Method for estimating iPSC sphere diameter and single cell size based on 3D culture technology

Abstract

The present invention relates to the technical field of stem cell differentiation research, and discloses a method for estimating the diameter of iPSC sphere and the size of a single cell based on 3D culture technology, including a linear model estimation method and a parameterized model estimation method; the linear model estimation method comprises the following steps: using a linear model to fit the relationship between the diameter of a cell sphere and the number of cells, and setting the coefficient of the linear model based on experimental data; the linear model is set to; the parameterized model estimation method comprises the following steps: constructing a parameterized model, and setting the coefficient of the parameterized model based on experimental data; the parameterized model is derived based on the relationship between the diameter of a cell sphere and the number of cells; the parameterized model is set to; wherein y is the diameter of a cell sphere, x is the number of cells, and b are coefficients; the experimental data is obtained based on a cell sphere experiment. The present invention can quickly estimate the diameter of a cell sphere and the diameter of a single cell, is easy to operate, has high estimation accuracy and low estimation cost.

Description

Technical Field

[0001] The present invention relates to the technical field of stem cell differentiation research, and in particular to a method for estimating the diameter of iPSC spheres and the size of single cells based on 3D culture technology. Background Art

[0002] In the field of stem cell research, induced pluripotent stem cells (iPSCs), as a cell type with broad application potential, are widely used in research such as regenerative medicine, drug screening, and disease model construction. 3D culture technology has become an important means in iPSC differentiation research because it can better simulate the in vivo microenvironment. iPSC suspension cultures aggregate into embryoid bodies (EBs), and EBs are used for 3D culture, which mimics the cell interactions in the in vivo environment and can more realistically reflect the behavior and function of cells. Studies have reported that EB size has an important influence on spontaneous differentiation, germ layer differentiation tendency, aggregation dynamics, etc. Therefore, estimating the EB sphere diameter is a key parameter in the development of iPSC differentiation process flow.

[0003] The estimation of the diameter of cell spheres can provide an effective reference for evaluating the cell growth status and differentiation process. By monitoring the diameter of iPSC spheres within a fixed time period (such as 24 hours), researchers can quickly obtain key information such as stem cell differentiation status and proliferation rate. This method not only provides data support for optimizing stem cell culture conditions, but also lays the foundation for promoting large-scale cell culture and application. Different culture conditions (such as cell density, culture medium components, etc.) will affect the change of sphere diameter. Therefore, accurate estimation of sphere diameter is of great significance for optimizing 3D culture systems and improving stem cell culture efficiency. In addition, the size of a single iPSC can be further estimated by knowing the total number of sphere cells and sphere diameter. This information is of great value for understanding the behavioral characteristics of a single stem cell and its spatial distribution within the sphere. Changes in cell size may reflect the dynamic changes of biological processes such as cell proliferation, differentiation, and metabolic activity. Mastering the diameter information of a single cell not only helps to build a relationship model between cell volume and its functional state, but also provides a theoretical basis for the design of cell therapy programs in regenerative medicine.

[0004] Therefore, the estimation of spheroid diameter is an indispensable part of stem cell research. At present, although some products or technologies provide solutions for the estimation of spheroid diameter, they all have certain defects. For example, the traditional microscope observation method is inefficient and easy to introduce human errors; the more advanced dynamic light scattering technology (DLS) and image analysis technology have great limitations. Among them, DLS measures the size of suspended particles by light scattering. Although it is suitable for the measurement of single cells or tiny particles, it is not accurate enough for complex 3D cell spheroid structures, especially in dynamic monitoring and large-scale screening. In addition, DLS equipment is expensive and complicated to operate, making it difficult to popularize and use in high-throughput experiments. Image analysis technology relies on high-resolution microscopes and specialized software processing to measure the diameter of cell spheres. Although it provides a visually accurate assessment, it relies on a large amount of data collection and processing, and the process is cumbersome and time-consuming, which is not suitable for rapid or large-scale experiments. In addition, there are more common deficiencies in existing technologies, including the lack of prior evaluation tools, automation technology and high-throughput capabilities, which leads to experiments relying on empirical judgment, poor reproducibility, and cumbersome optimization of culture conditions. Moreover, existing technologies are not yet mature enough to accurately estimate the diameter of individual cells, which limits researchers' in-depth understanding of the relationship between the function and morphology of different cell lines. Summary of the invention

[0005] The present invention aims to provide a method for estimating the iPSC sphere diameter and single cell size based on 3D culture technology, which can quickly estimate the cell sphere diameter and single cell diameter, is easy to operate, has high estimation accuracy and low estimation cost.

[0006] The basic scheme provided by the present invention is: a method for estimating the iPSC sphere diameter and single cell size based on 3D culture technology, including a linear model estimation method and a parameterized model estimation method; the linear model estimation method comprises the following steps:

[0007] A linear model was used to fit the relationship between the diameter of the cell sphere and the number of cells, and the coefficients of the linear model were set based on the experimental data; the linear model was set as ;

[0008] The parameterized model estimation method comprises the following steps:

[0009] A parameterized model is constructed, and the coefficients of the parameterized model are set based on experimental data; the parameterized model is derived based on the relationship between the cell sphere diameter and the number of cells; the parameterized model is set as ;

[0010] Where y is the diameter of the cell sphere, x is the number of cells, , and b are coefficients, and is the slope, b is a constant, is the diameter of a single cell; the experimental data is obtained based on a cell spheroid formation experiment;

[0011] Use a linear model or a parametric model to estimate the diameter of the cell spheroid and the diameter of a single cell.

[0012] The working principle and advantages of the present invention are as follows:

[0013] The present invention provides a method for estimating the diameter of iPSC spheroids and the size of single cells based on a 3D culture technique, and provides two calculation methods that can be used to estimate the diameter of iPSC spheroids and the size of single cells. Both methods are very simple and equivalent within a certain error range, and the estimation results are relatively accurate. The key points are as follows:

[0014] First, this solution provides a brand-new route for estimating the diameter of spheroids. By using mathematical modeling for diameter estimation, it can reduce costs and improve efficiency at the root. In the existing measurement schemes for the diameter of spheroids, since the cell itself is an entity and an intuitive visual feature, the common thinking is mostly like that described in the aforementioned background technology, that is, through intuitive measurement means, each cell is measured (for example, the DLS method directly measures the cell size through light scattering, and the image processing technology is consistent with the existing microscope observation principle and also measures the size one by one through actual measurement). This is also the mindset in the biochemical field when measuring sizes. However, this solution first breaks through this mindset and selects a relatively non-intuitive and non-direct measurement method of mathematical modeling to estimate the diameter of spheroids, thereby forming a brand-new route for estimating the diameter of spheroids and being able to complete the diameter estimation of cell spheroids and single cells. First, this solution deeply explores the actual needs in the process of stem cell differentiation research. When obtaining key information such as the differentiation state and proliferation rate of stem cells, the determination of these information stages can be achieved based on micron-level measurements, and the timeliness of the determination is a key factor in ensuring the research quality. On this basis, this solution makes a bold breakthrough in the estimation route. Second, on the basis of using data modeling, this solution also combines experimental operations, which can ensure a relatively high accuracy of estimation.

[0015] Moreover, compared with the prior art that requires reliance on advanced equipment or complex image processing, this solution does not rely on expensive equipment and does not require a large data sample for support, greatly reducing the experimental cost; instead, based on the verification and derivation of functional relationships, through mathematical modeling, a linear model and a parametric model are constructed to complete the estimation. During the estimation process, at least one or two groups of experimental data are only needed to set the coefficients, and a general and accurate estimation model can be obtained. In addition, the linear model and the parametric model are convenient for automation transformation and are convenient for forming an automated tool for estimating the diameter of spheroids, which can quickly complete the evaluation and is especially suitable for large-scale screening.

[0016] Second, this scheme has strong versatility, can adapt to different cell types and culture conditions, and maintains a high estimation accuracy. First, the linear model estimation method provided by this scheme can quickly estimate the cell sphere diameter; the parameterized model estimation method provided can estimate both the cell sphere diameter and the single cell diameter, which helps to deeply understand the functional characteristics of different cell lines. Secondly, the setting of the model in the two estimation methods is derived based on the benchmark rule of the relationship between the cell sphere diameter and the number of cells. This benchmark rule is stable and not easily interfered by external factors such as experimental conditions, which can ensure that the mathematical relationship set by the model is accurate and reliable. The setting of the coefficients is targeted based on specific experimental data, which can ensure that each model can actually match the experimental environment required for estimation, and then work together to ensure a high estimation accuracy.

[0017] Third, the operation is easy and simple to use, and does not require highly specialized technology or complex image processing. Among them, the linear model estimation method can be estimated using a simple calculator or even mental arithmetic, which is extremely convenient to operate and suitable for rapid evaluation. Although the parametric model estimation method has a slightly higher computational complexity than the former, it can not only estimate the cell sphere diameter, but can also be applied to the calculation of single cell diameter, which can provide a more in-depth analysis tool for cell research. In terms of cell sphere diameter estimation, their application is extremely simple and highly interchangeable.

[0018] In summary, this scheme solves the problems of existing technologies in insufficient data, low evaluation efficiency and imperfect standardization through mathematical modeling, and provides a low-cost, easy-to-operate and widely applicable tool. It not only provides new technical means for stem cell differentiation research, but also brings new solutions to improve stem cell culture efficiency and precision medical applications. It has broad application prospects in the fields of cell therapy and tissue engineering, and has important application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a schematic diagram of a method flow of an embodiment of a method for estimating iPSC sphere diameter and single cell size based on 3D culture technology of the present invention;

[0020] Figure 2 This is a microscopic image of a cell sphere when the number of cells is 3000 in the cell sphere experiment example 1 of the embodiment of the method for estimating the diameter of iPSC sphere and the size of a single cell based on the 3D culture technology of the present invention;

[0021] Figure 3 It is a schematic diagram of the linear relationship fitting results in the cell spheroidization experiment example 1 of the method for estimating the iPSC spheroid diameter and single cell size based on the 3D culture technology of the present invention;

[0022] Figure 4It is a linear approximation schematic diagram of the third power when the number of cells is in the range of 2000 to 8000 in an embodiment of the method for estimating the iPSC sphere diameter and single cell size based on 3D culture technology of the present invention;

[0023] Figure 5 The ratio of non-spheroidized cells in the embodiment of the method for estimating the iPSC spheroid diameter and single cell size based on 3D culture technology of the present invention Schematic diagram of linear fitting of correction factors;

[0024] Figure 6 The ratio of non-spheroidized cells in the embodiment of the method for estimating the iPSC spheroid diameter and single cell size based on 3D culture technology of the present invention Schematic diagram of linear approximation of the correction factor in the range [0~20%];

[0025] Figure 7 A relationship diagram of y obtained by fitting the parameterized model of the embodiment of the method for estimating the iPSC sphere diameter and single cell size based on the 3D culture technology of the present invention based on the least squares method and the y value obtained by actual measurement;

[0026] Figure 8 Schematic diagram of the mutual substitution of the linear model and the parameterized model of the embodiment of the method for estimating the iPSC sphere diameter and single cell size based on the 3D culture technology of the present invention. DETAILED DESCRIPTION

[0027] The following is a further detailed description through specific implementation methods:

[0028] The embodiment is basically as shown in the attached Figure 1 Shown: iPSC sphere diameter and single cell size estimation methods based on 3D culture technology, including linear model estimation methods and parameterized model estimation methods.

[0029] The linear model estimation method comprises the following steps:

[0030] A linear model was used to fit the relationship between the diameter of the cell sphere and the number of cells, and the coefficients of the linear model were set based on the experimental data; the linear model was set as .

[0031] The parameterized model estimation method comprises the following steps:

[0032] A parameterized model is constructed, and the coefficients of the parameterized model are set based on experimental data; the parameterized model is derived based on the relationship between the cell sphere diameter and the number of cells; the parameterized model is set as .

[0033] Where y is the diameter of the cell sphere, x is the number of cells, , and b are coefficients, and is the slope, b is a constant, is the diameter of a single cell; the experimental data are obtained based on a cell sphering experiment.

[0034] Estimate spheroid and single cell diameters using linear or parametric models.

[0035] Specifically, the step of acquiring the experimental data includes:

[0036] Select n groups of cells, perform a cell sphere formation experiment, and measure the diameter of the cell sphere after a specific culture period;

[0037] The average of multiple cell sphere diameter measurements obtained in each group of cell sphere formation experiments was taken as the experimental data.

[0038] 1 and take an integer; and when >1, select n groups of cells with different numbers and perform cell sphere formation experiments separately.

[0039] When setting the coefficients of the linear model, the least squares method is used to fit the experimental data and estimate the coefficients, including the slope and constant b, thereby determining the linear relationship between the cell sphere diameter and the number of cells and forming a linear model. This setting can accurately fit the change law of the cell sphere diameter and provide a reference for subsequent cell culture experiments.

[0040] Moreover, in the present embodiment, the number of cells is set to range from 2000 to 8000. Under this condition, the repeatability and biological characteristics of the experiment can be fully guaranteed. With respect to the former (i.e., repeatability of the experiment), the number of cells within this number range ensures the repeatability of the experimental results. When the number is less than 2000 cells, the sphere formation efficiency is low, the sphere is unstable and the shape is irregular, which affects the reliability of the experiment; while within 8000 cells, the cell sphere can maintain structural integrity, have good nutrient supply and metabolic balance, and can avoid apoptosis or necrosis of cells in the central area. With respect to the latter (i.e., biological characteristics), this number range covers the common density of cell sphere formation, ensuring the stability and predictability of the experimental results.

[0041] The cell sphere formation experiment includes the following steps:

[0042] S1, check the cell status, and when the cell status satisfies that the confluence is more than 80% and the proportion of differentiated cells and stacked growth cells is less than 5%, proceed to the next step; the cells are iPSCs;

[0043] S2, add appropriate amount of DPBS to wash the cells, repeat the washing once, then add appropriate amount of digestive enzyme and digest at 37℃ for 3-5min;

[0044] S3, when most of the cells are observed to become brighter and rounder (i.e., become round and bright spheres) under a microscope, knock on the edge of the culture dish to make most of the cells (i.e., the part of the cells that have become round and bright spheres) fall off, add iPSC culture medium to terminate digestion, and transfer the cell suspension to a centrifuge tube and pipette to prepare a single-cell suspension;

[0045] In this embodiment, most cells become brighter and rounder, which means that more than 50% of the cells become brighter and rounder;

[0046] S4, centrifuge at a centrifugal force of 300g for 3 minutes to form a cell pellet, take the cell pellet, add spheroidization medium to resuspend the cells, take an appropriate amount of cell suspension for counting, calculate the required number of cells according to the counting result, dilute the cell suspension, and inoculate the diluted cell suspension into a 96-well plate according to the determined number of cells; in this embodiment, the 96-well plate uses a U-bottom ultra-low adsorption 96-well plate.

[0047] S5, centrifuge the 96-well plate at 300g for 3 minutes. After centrifugation, place the 96-well plate in a cell culture incubator at 37°C and 5%. Under the culture condition of concentration, the cells were cultured overnight.

[0048] S6. Use a Pasteur pipette to transfer the cell spheres in the 96-well plate to a 6-well plate, photograph the cell sphere morphology under a microscope, and measure the sphere size of each cell sphere.

[0049] When deriving the parameterized model, the following steps are involved:

[0050] When the number of cells x is known, the theoretical relationship between the diameter y and the number of cells x can be derived from the volume formula of the cell sphere. Assume that each cell has a diameter Without considering the space gaps when cells are stacked, the total volume V of the cell sphere is composed of x cells with a diameter of If the sphere is composed of cells, then the volume of a cell sphere with a diameter of y is equal to the total volume of x cells.

[0051] The volume formula of a cell sphere is: ;

[0052] Therefore, the total volume of x cells is: ;

[0053] Assume that the diameter of the cell sphere is , its volume is: ;

[0054] Ignoring the space between cells when they are stacked, the volume is conserved, that is, the volume of the cell sphere is equal to the total volume of the cells: ;

[0055] Eliminating the common terms, we get: ;

[0056] Solve and and Relationship: ; .

[0057] The cell sphere diameter can be quickly estimated using the cell sphere diameter estimation formula using the cell diameter as a parameter.

[0058] In this step, the cell diameter estimated experimentally for a particular cell line is , that is, the size of a single iPSC, is a key factor in deeply understanding the behavioral characteristics of cells. It helps to reveal how cells are arranged and distributed during the sphering process, and can reflect the dynamic changes of biological processes such as cell proliferation, differentiation, and metabolic activity. This estimate not only provides a basis for modeling the association between cell volume and functional state, but also provides a theoretical basis for the design of cell therapy programs in the field of regenerative medicine. In addition, once Once the value of is determined, the diameter of the cell sphere formed by different cell numbers can be further estimated according to the above formula.

[0059] In the parameterized model estimation method, it also includes:

[0060] When the cell sphere contains non-spheroidized cells (specifically, non-spheroidized cells exist at the edge of the cell sphere), the single cell diameter is calculated after introducing a correction factor into the parameterized model. The correction factor is ; is the proportion of non-spheroidized cells at the edge of the cell sphere. After introducing the correction factor, the parameterized model is transformed into , is the corrected single cell diameter.

[0061] like Figure 5 As shown, As for the effect of diameter correction, it can be observed from the curve in the figure that when When increases, the correction factor gradually increases. When the value is small (e.g. 10%), the correction factor is close to 1.04, which means that the corrected diameter increases by about 3.6% compared to the initial estimate. When the value is larger (eg, 50%), the corrected diameter increases significantly by about 26%.

[0062] Furthermore, when the 3D culture experiment (i.e., cell spheroid experiment) is successful, most cells will be contained in the cell spheroid. When , the correction factor can be linearly fitted, such as Figure 6 shown.

[0063] because = 0, that is, all cells participate in the formation of cell spheres, and the correction term has no effect. , so the constant term of linear fitting b=1.0, and we only need to estimate the slope. Finally, we get the following formula:

[0064] ;in, is the slope; the parameterized model is transformed into In this embodiment, .

[0065] In addition, under certain conditions, the parameterized model can also be simplified by a linear model. Specifically, when the number of cells ranges from 2000 to 8000, the 1 / 3 power of the number of cells is close enough to the linear model, so the linear model can be used as a simplified description, such as Figure 4 As shown, a linear approximation diagram of the third power is shown when the number of cells is in the range of 2000 to 8000. The fitted linear model is: .

[0066] The mean square error (MSE) is 0.060330; the average percentage error is 1.29%; this proves that within the range of 2000 to 8000, the 1 / 3 power value of the number of cells can be approximately represented by this linear equation.

[0067] Furthermore, the diameter of the cell sphere can be obtained With cell number and the diameter of a single cell The linear calculation formula between: , and thus the linear estimation of a single parameter can be achieved.

[0068] When there is only one set of experiments, that is, there is only one experimental value of x, .

[0069] If you take (Most iPSCs are around 20 μm in size) .

[0070] In this embodiment, several experimental examples are combined to explain in detail the coefficient setting method of the linear model and the parameterized model.

[0071] (1) Cell spheroidization experiment example 1

[0072] Experiment Number: M240408-2

[0073] Cell line: iPSC-TXH-C3 P18D3

[0074] Select two groups of cells and perform cell spheroidization experiments according to the above cell spheroidization experimental steps. After culturing for a specific time, measure the diameter of the cell spheroids (e.g. Figure 2 As shown in the figure, it shows the microscopic image of the cell sphere when the number of cells is 3000). The final experimental data obtained are as follows:

[0075] The measured values ​​of cell sphere diameter when the number of cells was 3000 (unit: μm): [310.39, 284.04, 279.84, 268.05, 294.52, 319.10, 285.34, 305.08, 315.74, 311.95, 288.18, 309.60, 297.61, 297.95, 282.95, 301.00, 262.03, 314.22, 295.37, 269.34, 271. 40,292.90,267.49,302.42,306.94,303.82,287.57,294.35,295.61,279.72,295.74,306.23,331.20,283.95,294.88,260.83,278.80,262.89,312.35,290.11,288.96,307.86,313.40,300.06,288.52];

[0076] The measured values ​​of cell sphere diameter when the number of cells was 8000 (unit: μm): [397.34,439.70,441.15,473.59,370.49,460.74,424.84,437.57,424.87,389.27,453.43,414.53,417.47,394.16,469.15, 380.57,431.06,478.07,392.05,368.20,439.36,457.06,426.45,393.44,378.07,416.81,350.12,436.03,411.19,387.43,427.31,407.37,414.65,428.10];

[0077] Based on the above experimental data, the relationship between the diameter of the cell sphere and the number of cells was fitted using the least squares method, as shown in Figure 3 As shown, the following linear model is obtained: y=0.0250x+218.55, where y is the cell sphere diameter (μm), x is the number of cells, is the slope , is the intercept (constant).

[0078] Furthermore, for different cell lines, the relationship between the number of cells per well x and the diameter of the cell sphere y can be described by the following empirical formula:

[0079] ;in, is a constant that is cell line specific.

[0080] In specific applications, for different cell lines, parameters An initial estimate of can be obtained from experimental data. Through at least one set of experiments, measure the diameter of the cell spheres under different cell numbers, substitute the experimental data into the above empirical formula, and then determine This scheme can provide a reliable theoretical basis for estimating the diameter of cell spheres of different cell lines.

[0081] (2) Cell spheroidization experiment example 2

[0082] Experiment Number: M240314

[0083] Cell line: iPSC-TXH-C3 P11D3

[0084] Select a group of cells, perform a cell spheroidization experiment according to the above cell spheroidization experimental steps, and measure the diameter of the cell spheroids after a specific culture time. The final experimental data obtained are as follows:

[0085] The measured values ​​of the cell sphere diameter when the number of cells is 4000 (unit: μm): [307.40,320.82,302.30,288.13,325.81,295.51,310.42,306.16,306.49,299.59,301.37,303.81,291.46,316.44,306.88,311.51,302.98,307.15,325.88,306.00,298.27,299.62,314.52,322.88,311.29,302.35,320.60,297.59,313.54,316.92]

[0086] Based on the above experimental data, the average cell sphere diameter when the number of cells is 4000 is calculated to be 307.79, that is, when x=40002, y=307.79. According to the empirical formula Fitting the relationship between the cell sphere diameter and the cell number, the following linear model was obtained: , where y is the diameter of the cell sphere (μm), x is the number of cells, is the slope , is the intercept (constant).

[0087] Based on the cell spheroidization experiment example 1 and the cell spheroidization experiment example 2, the parameters of the linear model can be reduced to 1, thereby reducing the spheroidization and measurement experiments of specific cell lines, which is suitable for scenarios that require rapid estimation or are inconvenient for multiple experiments.

[0088] The present embodiment is described in detail below in combination with several application examples.

[0089] Application Example 1 (Linear Model Estimation Method)

[0090] When using a linear model to estimate the diameter of a spheroid, the "or" "For estimation, the former requires at least two sets of cell sphering experiments with different numbers, while the latter only requires one set of cell sphering experiments because there is only one parameter. Multiple sets of experimental data can improve the robustness and confidence of the results and reduce the impact of experimental errors. One set of experimental data has higher efficiency and lower estimation cost.

[0091] In the application ”, including the following steps:

[0092] Step 1. Select two groups of cells with different numbers (e.g., 3,000 and 4,000 cells) and conduct cell sphere formation experiments respectively. After culturing for a specific time (e.g., 24 hours), measure the diameter of each group of cell spheres.

[0093] The experimental data obtained are as follows:

[0094] The diameter of the cell sphere when the number of cells is 3000 (unit: μm):

[0095] [249.35,265.68,249.48,253.18,262.96,224.19,245.33,251.36,231.72,244.41,249.23,255.38,252.95,247.94,255.37,260.42,263.81,227.32,265.54,234.06,260.39,256.66,262.41,250.21,232.74,258.37,227.92,253.28,256.83];

[0096] The diameter of the cell sphere when the number of cells is 4000 (unit: μm):

[0097] [276.00,269.78,269.39,284.03,271.61,264.46,277.82,273.91,278.65,269.53,281.62,274.78,286.70,264.65,266.74,267.99,263.65,266.60,280.55,267.76,271.86,280.44,288.48,256.56,285.01,270.46,273.56,258.05];

[0098] Step 2: Calculate the average cell spheroid diameter y_mean (unit: μm) at different cell numbers x:

[0099] x: 3000, y_mean: 249.95;

[0100] x: 4000, y_mean: 272.88.

[0101] Step 3: Use the least squares method to fit the experimental data and estimate the slope and constant in, and obtain the fitting result: y = 0.0229x + 181.15.

[0102] Step 4: Use the fitting result to predict the cell spheroid diameter 24 hours later when the cell number is 5000.

[0103] x: 5000: y_estimated: 0.0229 * 5000 + 181.15 = 295.65;

[0104] That is, when the cell number is 5000, the estimated value of the cell spheroid diameter is 295.65.

[0105] When applying " ", step 1 only needs to do at least one set of experiments, such as taking the experiment with a cell number of 3000. Then, through step 2, x: 3000, y_mean: 249.95 is obtained.

[0106] Step 3: Use the least squares method to fit the experimental data and estimate the constant in, and obtain the fitting result: .

[0107] Step 4: Use the fitting result to predict the cell spheroid diameter 24 hours later when the cell number is 5000.

[0108] x: 5000: y_estimated: 5000 / 40 + 174.9479 = 299.95;

[0109] That is, when the number of cells is 5000, the estimated value of the cell sphere diameter is 299.95.

[0110] To verify the accuracy of the above linear equation, a spheroidization experiment with 5000 cells is used as an auxiliary explanation. The results of the spheroidization experiment are as follows:

[0111] The diameter of the cell sphere when the number of cells is 5000 (unit: μm):

[0112] The average sphere diameter was 298.72 μm.

[0113] It can be seen that using " "or" " can accurately estimate the diameter of spheroid cells.

[0114] Application Example 2 (Parameterized Model Estimation Method)

[0115] When using the parameterized model to estimate the diameter of the spheroid, the "or" ", because there is only one parameter, at least one set of cell sphering experiments is required. When conditions permit, two or more sets of experimental data can be used to help improve the robustness and confidence of the results, reduce the impact of experimental errors, and obtain a more robust estimation model. In this application example, compared with the linear model (such as compared with application example 1), the parameterized model selected in this application example has a slightly larger amount of calculation, but the parameter itself represents the diameter of iPSC stem cells and has a clearer practical significance.

[0116] Step 1: Select a group of cells (e.g., 4,000 cells) for a cell sphere formation experiment, and measure the diameter of the cell sphere after culturing for a specific time (e.g., 24 hours).

[0117] The experimental data obtained are as follows:

[0118] The diameter of the cell sphere when the number of cells is 4000 (unit: μm):

[0119] [276.00,269.78,269.39,284.03,271.61,264.46,277.82,273.91,278.65,269.53,281.62,274.78,286.70,264.65,266.74,267.99,263.65,266.60,280.55,267.76,271.86,280.44,288.48,256.56,285.01,270.46,273.56,258.05];

[0120] Step 2: Calculate the average cell sphere diameter y_mean (unit: μm) for different cell numbers x:

[0121] x:4000,y_mean:272.88.

[0122] Step 3: Use the least squares method to fit the experimental data and estimate the "or" The cell diameter constant in (for a specific iPSC stem cell line), and obtain the fitting results =17.19, that is, the cell diameter of the cell line used in this group of experiments was estimated to be 17.19 μm.

[0123] Step 4: When the number of cells is 5000, the estimated value of the cell sphere diameter is:

[0124] According to the formula ;

[0125] According to the formula

[0126] =289.53;

[0127] In order to verify the estimation accuracy of the above linear equation, a spheroidization experiment with 5000 cells is used as auxiliary explanation below. The experimental results of the spheroidization experiment are the same as those described in Application Example 1. The actual average cell spheroid diameter obtained is: 298.72 μm.

[0128] It can be seen that using " "or" " can estimate the diameter of spheroid cells relatively accurately. When the number of cells is 5000, The approximation will result in a slightly smaller estimate.

[0129] In addition, when the cell sphere contains non-spheroidized cells (specifically, there are obvious non-spheroidized cells at the edge of the cell sphere), the correction factor is introduced into the parameterized model before calculating the single cell diameter.

[0130] Correspondingly, in step 3, the fitting result is obtained =17.19, that is, the cell diameter of the cell line used in this group of experiments is estimated to be 17.19μm. The proportion of non-spheroidized cells η is observed or measured, such as η=5%. A correction factor is introduced to correct the single cell diameter. , .

[0131] Corrected single cell diameter =17.49; or =17.52.

[0132] Application Example 3 (Parameterized Model Estimation Method)

[0133] (Same data as Example 1, Experiment No.: M240408-2, Cell line: iPSC-TXH-C3 P18D3) This example is used to prove that the calculation results of this scheme have high accuracy, such as Figure 7 As shown in the figure, the relationship between the y value obtained by fitting the parameterized model based on the least squares method and the y value obtained by actual measurement is shown, among which the cell diameter obtained by fitting is It is 20.732367 μm. As can be seen from the figure, the fitting result of the parameterized model is close to the measured value.

[0134] Furthermore, the linear model estimation method and the parametric model estimation method can be selected and used. The linear model and the parametric model are highly interchangeable and easy to operate. In this application example, three different iPSCs (C3, C2, ZQ) were used, and 12 groups of cell sphere experiments were performed to verify the parameter b in application example 1 and the parameter b in application example 2. The consistency of the two columns of data is 0.99, which is very high. Figure 8 As shown, it shows that there is good collinearity between the data, and the relationship between the two variables can determine each other. It further verifies that the linear model and the parametric model have a high degree of mutual substitution.

[0135] The present embodiment provides a method for estimating the diameter and single cell size of iPSC spheres based on 3D culture technology, and provides two calculation methods that can be used to estimate the diameter and single cell size of iPSC spheres. Both methods are very simple and almost equivalent within a certain error range, and the estimation results are relatively accurate. Among them, the linear model estimation method can complete the estimation using a simple calculator or even oral calculation, which is extremely convenient to operate and suitable for rapid evaluation. Although the parameterized model estimation method has a slightly higher computational complexity than the former, it can not only estimate the diameter of the cell sphere, but also can be applied to the calculation of the diameter of a single cell, which can provide a more in-depth analysis tool for cell research. In terms of cell sphere diameter estimation, their application is extremely simple and highly interchangeable.

[0136] Moreover, compared with the existing technology, this solution has many advantages. First, in terms of cost, this solution does not rely on expensive equipment, which greatly reduces the cost of experiments. Secondly, the efficiency is significantly improved, and the evaluation can be completed quickly through automated and standardized processes, which is particularly suitable for large-scale screening. Third, the operation is relatively easy and simple to use, and does not require highly specialized technology or complex image processing. Finally, it is highly versatile and can adapt to different cell types and culture conditions. Through automation and mathematical modeling, this solution solves the problems of existing technologies in terms of insufficient data, low evaluation efficiency, and imperfect standardization, and provides a low-cost, easy-to-operate, and widely applicable tool.

[0137] The above is only an embodiment of the present invention. The common sense such as the known specific structure and characteristics in the scheme is not described in detail here. The ordinary technicians in the relevant field are aware of all the common technical knowledge in the technical field of the invention before the application date or priority date, can obtain all the existing technologies in the field, and have the ability to apply the conventional experimental means before that date. The ordinary technicians in the relevant field can improve and implement the scheme in combination with their own abilities under the enlightenment given by this application. Some typical known structures or known methods should not become obstacles for the ordinary technicians in the relevant field to implement this application. It should be pointed out that for the technicians in this field, without departing from the structure of the present invention, several deformations and improvements can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicality of the patent.

Claims

1. A method for estimating the diameter of iPSC spheres and single cell size based on 3D culture technology, characterized in that: It includes a linear model estimation method and a parameterized model estimation method; the linear model estimation method includes the following steps: A linear model was used to fit the relationship between the diameter of the cell sphere and the number of cells, and the coefficients of the linear model were set based on the experimental data; the linear model was set as ; The parameterized model estimation method comprises the following steps: A parameterized model is constructed, and the coefficients of the parameterized model are set based on experimental data; the parameterized model is derived based on the relationship between the cell sphere diameter and the number of cells; the parameterized model is set as ; Where y is the diameter of the cell sphere, x is the number of cells, , and b are coefficients, and is the slope, b is a constant, is the diameter of a single cell; the experimental data are obtained based on a cell sphering experiment; Estimate spheroid and single cell diameters using linear or parametric models.

2. The method for estimating iPSC sphere diameter and single cell size based on 3D culture technology according to claim 1, characterized in that: The step of obtaining the experimental data comprises: Select n groups of cells, perform a cell sphere formation experiment, and measure the diameter of the cell sphere after a specific culture period; The average of multiple cell sphere diameter measurements obtained in each group of cell sphere formation experiments was taken as the experimental data.

3. The method for estimating iPSC sphere diameter and single cell size based on 3D culture technology according to claim 2, characterized in that: 1 and take an integer; and when >1, select n groups of cells with different numbers and perform cell sphere formation experiments separately.

4. The method for estimating iPSC sphere diameter and single cell size based on 3D culture technology according to claim 2, characterized in that: The number of cells was set in the range of 2000~8000.

5. The method for estimating iPSC sphere diameter and single cell size based on 3D culture technology according to claim 1, characterized in that: When setting the coefficients of the linear model, the least squares method is used to fit the experimental data and estimate the coefficients, including the slope and constant b, thereby determining the linear relationship between the cell sphere diameter and the cell number and forming a linear model.

6. The method for estimating iPSC sphere diameter and single cell size based on 3D culture technology according to claim 2, characterized in that: The cell sphere formation experiment includes the following steps: S1, check the cell status, and when the cell status satisfies that the confluence is more than 80% and the proportion of differentiated cells and stacked growth cells is less than 5%, proceed to the next step; the cells are iPSCs; S2, add appropriate amount of DPBS to wash the cells, repeat the washing once, then add appropriate amount of digestive enzyme and digest at 37℃ for 3-5min; S3, when cells are observed to become round and shiny spheres under a microscope, knock on the edge of the culture dish to make the cells in this part fall off, add iPSC culture medium to terminate digestion, and transfer the cell suspension to a centrifuge tube and blow to prepare a single cell suspension; S4, centrifuge at 300g for 3 minutes to form a cell pellet, take the cell pellet, add spheroidization medium to resuspend the cells, take an appropriate amount of the cell suspension for counting, calculate the required number of cells according to the counting result, dilute the cell suspension, and inoculate the diluted cell suspension into a 96-well plate according to the determined number of cells; S5, centrifuge the 96-well plate at 300g for 3 minutes. After centrifugation, place the 96-well plate in a cell culture incubator at 37°C and 5%. Under the culture condition of concentration, the cells were cultured overnight. S6. Use a Pasteur pipette to transfer the cell spheres in the 96-well plate to a 6-well plate, photograph the cell sphere morphology under a microscope, and measure the sphere size of each cell sphere.

7. The method for estimating iPSC sphere diameter and single cell size based on 3D culture technology according to claim 1, characterized in that: In the parameterized model estimation method, it also includes: When the cell sphere contains non-spheroid cells, the single cell diameter is calculated after introducing the correction factor in the parameterized model.

8. The method for estimating iPSC sphere diameter and single cell size based on 3D culture technology according to claim 7, characterized in that: The correction factor is ; is the proportion of non-spheroidized cells at the edge of the cell sphere; after introducing the correction factor, the parameterized model is deformed into , is the corrected single cell diameter.

9. The method for estimating iPSC sphere diameter and single cell size based on 3D culture technology according to claim 8, characterized in that: when When , a linear fit is performed on the correction factor. , is the slope; the parameterized model is transformed into .

10. The method for estimating iPSC sphere diameter and single cell size based on 3D culture technology according to claim 1, characterized in that: Either the linear model estimation method or the parameterized model estimation method is selected.

Images