A method for constructing a mycobacterium infection model after zebrafish intestinal flora imbalance and application thereof in evaluating effect of probiotics in treating tuberculosis

Abstract

This application discloses a method for constructing a zebrafish mycobacterial infection model after intestinal flora dysbiosis and its application in evaluating the efficacy of probiotics in treating tuberculosis. This method constructs a zebrafish mycobacterial infection model after intestinal flora dysbiosis by treating with a combination of antibiotics and injecting Mycobacterium marineum. The model assesses the influence of intestinal flora status on the host's resistance to mycobacterial infection, as well as on granuloma pathological changes and the immune microenvironment. Results show that mixed antibiotic intervention significantly disturbs the zebrafish intestinal microecological structure, and intestinal flora dysbiosis significantly increases the mycobacterial infection load, exacerbating disease progression. Furthermore, the inflammatory imbalance induced by intestinal flora dysbiosis significantly promotes granuloma formation and the occurrence and development of necrotic pathology. Using this model to evaluate the efficacy of probiotics in treating tuberculosis, results show that restoring intestinal flora homeostasis through probiotics can significantly reverse the uncontrolled mycobacterial infection and necrotic tissue damage mediated by flora dysbiosis.

Description

Technical Field

[0001] This application relates to a method for constructing a mycobacterial infection model after zebrafish gut microbiota dysbiosis and its application in evaluating the efficacy of probiotics in treating tuberculosis, belonging to the field of biomedical technology. Background Technology

[0002] Tuberculosis (TB) remains a leading cause of death from infectious diseases worldwide, with approximately 10.7 million new cases and over 1.2 million deaths in 2024, continuing to constitute a significant public health burden (WHO, 2025). Its hallmark pathology is the formation of granulomas—organized immune structures that both limit the spread of mycobacteria and provide conditions for their persistence. Granulomas represent the dynamic interface between the host and pathogens, in which macrophages and lymphocytes work synergistically to exert antibacterial defenses while potentially creating a microenvironment that allows bacteria to survive. Although research into the biological mechanisms of granulomas at the site of infection is quite extensive, the determinants regulating granuloma initiation, tissue structure formation, and long-term stability remain incompletely understood.

[0003] Recent studies increasingly suggest that the gut microbiota, as a distal regulatory factor, plays a crucial role in shaping the host's systemic immune response and anti-infection processes. As one of the largest immune organs in the human body, the gut not only serves as a barrier and metabolic organ, but its symbiotic microbiota also deeply participates in maintaining host immune homeostasis by regulating macrophage activation, inflammatory set points, and cytokine signaling pathways. Metabolites and microbial-related molecular patterns derived from the gut microbiota can remodel host immune function, thereby influencing host susceptibility to infectious diseases. In tuberculosis research, both clinical and animal experiments have shown that infected individuals often exhibit reduced gut microbiota diversity and a decrease in immune-regulating bacteria, and these changes are closely related to disease severity and treatment outcomes. However, whether gut microbiota homeostasis directly affects the structural and functional evolution of granulomas during mycobacterial infection remains unclear.

[0004] Therefore, an experimental system is needed that can simultaneously analyze gut microbiota composition, immune dynamics, granuloma formation process, and evaluate the efficacy of probiotics in treating tuberculosis in vivo. Existing research models mainly suffer from the following problems: 1) Currently used animal models for tuberculosis infection research, including mice, rabbits, and chimpanzees, all use Mycobacterium tuberculosis, requiring a high level of biosafety in a P3 laboratory, resulting in high experimental costs and operational difficulties; 2) Current animal models studying the relationship between gut microbiota and tuberculosis mainly rely on traditional mouse antibiotic clearance models or germ-free mice. While this provides important tools for elucidating the role of gut microbiota in host immune regulation, it also has limitations. Germ-free mice, although allowing for precise study of the impact of gut microbiota deficiency on disease, are complex to operate, costly, and their physiological state differs significantly from that under natural conditions. While antibiotic clearance models are relatively simple to operate, their construction time is long, typically requiring continuous antibiotic gavage for about a month, which greatly increases the harm to the animals during the process.

[0005] Based on this, this application innovatively developed a zebrafish composite model of "mycobacterial infection after intestinal microbiota dysbiosis" using a combination of antibiotics and Mycobacterium marineis infection. It systematically evaluates the influence of intestinal microbiota status on the host's ability to resist mycobacterial infection, as well as on granulomatous pathological changes and the immune microenvironment. The aim is to establish a theoretical framework between intestinal microbiota homeostasis and systemic regulation of mycobacterial diseases, and to provide potential microbiota intervention ideas for host-oriented treatment strategies for tuberculosis. Summary of the Invention

[0006] The purpose of this invention is to address the shortcomings of the prior art by providing a method for constructing a mycobacterial infection model in zebrafish after gut microbiota dysbiosis and its application in evaluating the efficacy of probiotics in treating tuberculosis.

[0007] To achieve the above objectives, this application adopts the following technical solution:

[0008] This application provides a method for constructing a zebrafish intestinal flora dysbiosis model, comprising: constructing a zebrafish intestinal flora dysbiosis model by treating with compound antibiotics, then injecting Mycobacterium marineum to construct a zebrafish intestinal flora dysbiosis model, and evaluating the influence of intestinal flora status on the host's ability to resist mycobacterial infection, as well as its influence on granulomatous pathological changes and immune microenvironment.

[0009] Furthermore, the compound antibiotics comprise neomycin 0.5 mg / kg, ampicillin 0.5 mg / kg, metronidazole 0.25 mg / kg, and vancomycin 0.25 mg / kg, measured based on zebrafish body weight.

[0010] Furthermore, it also includes a step of evaluating the zebrafish gut microbiota dysbiosis model, including verifying whether the gut microbiota dysbiosis model has been successfully constructed by evaluating the zebrafish gut microecological structure.

[0011] Furthermore, the evaluation of the zebrafish gut microbiota dysbiosis model includes setting up a control group and an experimental group. The control group was treated with DMSO, while the experimental group was given oral administration of a compound antibiotic. The diversity and compositional changes of the gut microbiota in the control group and the experimental group were evaluated and analyzed by 16S rRNA sequencing.

[0012] Furthermore, the assessment of the influence of gut microbiota status on the host's ability to resist mycobacterial infection was carried out by comparing the number or concentration of Mycobacterium marineis in zebrafish in the control group and the experimental group. The control group was treated with DMSO and then injected with Mycobacterium marineis, while the experimental group was treated with compound antibiotics and then injected with Mycobacterium marineis.

[0013] Furthermore, the assessment of the influence of gut microbiota status on the pathological changes of granulomas was performed by detecting the distribution of Mycobacterium marineis in zebrafish granulomas in the control and experimental groups using acid-fast staining. The control group was treated with DMSO and then injected with Mycobacterium marineis, while the experimental group was treated with compound antibiotics and then injected with Mycobacterium marineis.

[0014] Furthermore, the assessment of the impact of gut microbiota status on the immune microenvironment includes evaluation by HE staining and quantitative statistics of at least one of the following: number of granulomas, percentage of granuloma necrosis, area of ​​granulomas, and number of granuloma immune cell infiltrations.

[0015] This application also provides the application of a zebrafish intestinal flora dysbiosis-induced mycobacterial infection model in evaluating the efficacy of probiotics in treating tuberculosis. The zebrafish intestinal flora dysbiosis-induced mycobacterial infection model is constructed by treating zebrafish with compound antibiotics and then injecting Mycobacterium marinum to construct a zebrafish intestinal flora dysbiosis-induced mycobacterial infection model.

[0016] This application also provides a method for evaluating the efficacy of probiotics in treating tuberculosis based on a zebrafish intestinal flora dysbiosis and mycobacterial infection model, comprising: constructing a zebrafish intestinal flora dysbiosis model by treating with compound antibiotics, then injecting Mycobacterium marineum to construct a zebrafish intestinal flora dysbiosis and mycobacterial infection model, administering probiotics, and evaluating the efficacy of probiotics in treating tuberculosis.

[0017] Furthermore, the evaluation of the efficacy of probiotics in treating tuberculosis includes detecting the repair of granulomatous tissue damage through pathological HE staining and / or detecting the concentration or quantity of Mycobacterium marinum.

[0018] Compared with the prior art, this application has the following beneficial effects: 1) This application pioneered the development of a zebrafish composite model of "mycobacterial infection after intestinal microbiota dysbiosis" using a combination of antibiotics and Mycobacterium marineis infection. It systematically evaluated the influence of intestinal microbiota status on the host's ability to resist mycobacterial infection, as well as on granulomatous pathological changes and the immune microenvironment. It established a theoretical framework between intestinal microbiota homeostasis and systemic regulation of mycobacterial diseases, and provided potential microbiota intervention ideas for host-oriented treatment strategies for tuberculosis.

[0019] 2) In this application, the marine mycobacterium used for zebrafish infection can not only simulate the pathological characteristics of the host after Mycobacterium tuberculosis infection, but also has low pathogenicity to humans, requires a low biosafety level, can be operated in ordinary laboratories, and greatly reduces costs.

[0020] 3) This application used the zebrafish composite model to evaluate the effect of probiotics in treating tuberculosis. The results showed that restoring gut microbiota homeostasis (probiotic treatment) could significantly reverse the uncontrolled mycobacterial infection and necrotic tissue damage mediated by dysbiosis, further supporting the key regulatory role of gut microbiota in the process of tuberculosis infection. Attached Figure Description

[0021] Figure 1 ABX induces changes in the diversity and composition of the gut microbiota in zebrafish (modeling phenotype); including: A. Schematic diagram of gut microbiota dysbiosis model construction; B. Venn diagram of 16S rRNA sequencing ABX group and control group; C. phylogenetic bar chart of microbiota in 16S rRNA sequencing ABX group and control group; D. LEfSe analysis of 16S rRNA sequencing ABX group and control group.

[0022] Figure 2 The study investigated how gut microbiota dysbiosis exacerbates mycobacterial infection load and reduces host survival (modeling phenotype). Specifically: A. Mycobacterial infection model: Flowchart of the zebrafish gut microbiota dysbiosis-mycobacterial infection model; B. Colonization of zebrafish with Mm-Wasabi (1500–2000 CFU) 7 days after infection; Data are expressed as mean ± standard error (SEM) (n = 14 for DMSO+Mm, n = 12 for ABX+Mm group); Statistical analysis of differences between groups was performed using independent samples t-tests. p<0.01; C. Acid-fast staining: Acid-fast staining shows the distribution of mycobacteria in the two groups of granulomas, with red dashed lines indicating granuloma areas; top scale bar = 50 μm, bottom scale bar = 20 μm; D. Survival curves: Survival curves for zebrafish infected or uninfected with Mm-Wasabi (~5000 CFU) DMSO, ABX, DMSO+Mm, and ABX+Mm groups; each group contained 9 fish; simple survival analysis (Kaplan-Meier method) was used for statistical analysis. p<0.05.

[0023] Figure 3 : Gut microbiota dysbiosis promotes the formation of tuberculous granulomas and aggravates necrotic pathological changes (modeling mechanism); Among them: A. HE staining image—Representative HE staining images of whole paraffin sections of zebrafish in the DMSO + Mm and ABX + Mm groups after Mm infection, with blue arrows indicating granulomas, scale bar = 500 μm; The image below shows a magnified view of the area within the black frame, with red dashed lines indicating granulomas and yellow dashed lines indicating necrotic areas, scale bar = 50 μm; B. Granuloma quantity statistics—Quantitative analysis of granulomas in zebrafish in the DMSO + Mm and ABX + Mm groups, each point represents one zebrafish; C. Granuloma necrosis percentage—The percentage of necrotic granulomas in the total number of granulomas in zebrafish in the DMSO + Mm and ABX + Mm groups, each point represents one fish; D. Granuloma area—Immune infiltration area in the DMSO + Mm and ABX + Mm groups, each point represents one zebrafish; E. Statistical analysis of the number of immune cells infiltrating granulomas—the number of immune cells in the granulomatous regions of zebrafish in the DMSO+Mm and ABX+Mm groups, with each point representing one zebrafish; data are expressed as mean ± standard error (SEM); differences between the two groups were statistically analyzed using independent samples t-test; p<0.05; p<0.01.

[0024] Figure 4: Fecal microbiota transplantation alleviates mycobacterial infection and tissue damage mediated by intestinal flora imbalance (application effect); including: A. Schematic diagram of FMT model construction—a schematic diagram of the experimental procedure of zebrafish fecal microbiota transplantation (FMT), including antibiotic pretreatment, fecal microbiota transplantation and subsequent Mycobacterium marinum infection; B. CFU—bacterial load in zebrafish infected with Mm-Wasabi (1500~2000 CFU) for 7 days after fecal microbiota transplantation in the ABX + saline + Mm, ABX + HC-FMT + Mm and ABX + TB-FMT + Mm groups; C. Pathological HE—representative HE staining images of paraffin sections of the ABX + saline + Mm, ABX + HC-FMT + Mm and ABX + TB-FMT + Mm groups infected with Mm-Wasabi for 7 days after fecal microbiota transplantation, with red dashed lines indicating granulomas and yellow dashed lines indicating necrotic cores, scale bar = 100 μm; D. Granuloma Quantification – Quantitative analysis of granulomas in zebrafish in the ABX + saline + Mm, ABX + HC-FMT + Mm, and ABX + TB-FMT + Mm groups, with each point representing one zebrafish; E. Granuloma Area Quantification – Immune infiltration area in the ABX + saline + Mm, ABX + HC-FMT + Mm, and ABX + TB-FMT + Mm groups, with each point representing one zebrafish; F. Infiltrating Cell Quantity Quantification – Number of immune cells in the granuloma region of zebrafish in the ABX + saline + Mm, ABX + HC-FMT + Mm, and ABX + TB-FMT + Mm groups, with each point representing one zebrafish; G. Probiotic Transplantation – Colonization of zebrafish infected with Mm-Wasabi (1500~2000 CFU) 7 days after AKK bacterial transplantation; Data are expressed as mean ± standard error (SEM); One-way ANOVA was used. ANOVA, combined with corresponding post-hoc tests, is used to determine statistical significance; ns, not significant; p<0.05; p<0.01. Detailed Implementation

[0025] To make the technical solution of this application clearer and easier to understand, preferred embodiments are described in detail below with reference to the accompanying drawings.

[0026] Unless otherwise specified, the experimental or testing methods described in the following examples are conventional methods; the reagents and materials described are obtained from conventional commercial sources unless otherwise specified.

[0027] Example 1 To construct a zebrafish model of gut microbiota dysbiosis, this study administered oral gavage to adult zebrafish a mixture of antibiotics (ABX, antibiotics) including neomycin (Neo, 0.5 mg / kg), ampicillin (Amp, 0.5 mg / kg), metronidazole (Met, 0.25 mg / kg), and vancomycin (Van, 0.25 mg / kg). The control group received DMSO as a solvent. After 14 consecutive days, the entire gut of both groups of zebrafish was collected for 16S rRNA sequencing. Figure 1 A). The results showed that a total of 3607 microorganisms were detected in the ABX group, while 3261 microorganisms were detected in the control group. Figure 1 B). The species diversity heatmap showed that the gut microbiota composition of the ABX group was different from that of the control group. At the phylum level, the relative abundance of beneficial phyla such as Bacteroidetes and Firmicutes that produce SCFAs was significantly reduced in the ABX group, while the opportunistic and potentially pathogenic phyla such as Fusobacterium and Campylobacter were significantly enriched. Figure 1 C).

[0028] To further analyze the characteristics of the differentially expressed bacterial communities, linear discriminant effect size analysis (LEfSe) and linear discriminant analysis (LDA) with a score >2 were used to screen for genera with significant differences between groups. Figure 1 (D) The results showed that the control group was significantly enriched with a variety of key symbiotic bacteria, which participate in carbohydrate fermentation, the production of beneficial metabolites such as butyrate, and play an important role in maintaining intestinal homeostasis. These bacteria included Prevotellaceae, Lachnospiraceae_NK4A136_group, and Eubacterium_oxidoreducens_group. However, these bacteria were significantly depleted in the ABX group. Most of the bacteria enriched in the ABX group are distributed in the environment but are relatively rare in the gut, such as Rhodothermaceate, Myxococcales, and Gaiellaceae. In conclusion, the mixed antibiotic intervention significantly disturbed the gut microbiota structure of zebrafish, manifested as a reduction in beneficial symbiotic bacteria and an abnormal proliferation of potentially pathogenic or environment-related bacteria, suggesting that the gut microbiota dysbiosis model was successfully constructed.

[0029] Example 2 To investigate the impact of gut microbiota dysbiosis on mycobacterial infection, this example further established a Mycobacterium marinum infection model after gut microbiota dysbiosis in zebrafish. Figure 2 A), and systematically assessed the infection burden and host outcomes. Results showed that, compared to the control group, the ABX-treated group had a significantly higher level of Mycobacterium marineis CFU in zebrafish (A). Figure 2(B) suggests that disruption of gut microbiota homeostasis weakens the host's ability to resist mycobacterial infection. Further acid-fast staining confirmed this finding, revealing a large accumulation of acid-fast positive mycobacteria within the granulomas of the ABX group, primarily distributed in the necrotic core region of the granuloma (Figure 2C). Simultaneously, the survival rate of zebrafish in the ABX group after infection was significantly lower than that in the control group (Figure 2C). Figure 2 D). These results indicate that gut microbiota dysbiosis significantly increases the mycobacterial infection load, exacerbates disease progression, and ultimately leads to decreased host viability.

[0030] Example 3 Excessive activation of the inflammatory response is closely related to tissue damage and necrosis. Therefore, this study evaluated whether severe inflammatory response caused by gut microbiota dysbiosis affects the pathological features of tuberculous granulomas. Pathological results showed that the granuloma structure in the control group was relatively intact, mainly exhibiting the early stage of immune cell infiltration, while the granuloma structure in the ABX group was disordered, with a significantly enlarged necrotic core. Figure 3 A). Quantitative analysis further confirmed that ABX treatment significantly increased the number of granulomas ( Figure 3 B), and increased the proportion of necrotizing granulomas in total granulomas (B). Figure 3 C). Furthermore, the area of ​​individual granulomas was significantly larger in the ABX group ( Figure 3 D), accompanied by an increase in the overall level of immune cell infiltration within the granuloma ( Figure 3 E). The above results indicate that inflammatory imbalance induced by gut microbiota dysbiosis can significantly increase the burden of granulomas and promote the occurrence and development of necrotizing pathology.

[0031] Example 4 Next, to further verify the causal role of gut microbiota dysbiosis in uncontrolled mycobacterial infection and necrotizing pathogenesis, this embodiment further utilized fecal microbiota transplantation (FMT) to transplant fecal microbiota from healthy individuals and tuberculosis patients into zebrafish with antibiotic-induced gut microbiota dysbiosis. Figure 4A). The results showed that, without antibiotic treatment, there was no significant difference in bacterial load and histopathological damage between zebrafish transplanted with fecal microbiota from healthy individuals and the Mm-infected group alone. In contrast, after antibiotic treatment, the mycobacterial bacterial load in zebrafish receiving FMT from healthy individuals was significantly reduced (Figure 4B). Histopathological analysis further showed that FMT treatment significantly improved the structural integrity of granulomas and reduced necrotic areas (Figure 4C), while the number of granulomas, infiltration area, and level of immune cell infiltration were significantly reduced (Figures 4D-F). However, the above phenotypes were not improved in zebrafish receiving fecal microbiota from tuberculosis patients. In addition, the intervention effect of Akkermansia muciniphila (Akk), a probiotic that has been shown to have anti-mycobacterial activity in previous studies, was further evaluated in the context of intestinal flora imbalance. The results showed that Akk transplantation alone showed a consistent protective effect with FMT from healthy individuals in reducing bacterial load and improving pathological damage (Figure 4B). Figure 4 (G). In summary, restoring gut microbiota homeostasis can significantly reverse the uncontrolled mycobacterial infection and necrotic tissue damage mediated by dysbiosis, further supporting the key regulatory role of gut microbiota in the tuberculosis infection process.

[0032] The above description is merely a preferred embodiment of this application and is not intended to limit this application in any form or substance. It should be noted that those skilled in the art can make several improvements and additions without departing from this application, and these improvements and additions should also be considered within the scope of protection of this application.

Claims

1. A method for constructing a mycobacterial infection model in zebrafish after intestinal flora dysbiosis, characterized in that, include: A zebrafish gut microbiota dysbiosis model was constructed by treating with compound antibiotics. Then, a zebrafish mycobacterium infection model was constructed by injecting Mycobacterium marineum. The effects of gut microbiota status on the host's resistance to mycobacterial infection, as well as its effects on granuloma pathological changes and the immune microenvironment, were evaluated.

2. The construction method according to claim 1, characterized in that, The compound antibiotics consist of neomycin 0.5 mg / kg, ampicillin 0.5 mg / kg, metronidazole 0.25 mg / kg and vancomycin 0.25 mg / kg, all measured based on zebrafish body weight.

3. The construction method according to claim 1, characterized in that, It also includes a step of evaluating the zebrafish gut microbiota dysbiosis model, including verifying whether the gut microbiota dysbiosis model has been successfully constructed by evaluating the composition of the zebrafish gut microbiota.

4. The construction method according to claim 3, characterized in that, The evaluation of the zebrafish gut microbiota dysbiosis model included setting up a control group and an experimental group. The control group was treated with DMSO, while the experimental group was given oral administration of a compound antibiotic. The diversity and compositional changes of the gut microbiota in the control and experimental groups were evaluated and analyzed by 16S rRNA sequencing.

5. The construction method according to claim 1, characterized in that, The assessment of the influence of gut microbiota status on the host's resistance to mycobacterial infection was conducted by comparing the number of Mycobacterium marineis in zebrafish in the control and experimental groups. The control group was treated with DMSO and then injected with Mycobacterium marineis, while the experimental group was treated with a combination of antibiotics and then injected with Mycobacterium marineis.

6. The construction method according to claim 1, characterized in that, The assessment of the influence of gut microbiota status on the pathological changes of granulomas was performed by detecting the distribution of Mycobacterium marineis in zebrafish granulomas in the control and experimental groups using acid-fast staining. The control group was treated with DMSO and then injected with Mycobacterium marineis, while the experimental group was treated with compound antibiotics and then injected with Mycobacterium marineis.

7. The construction method according to claim 1, characterized in that, The assessment of the impact of gut microbiota status on the immune microenvironment includes evaluation by HE staining and quantitative statistics of at least one of the following: number of granulomas, percentage of granuloma necrosis, area of ​​granulomas, and number of granuloma immune cell infiltrations.

8. The application of a zebrafish intestinal flora dysbiosis-induced mycobacterial infection model in evaluating the efficacy of probiotics in treating tuberculosis, characterized in that... The zebrafish intestinal flora dysbiosis and mycobacterial infection model was constructed by treating zebrafish with compound antibiotics to create an intestinal flora dysbiosis model, followed by injection of Mycobacterium marineum to create a zebrafish intestinal flora dysbiosis and mycobacterial infection model.

9. A method for evaluating the efficacy of probiotics in treating tuberculosis based on a zebrafish intestinal flora dysbiosis-induced mycobacterial infection model, characterized in that, include: A zebrafish gut microbiota dysbiosis model was established by treating with compound antibiotics. Then, a zebrafish mycobacterium infection model was established by injecting Mycobacterium marineum. Probiotic treatment was then administered to evaluate the efficacy of probiotics in treating tuberculosis.

10. The method according to claim 9, characterized in that, The evaluation of the efficacy of probiotics in treating tuberculosis includes detecting the repair of granulomatous tissue damage through pathological HE staining and / or detecting the number of Mycobacterium marinum.

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