Probiotic function evaluation method, model and application thereof

Abstract

The invention relates to a probiotic function evaluation method and model and application thereof. The method comprises the following steps: evaluating the tolerance of the probiotics through an in-vitro digestion tolerance model, evaluating the adhesion capacity of the probiotics through an intestinal organ model, and evaluating the inhibition effect of the probiotics on the adhesion and / or invasion of pathogenic bacteria through the intestinal organ model. The intestinal barrier repairing capacity and / or the intestinal inflammation relieving capacity are / is evaluated through the intestinal organ injury model. According to the method, the intestinal organ model is utilized, the specific action mechanism of the probiotics in relieving inflammation and repairing the intestinal barrier can be deeply explored, a functional verification method with higher scientificity and clinical transformation value is provided, the real digestion process of the human body can be simulated, and the method is suitable for large-scale popularization and application. A more comprehensive and accurate probiotic tolerance evaluation method is provided, the authenticity and transformability of experimental results are improved, and an efficient and accurate bacterial function evaluation method is constructed.

Description

Technical Field

[0001] The present invention relates to the field of microbial technology, and in particular to a method, model and application for evaluating the functions of probiotics. Background Art

[0002] Probiotics are a class of active microorganisms beneficial to the host. Colonized in the human intestine, they can regulate the normal intestinal flora of the human body, maintain the balance of the internal microecosystem, promote food digestion and relieve constipation, etc., and can produce definite health effects, thereby improving the microecological balance of the host and playing a beneficial role. With the understanding and research on the relationship between the intestinal flora and human health, probiotics have received increasing attention.

[0003] However, for the evaluation of probiotics, the practices in different countries are not the same, and there is no unified standard. In addition, the research and scientific evaluation of the efficacy of probiotics is a long-term, rigorous and scientific process, and there are also many difficulties. For example, in the process of evaluating the functions of probiotics, traditional intestinal cell models and animal models are mainly used. However, they each have some obvious defects, which limit the comprehensiveness and accuracy of the research results. Although traditional intestinal cell models (such as Caco-2 cells) are often used to study intestinal functions, they cannot fully reproduce the diversity and complex environment of the real human intestine, lack cell-cell interactions, and cannot simulate the dynamic changes of the intestine and the physical and biochemical conditions in the actual intestinal environment, such as pH value, enzyme secretion and mucus layer. These defects affect the comprehensive evaluation of the functions of probiotics. On the other hand, there are also obvious species differences in using animal models to study probiotics. For example, there are differences in intestinal length, pH value and microbiota. These differences make it difficult to directly apply animal experiments to humans. In addition, the intestinal flora composition of animals is different from that of humans, resulting in different functions and effects of probiotics in different species, which limits the extrapolation of experimental results. In addition, the intestinal immune response of animal models may be quite different from that of humans, and it is also difficult to fully reflect the true situation of the human intestinal immune system. These defects make it difficult to directly apply the results obtained from traditional intestinal models and animal experiments to the research of human health. Therefore, there is an urgent need to develop new methods for evaluating the functions of probiotics. Summary of the Invention

[0004] To solve the above technical problems, the present invention provides a method for evaluating the functions of probiotics. By using the intestinal organoid model, it deeply explores the specific action mechanisms of probiotics in relieving inflammation and repairing the intestinal barrier, and provides a more scientific and clinically translatable function verification method.

[0005] The first aspect of the present invention is to provide a method for evaluating the functions of probiotics, including the following steps: S1. Inoculate probiotics into a basal medium and culture until the logarithmic phase. After centrifugation, adjust the pH to 7 - 7.8, and filter to remove live bacteria to obtain a conditioned medium. S2. Pretreat the intestinal organoid model with the conditioned medium (co - incubate the conditioned medium and the organoids in an environment of 37°C and 5% CO2 for 6 h), and then add IFN - γ at a concentration of 100 - 400 ng / mL for treatment to obtain an intestinal organoid barrier injury model. S3. Measure the trans - epithelial electrical resistance value and / or intestinal barrier genes of the intestinal organoid barrier injury model to evaluate the intestinal barrier repair ability of the probiotics, and / or detect the inflammatory genes of the intestinal organoid barrier injury model to evaluate the intestinal inflammation alleviating ability of the probiotics.

[0006] In some embodiments of the present invention, in step S2, the concentration of IFN - γ is 150 - 250 ng / mL; preferably, the concentration of IFN - γ is 200 ng / mL.

[0007] In some embodiments of the present invention, in step S2, the treatment time of IFN - γ is 12 - 24 h; preferably, the treatment time of IFN - γ is 24 h.

[0008] In some embodiments of the present invention, in step S3, the trans - epithelial electrical resistance value is the TEER value.

[0009] In some embodiments of the present invention, in step S3, the inflammatory genes include at least one of IL - 1β, IL - 6, CCL3, TGF - β1, and IL - 10, and the intestinal barrier genes include at least one of ZO - 1, E - cadherin, MUC2, Occludin, JAM - A, and CLDN2 genes.

[0010] In some embodiments of the present invention, the intestinal barrier genes are tight junction genes.

[0011] In some embodiments of the present invention, the following steps are further included: conduct artificial gastric juice tolerance experiments, artificial intestinal juice tolerance experiments, and artificial bile salt tolerance experiments on the probiotics respectively to evaluate the digestive tolerance of the probiotics.

[0012] In some preferred embodiments of the present invention, the artificial gastric juice contains 0.5% w / v NaCl and 0.3% w / v pepsin, pH = 3.0; and / or In some embodiments of the present invention, the concentration of the artificial bile salt is 0.2% - 0.3%.

[0013] In some embodiments of the present invention, the following steps are further included: adding the probiotic and the pathogenic bacterium into the intestinal organoid model for co-incubation, calculating the number of adherent pathogenic bacteria and / or the pathogenic bacteria adhesion rate, and / or calculating the number of invasive pathogenic bacteria and / or the pathogenic bacteria invasion rate, and evaluating the inhibitory effect of the probiotic on the adhesion and / or invasion of pathogenic bacteria.

[0014] In some embodiments of the present invention, the following steps are further included: adding the probiotic into the intestinal organoid model for incubation, calculating the number of adherent probiotics and / or the adhesion rate, and evaluating the intestinal adhesion ability of the probiotic.

[0015] In some embodiments of the present invention, the following steps are specifically included: Evaluating the tolerance of probiotics through an in vitro digestion tolerance model: respectively evaluating the digestion tolerance of the probiotics through an artificial gastric juice tolerance experiment, an artificial intestinal juice tolerance experiment, and an artificial bile salt tolerance experiment; Evaluating the adhesion ability of probiotics through an intestinal organoid model: adding the probiotic into the intestinal organoid model for incubation, calculating the number of adherent probiotics and / or the adhesion rate, and evaluating the intestinal adhesion ability of the probiotic; Evaluating the inhibitory effect of probiotics on the adhesion and / or invasion of pathogenic bacteria through an intestinal organoid model: adding the probiotic and the pathogenic bacterium into the intestinal organoid model for co-incubation, calculating the number of adherent pathogenic bacteria and / or the pathogenic bacteria adhesion rate, and / or calculating the number of invasive pathogenic bacteria and / or the pathogenic bacteria invasion rate, and evaluating the inhibitory effect of the probiotic on the adhesion and / or invasion of pathogenic bacteria; Evaluating the intestinal barrier repair ability and / or the intestinal inflammation alleviation ability through an intestinal organoid injury model: S1. (Preparing a conditioned medium) Inoculating the probiotic into a basal medium and culturing it to the logarithmic phase, adjusting the pH to 7 - 7.8 after centrifugation, and filtering to remove live bacteria to obtain a conditioned medium; S2. (Constructing an intestinal organoid barrier injury model) Pretreating the intestinal organoid model with the conditioned medium, and then adding IFN-γ with a concentration of 100 - 400 ng / mL for treatment to obtain an intestinal organoid barrier injury model; S3. (Evaluating the intestinal barrier repair ability and / or the intestinal inflammation alleviation ability of the probiotic) Measuring the transcutaneous resistance value and / or the intestinal barrier genes of the intestinal organoid barrier injury model to evaluate the intestinal barrier repair ability of the probiotic, and / or detecting the inflammatory genes of the intestinal organoid barrier injury model to evaluate the intestinal inflammation alleviation ability of the probiotic.

[0016] The second aspect of the present invention is to provide a model for evaluating the functions of probiotics, including: An in vitro digestion tolerance evaluation model for respectively conducting an artificial gastric juice tolerance experiment, an artificial intestinal juice tolerance experiment, and an artificial bile salt tolerance experiment on probiotics to evaluate the digestion tolerance of probiotics; Probiotic intestinal adhesion evaluation model, which is used to calculate the number of adhered probiotics and / or the probiotic adhesion rate by incubating probiotics in an intestinal organoid model, and evaluate the intestinal adhesion ability of probiotics; Probiotic inhibition of pathogenic bacteria intestinal adhesion and / or invasion evaluation model, which is used to co-incubate the probiotics and pathogenic bacteria in an intestinal organoid model, calculate the number of adhered pathogenic bacteria and / or the pathogenic bacteria adhesion rate, and / or calculate the number of invasive pathogenic bacteria and / or the pathogenic bacteria invasion rate, and evaluate the inhibitory effect of the probiotics on the adhesion and / or invasion of pathogenic bacteria; Intestinal organoid injury model, which is used to evaluate the intestinal barrier repair ability and / or intestinal inflammation alleviation ability of probiotics through an IFN-γ-induced intestinal organoid model.

[0017] The third aspect of the present invention is to provide the application of the above methods or models in the evaluation of probiotic functions. According to the evaluation method, it is obtained that L. paracasei 207-27 and B. breve 207-1 have high digestive tolerance, intestinal adhesion ability, intestinal barrier repair ability and intestinal inflammation alleviation ability.

[0018] The above technical solutions of the present invention have the following advantages compared with the prior art: (1) The present invention uses an intestinal organoid model to deeply explore the specific action mechanism of probiotics in alleviating inflammation and repairing the intestinal barrier, and provides a more scientific and clinically translatable function verification method.

[0019] (2) The present invention has developed a continuous digestion model. By connecting the simulated environments of the oral cavity, stomach and intestinal stages, standardized pH values, enzyme concentrations and bile salt contents are established to more comprehensively evaluate the digestive tolerance and activity changes of probiotics. This continuous digestion method can not only screen out strains with strong tolerance for the research and development of functional probiotics, but also provide guidance for formulation development (such as acid-resistant coating and sustained-release capsules), and deeply explore the action mechanism of probiotics. By designing in vitro continuous digestion tests of the oral cavity, stomach and intestine to simulate the real human digestion process, a more comprehensive and accurate probiotic tolerance evaluation method is provided.

[0020] (3) The present invention uses an intestinal organoid model that is closer to the in vivo environment to evaluate the adhesion ability of probiotics, overcomes the limitations of traditional methods, and improves the authenticity and transformability of experimental results.

[0021] (4) With the help of the intestinal organoid model, the present invention can systematically evaluate the inhibitory effect of probiotics on the invasion and adhesion of pathogenic bacteria, and provide new research tools and evaluation means for the anti-infection function of probiotics.

[0022] (5) The present invention combines in vitro digestion simulation, intestinal organoid models, and multi-level functional evaluation to establish an integrated and standardized probiotic functional evaluation platform, providing an efficient and accurate technical means for probiotic screening and functional research. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] To make the content of the present invention easier to understand clearly, the following further details the present invention according to specific embodiments of the present invention in conjunction with the drawings, where Figure 1 is the result graph of artificial gastric juice tolerance in Example 1 of the present invention; among them, different letters (such as a, b, c) marked indicate that there are statistically significant differences between groups ( P < 0.05 ), and the same letter indicates no statistically significant difference; Figure 2 is the result graph of artificial intestinal juice tolerance in Example 1 of the present invention; among them, different letters (such as a, b, c) marked indicate that there are statistically significant differences between groups ( P < 0.05 ), and the same letter indicates no statistically significant difference; Figure 3 is the result graph of artificial bile salt tolerance in Example 1 of the present invention; among them, different letters (such as a, b, c) marked indicate that there are statistically significant differences between groups ( P < 0.05 ), and the same letter indicates no statistically significant difference; Figure 4 is the probiotic adhesion rate in Example 2 of the present invention; among them, different letters (such as a, b, c) marked indicate that there are statistically significant differences between groups ( P < 0.05 ), and the same letter indicates no statistically significant difference; Figure 5 is the scanning electron micrograph of the adhesion of probiotics to single cells of intestinal organoids in Example 2 of the present invention; Figure 6 is the effect of IFN-γ on the activity of intestinal organoids in Example 3 of the present invention; where *** indicates a significant difference compared to the NC group, and P < 0.001 ; Figure 7 is the expression level of related factors after IFN-γ treatment for 12 h in Example 3 of the present invention; where "*" indicates a significant difference compared to the NC group, and P < 0.05 , "**" indicates a significant difference compared to the NC group, and P < 0.01 ; Figure 8 is the expression level of related factors after IFN-γ treatment for 24 h in Example 3 of the present invention; where "*" indicates a significant difference compared to the NC group, and P < 0.05 , "***" indicates a significant difference compared to the NC group, andP < 0.001 ; Figure 9 is the effect of the lactic acid bacteria conditioned medium on TEER and FITC changes in Example 4 of the present invention; (A) Change in transendothelial electrical resistance value during the growth stage, (B) Change in transendothelial electrical resistance value during the treatment period, where, "**" indicates a significant difference compared with the IFN-γ group, and P < 0.01 、"***" indicates a significant difference compared with the IFN-γ group, and P < 0.001 , (C) Effect of the treatment on the permeability of fluorescein isothiocyanate, "***" indicates a significant difference compared with the NC group, and P < 0.001、 "" indicates a significant difference compared with the IFN-γ group, and P < 0.001 ; Figure 10 is the change in the expression level of tight junction factors in Example 5 of the present invention; where, "**" indicates a significant difference compared with the NC group, and P < 0.01 、"##" indicates a significant difference compared with the IFN-γ group, and P < 0.01 、"" indicates a significant difference compared with the IFN-γ group, and P < 0.001 ; Figure 11 is the change in the expression level of inflammatory factors in Example 5 of the present invention; where, "*" indicates a significant difference compared with the NC group, and P < 0.05 、"**" indicates a significant difference compared with the NC group, and P < 0.01 、"***" indicates a significant difference compared with the NC group, and P < 0.001 , "##" indicates a significant difference compared with the IFN-γ group, and P < 0.01 、"" indicates a significant difference compared with the IFN-γ group, and P < 0.001 ; Figure 12 is the inhibitory effect of lactic acid bacteria on the adhesion of Clostridium perfringens to colon organoids in Example 6 of the present invention; where, (A) Clostridium perfringens: lactic acid bacteria = 1:1; (B) Clostridium perfringens: lactic acid bacteria = 1:10; (C) Clostridium perfringens: lactic acid bacteria = 1:100; where, "**" indicates a significant difference compared with the NC group, and P < 0.01 、"***" indicates a significant difference compared with the NC group, and P < 0.001 、"#" indicates a significant difference compared with the LGG group, and P < 0.05, "##" indicates a significant difference compared with the LGG group, and P < 0.01 、"" indicates a significant difference compared with the LGG group, and P < 0.001 ; Figure 13It shows the inhibitory effect of lactic acid bacteria on the adhesion of invasive Escherichia coli to colon organoids in Example 6 of the present invention; wherein, (A) Invasive Escherichia coli: Lactobacillus = 1:1; (B) Invasive Escherichia coli: Lactobacillus = 1:10; (C) Invasive Escherichia coli: Lactobacillus = 1:100; wherein, "*" indicates a significant difference compared with the NC group, and P < 0.05 ,"**" indicates a significant difference compared with the NC group, and P < 0.01 ,"***" indicates a significant difference compared with the NC group, and P < 0.001 ,"#" indicates a significant difference compared with the LGG group, and P < 0.05 ,"" indicates a significant difference compared with the LGG group, and P < 0.001 ; Figure 14 It shows the inhibition of Clostridium perfringens and invasive Escherichia coli by lactic acid bacteria in Example 7 of the present invention; wherein, (A) The inhibitory effect of six lactic acid bacteria on the invasion of Clostridium perfringens into intestinal epithelial cells; (B) The inhibitory effect of six lactic acid bacteria on the invasion of invasive Escherichia coli into intestinal epithelial cells; wherein, "*" indicates a significant difference compared with the NC group, and P < 0.05 ,"***" indicates a significant difference compared with the NC group, and P < 0.001 ,"" indicates a significant difference compared with the LGG group, and P < 0.001 . Detailed implementation methods

[0024] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments, so that those skilled in the art can better understand the present invention and be able to implement it, but the exemplified embodiments are not intended to limit the present invention.

[0025] Example 1: Evaluation of the in vitro simulated digestion tolerance of probiotics In this example, an in vitro simulated digestion tolerance model of probiotics was constructed, and an in vitro continuous digestion test of the oral cavity, stomach, and intestine was designed to evaluate the digestion tolerance of probiotics.

[0026] 1.1 Artificial gastric juice tolerance experiment 1.1.1 Experimental procedure: The probiotic strains were inoculated at 2% into the corresponding broths and cultured overnight at 37 °C under aerobic / anaerobic conditions; then the cultures were centrifuged (5 °C, 6000 g, 20 min), resuspended in PBS buffer (pH = 7.4) and washed twice, and the bacterial suspension was collected by centrifugation (5 °C, 12000 g, 5 min) and resuspended in 10 ml of artificial gastric juice (0.5% w / v NaCl; 0.3% w / v pepsin) and incubated for 3 h. The artificial gastric juice was adjusted to pH = 3.0 with HCl. 1 ml of the sample was taken before and after incubation and serially diluted 10-fold with PBS buffer (pH = 7.4). It was spread on MRS agar and incubated under anaerobic conditions at 37 °C for 24 h. By comparing the final viable cell count after 3 h with the initial viable cell count at 0 h, the result was expressed as the percentage of survival. The calculation formula was: survival rate = N1 / N0 × 100%; where, N1 was the total number of viable bacteria after 3 h of treatment, and N0 was the total number of viable bacteria before treatment.

[0027] 1.1.2 Experimental results: Through the simulated artificial gastric juice digestion experiment, as Figure 1 shown, the results showed that the survival rates of each strain after treatment with artificial gastric juice were in turn: L. paracasei 207-27 was 96.28%, L. rhamnosus 203-10 was 93.64%, B. breve 207-1 was 90.72%, the standard strain LGG was 88.89%, L. paracasei 329-30 was 87.33%, L. rhamnosus 208-18 was 84.76%, and B. longum 199 was 79.09%. Statistical analysis showed that the survival rates of L.rhamnosus 203-10, L. paracasei 207-27 and B. breve 207-1 were significantly higher than those of the standard strain LGG. Although the survival rates of L. rhamnosus 208-18, L. paracasei 329-30 and B. longum 199 were lower than those of the standard strain LGG, they were all greater than 50%. In summary, L. paracasei 207-27, L. rhamnosus 203-10 and B. breve 207-1 showed extremely strong tolerance to artificial gastric juice.

[0028] 1.2 Artificial intestinal juice tolerance experiment 1.2.1 Experimental procedure: 10 ml of MRS broth was inoculated with probiotics (lactic acid bacteria) at 2% (v / v) and cultured overnight under anaerobic conditions at 37 °C; then the culture was centrifuged (5 °C, 6000 g, 20 min), resuspended in PBS buffer (pH = 7.4) and washed twice, and the bacterial suspension was collected by centrifugation (5 °C, 12000 g, 5 min) and resuspended in 10 ml of artificial intestinal fluid (prepared according to the Chinese Pharmacopoeia) and incubated for 8 h. The artificial intestinal fluid was adjusted to pH = 6.8 with HCl. 1 ml of the sample was taken before and after incubation and serially diluted 10-fold with PBS buffer (pH = 7.4). It was spread on MRS agar and incubated under anaerobic conditions at 37 °C for 24 h. By comparing the final viable count after 8 h with the initial viable count at 0 h, the result was expressed as the percentage of survival. The calculation formula was: survival rate = N2 / N0 × 100%; where N2 was the total number of viable bacteria after 8 h of treatment, and N0 was the total number of viable bacteria before treatment.

[0029] 1.2.2 Experimental results: Through the simulated artificial intestinal fluid digestion experiment, as Figure 2 shown, the results indicated that the survival rates of each strain after treatment with artificial intestinal fluid were as follows: L. paracasei 207-27 was 109.52%, B. breve 207-1 was 91.48%, the standard strain LGG was 90.88%, L. paracasei 329-30 was 83.32%, L. rhamnosus 208-18 was 76.27%, L. rhamnosus 203-10 was 72.89%, and B. longum 199 was 51.04%. Statistical analysis showed that the survival rates of L. paracasei 207-27 and B. breve 207-1 were both higher than that of the standard strain LGG, among which the increase of L. paracasei 207-27 compared with the standard strain LGG was significant (P < 0.001), while there was no significant difference in the survival rate between B. breve 207-1 and the standard strain LGG. Although the survival rates of L. rhamnosus 203-10, L. rhamnosus 208-18, L. paracasei 329-30 and B. longum 199 were lower than that of the standard strain LGG, they were all higher than 50%. In summary, L. paracasei 207-27 and B. breve 207-1 showed extremely high tolerance to artificial intestinal fluid digestion.

[0030] 1.3 Artificial bile salt tolerance experiment 1.3.1 Experimental procedure: Inoculate the overnight culture of each strain at 2% (v / v) into the broth containing 0.3%, 0.2%, 0% (w / v) bile salts. Incubate the culture anaerobically at 37 °C for 24 h. Take 1 ml of the sample before and after incubation and perform 10-fold serial dilutions using PBS buffer (pH = 7.4). Spread the dilutions on MRS agar and incubate anaerobically at 37 °C for 24 h. By comparing the final viable cell count after 24 h of treatment with the initial viable cell count at 0 h, the result is expressed as the percentage of survival. The calculation formula is: survival rate = N3 / N0 × 100%; where N3 is the total number of viable bacteria after 24 h of treatment, and N0 is the total number of viable bacteria before treatment.

[0031] 1.3.2 Experimental results: As Figure 3As shown, the experimental results indicate that in an environment of 0.2% artificial bile salts (Qingdao Haibo - HB8290), the tolerance of each strain from high to low is as follows: 76.38% of L. paracasei 207 - 27, 70.76% of the standard strain LGG, 69.79% of B. breve 207 - 1, 67.92% of L. rhamnosus 203 - 10, 63.52% of L. rhamnosus 208 - 18, 61.90% of L. paracasei 329 - 30, and 56.99% of B. longum 199. Statistical analysis shows that the survival rate of L. paracasei 207 - 27 is significantly higher than that of the standard strain LGG (P < 0.01). Although the survival rates of L. rhamnosus 203 - 10, L. rhamnosus 208 - 18, L. paracasei 329 - 30, and B. longum 199 are lower than that of the standard strain LGG, they are all greater than 50%, showing a certain degree of tolerance. In an environment of 0.3% artificial bile salts, the tolerance of each strain from high to low is as follows: 64.79% of L. paracasei 207 - 27, 62.53% of B. breve 207 - 1, 59.23% of the standard strain LGG, 58.96% of L. rhamnosus 208 - 18, 56.67% of L. rhamnosus 203 - 10, 54.83% of L. paracasei 329 - 30, and 47.33% of B. longum 199. The results of statistical analysis indicate that the survival rates of L. paracasei 207 - 27 and B. breve 207 - 1 are significantly higher than that of the standard strain LGG (P < 0.05). Although the survival rates of L. rhamnosus 203 - 10, L. rhamnosus 208 - 18, and L. paracasei 329 - 30 are lower than that of the standard strain LGG, they are all greater than 50%, showing good tolerance. Among them, B. longum 199 has the worst tolerance to 0.3% artificial bile salts, with a survival rate of only 47.33%.

[0032] Probiotics need to face a complex environment when passing through the human digestive tract, including oral enzymatic hydrolysis, gastric juice acidity, and the action of small intestinal bile salts and digestive enzymes. Their tolerance directly affects their functionality. Traditional research methods usually simulate the environment of a single stage (such as gastric juice or intestinal juice) alone, such as acid tolerance tests and bile salt tolerance tests. Although they have reference value, it is difficult to comprehensively reflect the survival and activity changes of probiotics during the entire digestion process. With technological progress, modern in vitro simulated digestive systems (such as static models and dynamic gastrointestinal models) have gradually been applied. Among them, the dynamic simulated digestive system (D-SIMs) can simulate the dynamic changes of the digestive tract, but its application is limited due to complex equipment and high costs. To solve this problem, this embodiment developed a continuous digestion model. By connecting the simulated environments of the oral, gastric, and intestinal stages, standardized pH values, enzyme concentrations, and bile salt contents were established to more comprehensively evaluate the digestive tolerance and activity changes of probiotics. This continuous digestion method can not only screen out strains with strong tolerance for the research and development of functional probiotics, but also provide guidance for formulation development (such as acid-resistant coating and sustained-release capsules), and deeply explore the mechanism of action of probiotics.

[0033] Previous studies on the tolerance of probiotics to the oral cavity, gastric juice, and intestinal juice mainly focused on single environments or in vitro models, lacking research on continuous digestion systems. In this embodiment, by constructing an in vitro simulated digestive tolerance model for probiotics, it is possible to simulate the real human digestion process and provide a more comprehensive and accurate method for evaluating probiotic tolerance.

[0034] Example 2: Evaluation of Probiotic Intestinal Adhesion Ability In this embodiment, the adhesion of probiotics (lactic acid bacteria) to the intestinal organoid model was evaluated by the spread plate counting method.

[0035] 2.1 Experimental procedure: Add 1 ml of lactic acid bacteria or bifidobacteria suspension (1×10 9 CFU / ml) or an equal volume of DMEM solution (control) to the washed monolayer of intestinal organoids, and incubate at 37 °C for 2 h. Then wash the monolayer three times with sterile D-PBS to remove unbound bacteria on the surface. Add 1 ml of sterile D-PBS to the culture plate, resuspend the adhered cells to make a bacterial suspension. Gradient dilute the bacterial suspension with sterile D-PBS and spread it on MRS agar (set 3 replicates for each gradient), and culture it at 37 °C for 24 h. Calculate the total number of bacteria in the cell suspension according to the plate counting results. The adhesion rate calculation formula is as follows: Adhesion rate (CFU / cell) = number of lactic acid bacteria adhered per well (CFU) / total number of cells per well × 100%.

[0036] 2.1 Experimental results: As Figure 4As shown, the experimental results show that the adhesion rates of each lactic acid bacterium from high to low are as follows: 8.20 bacterial / cell of L. paracasei 207-27, 5.70 bacterial / cell of B. breve 207-1, 5.20 bacterial / cell of L. paracasei 329-30, 4.90 bacterial / cell of L. rhamnosus 203-10, 4.70 bacterial / cell of the standard strain LGG, 4.00 bacterial / cell of B. longum 199, and 3.80 bacterial / cell of L. rhamnosus 208-18. Statistical analysis shows that the adhesion rates of L. rhamnosus 203-10, L. paracasei 207-27, L. paracasei 329-30, and B. breve 207-1 are all higher than that of the standard strain LGG, among which the adhesion rates of L. paracasei 207-27 and B. breve 207-1 are significantly higher than that of the standard strain LGG (P<0.05). In contrast, the adhesion rates of L. rhamnosus 208-18 and B. longum 199 are significantly lower than that of the standard strain LGG (P<0.05). Figure 5 The scanning electron microscope images of Figure 5 show the effect of lactic acid bacteria adhering to intestinal organoid cells, including the specific interactions between bacteria and cells, further verifying the reliability of the above experimental data.

[0037] In the study of evaluating the ability of probiotics to adhere to intestinal epithelial cells, there are some defects in using traditional cell models and animal models respectively. Traditional cell models, such as Caco-2 and HT-29 cells, although they can partially simulate some characteristics of the intestinal epithelium, they cannot fully represent the real intestinal environment. This is because these cell models only simulate a part of the intestinal epithelium and lack complete immune responses and barrier functions. The intestinal epithelium in the real environment is not only a physical barrier, but also interacts with microorganisms, the immune system, and metabolites in the complex intestinal microenvironment, and these characteristics are difficult to fully reproduce by traditional cell models. On the other hand, although animal models can be closer to the real intestinal environment, their heterogeneity is also a key issue. There are significant differences in the intestinal microenvironment, physical structure, and function among different animal species. For example, the intestinal microenvironment of mice and rats is very different from that of humans, which may affect the adhesion and action of probiotics. The use of animal models also involves ethical and cost issues, and due to their complexity, study design and data analysis become more complicated. Overly complex animal models may lead to limited translatability of research results.

[0038] Traditional probiotic adhesion studies are mostly based on monolayer cell models and cannot fully reflect the complex three-dimensional structure and functional characteristics of the intestine. In this example, an organoid model, which is closer to the in vivo environment, is used to evaluate the adhesion ability of probiotics, overcoming the limitations of traditional methods and improving the authenticity and translatability of experimental results.

[0039] Example 3: Screening of the concentration of the inducer IFN-γ for the intestinal organoid intestinal barrier injury model In this example, the concentration of the inducer IFN-γ (100, 200, 400 ng / ml) and the induction time (12 h, 24 h) were screened. To evaluate the effect of this inducer on the activity of organoids, a 3D organoid activity detection kit was used to detect the activity of the treated organoids.

[0040] 3.1 Experimental procedure: Remove the old medium from the wells of the mature organoids cultured in 96-well plates and wash three times with PBS. Then add basal medium containing IFN-γ at concentrations of (100, 200, 400 ng / ml) and treat for 24 h / 12 h. After washing three times with PBS, add CellTiter-Glo ® 3D reagent and PBS at 25 µl / well respectively, shake crosswise for 5 min, and incubate for 25 min. Record the luminescence value, and the results were normalized using the control group as the standard. The effects of different concentrations of IFN-γ (100 ng / mL, 200 ng / mL, and 400 ng / mL) on the activity of intestinal organoids were studied under the conditions of 12 h and 24 h.

[0041] 3.2 Experimental results: As Figure 6 shown, the experimental results showed that under the condition of 12 h, there was no significant difference in the viability of intestinal organoids in the 100 ng / mL and 200 ng / mL IFN-γ treatment groups compared with the control group (NC group), while the viability of intestinal organoids in the 400 ng / mL IFN-γ treatment group was significantly lower than that of the control group (P < 0.001). Under the condition of 24 h, similar results showed that there was no significant difference in the viability of intestinal organoids in the 100 ng / mL and 200 ng / mL IFN-γ treatment groups compared with the control group, while the viability of intestinal organoids in the 400 ng / mL IFN-γ treatment group was significantly reduced (P < 0.001). Based on the above results, subsequent experiments selected concentration gradients of 100 ng / mL and 200 ng / mL, and time gradients of 12 h and 24 h to further optimize the induction conditions for the intestinal organoid barrier injury and inflammation models.

[0042] As Figure 7As shown, the effects of IFN-γ at concentrations of 100 ng / mL and 200 ng / mL on the expression levels of tight junction factors and inflammatory factors were studied after treating intestinal organoids for 12 h. The experimental results showed that after treating with 100 ng / mL IFN-γ for 12 h, there were no significant differences in the expression levels of tight junction factors and inflammatory factors compared with the control group (NC group). However, when the concentration increased to 200 ng / mL, the expression levels of tight junction factors E-cadherin and MUC2 decreased significantly (P<0.05), while the expression levels of inflammatory factors IL-1β and CCL3 increased significantly (P<0.05). It can be seen that treating with 200 ng / mL IFN-γ for 12 h can significantly reduce the tight junction of intestinal epithelial cells and induce intestinal inflammatory responses.

[0043] As Figure 8 shown, the effects of IFN-γ at concentrations of 100 ng / mL and 200 ng / mL on the expression levels of tight junction factors and inflammatory factors were studied after treating intestinal organoids for 24 h. The experimental results showed that after treating with 100 ng / mL IFN-γ for 24 h, the expression levels of tight junction factors ZO-1 and E-cadherin in intestinal organoids decreased significantly compared with the control group (NC group) (P<0.05). After treating with 200 ng / mL IFN-γ for 24 h, the expression levels of ZO-1, E-cadherin and MUC2 all decreased significantly (P<0.001). In addition, after treating with 100 ng / mL IFN-γ for 24 h, the expression levels of pro-inflammatory factors IL-1β and CCL3 increased significantly (P<0.05). After treating with 200 ng / mL IFN-γ for 24 h, the expression levels of pro-inflammatory factors IL-1β, CCL3 and TNF-α increased significantly (P<0.001). These results indicate that the treatment concentration and time of IFN-γ have significant effects on the expression levels of tight junction factors and inflammatory factors in intestinal organoids.

[0044] In summary, IFN-γ at a concentration of 200 ng / mL was used to treat for 24 h subsequently to induce intestinal barrier damage and intestinal inflammation in intestinal organoids.

[0045] Example 4: Evaluation of the monolayer integrity and permeability of probiotics to intestinal organoids In this example, an intestinal epithelial monolayer barrier model was constructed in a Transwell chamber. The TEER values at three fixed positions in each well were detected every day, and each well was measured three times and the mean value was taken. When the TEER value of the intestinal epithelial monolayer stabilized at 200-300 Ω·cm 2 it represented that the intestinal epithelial monolayer had formed. The differentiation medium was replaced and cultured for another 2-3 days. The fully differentiated monolayer epithelial model could be used for subsequent experiments.

[0046] The TEER calculation formula is as follows: TEER (Ω·cm 2 ) = (resistance value of each well - resistance value of blank well) × membrane area.

[0047] After the monolayer was formed, fresh basal medium containing 5% (v / v) conditioned medium was added to the upper chamber for pretreatment for 6 h. The culture medium in the lower chamber was replaced with fresh DMEM / F-12. After the treatment, the culture medium was removed and the monolayer was washed 3 times with D-PBS. The monolayer was treated with basal medium containing 200 ng / mL IFN-γ for 24 h. The TEER value was measured every 4 h. Three replicates were set for each group, and each well was measured three times and the mean value was taken. After the TEER detection, the monolayer was washed 3 times with D-PBS and equilibrated at 37 °C for 30 min. The insert was transferred to a new well plate, and 200 μL of 1 mg / mL FITC solution preheated to 37 °C was added to the upper chamber. 600 μL of PBS was added to the lower chamber, and the mixture was incubated in the dark at 37 °C for 6 h. 100 μL of the lower chamber solution was taken to detect the fluorescence intensity with an excitation wavelength of 490 nm and an emission wavelength of 520 nm. The FITC concentration was calculated according to the standard curve.

[0048] Preparation of conditioned medium: Probiotics were inoculated into fresh DMEM / F-12 and cultured overnight at 37 °C until the logarithmic phase. The medium was centrifuged twice at 1500 g for 10 min, and the pH of the solution was adjusted to 7.4. The solution was filtered through a 0.22 μm filter to remove live bacteria and stored at -20 °C. An appropriate amount of conditioned medium was taken for plating and counting to determine whether there were live bacteria.

[0049] As Figure 9 shown, the experimental results showed that when the intestinal epithelial monolayer was cultured to the 14th day, the transmembrane resistance value tended to be stable and reached 250 Ω·cm², indicating that the intestinal epithelial monolayer had been formed. Then, the intestinal epithelial monolayer was treated with 200 ng / mL IFN-γ for 24 h to induce its leakage. According to Figure 9For the data of b in Figure 9 c). In summary, pretreatment with L. paracasei 207-27-CM and B. breve 207-1-CM can effectively prevent IFN-γ-induced intestinal barrier damage and exhibit good protective effects.

[0050] Example 5: Regulation of intestinal inflammation and barrier by probiotics in intestinal organoids In this example, after pretreatment with probiotic conditioned medium in the experimental wells for 6 h, differentiated and mature intestinal organoids were treated with 200 ng / ml IFN-γ for 24 h. After treating the differentiated and mature intestinal organoids with 200 ng / ml IFN-γ for 24 h, the intestinal organoid samples were collected by centrifugation. RNA was extracted using a microRNA extraction kit and reverse transcription was performed. The expression of inflammatory genes and intestinal barrier genes was detected by RT-qPCR.

[0051] Preparation of conditioned medium: The probiotics were inoculated into fresh DMEM / F-12 and cultured overnight at 37 °C until the logarithmic phase. The medium was centrifuged twice at 1500 g for 10 min, and the pH of the solution was adjusted to 7.4. It was filtered through a 0.22 μm filter to remove live bacteria and stored at -20 °C. An appropriate amount of conditioned medium was taken for plating and counting to determine whether there were live bacteria.

[0052] As Figure 10As shown, the results of the study on the effect of pretreatment with conditioned media of L. paracasei 207-27 and B. breve 207-1 on the expression of tight junction genes in intestinal organoids showed that IFN-γ treatment significantly decreased the expression of tight junction genes ZO-1, E-cadherin, MUC2, Occludin, and JAM-A (P<0.01), while significantly increasing the expression of the CLDN2 gene (P<0.001). This change indicates that IFN-γ treatment severely disrupted the tight junction structure between intestinal epithelial cells. However, in intestinal organoids pretreated with L. paracasei 207-27-CM and B. breve 207-1-CM, the expression of tight junction genes ZO-1, E-cadherin, Occludin, and JAM-A was significantly increased compared to the group treated with IFN-γ alone (P<0.01), while the expression of CLDN2 was significantly decreased (P<0.001). These results suggest that pretreatment with L. paracasei 207-27-CM and B. breve 207-1-CM can effectively prevent the decrease in intercellular tight junction induced by IFN-γ, thus contributing to the maintenance of the integrity of the intestinal barrier.

[0053] As Figure 11 shown, the results showed that IFN-γ treatment significantly increased the expression of pro-inflammatory factors IL-1β, IL-6, and CXCL10 (P<0.001), while significantly decreasing the expression of anti-inflammatory factors TGF-β1 and IL-10 (P<0.01). However, in the groups pretreated with L. paracasei 207-27-CM and B. breve 207-1-CM, the expression of pro-inflammatory factors was significantly inhibited (P<0.05), while the expression of anti-inflammatory factors IL-10 and TGF-β1 was significantly promoted. This indicates that pretreatment with L. paracasei 207-27 and B. breve 207-1 can inhibit the inflammatory response of intestinal epithelial cells and effectively relieve intestinal inflammation by regulating the expression of inflammatory factors.

[0054] For the repair of intestinal inflammation and barrier function, traditional in vitro models are difficult to accurately reflect the dynamic environment and complex signaling pathways of the intestine. Examples 3-5 utilize the intestinal organoid model to deeply explore the specific mechanism of action of probiotics in relieving inflammation and repairing the intestinal barrier, providing a more scientific and clinically translatable method for functional verification.

[0055] Example 6: Inhibitory effect of lactic acid bacteria on the adhesion of common pathogenic bacteria This example aims to study the inhibitory effect of six lactic acid bacteria on the adhesion of Clostridium perfringens and invasive Escherichia coli to colon organoids, and the competitive adhesion method was used in the experiment.

[0056] 6.1 Experimental procedure: After coating the bottom of a 24-well plate with hydrated matrix gel, colon organoids were seeded into the 24-well plate. After culturing until the cell monolayer was confluent, differentiation treatment was carried out. The differentiated colon organoid monolayer (i.e., the colon epithelial monolayer) was used for subsequent experiments. Lactobacilli and pathogenic bacteria were diluted with DMEM / F-12 medium without antibiotics. The concentration of pathogenic bacteria was adjusted to 5×10 7 CFU / ml, and the concentration of lactobacilli was adjusted to 5×10 7 CFU / ml, 5×10 8 CFU / ml, 5×10 9 CFU / ml for standby. After washing the cultured monolayer cells 3 times with D-PBS, 800 μl of DMEM / F-12, 100 μl of lactobacilli suspension and 100 μl of pathogenic bacteria suspension were added to each well, and cultured at 37 °C for 2 h. After the culture was completed, the monolayer was washed 3 times with D-PBS to remove unadhered bacteria. A bacterial and cell suspension was prepared by adding D-PBS at 1 ml / well. The suspension was serially diluted and spread on plates to count the number of pathogenic bacteria contained in the suspension. Adhesion rate (CFU / cell) = number of adhered pathogenic bacteria per well (CFU) / total number of cells per well × 100%.

[0057] 6.2 Experimental results: 6.2.1 Inhibitory effect of lactobacilli on the adhesion of Clostridium perfringens to colon organoids: Figure 12The inhibitory effect of gradient concentration lactic acid bacteria (LAB) on the adhesion of Clostridium perfringens (C. perfringens) to colon organoids was shown. The results indicated that when C. perfringens:LAB = 1:1, compared with the NC group with only L. paracasei 207-27 and B. breve 207-1, the adhesion rate of C. perfringens to colon organoids was significantly inhibited (P<0.05), while the other strains did not significantly reduce the adhesion rate of C. perfringens. When the ratio increased to 1:10, the groups of L. rhamnosus 203-10, L. rhamnosus 208-18, L. paracasei 207-27, L. paracasei 329-30 and B. breve 207-1 significantly inhibited the adhesion of C. perfringens to colon organoids compared with the NC group. Among them, the best inhibitory effects were shown by the groups of L. paracasei 207-27 and B. breve 207-1. The number of C. perfringens in each well decreased from 35000 CFU to 22166 CFU and 24000 CFU respectively, with a decrease ratio of approximately 36.7% and 31.4%. This indicated that at a ratio of 1:10, six strains of LAB could inhibit the adhesion of C. perfringens to colon organoids. The B. longum 199 group did not significantly inhibit the adhesion rate of C. perfringens compared with the NC group, but the adhesion rate was significantly increased compared with the standard strain LGG group (P<0.001). Thus, it can be seen that B. longum 199 had a poor inhibitory effect on the adhesion of C. perfringens. When C. perfringens:LAB = 1:100, the adhesion rate of C. perfringens to colon organoids was similar to that at 1:10. In summary, when lactic acid bacteria were added at a ratio of C. perfringens:LAB = 1:1, the inhibitory effect of lactic acid bacteria on the adhesion of C. perfringens to colon organoids was poor. When the ratio increased to 1:10, most lactic acid bacteria showed a significant inhibitory effect on the adhesion of C. perfringens. The effects of the ratios of 1:10 and 1:100 were almost the same.

[0058] 6.2.2 Inhibitory effect of lactic acid bacteria on the adhesion of invasive Escherichia coli to colon organoids: Figure 13The inhibitory effects of six lactic acid bacteria on the adhesion of enteroinvasive Escherichia coli (EIEC) to the colonic epithelial monolayer were demonstrated. When EIEC:LAB = 1:1, the adhesion rates of EIEC in the groups of L. rhamnosus 208-18, L. paracasei 207-27, and B. breve 207-1 were approximately 2.9×10 4 CFU / well. L. rhamnosus 208-18, L. paracasei 207-27, and B. breve 207-1 significantly inhibited the adhesion of EIEC compared with the NC group (P<0.05). However, the adhesion rates of EIEC in the groups of L. rhamnosus 203-10, L. paracasei 329-30, and B. longum 199 were approximately 3.3×10 4 CFU / well, and these lactic acid bacteria did not show inhibitory effects on the adhesion of EIEC. When EIEC:LAB = 1:10, all six lactic acid bacteria significantly inhibited the adhesion of EIEC to intestinal epithelial cells (P<0.01). Among them, the adhesion rates of EIEC in the groups of L. paracasei 329-30 and B. longum 199 after treatment were approximately 2.8×10 4 CFU / well. When EIEC:LAB = 1:100, the groups of L. rhamnosus 208-18, L. paracasei 207-27, and B. breve 207-1 still showed significant adhesion inhibitory effects (P<0.001), but the adhesion rate of EIEC was similar to that when EIEC:LAB = 1:10.

[0059] Example 7: Inhibitory effects of lactic acid bacteria on the invasion of common pathogenic bacteria This example aimed to study the inhibitory effects of six lactic acid bacteria on the invasion of Clostridium perfringens and enteroinvasive Escherichia coli into colonic organoids.

[0060] 7.1 Experimental procedure: After coating the bottom of a 24-well plate with hydrated Matrigel, colon organoids were inoculated into the 24-well plate and cultured until the cell monolayer was confluent, followed by differentiation treatment. The differentiated colon organoid monolayer was used for subsequent experiments. The lactic acid bacteria and pathogenic bacteria were separately diluted and adjusted to a concentration of 5×10 9 CFU / ml and 5×10 8CFU / ml, for backup. After washing the cultured monolayer cells 3 times with D-PBS, add 800 μl of DMEM / F-12, 100 μl of probiotic suspension and 100 μl of pathogenic bacterium suspension to each well, and culture at 37 °C for 2 h. After the culture, wash the monolayer 3 times with D-PBS to remove the non-adherent bacteria. Add 100 μg / ml gentamicin at 1 ml / well to remove the pathogenic bacteria adhered to the cell surface. Prepare a bacterial and cell suspension by adding D-PBS (containing 0.1% TritonX-100) at 1 ml / well. Perform gradient dilution coating on the suspension and count the number of pathogenic bacteria contained in the suspension.

[0061] Invasion rate (CFU / cell) = number of invading pathogenic bacteria per well (CFU) / total number of cells per well × 100%.

[0062] 7.2 Experimental results: Figure 14 Showed the inhibitory effects of six lactic acid bacteria on the invasion of Clostridium perfringens and Enteroinvasive Escherichia coli (EIEC) into the colonic epithelial monolayer. The results of the inhibitory effect of lactic acid bacteria on the adhesion of C. perfringens showed that the adhesion rate of C. perfringens was approximately 2.2×10 4CFU / well, showed a significant inhibitory effect compared with the NC group (P<0.001). After treatment with L. paracasei 329-30 and B. longum 199, the adhesion rate of C. perfringens was about 340 CFU / well, and no significant inhibitory effect was shown compared with the NC group. The results of the inhibitory effect of lactic acid bacteria on EIEC adhesion showed that the adhesion rates of the L. paracasei 207-27 and B. breve 207-1 groups were about 180 CFU / well, which were significantly decreased compared with the NC group (P<0.001), and the L. paracasei 207-27 group was significantly decreased compared with the standard strain LGG group (P<0.001); the adhesion rates of L. rhamnosus 203-10 and L. rhamnosus 208-18 were about 200 CFU / well, which were significantly decreased compared with the NC group (P<0.001); the adhesion rate of the L. paracasei 207-27 group was about 295 CFU / well, which was significantly decreased compared with the NC group (P<0.001) and significantly increased compared with the standard strain LGG group (P<0.001); the adhesion rate of the B. longum 199 group was about 338 CFU / well, which was significantly decreased compared with the NC group (P<0.05) and significantly increased compared with the standard strain LGG group (P<0.001).

[0063] Probiotics play a key role in maintaining intestinal health by inhibiting the adhesion and invasion of pathogenic bacteria. However, traditional studies mainly rely on monolayer cell models and animal models, which have limitations such as structural simplification and long experimental cycles, and it is difficult to comprehensively simulate the real intestinal microenvironment. These traditional models each have unique defects. Monolayer cell models, such as Caco-2 and HT-29 cells, are easy to operate, but they only simulate a part of the intestine, such as a simple epithelial layer, lacking a mucus layer and multiple intestinal epithelial cell types, which makes it difficult for these models to reflect the diversity and complexity in the intestinal environment. In addition, the static nature of monolayer cell models also limits the ability to study the mechanism of probiotics inhibiting the invasion of pathogenic bacteria. In addition, although animal models can reproduce some functions and structures of the intestine, compared with humans, there are significant differences in intestinal physiological characteristics and microenvironment in some aspects, resulting in limited clinical translation of research results. In addition, animal models have a long experimental cycle, high experimental costs, and uncontrollable external factors that may affect the consistency and repeatability of results. These limitations restrict the application efficiency of traditional research models in studying the mechanism of probiotics inhibiting the invasion of pathogenic bacteria.

[0064] Previous studies have mostly focused on the overall effect of probiotics in inhibiting pathogenic bacteria, but lack refined mechanism research and function evaluation. Examples 6 and 7, with the help of the intestinal organoid model, can systematically evaluate the inhibitory effect of probiotics on the invasion and adhesion of pathogenic bacteria, providing new research tools and evaluation methods for the anti-infective function of probiotics.

[0065] The present invention provides a method, a model and an application for evaluating the function of probiotics, including evaluating the tolerance of probiotics through an in vitro digestion tolerance model (Example 1), evaluating the adhesion ability of probiotics through an intestinal organoid model (Example 2), evaluating the inhibitory effect of the above-mentioned probiotics on the adhesion and / or invasion of pathogenic bacteria through an intestinal organoid model (Examples 3-5), and evaluating the intestinal barrier repair ability and / or intestinal inflammation alleviation ability through an intestinal organoid injury model (Examples 6-7). By using the intestinal organoid model, the present invention can deeply explore the specific mechanism of action of probiotics in alleviating inflammation and repairing the intestinal barrier, provide a more scientific and clinically translatable function verification method, and can simulate the real digestion process of the human body, provide a more comprehensive and accurate probiotic tolerance evaluation method, improve the authenticity and translatability of experimental results, and construct an efficient and accurate method for evaluating the function of bacteria.

[0066] Obviously, the above examples are only for illustration purposes and are not intended to limit the implementation methods. For those of ordinary skill in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all implementation methods here. And the obvious changes or modifications derived therefrom are still within the protection scope of the present invention.

Claims

1. A method for evaluating the function of probiotics, characterized in that, It includes the following steps: S1. Inoculate probiotics into a basal medium and culture until the logarithmic phase, adjust the pH to 7 - 7.8 after centrifugation, and filter to remove live bacteria to obtain a conditioned medium; S2. Pretreat the intestinal organoid model with the conditioned medium, and then add IFN-γ at a concentration of 100 - 400 ng / mL for treatment to obtain an intestinal organoid barrier injury model; S3. Measure the transcutaneous electrical resistance value of the intestinal organoid barrier injury model, evaluate the intestinal barrier repair ability of the probiotics, detect the inflammatory genes and / or intestinal barrier genes of the intestinal organoid barrier injury model, and evaluate the intestinal barrier repair and / or inflammation alleviation ability of the probiotics.

2. The method according to claim 1, characterized in that, In step S2, the concentration of IFN-γ is 150 - 250 ng / mL.

3. The method according to claim 1, wherein In step S2, the treatment time of IFN-γ is 12 - 24 h.

4. The method according to claim 1, wherein In step S3, the transcutaneous electrical resistance value is the TEER value; The inflammatory genes include at least one of IL-1β, IL-6, IL-8, IL-10, IL-12, CXCL10, TNF-α, TGF-β1, and IL-10; The intestinal barrier genes include at least one of ZO-1, E-cadherin, MUC2, Occludin, JAM-A, and CLDN2 genes.

5. The method according to claim 1, wherein It also includes the following steps: Conduct artificial gastric juice tolerance experiments, artificial intestinal juice tolerance experiments, and artificial bile salt tolerance experiments on the probiotics respectively to evaluate the digestive tolerance of the probiotics.

6. The method according to claim 1, wherein It also includes the following steps: Add the probiotics and pathogenic bacteria to the intestinal organoid model for co-incubation, calculate the number of adhered pathogenic bacteria and / or the pathogenic bacteria adhesion rate, calculate the number of invasive pathogenic bacteria and / or the pathogenic bacteria invasion rate, and evaluate the inhibitory effect of the probiotics on the adhesion and / or invasion of pathogenic bacteria.

7. The method according to claim 1, wherein It also includes the following steps: Add the probiotics to the intestinal organoid model for incubation, calculate the number of adhered probiotics and / or the probiotics adhesion rate, and evaluate the intestinal adhesion ability of the probiotics.

8. The method according to claim 1, wherein Specifically, it includes the following steps: Evaluate the probiotic tolerance through an in vitro digestion tolerance model: Evaluate the digestive tolerance of the probiotics through artificial gastric juice tolerance experiments, artificial intestinal juice tolerance experiments, and artificial bile salt tolerance experiments respectively; Evaluate the probiotic adhesion ability through the intestinal organoid model: Add the probiotics to the intestinal organoid model for incubation, calculate the number of adhered probiotics and / or the probiotics adhesion rate, and evaluate the intestinal adhesion ability of the probiotics; Evaluate the inhibitory effect of the probiotics on the adhesion and / or invasion of pathogenic bacteria through the intestinal organoid model: Add the probiotics and pathogenic bacteria to the intestinal organoid model for co-incubation, calculate the number of adhered pathogenic bacteria and / or the pathogenic bacteria adhesion rate, and / or calculate the number of invasive pathogenic bacteria and / or the pathogenic bacteria invasion rate, and evaluate the inhibitory effect of the probiotics on the adhesion and / or invasion of pathogenic bacteria; Evaluating the intestinal barrier repair ability and / or intestinal inflammation alleviation ability through an intestinal organoid injury model: S1. Inoculate probiotics into a basal medium and culture until the logarithmic phase, adjust the pH to 7 - 7.8 after centrifugation, and filter to remove live bacteria to obtain a conditioned medium; S2. Pretreat the intestinal organoid model with the conditioned medium, and then add IFN-γ at a concentration of 100 - 400 ng / mL for treatment to obtain an intestinal organoid barrier injury model; S3. Measure the transcutaneous resistance value of the intestinal organoid barrier injury model and / or intestinal barrier genes to evaluate the intestinal barrier repair ability of the probiotics, and / or detect the inflammatory genes of the intestinal organoid barrier injury model to evaluate the intestinal inflammation alleviation ability of the probiotics.

9. A model for evaluating the functions of probiotics, characterized in that, Including: An in vitro digestion tolerance evaluation model for conducting artificial gastric juice tolerance experiments, artificial intestinal juice tolerance experiments, and artificial bile salt tolerance experiments on probiotics respectively to evaluate the digestion tolerance of probiotics; A probiotic intestinal adhesion evaluation model for incubating probiotics in an intestinal organoid model and calculating the number of adhered probiotics and / or the probiotic adhesion rate to evaluate the intestinal adhesion ability of probiotics; A probiotic inhibitory effect on pathogenic bacteria intestinal adhesion and / or invasion evaluation model for co-incubating the probiotics and pathogenic bacteria in an intestinal organoid model and calculating the number of adhered pathogenic bacteria and / or the pathogenic bacteria adhesion rate, and / or calculating the number of invasive pathogenic bacteria and / or the pathogenic bacteria invasion rate to evaluate the inhibitory effect of the probiotics on pathogenic bacteria adhesion and / or invasion; An intestinal organoid injury model for evaluating the intestinal barrier repair ability and / or intestinal inflammation alleviation ability of probiotics through an IFN-γ-induced intestinal organoid model.

10. Use of the method as described in claims 1 - 8 in the evaluation of probiotic functions.

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