Lipid droplet degradation detection and quantitative analysis method for analyzing single lipid droplet level and single cell level

Abstract

The invention belongs to the field of interdisciplinary application of lipid catabolism quantitative detection and cell image analysis processing, and particularly relates to quantitative detection of lipid droplet degradation rate in fat cells by means of living cell image quantitative analysis. According to the present invention, with the combination of the microscope imaging and the biophysical modeling method, the method is particularly suitable for the detection of the lipolytic enzyme activity degree and the lipid droplet degradation rate under the condition of the trace cell number (the cell number is less than 100), and is also suitable for the lipolytic detection of the primary mature fat cells. The method is based on general microscope bright field imaging, is simple, does not need chemical reagents or isotope labels required by the existing lipolysis measurement technology, shows the detection advantages of accuracy, quantification and high repeatability, can objectively and accurately provide quantitative analysis measurement of the lipolysis rate of analysis of the single lipid droplet level and the single cell level, and has a good application prospect. Wide application prospects are realized.

Description

Technical Field

[0001] The present invention belongs to the field of biotechnology, and specifically relates to a lipid droplet degradation detection and quantitative analysis method analyzed at the single lipid droplet level and single cell level, and an application thereof. Background Art

[0002] Most of the body fat is stored in adipose tissue, among which adipocytes are the main cell type responsible for storing lipids as backup energy storage, and the stored lipids are mainly triglycerides stored in fat droplets in cells. When the human body needs to replenish energy during hunger or exercise, adipocytes receive signals such as norepinephrine or isoproterenol and activate the degradation of triglycerides in intracellular fat droplets into free fatty acids. This process is called lipid droplet degradation, which is a dynamic biological function phenomenon. When free fatty acids are further degraded by β-oxidation in mitochondria, adenosine triphosphate (ATP) energy can be generated for cell activities, so detecting the lipolysis ability of cells is a key indicator to characterize lipid degradation metabolism and energy production in cells. When the lipid degradation metabolic capacity of cells decreases, it will lead to abnormal accumulation of lipids stored in cells, which will lead to the occurrence of diseases such as obesity or fatty liver. Therefore, measuring the lipolysis ability of cells is an important detection technology requirement for assessing the risk of metabolic diseases such as obesity.

[0003] At present, the commonly used methods for detecting intracellular triglyceride degradation mainly include biochemical determination of glycerol release and isotope labeling determination of fatty acids. The detection principles of these two methods are based on the degradation reaction of triglycerides. 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 determination methods have three major technical disadvantages: (1) The required number of cells is large, and biochemical kits or isotope labeled substrates are required, which has a certain measurement cost. In particular, they are not suitable for lipolysis determination when the number of cell samples is too large. (2) Since a large number of cells are used, that is, lipolysis determination is performed at the level of a group of cells, 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 dynamic change result of the degradation and shrinkage of lipid droplets in living cells. However, the above two commonly used methods are indirect determinations 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 of the lipolysis process and the intuitiveness of the quantitative indicators.

[0004] In order to solve the key technical problems of the above-mentioned technologies, such as the lack of visibility and intuitiveness of lipolysis measurement, it is necessary to establish a new lipid droplet degradation detection and quantitative analysis device and method through organelle dynamic imaging technology to obtain lipid droplet degradation characteristics. Summary of the invention

[0005] The object of the present 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, which establishes a single lipid droplet level and single cell level analysis. In the case of activating cell lipolysis signals, the present invention uses high-quality live cell imaging and image analysis to obtain the dynamic changes in the size and number of intracellular lipid droplets, and then obtains quantitative data of characteristics such as the degradation rate of each visible lipid droplet in the cell through biophysical modeling analysis, thereby achieving quantitative analysis of the degradation rate of a single lipid droplet and the efficiency of lipolytic enzyme activity, as well as quantitative analysis of lipolysis at the single cell level. The present invention is simple, accurate, highly visible and intuitive, and has broad application prospects.

[0006] In order to achieve the above-mentioned object, the first aspect of the present invention discloses a method for detecting and quantitatively analyzing lipid droplet degradation at a single lipid droplet level or a single cell level, characterized in that it comprises the following steps: S1. Processing cells for detection; S2, taking high-magnification images of the cells treated with S1 to obtain image data of lipid droplet changes; S3. Perform image processing and analysis on the image data obtained in S2.

[0007] Preferably, the processing and analysis steps of S3 are as follows: A1. Image processing and analysis were performed with lipid droplets as spheres. The diameter of each visible lipid droplet in a single cell was measured as d in a set of live cell dynamic bright field image data collected in time series and recorded as a lipid droplet diameter curve that changes with time. The spherical volume was calculated as The volume of each visible lipid droplet can be recorded as a lipid droplet volume curve over time, and the ... The lipolysis rate is defined as ; It can be used to quantitatively characterize the degradation rate of a single lipid droplet in adipocytes; A2. Calculate the time-varying lipid droplet degradation rate and lipid droplet surface area obtained in A1 The relationship between the degradation rate of lipid droplets and the surface area of ​​lipid droplets was plotted and recorded. It can be found that when each lipid droplet is degraded and reduced, the degradation rate of lipid droplets decreases linearly with the reduction of lipid droplet surface area, and the linear change rate is ,definition It is the efficiency of lipolytic enzyme activity.

[0008] The above method can be used to quantitatively detect the degradation rate of lipid droplets in adipocytes.

[0009] Preferably, the cell culture method in S1 is as follows: after the cell culture cell density reaches 120% for full contact inhibition, an induction medium is added, and after 2 days of induction culture, the medium is replaced with a maturation medium, and on the 4th day, the medium is replaced with a fresh maturation medium, and the culture is continued for 2 days. On the 6th day of differentiation, the differentiation medium is replaced and the culture is continued until the 8th day when the differentiation into 3T3-L1 adipocytes is induced. The cells are cultured in a 37°C, 5% carbon dioxide incubator throughout the process.

[0010] (The induction medium contains high-glucose DMEM, 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) (Maturation medium contains high glucose DMEM, 10% fetal bovine serum, 1% penicillin / streptomycin, and 5 µg / mL insulin) (Differentiation medium high glucose DMEM medium contains high glucose DMEM medium, 10% fetal bovine serum and 1% penicillin / streptomycin).

[0011] The fat cells obtained after treatment with the above reagents have larger and more stored lipid droplets, which is helpful for subsequent high-magnification imaging of lipid droplets and obtaining more significant dynamic image data of lipid droplets.

[0012] The cells obtained by treating S1 with 10 µM isoproterenol were Preferably, the specific steps of S2 are: observing the cells under a bright field microscope using a 100x objective lens magnification, capturing and recording 1080*1080 pixel dynamic bright field images of living cells with a time interval of 10 minutes and a total duration of 7 hours, and storing and recording the dynamic changes of lipid droplets in all cells in the field of view during lipolysis.

[0013] The continuous improvement of dynamic imaging technology and high-definition image storage technology has achieved high-quality live cell imaging and image analysis, allowing researchers to observe the dynamic changes in the internal organelle structure during the biological function of the cell in real time, and further achieve high-quality dynamic quantitative analysis of structural changes and positioning, which 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 technologies such as automated imaging of microscopes and computer big data analysis, the characteristics of organelle imaging and image quantitative analysis such as high resolution, high throughput, high automation, and multi-parameter analysis can now be achieved.

[0014] The second aspect of the present invention discloses the application of the above method in measuring the cell fat degradation ability, and the application also includes the assessment of the risk of obesity metabolic diseases.

[0015] Compared with the prior art, the present invention achieves the following beneficial effects: The present invention belongs to the interdisciplinary application field of quantitative detection of lipid catabolism and cell image analysis and processing, and specifically relates to quantitative detection of lipid droplet degradation rate in adipocytes by means of quantitative analysis of living cell images. The present invention combines microscopic imaging with biophysical modeling methods, and is particularly suitable for detecting the activity of lipolytic enzymes and the size of lipid droplet degradation rate in the case of trace cell numbers (the number of cells is less than 100), and is also suitable for lipolysis detection of primary mature adipocytes. The present invention is based on general microscope bright field imaging, and does not require chemical reagents or isotope labels required by existing lipolysis measurement technology. It exhibits the advantages of accurate, quantitative, and highly repeatable detection, and can objectively and accurately provide quantitative analysis and measurement of lipolysis rate at the level of single lipid droplets and single cell levels, and has broad application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a diagram for detecting the expression of adipocyte-specific key proteins in the examples.

[0017] Figure 2 This is a schematic diagram of the dynamic image of lipid droplet detection in Example 1.

[0018] Figure 3 This is a curve diagram of the lipid droplet diameter changing with time in Example 1.

[0019] Figure 4 This is a curve diagram of the lipid droplet volume changing with time in Example 1.

[0020] Figure 5 This is a curve chart showing the change of lipid droplet degradation rate over time in Example 1.

[0021] Figure 6 The figure is a curve diagram showing the variation of lipid droplet degradation rate with lipid droplet surface area and the calculation of lipolytic enzyme activity efficiency in Example 1.

[0022] Figure 7 The lipolytic enzyme activity efficiency of a single lipid droplet in Example 1 and the initial diameter of the lipid droplet are statistically analyzed and plotted as a scatter plot.

[0023] Figure 8 (A) Schematic diagram of the dynamic image changes of a single lipid droplet after the single cell is treated in Example 2, (B) a curve diagram of the degradation rate of a single lipid droplet changing with time, and (C) a scatter plot correlation diagram of the activity efficiency of a single lipolytic enzyme and the initial diameter size of its lipid droplet.

[0024] Fig. 9 Graph showing (A) the degradation rate of a single lipid droplet changing over time after treating a single cell in Example 2, and (B) the degradation rate of the total lipid droplets in a single cell changing over time.

[0025] Fig.10 In Example 3, after knocking down the lipase PNAPL2 in adipocytes and treating with isoproterenol Iso, (A) immunoblot image of PNAPL2 protein expression, (B) curve graph of the change of single lipid droplet degradation rate over time in PNAPL2 knockdown adipocytes (shPNPLA2) or control adipocytes (shNC), and (C) graph of the change of single lipolytic enzyme activity efficiency in two adipocytes.

[0026] Fig.11 In Example 3, after overexpression of lipase PNAPL2-GFP in adipocytes and treatment with isoproterenol Iso, (A) immunoblot expression of PNAPL2-GFP protein, (B) curve chart of the change of single lipid droplet degradation rate over time in adipocytes overexpressing PNAPL2-GFP (PNAPL2-GFP) or control adipocytes (GFP), and (C) graph of the change of single lipolytic enzyme activity efficiency in the two adipocytes.

[0027] Fig.12 In Example 3, after adipocytes were treated with PNAPL2 inhibitor (Atglistatin) or DMSO and isoproterenol (Iso) at the same time, (A) immunoblot of HSL and CREB phosphorylation levels and PNAPL2-GFP protein expression, (B) curve chart of the change of single lipid droplet degradation rate over time in adipocytes treated with PNAPL2 inhibitor or control adipocytes (DMSO), and (C) graph of the change of single lipolytic enzyme activity efficiency in the two adipocytes.

[0028] Fig.13 This is a graph showing the changes in lipolytic enzyme activity efficiency in adipocytes after the loss of ABHD5, PNPLA2, PLIN1 and G0S2 in Example 3.

[0029] Fig.14 The scatter plot and linear regression fitting straight line graph of Example 3 are the lipolysis capacity in adipocytes after the loss of ABHD5, PNPLA2, PLIN1 and G0S2 measured by the biochemical assay of glycerol release.

[0030] Fig.15 This is a flow chart of the induction of differentiation in Example 4 to obtain in vitro differentiated brown adipocytes, white adipocytes and 3T3-L1 adipocytes.

[0031] Fig.16 This is a graph showing the differences in lipolytic enzyme activity efficiency among three different adipocytes in Example 4.

[0032] Fig.17 This is a curve chart showing the degradation rate of total lipid droplets in a single cell of three different adipocytes in Example 4 changing with time.

[0033] Figure 18-20 Graphs showing the difference in total degradation volume, the difference in maximum total degradation rate, and the difference in reaction time at the maximum total degradation rate of three different fat cells in Example 4.

[0034] Fig.21 The figure is a flow chart of the lipid droplet degradation detection and quantitative analysis method of the present invention. DETAILED DESCRIPTION

[0035] The present invention is further described below by way of examples, but the present invention is not limited to the scope of the examples. The experimental methods in the following examples, unless otherwise specified, are conventional methods, and are performed according to the techniques or conditions described in the literature in the art or according to the product instructions. The materials, reagents, etc. used in the following examples, unless otherwise specified, can all be obtained from commercial sources.

[0036] Example 1 In order to obtain the intracellular lipid droplet degradation characteristics through dynamic imaging technology and modeling quantitative analysis, such as lipid droplet degradation rate and lipolytic enzyme activity efficiency and other lipolysis quantitative indicators, the present invention proposes a detection device and quantitative analysis method for lipid droplet degradation characteristics analyzed at the level of a single lipid droplet, which is composed of two parts: living cell imaging and biophysical modeling analysis, and includes the following steps: (1) Live cell imaging 1-Cell preparation module: When 3T3-L1 preadipocytes were cultured to a cell density of 120% and fully contact-inhibited, 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 the 4th day, the medium was changed to fresh maturation medium and cultured for another 2 days. On the 6th day of differentiation, the medium was changed to differentiation medium (high-glucose DMEM medium containing 10% fetal bovine serum and 1% penicillin / streptomycin) and cultured until the 8th day when the cells were induced to differentiate into 3T3-L1 adipocytes. The cells were cultured in a 37°C, 5% carbon dioxide incubator throughout the process.

[0037] Western blotting was used to detect the degree of adipocyte differentiation, focusing on the upregulation of several adipocyte-specific key proteins (e.g. Figure 1), such as peroxisome proliferators-activated receptors-γ (PPARγ), perilipin-1 (PLIN1), cell death-inducing DNA fragmentation factor alpha-like effector-C (CIDEC), and lipolysis-related proteins such as Patatin-like phospholipase domain containing-2 (PNPLA2) and abhydrolase domain containing-5 (ABHD5); (2) Live cell imaging 2-lipid droplet dynamic imaging module: Use 10 µM isoproterenol to treat adipocytes to activate the cAMP-PKA lipolysis signaling pathway, then observe under a live cell culture with a bright field microscope using a 100x objective magnification, take and record 1080*1080 pixel live cell dynamic bright field images 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 adipocytes in the field of view during lipolysis. According to the above conditions, a set of dynamic imaging results can be stored as 43 frames of live cell dynamic bright field images; (3) Live Cell Imaging 3-Lipid Droplet Image Processing and Analysis Module: After the shooting is completed, it can be clearly observed from the dynamic images of live cell lipolysis that lipolysis activation causes all visible lipid droplets in the cell to gradually become smaller until they disappear (e.g. Figure 2 ). Image processing and analysis were performed with lipid droplets as spheres. The diameter of each visible lipid droplet in a single cell was measured as d in a set of live cell dynamic bright field image data collected in time series and recorded as a lipid droplet diameter curve graph that changes with time (e.g. Figure 3 ), after calculating the spherical volume, , the volume of each visible lipid droplet can be recorded as a lipid droplet volume curve over time (e.g. Figure 4 ); (4) Biophysical modeling analysis 1-Lipid droplet degradation rate calculation module: record the lipid droplet volume obtained in step (3) over time and calculate it per unit time The lipolysis rate is defined as , which can be used to quantitatively characterize the degradation rate of a single lipid droplet in adipocytes, and further record the curve of the lipid droplet degradation rate over time (such as Figure 5 ), its lipolysis rate It also changes dynamically over time; (5) Biophysical modeling analysis 2-lipolytic enzyme activity efficiency calculation module: calculate the time-varying lipid droplet degradation rate and lipid droplet surface area obtained in step (4) and plot the relationship between the lipid droplet degradation rate and the lipid droplet surface area (e.g. Figure 6 ), it can be found that when each lipid droplet is degraded and reduced, the degradation rate of lipid droplets decreases linearly with the reduction of lipid droplet surface area, and the linear change rate can be obtained. , we define is the lipolytic enzyme activity efficiency; (6) Biophysical modeling analysis 3-Lipolytic enzyme activity efficiency characteristic analysis module: The lipolytic enzyme activity efficiency of a single lipid droplet obtained in step (5) and the initial diameter of the lipid droplet are statistically analyzed and plotted into a scatter plot (e.g. Figure 7 ), it can be found that the efficiency of lipolytic enzyme activity has no correlation with the initial diameter of lipid droplets.

[0038] Example 2 In order to quantitatively analyze and obtain the degradation characteristics of all visible lipid droplets in a single cell, the present invention proposes a detection device and quantitative analysis method for lipid droplet degradation characteristics analyzed at the single cell level, which can obtain quantitative indicators of lipolysis, such as the lipolytic enzyme activity efficiency and total lipid droplet degradation rate of all visible degraded lipid droplets in a single cell. Specifically, the following steps are included: (1) 10 µM isoproterenol was used to activate the cAMP-PKA lipolysis signal of adipocytes, and then the cells were cultured in living cells and observed under a bright field microscope with a 100x objective magnification. 1080*1080 pixel live cell dynamic bright field images were recorded at 10-minute intervals and a total duration of 7 hours to record the dynamic changes of lipid droplets in adipocytes. A set of live cell dynamic bright field images with 43 frames of dynamic imaging; (2) Using lipid droplets as spheres, image processing and analysis of all visible lipid droplets in each single cell (e.g. Figure 8 At A in the middle), according to steps (4) and (5) in Example 1, the lipid droplet degradation rate of each lipid droplet in a single cell can be obtained. These lipid droplet degradation rates also decrease linearly with the decrease of lipid droplet surface area (such as Figure 8 Further analysis revealed that the efficiency of lipolytic enzyme activity in each degraded lipid droplet within a single cell was similar (Fig. Figure 8 (C in the middle); (3) In order to obtain the total lipid droplet degradation rate in a single cell, the degradation rate of each lipid droplet in a single cell is calculated according to step (2) to obtain a curve of the change in degradation rate over time (e.g. Fig. 9A in the middle), by summing up, we can obtain a curve graph of the total lipid droplet degradation rate in a single cell over time (such as Fig. 9 (B in the middle), the degradation rate of total lipid droplets also changes dynamically over time; (4) The total change in the lipid droplet volume of the cell during this measurement time can be calculated by summing up the area under the curve of the total lipid droplet degradation rate over time in a single cell obtained in step (3). (like Fig. 9 (B in the middle), the total change in the volume of the lipid droplets is taken as the total volume of the degraded lipid droplets of this cell; (5) In the curve graph of the total lipid droplet degradation rate obtained in step (3) that changes dynamically over time, measure the maximum total lipid droplet degradation rate (e.g. Fig. 9 B in the figure), and define this rate as When , the time when the cell is at the maximum total lipid droplet degradation rate can be obtained and defined as This time can be regarded as the response time of a single cell to the maximum lipolysis effect after activating the cAMP-PKA lipolysis signal. The shorter the time, the faster the response of the lipolysis effect.

[0039] Example 3 A quantitative detection method for lipid droplet degradation rate and lipolytic enzyme activity efficiency at the level of single lipid droplets, which can be used to detect specific gene expression knockdown (such as Pnpla2 , Abhd5 , Plin1 and G0s2 The evaluation of the regulatory effect on quantitative indicators of lipolysis such as lipid droplet degradation rate and lipolytic enzyme activity efficiency of adipocytes after gene knockdown (such as gene knockdown), overexpression (such as PNPLA2-GFP overexpression) or lipolytic enzyme activity inhibition treatment (such as PNPLA2 protease inhibitor, Atglistatin) specifically includes the following steps: (1) Knockdown of the expression of PNPLA2, a key protein in adipocyte lipolysis (shPNPLA2), and treatment of cells with an RNA silencing intervention sequence that does not target any gene (shNC) in the control group, and further treatment of these PNPLA2-deficient and control adipocytes with 10 µM isoproterenol can activate the lipolysis signals of these cells, such as p-HSL and p-CREB (such as Fig.10 (A in the middle); (2) Observe under a living cell bright field microscope using a 100x objective lens magnification, capture and record 1080*1080 pixel live cell dynamic bright field images at intervals of 10 minutes and a total duration of 7 hours to record the dynamic changes of lipid droplets in adipocytes; (3) The dynamic bright field image of the living cells obtained in step (2) is subjected to lipid droplet image processing and analysis, and according to steps (4) and (5) in Example 1, a curve graph showing the lipid droplet degradation rate of a single lipid droplet in PNPLA2-deficient and control adipocytes as a function of the lipid droplet surface area can be obtained (e.g. Fig.10 The comparison results showed that PNPLA2 deficiency significantly reduced the rate of lipid droplet degradation; (4) Based on the linear relationship between lipid droplet degradation rate and lipid droplet surface area obtained in step (3), the lipolytic enzyme activity efficiency in PNPLA2-deficient and control adipocytes can be calculated (e.g. Fig.10 (C in the middle). The comparison results showed that PNPLA2 deficiency significantly reduced the efficiency of lipolytic enzyme activity; (5) Overexpression of the key lipolysis protein PNPLA2 in adipocytes (PNPLA2-GFP), while the control group overexpressed GFP in adipocytes (e.g. Fig.11 The PNPLA2-GFP overexpressing and GFP control adipocytes were further treated with 10 µM isoproterenol. (6) Observe under a living cell bright field microscope using a 100x objective lens magnification, capture and record 1080*1080 pixel live cell dynamic bright field images at intervals of 10 minutes and a total duration of 7 hours to record the dynamic changes of lipid droplets in adipocytes; (7) The live cell dynamic bright field image obtained in step (6) is subjected to lipid droplet image processing and analysis, and according to steps (4) and (5) in Example 1, a curve graph showing the lipid droplet degradation rate of a single lipid droplet in PNPLA2 overexpressing and GFP control adipocytes as a function of the lipid droplet surface area can be obtained (e.g. Fig.11 (B in the middle). Comparison results showed that PNPLA2 overexpression significantly increased the lipid droplet degradation rate; (8) Based on the linear relationship between lipid droplet degradation rate and lipid droplet surface area obtained in step (7), the lipolytic enzyme activity efficiency in PNPLA2 overexpressing and GFP control adipocytes can be calculated (e.g. Fig.11 (C in the middle). The comparison results showed that PNPLA2 overexpression significantly increased the efficiency of lipolytic enzyme activity; (9) Treatment of adipocytes with an inhibitor of the activity of the key lipolysis protein PNPLA2 (Atglistatin) and treatment of adipocytes with 1% DMSO (equivalent to the DMSO concentration used in the Atglistatin formulation) in the control group, and further treatment of these PNPLA2 activity-inhibited and DMSO-treated adipocytes with 10 µM isoproterenol, activated the lipolysis signals of these cells, such as p-HSL and p-CREB (e.g. Fig.12 (A in the middle); (10) Observe under a living cell bright field microscope using a 100x objective lens magnification, capture and record 1080*1080 pixel live cell dynamic bright field images at intervals of 10 minutes and a total duration of 7 hours to record the dynamic changes of lipid droplets in adipocytes; (11) The live cell dynamic bright field image obtained in step (10) is subjected to lipid droplet image processing and analysis, and according to steps (4) and (5) in Example 1, a curve graph showing the lipid droplet degradation rate of a single lipid droplet in the PNPLA2 activity inhibition and DMSO treatment control adipocytes as a function of the lipid droplet surface area can be obtained (e.g. Fig.12 (B in the middle). Comparison results showed that inhibition of PNPLA2 activity significantly reduced the rate of lipid droplet degradation; (12) Based on the linear relationship between the lipid droplet degradation rate and the lipid droplet surface area obtained in step (11), the lipolytic enzyme activity efficiency in the adipocytes under PNPLA2 activity inhibition and DMSO treatment control can be calculated (e.g. Fig.12 (C in the middle). Comparison results showed that inhibition of PNPLA2 activity significantly reduced the efficiency of lipolytic enzyme activity; (13) The expression of adipocyte lipolysis regulatory proteins ABHD5, PNPLA2, PLIN1 and G0S2 was knocked down (in order such as shABHD5, shPNPLA3, shPLIN1, shG0S2, etc.), and the control group was treated with RNA silencing intervention sequences that did not target any gene (shNC), and further treated with 10 μM isoproterenol to treat these types of lipolysis regulatory protein-deficient and control adipocytes; (14) Observe under a living cell bright field microscope using a 100x objective lens magnification, capture and record 1080*1080 pixel live cell dynamic bright field images at intervals of 10 minutes and a total duration of 7 hours to record the dynamic changes of lipid droplets in adipocytes; (15) The dynamic bright field image of living cells obtained in step (14) is subjected to lipid droplet image processing and analysis, and the lipolytic enzyme 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. Fig.13 ). The comparison results showed that ABHD5 and PLIN1 deficiency significantly reduced the efficiency of lipolytic enzyme activity, among which ABHD5 deficiency caused the efficiency of lipolytic enzyme activity to drop even lower; in contrast, G0S2 deficiency significantly increased the efficiency of lipolytic enzyme activity; (16) In order to verify the results of lipolytic enzyme activity efficiency obtained in step (15), a biochemical assay of glycerol release (free glycerol assay kit, catalog number F6428, Sigma-Aldrich) was used to measure the lipolysis capacity of PLPNAL2, ABHD5, PLIN1 and G0S2 deficient and control adipocytes. The results showed that the method of the present invention had good similarity with the biochemical assay (correlation coefficient R 2 = 0.79, e.g. Fig.14 ).

[0040] Example 4 A quantitative detection method for lipid droplet degradation characteristics analyzed at the single cell level can be used to distinguish the differences in lipolytic enzyme activity efficiency and total lipid droplet degradation rate in 3T3-L1 adipocytes, white adipocytes and brown adipocytes, specifically comprising the following steps: (1) Obtain stromal vascular fraction cells from brown adipose tissue of mice, and obtain brown adipocytes by induction and differentiation; obtain stromal vascular fraction cells from white adipose tissue of mice, and obtain white adipocytes by induction and differentiation; obtain 3T3-L1 adipocytes by induction and differentiation of 3T3-L1 precursor adipocytes (such as Fig.15 ). Induction and differentiation can be achieved according to step (1) in Example 1. The cells are cultured in a 37°C, 5% carbon dioxide incubator throughout the process; (2) The three adipocytes were treated with 10 µM isoproterenol and observed under a living cell bright field microscope using a 100x objective magnification. Dynamic bright field images of living cells with a resolution of 1080 x 1080 pixels were recorded at intervals of 10 minutes and a total duration of 7 hours to record the dynamic changes of lipid droplets in adipocytes. (3) The dynamic bright field image of living cells obtained in step (2) is subjected to lipid droplet image processing and analysis, and the lipolytic enzyme 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. Fig.16 ). The comparison results showed that after the three adipocytes were treated with 10 µM isoproterenol, the lipolytic enzyme activity efficiency in 3T3-L1 adipocytes and brown adipocytes was comparable, while the lipolytic enzyme activity efficiency in white adipocytes was relatively low; (4) In order to obtain the total lipid droplet degradation rate in a single cell, the degradation rate of each lipid droplet in a single cell is summed up to obtain a curve of the degradation rate of the total lipid droplet in a single cell over time (e.g. Fig.17 ). The comparison results show that the characteristics of the total lipid droplet degradation rate of the three types of adipocytes over time are quite different. Among them, the total lipid droplet degradation rate and lipolysis response time of white adipocytes are relatively high; (5) In order to calculate the total volume of degraded lipid droplets in a single cell during this measurement time , the area under the curve of the total lipid droplet degradation rate in a single cell obtained in step (4) over time was statistically summed. The comparison results showed that the total volume of degraded lipid droplets in white adipocytes was the largest, followed by brown adipocytes, and the least in 3T3-L1 adipocytes (e.g. Fig.18 ); (6) Calculate and analyze the maximum total lipid droplet degradation rate obtained in step (4) (like Fig.19 ) and the response time to maximum lipolysis (like Fig. 20 ). The comparison results showed that white fat cells and It is the largest in these three types of cells, indicating that white adipocytes have the largest lipolysis rate and a slower response time under 10 µM isoproterenol treatment.

[0041] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for detecting and quantitatively analyzing lipid droplet degradation at a single lipid droplet level or a single cell level, characterized in that: The steps include: S1. Processing cells for detection; S2, taking high-magnification images of the cells treated with S1 to obtain image data of lipid droplet changes; S3, performing image processing and analysis on the image data obtained in S2; The specific steps of processing and analysis in S3 are as follows: A1. Image processing and analysis are performed with lipid droplets as spheres. In a set of live cell dynamic bright field image data sets collected in time series, the diameter of each visible lipid droplet in a single cell is measured as d and recorded as a lipid droplet diameter curve that changes with time. After calculating the spherical volume, it is The volume of each visible lipid droplet is recorded as a lipid droplet volume curve over time, and the volume of each visible lipid droplet is recorded as a lipid droplet volume curve over time. The lipolysis rate is defined as ; A2. Calculate the time-varying lipid droplet degradation rate and lipid droplet surface area obtained in A1 The relationship between the lipid droplet degradation rate and the lipid droplet surface area was plotted and the linear change rate was obtained. , It is the efficiency of lipolytic enzyme activity.

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

3. The method for detecting and quantitatively analyzing lipid droplet degradation at a single lipid droplet level or a single cell level according to claim 2, characterized in that: The induction medium contained 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 quantitatively analyzing lipid droplet degradation at a single lipid droplet level or a single cell level according to claim 2, characterized in that: The maturation medium contains high-glucose DMEM medium, 10% fetal bovine serum, 1% penicillin / streptomycin and 5 µg / mL insulin.

5. The method for detecting and quantitatively analyzing lipid droplet degradation at a single lipid droplet level or a 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 quantitatively analyzing lipid droplet degradation at a single lipid droplet level or a single cell level according to claim 1, characterized in that: The cells treated in S2 are cells treated with 10 µM isoproterenol.

7. The method for detecting and quantitatively analyzing lipid droplet degradation at a single lipid droplet level or a single cell level according to claim 1, characterized in that: The specific steps of high-magnification imaging in S2 are as follows: observe cells under a bright-field microscope using a high-power objective lens magnification, capture and record 1080*1080 pixel dynamic bright-field images of living 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 lipolysis.

8. Use of the method according to any one of claims 1 to 7 in determining the fat degradation capacity of cells.

9. The use according to claim 8, characterized in that: The application also includes the assessment of the risk of developing obesity metabolic diseases.

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