Method for rapid evaluation of cell state and application thereof

Abstract

The application discloses a cell state rapid evaluation method and application thereof, and belongs to the technical field of cell biology. The cell state evaluation method provided by the application takes "molecular index-function phenotype-generation threshold value" as a core logic, integrates omics screening, PCR verification, protein characterization and threshold modeling, mines differential genes (DEGs) related to cell stability (proliferation, apoptosis, aging and carcinogenesis) through transcriptomics, establishes a molecular marker library, designs a quantitative detection scheme for the core markers, determines the gene expression threshold values of different generations, verifies the correlation between the molecular index and the function phenotype through protein expression and subcellular localization, combines a ROC curve and Z-score standardization to construct a multi-gene joint scoring model, and realizes grading determination of "qualified / critical / unqualified", so that the method can realize rapid and accurate detection of the cell state.

Description

Technical Field

[0001] This invention relates to the field of cell biology technology, specifically to a method for rapid evaluation of cell state and its application. Background Technology

[0002] The stability of cell state is a core prerequisite for the accuracy of scientific research experiments and the safety of commercial production. Especially in the fields of large-scale manufacturing of cell-cultured meat, clinical translation of stem cell therapy, and production of recombinant protein drugs, functional degradation (such as slowed proliferation), mutation (such as the risk of cancer), and aging (such as telomere shortening) during cell passage directly affect the quality of the final product and the safety of its application.

[0003] Existing cell state detection technologies have significant limitations: (1) Single dimension: Most technologies only focus on cell activity (such as MTT assay for proliferation and trypan blue staining for viability), and cannot cover deep molecular mechanisms such as apoptosis, autophagy, and carcinogenesis; (2) Lack of dynamism: No correlation model of "generation-molecular indicators-functional phenotype" has been established, making it difficult to predict the stability of cells after long-term passage; (3) Poor commercial adaptability: There is no standardized detection process and threshold determination system, which cannot meet the detection needs of "fast, accurate and repeatable" in industrial production. Summary of the Invention

[0004] The purpose of this invention is to provide a rapid cell state evaluation method and its application. By integrating three major technologies—global transcriptomics analysis, precise targeted PCR quantification, and protein function characterization—a multi-dimensional and synergistic cell state detection system is constructed to achieve a closed-loop evaluation from "phenotypic observation" to "molecular tracing." This provides a standardized solution for commercial applications and solves the significant limitations of existing cell state detection technologies.

[0005] This invention is achieved through the following technical solution: This invention provides a method for rapid evaluation of cell state, comprising the following steps: Standardize the culture of target cells, establish a multi-generation gradient cell bank and retain samples; We will screen for core differentially expressed genes related to cell stability using transcriptomics and construct a molecular biomarker library. Real-time quantitative PCR was used to quantitatively detect the core biomarkers screened from the core differentially expressed genes, and the dynamic thresholds of gene expression at different generations were determined by combining ROC curves. By detecting at the protein level, the expression level and functional status of core proteins expressed by core differentially expressed genes were obtained, and the protein expression level was scored. A multi-dimensional joint scoring model is constructed based on the dynamic threshold of gene expression and the protein expression level score to achieve graded determination of cell status as qualified / critical / unqualified.

[0006] Further specified, the target cells include, but are not limited to, myoblasts, mesenchymal stem cells, CHO cells, or HEK293 cells; Preferably, the cell stability includes: proliferation, apoptosis, senescence, carcinogenesis, or adhesion.

[0007] More specifically, the cell stability during proliferation includes MYC, CCND1, and CDK1 as its core differentially expressed genes. When the cell stability is apoptosis, the core differentially expressed genes include BAX, CASP9, and FAS. The cell stability described is that during senescence, the core differentially expressed genes include CDKN2A and CDKN1A. When the cell stability is carcinogenic, its core differentially expressed genes include RAS, mutant TP53, and TERT. When the cell stability is defined as adhesion, its core differentially expressed genes include CDH1 and ITGA5.

[0008] Further specified, the screening criteria for differentially expressed genes are |log2FC|≥1 and FDR<0.05, where FC represents the fold change and FDR represents the false detection rate.

[0009] More specifically, evaluation methods at the protein level include: protein expression level detection, immunofluorescence, or flow cytometry.

[0010] Further specifying, the determination of the gene expression dynamic thresholds for different generations includes: Plot the ROC curves of the core differentially expressed genes and their relative expression levels to determine the optimal cutoff values ​​for the core differentially expressed genes. The relative expression levels of different core differentially expressed genes were normalized using the Z-score formula Z=(X-μ) / σ, where X is the sample value, μ is the mean, and σ is the standard deviation.

[0011] Further specifying, a multi-dimensional joint scoring model is constructed based on gene expression dynamic thresholds and protein expression level scores to achieve graded determination of cell status as qualified / critical / unqualified, including: Weights are assigned to different core differentially expressed genes based on their association with cell stability. Cell stability is scored using the following formula: Cell stability score = Σ(gene Z-score × weight) + Σ(protein expression level score × weight), where the protein expression level score is 1 point for normal state, 0.5 points for critical state, and 0 points for abnormal state. Based on the grading criteria, the cell status is determined as qualified / critical / unqualified according to the cell stability score. Preferably, the weights of cancer-related genes are 0.3, proliferation-related genes are 0.2, aging-related genes are 0.3, and apoptosis-related genes are 0.2.

[0012] More specifically, the grading criteria include: When the cell stability score is ≥0.8, and the indicators used to judge whether the cell function is normal or abnormal at the gene and protein levels do not exceed their corresponding critical values, the cell status is qualified. When 0.5 ≤ cell stability score < 0.8, and one or two of the indicators used to judge whether cell function is normal or abnormal at the gene level and / or protein level exceed their corresponding critical values, the cell state is critical. When the cell stability score is <0.5, and any of the criteria used to determine whether cell function is normal or abnormal at the gene and / or protein levels exceeds its corresponding threshold, the cell state is considered unqualified. Preferably, the gene-level assessment indicators include: apoptosis rate μ1, proliferation activity μ2, and senescence positivity rate μ3; wherein, the critical value of apoptosis rate μ1 is 5.3%, μ1≤5.3% indicates normal cell function, and μ1>5.3% indicates abnormal cell function; The critical value for proliferation activity μ2 is 1.6%; μ2 ≥ 1.6% indicates normal cell function; μ2 < 1.6% indicates abnormal cell function. The critical value for the senescence positivity rate μ3 is 3.7%; μ3 ≤ 3.7% indicates normal cell function; μ3 > 3.7% indicates abnormal cell function. Preferably, the protein-level assessment indicators include: protein expression level (F), fluorescence intensity (MFI), and apoptosis rate (μ1); wherein, the critical value for protein expression level (F) is 1.8 ng / mL, F ≥ 1.8 ng / mL indicates normal cell function, and F < 1.8 ng / mL indicates abnormal cell function. The critical value of fluorescence intensity MFI is the mean fluorescence intensity μ0 + 2 × standard deviation σ. MFI ≤ μ0 + 2σ indicates normal cell function; MFI > μ0 + 2σ indicates abnormal cell function. The critical value for apoptosis rate μ1 is 5.3%. If μ1 ≤ 5.3%, cell function is normal; if μ1 > 5.3%, cell function is abnormal.

[0013] The grading criteria include gene expression levels (normalized by Z-score) and protein functional status scores (assigned based on expression levels and localization) used to calculate cell stability. The numbers correspond to the core genes and key proteins detected (i.e., the sum of the number of core genes and key proteins screened), serving as the quantitative basis for cell status determination.

[0014] The present invention provides an electronic device comprising: a memory, a processor, and a computer program, wherein the computer program is stored in the memory and configured to be executed by the processor to implement the above-described rapid cell state evaluation method.

[0015] The present invention provides a computer-readable storage medium storing a computer program, which is executed by a processor to implement the above-described rapid cell state evaluation method.

[0016] Compared with the prior art, the present invention has the following advantages and beneficial effects: The rapid cell state assessment method provided by this invention integrates the global perspective of omics, the precise targeting of PCR, and the functional characterization of protein detection. It works synergistically from multiple dimensions at the molecular level to rapidly and accurately assess cell state. The results are both specific and comprehensive, with excellent reliability. It provides a new path for cell state analysis and has the potential for scientific research and commercial application. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be considered as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. In the drawings: Figure 1 A flowchart of the rapid cell state evaluation method provided by the present invention; Figure 2 The graph shows the expression trend of core genes in chicken muscle cells from generation P0 to P30, as provided in Example 1 of this invention. The horizontal axis represents cell generation (P1, P5, P10, P15, P20, P25, P30); the vertical axis represents the relative gene expression level (with generation P1 as 1); and the curves represent MYC (proliferation gene, lower limit critical value 0.35), BAX (apoptosis gene, upper limit critical value 1.8), and CDKN2A (senescence gene, upper limit critical value 2.5). Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to embodiments and accompanying drawings. The illustrative embodiments and descriptions of this invention are for explanation only and are not intended to limit the invention. Unless otherwise specified in the embodiments, conventional conditions or conditions recommended by the manufacturer shall apply. Reagents or instruments whose manufacturers are not specified are all commercially available conventional products. Example

[0019] Please refer to Figure 1 This invention provides a method for rapid evaluation of cell state, comprising the following steps: Step S1: Standardize the culture of target cells, establish a multi-generation gradient cell bank and retain samples.

[0020] Step S11: Cell culture and passage design.

[0021] (1) Select target cells (such as myoblasts for meat culture, mesenchymal stem cells for stem cell therapy, and CHO cells for biopharmaceuticals) and establish a passage gradient library (it is recommended to cover passages 0, 5, 10, 15, 20, 25, and 30, which can be expanded according to needs).

[0022] Further specifying, the target cells include, but are not limited to, myoblasts, mesenchymal stem cells, CHO cells, or HEK293 cells. (2) Control the consistency of culture conditions: unify the culture medium formula (e.g., high glucose DMEM + 10% fetal bovine serum for myoblasts), passage ratio (1:3-1:5), culture environment (37℃, 5% CO2, 95% humidity) to avoid external factors interfering with the test results.

[0023] Step S12, Sample Retention Specifications (1) Omics / PCR samples: Collect ≥3 biological replicates per generation. After collecting cells with a cell scraper, add Trizol reagent and freeze at -80℃ to preserve RNA integrity. (2) Protein samples: Cells of the same passage were directly collected into EP tubes and frozen at -80°C (avoid repeated freeze-thaw cycles) for subsequent Western blot / ELISA detection; (3) Morphological samples: Inoculate cells into 6cm culture dishes, fix them with 4% paraformaldehyde after they adhere to the wall, store them at 4℃, and use them for immunofluorescence or microscopic observation.

[0024] Step S2 involves screening for core differentially expressed genes related to cell stability using transcriptomics and constructing a molecular biomarker library.

[0025] Step S21, Transcriptome Sequencing and Data Processing (1) Perform whole transcriptome sequencing (Illumina NovaSeq platform) on key passages (such as P0, P10, P20, P30) of cells, with ≥3 biological replicates per group; (2) Data preprocessing: FastQC was used for quality control (filtering reads with Q30 < 80%), STAR / HISAT2 software was used to align clean reads to the reference genome, and DESeq2 / edgeR was used for gene quantification.

[0026] Step S22: Differential gene screening and functional annotation (1) Screening criteria: |log2FC|≥1, FDR<0.05, combined with WGCNA (weighted gene co-expression network analysis) to identify gene modules strongly associated with "generation"; (2) Functional enrichment: GO (biological processes: such as "cell cycle regulation" and "apoptosis process") and KEGG (pathways: such as p53 signaling pathway and PI3K-AKT pathway) annotations were performed using the Metascape database to identify core molecular markers. Preferably, the cell stability includes: proliferation, apoptosis, senescence, carcinogenesis, or adhesion.

[0027] More specifically, the cell stability during proliferation includes the core differentially expressed genes MYC, CCND1, and CDK1. Functional description: Upregulation of MYC / CCND1 promotes G1-S phase transition, while CDK1 regulates cell division.

[0028] When cell stability is at the apoptotic level, the core differentially expressed genes include BAX, CASP9, and FAS. Functional description: BAX / CASP9 activates the mitochondrial apoptosis pathway, and FAS mediates extrinsic apoptosis.

[0029] The core differentially expressed genes for cellular stability during senescence include CDKN2A and CDKN1A. Functional description: p16 / p21 upregulation inhibits the cell cycle and induces a senescent phenotype.

[0030] When the cell stability is carcinogenic, its core differentially expressed genes include RAS, mutant TP53, and TERT. Functional description: RAS activation promotes malignant cell proliferation, and high expression of TERT prolongs telomeres.

[0031] When cell stability is defined as adhesion, the core differentially expressed genes include CDH1 and ITGA5. Functional description: Downregulation of CDH1 / ITGA5 leads to weakened cell adhesion, increasing the risk of migration and invasion.

[0032] Further specified, the screening criteria for differentially expressed genes are |log2FC|≥1 and FDR<0.05, where FC represents the fold change and FDR represents the false detection rate.

[0033] Step S3: Real-time quantitative PCR was used to quantitatively detect the core biomarkers screened from the core differentially expressed genes, and the dynamic thresholds of gene expression at different generations were determined by combining ROC curves.

[0034] Step S31: Experimental Design for Real-Time Quantitative PCR (qPCR) (1) Primer design: Design specific primers for the core genes in Table 1 (such as CDKN2A primers: upstream 5'-GAAGGTGGAACCTGGCTCTG-3', downstream 5'-GGCGTTTGGAGCAGGTGAT-3'), with GAPDH / ACTB as the housekeeping gene for correction. (2) Evaluation method: The SYBR Green method (low cost, high throughput) or TaqMan probe method (high specificity) was used. Three technical replicates were set up for each sample. After calculating the Ct value, the relative gene expression level was calculated using the 2^(-ΔΔCt) method.

[0035] Step S32: Determining the dynamic threshold (1) Plot the “generation-gene expression level” curve and determine the optimal cut-off value for each gene through ROC curve analysis: for example, when the expression level of CDKN2A is ≥2.5 times (vsP0 generation), it is determined to be “critical risk of aging”; (2) Standardization: The expression levels of different genes were normalized using Z-score (Z=(X-μ) / σ, where X is the sample value, μ is the mean, and σ is the standard deviation) to avoid interference from differences in gene expression.

[0036] Further specifying, the determination of the gene expression dynamic thresholds for different generations includes: Plot the ROC curves of the core differentially expressed genes and their relative expression levels to determine the optimal cutoff values ​​for the core differentially expressed genes. The relative expression levels of different core differentially expressed genes were normalized using the Z-score formula Z=(X-μ) / σ, where X is the sample value, μ is the mean, and σ is the standard deviation.

[0037] Step S4: By detecting at the protein level, obtain the expression level and functional status of the core protein expressed by the core differentially expressed gene, and score the protein expression level.

[0038] More specifically, evaluation methods at the protein level include: protein expression level detection, immunofluorescence, or flow cytometry.

[0039] (1) Protein expression level detection (Western blot / ELISA) Western blot: Total protein was extracted from cells at each passage, and the expression of core proteins was detected (e.g., the LC3-II / LC3-I ratio reflects autophagy activity, and p53 protein expression reflects DNA damage). ImageJ was used to quantify the gray values ​​of the bands, with β-actin as an internal control. ELISA: Detects metabolic markers in cell supernatant or lysis buffer (such as lactate content reflecting the Warburg effect, and β-galactosidase activity reflecting aging). Strictly follow the kit instructions and calculate the concentration / activity value.

[0040] (2) Protein localization and morphological observation (immunofluorescence / flow cytometry) Immunofluorescence: Fixed cells were stained (e.g., CDH1 was labeled with Alexa Fluor 488, and LC3 was labeled with Alexa Fluor 594). Observation under laser confocal microscopy: CDH1 cell membrane localization decreased → abnormal adhesion function; LC3 punctate aggregation → autophagy activation.

[0041] Flow cytometry: Annexin V-FITC / PI double staining was used to detect apoptosis rate, and PI single staining was used to analyze the cell cycle: G1 phase arrest + S phase reduction → senescence or DNA damage; early apoptosis rate ≥10% → apoptosis activation.

[0042] Step S5: Construct a multi-dimensional joint scoring model based on the gene expression dynamic threshold and protein expression level score to achieve graded determination of cell status as qualified / critical / unqualified.

[0043] Step S51: Design of the scoring system (1) Weighting: The weights are assigned based on the correlation between genes / proteins and cell stability (e.g., RAS, a cancer-related gene, has a weight of 0.3; MYC, a proliferation-related gene, has a weight of 0.2; CDKN2A, a senescence-related gene, has a weight of 0.3; and BAX, an apoptosis-related gene, has a weight of 0.2). (2) Calculation formula: Cell stability score = Σ (gene Z-score × weight) + Σ (protein expression score × weight), where the protein expression score is graded as "normal (1 point), borderline (0.5 points), abnormal (0 points)".

[0044] Step S52: Setting Grading Criteria (1) Pass: The score is ≥0.8 and no single judgment indicator (such as apoptosis rate, cancer gene expression) exceeds the critical value; (2) Critical: 0.5≤score<0.8, and 1-2 judgment indicators are close to the critical value (needs to be combined with subsequent generation observation); (3) Unqualified: score <0.5, and any judgment indicator (such as RAS expression ≥3 times, apoptosis rate ≥15%) is significantly abnormal.

[0045] Further specifying, a multi-dimensional joint scoring model is constructed based on gene expression dynamic thresholds and protein expression level scores to achieve graded determination of cell status as qualified / critical / unqualified, including: Weights are assigned to different core differentially expressed genes based on their association with cell stability. Cell stability is scored using the following formula: Cell stability score = Σ(gene Z-score × weight) + Σ(protein expression level score × weight), where the protein expression level score is 1 point for normal state, 0.5 points for critical state, and 0 points for abnormal state. Based on the grading criteria, the cell status is determined as qualified / critical / unqualified according to the cell stability score.

[0046] More specifically, the weights of cancer-related genes are 0.3, proliferation-related genes are 0.2, aging-related genes are 0.3, and apoptosis-related genes are 0.2. Preferably, the grading criteria include: When the cell stability score is ≥0.8, and the indicators used to judge whether the cell function is normal or abnormal at the gene and protein levels do not exceed their corresponding critical values, the cell status is qualified. When 0.5 ≤ cell stability score < 0.8, and one or two of the indicators used to judge whether cell function is normal or abnormal at the gene level and / or protein level exceed their corresponding critical values, the cell state is critical. When the cell stability score is <0.5, and any of the criteria used to determine whether cell function is normal or abnormal at the gene and / or protein levels exceeds its corresponding threshold, the cell state is considered unqualified. Preferably, the gene-level assessment indicators include: apoptosis rate μ1, proliferation activity μ2, and senescence positivity rate μ3; wherein, the critical value of apoptosis rate μ1 is 5.3%, μ1≤5.3% indicates normal cell function, and μ1>5.3% indicates abnormal cell function; The critical value for proliferation activity μ2 is 1.6%; μ2 ≥ 1.6% indicates normal cell function; μ2 < 1.6% indicates abnormal cell function. The critical value for the senescence positivity rate μ3 is 3.7%; μ3 ≤ 3.7% indicates normal cell function; μ3 > 3.7% indicates abnormal cell function. Preferably, the protein-level assessment indicators include: protein expression level (F), fluorescence intensity (MFI), and apoptosis rate (μ1); wherein, the critical value for protein expression level (F) is 1.8 ng / mL, F ≥ 1.8 ng / mL indicates normal cell function, and F < 1.8 ng / mL indicates abnormal cell function. The critical value of fluorescence intensity MFI is the mean fluorescence intensity μ0 + 2 × standard deviation σ. MFI ≤ μ0 + 2σ indicates normal cell function; MFI > μ0 + 2σ indicates abnormal cell function. The critical value for apoptosis rate μ1 is 5.3%. If μ1 ≤ 5.3%, cell function is normal; if μ1 > 5.3%, cell function is abnormal.

[0047] The rapid cell state assessment method provided by this invention integrates the global perspective of omics, the precise targeting of PCR, and the functional characterization of protein detection. It works synergistically from multiple dimensions at the molecular level to rapidly and accurately assess cell state. The results are both specific and comprehensive, with excellent reliability. It provides a new path for cell state analysis and has the potential for scientific research and commercial application.

[0048] The cell state evaluation method provided by this invention is based on sample preparation and standardized culture, and integrates omics screening, PCR verification and protein characterization to construct a multi-dimensional joint scoring model, realizing multi-dimensional synergy, from "global screening" to "precise verification", avoiding the limitations of a single technology.

[0049] The cell state evaluation method provided by this invention uses "molecular indicators - functional phenotype - generation threshold" as its core logic, integrating omics screening, PCR validation, protein characterization, and threshold modeling to achieve rapid and accurate detection of cell state. Specifically, omics screening involves using transcriptomics to mine differentially expressed genes (DEGs) related to cell stability (proliferation, apoptosis, senescence, carcinogenesis) and establish a molecular marker library; PCR validation involves designing quantitative detection schemes for core markers to determine gene expression thresholds at different generations; protein characterization verifies the correlation between molecular indicators and functional phenotypes through protein expression levels and subcellular localization. Threshold modeling combines ROC curves and Z-score standardization to construct a multi-gene joint scoring model, achieving a graded judgment of "qualified / critical / unqualified".

[0050] The cell state evaluation method provided by this invention establishes a dynamic threshold for quantitative standards through generational correlation analysis, enabling "early warning and early intervention" and adapting to the long-term monitoring needs of commercial production.

[0051] The cell state evaluation method provided by this invention offers a complete standard operating procedure from sample preparation to detection to data analysis, and can be developed into a "cell state detection kit" (including qPCR primers and antibody combination) for easy large-scale application.

[0052] The cell state evaluation method provided by this invention can be used to study the life cycle of seed cells; can be used to identify the stability of cells from 0 to 30 generations or more; can be used to screen stable passaged cell lines; and can be used to identify the stability of different cell lines.

[0053] The rapid cell state evaluation method provided by this invention has core indicators for rapid cell state diagnosis. It is an effective means of judging cell functional status and guiding the rational use of cells. It can lay a solid technical foundation for cell quality control and mechanism research in cell meat engineering and other fields, and has broad application prospects.

[0054] The cell state evaluation method provided by this invention can adjust the detection markers for different cell types (myoblasts, stem cells, CHO cells), covering multiple fields such as cultured meat, cell therapy, and biopharmaceuticals. In the field of cultured meat, it can screen highly stable myoblast cell lines (such as porcine / chicken / bovine muscle satellite cells) and monitor the proliferation capacity and differentiation potential of cells in large-scale bioreactors. Its advantage lies in its ability to identify the stability of cells from passage 0 to 30 and above, ensuring that cells do not undergo carcinogenesis or functional degradation during cultured meat production, thus guaranteeing product safety. In the field of cell therapy, it evaluates the passage stability of mesenchymal stem cells and CAR-T cells, avoiding treatment failure caused by cell aging or apoptosis in clinical applications. Its advantage lies in its ability to quickly eliminate "unqualified" cell batches through multi-gene joint scoring, reducing clinical risks. In the field of biopharmaceuticals, it can monitor the passage status of CHO cells and HEK293 cells, ensuring the stable yield and quality of recombinant proteins (such as antibody drugs). Its advantage lies in its ability to predict cell functional degradation 10-15 passages in advance compared to traditional detection methods (such as cell viability), reducing production losses. Example

[0055] This embodiment provides an electronic device, which includes a memory, a processor, and a computer program. The computer program is stored in the memory and configured to be executed by the processor to implement the rapid cell state evaluation method of Embodiment 1. Example

[0056] This embodiment provides a computer-readable storage medium storing a computer program, which is executed by a processor to implement the rapid cell state evaluation method of Embodiment 1.

[0057] 1. Experimental Materials Cells: Chicken muscle satellite cells (primary isolated from skeletal muscle of 1-day-old SPF chickens). Reagents: Trizol reagent (Invitrogen), SYBR Green qPCR Mix (Takara), Western blot antibodies (CDKN2A, MYC, β-actin, Abcam), Annexin V-FITC / PI apoptosis detection kit (BD); Instruments: Illumina NovaSeq 6000, real-time quantitative PCR instrument (Bio-Rad CFX96), laser confocal microscope (Zeiss LSM880).

[0058] 2. Experimental Procedure (1) Cell culture and generation sample preparation Culture medium: high glucose DMEM + 15% fetal bovine serum + 1% penicillin / streptomycin; Passaging: When the cell confluence reaches 80%-90%, digest with 0.25% trypsin and passage at a ratio of 1:4 to obtain P0, P5, P10, P15, P20, P25 and P30 cells in sequence. Sample retention: Three biological replicates are collected per generation for transcriptome sequencing (preserved in Trizol), qPCR (same as transcriptome sample), Western blot (frozen at -80℃), and apoptosis detection (fresh cells).

[0059] (2) Screening for differentially expressed genes using transcriptomics Sequencing results: Compared with the P0 generation, CDKN2A (log2FC=2.3, FDR=0.01) and BAX (log2FC=1.8, FDR=0.02) were significantly upregulated in the P30 generation cells, while MYC (log2FC=-1.5, FDR=0.03) was significantly downregulated. Functional enrichment: Differentially expressed genes were mainly enriched in the "cellular senescence" (GO:0007568) and "cell cycle arrest" (GO:0045786) pathways.

[0060] (3) qPCR verification of core genes Detected genes: CDKN2A, MYC, BAX, GAPDH (internal reference); See results Figure 1 As shown, the relative expression levels of CDKN2A in generation P30 were 2.7 times that of generation P0, MYC was 0.4 times, and BAX was 1.9 times, consistent with the transcriptome results. Threshold setting: ROC curve analysis showed that when the expression level of CDKN2A was ≥2.5 times (vsP0), it was determined to be "senescence threshold" (sensitivity 92%, specificity 88%).

[0061] (4) Protein detection and apoptosis analysis Western blot: The expression level of CDKN2A protein in generation P30 was 3.1 times that in generation P0, and MYC was 0.3 times. Flow cytometry: The early apoptosis rate of P30 generation cells was 12.3% (compared to 3.5% in P0 generation), and the proportion of cells in G1 phase increased from 52.1% in P0 generation to 78.4% in P30 generation (while the proportion in S phase decreased from 35.2% to 15.7%).

[0062] (5) Stability scoring and judgment Scoring calculation: CDKN2A (Z=-1.8, weight 0.3), MYC (Z=1.2, weight 0.2), BAX (Z=-1.5, weight 0.2), apoptosis rate (0.5 points, weight 0.3) → total score = (-1.8×0.3) + (1.2×0.2) + (-1.5×0.2) + (0.5×0.3) = -0.45; Judgment result: Score <0.5, P30 generation chicken muscle cells are "unqualified" and not suitable for large-scale production of cell cultured meat.

[0063] The detection was performed following the steps and methods in Example 1. The core results are as follows: Passage observation: P20 pre-passage CHO cells showed stable MYC expression (relative expression level 0.8-1.2 times vs P0), apoptosis rate <5%, and stability score ≥0.9, and were judged as "qualified"; Warning function: The expression level of CDKN2A in P25 generation cells increased to 2.1 times (close to the critical value of 2.5), and the score dropped to 0.7, which was judged as "critical", indicating that the culture conditions need to be optimized or the cell batch needs to be changed.

[0064] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for rapid evaluation of cell state, characterized in that, Includes the following steps: Standardize the culture of target cells, establish a multi-generation gradient cell bank and retain samples; A molecular biomarker library was constructed by screening core differentially expressed genes related to cell stability using transcriptomics; wherein, cell stability includes: proliferation, apoptosis, senescence, carcinogenesis, or adhesion. Real-time quantitative PCR was used to quantitatively detect the core biomarkers screened from the core differentially expressed genes, and the dynamic thresholds of gene expression at different generations were determined by combining ROC curves. By detecting at the protein level, the expression level and functional status of core proteins expressed by core differentially expressed genes were obtained, and the protein expression level was scored. A multi-dimensional joint scoring model was constructed based on gene expression dynamic thresholds and protein expression level scores to achieve graded determination of cell states as qualified / critical / unqualified, including: Weights are assigned to different core differentially expressed genes based on their association with cell stability. Cell stability is scored using the following formula: Cell stability score = Σ(gene Z-score × weight) + Σ(protein expression level score × weight), where the protein expression level score is 1 point for normal state, 0.5 points for critical state, and 0 points for abnormal state. Based on the grading criteria, the cell status is determined as qualified / critical / unqualified according to the cell stability score.

2. The rapid cell state evaluation method according to claim 1, characterized in that, The target cells are: myoblasts, mesenchymal stem cells, CHO cells, or HEK293 cells.

3. The rapid cell state evaluation method according to claim 2, characterized in that, The cell stability during proliferation includes MYC, CCND1, and CDK1 as its core differentially expressed genes. When the cell stability is apoptosis, the core differentially expressed genes include BAX, CASP9, and FAS. The cell stability described is that during senescence, the core differentially expressed genes include CDKN2A and CDKN1A. When the cell stability is carcinogenic, its core differentially expressed genes include RAS, mutant TP53, and TERT. When the cell stability is defined as adhesion, its core differentially expressed genes include CDH1 and ITGA5.

4. The rapid cell state evaluation method according to claim 1, characterized in that, The screening criteria for differentially expressed genes are |log2FC|≥1 and FDR<0.05, where FC represents the fold change and FDR represents the false detection rate.

5. The rapid cell state evaluation method according to claim 1, characterized in that, Protein-level detection methods include: protein expression level detection, immunofluorescence, or flow cytometry.

6. The rapid cell state evaluation method according to claim 1, characterized in that, The determination of the gene expression dynamic thresholds for different generations includes: Plot the ROC curves of the core differentially expressed genes and their relative expression levels to determine the optimal cutoff values ​​for the core differentially expressed genes. The relative expression levels of different core differentially expressed genes were normalized using the Z-score formula Z=(X-μ) / σ, where X is the sample value, μ is the mean, and σ is the standard deviation.

7. The rapid cell state evaluation method according to claim 1, characterized in that, The weights of cancer-related genes were 0.3, proliferation-related genes were 0.2, aging-related genes were 0.3, and apoptosis-related genes were 0.

2.

8. The rapid cell state evaluation method according to claim 7, characterized in that, The grading criteria include: When the cell stability score is ≥0.8, and the indicators used to judge whether the cell function is normal or abnormal at the gene and protein levels do not exceed their corresponding critical values, the cell status is qualified. When 0.5 ≤ cell stability score < 0.8, and one or two of the indicators used to judge whether cell function is normal or abnormal at the gene level and / or protein level exceed their corresponding critical values, the cell state is critical. When the cell stability score is <0.5, and any of the criteria used to determine whether cell function is normal or abnormal at the gene and / or protein levels exceeds its corresponding threshold, the cell state is considered unqualified.

9. The rapid cell state evaluation method according to claim 8, characterized in that, The genetic level indicators include: apoptosis rate μ1, proliferation activity μ2, and senescence positivity rate μ3; among them, the critical value of apoptosis rate μ1 is 5.3%, μ1≤5.3% indicates normal cell function, and μ1>5.3% indicates abnormal cell function. The critical value for proliferation activity μ2 is 1.6%; μ2 ≥ 1.6% indicates normal cell function; μ2 < 1.6% indicates abnormal cell function. The critical value for the senescence positivity rate μ3 is 3.7%. If μ3 ≤ 3.7%, cell function is normal; if μ3 > 3.7%, cell function is abnormal.

10. The rapid cell state evaluation method according to claim 8, characterized in that, The indicators for protein-level assessment include: protein expression level (F), fluorescence intensity (MFI), and apoptosis rate (μ1). Among them, the cutoff value for protein expression level (F) is 1.8 ng / mL. F ≥ 1.8 ng / mL indicates normal cell function, while F < 1.8 ng / mL indicates abnormal cell function. The critical value of fluorescence intensity MFI is the mean fluorescence intensity μ0 + 2 × standard deviation σ. MFI ≤ μ0 + 2σ indicates normal cell function; MFI > μ0 + 2σ indicates abnormal cell function. The critical value for apoptosis rate μ1 is 5.3%. If μ1 ≤ 5.3%, cell function is normal; if μ1 > 5.3%, cell function is abnormal.

11. An electronic device, characterized in that, The electronic device includes a memory, a processor, and a computer program, the computer program being stored in the memory and configured to be executed by the processor to implement the rapid cell state evaluation method according to any one of claims 1-10.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that is executed by a processor to implement the rapid cell state evaluation method according to any one of claims 1-10.

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