CN112322582A - Physiological mechanics microenvironment model for culturing and directionally differentiating adipose-derived stem cells in simulated in vivo growth environment - Google Patents
Physiological mechanics microenvironment model for culturing and directionally differentiating adipose-derived stem cells in simulated in vivo growth environment Download PDFInfo
- Publication number
- CN112322582A CN112322582A CN202010972573.6A CN202010972573A CN112322582A CN 112322582 A CN112322582 A CN 112322582A CN 202010972573 A CN202010972573 A CN 202010972573A CN 112322582 A CN112322582 A CN 112322582A
- Authority
- CN
- China
- Prior art keywords
- cell
- cells
- physiological
- derived stem
- stem cells
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 210000000130 stem cell Anatomy 0.000 title claims abstract description 38
- 238000001727 in vivo Methods 0.000 title claims abstract description 23
- 230000012010 growth Effects 0.000 title claims abstract description 15
- 238000012258 culturing Methods 0.000 title claims abstract description 12
- 210000004027 cell Anatomy 0.000 claims abstract description 71
- 239000005090 green fluorescent protein Substances 0.000 claims abstract description 40
- 108010043121 Green Fluorescent Proteins Proteins 0.000 claims abstract description 32
- 102000004144 Green Fluorescent Proteins Human genes 0.000 claims abstract description 32
- 230000009471 action Effects 0.000 claims abstract description 10
- 239000001963 growth medium Substances 0.000 claims abstract description 5
- 238000006073 displacement reaction Methods 0.000 claims description 35
- 239000002245 particle Substances 0.000 claims description 21
- 230000004069 differentiation Effects 0.000 claims description 18
- 210000003855 cell nucleus Anatomy 0.000 claims description 11
- 230000000638 stimulation Effects 0.000 claims description 11
- 230000000694 effects Effects 0.000 claims description 8
- 238000004458 analytical method Methods 0.000 claims description 7
- 238000004364 calculation method Methods 0.000 claims description 6
- 238000009792 diffusion process Methods 0.000 claims description 6
- 238000005516 engineering process Methods 0.000 claims description 6
- 238000000034 method Methods 0.000 claims description 6
- 238000012545 processing Methods 0.000 claims description 6
- 238000010276 construction Methods 0.000 claims description 5
- 230000002159 abnormal effect Effects 0.000 claims description 4
- 230000000007 visual effect Effects 0.000 claims description 4
- 108010077544 Chromatin Proteins 0.000 claims description 3
- 238000006243 chemical reaction Methods 0.000 claims description 3
- 210000003483 chromatin Anatomy 0.000 claims description 3
- 238000004043 dyeing Methods 0.000 claims description 3
- 238000000605 extraction Methods 0.000 claims description 3
- 238000002073 fluorescence micrograph Methods 0.000 claims description 3
- 230000004927 fusion Effects 0.000 claims description 3
- 230000033001 locomotion Effects 0.000 claims description 3
- 230000009467 reduction Effects 0.000 claims description 3
- 238000005070 sampling Methods 0.000 claims description 3
- 230000035790 physiological processes and functions Effects 0.000 abstract description 2
- 238000011160 research Methods 0.000 description 14
- 230000010261 cell growth Effects 0.000 description 5
- 238000000338 in vitro Methods 0.000 description 5
- 239000000499 gel Substances 0.000 description 4
- 230000001105 regulatory effect Effects 0.000 description 4
- 102000010834 Extracellular Matrix Proteins Human genes 0.000 description 3
- 108010037362 Extracellular Matrix Proteins Proteins 0.000 description 3
- 238000002306 biochemical method Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 210000002744 extracellular matrix Anatomy 0.000 description 3
- 239000011159 matrix material Substances 0.000 description 3
- 238000005259 measurement Methods 0.000 description 3
- 210000002901 mesenchymal stem cell Anatomy 0.000 description 3
- 210000004940 nucleus Anatomy 0.000 description 3
- 210000004927 skin cell Anatomy 0.000 description 3
- 210000001519 tissue Anatomy 0.000 description 3
- 239000002473 artificial blood Substances 0.000 description 2
- 230000033228 biological regulation Effects 0.000 description 2
- 210000004204 blood vessel Anatomy 0.000 description 2
- 230000001276 controlling effect Effects 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 238000002474 experimental method Methods 0.000 description 2
- 230000006698 induction Effects 0.000 description 2
- 230000005415 magnetization Effects 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 239000000758 substrate Substances 0.000 description 2
- 230000004083 survival effect Effects 0.000 description 2
- HRPVXLWXLXDGHG-UHFFFAOYSA-N Acrylamide Chemical compound NC(=O)C=C HRPVXLWXLXDGHG-UHFFFAOYSA-N 0.000 description 1
- 206010061218 Inflammation Diseases 0.000 description 1
- OAICVXFJPJFONN-UHFFFAOYSA-N Phosphorus Chemical compound [P] OAICVXFJPJFONN-UHFFFAOYSA-N 0.000 description 1
- 208000028990 Skin injury Diseases 0.000 description 1
- 102000040945 Transcription factor Human genes 0.000 description 1
- 108091023040 Transcription factor Proteins 0.000 description 1
- 230000001464 adherent effect Effects 0.000 description 1
- 210000001789 adipocyte Anatomy 0.000 description 1
- 230000009815 adipogenic differentiation Effects 0.000 description 1
- 210000000577 adipose tissue Anatomy 0.000 description 1
- 230000033115 angiogenesis Effects 0.000 description 1
- 230000006909 anti-apoptosis Effects 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 description 1
- 239000012620 biological material Substances 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 230000017531 blood circulation Effects 0.000 description 1
- 230000024245 cell differentiation Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 210000001612 chondrocyte Anatomy 0.000 description 1
- 230000006378 damage Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000002950 deficient Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 230000005489 elastic deformation Effects 0.000 description 1
- 210000005260 human cell Anatomy 0.000 description 1
- 239000000017 hydrogel Substances 0.000 description 1
- 230000001939 inductive effect Effects 0.000 description 1
- 230000004054 inflammatory process Effects 0.000 description 1
- 210000004153 islets of langerhan Anatomy 0.000 description 1
- 230000009191 jumping Effects 0.000 description 1
- 238000007443 liposuction Methods 0.000 description 1
- 210000004072 lung Anatomy 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 210000000107 myocyte Anatomy 0.000 description 1
- ZIUHHBKFKCYYJD-UHFFFAOYSA-N n,n'-methylenebisacrylamide Chemical compound C=CC(=O)NCNC(=O)C=C ZIUHHBKFKCYYJD-UHFFFAOYSA-N 0.000 description 1
- 210000004498 neuroglial cell Anatomy 0.000 description 1
- 210000002569 neuron Anatomy 0.000 description 1
- 210000000056 organ Anatomy 0.000 description 1
- 210000000963 osteoblast Anatomy 0.000 description 1
- 230000009818 osteogenic differentiation Effects 0.000 description 1
- 230000003647 oxidation Effects 0.000 description 1
- 238000007254 oxidation reaction Methods 0.000 description 1
- 229910052760 oxygen Inorganic materials 0.000 description 1
- 239000001301 oxygen Substances 0.000 description 1
- 230000001575 pathological effect Effects 0.000 description 1
- 230000000737 periodic effect Effects 0.000 description 1
- 230000000704 physical effect Effects 0.000 description 1
- 230000035755 proliferation Effects 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 102000004169 proteins and genes Human genes 0.000 description 1
- 108090000623 proteins and genes Proteins 0.000 description 1
- 230000010349 pulsation Effects 0.000 description 1
- 230000029058 respiratory gaseous exchange Effects 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 230000035897 transcription Effects 0.000 description 1
- 230000002792 vascular Effects 0.000 description 1
Images
Classifications
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12N—MICROORGANISMS OR ENZYMES; COMPOSITIONS THEREOF; PROPAGATING, PRESERVING, OR MAINTAINING MICROORGANISMS; MUTATION OR GENETIC ENGINEERING; CULTURE MEDIA
- C12N5/00—Undifferentiated human, animal or plant cells, e.g. cell lines; Tissues; Cultivation or maintenance thereof; Culture media therefor
- C12N5/06—Animal cells or tissues; Human cells or tissues
- C12N5/0602—Vertebrate cells
- C12N5/0652—Cells of skeletal and connective tissues; Mesenchyme
- C12N5/0662—Stem cells
- C12N5/0667—Adipose-derived stem cells [ADSC]; Adipose stromal stem cells
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
- G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
- G01N21/64—Fluorescence; Phosphorescence
- G01N21/6428—Measuring fluorescence of fluorescent products of reactions or of fluorochrome labelled reactive substances, e.g. measuring quenching effects, using measuring "optrodes"
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/5005—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12N—MICROORGANISMS OR ENZYMES; COMPOSITIONS THEREOF; PROPAGATING, PRESERVING, OR MAINTAINING MICROORGANISMS; MUTATION OR GENETIC ENGINEERING; CULTURE MEDIA
- C12N2513/00—3D culture
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12N—MICROORGANISMS OR ENZYMES; COMPOSITIONS THEREOF; PROPAGATING, PRESERVING, OR MAINTAINING MICROORGANISMS; MUTATION OR GENETIC ENGINEERING; CULTURE MEDIA
- C12N2529/00—Culture process characterised by the use of electromagnetic stimulation
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
- G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
- G01N21/64—Fluorescence; Phosphorescence
- G01N21/6428—Measuring fluorescence of fluorescent products of reactions or of fluorochrome labelled reactive substances, e.g. measuring quenching effects, using measuring "optrodes"
- G01N2021/6439—Measuring fluorescence of fluorescent products of reactions or of fluorochrome labelled reactive substances, e.g. measuring quenching effects, using measuring "optrodes" with indicators, stains, dyes, tags, labels, marks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
Landscapes
- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Physics & Mathematics (AREA)
- Chemical & Material Sciences (AREA)
- Immunology (AREA)
- Biomedical Technology (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Biotechnology (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- Genetics & Genomics (AREA)
- Organic Chemistry (AREA)
- Urology & Nephrology (AREA)
- Pathology (AREA)
- Analytical Chemistry (AREA)
- Molecular Biology (AREA)
- Cell Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Hematology (AREA)
- Microbiology (AREA)
- Wood Science & Technology (AREA)
- Zoology (AREA)
- General Engineering & Computer Science (AREA)
- Developmental Biology & Embryology (AREA)
- Geometry (AREA)
- Rheumatology (AREA)
- Computer Hardware Design (AREA)
- Chemical Kinetics & Catalysis (AREA)
- Tropical Medicine & Parasitology (AREA)
- Optics & Photonics (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Evolutionary Computation (AREA)
- Food Science & Technology (AREA)
- Medicinal Chemistry (AREA)
- Computer Graphics (AREA)
- Software Systems (AREA)
- Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
- Micro-Organisms Or Cultivation Processes Thereof (AREA)
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).
Claims (5)
1. A physiological mechanics microenvironment model for culturing and directionally differentiating adipose-derived stem cells in a simulated in vivo growth environment is characterized in that: comprises three generations of human adipose-derived stem cells marked by green fluorescent protein, a super-resolution biomechanics platform based on 3D-MTC, 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.
2. The biomechanical microenvironment model for culturing and committed differentiation of adipose-derived stem cells in a simulated in vivo growth environment of claim 1, wherein: 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.
3. The biomechanical microenvironment model for culturing and committed differentiation of adipose-derived stem cells in a simulated in vivo growth environment of claim 1, wherein: 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.
4. The biomechanical microenvironment model for culturing and committed differentiation of adipose-derived stem cells in a simulated in vivo growth environment of claim 1, wherein: 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.
5. The biomechanical microenvironment model for culturing and committed differentiation of adipose-derived stem cells in a simulated in vivo growth environment of claim 4, wherein: 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.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010972573.6A CN112322582A (en) | 2020-09-16 | 2020-09-16 | Physiological mechanics microenvironment model for culturing and directionally differentiating adipose-derived stem cells in simulated in vivo growth environment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010972573.6A CN112322582A (en) | 2020-09-16 | 2020-09-16 | Physiological mechanics microenvironment model for culturing and directionally differentiating adipose-derived stem cells in simulated in vivo growth environment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112322582A true CN112322582A (en) | 2021-02-05 |
Family
ID=74303120
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010972573.6A Pending CN112322582A (en) | 2020-09-16 | 2020-09-16 | Physiological mechanics microenvironment model for culturing and directionally differentiating adipose-derived stem cells in simulated in vivo growth environment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112322582A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117409867A (en) * | 2023-10-25 | 2024-01-16 | 华东交通大学 | Deep learning-based iPSCs directional differentiation regulation and control system and regulation and control method |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120165904A1 (en) * | 2010-11-22 | 2012-06-28 | Jin Hyung Lee | Optogenetic magnetic resonance imaging |
| WO2013068113A1 (en) * | 2011-11-08 | 2013-05-16 | Deutsches Krebsforschungszentrum Stiftung des öffentlichen Rechts | A method, system and computer program product for determining the mobility of fluorescent particles |
| JP2016118792A (en) * | 2016-01-07 | 2016-06-30 | ザ ボード オブ トラスティーズ オブ ザ レランド スタンフォード ジュニア ユニバーシティー | Microscopy imaging device with advanced imaging properties |
| US20160238610A1 (en) * | 2015-02-16 | 2016-08-18 | Bar-Ilan University | Cell analysis using dynamic biophysical methods |
| CN112280731A (en) * | 2020-09-30 | 2021-01-29 | 华东交通大学 | Method for inducing adipose-derived stem cells to directionally differentiate into human skin fibroblasts and application |
-
2020
- 2020-09-16 CN CN202010972573.6A patent/CN112322582A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120165904A1 (en) * | 2010-11-22 | 2012-06-28 | Jin Hyung Lee | Optogenetic magnetic resonance imaging |
| WO2013068113A1 (en) * | 2011-11-08 | 2013-05-16 | Deutsches Krebsforschungszentrum Stiftung des öffentlichen Rechts | A method, system and computer program product for determining the mobility of fluorescent particles |
| US20160238610A1 (en) * | 2015-02-16 | 2016-08-18 | Bar-Ilan University | Cell analysis using dynamic biophysical methods |
| JP2016118792A (en) * | 2016-01-07 | 2016-06-30 | ザ ボード オブ トラスティーズ オブ ザ レランド スタンフォード ジュニア ユニバーシティー | Microscopy imaging device with advanced imaging properties |
| CN112280731A (en) * | 2020-09-30 | 2021-01-29 | 华东交通大学 | Method for inducing adipose-derived stem cells to directionally differentiate into human skin fibroblasts and application |
Non-Patent Citations (7)
| Title |
|---|
| YUEJIN ZHANG等: "Interfacing 3D magnetic twisting cytometry with confocal fluorescence microscopy to image force responses in living cells", 《NATURE PROTOCOLS》 * |
| 吕东媛等: "干细胞的生物力学研究", 《力学进展》 * |
| 周浩天等: "弹性蛋白力学特性的单分子力谱", 《物理学报》 * |
| 张英昊: "一种可快速感受机械力的传感器细胞的理论设计方案", 《科技视界》 * |
| 张跃进: "三维细胞磁力扭曲仪与STED纳米显微镜耦合的细胞生物力学平台构建", <中国优秀博硕士学位论文全文数据库(博士)医药卫生科技辑> * |
| 王琳等: "细胞梯度力学微环境体外构建的研究", 《生命科学研究》 * |
| 韦富香: "力学信号直接诱导染色质形变及基因表达的研究", 《中国优秀博硕士学位论文全文数据库(博士)基础科学辑》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117409867A (en) * | 2023-10-25 | 2024-01-16 | 华东交通大学 | Deep learning-based iPSCs directional differentiation regulation and control system and regulation and control method |
| CN117409867B (en) * | 2023-10-25 | 2024-06-21 | 华东交通大学 | Deep learning-based iPSCs directional differentiation regulation and control system and regulation and control method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Ribeiro et al. | Magnetically activated electroactive microenvironments for skeletal muscle tissue regeneration | |
| Ramaswamy et al. | The role of organ level conditioning on the promotion of engineered heart valve tissue development in-vitro using mesenchymal stem cells | |
| JP6078943B2 (en) | Image processing apparatus and method, and program | |
| Castro12 et al. | Magnetic force-based tissue engineering and regenerative medicine | |
| US9752139B2 (en) | Magnetic three-dimensional cell culture apparatus and method | |
| Mao et al. | Passive and active microrheology for biomedical systems | |
| CN105518126B (en) | The method of mescenchymal stem cell is cultivated according to cell size | |
| CN112322582A (en) | Physiological mechanics microenvironment model for culturing and directionally differentiating adipose-derived stem cells in simulated in vivo growth environment | |
| CN112280731B (en) | Method for inducing adipose-derived stem cells to directionally differentiate into human skin fibroblasts and application | |
| Geng et al. | Review of cellular mechanotransduction on micropost substrates | |
| KR20230059734A (en) | Apparatus and method for distinguishing cells using artificial intelligence | |
| US20210054319A1 (en) | Flow bioreactor device for monitoring cellular dynamics | |
| Wang et al. | Wound-on-a-chip: High-throughput 3D wound healing assay with a novel SU-8 mesh chip | |
| Pang et al. | Design and development of a novel biostretch apparatus for tissue engineering | |
| CN107201310A (en) | It is loaded with intelligent heart analog chip of Human Cardiomyocytes and preparation method and application | |
| Princz et al. | New bioreactor vessel for tissue engineering of human nasal septal chondrocytes | |
| JP6436142B2 (en) | Image processing apparatus and method, and program | |
| Sawyer et al. | In situ monitoring of 3D in vitro cell aggregation using an optical imaging system | |
| IMURA et al. | Development of a three-dimensional cell culture system for the enhancement of nerve axonal extension by cyclic stretch stimulation | |
| Taheri et al. | Experimental and theoretical investigation of Young's modulus of liver cancer tissue using rectangular, V-shaped and dagger cantilevers of an atomic force microscope | |
| Liu | Application of Microscope in Cell Culture Experiment of Biomaterials in Vitro. | |
| Tang et al. | Non-destructive Two-Dimensional Motion Measurement of Cardiomyocytes Based on Hough Transform | |
| Ma et al. | Heart-on-a-chip based on machine vision and artificial intelligence | |
| Dai et al. | Effect of Static and Dynamic Stretching on Corneal Fibroblast Cell. Processes 2022, 10, 605 | |
| Hsieh et al. | Applications of fabricated micro-and nanostructures in biomedicine |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20210205 |