CN112322582A - A physio-mechanical microenvironmental model for adipose-derived stem cells cultured and directed differentiation in a simulated in vivo growth environment - Google Patents
A physio-mechanical microenvironmental model for adipose-derived stem cells cultured and directed differentiation in a simulated in vivo growth environment Download PDFInfo
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Abstract
The invention provides a physiological mechanics microenvironment model for culturing and directionally differentiating adipose-derived stem cells in a simulated in vivo growth environment, which comprises three generations of human adipose-derived stem cells marked by green fluorescent protein, a 3D-MTC-based super-resolution biomechanics platform, a mechanical signal loading module, a feedback parameter characteristic database and a culture medium. The super-resolution biomechanical platform comprises a magnetizer, a magnetic ball adhered to the surface of a cell and an external magnetic field, wherein the magnetizer is used for magnetizing the magnetic ball adhered to the surface of the cell, and the magnetic ball generates moment under the action of the external magnetic field and is applied to the surface of a three-generation human adipose-derived stem cell marked by green fluorescent protein. The invention can control the output of mechanical load by selecting proper control mode and parameter value, simulate the physiological state of stem cells under natural condition, generate different mechanical loads within the physiological strain range, and realize the quantitative control of ADSCs stress.
Description
Technical Field
The invention belongs to the technical field of stem cells, relates to a model for culturing and directionally differentiating adipose-derived stem cells in a simulated in-vivo growth environment, and particularly relates to a physiological mechanics microenvironment model.
Background
Adipose tissue is abundant in human body, a large number of adipose-derived stem cells (ADSCs) obtained by liposuction have the potential of self-renewal, proliferation and multidirectional differentiation, can be differentiated into adipocytes, chondrocytes, myocytes, osteoblasts, nerve cells, glial cells and islet cells, can secrete various angiogenesis promoting factors and anti-apoptosis factors to resist inflammation and oxidation, can resist the damage of oxygen free radicals, and is expected to become a stem cell source for repairing damaged tissues and organs. At present, considerable data have been accumulated in research on directed differentiation experiments of ADSCs, and most of research on directed adipogenic and osteogenic differentiation of ADSCs is focused on clinically relevant applications. In the traditional research, a simple biochemical method has low induction efficiency and is unstable, and meanwhile, abnormal complex mechanical factors in the microenvironment of human cells are not considered. In the early research of vascular tissue engineering, the research on the biomechanical property of the artificial blood vessel is seriously deficient, so that the artificial blood vessel is difficult to adapt to the change of mechanical factors in a physiological microenvironment and is easy to crack or fray under the physiological load such as repeated pulsation and the like in a body. Similarly, the skin cells formed by the differentiation of the ADSCs induced by the biochemical method cannot bear the mechanical load of physiological strength and the mechanical adaptability of the skin cells are unknown, and the skin cells can not adapt to the action of various mechanical factors changing constantly in the cell microenvironment when being used for repairing skin injuries in clinical practice.
With the continuous development of science, the evidence that the mechanical microenvironment determines the fate of stem cells is gradually increased, the research on the influence of the in vitro differentiation of stem cells is expanded from a biochemical method to the effect of mechanical factors on the differentiation of stem cells, besides soluble molecules, the expression of transcription factors for the differentiation of stem cells can be regulated by mechanical stimulation and physical properties of Extracellular matrix (ECM), and the differentiation of stem cells is regulated by the synergy of the biomechanics and the biochemical microenvironment. The Mesenchymal Stem Cells (MSCs) can respond to different forms of mechanical stimulation, and Engler and other researches prove that physical signals such as Cell substrate hardness and mechanical stimulation on cells can determine the form, transcription program and Cell fate of the cells better than chemical signals, and the mechanical stimulation can independently regulate the differentiation of the MSCs without depending on soluble factors. At present, the mechanical force loading mode for inducing stem cell differentiation mainly comprises two-Dimensional (2-Dimensional,2D) and three-Dimensional (3-Dimensional,3D) mechanical loading approaches, a biological microenvironment of a 3D culture mode has higher similarity with a cell growth microenvironment in vivo, and the biomechanical characteristics of stem cells can be observed more intuitively. The Xufeng professor team and the like construct a three-dimensional stem cell microenvironment with a space mechanical gradient and dynamic mechanical characteristics by designing a hydrogel material structure and combining an advanced manufacturing technology, and discuss the potential application of the three-dimensional stem cell mechanical microenvironment with space-time regulation in the field of biomedical engineering.
The similarity between the cell growth environment and the real in vivo environment is closely related, the in vitro research result is poorer in conformity with the in vivo situation, and meanwhile, the ECM has the defects of poorer forming effect and mechanical property, insufficient controllability of stress loading range and the like, and no model can cover the mechanical microenvironment of the in vivo cells. The field needs to construct a near-physiological ADSCs three-dimensional mechanical microenvironment for finely regulating the directed differentiation of the ADSCs.
Disclosure of Invention
The invention provides a physiological mechanics microenvironment model for culturing and directionally differentiating adipose-derived stem cells in a simulated in vivo growth environment, which can control the output of mechanical loads by selecting a proper control mode and parameter values, simulate the physiological state of the stem cells under natural conditions, and generate different mechanical loads within a physiological strain range, thereby realizing the quantitative control of the stress of ADSCs, researching the influence of different parameters on the differentiation behavior of ADSCs, and providing experimental support for the directional differentiation research of ADSCs.
The technical scheme adopted for realizing the above purpose of the invention is as follows:
a physiological mechanics microenvironment model for culturing and directionally differentiating adipose-derived stem cells in a simulated in vivo growth environment comprises three generations of human adipose-derived stem cells marked by green fluorescent protein, a 3D-MTC-based super-resolution biomechanics platform, a mechanical signal loading module, a feedback parameter characteristic database and a culture medium,
the 3D-MTC-based super-resolution biomechanical platform comprises a magnetizer, a magnetic ball adhered to the surface of a cell and an external magnetic field, wherein the magnetizer is used for magnetizing the magnetic ball adhered to the surface of the cell, and the magnetic ball generates moment under the action of the external magnetic field and is applied to the surface of a three-generation human adipose-derived stem cell marked by green fluorescent protein;
the mechanical signal loading module comprehensively considers physiological and mechanical micro-environments of the human body in different states by simulating the growth environment in the human body so as to determine the type of a physiological and mechanical signal applied to cells, and controls an external magnetic field through current so as to realize accurate control of mechanical stimulation applied to the cells;
the feedback model database is a database containing data of deformation and displacement fields in the cell nucleus under different stress effects.
The construction method of the 3D-MTC-based super-resolution biomechanics platform comprises the following steps: (1) determining the range of the oval cells in the visual field, making an ellipse surrounding the cells, wherein the ellipse can minimize the area of all the cells, and establishing a corresponding two-dimensional plane by taking the long axis of the ellipse as the long axis of the cells;
(2) setting a long axis parallel to the long axis of the cell as a two-dimensional coordinate system, a short axis vertical to the long axis of the cell as a short axis, and an angle between the force application direction and the long axis as theta;
(3) constructing a three-dimensional coordinate model on the basis of the two-dimensional coordinates, and applying force to cells at different angles to construct a multi-modal three-dimensional physiological mechanical signal model;
(4) the magnetizer generates pulses, magnetizes the magnetic balls adhered to the surfaces of the cells along the Z-axis direction vertical to the cell plane, and re-magnetizes the magnetic balls at regular intervals to keep the magnetic field intensity and the direction unchanged;
(5) a sinusoidal external magnetic field forming an angle of 0-90 degrees with the long axis of the cell is applied to the magnetic ball, the magnetic ball generates moment under the action of the external magnetic field, and the moment is applied to the surface of the three-generation human adipose-derived stem cell marked by green fluorescent protein.
The physiological mechanical signal types comprise frequency, amplitude, intensity, stress application time, stress application angle and stress application mode, and the physiological mechanical signal parameters of each type are set as follows:
frequency: 0.2 Hz-1 Hz, 1-3 Hz, 3-10 Hz, 10 Hz-20 Hz;
amplitude: 5%, 10%, 15%, 30%, 50%;
strength: 9kPa, 12kPa, 15kPa, 50 kPa;
force application time: 4hours/d, 8hours/d, 24 hours/d;
force application angle: 0 °, 45 °, 90 °;
force application mode: sine wave, square wave.
In the feedback model database, the calculation method of the deformation and displacement field data in the cell nucleus under the action of different stresses is as follows: (1) processing the acquired image by adopting a Matlab magnetic ball tracking program, and rejecting abnormal displacement data of the magnetic ball by calculating and outputting data records comprising sampling time, period and magnetic ball displacement coordinate values;
(2) adopting a single molecule tracking technology to obtain GFP fluorescent particle tracks, further calculating the mean square displacement MSD of GFP fluorescent particle diffusion, collecting and storing images before and after stress application, and then carrying out noise reduction, registration, fusion, format conversion and edge analysis processing on the images;
(3) solving a two-dimensional or three-dimensional displacement field of a cell image by adopting a three-dimensional fast Fourier transform algorithm and a displacement extraction algorithm in Matlab based on a digital image cross-correlation theorem, and detecting the shape, structure and cell mechanical property of the whole cell nucleus and chromatin under the stimulation of near physiological mechanics; and calculating a cross correlation coefficient by comparing the reference image before stress application with the deformation image after stress application to obtain a cell image displacement field.
The specific method in the step (2) is as follows: firstly, a plurality of images which are not stressed and periodically stressed are positioned and registered by utilizing a Matlab program to obtain the displacement of GFP, the GFP fluorescence image is converted into a gray image, then the Matlab program is adopted for operation and analysis, the mass center coordinate data of GFP fluorescence particles on the image are obtained from a binary image, the mean square displacement MSD value of each GFP fluorescence particle is calculated through the obtained coordinates, and the mean square displacement MSD value is combined after being fitted at different stress application angles so as to analyze and judge the influence of a mechanical signal on the dyeing quality;
the function of the two-dimensional diffusion motion of the GFP fluorescent particles used to calculate the mean square shift is shown in equation 1:
where Δ t represents the time interval between two frames of pictures, N represents the total frame number, and r (t) represents the position of the GFP fluorescent particles at time t.
Compared with the prior art, the invention has the following advantages: in the invention, three-generation human adipose-derived stem cells (hADSCs) marked by Green Fluorescent Protein (GFP) are taken as a research object, a 3D-MTC and super-resolution technology are combined to simulate an in-vivo mechanical microenvironment, a real-time loading and visual detection experiment model is constructed in vitro, and physiological mechanical signals with controllable parameters are reproduced. Applying mechanical signals with near physiological strength to hADSCs, detecting in real time, establishing a mechanical signal loading and feedback model database, and determining the optimal mechanical signal mode and parameters for further determining and controlling the directional stable differentiation of hADSCs into target cells.
Drawings
FIG. 1 is a schematic diagram of the construction of a 3D-MTC-based super-resolution biomechanics platform in the invention;
FIG. 2 is a plot of a fit of MSD versus time interval (Δ t) for GFP fluorescent particles of the present invention;
FIG. 3 is a diagram of measurement and calculation of deformation and displacement fields in nuclei under different stress effects in the present invention.
Detailed Description
The present invention will be described in detail with reference to the accompanying drawings and embodiments.
The physiological mechanics microenvironment model for culturing and directionally differentiating the adipose-derived stem cells in the simulated in vivo growth environment provided in the embodiment comprises three generations of human adipose-derived stem cells marked by green fluorescent protein, a 3D-MTC-based super-resolution biomechanics platform, a mechanical signal loading module, a feedback parameter characteristic database and a culture medium. The culture medium adopts novel 3D PA gel, the environment provided by the natural PA gel biomaterial cell matrix can simulate a mechanical microenvironment similar to the growth of cells in vivo, the matrix with good biocompatibility for simulating the growth of cells in vivo is adopted, and the hardness of ADSCs (all-dielectric self-supporting cells) for reflecting the survival of cells in vivo is constructed by controlling the proportion of acrylamide to bisacrylamide. And observing and analyzing the regulation and control effect of the substrate hardness on the specific differentiation and formation of target cells by using the ADSCs marked by the GFP. In order to search for an extracellular gel matrix suitable for the survival of adherent cells, it was attempted to introduce cell microcarriers inside an inert gel network and optimize the material for improving its cell activity.
Aiming at the problem that the similarity between the in vitro research result and the in vivo situation is determined by the similarity between the stem cell growth microenvironment and the real in vivo microenvironment in the earlier research, a near physiological microenvironment model with controllable mechanical signal parameters and capable of reproducing ADSCs in vivo is constructed in vitro by combining 3D-MTC and a super-resolution technology. The 3D-MTC-based super-resolution biomechanical platform comprises a magnetizer, a magnetic ball adhered to the surface of a cell and an external magnetic field, wherein the magnetizer is used for magnetizing the magnetic ball adhered to the surface of the cell, and the magnetic ball generates moment under the action of the external magnetic field and is applied to the surface of a three-generation human adipose-derived stem cell marked by green fluorescent protein; the specific construction method comprises the following steps:
(A) determining the range of the oval cells in the visual field, making an ellipse around the cells, which can minimize the area of all the cells, and establishing a corresponding two-dimensional plane by taking the long axis of the ellipse as the long axis of the cells.
(B) The direction parallel to the long axis of the cell is set as the long axis of a two-dimensional coordinate system, the direction perpendicular to the long axis of the cell is set as the short axis, and the angle between the force application direction and the long axis is set as theta.
(C) A three-dimensional coordinate model is constructed on the basis of the two-dimensional coordinates, the force can be applied to cells at different angles, and the model is modeled and loaded by the multi-modal three-dimensional physiological mechanical signals and is shown in figure 1.
(D) The magnetizer generates a 500ms pulse to magnetize the magnetic ball adhered to the cell surface along the Z-axis direction vertical to the cell plane, the magnetic ball generates the magnetization (M) vertical to the cell plane direction to be about 2500Gauss/ms, the magnetization is carried out for 2-3 times, and the magnetic ball needs to be magnetized again every 15min to maintain the strength and the direction of the magnetic field unchanged.
(E) A sine external magnetic field which forms a certain angle (0-90 degrees) with the long axis of the cell is applied to the magnetic ball, the magnetic induction intensity (H), and the vector product of M and H is equal to the size of a sine torque (T) stretching force applied to the magnetic ball.
The constructed 3D-MTC-based super-resolution cell biomechanics experimental research platform is used for applying mechanical signals in physiological and pathological strain ranges of a living body, and the physiological frequency is 0.2-20 Hz. In the normal breathing process or during the blood flow in the lung, the low frequency of the stress signal waveform (sine wave and square wave) fluctuates within the range of 0.2-1 Hz; during exercise, the heart rate can reach 180-200 times/minute, and the frequency can reach about 3 Hz; during running or jumping, the frequency of foot tissue can reach above 5-20 Hz. The mechanical signal loading module comprehensively considers physiological and mechanical micro-environments of the human body in different states by simulating the growth environment in the human body so as to determine the type of a physiological and mechanical signal applied to cells, and controls an external magnetic field through current so as to realize accurate control of mechanical stimulation applied to the cells; the physiological mechanical signal types comprise frequency, amplitude, intensity, stress application time, stress application angle and stress application mode, and the physiological mechanical signal parameters of each type are set as follows:
frequency: 0.2 Hz-1 Hz, 1-3 Hz, 3-10 Hz, 10 Hz-20 Hz;
amplitude: 5%, 10%, 15%, 30%, 50%;
strength: 9kPa, 12kPa, 15kPa, 50 kPa;
force application time: 4hours/d, 8hours/d, 24 hours/d;
force application angle: 0 °, 45 °, 90 °;
force application mode: sine wave, square wave.
And the directed differentiation of the ADSCs to target cells is regulated and controlled by changing the parameter setting of the mechanical signals.
The feedback model database is a database containing data of deformation and displacement fields in the cell nucleus under different stress effects. The construction method comprises the following steps: the method comprises the steps of selecting three generations of hADSCs with stable biological characteristics as research objects, applying mechanical stimulation with certain modes and parameter types to magnetic spheres adhered to the surfaces of cells, processing collected images by adopting a user-defined Matlab magnetic sphere tracking program, and removing abnormal displacement data of the magnetic spheres by calculating and outputting data records including sampling time, period and magnetic sphere displacement coordinate values.
(C) GFP particles are embedded and transfected in hADSCs nuclei as markers, a single molecule tracking technology is adopted to obtain GFP fluorescent particle tracks, then Mean Square Displacement (MSD) of GFP fluorescent particle diffusion is calculated, images before and after stress application are collected and stored, and then the images are subjected to noise reduction, registration, fusion, format conversion, edge analysis and the like.
Writing a Matlab program to perform positioning registration on a plurality of images without applying force and periodic force to obtain GFP displacement, converting a GFP fluorescence image into a gray image, then performing operation and analysis by adopting a custom Matlab program, acquiring centroid coordinate data of GFP fluorescence particles on the image from a binary image, calculating MSD values of the GFP fluorescence particles through the acquired coordinates, respectively fitting at different force application angles, and then combining the coordinates so as to analyze and judge the influence of a mechanical signal on the dyeing quality, wherein the diagram is shown in FIG. 2.
The mean square shift is calculated as a function of the two-dimensional diffusion motion of the GFP phosphor particles, as shown in equation 1:
where Δ t represents the time interval between two frames of pictures, N represents the total frame number, and r (t) represents the position of the GFP fluorescent particles at time t.
(D) In order to realize the measurement of the deformation and displacement field in the cell nucleus, GFP particles are embedded and transfected in the cell nucleus as a mark, and a Matlab code is compiled to execute a high-throughput analysis processing function, so that the displacement variation, the elastic deformation and the like of the protein in the cell nucleus are represented. The method is characterized in that a calculation code is compiled by adopting a three-dimensional fast Fourier transform algorithm in Matlab based on a digital image cross-correlation theorem, the whole calculation process is ensured to be completed quickly, a two-dimensional or three-dimensional Displacement field (Displacement) of a cell image is solved by a compiled Displacement extraction algorithm, and the detection of the shape, the structure and the cell mechanical property of the whole cell nucleus and chromatin under the stimulation of near-physiological mechanics is realized. The cell Image displacement field is obtained by comparing the reference Image a (before application of force) and the deformation Image B (after application of force) and then calculating the cross-correlation coefficient. FIG. 3 shows the results of three-dimensional measurement and calculation of deformation and displacement fields in nuclei under the action of positive stress (Normal stress) and Shear stress (Shear stress).
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