication timing, DNA methylation belongs to the key processes in epigenetic regulation of gene expression. Therefore, reliable information about the methylation level of particular DNA fragments is of major interest. Herein the methylation level at two positions of the promoter region of the gene methylguanine‐O⁶‐DNA‐Methyltransferase (MGMT) was investigated. Previously, it was demonstrated that the epigenetic status of this DNA region correlates with response to alkylating anticancer agents. An automated CGE method with LIF detection was established to separate the six DNA fragments resulting from combined bisulfite restriction analysis of the methylated and non‐methylated MGMT promoter. In COBRA, the DNA was treated with bisulfite converting cytosine into uracil. During PCR uracil pairs with adenine, which changes the original recognition site of the restriction enzyme Taql. Artificial probes generated by mixing appropriate amounts of DNA after bisulfite treatment and PCR amplification were used for validation of the method. The methylation levels of these samples could be determined with high accuracy and precision. DNA samples prepared by mixing the corresponding clones first and then performing PCR amplification led to non‐linear correlation between the corrected peak areas and the methylation levels. This effect is explained by slightly different PCR amplification of DNA with different sequences present in the mixture. The superiority of CGE over PAGE was clearly demonstrated. Finally, the established method was used to analyze the methylation levels of human brain tumor tissue samples.     

Analysis of DNA methylation markers for tissue identification in individuals with different clinical phenotypes

Deoxyribonucleic acid (DNA) methylation patterns can be used to identify the type of tissue or body fluid found at a crime scene. However, tissue-related methylation levels have not been analyzed in individuals with different illnesses and medical conditions in forensic-specific studies. The primary goal of this study was to investigate if certain clinical phenotypes can alter the methylation levels of CpG sites in genes involved in tissue typing. Four studies with focus on DNA methylation analysis on individuals with different clinical conditions were selected from the Gene Expression Omnibus database. Then, a list of 137 CpG sites was compiled for further investigation. Statistical tests were performed to compare the beta-values results obtained for the control groups and the individuals affected by medical conditions. For each study, CpG sites that presented significant statistical differences between patients and control group were identified and it was possible to notice that DNA methylation levels can be affected in sites with potential forensic use. Although the observed DNA methylation variation (less than 10% difference) in this study would likely not cause any issues in body fluid identification, the results are important to show that this type of analysis should be taken into consideration when investigating and further validating body fluid markers. The CpG sites identified in this study should be further investigated by future studies on body fluids identification, and due to the significant difference in methylation levels in samples from affected individuals, caution must be taken before including these sites in tissue identification investigations.     

Genetic analyzer-dependent DNA methylation detection and its application to existing age prediction models

DNA methylation is the most promising biomarker for estimating human age. There are various methods used for analyzing DNA methylation. Among those, the SNaPshot assay-based method provides a semi-quantitative measurement of DNA methylation using capillary electrophoresis on genetic analyzers. However, DNA methylation measures produced using different types of genetic analyzers have never been compared, although differences in methylation values can directly affect age estimates. To evaluate the differences between the results generated by different genetic analyzers, we analyzed the same blood, saliva, and control methylated DNA using three genetic analyzers—the Applied Biosystems 3130, 3500, and SeqStudio—and compared the methylation values at five CpG sites: ELOVL2, FHL2, KLF14, MIR29B2C, and TRIM59. The methylation value at each of the five CpG sites decreased in the order 3130, 3500, and SeqStudio. The differences in the results produced by the different genetic analyzers resulted in significant errors when applying the 3500 and SeqStudio data to a previous age estimation model constructed using the 3130 Genetic Analyzer data. Therefore, DNA methylation measurements from 3500 and SeqStudio were corrected using the regression functions obtained by plotting the DNA methylation data of one instrument versus the other to facilitate the application of DNA methylation data from one instrument to the age prediction model based on other instruments. The age prediction accuracy obtained by applying corrected 3500 and SeqStudio data to the existing age estimation model was as high as observed in the 3130 data.     

DNA methylation-based age prediction with bloodstains using pyrosequencing and random forest regression

The use of DNA methylation to predict chronological age has shown promising potential for obtaining additional information in forensic investigations. To date, several studies have reported age prediction models based on DNA methylation in body fluids with high DNA content. However, it is often difficult to apply these existing methods in practice due to the low amount of DNA present in stains of body fluids that are part of a trace material. In this study, we present a sensitive and rapid test for age prediction with bloodstains based on pyrosequencing and random forest regression. This assay requires only 0.1 ng of genomic DNA and the entire procedure can be completed within 10 h, making it practical for forensic investigations that require a short turnaround time. We examined the methylation levels of 46 CpG sites from six genes using bloodstain samples from 128 males and 113 females aged 10–79 years. A random forest regression model was then used to construct an age prediction model for males and females separately. The final age prediction models were developed with seven CpG sites (three for males and four for females) based on the performance of the random forest regression. The mean absolute deviation was less than 3 years for each model. Our results demonstrate that DNA methylation-based age prediction using pyrosequencing and random forest regression has potential applications in forensics to accurately predict the biological age of a bloodstain donor.     

Quantitative DNA methylation analysis by fluorescent polymerase chain reaction single-strand conformation polymorphism using an automated DNA sequencer

A novel DNA methylation assay technique, termed bisulfite single-strand conformation polymorphism (bisulfite-SSCP), is a combination of sodium-bisulfite modification and fluorescence-based polymerase chain reaction (PCR)-SSCP. After bisulfite treatment followed by PCR amplification, methylated and unmethylated alleles can be simultaneously separated in a nondenaturing gel using an automated DNA sequencer. Using bisulfite-SSCP, methylation of hMLH1 was detected in a quantitative manner. This method is not only simple, quick, accurate, and quantitative, but detailed information about methylation is also available with less work. Methylation analysis of large numbers of samples for multiple loci will be facilitated by bisulfite-SSCP.     

Evaluation of a potential epigenetic biomarker by quantitative methyl-single nucleotide polymorphism analysis

Tumorigenesis is characterized by alterations of methylation profiles including loss and gain of 5-methylcytosine. Recently, we identified a single CpG, which seemed to be consistently hypomethylated in pilocytic astrocytomas but not in other gliomas. To evaluate its applicability as a biomarker, we examined its methylation status in a large panel of gliomas (n = 97). Methylation-dependent DNA sequence variation may be considered a kind of single nucleotide polymorphism (methylSNP). MethylSNPs can be easily converted into common SNPs of the C/T type by sodium bisulfite treatment of the DNA and afterwards subjected to conventional SNP typing. We adapted SnaPshot trade mark and Pyrosequencing trade mark to determine the methylation of our test CpG in a quantitative manner. The adapted methods, called SNaPmeth and PyroMeth, respectively, gave nearly identical results, however data obtained with PyroMeth showed less scattering. Furthermore, the integrated software for allele frequency determination from Pyrosequencing could be used directly for data analysis while SnaPmeth data had to be exported and processed manually. Although data did not confirm our previous result of a preferential hypomethylation of the tested CpG in pilocytic astrocytomas, we consider quantitative methylSNP analysis by SNaPmeth or PyroMeth a favorable alternative to existing high-throughput methylation assays. It combines single CpG analysis with accurate quantitation and is amenable to high throughput.     

Novel Photodynamic Effect of a Psoralen‐Conjugated Oligonucleotide for the Discrimination of the Methylation of Cytosine in DNA

DNA methylation and demethylation significantly affect the deactivation and activation processes of gene expression significantly. In particular, C‐5‐methylation of cytosine in the CpG islands is important for the epigenetic modification in genes, which plays a key role in regulating gene expression. The determination of the location and frequency of DNA methylation is important for the elucidation of the mechanisms of cell differentiation and carcinogenesis. Here we designed a psoralen‐conjugated oligonucleotide (PS‐oligo) for the discrimination of 5‐methylcytosine (5‐mC) in DNA. The cross‐linking behavior of psoralen derivatives with pyrimidine bases, such as thymine, uracil and cytosine has been well discussed, but there are no reports which have examined whether cross‐linking efficiency of psoralen with cytosine would be changed with or without C‐5 methylation. We found that the cross‐linking efficiency of PS‐oligo with target‐DNA containing 5‐mC was greatly increased compared to the case of target‐DNA without 5‐mC, approximately seven‐fold higher. Here we report a new aspect of the photocross‐linking behavior of psoralen with 5‐mC that is applicable to a simple, sequence‐specific and quantitative analysis for the discrimination of 5‐mC in DNA, which can be applicable to study the epigenetic behavior of gene expressions.     

Viscoelastic particle focusing in human biofluids

Saliva and blood plasma are non-Newtonian viscoelastic fluids that play essential roles in the transport of particulate matters (e.g., food and blood cells). However, whether the viscoelasticity of such biofluids alters the dynamics of suspended particles is still unknown. In this study, we report that under pressure-driven microflows of both human saliva and blood plasma, spherical particles laterally migrate and form a focused stream along the channel centerline by their viscoelastic properties. We observed that the particle focusing varied among samples on the basis of sampling times/donors, thereby demonstrating that the viscoelasticity of the human biofluids can be affected by their compositions. We showed that the particle focusing, observed in bovine submaxillary mucin solutions, intensified with the increase in mucin concentration. We expect that the findings from this study will contribute to the understanding of the physiological roles of viscoelasticity of human biofluids.     

The role of DNA hypermethylation in human neoplasia

Cancer development and progression is dictated by a series of alterations in genes such as oncogenes, tumor suppressor genes, DNA repair genes, and others. DNA methylation is an epigenetic modification that is profoundly altered in most cancers. Recently, hypermethylation of CpG-rich areas located in the promoter of genes (CpG islands) has been shown to be commonly implicated in silencing tumor suppressor genes in cancer. By cloning and characterizing a large number of such CpG islands hypermethylated in colon cancer, we found that two processes explain most of these events. Age-related CpG island methylation in a subset of cells in normal tissues, followed by intensification of methylation in cancer cells explains the majority of hypermethylation events in colon cancer and may provide a mechanistic link between aging and cancer formation. Most of the other CpG islands methylated in colon cancer can be explained by a newly described phenotype, the CpG island methylator phenotype (CIMP) which results in multiple methylation events in a subset of cancers. CIMP accounts for the majority of sporadic colon cancers characterized by microsatellite instability, as well as most tumors with k-ras mutations. Understanding further the factors that lead to, and modulate, aberrant methylation in cancer may provide novel avenues for prevention and treatment of this disease.