Detection of oxidative stress in cells using epigenetic tools

Abstract

The present invention relates to epigenetic tools for detecting oxidative stress. The present invention relates to a method for identifying oxidative stress (OS) in a test cell, comprising: (a) determining the methylation status of at least one CpG site in a DNA sample obtained from a test cell; and (b) comparing the methylation status of the CpG sites from (a) with the methylation status of a control that does not contain OS; wherein a difference in methylation status of the CpG site in the test cell compared to the control CpG site indicates that the test cell has the OS.

Description

[Technical field]

[0001] The present invention relates to a method for detecting oxidative stress (OS) in cells using epigenetic markers. In particular, the method comprises determining the methylation status of CpG sites in a test cell and comparing the obtained methylation status with that of a control not containing OS, whereby a difference in the methylation status of the CpG sites in said test cell indicates the presence of said OS in said test cell. [Background technology]

[0002] Living organisms are constantly exposed to various stresses from the external environment. They maintain homeostasis and resist the stresses through various regulatory systems. Oxidative stress refers to a serious imbalance between the levels of reactive oxygen species (ROS) in a cell and its antioxidant defense mechanisms. To maintain its homeostasis, living organisms have a system called redox regulation, which regulates the redox state to deal with and resist stress. This system functions to adapt to oxidative stress from many external stressors, such as radiation, ultraviolet light, environmental pollutants, high heat, low temperature, hypoxic conditions, and infectious diseases, as well as lifestyle-related diseases, such as cancer, diabetes, arteriosclerosis, hypertension, and obesity. However, when this regulatory mechanism is disrupted due to some cause, oxidative stress (OS) occurs. OS can lead to cell damage, DNA fragmentation, apoptosis, and cell death. Early detection of OS can prevent further damage in the organism, which causes the organism to receive early treatment or start using protective mechanisms. Summary of the Invention [Problem to be solved by the invention]

[0003] There are several methods known in the art for the early detection of OS, however, none of the methods known in the art formally use a genomic sample of the body to detect OS in cells.

[0004] Human skin is constantly exposed to large amounts of oxidative stress and free radicals, e.g., ROS, which are derived from normal metabolic reactions as well as continuous exposure to air, radiation and UV rays, environmental pollutants, and physical and / or chemical agents (e.g., cosmetics). Under certain conditions, the production of ROS can be so significant that it can contribute to the pathogenesis of, for example, psoriasis or skin cancer. Oxidative damage caused by free radicals such as ROS is also the main cause of body aging in general, and skin aging in particular. Therefore, there is a need in the art for the detection of OS in cells, e.g., skin cells, to prevent further damage to cells. [Means for solving the problem]

[0005] The present invention seeks to solve the above problem by providing a method for detecting oxidative stress (OS) in a test cell by comparing the methylation status of at least one CpG site in said test cell with a corresponding CpG site in a control cell lacking OS, wherein the presence of hypo- or hypermethylation of a CpG site in said test cell indicates the presence of said OS in said test cell. Environmental factors / agents such as UV light exposure, aging, diet, etc. can induce OS by recruiting DNA methyltransferases (DNMTs) and TET enzymes to various promoters, which can further induce changes in the promoter CpG methylation status of genes, so biomarkers that result in differential methylation in cells with OS are essential to overcome the above challenges. In particular, CpG sites can be used as biomarkers to detect OS in cells. CpG sites in cells with OS are differentially methylated (i.e., hypomethylated or hypermethylated) compared to the corresponding CpG sites in cells without OS. Thus, the CpG sites can be effectively used to determine the presence or absence of OS in cells. This is particularly advantageous because epigenetics provides a means to predict the onset of OS in cells, and therefore OS can be treated earlier before the cells are further damaged. Furthermore, epigenetic markers are long-term biomarkers, i.e., heritable, and can be used to detect OS in subsequent generations, if necessary. In one aspect of the invention, there is provided a method for identifying oxidative stress (OS) in a test cell, comprising the steps of: (a) determining the methylation status of at least one CpG site in a DNA sample obtained from a test cell; and (b) comparing the methylation status of the CpG sites from (a) with the methylation status of a control that does not contain OS, wherein a difference in the methylation status of the CpG sites in the test cell compared to the CpG sites in the control indicates the presence of the OS in the test cell.

[0006] The term "cell" as used herein refers to a whole living cell, naturally occurring or modified. The cell may be isolated from other cells, mixed with other cells in culture, or within a tissue (partially or whole) or organism. In particular, the cell may be a eukaryotic cell. More particularly, the cell may be a mammalian cell. The term "mammalian cell" refers to any cell derived from a mammalian subject. The cell may also be a cell derived from the culture and propagation of cells obtained from a subject. The cell may also be genetically modified to express recombinant proteins and / or nucleic acids. Mammalian cells may be derived from humans and other primates, including non-human primates such as chimpanzees and other ape and monkey species; domestic animals such as cows, sheep, pigs, goats and horses; domestic mammals such as dogs and cats; rodents such as mice, rats, rabbits, hamsters and guinea pigs; domestic animals such as chickens, turkeys and other galliformes, ducks, geese, and birds, including wild and game birds. In particular, the subject is a mammal. More particularly, the mammal is selected from the group consisting of mouse, rat, guinea pig, dog, mini pig, human, cow, sheep, pig, goat, horse, donkey and mule. In particular, the mammalian cell may be a skin cell, a stem cell or a cell derived therefrom. More particularly, the mammalian cell may be a skin cell.

[0007] As used herein, a "CpG site" or "methylation site" is a nucleotide in a nucleic acid (DNA or RNA) that is susceptible to methylation, either by naturally occurring events in vivo or by events initiated to chemically methylate the nucleotide in vitro. Some of these sites may be hypermethylated or hypomethylated in cells with OS compared to cells without OS.

[0008] As used herein, the term "methylated nucleic acid molecule" refers to a nucleic acid molecule that contains one or more nucleotides that are methylated. "CpG island" as used herein describes a segment of DNA sequence that contains functionally or structurally deviant CpG density. For example, Yamada et al. report a set of standards for determining CpG island, which must be at least 400 nucleotides long, have a GC content higher than 50%, and an OCF / ECF ratio higher than 0.6 (Yamada et al., 2004, Genome Research, 14, 247-266). Other researchers define CpG island as a sequence at least 200 nucleotides long, with a GC content higher than 50% and an OCF / ECF ratio higher than 0.6, but are less strict (Takai et al., 2002, Proc. Natl. Acad. Sci. USA, 99, 3740-3745). In the context of the present invention, the terms "methylation profile", "methylation pattern", "methylation state" or "methylation status" are used herein to describe the state, condition or status of methylation of a genomic sequence, which refers to the characteristics of a DNA segment at a particular genomic locus related to methylation, including but not limited to whether any of the cytosine (C) residues in this DNA sequence are methylated, the position of the methylated C residues, the ratio of methylated C in any particular stretch of residues, and allelic differences in methylation due to, for example, different origins of the alleles. The term "methylation state" refers to the state of a particular methylation site (i.e., methylated vs. unmethylated), meaning that the residue or methylation site is methylated or unmethylated. A methylation profile can then be determined based on the methylation state of one or more methylation sites. Thus, the term "methylation profile" or "methylation pattern" refers to the relative or absolute concentration of methylated or unmethylated C residues in any particular stretch of residues in the genomic material of a biological sample. For example, if a cytosine (C) residue that is normally unmethylated in a DNA sequence is methylated, it may be referred to as "hypermethylated"; whereas, if a cytosine (C) residue that is normally methylated in a DNA sequence is unmethylated, it may be referred to as "hypomethylated". Similarly, if a cytosine (C) residue in a DNA sequence (e.g., DNA from a sample nucleic acid from a test subject) is methylated compared to other sequences from different regions or from different individuals (e.g., compared to a standard nucleic acid of a normal nucleic acid or reference sequence), the sequence is considered to be hypermethylated compared to other sequences. Alternatively, if a cytosine (C) residue in a DNA sequence is unmethylated compared to other sequences from different regions or different individuals, the sequence is considered to be hypomethylated compared to other sequences. The sequence is said to be "differentially methylated". Measuring the level of differential methylation can be done by various methods known to those skilled in the art. One method is, as a non-limiting example, measuring the methylation level of each interrogated CpG site as determined by bisulfite sequencing. The term "methylated nucleotide" or "methylated nucleotide base" as used herein refers to the presence of a methyl moiety on a nucleotide base, which is not normally present in recognized normal nucleotide bases. For example, cytosine in its normal form does not contain a methyl moiety on the pyrimidine ring, but 5-methylcytosine contains a methyl moiety at the 5-position of the pyrimidine ring. Thus, cytosine in its normal form cannot be a methylated nucleotide, and 5-methylcytosine may be considered a methylated nucleotide. In another example, thymine may have a methyl moiety at the 5-position of the pyrimidine ring, but for the purposes of this specification, thymine may not be considered a methylated nucleotide when present in DNA. The normal nucleotide bases of DNA are thymine, adenine, cytosine, and guanine. The normal bases of RNA are uracil, adenine, cytosine, and guanine. Correspondingly, a "methylation site" is a position in a target gene nucleic acid region where methylation can occur. For example, a position containing CpG is a methylation site regardless of cytosine methylation. In particular, the term "methylated nucleotide" refers to a nucleotide with a methyl group attached to a position of the nucleotide accessible for methylation. Such methylated nucleotides are usually found in nature and to date can be considered as most common with methylated cytosine occurring mostly in the context of the dinucleotide CpG, but also in the context of CpNpGand CpnPn sequences. In principle, other naturally occurring nucleotides can also be methylated, but they are not considered in relation to any aspect of the present invention. The terms "methylation profile", "methylation pattern", "methylation state" or "methylation status" in the context of the present invention are used herein to describe the state, condition or status of methylation of a genomic sequence, which refers to the characteristics of a DNA segment at a particular genomic locus related to methylation, including but not limited to whether any of the cytosine (C) residues in this DNA sequence are methylated, the position of the methylated C residues, the ratio of methylated C in any particular stretch of residues, and allelic differences in methylation due to, for example, different origins of the alleles.

[0009] The term "hypermethylation" refers to an average methylation state that corresponds to an increased presence of 5-mCyt at one or more CpG dinucleotides in a DNA sequence of a test DNA sample compared to the amount of 5-mCyt found at the corresponding CpG dinucleotide in a normal control DNA sample. In particular, the control refers to cells that do not exhibit OS. The term "hypomethylation" refers to an average methylation state that corresponds to a decrease in the presence of 5-mCyt at one or more CpG dinucleotides in a DNA sequence of a test DNA sample compared to the amount of 5-mCyt found at the corresponding CpG dinucleotide in a normal control DNA sample. In particular, the control refers to cells that do not exhibit OS.

[0010] As used herein, the term "genomic material" refers to a nucleic acid molecule or fragment of the genome of a subject or group of subjects. In particular, the nucleic acid molecule or fragment is DNA or RNA or a hybrid thereof, and most preferably is a molecule of the DNA genome of the subject or group of subjects. As used herein, the term "DNA sample" refers to DNA extracted from cells according to any embodiment of the present invention using methods known in the art. In particular, the test cell has OS if differential methylation is detected in the test cell, i.e., the cell exhibits hypermethylation or hypomethylation at at least one CpG site compared to a control (i.e., a cell without signs of OS). More specifically, the test cell has OS if a CpG site exhibits hypomethylation in the test cell compared to the corresponding CpG site in the control cell. In another example, the test cell has OS if a CpG site exhibits hypermethylation in the test cell compared to the corresponding CpG site in the control cell. In particular, in the method according to any aspect of the present invention, in (a), at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48 , 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 100 CpG sites are determined. A person skilled in the art can determine the number of CpG sites that need to be used in (a) according to any embodiment of the invention. Even more specifically, the methylation status of at least two CpG sites is determined in (a) of the method according to any embodiment of the invention. More specifically, in (a), the CpG site is selected from the group consisting of those shown in Table 2 below: Table 2 List of 96 differentially methylated CpG sites in OS

[0011] [Table 1] The selection is made from the list provided in A method according to any of the aspects of the present invention comprises the steps of: (i) prior to (a), subjecting the DNA sample to bisulfite modification; Includes.

[0012] "Bisulfite treatment" of genomic DNA, which is used interchangeably with the term "bisulfite modification," refers to the treatment of genomic DNA with a deaminating agent such as bisulfite, which can be used to treat all DNA, whether methylated or not. In particular, the term "bisulfite" as used herein includes any suitable bisulfite, such as sodium hydrogen sulfite, or other chemical agents that can chemically convert cytosine (C) to uracil (U) without chemically modifying methylated cytosine, and thus can be used to differentially modify DNA sequences based on the methylation status of the DNA (e.g., U.S. Patent Application Publication No. 2010 / 0112595). As used herein, a reagent that "differentially modifies" methylated or unmethylated DNA includes any reagent that modifies methylated and / or unmethylated DNA in a process that results in products that can be distinguished from methylated and unmethylated DNA, thereby allowing identification of DNA methylation status. Such processes may include, but are not limited to, chemical reactions (e.g., C to U conversion with bisulfite) and enzymatic treatments (e.g., cleavage with methylation-dependent endonucleases). Thus, enzymes that preferentially cleave or digest methylated DNA can cleave or digest DNA molecules with much higher efficiency when the DNA is methylated, while the efficiency of enzymes that preferentially cleave or digest unmethylated DNA is significantly higher when the DNA is unmethylated. Therefore, prior to (a) above according to any aspect of the invention, the genomic DNA contained in / obtained from or extracted from the cell is first bisulfite treated. Alternative methods available in the art may be used instead of bisulfite treatment. Those skilled in the art will understand which other methods to use. In one example, TET-assisted pyridine borane sequencing (TAPS) can be used to detect 5mC and 5hMC (Yibin Liu, et al., Nature Biotechnology, 37: 424-429 (2019)). The cells used in any aspect of the invention are obtained from a biological sample selected from the group consisting of blood, brain, sperm and any other tissue or sample that provides genomic DNA for use in the method according to any aspect of the invention. In particular, the biological sample may include any biological material obtained from a subject that contains DNA, and may be a liquid, solid, or both, such as tissue or bone or a body fluid such as blood, lymph, etc. In particular, the biological sample useful in the present invention may include biological cells or fragments thereof. The term "test" in conjunction with the term "cell" herein refers to a cell that is subjected to a method according to any embodiment of the present invention and is the basis for an analytical application of the present invention. Thus, a "test cell" is a cell or group of cells that is tested according to any embodiment of the present invention, or a profile obtained or generated in this context. Conversely, the term "reference" or "control" refers to a mostly predefined entity that is used for comparison with a test entity. In particular, a "test cell" refers to a cell that is tested for an OS whose methylation status is to be determined, and a "control" refers to a cell in which the methylation status is already known and no OS is used as a reference.

[0013] OS according to any aspect of the present invention may be caused by or may be the result of UV light exposure, aging, H2O2 exposure, and combinations thereof (i.e., UV light and H2O2 exposure, UV light exposure and aging, H2O2 exposure and aging, or UV light and H2O2 exposure and aging).

[0014] In a further aspect of the present invention, there is provided a method for detecting the occurrence of oxidative stress (OS) in a cell, comprising detecting an epigenetic change at at least one CpG site in the cell, wherein detection of the epigenetic change is indicative of the occurrence of OS, and wherein the epigenetic change is methylation. In particular, methylation is hypomethylation. DNA hypomethylation profiling can be extremely useful for stratifying cell culture systems ranging from 1D to 3D, stem cells into differentiated skin tissue models under stress. As used herein, the term "epigenetic changes" refers to chemical (e.g., methylation) or protein (e.g., histone) changes that occur to gene bodies or their promoters. Through epigenetic changes, environmental factors such as diet, stress, and prenatal nutrition can affect which genes are passed from one generation to the next. [Brief description of the drawings]

[0015] [Figure 1] FIG 1A is a scatter plot showing that a large number of probes are in a differential methylation state in cells induced with artificial OS (high UV, 24 hours) according to Example 1. As can be seen, there are a large number of hypomethylated probes as well as hypermethylated probes. FIG 1B is a box plot confirming the results of FIG 1A showing that a large number of probes are in a differential methylation state in cells induced with artificial OS (high UV, 24 hours) according to Example 1. [Diagram 2] FIG 2A is a scatter plot showing that multiple probes are differentially methylated in cells induced with artificial OS (low UV for 72 hours) according to Example 1. As can be seen, there are multiple hypomethylated probes as well as hypermethylated probes. FIG 2B is a box plot confirming the results of FIG 2A showing multiple probes are differentially methylated in cells induced with artificial OS (low UV for 72 hours) according to Example 1. [Diagram 3] FIG. 3A is a scatter plot showing that multiple probes are differentially methylated in cells induced with artificial OS (low H2O2, 24 hours) according to the embodiment. As can be seen, there are multiple probes that are hypomethylated in cells containing OS compared to control cells without OS. FIG. 3B is a box plot confirming the results of FIG. 3A showing multiple probes are differentially methylated in cells induced with artificial OS (low H2O2, 24 hours) according to the embodiment. [Figure 4]FIG 4A is a scatter plot showing that multiple probes are differentially methylated in cells induced with artificial OS (high H2O2, 24 hours) according to Example 2. As can be seen, there are multiple probes that are hypomethylated in cells containing OS compared to control cells without OS. FIG 4B is a box plot confirming the results of FIG 4A showing multiple probes are differentially methylated in cells induced with artificial OS (high H2O2, 24 hours) according to Example 2. [Diagram 5] FIG. 5A is a scatter plot showing that multiple probes are differentially methylated when artificial OS according to Example 3 is induced in cells with Medox®. As can be seen, there are multiple probes that are hypomethylated in OS-containing cells compared to non-OS containing control cells. FIG. 5B is a box plot that confirms the results of FIG. 5A showing that multiple probes are differentially methylated when artificial OS according to Example 3 is induced in cells with Medox®. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0016] The above describes preferred embodiments, and as will be understood by those skilled in the art, the present invention may be subject to changes or modifications in design, structure, or operation without departing from the scope of the claims. Such variations are intended to be covered, for example, by the claims. EXAMPLES

[0017] UV-induced oxidative stress in human tissues Artificial oxidative stress was induced in cell culture systems and skin tissue models, and the promoter methylation status was analyzed. The T-Skin models were obtained from Episkin SA (France) and consisted of reconstructed human skin. Each skin model consisted of a dermal equivalent covered by a stratified, well-differentiated epidermis derived from normal human keratinocytes. After receiving the skin models, they were harvested by incubating in T-Skin culture medium overnight at 37° C. in a 5% CO2 incubator. To induce oxidative stress in human tissue systems, skin models (5x replicates) were exposed to UV light (UVA 24 J / cm 2 +UVB 50mJ / cm 2 ) for 24 hours each day. In another group, the skin model (5x replicates) was exposed to UV light (UVA 12 J / cm 2 +UVB 25mJ / cm 2 ) daily for 72 hours. Exposure to UV irradiation generates ROS, which ultimately leads to oxidative stress in cells. A control set of skin models (5x replicates) was kept without exposure to UV irradiation for 72 hours. After treatment, the skin models were harvested and genomic DNA was purified from the tissue samples using DNeasy® Blood & Tissue Kit (Qiagen). Genomic DNA was quantified using PicroGreen® or NanoDrop™ 2000. Genomic DNA (500 ng) from tissue samples was subjected to bisulfite conversion using the EZ DNA Methylation-Gold™ kit (Zymo Research). The Infinium MethylationEPIC v2.0 kit (Illumina) can be used to quantitatively analyze over 850,000 methylation sites across the genome at single-base resolution. Quality Control and Data Processing Methylation EPIC array data processing was performed in R version 4.1.2 (2021-11-01) using minfi version 1.40.0. Raw intensity data (IDAT) were imported into R (4.1.2) and processed using minfi (1.4.0); Bioconductor package, 18. Sample quality check was performed and probes with detection P value < 0.01 in one or more samples or average detection P value < 0.05 across all samples were kept. Samples were then normalized using the function normalization (done by the preprocessFunnorm function in minfi) for type bias correction and background correction. Before differential methylation analysis, probes with non-specific binding, cross-reactive probes, probes affected by common SNPs, and probes annotated to chromosomes X and Y were also filtered out. The beta and M values ​​of the normalized and filtered samples were calculated using the getBeta and getM functions, respectively, and the samples were subjected to further downstream analysis. Differential methylation analysis Differential methylation analysis was performed using the packages limma version 3.50.1 and DMRcate version 2.8.5. Contrast matrices were set by comparing each corresponding treatment group with the control group, and the empirical Bayes algorithm was used to fit M values ​​based on the design and contrast model. Probes with adjusted P values ​​lower than 0.05 were considered as differentially methylated positions (DMPs). Annotation was performed using IlluminaHumanMethylationEPICanno .ilm10b2.hg19 and the annotatr package (1.20.0). As can be seen in Figures 1A and B and 2A and 2B, there are many probes that are differentially methylated in the OS-containing cells compared to the non-OS control cells. The results also show that there were an equal number of hypomethylated probes as hypermethylated probes. EXAMPLES

[0018] H 2 O 2 Oxidative stress on human tissues caused by Another method of inducing oxidative stress in human tissue systems is by hydrogen peroxide treatment, which leads to the generation of ROS in cells. Skin models (5x replicates) were treated with two different concentrations of hydrogen peroxide [100μM (low) and 200μM (high)] for 2 hours and maintained for 24 hours. A control set of skin models (5x replicates) was maintained for 24 hours without hydrogen peroxide treatment. After treatment, the skin models were harvested and genomic DNA was purified from the tissue samples using DNeasy® Blood & Tissue Kit (Qiagen). Genomic DNA was quantified using PicroGreen® or NanoDrop™ 2000. The samples in this example were subjected to similar quality control and data processing methods as disclosed in Example 1. In addition, the data obtained in Example 2 was subjected to similar analysis as the differential methylation analysis disclosed in Example 1. As can be seen in Figures 3A and 3B and 4A and 4B, there are many probes that are differentially methylated in the OS-containing cells compared to the non-OS control cells. There are many probes that are hypomethylated in the OS-containing cells compared to the non-OS control cells. EXAMPLES

[0019] Oxidative stress on cell culture systems using Medox® To investigate oxidative stress in cell culture systems, mesenchymal stem cells (MSCs) were treated with Medox® (Evonik batch: H-080719), which contains many natural anthocyanins associated with antioxidant and anti-inflammatory properties. Bone marrow-derived MSCs were cultured for one week in Mesencult ACF Plus Medium with two doses of Medox® (4x replication): 25 μg / ml (low) and 100 μg / ml (high). The medium with Medox® was changed every two days for one week. As a control (4x replication), MSCs were cultured for one week in Mesencult ACF Plus Medium without any Medox® treatment. Medox® treatment is expected to produce an opposite reaction to OS. After this, the cell pellet was collected and genomic DNA was purified from the cell pellet using the DNeasy® Blood & Tissue Kit (Qiagen). Genomic DNA was quantified using PicroGreen® or NanoDrop™ 2000. Genomic DNA (500 ng) from cell pellets was subjected to bisulfite conversion using the EZ DNA Methylation-Gold™ kit (Zymo Research). The Infinium MethylationEPIC v2.0 kit (Illumina) allows quantitative analysis of over 850,000 methylation sites across the genome at single-base resolution. DNA methylation profiling has proven to be a powerful analytical tool for accurately identifying tissue origin and the effects of environmental factors. It has the advantage as a biomarker classifier since it is a stable marker, facilitating quantitative analysis at single nucleotide resolution. The samples in this example were subjected to similar quality control and data processing methods as disclosed in Example 1. In addition, the data generated in Example 3 was subjected to similar analysis as the differential methylation analysis disclosed in Example 1. In Medox® versus low treatment of MSCs, 35,532 differentially methylated probes (p<0.05) were identified, of which 15,368 probes were hypermethylated and 20,164 probes were hypomethylated. As can be seen in Figures 5A and B, there are many probes that are differentially methylated in OS-containing cells compared to non-OS control cells. There are many probes that are hypomethylated in OS-containing cells compared to non-OS control cells. EXAMPLES

[0020] Oxidative stress in human tissues induced by UV radiation Artificial oxidative stress was induced in cell culture systems and skin tissue models, and the promoter methylation status was analyzed. The T-Skin models were obtained from Episkin SA (France) and consisted of reconstructed human skin. Each skin model consisted of a dermal equivalent covered by a stratified, well-differentiated epidermis derived from normal human keratinocytes. After receiving the skin models, they were harvested by incubating in T-Skin culture medium overnight at 37° C. in a 5% CO2 incubator. To induce oxidative stress in human tissue systems, skin models (5x replicates) were exposed to UV light (UVA 24 J / cm 2 +UVB 50mJ / cm 2 ) (high UV) and cultured for 24 hours. In another group, the skin model (5x replicates) was exposed to UV radiation (UVA 12 J / cm 2+UVB 25mJ / cm 2 ) (low UV) and exposed to for 24 hours each day. Exposure to UV irradiation generates ROS, which ultimately leads to oxidative stress in cells. A control set of skin models (5x replicates) was maintained for 24 hours without exposure to UV irradiation. After treatment, the skin models were harvested and genomic DNA was purified from the tissue samples using DNeasy® Blood & Tissue Kit (Qiagen). Genomic DNA was quantified using PicroGreen® or NanoDrop™ 2000. Genomic DNA (500 ng) from tissue samples was subjected to bisulfite conversion using the EZ DNA Methylation-Gold™ kit (Zymo Research). The Infinium MethylationEPIC v2.0 kit (Illumina) can be used to quantitatively analyze over 850,000 methylation sites across the genome at single-base resolution.

[0021] H 2 O 2 Oxidative stress on human tissues caused by Another method of inducing oxidative stress in human tissue systems is by hydrogen peroxide treatment, which leads to the generation of ROS in cells. Skin models (5x replicates) were treated with two different concentrations of hydrogen peroxide [100μM (low) and 200μM (high)] for 2 hours and maintained for 24 hours. A control set of skin models (5x replicates) was maintained for 24 hours without hydrogen peroxide treatment. After treatment, the skin models were harvested and genomic DNA was purified from the tissue samples using DNeasy® Blood & Tissue Kit (Qiagen). Genomic DNA was quantified using PicroGreen® or NanoDrop™ 2000. Genomic DNA (500 ng) from tissue samples was subjected to bisulfite conversion using the EZ DNA Methylation-Gold™ kit (Zymo Research). The Infinium MethylationEPIC v2.0 kit (Illumina) can be used to quantitatively analyze over 850,000 methylation sites across the genome at single-base resolution.

[0022] Oxidative stress on human tissues in the presence of particulate matter 2.5 Another method to induce oxidative stress in human tissue systems is by particulate matter 2.5 (PM2.5) treatment, which generates ROS in cells due to its chemical components and metals. Skin models (5x replicates) were treated with two different concentrations [15 μg / cm 2 (low) and 30μg / cm 2 (high)] PM2.5 and maintained for 24 hours. A control set of skin models (5x replicates) was maintained for 24 hours without PM2.5 treatment. After treatment, the skin models were harvested and genomic DNA was purified from the tissue samples using DNeasy® Blood & Tissue Kit (Qiagen). Genomic DNA was quantified using PicroGreen® or NanoDrop™ 2000. Genomic DNA (500 ng) from tissue samples was subjected to bisulfite conversion using the EZ DNA Methylation-Gold™ kit (Zymo Research). The Infinium MethylationEPIC v2.0 kit (Illumina) can be used to quantitatively analyze over 850,000 methylation sites across the genome at single-base resolution.

[0023] Oxidative stress in human tissues using glyoxal Another method to induce oxidative stress in human tissue systems is by glyoxal treatment, which produces advanced glycation end products and increases intracellular ROS levels, causing oxidative stress. Skin models (5x replicates) were treated with two different concentrations of glyoxal [0.5mM (low) and 1mM (high)] and maintained for 24 hours. A control set of skin models (5x replicates) was not treated with glyoxal and maintained for 24 hours. After treatment, the skin models were harvested and genomic DNA was purified from the tissue samples using the DNeasy® Blood & Tissue Kit (Qiagen). Genomic DNA was quantified using PicroGreen® or NanoDrop™ 2000. Genomic DNA (500 ng) from tissue samples was subjected to bisulfite conversion using the EZ DNA Methylation-Gold™ kit (Zymo Research). The Infinium MethylationEPIC v2.0 kit (Illumina) can be used to quantitatively analyze over 850,000 methylation sites across the genome at single-base resolution.

[0024] Oxidative stress in human tissues during aging Another way of inducing oxidative stress in human tissue systems is through aging, which leads to the generation of reactive oxygen and nitrogen species (RONS) within cells. The skin models were maintained in deep-well plates with culture medium for 14 days (repeated six times), and the medium was changed after 7 days to induce aging of the skin tissue. After 14 days, the skin models were harvested, and genomic DNA was purified from the tissue samples using DNeasy® Blood & Tissue Kit (Qiagen). Genomic DNA was quantified using PicroGreen® or NanoDrop™ 2000. Genomic DNA (500 ng) from tissue samples was subjected to bisulfite conversion using the EZ DNA Methylation-Gold™ kit (Zymo Research). The Infinium MethylationEPIC v2.0 kit (Illumina) can be used to quantitatively analyze over 850,000 methylation sites across the genome at single-base resolution.

[0025] Quality Control and Data Processing A total of 103 samples from 16 different treatments and their respective controls were analyzed. Treatments can be grouped into two batches. Batch 1 consisted of all treatments at high and low concentrations for 24 hours. All treatments in batch 1 shared the same control group. Table 1 shows the sample information for batch 1. Methylation EPIC array data processing was performed in R version 4.2.2 (2021-11-10 r83330) using minfi version 1.42.0. Raw intensity data (IDAT) were imported into R (4.2.2) and processed using minfi (1.42.0). A Bioconductor package sample quality check was performed to retain probes with a detection P value < 0.01 in one or more samples or an average detection P value < 0.05 across all samples. Samples were then normalized using the function normalization (performed by the preprocessFunnorm function in minfi) for type bias correction and background correction. Before differential methylation analysis, probes with non-specific binding, cross-reactive probes, probes affected by common SNPs, and probes annotated to chromosomes X and Y were also filtered out. The beta and M values ​​of the normalized and filtered samples were calculated using the getBeta and getM functions, respectively, and the samples were subjected to further downstream analysis. Table 1: Sample information for batch 1

[0026] [Table 2] Differential methylation analysis Pairwise differential methylation analysis (total 16 pairs) was performed using the limma package version 3.52.4. Samples from batch 1 were analyzed together. A contrast matrix was set up comparing each corresponding treatment group with the control group, and an empirical Bayes algorithm was used to fit M values ​​based on the design and contrast model. Probes with adjusted P values ​​below 0.05 were considered as differentially methylated positions (DMPs). DMPs within batch 1 comparison, batch 1 high comparison, and batch 1 low comparison were then compared to identify common DMPs that were present in all comparisons within each group and had the same methylation status throughout. In the Batch 1 comparison, there were a total of 96 common DMPs, in the Batch 1 High comparison there were a total of 616 common DMPs, and in the Batch 1 Low comparison there were a total of 238 common DMPs. Tables 2, 3, and 4 show the list of common DMPs within each group for the Batch 1 Comparison, Batch 1 High Comparison, and Batch 1 Low Comparison, respectively. Table 2: List of common DMPs within groups for batch 1 comparison (i.e., all treatments)

[0027] [Table 3] Table 3: List of common DMPs within groups for batch 1 high comparison

[0028] [Table 4]

[0029] [Table 5] TIFF2025514492000006.tif230170 Table 4: List of common DMPs within groups for batch 1 low comparisons

[0030] [Table 6]

Claims

1. A method for identifying oxidative stress (OS) in test cells, (a) Determine the methylation status of at least one CpG site in the DNA sample obtained from test cells, and, (b) Comparing the methylation state of the CpG site with the methylation state of a control that does not contain OS, A method comprising the above, wherein the difference in the methylation state of the CpG sites of the test cells described in (a) compared with the control CpG sites indicates that the test cells have OS.

2. The method according to claim 1, wherein the difference in methylation status is hypomethylation or hypermethylation of the CpG site of the test cell, and the hypomethylation or hypermethylation of the CpG site indicates that the test cell has the OS.

3. The aforementioned CpG sites are shown in the following table: Table 1 The method according to claim 1, wherein the CpG site is selected from a list of CpG sites.

4. The method according to claim 1, wherein in (a) above, the methylation state of at least two of the CpG sites is determined.

5. The method according to claim 1, wherein in (a) above, the methylation state of at least three of the CpG sites is determined.

6. The method according to claim 1, wherein in (a) above, the methylation state of at least five of the CpG sites is determined.

7. The method according to claim 3, wherein the methylation state of all the CpG sites listed in (a) above is determined.

8. (i) Before (a) above, perform bisulfite modification on the DNA sample. The method according to claim 1, including the method described in claim 1.

9. The method according to claim 1, wherein the test cells are obtained from a biological sample selected from the group consisting of blood, brain, sperm, and any other tissue or sample providing genomic DNA.

10. The method according to claim 1, wherein the test cells are eukaryotes.

11. The method according to claim 1, wherein the test cells are derived from a mammal.

12. The method according to claim 11, wherein the mammal is a mouse, rat, guinea pig, dog, miniature pig, human, cow, sheep, pig, goat, horse, donkey, and mule.

13. The method according to claim 1, wherein the test cells are skin cells, stem cells, or cells derived therefrom.

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