An efficient mitochondrial gene methylation modification tool and its application

Abstract

The present invention discloses an efficient mitochondrial gene methylation modification tool and its application, which relates to the technical fields of molecular biology and genetic engineering. The present invention has developed a brand-new mitochondrial gene methylation modification tool MEE, and this methylation modification tool MEE shows extremely high editing efficiency in the methylation modification of specific sites, up to more than 90%; and whole-genome sequencing shows that the off-target rate is less than 0.1%. MEE is a new methylation modification tool for aging and anti-aging research.

Description

Technical Field

[0001] The present invention relates to the technical fields of molecular biology and genetic engineering, and particularly relates to a mitochondrial gene methylation modification tool (MEE) constructed based on a transcription activator-like effector protein (TALE) module, and its applications in mitochondrial epigenetics research, analysis of the mechanisms of aging-related diseases, development of anti-aging drug targets, and gene therapy. Background Art

[0002] Methylation modification of mitochondrial genome (mtDNA) is one of the important mechanisms of epigenetic regulation, and is closely related to energy metabolism, aging, and various diseases. Mitochondria, as the energy metabolism center of cells, the regulation mechanism of its DNA has long been considered independent of nuclear epigenetic modification. Recent studies have found that dynamic methylation modifications exist in mitochondrial DNA and RNA, such as 5-methylcytosine (5mC) and N6-methyladenosine (m6A), and their mechanisms may involve the mitochondrial localization of nuclear-derived DNA methyltransferases (such as DNMT3A) or the action of mitochondrial-specific enzymes. These modifications affect oxidative phosphorylation efficiency and reactive oxygen species (ROS) balance by regulating mtDNA replication, transcription, and RNA stability, and thus participate in the occurrence of aging, tumors, and metabolic diseases. For example, high methylation of mtDNA in tumor cells may promote the Warburg effect by inhibiting the expression of electron transport chain genes. However, the existing technologies have the following limitations in site-specific methylation modification of mitochondrial genes: (1) Low tool efficiency and high off-target rate. Traditional CRISPR systems are difficult to achieve precise methylation modification because they cannot efficiently target mitochondria and rely on the DNA double-strand break mechanism; existing methyltransferase fusion proteins have significant deficiencies in mitochondrial localization and targeting efficiency. (2) Immature delivery system. There is a lack of carriers that can efficiently penetrate the mitochondrial double membrane and deliver macromolecular tools, resulting in limited in vivo applications. (3) Insufficient research on methylation sites related to aging. Currently, there is a lack of systematic analysis of the association between mtDNA dynamic methylation and aging, and the key functional sites have not been clarified, which restricts the development of anti-aging targeted therapies. Summary of the Invention

[0003] The development of a TALE-based mitochondrial targeting methylation tool in the present invention has important innovative value. TALE proteins can precisely recognize specific sequences of mtDNA through modular design. If fused with a methyltransferase (such as the catalytic domain of DNMT3A) and a mitochondrial localization signal (MTS) is added, it is expected to achieve site-specific methylation editing. Compared with traditional CRISPR-derived tools, the TALE system does not require a guide RNA and is more suitable for environments where mitochondrial RNA delivery is difficult. Such tools can analyze the functions of specific mtDNA methylation sites, help construct disease models, and provide new strategies for mitochondrial epigenetic therapy. For example, by regulating mtDNA methylation in cardiomyocytes, it can improve abnormal energy metabolism in heart failure. The progress in this field will promote the transition of mitochondrial epigenetics from mechanism research to the era of precise intervention.

[0004] The present invention aims to construct a methylation modification tool MEE that targets specific sites of mitochondrial genes to achieve precise and efficient 5mC methylation modification of mitochondrial genes and regulate gene expression. Through high-throughput sequencing of the methylation of the mitochondrial genome of mice of different ages, methylation modification sites related to aging are mined, and MEE is applied to in vivo methylation modification of aging-related sites in mice, providing a new technical method for the research of aging and methylation-related sites and disease treatment.

[0005] In view of the above technical bottlenecks, the present invention provides an efficient and precise mitochondrial gene methylation modification tool MEE and clarifies its key applications in the research and intervention of aging mechanisms. Specifically, it includes the following innovations:

[0006] 1. Tool innovation. Based on the TALE module, the MEE tool is developed and designed as a novel mitochondrial targeting methylation tool MEE, whose core consists of the following modules:

[0007] (a) The TALE protein targeting unit, which is used to specifically recognize the target sequence in the mitochondrial genome, and realizes precise recognition of specific sites of mtDNA through customized TALE arrays;

[0008] (b) The methyltransferase catalytic unit, which contains the functional domains of DNA methyltransferases DNMT3A and DNMT3L to catalyze the methylation of CpG sites;

[0009] (c) The mitochondrial localization signal peptide, which is used to guide the methylation modification tool to localize to the mitochondrial matrix.

[0010] Verified by experiments, the methylation modification efficiency of MEE for specific sites of mtDNA reaches more than 90%, the expression level of the targeted gene is down-regulated by more than 90%, and whole-genome sequencing shows that the off-target rate is lower than 0.1%, which is significantly better than the existing technology.

[0011] Preferably, the TALE protein targeting unit consists of 12-18 repeat variable diresidue domains.

[0012] Preferably, in the methyltransferase catalytic unit, DNA methyltransferase DNMT3A and DNMT3L are fused through a flexible linker peptide;

[0013] The amino acid sequence of the DNA methyltransferase DNMT3A is the amino acid sequence of positions 1-302 shown in SEQ ID NO.1;

[0014] The amino acid sequence of DNMT3L is the amino acid sequence of positions 330-544 shown in SEQ ID NO.1;

[0015] The amino acid sequence of the flexible linker peptide is the amino acid sequence of positions 303-329 shown in SEQ ID NO.1.

[0016] Preferably, the amino acid sequence of the mitochondrial localization signal peptide is MLGFVGRVAAAPASGALRRLTPSASLPPAQLLLRAAPTAVHPVRDYAAQTSESGGGGSPG.

[0017] Preferably, the mitochondrial genome locus targeted by the TALE protein targeting unit is selected from at least one of the following:

[0018] The promoter region of the mitochondrial genome;

[0019] The coding region of the mitochondrial genome;

[0020] The hypervariable region of the mitochondrial genome.

[0021] Furthermore, the mitochondrial genome locus targeted by the TALE protein targeting unit is specifically at least one of the following gene regions:

[0022] The promoter region of the mt-COX1 gene; the coding region of the mt-ND4 gene; the coding region of the mt-COX2 gene; the coding region of the mt-ND5 gene; the coding region of the mt-RNR1 gene; the coding region of the mt-ATP8 gene; the coding region of the mt-CYTB gene.

[0023] The present invention also provides a construction method of the mitochondrial gene methylation modification tool, comprising the following steps:

[0024] (1) Design a TALE array targeting the mitochondrial gene;

[0025] (2) Link the coding sequences of the TALE array, the methyltransferase catalytic unit and the mitochondrial localization signal peptide to an expression vector;

[0026] (3) Transfect the cells and screen to obtain a cell line expressing MEE.

[0027] In some embodiments of the present invention, the repeat variable diresidue sequences of the TALE array are selected from at least one of the following:

[0028] NG-NG-NI-NI-HD-HD-HD-NI-NI-NN-NG-HD-NI-NI-NG-NI;

[0029] NI-NN-NN-NN-NG-NN-NI-NN-HD-NI-NG-HD-NI-NI-NI-HD;

[0030] NG-HD-NG-HD-NI-NN-NN-HD-NG-NG-HD-NI-NI-HD-NI-NG;

[0031] NI-HD-NI-NG-HD-NN-NI-NI-NG-NI-HD-NN-HD-HD-NN-HD;

[0032] NI-HD-NI-NN-HD-NI-NG-NI-HD-HD-HD-HD-HD-NN-NI-NG;

[0033] NG-NI-HD-HD-NI-NI-NI-HD-NN-HD-HD-HD-HD-NG-HD-NG;

[0034] NG-NI-NN-NI-HD-NI-HD-NI-HD-NN-NI-NN-HD-NI-NG-NI;

[0035] NG-NG-NG-NN-NI-NN-NI-NI-NN-HD-HD-NG-NG-HD-NN-HD;

[0036] NG-NI-NN-NG-HD-HD-NG-HD-NI-NG-HD-NN-HD-HD-HD-NG;

[0037] NG-NI-HD-NN-HD-NI-NG-HD-HD-NG-NG-NG-NI-HD-NI-NG;

[0038] NI-HD-HD-NG-NI-HD-NN-NI-NN-NG-NI-HD-NI-HD-HD-NN;

[0039] NG-NG-NI-NI-NI-NI-NI-HD-NI-NN-NI-NG-NN-HD-NI-NI;

[0040] NI-NN-NI-NI-HD-HD-NI-NI-NI-NI-NG-NN-NI-NI-HD-NN;

[0041] NG-NG-HD-NI-NI-HD-HD-NI-NI-NG-NI-NN-HD-HD-HD-NG;

[0042] NI-NI-HD-NG-NG-NG-HD-HD-NG-HD-NI-HD-NG-NI-NG-HD;

[0043] NG-NI-NI-NI-NI-HD-NG-NI-NN-NN-HD-NN-NN-HD-NG-NI;

[0044] NI-NN-NI-NG-NG-NN-NG-NN-NI-NI-NG-HD-NG-NN-NI-HD;

[0045] NG-HD-HD-NI-NI-HD-NG-NN-NG-NG-HD-NI-NG-HD-NN-NN;

[0046] NG-HD-HD-HD-HD-NG-NI-NG-HD-NG-NI-NN-NN-HD-HD-NG;

[0047] NI-NN-NI-HD-NN-NG-NI-NI-NI-NG-NG-NI-NG-NN-NN-HD。

[0048] The above finally corresponding DNA sequences are as follows: TTAACCCAAGTCAATA; AGGGTGAGCATCAAACT; TCTCAGGCTTCAACAT; ACATCGAATACGCCGCA; ACAGCATACCCCCGAT; TACCAAACGCCCCTCTT; TAGACACACGAGCATAT; TTTGAGAAGCCTTCGCT; TAGTCCTCATCGCCCT; TACGCATCCTTTACAT; ACCTACGAGTACACCGA; TTAAAAACAGATGCAAT; AGAACCAAAATGAACGAA; TTCAACCAATAGCCCT; AACTTTCCTCACTATCT; TAAAACTAGGCGGCTAT; AGATTGTGAATCTGACAA; TCCAACTGTTCATCGGCT; TCCCCTATCTAGGCCT; AGACGTAAATTATGGCT.

[0049] The present invention also provides a method for screening aging-related mitochondrial differentially methylated sites, comprising the following steps:

[0050] S1: Extract mitochondrial DNA from mammalian tissues of different ages;

[0051] S2: Screen for differentially methylated sites that change with age through whole-genome methylation sequencing;

[0052] S3: Identify functional sites where the methylation rate is significantly positively or negatively correlated with aging.

[0053] Specifically, through whole-genome methylation sequencing (mtDNA-MeDIP-seq) of the mtDNA of 1-month-old (juvenile), 3, 5-month-old (middle-aged), and 12, 21-month-old (old) mice, a total of 127 aging-related differentially methylated sites (DMRs) were identified. Among them, the methylation rate of 68 sites increased significantly with aging (such as the promoter region of the mt-COX1 gene), and the methylation rate of 59 sites decreased significantly (such as the coding region of the mt-ND4 gene).

[0054] Preferably, the differentially methylated sites include at least one of the following:

[0055] The methylation rate of the promoter region of the mt-COX1 gene increases with aging;

[0056] The methylation rate of the coding region of the mt-ND4 gene decreases with aging;

[0057] The methylation rate of the coding region of the mt-ND5 gene increases with aging.

[0058] The present invention also provides the application of the mitochondrial gene methylation modification tool in aging-related research or drug development, by targeting and modifying the methylation sites of mitochondrial genes to regulate gene expression.

[0059] In some embodiments of the present invention, the application includes at least one of the following:

[0060] Inhibit mitochondrial gene expression by upregulating the methylation level of the target site to simulate the aging phenotype;

[0061] Develop anti-aging drugs by downregulating the methylation level of the target site to restore gene expression.

[0062] Compared with the prior art, the beneficial effects of the present invention:

[0063] The present invention has developed a brand-new mitochondrial gene methylation modification tool MEE. This methylation modification tool MEE has shown extremely high editing efficiency in methylation modification at specific sites, up to over 90%; and whole-genome sequencing shows that the off-target rate is less than 0.1%. MEE is a new methylation modification tool for aging and anti-aging research. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 is the stable expression cell line of MTS-Dnmt3A_3L; wherein, a. Schematic diagram of the CMV-MTS-Dnmt3A_3L expression backbone; b. Flow chart for the construction of the stable expression cell line of MTS-Dnmt3A_3L.

[0065] Figure 2 is the Dnm3A knockout cell line; wherein, a. Designed sequence of the Dnmt3A knockout sgRNA; b. Sequencing map of the target sequence of the Dnmt3A knockout monoclonal cell; c. WB detection result map of the Dnmt3A knockout monoclonal cell.

[0066] Figure 3 is the schematic diagram of the overexpression vector during the methylation library sequencing of the cell genome.

[0067] Figure 4 is the analysis of the cell genome methylation sequencing results; wherein, a. Statistical analysis of the differential methylation of the mitochondrial genomes in each experimental group; b. The statistical indicators are the numerical distribution of >10 reads and methylation rate >1%.

[0068] Figure 5 is the working principle diagram of the mitochondrial methylation modification tool MEE.

[0069] Figure 6 is the information of 20 differential mitochondrial gene methylation sites.

[0070] Figure 7 is the map of 20 differential methylation sites and targeted mitochondrial genes.

[0071] Figure 8 is the analysis of the methylation modification of mitochondrial genome sites and target gene expression mediated by MEEs; a. Analysis of the site methylation modification and gene expression of the MT-ND1 gene mediated by MEE; b. Analysis of the site methylation modification and gene expression of the MT-COX1 gene mediated by MEE; c. Analysis of the site methylation modification and gene expression of the MT-COX2 gene mediated by MEE; d. Analysis of the site methylation modification and gene expression of the MT-ND5 gene mediated by MEE; wherein, P Those with p < 0.05 all indicate significant differences, and the scatter points are parallel samples.

[0072] Figure 9 It is the off-target analysis result graph of the mitochondrial methylation modification tool MEE; among them, the scatter points are different differentially methylated sites.

[0073] Figure 10 It is the reference graph for the selection of mice of different ages.

[0074] Figure 11 It is the biochemical detection of senescence markers in plasma; a-f are the biochemical detections of senescence markers IGF-1, NFL, sTREM-2, p-Tau, GFAP, and t-Tau respectively; among them, P Those with < 0.05 all indicate significant differences, P Those with > 0.05 all indicate no significant differences.

[0075] Figure 12 It is the methylation detection and sequencing analysis of the mitochondrial genomes of mouse brain tissue and thymus tissue.

[0076] Figure 13 It is the distribution map of mitochondrial genome methylation sites in mouse tissues; a. Distribution map of mitochondrial genome methylation sites in mouse brain tissue; b. Distribution map of mitochondrial genome methylation sites in mouse thymus tissue. Detailed implementation methods

[0077] Example 1 Exploration of the methylation level of Dnmt3A_3L-expressing cells

[0078] (1) Construction of Dnmt3A_3L overexpressing cells

[0079] The nucleotide expression sequence (sequence as shown in SEQ ID NO.2) of the fusion protein of human Dnmt3A gene (NCBI Gene ID: 1788) and Dnmt3L gene (NCBI Gene ID: 29947) (abbreviation: DNMT3A / 3L fusion protein, amino acid sequence as shown in SEQ ID NO.1) was cloned into the vector pCDH-CMV-MCS-EF1-GFP (Addgene, #197989), and the MTS mitochondrial localization signal peptide sequence (amino acid sequence as shown in SEQ ID NO.3, nucleotide sequence as shown in SEQ ID NO.4) was fused to the N-terminus of the Dnmt3A expression sequence to construct the CMV-MTS-Dnmt3A_3L eukaryotic expression vector ( Figure 1 in a), and the plasmid was extracted. HEK293T cells were transfected with Lipofectamine 3000 (Thermo Fisher), and 48 hours later, GFP-positive monoclonal cells were sorted by flow cytometry (FACS) and expanded to a stable cell line (Figure 1 in b) of

[0080] (2) Construction of Dnmt3A knockout cells

[0081] A total of three sgRNAs were designed for the first exon Exon1 (abbreviated as E1) and the second exon Exon2 (abbreviated as E2) of the Dnmt3A gene ( Figure 2 in a), and the nucleotide sequences of the two sgRNAs for Exon1 are (5'-3'):

[0082] sgRNA1: GACGCGGCGCCGCGGCACCA (PAM: GGG);

[0083] sgRNA2: GGTGCCGCGGCGCCGCGTCC (PAM: CGG);

[0084] The nucleotide sequence of the sgRNA targeting Exon2 is (5'-3'):

[0085] sgRNA3: GATCCCGGTGTTGAGCCCTC (PAM: TGG). The sgRNA sequence was constructed into the LentiCRISPRv2 knockout vector (Addgene #52961), and HeLa and HEK293T cells were transfected using Lipofectamine 3000 (Thermo Fisher). After 48 hours, GFP-positive cells were sorted by flow cytometry (FACS). The knockout efficiency was verified by PCR amplification of the target fragment sequencing and Western blot. The experimental results are as Figure 2 shown. For the 6th clone of HeLa cells and the 4th and 5th clones of HEK293T cells screened, complete knockout of the Dnmt3A gene was achieved.

[0086] (3) Cell genomic DNA extraction and methylation library construction and sequencing

[0087] The mitochondrial genomic DNA extraction kit (Qiagen #37624) was used to isolate the complete mtDNA genomes of cells in each group. There were three groups in total, namely the CMV-MTS-Dnmt3A_3L overexpression group (MTS-Dnmt3A), the Dnmt3A gene knockout group (Dnmt3A-ko), and the CMV-MTS-GFP expression control cell group (Dnmt3A-wt) (the schematic diagram of the overexpression vector is as Figure 3As shown). Bisulfite conversion was performed using the EZ DNA Methylation-Gold Kit (Zymo Research). After library construction, whole-genome bisulfite sequencing (WGBS) was performed using the Illumina NovaSeq 6000, including methylation analysis of the nuclear genome and methylation analysis of the mitochondrial genome.

[0088] (4) Analysis of the results of genome methylation sequencing

[0089] The methylation sequencing data was stored as reads sequences in FASTA / FASTQ format, and FastQC was used to perform quality control on the sequencing data before preprocessing. Data preprocessing included trimming of reads and adapters. Reads trimming: reducing methylation recognition errors by trimming bases with lower quality scores; Adapter trimming: removing known adapter sequences from the reads sequences to improve alignment efficiency. Experiments before methylation sequencing convert unmethylated cytosine (C) to thymine (T), and the methylation sequencing data was aligned with the reference genome to estimate the methylation level. After obtaining the methylation information of CpG sites, differential methylation (DM) analysis was performed, including identifying differentially methylated sites (DMCs) or differentially methylated regions (DMRs).

[0090] The analysis results are as Figure 4 shown. The average methylation rate of mtDNA in the overexpression group increased by 15% (p < 0.01, t-test), and a large number of differentially methylated sites were counted, while there was no significant change in the nuclear genome (p > 0.05), indicating that Dnmt3A specifically regulates mtDNA methylation.

[0091] Example 2 Development of the mitochondrial methylation modification tool MEE

[0092] (1) Construction of the MEE expression vector

[0093] To improve the methylation efficiency of the tool, a CMV-MTS-Dnmt3A_3L expression vector was constructed based on the DNMT3A / 3L fusion protein. The TALE array (such as targeting the mt-COX2 C7829 (H) site, designing the RVD (Repeat Variable Diresidues) sequence: NG-NI-NN-NG-HD-HD-NG-HD-NI-NG-HD-NN-HD-HD-HD-NG), the DNMT3A / 3L fusion protein, and MTS were cloned into the MTS-Dnmt3A-GFP eukaryotic expression vector (the synthesized MTS-Dnmt3A sequence was constructed into the pCDH-CMV-MCS-EF1-GFP vector, and the synthetic nucleotide sequence of MTS-Dnmt3A is shown in SEQ ID NO.8). Through Gibson assembly, the MEE targeting the mt-COX2 C7829 (H) site: MTS-TALE-Dnmt3A_3L-GFP expression vector was constructed. In this part, a total of 20 MEEs targeting different methylated sites of mitochondrial genes were constructed ( Figure 5 ), which were derived from the first 20 different methylated sites in the examples. The statistically calculated differential methylation rates are shown in Figure 6 .

[0094] The TALE sequences of the specific 20 sites are shown in Table 1 below:

[0095] Table 1 TALE sequences of 20 different methylated sites of mitochondrial genes

[0096]

[0097] (3) Cell transfection and sample collection

[0098] Gently aspirate the original culture medium in the cell culture dish or well plate, taking care to avoid mechanical damage to the cells. Gently wash the cells once with pre-cooled phosphate-buffered saline (PBS) to remove residual culture medium and possible impurities. Dropwise add the pre-prepared MEE plasmid and Lipofectamine 3000 transfection reagent complex into the wells, ensuring that the complex evenly covers the cell layer. After adding the complex, supplement with 1.5 mL of DMEM medium containing serum to make the final volume reach 2 mL. Gently shake the culture dish or well plate to ensure uniform distribution of the medium. Incubate the cells in a 37 °C incubator for 6 hours to ensure sufficient contact between the transfection reagent and the cells and to allow it to take effect. After incubation, gently aspirate the old medium and replace it with fresh complete medium to support further cell growth and improve transfection efficiency. 48 hours after transfection, when the expression of MEE protein reaches its peak, collect the cells. At this time, the transfection efficiency and protein expression level of the cells should be in the optimal state. Digest the cells with 0.25% trypsin, gently shake the culture dish or well plate to ensure even action of trypsin on the cell layer, and digest for 3 - 5 minutes. Transfer the digested cell suspension to a centrifuge tube and centrifuge at 1000 rpm for 5 minutes to pellet the cells. Carefully discard the supernatant and gently resuspend the cells in PBS, ensuring uniform distribution of the cells. Use flow cytometry (FACS, BD FACSAria III) to sort 10 6 GFP + positive cells to obtain a highly pure transfected cell population.

[0099] (4)Genomic extraction and bisulfite treatment of cell samples

[0100] Bisulfite sequencing PCR (BSP) is a classic method for detecting gene methylation. Its principle is as follows: Genomic DNA is modified and treated with sodium bisulfite, and all unmethylated cytosines (C) are converted to uracils (U), while methylated cytosines remain unchanged. Use a mitochondrial DNA extraction kit (Abcam #ab65321) to enrich mtDNA, treat genomic DNA with bisulfite, and all unmethylated cytosines are converted to uracils, while methylated cytosines remain unchanged; then design primers at both ends of the CpG island for PCR amplification (PCR primers are shown in Table 2), purify the target product and perform TA cloning, pick 20 positive clones from each clone for sequencing, and finally compare the measured sequences with the original sequences, count the methylation sites and their numbers, and analyze the degree of methylation.

[0101] Table 2 PCR primers for amplifying target fragments in BSP experiments at 20 sites

[0102]

[0103] (5) Detection of endogenous RNA expression (Q-PCR)

[0104] Collecting MEE-targeted site-modified GFP + Positive cells were extracted with Trizol method to measure the concentration of RNA. The reverse transcription kit was used to reverse transcribe the same amount of RNA from each group of samples to obtain cDNA samples. Based on the sequence information of endogenous RNA, Q-PCR detection primers were designed and synthesized. The cDNA samples were quantitatively detected by Q-PCR. β-actin was selected as the internal reference and WT cells were selected as the negative control. -ΔΔCt The Q-PCR test data were analyzed using the Student's T Test to analyze the differences between the data groups. The Q-PCR primers are shown in Table 3:

[0105] Table 3 Q-PCR primer sequences for target gene expression detection

[0106]

[0107] (6) BSP detection of methylation modification effect of MEE

[0108] Among the 20 differentially methylated sites detected, C15634 (L) targets the MT-RNR1 (Gene ID: 4549, NC_012920.1) gene, C3687 (H), C3951 (H), C3966 (H) and C4152 (H) target the MT-ND1 (Gene ID: 4535, NC_012920.1) gene, C6464 (H), C6824 (H) and C9228 (L) target the MT-COX1 (Gene ID: 4512, NC_012920.1) gene, C7829 (H), C8720 (L), C8642 (L) and C8452 (L) target the MT-COX2 (Gene ID: 4513, NC_012920.1) gene, and C8544 (H) targets the MT-ATP8 (Gene ID: 4535, NC_012920.1). ID: 4509, NC_012920.1) gene, C9867 (H) targets the MT-COX3 gene, C12191 (H), C3795 (L) and C13967 (H) target the MT-ND5 (Gene ID: 4540, NC_012920.1) gene, C14984 (H) targets the MT-CYTB (Gene ID: 4519, NC_012920.1) gene, and C9001 (H) and C11492 (H) target the MT-tRNA ( Figure 7 ).

[0109] Through BSP experimental detection and analysis, MEEs achieved efficient methylation editing at these 20 methylation sites, and the expression levels of target genes decreased significantly (p<0.05). Among them, the methylation efficiency of MEE targeting the C13967 (H) site reached over 90%, and the mRNA expression level of the target gene MT-ND5 decreased by 95% ( Figure 8 ).

[0110] (6)Off-target detection of MEE

[0111] To explore the specificity of the mitochondrial methylation modification tool MEE, we performed whole-genome methylation library sequencing analysis on cell samples of three sites targeted by MEE, namely C15634 (L), C3687(H), and C3951 (H), and set up GFP expression and WT controls. Similarly, the MEE expression vector guided by MTS was transfected into HEK293T cells in a 6 cm dish. The fresh medium was changed 6 h after transfection. At 48 h after transfection, GFP + positive cells were collected by flow cytometry sorting, the cell genome was extracted, and genome methylation detection sequencing was performed. The latest version of the human genome data Homo sapiens (assembly GRCh38.p14) was used as the reference genome, and bioinformatics methods were used for data analysis of the sequencing to count differentially methylated sites. The analysis results showed that compared with GFP-transfected cells, 786, 771, and 771 differentially methylated sites in the mitochondrial genome and 480, 479, and 507 differentially methylated sites in the nuclear genome were found in cells with specific site modifications of C15634 (L), C3687 (H), and C3951(H) mediated by MEE, respectively; compared with WT cells, 748, 730, and 731 differentially methylated sites in the mitochondrial genome and 229, 201, and 192 differentially methylated sites in the nuclear genome were found in cells with specific site modifications of C15634 (L), C3687 (H), and C3951 (H) mediated by MEE, respectively. 4 differentially methylated sites in the nuclear genome were found in GFP-transfected cells ( Figure 9 ). Generally speaking, MEE is a precise mitochondrial methylation modification tool with broad application prospects.

[0112] Example 3 Mining of aging-related mitochondrial methylation sites and MEE-targeted mitochondrial methylation modification of cells

[0113] (1)Collection of mouse samples at different ages

[0114] Based on the comparison of human age and mouse age ( Figure 10), mice at 1, 3, 5, 12, and 21 months of age were respectively selected as experimental subjects, with 3 male and 3 female C57BL / 6JN mice. The tissues / organs collected were bladder, bone marrow, brain (cerebellum, cortex, hippocampus, and striatum), fat (brown, gonadal, mesenteric, and subcutaneous), heart and aorta, kidney, large intestine, limb muscle and diaphragm, liver, lung, mammary gland, pancreas, skin, spleen, thymus, tongue, and trachea. At the same time, the blood of the mice was collected to detect the expression of senescence markers T-Tau, p-Tau, NFL, Strem-2, GFAP, and IGF-1 in plasma samples.

[0115] (2)Detection of biochemical indexes in plasma of mice at different ages

[0116] Plasma samples of mice at 1, 3, 5, 12, and 21 months of age were collected, and the expression of senescence markers T-Tau, p-Tau, NFL, Strem-2, GFAP, and IGF-1 was respectively detected. The detection results showed that the expressions of IGF-1, NFL, and sTREM-2 were significantly up-regulated in older mice (12, 21 months of age) compared with younger mice (1, 3, 5 months of age) ( Figure 11 ).

[0117] (3)Methylation library construction analysis of mitochondrial genomes in brain tissue samples of mice at different ages

[0118] In this study, mitochondria were respectively extracted from the brain tissue and thymus tissue of the main senescent tissues. After bisulfite treatment and library construction, methylation library sequencing of the mitochondrial genomes of the brain tissue and thymus tissue of mice at different ages was completed ( Figure 12 ).

[0119] The specific steps are as follows:

[0120] 1. Sample preparation and grouping

[0121] Mice at different ages were selected, and brain tissue and thymus tissue were collected. Biological replicates were set in each group (n≥3). Mitochondria were separated by differential centrifugation. After tissue homogenization, the nucleus and debris were removed by low-speed centrifugation (800×g, 10 min) in sequence, and mitochondria were enriched by high-speed centrifugation (10,000×g, 20 min). DNase I was used to remove the residual nuclear DNA contamination to ensure the purity of mitochondria.

[0122] 2. Extraction and quality control of mitochondrial DNA (mtDNA)

[0123] A mitochondrial DNA-specific extraction kit was used to avoid nuclear genome contamination. The purity was verified by Nanodrop, Qubit quantification, and agarose gel electrophoresis.

[0124] 3. Bisulfite treatment and verification of conversion efficiency

[0125] The mtDNA (500 ng) was treated with the EZ DNA Methylation-Gold Kit to convert unmethylated cytosine (C) to uracil (U), while methylated C remained unchanged. The conversion rate was evaluated by spike-in λ-DNA (without methylation) (required to be >99%), and the proportion of unconverted C was <1%.

[0126] 4. Whole Genome Bisulfite Sequencing (WGBS) library construction

[0127] The converted DNA was fragmented to 200 - 300 bp (using a Covaris sonicator). The Illumina TruSeqDNA methylation library construction kit was used to add methylated adapter. The bisulfite-treated DNA was selectively amplified (12 - 15 cycles) to avoid introducing bias due to over-amplification.

[0128] 5. High-throughput sequencing and data quality control

[0129] On the Illumina NovaSeq platform, in PE150 mode, the target sequencing depth was ≥30× (covering the full-length mitochondrial genome of 16.3 kb, and a depth of ≥100× was required to detect hypomethylated sites). FastQC was used to evaluate the read quality, and TrimGalore was used to remove low-quality sequences and adapter contamination.

[0130] 6. Bioinformatics analysis

[0131] The Bismark software was used to align the clean reads to the mouse mitochondrial reference genome (NC_005089.1), allowing ≤2 mismatches. The methylation level of CpG sites (the proportion of methylated C) was extracted, and sites with a coverage <10× were filtered. The DSS or methylKit was used for the analysis of differentially methylated regions (DMRs) between ages and tissues (threshold: |Δβ|≥0.2, FDR<0.05).

[0132] (4)Mining of aging-related mitochondrial methylation sites

[0133] The analysis results of WGBS sequencing data showed that a large number of differentially methylated sites appeared in the mitochondrial genomes of mouse brain tissues and thymus tissues at different ages ( Figure 13). By analyzing the mitochondrial genomes of brain tissues from 1-month-old (juvenile), 3-month-old, 5-month-old (middle-aged), 12-month-old, and 21-month-old (aged) C57BL / 6J mice using the mtDNA-MeDIP-seq technique, 127 aging-related differentially methylated regions (DMRs) were screened out. Among them, the methylation rates of 68 sites (such as c.590-650 in the mt-COX1 promoter region) increased significantly with aging, and the methylation rates of 59 sites (such as c.1200 in the mt-ND4 coding region) decreased significantly.

Claims

1. A mitochondrial gene methylation modification tool, characterized in that, The mitochondrial gene methylation modification tool consists of a mitochondrial localization signal peptide with an amino acid sequence as shown in SEQ ID NO.3, a TALE array, and a DNMT3A / 3L fusion protein with an amino acid sequence as shown in SEQ ID NO.1 in the order of N-terminus - C-terminus. The TALE array contains any one of the following repeat variable diresidue sequences: NG-NG-NI-NI-HD-HD-HD-NI-NI-NN-NG-HD-NI-NI-NG-NI; NI-NN-NN-NN-NG-NN-NI-NN-HD-NI-NG-HD-NI-NI-NI-HD; NG-HD-NG-HD-NI-NN-NN-HD-NG-NG-HD-NI-NI-HD-NI-NG; NI-HD-NI-NG-HD-NN-NI-NI-NG-NI-HD-NN-HD-HD-NN-HD; NI-HD-NI-NN-HD-NI-NG-NI-HD-HD-HD-HD-HD-NN-NI-NG; NG-NI-HD-HD-NI-NI-NI-HD-NN-HD-HD-HD-HD-NG-HD-NG; NG-NI-NN-NI-HD-NI-HD-NI-HD-NN-NI-NN-HD-NI-NG-NI; NG-NG-NG-NN-NI-NN-NI-NI-NN-HD-HD-NG-NG-HD-NN-HD; NG-NI-NN-NG-HD-HD-NG-HD-NI-NG-HD-NN-HD-HD-HD-NG; NG-NI-HD-NN-HD-NI-NG-HD-HD-NG-NG-NG-NI-HD-NI-NG; NI-HD-HD-NG-NI-HD-NN-NI-NN-NG-NI-HD-NI-HD-HD-NN; NG-NG-NI-NI-NI-NI-NI-HD-NI-NN-NI-NG-NN-HD-NI-NI; NI-NN-NI-NI-HD-HD-NI-NI-NI-NI-NG-NN-NI-NI-HD-NN; NG-NG-HD-NI-NI-HD-HD-NI-NI-NG-NI-NN-HD-HD-HD-NG; NI-NI-HD-NG-NG-NG-HD-HD-NG-HD-NI-HD-NG-NI-NG-HD; NG-NI-NI-NI-NI-HD-NG-NI-NN-NN-HD-NN-NN-HD-NG-NI; NI-NN-NI-NG-NG-NN-NG-NN-NI-NI-NG-HD-NG-NN-NI-HD; NG-HD-HD-NI-NI-HD-NG-NN-NG-NG-HD-NI-NG-HD-NN-NN; NG-HD-HD-HD-HD-NG-NI-NG-HD-NG-NI-NN-NN-HD-HD-NG; NI-NN-NI-HD-NN-NG-NI-NI-NI-NG-NG-NI-NG-NN-NN-HD.

2. A method for constructing the mitochondrial gene methylation modification tool according to claim 1, characterized in that, It includes the following steps: (1) Design a TALE array targeting mitochondrial genes; (2) Link the coding sequences of the TALE array, DNMT3A / 3L fusion protein, and mitochondrial localization signal peptide to an expression vector; (3) Transfect cells and screen to obtain a cell line expressing the mitochondrial gene methylation modification tool.

3. The application of the mitochondrial gene methylation modification tool according to claim 1 in methylation editing, which regulates gene expression by targeting and modifying the methylation sites of mitochondrial genes, and the application is for non-disease diagnosis or treatment purposes.

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