Stem cell culture generation identification method based on epigenetics clock

Abstract

The invention discloses a stem cell culture generation identification method based on an epigenetics clock. Belongs to the field of biotechnology and molecular biology, and designs a specific multiple PCR primer pool and establishes a high-precision generation prediction model by screening eight CpG sites highly related to stem cell replicative senescence. The method comprises the following steps: firstly, carrying out hydrosulfite conversion on sample DNA (Deoxyribonucleic Acid), carrying out targeted amplification by adopting a primer group with an optimized ratio, calculating a methylation level through high-throughput sequencing, and substituting into a formula to output a result. The model has small mean absolute error and is significantly related to aging function indexes. Compared with traditional chip detection, the cost is reduced, the detection period is shortened, and the method is suitable for release inspection of stem cell treatment products, anti-aging drug screening and cell bank quality management.

Description

Technical Field

[0001] This invention belongs to the fields of biotechnology and molecular biology, and relates to stem cell quality control technology, particularly a method for identifying stem cell culture passages based on epigenetic clocks. Background Technology

[0002] Stem cells are a type of primitive cell with continuous self-renewal capacity and multi-directional differentiation potential under specific conditions. They possess important biological characteristics such as self-renewal, multi-directional differentiation, paracrine function, and homing effect, making them the core cell population for maintaining tissue homeostasis and repairing damage. Their unique role in tissue regeneration and repair has made stem cell therapy a hot topic in regenerative medicine research. Stem cell therapy refers to the isolation, culture, expansion, directed differentiation, and even gene modification of stem cells in vitro to obtain healthier and more vigorous stem cells, which are then transplanted into patients via intravenous infusion, local injection, or subarachnoid injection. Currently, stem cells have shown broad application prospects in the treatment of hematological diseases, immunodeficiency diseases, inherited metabolic diseases, and anti-aging research.

[0003] However, cellular senescence is one of the key factors affecting stem cell function. As stem cells age, their proliferative capacity gradually declines, and their differentiation potential also weakens. The functional decline of stem cells not only weakens tissue regeneration and repair capabilities but is also closely related to the occurrence and development of various diseases. For example, senescent stem cells not only struggle to effectively repair damaged myocardial tissue but may also exacerbate heart damage by secreting pro-inflammatory factors, leading to heart failure; senescence of stem cells in pulmonary blood vessels may participate in the formation of pulmonary hypertension.

[0004] During in vitro expansion, stem cells inevitably undergo "replicative senescence." This is a biological process driven by intrinsic mechanisms such as telomere loss, epigenetic alterations, and the accumulation of DNA damage, directly leading to stem cell proliferation arrest and a decline in multi-lineage differentiation potential. The result is inconsistent quality of stem cell products obtained for clinical use, ultimately affecting the stability and efficacy of treatments. Currently, population doubling counts are commonly used to define cell generations, but this method has significant errors and cannot reflect the intrinsic biological age of cells. Furthermore, some cells may prematurely age due to stress in the early stages of culture, while others may remain in a relatively "young" state. This heterogeneity poses a significant risk to the safety and efficacy of stem cell-based therapies (such as cell therapy and tissue engineering).

[0005] Currently, common methods for detecting cellular senescence mainly include β-galactosidase (SA-β-Gal) staining, telomere length detection, and senescence-associated secretory phenotype (SASP) factor detection (Mohamad Kamal NS, et al. Aging of the cells: Insight into cellular senescence and detection Methods. Eur J CellBiol. 2020;99(6):151108), but these methods generally suffer from insufficient accuracy and low sensitivity. In contrast, epigenetic clocks based on DNA methylation changes have higher predictive accuracy. The multiplex PCR combined with next-generation sequencing (NGS) strategy adopted in this invention has advantages such as clear targeting, high throughput, low cost, and excellent detection sensitivity compared with current epigenetic clock schemes based on whole-genome methylation sequencing (WGBS) or microarrays. It is especially suitable for standardized quality control processes in clinical diagnosis and large-scale industrial production. The results obtained by this method are highly correlated with cellular functional senescence indicators (such as decreased differentiation potential and increased SA-β-Gal activity). This technology can be widely used in quality control of stem cell preparation processes, release testing of cell therapy products, screening of anti-aging drugs, and quality management of stem cell banks, providing a reliable and efficient standardized tool for the field of regenerative medicine. Summary of the Invention

[0006] To address the aforementioned technical problems, the present invention aims to provide a method for identifying stem cell culture passages based on epigenetic clocks.

[0007] The technical solution of the present invention is as follows:

[0008] A method for identifying stem cell culture passages based on epigenetic clocks includes the following steps:

[0009] (1) Extract genomic DNA from the stem cell sample to be tested and convert it to bisulfite;

[0010] (2) The transformed DNA was amplified using a multiplex PCR primer pool containing a primer set targeting 8 specific CpG sites;

[0011] (3) Perform high-throughput sequencing on the amplified products and calculate the methylation level of each CpG site;

[0012] (4) Input the methylation level into the epigenetic clock model and output the predicted value of stem cell culture passage;

[0013] (5) The model expression is: Prediction generation = β0 + (β1×CpG1) + (β2×CpG2) + ... + (β8×CpG8), where β0 is the intercept and β1 to β8 are the weight coefficients assigned by the model to each target CpG site.

[0014] In the above technical solution, the 8 CpG sites include:

[0015] chr1:207823715-207823716,

[0016] chr18:68722183-68722184,

[0017] chr18:68722210-68722211,

[0018] chr6:11044585-11044586,

[0019] chr2:105399288-105399289,

[0020] chr7:130734355-130734356,

[0021] chr19:18233105-18233106,

[0022] chr3:160450199-160450200.

[0023] In the above technical solution, the multiplex PCR primer pool includes the following sequence combinations:

[0024] CpG1 primers: SEQ ID NO: 1 / 2

[0025] CpG2 & 3 primers: SEQ ID NO: 3 / 4

[0026] CpG4 primers: SEQ ID NO:5 / 6

[0027] CpG5 primers: SEQ ID NO:7 / 8

[0028] CpG6 primers: SEQ ID NO:9 / 10

[0029] CpG7 primers: SEQ ID NO:11 / 12

[0030] CpG8 primers: SEQ ID NO:13 / 14.

[0031] In the above technical solution, the volume ratio of each primer set in the primer pool is: CpG1:CpG2&3:CpG4:CpG5:CpG6:CpG7:CpG8 = 4:2:2:2:1:1:1.

[0032] In the above technical solution, the coefficients of the epigenetic clock model are:

[0033] β0: Intercept term;

[0034] β1 to β8: [-7.76, -13.53, -14.97, 4.77, 4.36, 3.95, 4.62, 11.55] ±10%.

[0035] In the above technical solution, the formula for calculating the methylation level in step (3) is:

[0036] .

[0037] In the above technical solution, the stem cells are umbilical cord-derived mesenchymal stem cells.

[0038] A primer set for stem cell passage identification, comprising the above-mentioned 8 pairs of specific primer sequences.

[0039] An application of an epigenetic clock model in stem cell quality control, wherein the model predicts culture passages based on the methylation data of the aforementioned CpG sites.

[0040] A method for assessing the aging state of stem cells involves calculating the difference between the predicted generation and the actual generation using the above method. A difference > 0 indicates accelerated aging, while a difference < 0 indicates decelerated aging.

[0041] Beneficial effects:

[0042] 1. Breakthrough in detection accuracy: The epigenetic clock model has a small mean absolute error, which is significantly better than the traditional population doubling counting method.

[0043] 2. Cost-effectiveness advantages: The multiplex PCR-NGS approach reduces costs and significantly shortens the detection cycle compared to the 850K chip;

[0044] 3. Strong technical compatibility: Minimal DNA input, suitable for precious clinical samples;

[0045] 4. Quality control innovation: Achieve objective quantification of the "biological age" of stem cell products, providing a new standard for the release of cell therapy products. Attached Figure Description

[0046] Figure 1 Heatmap showing the distribution of methylation levels at 15 methylation sites across culture generations;

[0047] Figure 2 Correlation analysis between multiplex PCR system and Illumina BeadChip 850K chip in methylation quantification;

[0048] Figure 3 Scatter plot of the correlation between epigenetic clock generations and actual generations;

[0049] Figure 4 : Bar chart of epigenetic clock aging status and distribution of β-galactosidase and CCK-8. Detailed Implementation

[0050] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. However, the following embodiments are only for explaining the present invention, and the scope of protection of the present invention should include all the contents of the claims. Moreover, through the description of the following embodiments, those skilled in the art can fully implement all the contents of the claims of the present invention.

[0051] This embodiment proposes a method for identifying stem cell culture passages based on the epigenetic clock, employing the following technical solution:

[0052] (1) Cell culture and sample collection

[0053] Umbilical cord samples were collected from full-term fetuses delivered via cesarean section. After aseptic cleaning and mincing, mononuclear cells were isolated using density gradient centrifugation and seeded at high density in MesenCult-XF Medium for primary culture at 37°C and 5% CO2. Cells were passaged periodically and digested using trypsin-EDTA. Cell samples from different passages were systematically collected, starting from the primary culture (P0) and collecting samples every other passage until reaching P10. The population doubling time and passage number for each sample were accurately recorded, and a portion of cells was retained for subsequent functional validation. After washing with PBS, genomic DNA was extracted directly from the collected cells, or the cells were cryopreserved at -80°C or in liquid nitrogen using appropriate cell preservation solutions for batch testing.

[0054] (2) Screening for specific CpG sites associated with replicative aging

[0055] High-quality genomic DNA was extracted from the samples collected in step (1), covering generations from P0 to P10. The DNA samples were then converted to bisulfite, and whole-genome DNA methylation analysis was performed using an Illumina Infinium Methylation EPIC BeadChip 850K chip. The obtained methylation data were correlated with the actual culture generations of the samples. Loci with a correlation coefficient |r| > 0.8 were selected, and a resilient network regression algorithm was used to screen for the core locus combination that contributes most to generation prediction. This resulted in a small but precise set of specific CpG loci across the entire genome, which were used to construct a high-precision epigenetic clock model. Eight loci were ultimately selected; specific locus information is shown in Table 1.

[0056] Table 1. Information on CpG sites associated with replicative aging

[0057] (3) Primer design and synthesis

[0058] To achieve efficient, economical, and high-throughput detection of core CpG sites, this invention develops a targeted methylation sequencing method based on multiplex PCR. This method uses Meth Primer software to design specific amplification primers for each core CpG target site. All primers are mixed to form a multiplex PCR primer pool, enabling efficient parallel amplification and accurate quantification of all target regions in a single-tube reaction. The relevant primer sequences are detailed in Table 2.

[0059] Table 2. Specific primer sequences

[0060] In addition, during primer design, the universal sequence ACACTCTTTCCCTACACGACGCTCTTCCGATCT was added to the 5' end of all forward primers, and the universal sequence GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT was added to the 5' end of all reverse primers for the first round of PCR amplification. A second round of PCR amplification was then performed based on the first round of PCR products to ligate Illumina sequencing platform-compatible adapters and add sample barcodes to construct an NGS sequencing library. High-throughput sequencing was performed using the Illumina NovaSeq 6000 platform.

[0061] The primer information for the second round of PCR is as follows:

[0062] The P5 end primer composition is as follows:

[0063] 5’-AATGATACGGCGACCACCGAGATCTACAC <barcode1>ACACTCTTTCCCTACACGACGCTCTTCCGATCT-3',

[0064] The P7 end primer composition is as follows:

[0065] 5'-CAAGCAGAAGACGGCATACGAGAT <barcode2>GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCT-3'

[0066] (4) Bioinformatics analysis

[0067] The fastq raw data was quality controlled, adapter was removed and low quality sequences were filtered using software TrimGalore version 0.6.7; the filtered sequences were aligned to the reference genome using software Bismark version 0.24.2; the obtained bam files were sorted and indexed using software samtools version 1.16.1; the average sequencing depth was calculated using software bedtools2 version 2.30.0; the sequences of the target region were screened from the bam files, the C of the methylation site was identified, the proportion of A / C / G / T at the site was calculated and the methylation level was calculated. The methylation level calculation formula is:

[0068]

[0069] (5) Construction of epigenetic clock model

[0070] The targeted methylation data matrix of the training set samples obtained in step (4) was used as the characteristic variable (X), and the corresponding actual culture passage was used as the response variable (Y). The elastic network regression algorithm was used for model training. This algorithm can effectively handle the problem of multicollinearity and automatically perform feature selection to generate a robust regression model. The output of the model is a continuous predicted passage value. The 10-fold cross-validation method was used for internal validation of the model. On this basis, the determination coefficient (R2) and the mean absolute error (MAE) between the predicted passage and the actual passage were calculated to evaluate the goodness of fit and the prediction bias of the model, respectively, so as to comprehensively judge its accuracy and reliability in practical application.

[0071] The epigenetic clock model can be expressed as the following formula:

[0072] Predicted passage = β0+ (β1xCpG1) + (β2xCpG2) +... + (β8xCpG8)

[0073] Wherein, β0is the intercept, β1to β8are the weight coefficients assigned by the model to each target CpG site. The specific coefficients can be seen in Table 3.

[0074] Table 3. Coefficients of each CpG site in the epigenetic clock model

[0075] (6) Correlation verification with functional senescence indicators

[0076] To ensure the biological significance of this epigenetic clock model and the clinical relevance of its prediction results, it needs to be associated and verified with classical cell functional aging indicators.

[0077] SA-β-Gal staining: centrifuge the cell culture at 1000xg for 20 minutes, take the supernatant for detection. Use double antibody one-step sandwich ELISA kit. Into the coated microplate coated with human SA-β-Gal capture antibody, add samples, standards, HRP labeled detection antibody in turn, incubate and wash thoroughly. Color development with substrate TMB, TMB is converted to blue under the catalysis of peroxidase, and to the final yellow under the action of acid. Use the microplate reader to measure the absorbance (OD value) at 450 nm wavelength, and calculate the sample concentration.

[0078] Proliferation capacity detection: CCK-8 method is used to detect cell proliferation activity. In the presence of electronic coupling reagent, it can be reduced by dehydrogenase in mitochondria to form highly water-soluble orange yellow formazan product. The depth of color is proportional to the proliferation of cells and inversely proportional to the cytotoxicity. Use the microplate reader to measure the OD value at 450 nm wavelength, which indirectly reflects the number of living cells.

[0079] Example 1 Stem cell collection, culture and passage

[0080] Select full-term cesarean section fetal umbilical cord about 15 cm, wash repeatedly under sterile conditions with PBS to remove residual blood. Cut it into tissue blocks about 1.0 cm long with sterile scissors in RPMI MEDIUM 1640 medium, remove its blood vessels and cut as much as possible. Shake the tissue blocks in a 50 ml centrifuge tube with RPMI MEDIUM 1640 medium to mix thoroughly, then centrifuge at 2000 rpm for 5 minutes, discard the supernatant, repeat 3 times. After centrifugation, about 20 ml of umbilical cord tissue fragments are obtained. Mix the centrifugation sediment with MesenCult-XF Mediums complete medium, shake evenly, plant in a cell culture dish, and place in a 37℃, 5% CO2 incubator. On the 5th day of culture, all the tissue blocks are aspirated and discarded, and the culture medium is supplemented. Under a microscope, observe the adherent spindle-shaped or polygonal cells, then replace the culture medium every 3 days. About 15 days after culture, the cells are about 80% confluent, passaged at a ratio of 1:3, then passaged every 3 days.

[0081] During cell passage, different generations of cell samples are systematically collected, starting from primary cells (P0), every 1 generation, until the cells enter P10 generation. Each sample needs to accurately record its population doubling number and passage number, and part of the cells are reserved for subsequent functional verification.

[0082] Example 2: Specific CpG site screening

[0083] To screen for specific CpG sites, this study performed whole-genome DNA methylation analysis according to the following procedure. First, after washing the collected cells with PBS, total DNA was extracted using the TIAGEN DP304 genomic DNA extraction kit, and DNA quality was assessed by 1.0% TAE agarose gel electrophoresis and Qubit quantitative PCR. Subsequently, methylation analysis was performed using an Illumina Infinium Methylation EPIC BeadChip 850K chip, with the specific steps as follows:

[0084] (1) Bisulfite transformation: Take 500 ng of genomic DNA and transform it using EZ DNA Methylation Kit. The reaction conditions are denaturation at 98℃ for 10 minutes, followed by incubation at 64℃ for 2.5 hours.

[0085] (2) Whole genome amplification: Mix the transformed DNA with MA1 reagent and incubate at 37°C for 20-24 hours; after adding MA2 reagent, continue the reaction at 37°C for 1 hour, and seal the plate with a sealing film to prevent evaporation throughout the process.

[0086] (3) Fragmentation: Add FMS reagent to the amplification product and incubate at 37°C for 1 hour to randomly break the DNA into fragments of 300-600 bp.

[0087] (4) Precipitation and resuspension: Add PM1 precipitant and let stand at 4°C for 30 minutes; then centrifuge at 4°C and 3000-4000 g for 20 minutes and discard the supernatant; wash the precipitate with pre-cooled 85% and 100% ethanol in sequence, centrifuge to remove the supernatant and dry in air for 5-10 minutes; finally resuspend the precipitate with RA1 reagent and incubate at 48°C for 1 hour to fully dissolve the DNA.

[0088] (5) Hybridization: Denature the DNA at 95°C for 20 minutes, cool it immediately in an ice bath, add the sample to each channel of the EPIC chip, seal it and place it in a hybridization oven at 48°C for 16-24 hours.

[0089] (6) Washing: After hybridization, the chip is moved to a fluid workstation and thoroughly cleaned with the specified washing solution to remove unhybridized and non-specifically bound fragments.

[0090] (7) Single base extension: XStain reagent containing DNA polymerase and labeled nucleotides is added to the chip, and primer extension reaction is carried out in a temperature-controlled chamber.

[0091] (8) Immunostaining: The cells were treated with streptavidin-Cy3 to bind biotin-labeled nucleotides, and then with anti-DNP antibody solution to bind DNP-labeled nucleotides. After each staining, the cells were washed to remove non-specific dyes.

[0092] (9) Sealing: Apply a special sealing medium to the chip surface and cover it with a coverslip to protect the hybridization signal.

[0093] (10) Chip scanning: Use the Illumina iScan system to scan the chip, acquire fluorescence images and generate .idat data files.

[0094] (11) Data analysis: Import the .idat file into Illumina GenomeStudio software for background correction, standardization, β and M value calculation and quality control filtering; further use the minfi package of R / Bioconductor platform for low quality and cross-reactive probe filtering, batch effect correction and differential methylation analysis.

[0095] The obtained methylation data were correlated with the actual culture passages of the samples. Loci with a correlation coefficient |r| > 0.8 with passage passages were selected, and an elastic network regression algorithm was used to screen out the core locus combinations that contributed the most to passage passage prediction. The top 15 methylation loci were initially selected for subsequent epigenetic clock modeling. The distribution heatmap of methylation levels of these 15 loci with culture passages shows... Figure 1 .

[0096] To obtain a more concise and efficient prediction model, this invention combines the aforementioned 15 methylation sites in various ways and constructs an epigenetic clock model based on the elastic network algorithm, using the coefficient of determination (R²) as the basis. 2 The mean absolute error (MAE) and other metrics were used as evaluation indicators for model performance. The results showed that the MAE of combinations 3, 5, and 6 were all 0.20, but combination 3 used the fewest methylation sites. Although combinations 1 and 2 had fewer sites, their prediction errors were higher than those of combination 3 (see Table 4). Considering both model simplicity and prediction accuracy, this invention ultimately selected the eight methylation sites contained in combination 3 to construct the final epigenetic clock model. The corresponding methylation site information is listed in Table 3.

[0097] Table 4. Predictive performance of epigenetic clock models under different combinations

[0098] Example 3: Multiplex PCR Primer Design

[0099] Considering the high cost of the Illumina Infinium MethylationEPIC BeadChip 850K chip, this invention employs a targeted methylation detection method based on multiplex PCR amplification and next-generation sequencing (NGS), which significantly reduces detection costs while ensuring prediction accuracy. To this end, this invention designs specific primers for each of the eight methylation sites included in combination 3, and adds a universal sequence to the 5' end of each specific primer.

[0100] After bisulfite conversion, unmethylated cytosine C is converted to uracil U. During PCR amplification, the complexity of the DNA template decreases, making it easier for primer dimers to form, resulting in reduced targeted capture efficiency. Therefore, this invention employs primer screening during the primer design phase to obtain primer combinations with optimal capture efficiency. The specific operations are as follows:

[0101] Primer3 was used as the primer design software, limiting the amplified fragment length to 120–250 bp. The primer length parameters were set to Min: 20, Opt: 25, Max: 30, with the rest set to default. The primer selection criteria were: (1) Primer dimer: ΔG > -5 kcal / mol, with lower values ​​(more negative values) indicating more stable dimers and lower quality; (2) Hairpin structure: ΔG > -2 kcal / mol; (3) Terminal stability: expressed as ΔG value, generally recommended to be between -5 and -9 kcal / mol; (4) Tm value (melting temperature): the Tm difference between two primers should ideally be < 2℃; (5) GC content: between 30% and 70%. Subsequently, MPprimer software was used to analyze the dimers between different primers, removing primers that had dimers with other primers, and redesigning the analysis until no primer dimers existed between the entire primer set. The primer information for each methylation site can be found in Table 5. Combination 1 is the original primer combination (including P1+P2+P3+P4+P5+P7+P8), Combination 2 is the combination optimized for the first time (including P1+P2+P3+P4+P6+P7+P8), and Combination 3 is the combination optimized for the second time (including P1+P2+P3+P4+P6+P7+P9).

[0102] In addition, we verified the above results through experiments. 100 ng of genomic DNA was taken and transformed using the EZ DNA Methylation Kit. The reaction conditions were denaturation at 98°C for 10 minutes, followed by incubation at 64°C for 2.5 hours, and elution was performed with 50 μL. The first round of PCR reaction consisted of a total volume of 25 μL, including 12.5 μL of 2×Multiplex PCR Mix (High GC) (E287, Chinese nearshore protein), 1 μL of specific mixed primers, and 11.5 μL of DNA transformation product. The reaction conditions were: 94℃ / 1 min, 30 cycles (95℃ / 15 s, 60℃ / 30 s, 72℃ / 30 s), 5 cycles (95℃ / 15 s, 55℃ / 30 s, 72℃ / 30 s), 72℃ / 5 min, 4℃ / hold on. After the first round, the product was purified using 1.5×Beads (AMPure XP), and the purified product was eluted with 12 μL of water. The second round of PCR reaction consisted of a total volume of 25 μL, including 12.5 μL of 2×Multiplex PCR Mix (High GC) (E287, Chinese nearshore protein). The reaction consisted of GC, 1 μL of barcode primers (final concentration 0.2 μM), and 11.5 μL of purified DNA product. The reaction conditions were 94 °C / 1 min, 5 cycles (95 °C / 15 s, 60 °C / 30 s, 72 °C / 30 s), 72 °C / 5 min, 4 °C / holdon. After the second round of reaction, purification was performed using 1.0 × Beads (AMPure XP), and the purified product was eluted with 20 μL of water. After complete library construction, sequencing was performed using a 2 × 150 bp sequencing strategy on an Illumina NovaSeq6000 (Illumina, CA, USA), with each sample yielding 0.2 G of data.

[0103] Sequencing results showed that combination 3 had the highest target hit rate and alignment rate, meeting the requirements. See Table 6.

[0104] Table 5. Primer information for each methylation site

[0105] Table 6. Quality control analysis of different primer combinations

[0106] Example 4: Establishment of a methylation-targeted sequencing multiplex PCR system

[0107] Since different primers have different amplification efficiencies, there are significant differences in sequencing depth between sites in a single reaction. To address this issue, this study optimized the volume ratio of different primers (see Table 7) to obtain a mixed primer pool with sequencing depths of all genes at the same level.

[0108] Take 100 ng of genomic DNA and transform it using the EZ DNA Methylation Kit. The reaction conditions are: denaturation at 98°C for 10 minutes, followed by incubation at 64°C for 2.5 hours, and elution with 50 μL. The first round of PCR reaction consisted of a total volume of 25 μL, including 12.5 μL of 2×Multiplex PCR Mix (High GC) (E287, Chinese nearshore protein), 1 μL of specific mixed primers, and 11.5 μL of DNA transformation product. The reaction conditions were: 94℃ / 1 min, 30 cycles (95℃ / 15 s, 60℃ / 30 s, 72℃ / 30 s), 5 cycles (95℃ / 15 s, 55℃ / 30 s, 72℃ / 30 s), 72℃ / 5 min, 4℃ / hold on. After the first round, the product was purified using 1.5×Beads (AMPure XP), and the purified product was eluted with 12 μL of water. The second round of PCR reaction consisted of a total volume of 25 μL, including 12.5 μL of 2×Multiplex PCR Mix (High GC) (E287, Chinese nearshore protein). The reaction consisted of GC, 1 μL of barcode primers (final concentration 0.2 μM), and 11.5 μL of purified DNA product. The reaction conditions were 94 °C / 1 min, 5 cycles (95 °C / 15 s, 60 °C / 30 s, 72 °C / 30 s), 72 °C / 5 min, 4 °C / hold on. After the second round of reaction, purification was performed using 1.0 × Beads (AMPure XP), and the purified product was eluted with 20 μL of water. After complete library construction, sequencing was performed using a 2 × 150 bp sequencing strategy on an Illumina NovaSeq6000 (Illumina, CA, USA), with each sample yielding 0.2 G of data.

[0109] Sequencing results show that the sequencing depth of different methylation sites in System 3 is relatively balanced, with the smallest coefficient of variation, which meets the requirements. See Table 8.

[0110] Table 7. Primer ratio adjustment and optimization

[0111] Table 8. Sequencing depth analysis of each gene in different mixed primer pool systems

[0112] Example 5: Construction of an Epigenetic Clock Model

[0113] This invention, based on System 3 in Example 3, employs methylation-targeted capture technology to analyze stem cells of different passages. Sequencing data were aligned using Bismark software (version 0.24.2), and the generated BAM files were then sorted and indexed using samtools software (version 1.16.1). Target region sequences were further extracted from the BAM files, methylated cytosine sites (C) were identified, and the base ratios (A / C / G / T) at each site were statistically analyzed to calculate the methylation level.

[0114] To verify the reliability of the multiplex PCR system in methylation quantification, this study compared its results with those of the Illumina BeadChip 850K chip. Analysis showed that the two methods exhibited high consistency in quantifying methylation levels at different sites, with correlation coefficients ranging from 0.979 to 0.999. These results indicate that the multiplex PCR method established in this invention can effectively replace the Illumina BeadChip 850K chip and is suitable for the construction of epigenetic clock models.

[0115] To construct an epigenetic clock, this study used the methylation data matrix obtained by multiplex PCR as the feature variable (X) and the actual cell culture passage number as the response variable (Y). An elastic network regression algorithm was employed for modeling to establish a quantitative relationship between methylation patterns and culture passage numbers. The resulting linear model is shown below:

[0116] Predicted generation = β0 + β1 × CpG1 + β2 × CpG2 + ... + β8 × CpG8

[0117] In this model, β0 represents the intercept, and β1 to β8 are the regression coefficients corresponding to the eight key CpG sites. For details of their values, please refer to Appendix Table 3.

[0118] Model validation results show that its mean absolute error (MAE) is 0.194 and its coefficient of determination (R²) is [missing value]. 2 The error reached 0.997. This is an extremely low error with an R² close to 1. 2 The values ​​together indicate that the model can infer cell culture passages with extremely high accuracy based on methylation status.

[0119] Example 6: Correlation Validation of Functional Aging Indicators

[0120] To ensure the biological significance of this epigenetic clock model and the relevance of its predictions, it was validated by association with classic indicators of cellular functional aging. Aging rate = predicted generation - actual generation, where aging rate > 0 indicates accelerated aging, and aging rate < 0 indicates accelerated aging. We compared β-galactosidase and cell proliferation capacity (CCK-8 assay) between these two groups. The methods for detecting β-galactosidase and cell proliferation capacity are as follows:

[0121] Age-associated β-galactosidase (SA-β-Gal) staining: Cell culture was centrifuged at 1000×g for 20 minutes, and the supernatant was used for detection. A one-step sandwich enzyme-linked immunosorbent assay (ELISA) kit (Shanghai Keabob Biotechnology) was used. The sample, standard, and HRP-labeled detection antibody were added sequentially to the microwells pre-coated with human age-associated β-galactosidase (SA-β-Gal) capture antibody, followed by incubation and thorough washing. The substrate TMB was used for color development; TMB was converted to blue under the catalysis of peroxidase, and then to yellow under acidic conditions. The absorbance (OD value) was measured at 450 nm using a microplate reader, and the sample concentration was calculated.

[0122] Cell proliferation assay: Cell proliferation activity was detected using the Cell Counting Kit (CCK-8) (Shanghai Yisheng Biotechnology). In the presence of an electron coupling reagent, cells are reduced by mitochondrial dehydrogenases to form a highly water-soluble, orange-yellow formazan product. A standard curve was first established. The number of cells in the prepared cell suspension was counted using a cell counting chamber, and then the cells were seeded into culture plates. Cell suspension was seeded in 96-well plates (100 μL / well). The culture plates were pre-cultured in an incubator for a period of time (37℃, 5% CO2). 10 μL of CCK-8 solution was added to each well (avoiding air bubbles, as they will affect the OD value reading). The culture plates were incubated for 1–4 hours. The absorbance at 450 nm was measured using a microplate reader.

[0123] Intergroup comparisons showed that the β-galactosidase level in the aging deceleration group was significantly lower than that in the aging acceleration group (P<0.05), while the CCK-8 level in the aging deceleration group was significantly higher than that in the aging acceleration group (P<0.05). These results indicate that this model not only accurately reflects cell culture passages but is also closely related to the functional state of stem cell aging, demonstrating significant biological value and application potential.

[0124] The above description is merely a specific embodiment of this application, enabling those skilled in the art to understand or implement this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for identifying the passage of stem cell culture based on epigenetic clock, characterized in that, Comprising the following steps: (1) Extracting genomic DNA of the stem cell sample to be tested and performing bisulfite conversion; (2) Amplifying the converted DNA using a multiplex PCR primer pool comprising primer sets for 8 specific CpG sites; (3) High-throughput sequencing of the amplification products to calculate the methylation level of each CpG site; (4) Inputting the methylation level into an epigenetic clock model to output the predicted value of the culture passage number of the stem cell; (5) The model expression is: Predicted Passage = β0 + (β1xCpG1) + (β2xCpG2) +... + (β8xCpG8), β0 is the intercept, β1 to β8 are the weight coefficients assigned by the model to each target CpG site, β1 to β8: [-7.76, -13.53, -14.97, 4.77, 4.36, 3.95, 4.62, 11.55] ±10%; The 8 specific CpG sites include: chr1:207823715-207823716, chr18:68722183-68722184, chr18:68722210-68722211, chr6:11044585-11044586, chr2:105399288-105399289, chr7:130734355-130734356, chr19:18233105-18233106, chr3:160450199-160450200.

2. The method of claim 1, wherein: The multiplex PCR primer pool comprises the following sequence combinations: CpG1 primers: SEQ ID NO: 1 / 2, CpG2 & 3 primers: SEQ ID NO: 3 / 4, CpG4 primers: SEQ ID NO: 5 / 6, CpG5 primers: SEQ ID NO: 7 / 8, CpG6 primers: SEQ ID NO: 9 / 10, CpG7 primers: SEQ ID NO: 11 / 12, CpG8 primers: SEQ ID NO: 13 / 14.

3. The method of claim 3, wherein: The volume ratio of each primer set in the primer pool is: CpG1:CpG2 & 3:CpG4:CpG5:CpG6:CpG7:CpG8 = 4:2:2:2:1:1:

1.

4. The method of claim 1, wherein: The methylation level calculation formula in step (3) is: 。 5. The method of claim 1, wherein: The stem cell is an umbilical cord-derived mesenchymal stem cell.

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