A method for detecting cell mitochondrial autophagy

Abstract

The present invention relates to the field of biological autophagy detection technology. The present invention discloses a method and system for detecting mitochondrial autophagy in cells. The method simulates the cell microenvironment by constructing an experimental platform, combines fluorescent probe labeling, dynamic monitoring and gene regulation, and realizes real-time monitoring and quantitative analysis of the dynamic changes of mitochondrial autophagy. Compared with the existing technology, the present invention shows its unique advantages in many aspects: first, through microfluidic technology, the intracellular drug and gene status can be independently regulated to achieve parallel processing of samples and significantly improve detection efficiency; second, the new strategy of quantitative fluorescence imaging and data processing is adopted, which not only improves the reliability of the signal, but also clarifies the selection mechanism of biomarkers, thereby enhancing the accuracy of identifying the autophagic state; the present invention provides a more systematic experimental basis for studying the molecular mechanism of mitochondrial autophagy by comprehensively analyzing the relationship between fluorescence signals and gene regulation.

Description

Technical Field

[0001] The present invention relates to the technical field of biological autophagy detection, and in particular to a method for detecting cell mitochondrial autophagy. Background Art

[0002] In recent years, mitochondrial autophagy, as an important form of cellular autophagy, has gradually attracted widespread attention from biomedical researchers. Mitochondrial autophagy is not only an important component of the intracellular autophagy pathway, but also a key mechanism for cells to regulate energy metabolism, maintain cellular homeostasis, and resist oxidative stress and other physiological processes. Existing technologies mainly rely on traditional methods such as fluorescence microscopy, immunofluorescence staining, and flow cytometry to quantitatively analyze mitochondrial autophagy. These technologies infer the activity level of intracellular autophagy by specifically labeling mitochondrial autophagy-related molecules and combining them with quantitative measurement of fluorescence signals. However, these methods usually have many problems such as non-specific labeling, time delay, signal attenuation, and complex data processing, and are highly dependent on the technical level of the operator and the stability of the experimental conditions.

[0003] Although some studies have attempted to improve the monitoring methods of mitophagy, they still face many challenges. For example, existing detection methods often lack precise control of the cellular microenvironment and cannot simultaneously monitor the expression levels of multiple autophagy-related proteins. In addition, many existing methods fail to fully consider the differences between different cell types and treatment conditions, resulting in low data reproducibility and insufficient universal applicability. Therefore, a novel and widely applicable autophagy detection method is urgently needed to address the limitations of traditional technologies in terms of accuracy, sensitivity, and multiple detection. Summary of the Invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a method for detecting mitochondrial autophagy. By constructing an experimental platform that can simulate the cellular microenvironment, combined with fluorescent probe labeling technology, dynamic monitoring, and gene regulation methods, it can achieve comprehensive monitoring and analysis of the mitochondrial autophagy process. This detection method not only improves sensitivity and specificity, but also can capture the dynamic changes of cellular autophagy in real time.

[0006] To solve the above technical problems, the present invention provides the following technical solution: a method for detecting mitochondrial autophagy, comprising: constructing an experimental platform to simulate the cellular microenvironment; labeling mitochondrial autophagy-related proteins with fluorescent probes, and dynamically monitoring and capturing fluorescent signals; selecting vectors through gene regulation, quantitatively analyzing fluorescent signals, identifying and screening biomarkers; and outputting a visual report to display the dynamic process of autophagy.

[0007] As a preferred embodiment of the method for detecting mitochondrial autophagy of the present invention, the experimental platform includes selecting cell culture medium and growth conditions to construct a system simulating the cell microenvironment, including control of temperature, pH, oxygen level and nutrient concentration;

[0008] Microfluidic channels are designed in the incubator to allow samples to flow in various channels. Each channel can independently change the drug and gene status of the sample to complete parallel testing.

[0009] As a preferred embodiment of the method for detecting mitochondrial autophagy of the present invention, the labeling of mitochondrial autophagy-related proteins includes determining key proteins related to mitochondrial autophagy, selecting peptides with high specificity to design fluorescent probes, and adding the designed fluorescent probes to the cell culture medium;

[0010] The fluorescent labeling reaction was started and the duration was set to a fixed value of 30 minutes to 1 hour. The cells were washed with PBS buffer to remove unbound probes.

[0011] As a preferred embodiment of the method for detecting mitochondrial autophagy of the present invention, the dynamic monitoring includes setting an integrated sensor in the experimental platform to detect fluorescence signals in different wavelength ranges; monitoring the fluorescence intensity of the labeled cells, using signal denoising based on wavelet transform, automatically capturing the fluorescence signal, and performing fluorescence imaging at set time intervals;

[0012] The sensor output is read in real time by a microcontroller, the captured intracellular fluorescence signal stream is input into a computer for processing, and a graph of the relationship between fluorescence intensity and time is plotted in real time.

[0013] As a preferred embodiment of the method for detecting mitochondrial autophagy of the present invention, the gene regulation includes determining the target gene, introducing exogenous Cas9 protein with a gRNA targeting the selected gene, transfecting the gRNA and Cas9 into cells using electroporation, and determining the cell line with successful gene editing through antibiotic screening and genome sequencing;

[0014] Build a dynamic model to describe gene expression levels:

[0015]

[0016] in, Indicates the gene expression level, represents the CRISPR targeting efficiency, represents the concentration of transcription factors, represents the half-saturation constant, represents the regulating factor;

[0017] When the targeting efficiency of the CRISPR system is improved, the gene expression level increases accordingly. At the same time, the concentration of transcription factors also significantly affects gene expression. As the concentration increases, the gene expression level rises rapidly in the initial stage with the increase of transcription factors. After reaching the concentration threshold, the growth rate slows down and eventually tends to a stable state. This saturation effect is captured by the half-saturation constant; the shape of the nonlinear regulatory factor expression curve.

[0018] As a preferred embodiment of the method for detecting mitochondrial autophagy of the present invention, the quantitative analysis of the fluorescence signal includes capturing the fluorescence signal of the labeled cells in real time using a fluorescence microscope, storing the data as a signal intensity matrix, normalizing the data, adjusting the fluorescence intensity to a uniform range, and calculating the corrected fluorescence amount using the fluorescence intensity based on the region:

[0019]

[0020] in, The corrected fluorescence intensity, is the total number of pixels in the area, is the fluorescence intensity of the pixel, is the background signal intensity of the corresponding point; the final result serves as the basic input for feature extraction.

[0021] As a preferred embodiment of the method for detecting cell mitochondrial autophagy described in the present invention, the identification and screening of biomarkers includes extracting autophagy-related image features using local binary patterns combined with histogram features, and establishing feature vectors. :

[0022]

[0023] in, Represents the mth feature extracted, where m is prepared according to the target number of features set in the experiment;

[0024] For each feature Calculate the statistical significance value and select less than the threshold Features:

[0025]

[0026] in, To select the result, The significance value of each feature is obtained by comparing it with the background noise. Only when the current feature is considered a biomarker.

[0027] Another object of the present invention is to provide a detection system for cell mitochondrial autophagy, which can efficiently perform the detection task of cell mitochondrial autophagy and improve the overall flexibility of the experiment and the accuracy of data analysis.

[0028] As a preferred embodiment of the detection system for cell mitochondrial autophagy described in the present invention, it includes: an experimental platform module, a fluorescent probe labeling module, a dynamic monitoring module, a gene regulation module, and a data analysis and reporting module;

[0029] The experimental platform module constructs a simulated cell microenvironment and designs microfluidic channels to achieve parallel processing of samples and independent drug-gene status regulation;

[0030] The fluorescent probe labeling module is responsible for designing and synthesizing fluorescent probes to label mitophagy-related proteins, performing fluorescent labeling reactions through appropriate time settings, and providing basic data for subsequent monitoring;

[0031] Dynamic monitoring module, with integrated sensors for real-time monitoring of fluorescent signals of labeled cells, automatically capturing and denoising fluorescent data;

[0032] The gene regulation module regulates target genes through gene editing technology and describes the relationship between gene expression and transcription factors by constructing a mathematical model to describe the regulatory effect of gene expression;

[0033] The data analysis and reporting module is responsible for quantitative analysis of the captured fluorescence signals and biomarker screening. It uses significance analysis to gradually screen qualified biomarkers, generate quantitative reports, and visualize the results.

[0034] A computer device includes a memory and a processor, wherein the memory stores a computer program, and is characterized in that when the processor executes the computer program, it implements the steps of a method for detecting cell mitochondrial autophagy.

[0035] A computer-readable storage medium stores a computer program thereon, wherein the computer program, when executed by a processor, implements the steps of a method for detecting mitochondrial autophagy in cells.

[0036] Beneficial effects of the present invention: This method performs parallel sample processing in a controlled microenvironment, which greatly improves the efficiency and accuracy of the experiment. In addition, by designing specific fluorescent probes and gene editing strategies, real-time monitoring of the autophagy process in cells can be achieved, thereby objectively reflecting the dynamic response of cells to changes in internal and external environments. At the same time, the introduction of the data analysis module not only enhances the identification and screening capabilities of biomarkers, but also provides quantitative experimental data for in-depth analysis of the molecular mechanism of mitochondrial autophagy. This new detection method effectively fills the gaps in existing technologies in real-time dynamic monitoring, autophagy regulatory mechanism modeling, and high-throughput screening. Therefore, the introduction of this method is expected to provide new tools and ideas for the research and treatment of related diseases, and has important application prospects and scientific research value. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be derived from these drawings without inventive efforts. Among them:

[0038] Figure 1 A schematic flow chart of a method for detecting cell mitochondrial autophagy provided in one embodiment of the present invention.

[0039] Figure 2 A schematic diagram of the working modules of a cell mitochondrial autophagy detection system provided in one embodiment of the present invention. DETAILED DESCRIPTION

[0040] To make the above-mentioned objects, features, and advantages of the present invention more clearly understood, the following detailed description of the specific embodiments of the present invention is given in conjunction with the accompanying drawings. It is obvious that the examples described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in this field without creative work should fall within the scope of protection of the present invention.

[0041] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0042] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it constitute a separate or selective embodiment that is mutually exclusive with other embodiments.

[0043] The present invention is described in detail with reference to schematic diagrams. For ease of illustration, cross-sectional views of device structures may be partially enlarged and not to scale when describing embodiments of the present invention. Furthermore, the schematic diagrams are merely illustrative and should not limit the scope of the present invention. Furthermore, in actual production, the three-dimensional dimensions of length, width, and depth should be included.

[0044] Furthermore, in the description of the present invention, it should be noted that the terms "upper, lower, inner, and outer" and other references to orientations or positional relationships are based on the orientations or positional relationships shown in the accompanying drawings and are intended solely to facilitate and simplify the description of the present invention. They are not intended to indicate or imply that the devices or components referred to must have, be constructed, or operate in a specific orientation, and therefore should not be construed as limiting the present invention. Furthermore, the terms "first, second, or third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0045] In this disclosure, unless otherwise specified or limited, the terms "mounted," "connected," and "connected" should be interpreted broadly. For example, they may refer to fixed, removable, or integral connections. They may also refer to mechanical, electrical, or direct connections, indirect connections through an intermediary, or internal communication between two components. Those skilled in the art will understand the specific meanings of these terms in this disclosure.

[0046] Example 1, with reference to Figure 1 , which is the first embodiment of the present invention, provides a method for detecting cell mitochondrial autophagy, comprising:

[0047] S1: Construct an experimental platform to simulate the cell microenvironment.

[0048] Furthermore, cell culture media and growth conditions are selected to construct a system that mimics the cell microenvironment, which includes control of temperature, pH, oxygen levels, and nutrient concentrations;

[0049] Microfluidic channels are designed in the incubator to allow samples to flow in various channels. Each channel can independently change the drug and gene status of the sample to complete parallel testing.

[0050] S2: Label mitochondrial autophagy-related proteins with fluorescent probes and perform dynamic monitoring to capture fluorescent signals.

[0051] Furthermore, key proteins related to mitochondrial autophagy were identified, and highly specific peptides were selected to design fluorescent probes, which were then added to the cell culture medium.

[0052] Start the fluorescent labeling reaction, set the duration to a fixed 30 minutes to 1 hour, and wash the cells with PBS buffer to remove unbound probes. Set the fluorescence signal intensity and intracellular target protein concentration , fluorescent probe binding efficiency and background signal The relationship between:

[0053]

[0054] in, is the quantum yield of the fluorescent probe.

[0055] Furthermore, an integrated sensor is set up in the experimental platform to detect fluorescence signals in different wavelength ranges; the fluorescence intensity of the labeled cells is monitored, and signal denoising based on wavelet transform is used to automatically capture the fluorescence signal, and fluorescence imaging is performed at set time intervals;

[0056] In different time periods Under the fluorescence intensity The change can be expressed by the differential equation:

[0057]

[0058] in, is the reaction rate constant, is the target protein concentration that changes with time, is the fluorescence decay constant;

[0059] The sensor output is read in real time by a microcontroller, the captured intracellular fluorescence signal stream is input into a computer for processing, and a graph of the relationship between fluorescence intensity and time is plotted in real time.

[0060] S3: Select vectors through gene regulation, quantitatively analyze fluorescence signals, and identify and screen biomarkers.

[0061] Furthermore, the target gene is identified, gRNA targeting the selected gene is introduced, exogenous Cas9 protein is introduced, gRNA and Cas9 are transfected into cells using electroporation, and cell lines with successful gene editing are identified through antibiotic screening and genome sequencing;

[0062] Build a dynamic model to describe gene expression levels:

[0063]

[0064] in, Indicates gene expression level, represents the CRISPR targeting efficiency, represents the concentration of transcription factors, represents the half-saturation constant, represents the regulating factor;

[0065] When the targeting efficiency of the CRISPR system is improved, the gene expression level increases accordingly. At the same time, the concentration of transcription factors also significantly affects gene expression. As the concentration increases, the gene expression level rises rapidly in the initial stage with the increase of transcription factors. After reaching the concentration threshold, the growth rate slows down and eventually tends to a stable state. This saturation effect is captured by the half-saturation constant; the shape of the nonlinear regulatory factor expression curve.

[0066] It should be noted that the fluorescence signals of labeled cells were captured in real time using a fluorescence microscope and stored as a signal intensity matrix. The data were normalized to adjust the fluorescence intensity to a uniform range, and the corrected fluorescence amount was calculated using the fluorescence intensity based on the area:

[0067]

[0068] in, The corrected fluorescence intensity, is the total number of pixels in the area, is the fluorescence intensity of the pixel, is the background signal intensity of the corresponding point; the final result serves as the basic input for feature extraction.

[0069] Furthermore, the local binary pattern is combined with the histogram feature to extract the autophagy-related image features and establish the feature vector :

[0070]

[0071] in, Represents the mth feature extracted, where m is prepared according to the target number of features set in the experiment;

[0072] For each feature Calculate the statistical significance value and select less than the threshold Features:

[0073]

[0074] in, To select the result, The significance value of each feature is obtained by comparing it with the background noise. =0.05, the current feature is considered a biomarker.

[0075] S4: Output a visualization report to show the dynamic process of autophagy.

[0076] Furthermore, the fluorescence signal intensity data is extracted from the dynamic monitoring module, the gene expression level data is obtained from the gene regulation module, and the relevant data of the cell survival rate is recorded.

[0077] The above data formats are unified and integrated into a database or table, including dimensions such as fluorescence signals, gene expression, and cell survival rate.

[0078] Choose appropriate data visualization software based on your needs and use context-sensitive chart types (e.g., line charts, heat maps, scatter plots, etc.) to display data of different dimensions. Integrate a graph of fluorescence intensity over time, overlay gene expression curves, and annotate cell viability.

[0079] Furthermore, adding interactive components such as data zooming, floating tooltips, and data filtering buttons allows researchers to analyze data from different perspectives, and provides export functions so that researchers can save charts and data analysis results.

[0080] It should be noted that if a gene is found to significantly influence the results during autophagy, redesigning the gRNA to target other related genes for further exploration can be considered. Adjusting gene regulation methods, such as introducing different transcription factors or regulatory elements, can be used to carefully study their regulatory effects on the target gene. Implementing new parameter settings and re-running the experiment will ensure that the adjustments after feedback improve the accuracy and reproducibility of the experiment.

[0081] Record in detail the parameters adjusted each time and their impact on the experimental results to accumulate data for subsequent research and experiments.

[0082] Example 2 is an embodiment of the present invention, which provides a method for detecting cell mitochondrial autophagy. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through experiments.

[0083] The experiment used mouse embryonic fibroblasts (MEFs) as the research subject. First, an experimental platform incorporating microfluidics technology was established to simulate the cellular microenvironment. The researchers selected DMEM medium and set growth conditions including a temperature of 37°C, a pH of 7.4, an oxygen level of 5%, and a glucose concentration of 25 mM to optimize the cell's metabolic state.

[0084] Four independent microfluidic channels were designed into the experimental platform to enable parallel processing of different drug treatments. Specifically, Channel A was treated with rapamycin, a drug known to promote autophagy; Channel B was treated with chloroquine, a drug known to block autophagy; and Channels C and D served as control groups, containing only culture medium. Next, fluorescent probes were designed using specific peptides to label key proteins associated with mitophagy, such as LC3-II, to ensure sensitive and targeted detection.

[0085] After the fluorescent labeling reaction, i.e., the fluorescent probe was added, the reaction was carried out in a temperature-controlled incubator for 30 minutes. The experimental results are shown in Table 1.

[0086] Table 1: Control experiment data

[0087]

[0088] The experimental data table above shows significant differences between the groups in fluorescence signal intensity, cell survival rate, gene expression, and number of biomarkers. Specifically, the fluorescence signal intensity in the Channel A (Rapamycin) group reached 1500 AU, and the cell survival rate remained at 85%, indicating that the drug effectively promoted mitochondrial autophagy and maintained cell survival. In contrast, the fluorescence signal intensity in Channel B (Chloroquine) was only 300 AU, and the survival rate dropped to 60%. This indicates that the use of chloroquine significantly inhibited the autophagy process, resulting in low cell survival, validating its role in regulating autophagy.

[0089] Furthermore, considering gene expression levels, channel A showed a gene expression level of 320 FG / g, while channel B showed only 180 FG / g, further demonstrating the positive effect of rapamycin in promoting autophagy and corresponding gene expression. Results for the control group showed that the fluorescence signal intensity and gene expression levels in channels C and D were 500 AU and 520 AU, respectively, and 350 FG / g and 340 FG / g, respectively. This suggests that in the absence of exogenous drugs, the control group exhibited low autophagy activity but still displayed normal cell viability and gene expression.

[0090] Combined with the above experimental data, it is shown that this detection method is indeed innovative in observing the dynamic process of mitochondrial autophagy in cells. In traditional autophagy detection, static analysis and qualitative evaluation are often relied upon. However, the present invention provides a comprehensive and in-depth understanding through the technical means of combining real-time dynamic monitoring with gene regulation, further expanding the depth of autophagy research. In particular, the introduction of microfluidics technology and the use of fluorescent probes greatly improve the specificity and sensitivity of fluorescent labeling. At the same time, accompanied by real-time data processing, it can promptly reflect changes in the physiological state of cells, providing a reliable basis for subsequent biomarker screening.

[0091] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0092] Embodiment 3, the third embodiment of the present invention, is different from the first two embodiments in that:

[0093] If the functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage media include various media capable of storing program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0094] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0095] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, and then editing, interpreting, or processing in another suitable manner as necessary, and then storing it in a computer memory.

[0096] It should be understood that various components of the present invention may be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods may be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof may be used: a discrete logic circuit having logic gate circuits for implementing logic functions on data signals, an application-specific integrated circuit having suitable combinational logic gate circuits, a programmable gate array (PGA), a field-programmable gate array (FPGA), etc.

[0097] Example 4, reference Figure 2 , is an embodiment of the present invention, providing a cell mitochondrial autophagy detection system, characterized by: comprising an experimental platform module, a fluorescent probe labeling module, a dynamic monitoring module, a gene regulation module, and a data analysis and reporting module;

[0098] The experimental platform module constructs a simulated cell microenvironment and designs microfluidic channels to achieve parallel processing of samples and independent drug-gene status regulation;

[0099] The fluorescent probe labeling module is responsible for designing and synthesizing fluorescent probes to label mitophagy-related proteins, performing fluorescent labeling reactions through appropriate time settings, and providing basic data for subsequent monitoring;

[0100] Dynamic monitoring module, with integrated sensors for real-time monitoring of fluorescent signals of labeled cells, automatically capturing and denoising fluorescent data;

[0101] The gene regulation module regulates target genes through gene editing technology and describes the relationship between gene expression and transcription factors by constructing a mathematical model to describe the regulatory effect of gene expression;

[0102] The data analysis and reporting module is responsible for quantitative analysis of the captured fluorescence signals and biomarker screening. It uses significance analysis to gradually screen qualified biomarkers, generate quantitative reports, and visualize the results.

[0103] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for detecting cell mitochondrial autophagy, characterized in that: include, Construct an experimental platform to simulate the cell microenvironment; The experimental platform includes selecting cell culture media and growth conditions to construct a system that simulates the cell microenvironment, including control of temperature, pH, oxygen levels, and nutrient concentrations; Designing microfluidic channels in the incubator allows samples to flow through various channels. Each channel can independently change the drug and gene status of the sample to complete parallel testing; Mitochondrial autophagy-related proteins are labeled with fluorescent probes and dynamically monitored to capture fluorescent signals; Vectors are selected through gene regulation, fluorescence signals are quantitatively analyzed, and biomarkers are identified and screened. Gene regulation includes identifying the target gene, directing RNA (gRNA) targeting the selected gene, introducing exogenous Cas9 protein, transfecting the gRNA and Cas9 into cells using electroporation, and confirming successful gene-edited cell lines through antibiotic screening and genome sequencing. Build a dynamic model to describe gene expression levels: Among them, G represents the gene expression level, E g represents the CRISPR targeting efficiency, T represents the concentration of the transcription factor, K represents the half-saturation constant, and β represents the regulatory factor; When the targeting efficiency of the CRISPR system increases, gene expression levels rise accordingly. At the same time, the concentration of transcription factors also significantly affects gene expression. As the concentration increases, gene expression levels rise rapidly in the initial stage as the transcription factor increases. After reaching the concentration threshold, the growth rate slows down and eventually reaches a stable state. This saturation effect is captured by the half-saturation constant; the shape of the nonlinear regulatory factor expression curve; The identification and screening of biomarkers includes extracting autophagy-related image features using local binary patterns combined with histogram features, and establishing a feature vector V: V=[f1,f2,...,f m ] Among them, f m Represents the mth feature extracted, where m is prepared according to the target number of features set in the experiment; For each feature f m Calculate the statistical significance value and select features that are less than the threshold α: Among them, S m For the selection result, p m is the feature significance value. The significance of each feature is obtained by comparing it with the background noise. Only when the significance p value is less than the preset threshold α, the current feature is considered to be a biomarker; Output a visual report to show the dynamic process of autophagy.

2. The method for detecting cell mitophagy according to claim 1, wherein: The labeling of mitophagy-related proteins includes determining key proteins related to mitophagy, selecting peptides with high specificity to design fluorescent probes, and adding the designed fluorescent probes to the cell culture medium; The fluorescent labeling reaction was started and the duration was set to a fixed value of 30 minutes to 1 hour. The cells were washed with PBS buffer to remove unbound probes.

3. The method for detecting cell mitophagy according to claim 2, wherein: The dynamic monitoring includes setting an integrated sensor in the experimental platform to detect fluorescence signals in different wavelength ranges; monitoring the fluorescence intensity of the labeled cells, using signal denoising based on wavelet transform, automatically capturing the fluorescence signal, and setting time intervals for fluorescence imaging; The sensor output is read in real time by a microcontroller, the captured intracellular fluorescence signal stream is input into a computer for processing, and a graph of the relationship between fluorescence intensity and time is plotted in real time.

4. The method for detecting cell mitochondrial autophagy according to claim 3, wherein: The quantitative analysis of the fluorescence signal includes capturing the fluorescence signal of the labeled cells in real time using a fluorescence microscope, storing the data as a signal intensity matrix, normalizing the data to adjust the fluorescence intensity to a uniform range, and calculating the corrected fluorescence amount using the fluorescence intensity based on the region: Where F is the corrected fluorescence amount, N is the total number of pixels in the area, and I i is the fluorescence intensity of the pixel, B i is the background signal intensity of the corresponding point; the final result serves as the basic input for feature extraction.

5. A system using the method for detecting cell mitophagy according to any one of claims 1 to 4, characterized in that: It includes experimental platform module, fluorescent probe labeling module, dynamic monitoring module, gene regulation module, and data analysis and reporting module; The experimental platform module constructs a simulated cell microenvironment and designs microfluidic channels to achieve parallel processing of samples and independent drug-gene status regulation; The fluorescent probe labeling module is responsible for designing and synthesizing fluorescent probes to label mitophagy-related proteins, performing fluorescent labeling reactions through appropriate time settings, and providing basic data for subsequent monitoring; The dynamic monitoring module integrates a sensor for real-time monitoring of the fluorescence signal of the labeled cells, automatically capturing the fluorescence data and performing denoising; The gene regulation module regulates the target gene through gene editing technology and describes the relationship between gene expression and transcription factors by constructing a mathematical model to describe the regulatory effect of gene expression; The data analysis and reporting module is responsible for quantitative analysis of the captured fluorescence signals and biomarker screening, using significance analysis to gradually screen qualified biomarkers, generate quantitative reports and visualize the results.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 4 are implemented.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

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