CN114958953A - Screening method for anti-aging efficacy of in-vitro 3D whole skin model of cosmetic raw materials - Google Patents

Screening method for anti-aging efficacy of in-vitro 3D whole skin model of cosmetic raw materials Download PDF

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CN114958953A
CN114958953A CN202210608302.1A CN202210608302A CN114958953A CN 114958953 A CN114958953 A CN 114958953A CN 202210608302 A CN202210608302 A CN 202210608302A CN 114958953 A CN114958953 A CN 114958953A
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skin model
raw material
aging
full
detection
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王博
王飞飞
张超
马骁
郭振宇
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Midas Shanghai Biotechnology Co ltd
Yunnan Yunke Characteristic Plant Extraction Laboratory Co ltd
Yunnan Beitani Biotechnology Group Co ltd
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Midas Shanghai Biotechnology Co ltd
Yunnan Yunke Characteristic Plant Extraction Laboratory Co ltd
Yunnan Beitani Biotechnology Group Co ltd
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Abstract

The invention discloses a screening method of anti-aging efficacy of an in-vitro 3D whole skin model of a cosmetic raw material, which screens the anti-aging activity of a target raw material, comprises detection of four dimensions of immunology, molecular biology, histology and physiology, constructs an anti-aging efficacy evaluation method of the cosmetic raw material, belongs to a system type evaluation method, and has the advantages of quickness, high efficiency and comprehensiveness; the method provides a quick and reliable evaluation method for early verification and screening of the anti-aging active raw materials of the skin care products, provides a reference basis for a compounding scheme of the anti-aging raw materials, and also provides an effective basis for further research of animal substitution experiments, skin care product development and efficacy verification in the skin care product industry.

Description

Screening method for anti-aging efficacy of in-vitro 3D whole skin model of cosmetic raw materials
Technical Field
The invention relates to a screening method for anti-aging efficacy of an in-vitro 3D whole skin model of a cosmetic raw material, belonging to the technical field of performance test of the cosmetic raw material.
Background
In the development of anti-aging skin care products with efficacy, the evaluation of the anti-aging efficacy of active raw materials is one of the important steps in the early stage of formula design. The evaluation means of the anti-aging efficacy of the traditional active raw materials is not referred to in the technical Specification for cosmetic safety. At present, main evaluation means are focused on experiments on the removal effect of DPPH free radicals, hydroxyl free radicals and the like, and the method has the defects of single experiment result, single experiment dimension, false positive and inconvenience for raw material screening. With the continuous and intensive systematic research on cells, organoids, animals and humans in the biological field, the evaluation of the efficacy of raw materials by multidimensional biological means has gradually replaced single experiments. Meanwhile, with the introduction of the circular economy concept of the 3R principle, the 3R principle has become a standard for the research of biomedical science and the general compliance of related regulation and management, the European cosmetic laws also promulgate prohibitions about animal experiments in cosmetic products, and the change of the laws promotes the development and application of in vitro substitution verification methods. The 3D skin model has become an excellent experimental model in vitro substitution experiments due to the characteristics of similarity to the structure and physiological function of human skin. Therefore, the construction of the in vitro substitution efficacy verification method is beneficial to more economically and efficiently realizing the development and screening of the anti-aging cosmetic raw materials.
Skin aging is usually caused by loss of collagen from the dermis, activation of oxidative stress pathways, impaired skin barrier, and the influence of external environmental factors (uv irradiation, haze, off-gas, PM2.5, etc.). When the skin is aged, the moisture value of the skin is reduced, the gene expression of matrix metalloproteinase MMP family is up-regulated, the gene expression of collagen family is down-regulated, and the related gene and protein expression at the true epidermal junction are down-regulated. The 3D full-skin model has the physiology and structure similar to the normal skin of a human body, the 3D full-skin sold in the market is produced in a unified mode, the structural characteristics are stable, the 3D full-skin model is used for detecting the anti-aging active substances, the 3D full-skin model can be used for simulating the gradual aging state of the real skin, and meanwhile the anti-aging effect of the cosmetic raw materials is evaluated. At the transcriptomic level, the proteomic level, the histological level and the physiological level, the in vitro method for comprehensively evaluating the anti-aging efficacy of the cosmetic raw material by combining the 3D whole skin model and four evaluation dimensions is not reported in related patents and documents.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, provides a screening method for the anti-aging efficacy of a cosmetic raw material in-vitro 3D whole-skin model, comprises evaluation means with four dimensions, detection with four dimensions of immunology, molecular biology, histology and physiology, and an anti-aging efficacy evaluation method for constructing the cosmetic raw material, belongs to a system type evaluation method, and has the advantages of rapidness and high efficiency.
The technical scheme for realizing the purpose is as follows: a screening method for anti-aging effects of an in-vitro 3D full-skin model of cosmetic raw materials is characterized in that the anti-aging activity of target raw materials is screened from four dimensions by using the 3D full-skin model, and the screening method specifically comprises the following steps:
s1, evaluating the solubility of the raw material sample and determining a dissolution scheme;
s2, culturing a 3D full-skin model;
s3, determining the detection concentration of the raw material sample by the activity detection of the 3D full-skin model, and comprising the following procedures:
s31, taking the 3D whole skin model with stable growth state in the step S2, adding an experimental sample, wherein the experimental sample comprises a plurality of raw material samples with different concentration gradients, the reference sample is a buffer solution without any sample, culturing for 3-10 days, and detecting the tissue survival rate of the 3D whole skin model by MTT;
s32, screening to obtain the administration concentration of the 3D whole skin model of the corresponding raw material sample at CV90, wherein the survival rate of the CV90 representing 3D skin tissues is 90%;
s4, a step of detecting moisture value of the 3D full-skin model, a step of detecting gene expression, a step of immunofluorescence examination and a step of detecting thickness of a dermis layer, wherein the steps comprise the following steps:
s41, taking the 3D full-skin with stable growth state in the step S2, setting a negative control group and a sample group, adding a buffer solution into the negative control group, adding a raw material sample with a CV90 corresponding to the administration concentration in the step S32 into the sample group, and culturing the negative control group and the sample group for 3-10 days respectively;
s42, collecting the 3D full-skin model cultured in the step S41, and carrying out the water content value expression detection of the 3D full-skin model;
s43, collecting the 3D full-skin model cultured in the step S41, and respectively carrying out gene expression detection of MMP9, COL3A1, Elastin and Nrf2 in the 3D full-skin model;
s44, collecting the normal 3D skin model cultured in the step S41, embedding paraffin and slicing, and then respectively carrying out immunofluorescence expression detection of Collagen VI and proCollagen I in the 3D full-skin model;
s45, collecting the normal 3D skin model cultured in the step S41, embedding paraffin and slicing, and then respectively detecting the thickness of the dermis layer in the 3D full-skin model;
s5, an evaluation step, specifically including the following:
s51, moisture value detection evaluation step: summarizing the water value detection results in the step S42, calculating the water value content of the detection raw material sample group and the negative control group, comparing the water value of the sample group and the negative control group, and drawing by using GraphPad Prism, wherein the score of the water value content of the detection raw material sample group is 0 when the water value content of the detection raw material sample group is lower than that of the negative control group; score 1 above negative control;
s52, procedure for evaluating relative gene expression level: summarizing the gene expression detection results in the step S43, calculating the gene expression ratio of the gene expression of the detection raw material sample group to the gene expression of the negative control group to obtain the relative expression quantity of the genes, and applying GraphPad Prism to map, wherein the result is expressed as Mean +/-SD; the comparison among the groups adopts Two-way ANOVA statistical analysis; all statistical analyses are two-tailed;
p <0.05 is considered to have a significant difference, indicated by "+", indicating that the test substance has a certain anti-aging effect and is scored as 0.3;
p <0.01 is considered to have a very significant difference, indicated by "+", indicating that the subject has significant anti-aging effect, with a score of 0.5;
p <0.001 is considered to have a very significant difference, indicated by ". x.", indicating that the subject has a very significant anti-aging effect, scored 0.7;
p <0.0001 is considered to have an extremely significant difference, indicated by ". x.", indicating that the subject has an extremely significant anti-aging effect, scored 1.0;
s53, immunofluorescence expression evaluation procedure: summarizing the immunofluorescence expression detection results in the step S44, calculating fluorescence intensity by using Image J, and expressing the results as Mean +/-SD; sequencing according to the fluorescence intensity, wherein the higher the numerical value is, the stronger the anti-aging effect of the test object is; plotting by using GraphPad Prism, and performing statistical analysis on comparison among groups by using Two-way ANOVA; all statistical analyses are two-tailed;
p <0.05 is considered to have a significant difference, indicated by "+", indicating that the test substance has a certain anti-aging effect and is scored as 0.3;
p <0.01 is considered to have a very significant difference, indicated by "+", indicating that the subject has significant anti-aging effect, with a score of 0.5;
p <0.001 is considered to have a very significant difference, indicated by ". x.", indicating that the subject has a very significant anti-aging effect, scored 0.7;
p <0.0001 is considered to have an extremely significant difference, indicated by ". x.", indicating that the subject has an extremely significant anti-aging effect, scored 1.0;
s54, evaluating the thickness of the dermis layer: summarizing the result of the thickness of the dermis layer in the step S45, comparing the thickness values of the sample group and the negative control group, and plotting by using GraphPad Prism; a score of 0 below the negative control group; a score of 1 above negative control;
s6, collecting all detection index scores according to the scoring standard of the step S5, wherein the scoring formula is as follows:
the raw material score is moisture value score multiplied by 0.1+ gene relative expression quantity score multiplied by 0.1333+ immunofluorescence protein intensity relative expression quantity score multiplied by 0.1333+ dermis thickness value score multiplied by 0.1;
wherein 0.1, 0.1333 and 0.1 are coefficients; the relative expression quantity scores of the genes are the sum of the relative expression quantity scores of four genes of MMP9, COL3A1, Elastin and Nrf 2; the relative expression quantity value of the intensity of the immunofluorescence protein is the sum of the relative expression quantity values of the intensity of two kinds of immunofluorescence proteins, namely Collagen VI and proCollagen I; screening out the raw materials with the best anti-aging effect according to the scores of the raw materials.
In the screening method for the anti-aging effect of the in-vitro 3D skin model of the cosmetic raw materials, in A3D full-skin model with an epidermal layer and a dermal layer, the implemented moisture value detection forms a physiological level evaluation index, at least one gene expression detection in the implemented gene expression detections of MMP9, COL3A1, Elastin and Nrf2 forms a transcriptomic level evaluation index, and at least one immunofluorescence expression detection in the implemented immunofluorescence expression detections of Collagen VI and ProCollagen I forms a proteomic level evaluation index; the performed thickness examination of the dermis layer constitutes a histological level evaluation index.
In the screening method for the anti-aging effect of the in-vitro 3D skin model of the cosmetic raw materials, in the step S1, a raw material sample with the water solubility of more than or equal to 1000 mug/mL is directly dissolved in a culture medium for subsequent experiments;
the subsequent experiments were carried out after a sample of the starting material having a solubility in water of < 1000. mu.g/mL was dissolved in dimethyl sulfoxide solvent.
In the screening method for the anti-aging efficacy of the in-vitro 3D skin model of the cosmetic raw materials, when dimethyl sulfoxide is used as the solvent, the volume percentage concentration of the solvent is not more than 5% of the total volume, and the volume proportion of the solvent in the control sample is the same as that in the experimental sample.
In the screening method for the anti-aging effect of the in-vitro 3D skin model of the cosmetic raw materials, in step S2, the 3D skin is purchased and is cultured in a special culture medium in a gas-liquid two-phase way, and all culture conditions are 37 +/-0.5 ℃ and (5 +/-1)% CO 2 Concentration, saturation humidity.
In the screening method for the anti-aging efficacy of the in-vitro 3D skin model of the cosmetic raw materials, in step S32, each raw material sample to be tested is provided with the administration concentration corresponding to CV90, and each concentration is provided with 2 or more multiple holes.
In the screening method for the anti-aging effect of the in-vitro 3D skin model of the cosmetic raw materials, in step S42, the moisture value is detected by adopting a probe of a Courage + Khazaka skin moisture tester to measure the moisture value content of the skin model.
In the screening method for the anti-aging effect of the in-vitro 3D skin model of the cosmetic raw materials, in the step S43, the gene expression detection of MMP9, COL3A1, Elastin and Nrf2 adopts a quantitative RT-PCR method.
In the screening method for the anti-aging effect of the in-vitro 3D skin model of the cosmetic raw materials, in the step S44, immunofluorescence expression of the Collagen VI and the proCollagen I is performed on the corresponding skin model through immunofluorescence detection to obtain immunofluorescence localization and expression quantity.
The screening method for the anti-aging effect of the in-vitro 3D skin model of the cosmetic raw materials comprises a model with four dimensionalities, so that the acting objects of the cosmetic raw materials cover the epidermis layer and the dermis layer of normal full-skin, and the anti-aging effect evaluation method of the cosmetic raw materials is constructed, belongs to a system type evaluation method, and has the advantages of being rapid and efficient; the method provides a quick and reliable evaluation method for early verification and screening of the anti-aging active raw materials of the skin care products, provides a reference basis for a compounding scheme of the anti-aging raw materials, and also provides an effective basis for further research of animal substitution experiments, development of the skin care products and efficacy verification in the skin care product industry.
Drawings
FIG. 1 shows the survival rates of T-skin tissues of subjects 1 to 4;
FIG. 2 shows the moisture content of the test substances 1 to 4 in the T-skin full-scale model;
FIG. 3a shows the relative expression level of the T-skin full-skin model gene MMP9 of the test substances 1-4;
FIG. 3b is a graph showing the relative expression levels of COL3A1 genes in the T-skin full-thickness model genes of the test substances 1 to 4;
FIG. 3c shows the relative expression levels of T-skin full-skin model genes Elastin of the test substances 1-4;
FIG. 3d is a diagram showing the relative expression amounts of T-skin full-skin model genes Nrf2 of the test substances 1 to 4;
FIG. 4a shows the relative expression of immunofluorescence of the T-skin full-thickness model protein Collagen VI and image J protein of the test substances 1-4;
FIG. 4b shows the relative expression of immunofluorescence of the T-skin whole skin model protein proCollagen I and image J protein of the test objects 1-4;
FIG. 5 is a graph showing the thickness measurement of the dermis layer of the T-skin full-skin model of the test substances 1-4;
fig. 6 is a flow chart of the screening method for anti-aging efficacy of the cosmetic raw material in-vitro 3D skin model of the present invention.
Detailed Description
In order that those skilled in the art will better understand the technical solution of the present invention, the following detailed description is given with reference to the accompanying drawings:
the reagents and materials used in the examples were all those conventionally available on the market without specific description.
First, experimental material
1. Experimental materials and instruments
1.13D Whole skin
The 3D full-skin is derived from a commercially available functionally stable human recombinant 3D full-skin model. In this example, the T-skin full skin model was obtained from Shanghai Spirono Biotech, Inc.
1.2 Primary reagents
(1)3D whole skin culture related reagents: the T-skin maintenance medium and the T-skin detection medium are purchased from Shanghai's Anfunuo Biotechnology Co., Ltd., and the DPBS is purchased from Gibco Co., USA;
(2) chemical reagents, thiazole blue (MTT), polyoxyethylene ether (triton x100), (bovine serum albumin) BSA were purchased from Sigma, usa; DMSO, hydrochloric acid, isopropanol, PBS, ethanol, xylene, paraffin, citric acid and sodium citrate are all purchased from chemical reagents of national medicine group, Inc.; DAPI staining solution and HE (hematoxylin and eosin) staining solution were purchased from Shanghai Bin Yuntian biotechnology, Inc.
(4) Quantitative RT-PCR detection: PRC primer was synthesized from Shanghai Biotech Ltd, SYBR was purchased from Roche reagent, GeneJET RNA Purification Kit was purchased from Thermo, and reverse transcription Kit PrimeScript TM RT reagent Kit (Perfect Real Time) was purchased from TaKaRa.
(5) And (3) performing immunofluorescence detection: antibodies to Collagen VI and proCollagen I were purchased from Abcam, respectively.
1.3 solution preparation
(1) Thiazole blue (MTT) solution: weighing 100mg of MTT powder, adding PBS20mL, performing vortex oscillation dissolution, performing filtration sterilization through a 0.22 mu m filter membrane, storing at-20 ℃ in a dark place, and unfreezing at 4 ℃ when in use;
(2)3D whole skin MTT assay: diluting the MTT solution to 0.3mg/mL in a T-skin detection culture medium;
(3)3D whole skin acidified isopropanol extract: hydrochloric acid was dissolved in isopropanol to a final concentration of 0.04 mol/mL.
(4) Sodium citrate: 10mM sodium citrate (PH6.0)
(5) Sealing liquid: 0.025% TritonX100+ 1.5% BSA
1.4 instruments
CO 2 Incubator (Thermo, usa), upright microscope (ZESS, germany), biosafety cabinet (Thermo, usa), high-speed cryocentrifuge (Thermo, usa), paraffin slicer (leica, germany), embedding machine (leica, germany), slide machine (leica, germany), Nanodrop (Thermo, usa), real-time fluorescence quantitative PCR
Figure BDA0003671199480000071
96(Roche, Switzerland), Courage + Khazaka skin moisture tester (Courage + Khazaka, Germany)
2. Raw material sample to be tested
The names of the raw material samples, i.e., the test substances, are shown in table 1:
numbering Sample name
1 Active A (methylene blue)
2 Active B (palmitoyl 5 peptide-4)
3 Active C (ascorbic acid)
4 Active D (palmitoyl hexapeptide-12)
5 Active E (carnosine)
6 Active substance F (acetyl 6 peptide-8)
TABLE 1
Second, 3D full skin model moisture value evaluation raw material anti-aging activity
Transporting the 3D full-skin model, placing into 6-well plate, stably culturing with 2ml culture medium per well under the conditions of 37 deg.C and 5% CO 2 And saturated humidity, and is used after stable culture for 12 h.
2.1 test substance 3D Total skin toxicity MTT assay
2.1.13D Whole skin MTT assay
Diluting each raw material sample (test substance) with culture medium to 3 concentrations (mass concentration of 10%, 5% and 1%, respectively), and adding 1-20mg/cm 2 On a 3D full skin model, 5% CO at 37 ℃ 2 And culturing for 3-10 days under the saturated humidity condition, changing every day, thoroughly washing with DPBS buffer solution to remove the sample and negative control on the surface of the full-skin model, slightly sucking the residual liquid on the surface of each full-skin model with a cotton swab, and performing subsequent MTT detection.
0.3mg/ml MTT working solution was added to the 6-well plate, and the whole skin model was transferred to the well to confirm that no air bubbles were present. The plates loaded with MTT solution and epidermal model were placed at 37 ℃ in 5% CO 2 Saturated humidity of CO 2 The incubator is used for 3 h. The whole skin model piece was removed with a scalpel, the epidermis model was gently detached from the dermis layer holder with forceps and turned over, the epidermis and the dermis layer were transferred into a 4ml centrifuge tube, 2ml of acidified isopropanol was added, the mixture was mixed with a vortex shaker, and formazan was extracted overnight at room temperature or after standing at 4 ℃ for 72 hours in the dark. Transfer 200 μ l of acidified isopropanol extract to 96-well plates and read absorbance (OD value) at 570nm, and each full skin model was tested in duplicate on 96-well plates.
2.1.23D skin cell viability analysis
Referring to fig. 1, the cell viability calculation formula is as follows:
the cell survival rate is equal to [ (As-Ab)/(Ac-Ab) ] x 100%
In the formula: as is the OD value of the experimental hole (containing 3D whole skin culture medium, MTT and the object to be tested);
ac is the OD value of control wells (medium with 3D whole skin, MTT, no test substance);
ab is blank well (medium without 3D whole skin and subject, MTT) OD value;
the calculation formula for the 90% viability rate (CV90) of 3D skin cells is:
Figure BDA0003671199480000081
in the formula: a is the minimum value of the cell viability rate exceeding 90%; c is the maximum value for which the cell viability is less than 90%; b and d represent the concentration of a and c corresponding to the cell activity in a-to-c correspondence;
calculating the cell viability of the test objects 1-4 in the table 1 according to a formula, selecting the concentration corresponding to CV90 as the anti-aging verification administration concentration, and referring to the T-skin whole-skin tissue survival rate of the test objects 1-4 in the figure 1.
2.23D Whole skin model moisture value determination
Referring to FIG. 2, the concentration of CV90 is selected for the test substance, and 1-20mg/cm is added to each well 2 On a 3D full skin model, 5% CO at 37 ℃ 2 And culturing for 3-10 days under the saturated humidity condition, changing every day, thoroughly washing with a DPBS buffer solution to remove the sample and the negative control on the surface of the whole-skin model, and slightly sucking residual liquid on the surface of each whole-skin model with a cotton swab. Moisture values were determined for the T-skin model using a Courage + Khazaka skin moisture tester probe, three times for each model, and averaged.
Three, 3D full skin model quantitative RT-PCR gene expression detection and evaluation of raw material anti-aging activity
Referring to FIGS. 3a, 3b, 3c and 3D, the concentration of CV90 was selected for the test subjects, and 200 μ L of CV90 was added to each well of the 3D epidermal model at 37 ℃ and 5% CO 2 Culturing for 3-10 days under saturated humidity condition, and thoroughly flushing with DPBS buffer solutionThe surface of the full skin model was washed to remove the sample and negative control, and the residual liquid on the surface of each full skin model was gently blotted with a cotton swab. The whole skin model piece was removed with a scalpel, and RNA of the skin model was extracted with the Kit GeneJET RNA Purification Kit, according to the Kit instructions. The RNA concentration was measured using a Nanodrop spectrophotometer, and the instructions were referred to in the specification. Reverse transcription Using PrimeScript TM RT reagent Kit (Perfect Real Time) Kit, instructions for use refer to the description. Using primer sequences for the genes in Table 2, using
Figure BDA0003671199480000091
Real-time PCR was performed at 96 (Roche).
beta-Acting forward primer GCAAAGACCTGTACGCCAAC
Beta-activating reverse primer GATCTTCATTGTGCTGGGTGC
MMP9 Forward primer GCAATGCTGATGGGAAACCC
MMP9 reverse primer AGAAGCCGAAGAGCTTGTCC
COL3A1 Forward primer ATGGTTGCACGAAACACACT
COL3A1 reverse primer CTTGATCAGGACCACCAATG
Elastin forward primer TCTGAGGTTCCCATAGGTTAGGG
Elastin reverse primer CTAAGCCTGCAGCAGCTCCT
Nrf2 forward primer AGTGGATCTGCCAACTACTC
Nrf2 reverse primer CATCTACAAACGGGAATGTCTG
TABLE 2
By
Figure RE-GDA0003764326540000092
The cycle threshold (Ct value) calculated by 96SW1.1 normalizes the Acting mRNA of each sample, and calculates the relative expression quantity of the genes of MMP9, COL3A1, Elastin and Nrf2 of the tested substances 1-4 on the 3D full-skin model. FIG. 3a shows the relative expression level of MMP9 in the T-skin model gene, and FIG. 3b shows the relative expression level of COL3A1 in the T-skin model gene; FIG. 3c shows the relative expression level of the T-skin full-skin model gene Elastin; FIG. 3d shows the relative expression level of T-skin whole skin model gene Nrf 2.
Fourth, 3D Whole skin model Collagen VI and ProCollagen I immunofluorescence assay evaluation of anti-aging Activity of raw materials
Referring to FIGS. 4a and 4b, the concentration of CV90 was selected for the test substance and 1-20mg/cm was added to each well 2 On a 3D full skin model, 5% CO at 37 ℃ 2 And culturing for 3-10 days under the saturated humidity condition, changing every day, thoroughly washing with a DPBS buffer solution to remove the sample and the negative control on the surface of the full-skin model, and slightly sucking residual liquid on the surface of each full-skin model with a cotton swab.
The 3D full skin model Collagen VI and ProCollagen I immunofluorescence detection procedures were as follows:
the whole skin model material was cut with a scalpel, fixed in 4% tissue fixative and washed with PBS. And (5) gradient ethanol dehydration. Soaking in pure xylene, and soaking the skin material in liquid paraffin overnight in paraffin embedding system. The thickness meter is adjusted as required, preferably to 5 to 12 μm. After the skin material was applied to the patch, 100% xylene was deparaffinized 2 times, and the patch was reconstituted in a gradient and soaked in distilled water. Antigen retrieval was performed at 97 ℃ in 10mM sodium citrate solution (pH 6.0). Blocking with 0.025% TritonX-100+ 1.5% BSA in PBS for 1-2 h. The antibodies were diluted in the proportions required by the instructions and literature. After blocking, 100-200. mu.l (blocking solution + antibody) was applied to the slide and sealed with PARAFILM sealing membrane. 4 ℃ Single antibody overnight. Wash 3 times with PBS. The antibody was diluted with PBS as a diluent according to the instructions for the secondary antibody, and after dilution, 200. mu.l (blocking solution + antibody) was added to the slide, sealed with PARAFILM seal film, and incubated for 1-2h at room temperature in the absence of light. Wash 3 times with PBS. Nuclei were counterstained with DAPI stain. Wash 3 times with PBS. Fluorescence channel FITC and DAPI (385nm) fluorescence recommended by selection instructions fluorescence was observed separately and fluorescence intensity was calculated using imageJ. FIG. 4a is the immunofluorescence and imageJ protein relative expression of the T-skin full skin model protein Collagen VI; FIG. 4b shows the relative expression of immunofluorescence and imageJ protein of the T-skin whole skin model protein proCollagen I.
Five, 3D full skin model dermis layer thickness detection and evaluation raw material anti-aging activity
Referring to FIG. 5, the concentration of CV90 was selected for the test substance, and 1-20mg/cm was added to each well 2 On a 3D full skin model, 5% CO at 37 ℃ 2 And culturing for 3-10 days under the saturated humidity condition, changing every day, thoroughly washing with DPBS buffer solution to remove the sample and negative control on the surface of the full-skin model, and slightly sucking the residual liquid on the surface of each full-skin model with a cotton swab.
The detection process of the thickness of the dermis layer of the 3D full-skin model comprises the following steps:
the skin model material was cut with a scalpel, fixed in 4% tissue fixative and washed with PBS. And (5) gradient ethanol dehydration. Soaking in pure xylene, and soaking the skin material in liquid paraffin overnight in paraffin embedding system. The thickness meter is adjusted as required, preferably to 5 to 12 μm. After the skin material is pasted, wax is removed by 100 percent dimethylbenzene for 2 times, and the skin material is subjected to gradient rehydration and is soaked in distilled water. Histological staining of skin sections was performed using HE (hematoxylin eosin) staining kit, with instructions for use according to the instructions. FIG. 5 shows the T-skin full-skin model true skin layer thickness values for subjects 1-4.
Sixthly, result analysis
The results are expressed as Mean ± SD using GraphPad Prism mapping. Comparisons between groups were analyzed using Two-way ANOVA statistics. All statistical analyses were two-tailed. p <0.05 was considered to have significant differences, indicated by ". x.", p <0.01 was considered to have very significant differences, indicated by ". x.", and p <0.001 was considered to have very significant differences, indicated by ". x.".
6.13D Total skin model moisture value evaluation raw material anti-aging activity detection result
6.1.1 test substance 3D Whole skin toxicity assay
The MTT detection results of the cell survival rates of the test substances (raw material samples) 1-4 are shown in figure 1, CV90 is calculated according to the obtained results and a formula, the corresponding concentration of CV90 of the sample to be detected on a 3D skin model is shown in table 3, and subsequent administration is carried out incubation according to the concentration.
Numbering CV90
1 5％
2 5％
3 1％
4 1％
5 1％
6 1％
TABLE 3
6.1.23D moisture determination of full skin model
Referring to FIG. 2, raw material samples corresponding to CV90 administration concentration were added to the sample group, cultured for 3 to 10 days, and after washing with buffer solution, moisture values were measured for T-skin full skin models by a Courage + Khazaka skin moisture tester probe, three times for each model, and an average value was obtained (see FIG. 6). Sequencing in sequence, wherein the score of the negative control group is 0; the score was 1 above the negative control group.
6.23 relative expression quantity evaluation raw material anti-aging activity detection result of whole skin model gene
6.2.1 test substance 3D Whole skin toxicity assay
The MTT detection results of the cell survival rates of the test substances (raw material samples) 1-4 are shown in figure 1, CV90 is calculated according to the obtained results and a formula, the corresponding concentration of CV90 of the sample to be detected on a 3D skin model is shown in table 3, and subsequent administration is carried out incubation according to the concentration.
6.2.23D full skin model gene relative expression detection
3D skin tissue was collected and the GeneJET RNA Purification Kit extracted the RNA from the skin model, according to the Kit instructions. The RNA concentration was measured using a Nanodrop spectrophotometer, and the instructions were referred to in the specification. Reverse transcription Using PrimeScript TM RT reagent Kit (Perfect Real Time) Kit, using the instruction reference. Using a primer set for the following genes
Figure RE-GDA0003764326540000111
Real-time PCR was performed at 96 (Roche). By
Figure RE-GDA0003764326540000112
The cycle threshold (Ct value) calculated at 96SW1.1 was normalized to the Acting mRNA of each sample and the relative expression level was calculated against the negative control group. The relative expression level of MMP9 gene is shown in FIG. 3a, the relative expression levels of COL3A1, Elastin and Nrf2 genes are shown in FIGS. 3b, 3c and 3d, and P<0.05,**P<0.01，***P<0.001，****P<0.0001 is the comparison of the sample group and the negative control group.
6.33 full skin model proteins Collagen VI and ProCollagen I immunofluorescence and imageJ protein relative expression evaluation raw material anti-aging Activity test results
6.3.1 test substance 3D Whole skin toxicity assay
The MTT detection results of the cell survival rates of the test substances (raw material samples) 1-4 are shown in figure 1, CV90 is calculated according to the obtained results and a formula, the corresponding concentration of CV90 of the sample to be detected on a 3D skin model is shown in table 3, and subsequent administration is carried out incubation according to the concentration.
6.3.23D full skin model immunofluorescence protein expression detection
3D whole skin tissues are collected and subjected to an immunofluorescence staining experiment. The antibodies were diluted in the proportions required by the instructions and literature and hybridized with each other. And (4) photographing by using a fluorescence microscope, calculating fluorescence intensity by using imageJ, and calculating the relative expression amount of the protein by using a negative control group as a control. The relative expression of Collagen VI protein is shown in fig. 3a, and the relative expression of proCollagen I protein is shown in fig. 3b, P <0.05, P <0.01, P <0.001, P <0.0001 for the sample group versus the negative control group.
6.43D full-skin model dermis thickness evaluation raw material anti-aging activity detection result
6.4.1 test substance 3D Whole skin toxicity assay
The MTT detection results of the cell survival rates of the test substances (raw material samples) 1-4 are shown in figure 1, CV90 is calculated according to the obtained results and a formula, the corresponding concentration of CV90 of the sample to be detected on a 3D skin model is shown in table 3, and subsequent administration is carried out incubation according to the concentration.
6.4.23D full skin model dermis layer thickness determination
3D skin tissues were collected, tissue embedded and paraffin sectioned for HE staining. Staining was performed as per the instructions, photographs were taken with an optical microscope, measurements were made with the measuring tool of computer software, the thickness values of the sample group and the negative control group were compared, and GraphPad Prism was used for plotting. Score 0 below negative control; the score was 1 above the negative control group.
6.5 comprehensive assessment results and analysis
All the test substances are evaluated according to the flow shown in fig. 6, the results of the water content values of the 3D full-skin model of the 4 test substances detected in the embodiment are summarized in table 4, the results of the experimental significance differences of the gene expression levels of the 3D full-skin model are summarized in table 5 in a one-to-one correspondence manner, the results of the experimental significance differences of the protein expression levels of the 3D full-skin model are summarized in table 6 in a one-to-one correspondence manner, the results of the dermal layer thickness values of the 3D full-skin model are summarized in table 7, the evaluation and scoring are performed according to the scoring standards of table 8, the anti-aging efficacy evaluation results of the test substances are shown in table 9, the water value dimension proportion is 0.1, the gene relative expression quantity dimension proportion is 0.3, the immunofluorescence protein intensity relative expression quantity dimension proportion is 0.1333, and the dermal layer thickness value proportion is 0.1; the weighted sum total is 1 (moisture value score × 0.1+ gene relative expression score × 0.1333+ immunofluorescence protein intensity relative expression score × 0.1333+ dermis layer thickness value score × 0.1 ═ 1); and sequencing according to the summary score results, wherein the test substances in the batch have the anti-aging effect, the efficacy strength is sequenced into a test substance 1, a test substance 2, a test substance 3, a test substance 4, a test substance 5 and a test substance 6, and the best anti-aging effect raw material is selected as an active substance A.
Numbering Moisture value (0 day) Moisture value (3-10 days) Score of
1 56.92 55.76 1
2 62.6 66.02 1
3 60.86 61.82 1
4 56.08 55.06 1
5 55.0 47.0 1
6 64.01 35.0 0
Control group 69.86 44.16 0
TABLE 4
Figure BDA0003671199480000131
TABLE 5
Number of Relative expression amount of CollagenVI fluorescent protein Relative expression amount of procollagen I fluorescent protein
1 **** **
2 *** **
3 ns ns
4 ns ns
5 ns ns
6 ns ns
TABLE 6
Numbering Thickness value (μm) Score of
1 338.7109±10.76942 1
2 298.9269±24.33836 1
3 323.2044±22.10997 1
4 153.6947±35.35029 0
5 200.0121±25.15014 0
6 180.1203±31.17027 0
Negative control group 249.1554±27.9168 0
TABLE 7
Figure BDA0003671199480000141
TABLE 8
Figure BDA0003671199480000142
TABLE 9
Referring to fig. 6, the method for screening the anti-aging efficacy of the in vitro 3D skin model of the cosmetic raw materials of the present invention includes the following steps:
s1, evaluating the solubility of the raw material sample and determining a dissolution scheme;
s2, culturing a 3D full-skin model;
s3, determining the detection concentration of the raw material sample by the activity detection of the 3D full-skin model, and comprising the following procedures:
s31, adding an experimental sample into the 3D full-skin model with the stable growth state in the step S2, wherein the experimental sample comprises a plurality of raw material samples with different concentration gradients, the control sample is a buffer solution without any sample, culturing is carried out for 3-10 days, and the survival rate of the 3D full-skin model tissue is detected by MTT;
s32, screening to obtain the administration concentration of the 3D whole skin model of the corresponding raw material sample at CV90, wherein the survival rate of the CV90 representing 3D skin tissues is 90%;
s4, a step of detecting moisture value of the 3D full-skin model, a step of detecting gene expression, a step of immunofluorescence examination and a step of detecting thickness of a dermis layer, wherein the steps comprise the following steps:
s41, taking the 3D full-skin with stable growth state in the step S2, setting a negative control group and a sample group, adding a buffer solution into the negative control group, adding a raw material sample with a CV90 corresponding to the administration concentration in the step S32 into the sample group, and culturing the negative control group and the sample group for 3-10 days respectively;
s42, collecting the 3D full-skin model cultured in the step S41, and carrying out the water content value expression detection of the 3D full-skin model;
s43, collecting the 3D full-skin model cultured in the step S41, and respectively carrying out gene expression detection of MMP9, COL3A1, Elastin and Nrf2 in the 3D full-skin model;
s44, collecting the normal 3D skin model cultured in the step S41, embedding paraffin and slicing, and respectively carrying out immunofluorescence expression detection of Collagen VI and proCollagen I in the 3D whole skin model;
s45, collecting the normal 3D skin model cultured in the step S41, embedding paraffin and slicing, and respectively detecting the thickness of a dermis layer in the 3D full-skin model;
s5, an evaluation step, specifically including the following:
s51, moisture value detection evaluation step: summarizing the water value detection results in the step S42, calculating the water value contents of the detection raw material sample group and the negative control group, comparing the water values of the sample group and the control group, and applying GraphPad Prism to map. A score of 0 below the negative control group; score 1 above negative control;
s52, procedure for evaluating relative gene expression level: summarizing the gene expression detection results in the step S43, calculating the gene expression ratio of the gene expression of the detection raw material sample group to the gene expression of the negative control group to obtain the relative expression quantity of the genes, and applying GraphPad Prism to map, wherein the result is expressed as Mean +/-SD; the comparison among the groups adopts Two-way ANOVA statistical analysis; all statistical analyses are two-tailed;
p <0.05 is considered to have a significant difference, indicated by "+", indicating that the test substance has a certain anti-aging effect and is scored as 0.3;
p <0.01 is considered to have a very significant difference, indicated by "+", indicating that the subject has significant anti-aging effect, with a score of 0.5;
p <0.001 is considered to have a very significant difference, indicated by ". x.", indicating that the subject has a very significant anti-aging effect, scored 0.7;
p <0.0001 is considered to have an extremely significant difference, indicated by "×", indicating that the subject has an extremely significant anti-ageing effect, with a score of 1.0;
s53, immunofluorescence expression evaluation step: summarizing the immunofluorescence expression detection results in the step S44, calculating fluorescence intensity by using Image J, and expressing the results as Mean +/-SD; sequencing according to the fluorescence intensity, wherein the higher the numerical value is, the stronger the anti-aging effect of the test object is; plotting by GraphPad Prism, and carrying out statistical analysis on comparison among groups by adopting Two-way ANOVA; all statistical analyses are two-tailed;
p <0.05 is considered to have a significant difference, indicated by "+", indicating that the test substance has a certain anti-aging effect and is scored as 0.3;
p <0.01 is considered to have a very significant difference, indicated by "+", indicating that the subject has significant anti-aging effect, with a score of 0.5;
p <0.001 is considered to have a very significant difference, indicated by ". x.", indicating that the subject has a very significant anti-aging effect, scored 0.7;
p <0.0001 is considered to have an extremely significant difference, indicated by ". x.", indicating that the subject has an extremely significant anti-aging effect, scored 1.0;
s54, evaluating the thickness of the dermis layer: the results of the dermal layer thickness in step S45 were summarized, and the moisture values of the sample group and the negative control group were compared and plotted using GraphPad Prism. A score of 0 below the negative control group; a score of 1 above negative control;
s6, collecting all detection index scores according to the scoring standard of the step S5, wherein the scoring formula is as follows:
the raw material score is equal to the moisture value score multiplied by 0.1+ gene relative expression quantity score multiplied by 0.1333+ immunofluorescence protein intensity relative expression quantity score multiplied by 0.1333+ dermis layer thickness value score multiplied by 0.1;
wherein 0.1, 0.1333 and 0.1 are coefficients; the relative expression quantity score of the gene is the sum of the relative expression quantity scores of four genes of MMP9, COL3A1, Elastin and Nrf 2; the relative expression quantity value of the intensity of the immunofluorescence protein is the sum of the relative expression quantity values of the intensity of two kinds of immunofluorescence proteins, namely Collagen VI and proCollagen I; the raw material score shows the anti-aging effect of the raw material, the higher the score is, the better the anti-aging effect is, and the raw material with the best anti-aging effect can be screened.
In A3D full-skin model with an epidermal layer and a dermal layer, the detected moisture value forms a physiological level evaluation index, at least one gene expression detection in the detected gene expression detections of MMP9, COL3A1, Elastin and Nrf2 forms a transcriptomic level evaluation index, and at least one immunofluorescence expression detection in the detected immunofluorescence expression detections of Collagen VI and proCollagen I forms a proteomic level evaluation index; the detected thickness examination of the dermis layer constitutes a histological level evaluation index.
In conclusion, the screening method for the anti-aging efficacy of the in-vitro 3D skin model of the cosmetic raw materials comprises a model with four dimensions, so that the acting objects of the cosmetic raw materials cover the epidermis layer and the dermis layer of normal skin, and the anti-aging efficacy evaluation method of the cosmetic raw materials is constructed, belongs to a system type evaluation method, and has the advantages of being rapid and efficient; the method provides a quick and reliable evaluation method for early verification and screening of the anti-aging active raw materials of the skin care products, provides a reference basis for a compounding scheme of the anti-aging raw materials, and also provides an effective basis for further research of animal substitution experiments, skin care product development and efficacy verification in the skin care product industry.
It should be understood by those skilled in the art that the above embodiments are only for illustrating the present invention and are not to be used as a limitation of the present invention, and that the changes and modifications of the above embodiments are within the scope of the appended claims as long as they are within the true spirit of the present invention.

Claims (10)

1. A screening method for anti-aging efficacy of a cosmetic raw material in-vitro 3D whole skin model is characterized in that the anti-aging activity of a target raw material is screened from four dimensions by using the 3D whole skin model, and the screening method specifically comprises the following steps:
s1, evaluating the solubility of the raw material sample and determining a dissolution scheme;
s2, culturing a 3D full-skin model;
s3, determining the detection concentration of the raw material sample by the activity detection of the 3D full-skin model, and comprising the following procedures:
s31, adding an experimental sample into the 3D full-skin model with the stable growth state in the step S2, wherein the experimental sample comprises a plurality of raw material samples with different concentration gradients, the control sample is a buffer solution without any sample, culturing is carried out for 3-10 days, and the survival rate of the 3D full-skin model tissue is detected by MTT;
s32, screening to obtain the administration concentration of the 3D whole skin model of the corresponding raw material sample at CV90, wherein the survival rate of the CV90 representing 3D skin tissues is 90%;
s4, a step of detecting moisture value of the 3D full-skin model, a step of detecting gene expression, a step of immunofluorescence examination and a step of detecting thickness of a dermis layer, wherein the steps comprise the following steps:
s41, taking the 3D full-skin with stable growth state in the step S2, setting a negative control group and a sample group, adding a buffer solution into the negative control group, adding a raw material sample with a CV90 corresponding to the administration concentration in the step S32 into the sample group, and culturing the negative control group and the sample group for 3-10 days respectively;
s42, collecting the 3D full-skin model cultured in the step S41, and carrying out the water content value expression detection of the 3D full-skin model;
s43, collecting the 3D full-skin model cultured in the step S41, and respectively carrying out gene expression detection of MMP9, COL3A1, Elastin and Nrf2 in the 3D full-skin model;
s44, collecting the normal 3D skin model cultured in the step S41, carrying out paraffin embedding and slicing, and then respectively carrying out immunofluorescence expression detection of Collagen VI and proCollagen I in the 3D full-skin model;
s45, collecting the normal 3D skin model cultured in the step S41, carrying out paraffin embedding and slicing, and then respectively carrying out detection on the thickness of the dermis layer in the 3D full-skin model;
s5, an evaluation step, specifically including the following:
s51, evaluation step of moisture value detection: summarizing the water value detection results in the step S42, calculating the water value contents of the detection raw material sample group and the negative control group, comparing the water values of the sample group and the negative control group, and applying GraphPad Prism mapping, wherein the score of the water value contents is 0 when the water value contents are lower than that of the negative control group; score 1 above negative control;
s52, procedure for evaluating relative gene expression level: summarizing the gene expression detection results in the step S43, calculating the gene expression ratio of the gene expression of the detection raw material sample group to the gene expression ratio of the negative control group to obtain the relative expression quantity of the genes, and mapping by using GraphPad Prism, wherein the result is expressed as Mean plus or minus SD; the comparison among the groups adopts Two-way ANOVA statistical analysis; all statistical analyses are two-tailed;
p <0.05 is considered to have a significant difference, indicated by an "+" indicating that the test substance has a certain anti-aging effect, and the score is 0.3;
p <0.01 is considered to have a very significant difference, indicated by an "+" indicating that the subject has significant anti-aging effect, and is scored at 0.5;
p <0.001 is considered to have a very significant difference, indicated by "×", indicating that the subject has a very significant anti-ageing effect, scoring 0.7;
p <0.0001 is considered to have an extremely significant difference, indicated by ". x.", indicating that the subject has an extremely significant anti-aging effect, scored 1.0;
s53, immunofluorescence expression evaluation step: summarizing the immunofluorescence expression detection results in the step S44, calculating fluorescence intensity by using Image J, and expressing the results as Mean +/-SD; sequencing according to the fluorescence intensity, wherein the higher the numerical value is, the stronger the anti-aging effect of the test object is; plotting by using GraphPad Prism, and performing statistical analysis on comparison among groups by using Two-way ANOVA; all statistical analyses are two-tailed;
p <0.05 is considered to have a significant difference, indicated by an "+" indicating that the test substance has a certain anti-aging effect, and the score is 0.3;
p <0.01 is considered to have a very significant difference, indicated by "+", indicating that the subject has significant anti-aging effect, with a score of 0.5;
p <0.001 is considered to have a very significant difference, indicated by "×", indicating that the subject has a very significant anti-ageing effect, scoring 0.7;
p <0.0001 is considered to have an extremely significant difference, indicated by ". x.", indicating that the subject has an extremely significant anti-aging effect, scored 1.0;
s54, evaluating the thickness of the dermis layer: summarizing the result of the thickness of the dermis layer in the step S45, comparing the thickness values of the sample group and the negative control group, and plotting by using GraphPad Prism; a score of 0 below the negative control group; score 1 above negative control;
s6, collecting all detection index scores according to the scoring standard of the step S5, wherein the scoring formula is as follows:
the raw material score is equal to the moisture value score multiplied by 0.1+ gene relative expression quantity score multiplied by 0.1333+ immunofluorescence protein intensity relative expression quantity score multiplied by 0.1333+ dermis layer thickness value score multiplied by 0.1;
wherein 0.1, 0.1333 and 0.1 are coefficients; the relative expression quantity scores of the genes are the sum of the relative expression quantity scores of four genes of MMP9, COL3A1, Elastin and Nrf 2; the relative expression quantity score of the intensity of the immunofluorescence protein is the sum of the relative expression quantity scores of the intensity of two kinds of immunofluorescence proteins, namely Collagen VI and proCollagen I; screening out the raw materials with the best anti-aging effect according to the scores of the raw materials.
2. The method for screening anti-aging efficacy of the in vitro 3D whole skin model of cosmetic raw materials according to claim 1, wherein in A3D whole skin model having an epidermal layer and a dermal layer, the moisture value detection performed constitutes a physiological level evaluation index, at least one of the gene expression detections of MMP9, COL3A1, Elastin, and Nrf2 performed constitutes a transcriptomic level evaluation index, and at least one of the immunofluorescence expression detections of Collagen VI and ProCollagen I performed constitutes a proteomic level evaluation index; the performed thickness examination of the dermis layer constitutes a histological level evaluation index.
3. The method for screening the anti-aging efficacy of the in vitro 3D whole skin model of the cosmetic raw materials according to claim 1, wherein in step S1, a raw material sample with the water solubility of more than or equal to 1000 μ g/mL is directly dissolved in a culture medium for subsequent experiments;
the raw material sample with the solubility of less than 1000 mu g/mL in water is dissolved by a dimethyl sulfoxide solvent and then is subjected to subsequent experiments.
4. The method for screening anti-aging efficacy of in vitro 3D whole skin model of cosmetic raw material according to claim 3, wherein the volume percentage concentration of the solvent is not more than 5% of the total volume when dimethyl sulfoxide is used as the solvent, and the volume ratio of the solvent in the control sample and the experimental sample is the same.
5. The method for screening anti-aging effects of in vitro 3D whole skin model using cosmetic raw materials according to claim 1, wherein in step S2, the 3D whole skin model is purchased with a special culture medium and cultured in gas-liquid two-phase, and all culture conditions are 37 ± 0.5 ℃ and (5 ± 1)% CO 2 Concentration, saturation humidity.
6. The method for screening anti-aging efficacy of the in vitro 3D whole skin model of cosmetic raw materials according to claim 1, wherein in step S31, each raw material sample to be tested is provided with the administration concentration corresponding to CV90, and each concentration is provided with 2 or more multiple holes.
7. The method for screening anti-aging efficacy of the in vitro 3D whole skin model of the cosmetic raw material according to claim 1, wherein the buffer solution is DPBS buffer solution in step S41.
8. The method for screening the anti-aging efficacy of the in vitro 3D whole skin model of the cosmetic raw material according to claim 1, wherein in step S42, the moisture value is measured by using a Courage + Khazaka skin moisture tester probe to measure the moisture value content of the skin model.
9. The method for screening the anti-aging efficacy of the in vitro 3D whole skin model of the cosmetic raw material according to claim 1, wherein in the step S43, the gene expression detection of MMP9, COL3A1, Elastin and Nrf2 adopts a quantitative RT-PCR method.
10. The method for screening the anti-aging efficacy of the in vitro 3D whole skin model of the cosmetic raw materials according to claim 1, wherein in the step S44, the immunofluorescence expression of Collagen VI and proCollagen I is performed on the corresponding skin model through immunofluorescence detection to obtain the immunofluorescence localization and the expression quantity.
CN202210608302.1A 2022-05-31 2022-05-31 Screening method for anti-aging efficacy of in-vitro 3D whole skin model of cosmetic raw materials Pending CN114958953A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117789828A (en) * 2024-02-28 2024-03-29 四川大学华西医院 Anti-aging target spot detection system based on single-cell sequencing and deep learning technology

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117789828A (en) * 2024-02-28 2024-03-29 四川大学华西医院 Anti-aging target spot detection system based on single-cell sequencing and deep learning technology
CN117789828B (en) * 2024-02-28 2024-04-30 四川大学华西医院 Anti-aging target spot detection system based on single-cell sequencing and deep learning technology

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