A method for detecting and quantifying lipid droplet degradation at both the single-droplet and single-cell levels.

Abstract

This invention belongs to the interdisciplinary field of quantitative detection of lipid catabolism and cell image analysis, specifically involving the quantitative detection of lipid droplet degradation rate in adipocytes through live-cell image quantitative analysis. This invention combines microscopic imaging with biophysical modeling methods, making it particularly suitable for detecting the activity of lipases and the size of lipid droplet degradation rates in small cell numbers (less than 100 cells), and also applicable to the detection of lipolysis in primary mature adipocytes. Based on general bright-field microscopy, this invention is simple and does not require the chemical reagents or isotope labeling required by existing lipolysis measurement techniques, exhibiting advantages of accuracy, quantification, and high repeatability. It can objectively and accurately provide quantitative analysis and measurement of lipolysis rates at the single lipid droplet and single-cell levels, and has broad application prospects.

Description

Technical Field

[0001] This invention belongs to the field of biotechnology, specifically relating to a method for detecting and quantifying lipid droplet degradation at the single-droplet and single-cell levels, and its application. Background Technology

[0002] Most human fat is stored in adipose tissue, with adipocytes being the primary cell type responsible for storing lipids as a reserve energy source. The stored lipids are mainly triglycerides, stored as lipid droplets within the cell. When the body needs energy during hunger or exercise, adipocytes receive signals from norepinephrine or isoproterenol, activating the degradation of triglycerides in intracellular lipid droplets into free fatty acids. This process is called lipid droplet degradation, a dynamic biological phenomenon. When free fatty acids are further degraded by β-oxidation in the mitochondria, they produce adenosine triphosphate (ATP), providing energy for cellular activities. Therefore, detecting cellular lipolysis capacity is a key indicator characterizing intracellular lipid degradation metabolism and energy production. A decline in cellular lipid degradation metabolism capacity leads to abnormal accumulation of lipids in cells, resulting in diseases such as obesity or fatty liver. Therefore, measuring cellular lipolysis capacity is an important technical requirement for assessing the risk of obesity and other metabolic diseases.

[0003] Currently, the commonly used methods for detecting intracellular triglyceride degradation mainly include biochemical assays of glycerol release and isotope labeling assays of fatty acids. The detection principle of both methods is based on the degradation reaction of triglycerides, and the lipolysis capacity of cells is quantified by measuring the amount of glycerol or free fatty acids released into the cell culture medium produced by lipolysis. However, these two lipolysis assay methods have three major technical disadvantages: (1) They require a large number of cells and require the use of biochemical reagent kits or isotope labeled substrates, which has a certain measurement cost, especially for lipolysis assays with a large number of cell samples. (2) Since a large number of cells are used, that is, lipolysis assays are performed at the population cell level, the measurement result is the average lipolysis level of a group of cells, which is not suitable for single-cell detection and analysis. (3) Lipolysis is the result of the dynamic change of lipid droplet degradation and shrinkage in living cells, but the two commonly used methods above are both measured indirectly through the products after lipolysis, which cannot show the dynamic changes of intracellular lipid droplets during lipolysis. Therefore, the biggest technical disadvantage of the two methods is the lack of visibility in measuring the lipolysis process and the intuitiveness of quantitative indicators.

[0004] To address the key technical issues of the current lack of visualization and intuitiveness in lipolysis measurement, it is necessary to establish novel devices and methods for detecting and quantitatively analyzing lipid droplet degradation using organelle dynamic imaging technology to obtain lipid droplet degradation characteristics. Summary of the Invention

[0005] The purpose of this invention is to provide a detection device and quantitative analysis method for lipid droplet degradation based on live-cell imaging technology and biophysical modeling analysis, establishing resolution at the single-droplet and single-cell levels. This invention, under the condition of activating cellular lipolysis signals, uses high-quality live-cell imaging and image analysis to obtain the dynamic changes in the size and number of intracellular lipid droplets. Then, through biophysical modeling analysis, it obtains quantitative data on the degradation rate and other characteristics of each visible lipid droplet within the cell, achieving quantitative analysis of single-droplet degradation rate and lipolytic enzyme activity efficiency, as well as quantitative analysis of lipolysis at the single-cell level. This invention is simple, accurate, highly visual, and intuitive, and has broad application prospects.

[0006] To achieve the above objectives, the first aspect of the present invention discloses a method for detecting and quantifying lipid droplet degradation at the single lipid droplet level or the single-cell level, characterized by comprising the following steps:

[0007] S1. Process the cells used for detection;

[0008] S2. High-magnification imaging was performed on the cells treated in S1 to obtain image data of lipid droplet changes;

[0009] S3. Perform image processing and analysis on the image data obtained in S2.

[0010] Preferably, the processing and analysis steps for S3 are as follows:

[0011] A1. Image processing and analysis are performed using lipid droplets as spheres. In a dataset of time-series acquired live-cell dynamic bright-field images, the diameter 'd' of each visible lipid droplet within a single cell is measured and recorded as a lipid droplet diameter curve over time. The spherical volume is then calculated. The volume of each visible lipid droplet can be recorded as a lipid droplet volume curve over time, and within a unit of time... The change in the volume of a single lipid droplet is defined as the lipolysis rate. It can be used to quantitatively characterize the rate of degradation of a single lipid droplet in an adipocyte;

[0012] A2. Calculate the lipid droplet degradation rate and lipid droplet surface area obtained in A1 as a function of time. The relationship between the two was analyzed, and a graph was plotted to record the change in lipid droplet degradation rate as a function of lipid droplet surface area. It was found that as each lipid droplet degrades and shrinks, the degradation rate decreases linearly with the reduction of the lipid droplet surface area, yielding a linear rate of change. ,definition This refers to the efficiency of lipase activity.

[0013] The above method can be used to quantitatively detect the degradation rate of lipid droplets in adipocytes.

[0014] Preferably, the cell culture method in S1 is as follows: after the cell density reaches 120% and sufficient contact inhibition is achieved, induction medium is added, and after 2 days of induction culture, it is replaced with maturation medium. On the 4th day, it is replaced with fresh maturation medium, and cultured for another 2 days. On the 6th day of differentiation, it is replaced with fractionation medium and cultured until the 8th day when it is induced to differentiate into 3T3-L1 adipocytes. The cells are cultured throughout the entire process in a 37℃, 5% CO2 incubator.

[0015] (The induction medium contains high-glucose DMEM medium, 10% fetal bovine serum, 1% penicillin / streptomycin, 5 µg / mL insulin, 0.5 mM competitive phosphodiesterase inhibitor IBMX, 1 µM dexamethasone and 1 µM rosiglitazone)

[0016] (The maturation medium contains high-glucose DMEM medium, 10% fetal bovine serum, 1% penicillin / streptomycin and 5 µg / mL insulin)

[0017] (The differentiation medium, high-glucose DMEM medium, contains high-glucose DMEM medium, 10% fetal bovine serum, and 1% penicillin / streptomycin.)

[0018] The adipocytes obtained after treatment with the above reagents have a large number of lipid droplets stored, which is helpful for subsequent high-magnification imaging of lipid droplets and obtaining more significant dynamic image data of lipid droplet changes.

[0019] Cells obtained from S1 were treated with 10 µM isoproterenol.

[0020] Preferably, the specific steps of S2 are as follows: observe the cells under a bright-field microscope using a 100x objective lens, take and record 1080*1080 pixel dynamic bright-field images of live cells with a time interval of 10 minutes and a total duration of 7 hours, and store and record the dynamic changes of lipid droplets in all cells in the field of view during the lipolysis process.

[0021] The continuous advancements in dynamic imaging and high-definition image storage technologies have enabled high-quality live-cell imaging and image analysis. This allows researchers to observe in real-time the dynamic changes in organelle structures during cellular biological functions, and further achieve high-quality dynamic quantitative analysis of structural changes and localization. This is crucial for explaining biological regulatory mechanisms such as lipid droplet degradation related to lipid storage through intuitive observation and measurement. Secondly, thanks to the rapid development of automated microscopy imaging and computer big data analysis technologies, organelle imaging and quantitative image analysis can now be achieved with high resolution, high throughput, high automation, and multi-parameter analysis capabilities.

[0022] A second aspect of this invention discloses the application of the above-described method in measuring cellular lipid degradation capacity. This application also includes the assessment of the risk of developing obesity-related metabolic diseases.

[0023] Compared to existing technologies, this invention achieves the following beneficial effects: This invention belongs to the interdisciplinary field of quantitative detection of lipid catabolism and cell image analysis and processing, specifically involving the quantitative detection of lipid droplet degradation rates in adipocytes through live cell image quantitative analysis. This invention combines microscopic imaging with biophysical modeling methods, making it particularly suitable for detecting the activity of lipases and the size of lipid droplet degradation rates in cases with a small number of cells (less than 100 cells), and also applicable to the detection of lipolysis in primary mature adipocytes. Based on general bright-field microscopy, this invention is simple and does not require the chemical reagents or isotope labeling required by existing lipolysis measurement techniques, exhibiting advantages of accuracy, quantification, and high repeatability. It can objectively and accurately provide quantitative analysis and measurement of lipolysis rates at the single lipid droplet and single-cell levels, and has broad application prospects. Attached Figure Description

[0024] Figure 1 This is a graph showing the expression detection of adipocyte-specific key proteins in the examples.

[0025] Figure 2 This is a schematic diagram of the dynamic image of lipid droplet detection in Example 1.

[0026] Figure 3 This is a graph showing the lipid droplet diameter changing over time in Example 1.

[0027] Figure 4 This is a graph showing the lipid droplet volume changing over time in Example 1.

[0028] Figure 5 This is a graph showing the change in lipid droplet degradation rate over time in Example 1.

[0029] Figure 6 This is a graph showing the change in lipid droplet degradation rate with lipid droplet surface area in Example 1, along with an explanation of the calculation of lipase activity efficiency.

[0030] Figure 7 The lipase activity efficiency of a single lipid droplet in Example 1 was statistically analyzed and plotted as a scatter plot with respect to the initial diameter of the lipid droplet.

[0031] Figure 8 The following are examples from Example 2: (A) Schematic diagram of dynamic changes in a single lipid droplet after treatment with a single cell; (B) Curve of degradation rate of a single lipid droplet over time; and (C) Scatter plot of correlation between the activity efficiency of a single lipase and the initial diameter of the lipid droplet.

[0032] Figure 9 The graphs shown in Example 2 are (A) the degradation rate of a single lipid droplet over time and (B) the degradation rate of the total lipid droplets in a single cell over time after treatment with a single cell.

[0033] Figure 10 For Example 3, after knocking down the lipase PNAPL2 in adipocytes and treating with isoproterenol (Iso), (A) is an immunoblot image of PNAPL2 protein expression, (B) is a graph showing the change in the degradation rate of a single lipid droplet over time in PNAPL2 knockdown adipocytes (shPNPLA2) or control adipocytes (shNC), and (C) is a graph showing the change in the activity efficiency of a single lipase in the two types of adipocytes.

[0034] Figure 11 For Example 3, after overexpressing lipase PNAPL2-GFP in adipocytes and treating with isoproterenol (Iso), (A) is an immunoblot image of PNAPL2-GFP protein expression, (B) is a graph showing the change in the degradation rate of a single lipid droplet (GFP) over time in adipocytes overexpressing PNAPL2-GFP or control adipocytes, and (C) is a graph showing the change in the activity efficiency of a single lipase in the two types of adipocytes.

[0035] Figure 12 For Example 3, after adipocytes were treated simultaneously with the PNAPL2 inhibitor (Atglistatin) or DMSO and isoproterenol (Iso), (A) Western blot image of the phosphorylation degree of HSL and CREB and the expression of PNAPL2-GFP protein, (B) curve of the degradation rate of single lipid droplets (DMSO) over time in adipocytes treated with the PNAPL2 inhibitor or control adipocytes, and (C) graph of the change in the activity efficiency of single lipases in the two types of adipocytes.

[0036] Figure 13 This is a graph showing the changes in lipase activity efficiency in adipocytes after the loss of ABHD5, PNPLA2, PLIN1, and GOS2 in Example 3.

[0037] Figure 14 The scatter plot and linear regression line plot for Example 3 are used to measure the lipolysis capacity of adipocytes after the loss of ABHD5, PNPLA2, PLIN1 and GOS2 using a biochemical assay of glycerol release.

[0038] Figure 15 This is a flowchart illustrating the process of obtaining in vitro differentiated brown adipocytes, white adipocytes, and 3T3-L1 adipocytes through induced differentiation in Example 4.

[0039] Figure 16This is a graph showing the difference in lipase activity efficiency among three different types of adipocytes in Example 4.

[0040] Figure 17 This is a graph showing the change in the total lipid droplet degradation rate within a single cell of three different adipocytes in Example 4 over time.

[0041] Figure 18-20 The graphs show the differences in total degradation volume, maximum total degradation rate, and reaction time at the maximum total degradation rate for the three different types of adipocytes in Example 4.

[0042] Figure 21 This is a flowchart of the lipid droplet degradation detection and quantitative analysis method of the present invention. Detailed Implementation

[0043] The present invention is further illustrated below by way of embodiments, but these embodiments are not intended to limit the invention to their scope. Unless otherwise specified, the experimental methods used in the following embodiments are conventional methods, performed according to the techniques or conditions described in the literature or according to the product instructions. Unless otherwise specified, the materials and reagents used in the following embodiments are commercially available.

[0044] Example 1

[0045] To obtain intracellular lipid droplet degradation characteristics, such as lipid droplet degradation rate and lipolytic enzyme activity efficiency, through dynamic imaging technology and modeling quantitative analysis, this invention proposes a detection device and quantitative analysis method for lipid droplet degradation characteristics at the single-droplet level. This method consists of two main parts: live-cell imaging and biophysical modeling analysis, and includes the following steps:

[0046] (1) Live-cell imaging 1 - Cell preparation module: When the 3T3-L1 precursor adipocytes reached a cell density of 120% and sufficient contact inhibition was achieved, induction medium (high glucose DMEM medium containing 10% fetal bovine serum, 1% penicillin / streptomycin, 5 µg / mL insulin, 0.5 mM competitive phosphodiesterase inhibitor IBMX, 1 µM dexamethasone, and 1 µM rosiglitazone) was added and marked as day 0. After 2 days of induction culture, the medium was changed to maturation medium (high glucose DMEM medium containing 10% fetal bovine serum, 1% penicillin / streptomycin, and 5 µg / mL insulin). On day 4, the medium was changed to fresh maturation medium and cultured for another 2 days. On day 6 of differentiation, the medium was changed to fractionation medium (high glucose DMEM medium containing 10% fetal bovine serum and 1% penicillin / streptomycin) and cultured until day 8 when the cells were induced to differentiate into 3T3-L1 adipocytes. The cells were cultured at 37°C in a 5% CO2 incubator throughout the entire process.

[0047] Western blotting was used to detect the degree of adipocyte differentiation, with a focus on observing the upregulation of expression of several key adipocyte-specific proteins (such as...). Figure 1 Such proteins include peroxisome proliferators-activated receptors (PPARγ), perilipin-1 (PLIN1), cell death-inducing DNA fragmentation factor alpha-like effector-C (CIDEC), and lipolysis-related proteins such as those containing the Patatin-like phospholipase domain-2 (PNPLA2) and the Abhydrolase domain-5 (ABHD5).

[0048] (2) Live-cell imaging 2 - Lipid droplet dynamic imaging module: Adipocytes were treated with 10 µM isoproterenol to activate the cAMP-PKA lipolysis signaling pathway. Then, live-cell culture was performed under a bright-field microscope with a 100x objective lens. Live-cell dynamic bright-field images of 1080*1080 pixels were captured and recorded in 10-minute intervals for a total duration of 7 hours. The dynamic changes of lipid droplets in all adipocytes within the field of view during lipolysis were stored. Under these conditions, a set of dynamic imaging results can be stored as 43 frames of live-cell dynamic bright-field images.

[0049] (3) Live Cell Imaging 3 - Lipid Droplet Image Processing and Analysis Module: After the image is captured, it can be clearly observed from the live cell lipolysis dynamic image that lipolysis activation causes all visible lipid droplets in the cell to gradually shrink until they disappear (e.g. Figure 2 Image processing and analysis were performed using lipid droplets as spheres. The diameter 'd' of each visible lipid droplet within a single cell was measured from a dataset of time-series acquired live-cell dynamic bright-field images, and the results were recorded as a lipid droplet diameter curve over time (e.g., ...). Figure 3 The volume of a sphere is calculated as follows: The volume of each visible lipid droplet can be recorded as a lipid droplet volume curve over time (e.g., ...). Figure 4 );

[0050] (4) Biophysical modeling analysis 1 - Lipid droplet degradation rate calculation module: Record the lipid droplet volume obtained in step (3) as a function of time, and calculate the lipid droplet degradation rate per unit time. The change in the volume of a single lipid droplet is defined as the lipolysis rate. This can be used to quantify the rate of degradation of a single lipid droplet in an adipocyte, and further, to record a curve of the lipid droplet degradation rate over time (e.g., Figure 5 ), its lipolysis rate It also changes dynamically over time;

[0051] (5) Biophysical modeling analysis 2-Lipoase activity efficiency calculation module: calculate the lipid droplet degradation rate and lipid droplet surface area obtained in step (4) as a function of time. The relationship between the lipid droplet degradation rate and its surface area is plotted and recorded (e.g., ...). Figure 6 It can be observed that during the degradation and shrinkage of each lipid droplet, the degradation rate decreases linearly with the reduction of the droplet surface area, and the linear change rate can be obtained. We define The efficiency of lipase activity;

[0052] (6) Biophysical modeling analysis 3-Lipolysis enzyme activity efficiency characteristic analysis module: The lipolysis enzyme activity efficiency of the single lipid droplet obtained in step (5) is statistically analyzed with its initial diameter and plotted as a scatter plot (e.g. Figure 7 It can be found that the activity efficiency of lipase is not correlated with the initial diameter of lipid droplets.

[0053] Example 2

[0054] To quantitatively analyze the degradation characteristics of all visible lipid droplets within a single cell, this invention proposes a detection device and quantitative analysis method for lipid droplet degradation at the single-cell level. This method can obtain quantitative lipolysis indicators such as the lipase activity efficiency of all visible degrading lipid droplets within a single cell and the total lipid droplet degradation rate. Specifically, it includes the following steps:

[0055] (1) The cAMP-PKA lipolysis signal of adipocytes was activated by treatment with 10 µM isoproterenol. Then, the adipocytes were observed under a bright-field microscope with a 100x objective lens in live cell culture. Dynamic bright-field images of live cells were captured at 10-minute intervals for a total duration of 7 hours, recording the dynamic changes of lipid droplets in adipocytes. One set of dynamic imaging consisted of 43 frames of dynamic bright-field images of live cells.

[0056] (2) Using lipid droplets as spheres, perform image processing and analysis on all visible lipid droplets within each single cell (e.g.) Figure 8 At point A in the middle, following steps (4) and (5) in Example 1, the lipid droplet degradation rate of each lipid droplet within a single cell can be obtained. These lipid droplet degradation rates also decrease linearly with the reduction of lipid droplet surface area (e.g., ...). Figure 8 (at point B in the middle), further analysis revealed that the lipase activity efficiency of each lipid droplet degrading within a single cell was similar (e.g., Figure 8 (Center C)

[0057] (3) In order to obtain the total lipid droplet degradation rate in a single cell, calculate the curve of the degradation rate of each lipid droplet in a single cell over time according to step (2) (e.g.) Figure 9 (At point A in the middle), by summing the data, a curve showing the change in the total lipid droplet degradation rate in a single cell over time can be obtained (e.g., ...). Figure 9 At point B in the middle, the total lipid droplet degradation rate also changes dynamically over time;

[0058] (4) By summing up the areas under the curves of the total lipid droplet degradation rate in a single cell obtained in step (3) over time, the total change in lipid droplet volume in the cell during this measurement period can be calculated. (like Figure 9 (at point B in the middle), the total change in the volume of this lipid droplet is taken as the total volume of the degraded lipid droplets in this cell;

[0059] (5) Measure the maximum total lipid droplet degradation rate (e.g., in step (3)) from the curve of the total lipid droplet degradation rate dynamically changing over time. Figure 9 (at point B), and define this rate as The time at which the cell reaches its maximum total lipid droplet degradation rate can be obtained and defined as... The speed of this time can be considered as the response time of a single cell to the maximum lipolysis effect after activation of the cAMP-PKA lipolysis signal; the shorter the time, the faster the response of the lipolysis effect.

[0060] Example 3

[0061] A quantitative detection method for lipid droplet degradation rate and lipase activity efficiency based on single-droplet level analysis can be used to detect specific gene expression knockdown (e.g., Pnpla2 , Abhd5 , Plin1 and G0s2 The evaluation of the regulatory effects of gene knockdown, overexpression (e.g., PNPLA2-GFP overexpression), or lipase activity inhibition treatment (e.g., PNPLA2 protease inhibitor, Atglistatin) on quantitative lipolysis indicators such as lipid droplet degradation rate and lipase activity efficiency in adipocytes includes the following steps:

[0062] (1) Knockdown of PNPLA2, a key protein in adipocyte lipolysis (shPNPLA2), and treatment of control cells with an RNA silencing intervention sequence that does not target any gene (shNC), followed by treatment of these PNPLA2-deficient and control adipocytes with 10 µM isoproterenol, can activate lipolysis signals in these cells, such as p-HSL and p-CREB (e.g., Figure 10 (at point A in the middle)

[0063] (2) Under a bright-field microscope, observe the cells with a 100x objective lens and record dynamic bright-field images of 1080*1080 pixels of live cells in 10-minute intervals for a total duration of 7 hours. Record the dynamic changes of lipid droplets in adipocytes.

[0064] (3) The live cell dynamic bright-field image obtained in step (2) is processed and analyzed for lipid droplet images. According to steps (4) and (5) in Example 1, the lipid droplet degradation rate of single lipid droplets in PNPLA2-deficient and control adipocytes can be obtained as a function of lipid droplet surface area (e.g. Figure 10 (At point B in the middle). The comparison results showed that PNPLA2 deficiency significantly reduced the lipid droplet degradation rate;

[0065] (4) Based on the linear relationship between lipid droplet degradation rate and lipid droplet surface area obtained in step (3), the lipase activity efficiency in PNPLA2-deficient and control adipocytes can be calculated (e.g., Figure 10 (At position C). The comparison results showed that PNPLA2 deficiency significantly reduced the efficiency of lipase activity;

[0066] (5) Overexpression of the key lipolysis protein PNPLA2 (PNPLA2-GFP) in adipocytes, while the control group overexpressed GFP in adipocytes (e.g., Figure 11 (at point A in the middle), and further treated these adipocytes that overexpressed PNPLA2-GFP and the GFP control with 10 µM isoproterenol;

[0067] (6) Under a bright-field microscope, observe the cells with a 100x objective lens and record dynamic bright-field images of 1080*1080 pixels of live cells in 10-minute intervals for a total duration of 7 hours. Record the dynamic changes of lipid droplets in adipocytes.

[0068] (7) The live cell dynamic bright-field image obtained in step (6) is processed and analyzed for lipid droplet images. According to steps (4) and (5) in Example 1, the lipid droplet degradation rate of a single lipid droplet in PNPLA2 overexpression and GFP control adipocytes as a function of lipid droplet surface area can be obtained (e.g., Figure 11 (At point B in the middle). The comparison results showed that PNPLA2 overexpression significantly increased the lipid droplet degradation rate;

[0069] (8) Based on the linear relationship between lipid droplet degradation rate and lipid droplet surface area obtained in step (7), the lipase activity efficiency in adipocytes overexpressing PNPLA2 and those controlling GFP can be calculated (e.g., Figure 11 (At position C). The comparison results showed that PNPLA2 overexpression significantly increased the efficiency of lipase activity;

[0070] (9) Treatment of adipocytes with an inhibitor of the lipolysis key protein PNPLA2 (Atglistatin), while control adipocytes were treated with 1% DMSO (the equivalent DMSO concentration used in the Atglistatin formulation), followed by further treatment of these PNPLA2-inhibited and DMSO-treated adipocytes with 10 µM isoproterenol, activated lipolysis signals in these cells, such as p-HSL and p-CREB (e.g., ...). Figure 12 (at point A in the middle)

[0071] (10) Under a bright-field microscope, observe the cells using a 100x objective lens and record dynamic bright-field images of 1080*1080 pixels of live cells in 10-minute intervals for a total duration of 7 hours. Record the dynamic changes of lipid droplets in adipocytes.

[0072] (11) The live cell dynamic bright-field image obtained in step (10) is processed and analyzed for lipid droplet image, and according to steps (4) and (5) in Example 1, a curve of the lipid droplet degradation rate of a single lipid droplet in the control adipocytes of PNPLA2 activity inhibition and DMSO treatment as a function of the lipid droplet surface area can be obtained (e.g. Figure 12 (At point B in the middle). The comparison results showed that the inhibition of PNPLA2 activity significantly reduced the lipid droplet degradation rate;

[0073] (12) Based on the linear relationship between lipid droplet degradation rate and lipid droplet surface area obtained in step (11), the lipase activity efficiency in PNPLA2 activity inhibition and DMSO-treated control adipocytes can be calculated (e.g., Figure 12 (At position C). The comparison results showed that inhibition of PNPLA2 activity significantly reduced the efficiency of lipase activity;

[0074] (13) The expression of lipolysis regulatory proteins ABHD5, PNPLA2, PLIN1 and G0S2 in adipocytes was knocked down (in order such as shABHD5, shPNPLA3, shPLIN1, shG0S2, etc.), while the control group was treated with RNA silencing intervention sequence that did not target any gene (shNC), and further treated with 10 µM isoproterenol in adipocytes lacking these lipolysis regulatory proteins and control cells.

[0075] (14) Under a bright-field microscope, observe the cells with a 100x objective lens and record dynamic bright-field images of 1080*1080 pixels of live cells in 10-minute intervals for a total duration of 7 hours. Record the dynamic changes of lipid droplets in adipocytes.

[0076] (15) The live cell dynamic bright-field image obtained in step (14) is processed and analyzed for lipid droplet images, and the lipase activity efficiency in ABHD5, PLIN1 and G0S2 deficient and control adipocytes can be calculated according to steps (4) and (5) in Example 1 (e.g. Figure 13 The comparison results showed that the deletion of ABHD5 and PLIN1 both significantly reduced the lipase activity efficiency, with the deletion of ABHD5 resulting in a lower reduction in lipase activity efficiency; in contrast, the deletion of G0S2 significantly increased the lipase activity efficiency.

[0077] (16) To verify the lipase activity efficiency results obtained in step (15), a biochemical assay for glycerol release (Free Glycerol Assay Kit, catalog number F6428, Sigma-Aldrich) was simultaneously used to determine the lipolysis capacity of adipocytes lacking PLPNAL2, ABHD5, PLIN1, and GOS2, and control adipocytes. The results showed that the method of the present invention had good similarity to the biochemical assay (correlation coefficient R). 2 = 0.79, such as Figure 14 ).

[0078] Example 4

[0079] A quantitative detection method for lipid droplet degradation characteristics at the single-cell level can be used to differentiate the differences in lipase activity and total lipid droplet degradation rate among 3T3-L1 adipocytes, white adipocytes, and brown adipocytes. The method specifically includes the following steps:

[0080] (1) Matrix vascular component cells were obtained from brown adipose tissue of mice, and brown adipocytes were obtained through induction and differentiation; matrix vascular component cells were obtained from white adipose tissue of mice, and white adipocytes were obtained through induction and differentiation; 3T3-L1 precursor adipocytes were induced and differentiated to obtain 3T3-L1 adipocytes (e.g. Figure 15 Induction and differentiation can be achieved according to step (1) in Example 1. Cells are cultured at 37°C in a 5% CO2 incubator throughout the entire process;

[0081] (2) Treat these three types of adipocytes with 10 µM isoproterenol and observe them under a live cell bright field microscope with a 100x objective magnification. Record 1080*1080 pixel live cell dynamic bright field images with 10-minute intervals and a total duration of 7 hours to record the dynamic changes of lipid droplets in adipocytes.

[0082] (3) The live cell dynamic bright-field image obtained in step (2) is processed and analyzed for lipid droplet images, and the lipase activity efficiency in 3T3-L1 adipocytes, white adipocytes and brown adipocytes can be calculated according to steps (4) and (5) in Example 1 (e.g. Figure 16 The comparison results showed that after treatment with 10 µM isoproterenol, the lipase activity efficiency in 3T3-L1 adipocytes and brown adipocytes was comparable, while the lipase activity efficiency in white adipocytes was relatively low.

[0083] (4) To obtain the total lipid droplet degradation rate within a single cell, the total lipid droplet degradation rate within a single cell can be obtained by summing the curves of the degradation rate of each lipid droplet within the single cell over time (e.g., ...). Figure 17 The comparison results showed that the characteristics of the total lipid droplet degradation rate over time were quite different among the three types of adipocytes, with white adipocytes exhibiting both a relatively high total lipid droplet degradation rate and a relatively high lipolysis response time.

[0084] (5) In order to calculate the total volume of degraded lipid droplets in a single cell during this measurement time. The areas under the curves of the total lipid droplet degradation rate in a single cell obtained in step (4) over time were statistically summed. The comparison results showed that white adipocytes had the largest total volume of degraded lipid droplets, followed by brown adipocytes, while 3T3-L1 adipocytes had the smallest (e.g., ...). Figure 18 );

[0085] (6) The maximum total lipid droplet degradation rate was calculated and analyzed in step (4). (like Figure 19 and the response time of the maximum lipolysis effect. (like Figure 20 The comparison results showed that white adipocytes and The rate was the largest among all three cell types, indicating that white adipocytes had the highest lipolysis rate and the slowest response time under 10 µM isoproterenol treatment.

[0086] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for detecting and quantifying lipid droplet degradation at the single-droplet or single-cell level, characterized in that, Includes the following steps: S1. Process the cells used for detection; S2. High-magnification imaging was performed on the cells treated in S1 to obtain image data of lipid droplet changes; S3. Perform image processing and analysis on the image data obtained in S2; The specific steps for processing and analysis in S3 are as follows: A1. Using lipid droplets as spheres for image processing and analysis, in a dataset of time-series acquired live cell dynamic bright-field images, the diameter d of each visible lipid droplet in a single cell is measured and recorded as a lipid droplet diameter curve over time. The spherical volume is calculated as V = 4π / 3 × (d / 2). 3 The volume of each visible lipid droplet was recorded as a lipid droplet volume curve over time, and the change in the volume of a single lipid droplet per unit time Δt was defined as the lipolysis rate. A2. Calculate the lipid droplet degradation rate and lipid droplet surface area obtained in A1 as a function of time. The relationship between the lipid droplet degradation rate and its surface area was determined, and a curve was plotted to record the linear change rate κ=dφ / dA| A→0 =φ i+1 -φ i / A i+1 -A i κ represents the lipase activity efficiency.

2. The method for detecting and quantifying lipid droplet degradation at the single lipid droplet level or single cell level according to claim 1, characterized in that, The cells described in S1 include mature cells obtained through normal induced differentiation, or cells cultured by the following methods: After the undifferentiated cells reached a cell density of 120% and were fully exposed to inhibition, induction medium was added. After 2 days of induction culture, the medium was replaced with maturation medium. On the 4th day, the medium was replaced with fresh maturation medium and cultured for another 2 days. On the 6th day of differentiation, the medium was replaced with fractionation medium and cultured until the 8th day when the cells were induced to differentiate into adipocytes. The cells were cultured at 37°C in a 5% CO2 incubator throughout the entire process.

3. The method for detecting and quantifying lipid droplet degradation at the single lipid droplet level or single cell level according to claim 2, characterized in that, The induction medium contains high-glucose DMEM medium, 10% fetal bovine serum, 1% penicillin / streptomycin, 5 μg / mL insulin, 0.5 mM competitive phosphodiesterase inhibitor IBMX, 1 μM dexamethasone and 1 μM rosiglitazone.

4. The method for detecting and quantifying lipid droplet degradation at the single lipid droplet level or single cell level according to claim 2, characterized in that, The maturation culture medium contains high-glucose DMEM medium, 10% fetal bovine serum, 1% penicillin / streptomycin and 5 μg / mL insulin.

5. The method for detecting and quantifying lipid droplet degradation at the single-droplet or single-cell level according to claim 2, characterized in that, The differentiation medium, high-glucose DMEM medium, contains high-glucose DMEM medium, 10% fetal bovine serum, and 1% penicillin / streptomycin.

6. The method for detecting and quantifying lipid droplet degradation at the single-droplet or single-cell level according to claim 1, characterized in that, The cells treated in S2 are cells obtained by treating with 10 μM isoproterenol.

7. The method for detecting and quantifying lipid droplet degradation at the single-droplet or single-cell level according to claim 1, characterized in that, The specific steps for high-magnification imaging in S2 are as follows: observe cells under a bright-field microscope using a high-magnification objective lens, record 1080×1080 pixel dynamic bright-field images of live cells with a time interval of 10 minutes and a total duration of 7 hours, and store and record the dynamic changes of lipid droplets in all cells within the field of view during the lipolysis process.

8. The application of the method according to any one of claims 1-7 in determining the ability of cells to degrade lipids.

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