Clostridium perfringens in excrement as molecular marker for grading and judging fatty liver diseases related to metabolic dysfunction and application of clostridium perfringens

Abstract

The invention relates to clostridium perfringens in excrement as a molecular marker for grading and judging fatty liver diseases related to metabolic dysfunction and application of the clostridium perfringens, the clostridium perfringens contains alpha toxin CPA according to the types of main toxins generated by the clostridium perfringens, the coding gene of the alpha toxin CPA is plc gene, and the content of the alpha toxin CPA is determined by quantitatively detecting the plc gene. The molecular level detection of the clostridium perfringens in the excrement sample is realized; besides, the clostridium perfringens further contain nirA genes related to nitrogen metabolism, the nirA genes participate in the metabolic process related to microbial ammonia production, the functional state of the intestinal ammonia-producing microorganisms is reflected by detecting the expression level of the nirA genes, stable acquisition of the molecular characteristics of the intestinal microorganisms related to the MASLD is achieved, and the application prospect is broad. A molecular basis is provided for analyzing the correlation between the abnormal ammonia metabolism and the occurrence and development of the MASLD.

Description

Technical Field

[0001] This invention relates to the field of biomedical technology, and in particular to a molecular marker for grading metabolic dysfunction-associated steatotic liver disease (MASLD) using Clostridium perfringens in feces and its application. It is a molecular detection method for gut microbiota in the study of MASLD in non-human primate models. Background Technology

[0002] Metabolic dysfunction-associated fatty liver disease (MASLD) is a chronic liver disease characterized by hepatic lipid deposition, inflammation, and fibrosis progression. Its disease spectrum includes simple fatty liver disease (MASL) and metabolic dysfunction-associated steatohepatitis (MASH), and can further progress to liver fibrosis, cirrhosis, and even hepatocellular carcinoma. Epidemiological studies show that the prevalence of MASLD in the global population is approximately 25%, making it a significant risk factor for end-stage liver disease. However, effective treatments for MASLD, especially in its advanced stages, remain limited. Therefore, research into the pathogenesis, grading, assessment, and monitoring methods of MASLD is of great importance.

[0003] Previous studies have shown that hepatic ammonia metabolism disorder is one of the important pathological features in the progression of MASLD. With the continuous increase of intrahepatic ammonia load, hepatocellular inflammation and metabolic damage worsen, driving MASL to the MASH stage. Recent studies have shown that, in addition to host metabolic disorders, gut microbiota imbalance plays a key role in the occurrence and development of MASLD, among which the "gut-liver axis" mechanism has gradually received widespread attention.

[0004] In MASLD and related metabolic liver diseases, the intestinal barrier function is impaired, allowing enterogenic metabolites to enter the liver via the portal vein system, thereby exacerbating liver inflammation and metabolic burden. Ammonia, as an important enterogenic metabolite, is considered to be closely related to liver inflammation, mitochondrial dysfunction, and hepatocyte damage due to its abnormally elevated levels. Gut microbiota is one of the important sources of ammonia in the body, especially ammonia-producing intestinal bacteria, whose abundance and function may undergo significant changes under pathological conditions.

[0005] Clostridium perfringens ( Clostridium perfringens*Ammonia spp.* is a widely distributed opportunistic pathogen in the gut, belonging to the Gram-positive anaerobic bacteria. Its cell wall is thick and rich in peptidoglycan, giving it a strong capacity for protein and amino acid metabolism. It participates in ammonia production through multiple metabolic pathways. Under conditions of gut microbiota dysbiosis, an abnormally high abundance of *Ammonia spp.* may lead to increased intestinal ammonia production. Excess ammonia is absorbed through the intestine and enters the liver via the portal vein system, thus increasing the liver's detoxification burden. Abnormal accumulation of ammonia in the liver can induce mitochondrial dysfunction, increased oxidative stress, and activation of inflammatory signaling pathways in hepatocytes, further promoting hepatocyte damage and inflammatory responses. The article "The gut-liver axis and gut microbiota in health and liver disease. Nature Reviews" points out that through the synergistic effect of the "gut-liver axis" mechanism, it has a persistent adverse effect on liver structure and function, thereby promoting the progression of MASLD from the simple fat deposition stage to MASH and even liver fibrosis.

[0006] However, due to the dense cell wall structure of Gram-positive bacteria, they are highly resistant to chemical lysis and conventional lysis conditions, making it difficult to fully release their genomic DNA in fecal samples. Furthermore, there is currently a lack of mature solutions for the differentiated extraction of Gram-positive and Gram-negative bacteria from fecal samples. In the complex fecal matrix environment, these factors further increase the difficulty of nucleic acid extraction and detection of Clostridium perfringens, easily leading to low DNA extraction efficiency, insufficient detection sensitivity, and poor result stability. Therefore, how to efficiently extract Gram-positive bacterial DNA while ensuring nucleic acid integrity is one of the key technical challenges restricting the accuracy of its molecular detection.

[0007] Nitrate reductase-related genes (such as the nirA gene) play a crucial role in microbial nitrogen metabolism and ammonia production, and their expression levels can reflect the ammonia-producing potential of gut microbiota to some extent. Existing detection methods for Clostridium perfringens mainly include bacterial culture, conventional PCR, and microbial community analysis based on 16S rRNA sequencing. However, these methods generally suffer from limitations such as complex operation, long cycle time, high cost, or insufficient quantitative reproducibility, making it difficult to meet the stability and reproducibility requirements of MASLD grading.

[0008] Furthermore, the articles "Distinct modes of presynaptic inhibition of cutaneous aphrodisiacs and their functions in behavior. Neuron" and "Under diagnosed veno-occlusive disease / sinusoidal obstruction syndrome (VOD / SOS) as a major cause of multi-organ failure in acute leukemia transplant patients: An analysis from the EBMT acute leukemia working party. Bone Marrow Transplantation" point out that non-human primate models, especially monkey models, are widely used in MASLD-related research due to their high similarity to human physiological and metabolic characteristics. However, monkey fecal samples contain a large number of PCR inhibitors, and their microbial composition and cellular structure characteristics differ from those of humans. Existing nucleic acid extraction and detection methods established for humans or rodents are difficult to directly apply to monkey fecal samples, thus limiting the in-depth development of related research.

[0009] Currently, the clinical diagnosis and staging of MASLD mainly rely on imaging examinations, serum biochemical indicators, and liver histopathological assessment, with liver biopsy still considered the gold standard for diagnosis. However, these methods have limitations such as high invasiveness, poor patient compliance, difficulty in repeating monitoring, and inability to reflect early disease changes, restricting their widespread application in disease screening, dynamic monitoring, and basic research. Therefore, developing a novel diagnostic indicator based on non-invasive samples that can objectively reflect MASH-related pathological changes has significant clinical and research value.

[0010] Fecal samples are an important source of information on gut microbiota, offering advantages such as convenient collection, high reproducibility, and non-invasiveness. Given that *Clostridium perfringens* abundance increases under MASLD conditions and plays a crucial role in ammonia production and gut-hepatic axis regulation, changes in its fecal concentration are expected to reflect the state of gut ammonia-producing microbes and the associated hepatic metabolic burden. However, a standardized detection method is currently lacking for using quantitative results of *Clostridium perfringens* in feces for MASLD grading or auxiliary determination, especially when combined with efficient DNA extraction from Gram-positive bacteria and detection of ammonia-related functional genes. A mature, reliable, and applicable technical solution for monkey models has not yet been developed.

[0011] Therefore, it is necessary to establish a method that uses fecal samples as the detection target, quantitatively analyzes Clostridium perfringens, and combines its ammonia-related molecular characteristics to determine or assist in determining the status of MASLD, thereby providing new technical means and judgment basis for the study of MASLD mechanism, model evaluation, and effect assessment of related intervention measures. Summary of the Invention

[0012] To address the lack of existing methods for grading and diagnosing MASLD based on non-invasive samples, this invention aims to provide a molecular marker for grading metabolic dysfunction-related fatty liver disease (MASLD) using fecal Clostridium perfringens as a marker and its application. By using fecal samples as the detection target, quantitative analysis of fecal Clostridium perfringens and combining it with its ammonia-producing molecular characteristics, a correlation is established between the state of intestinal ammonia-producing microorganisms and the progression of MASLD, thereby achieving stratified assessment of different stages of MASLD.

[0013] To achieve the above objectives, the technical solution of the present invention is as follows: A fecal Clostridium perfringens strain is proposed as a molecular marker for grading metabolic dysfunction-related fatty liver disease (MASLD). The Clostridium perfringens strain is classified into at least five toxin types (A, B, C, D, and E) based on the main toxins it produces. All five toxin-typed strains contain the α-toxin CPA, encoded by the plc gene. Quantitative detection of the plc gene enables molecular-level detection of Clostridium perfringens in fecal samples. Furthermore, Clostridium perfringens also contains the nirA gene, which is involved in nitrogen metabolism and participates in microbial ammonia production-related metabolic processes. Detection of the nirA gene expression level reflects the functional status of intestinal ammonia-producing microorganisms, providing molecular evidence for analyzing the association between abnormal ammonia metabolism and the development of MASLD.

[0014] The nucleotide sequence of the forward amplification primer for the plc gene is SEQ ID NO.1, the nucleotide sequence of the reverse amplification primer is SEQ ID NO.2, and the probe sequence is SEQ ID NO.3.

[0015] The nucleotide sequence of the forward amplification primer for the aminogenin nirA is SEQ ID NO.4, and the nucleotide sequence of the reverse amplification primer is SEQ ID NO.5; the nucleotide sequence of the forward amplification primer for the internal reference gene rrs is SEQ ID NO.6, and the nucleotide sequence of the reverse amplification primer is SEQ ID NO.7.

[0016] The application of Clostridium perfringens in feces as a molecular marker for grading metabolic dysfunction-related fatty liver disease (MASLD), wherein the expression of the amino-producing factor nirA contained in Clostridium perfringens is positively correlated with the pathological severity of MASLD; and the toxin CPA contained in Clostridium perfringens is associated with the gene plc, the expression of the gene plc is positively correlated with the pathological severity of MASLD.

[0017] The specific application is as follows: Step 1: Using qPCR with TaqMan probe technology, obtain the Ct value of gene plc. Establish a standard curve based on the Ct value of the standard. Obtain the plc gene copy number of each sample based on the standard curve. Using qPCR, obtain the Ct values ​​of the amino-producing gene nirA and the internal reference gene rrs, respectively. Subtract the Ct value of rrs from the Ct value of nirA to obtain ΔCt, and obtain the relative quantitative value of nirA 2^(-ΔCt). Step 2: Construct an ROC curve by incorporating the obtained plc gene copy number or relative quantitative value of nirA 2^(-ΔCt) and the MASLD state to be identified into variables. Select the point corresponding to the maximum sum of sensitivity and specificity in the coordinate correspondence table as the cut-off point of the ROC curve, which is the critical point used to determine whether the sample is in the first or second state. The MASLD state to be identified is obtained based on liver pathological staining and NAS scoring and fibrosis staging.

[0018] Step 3: The cutoff value obtained from the ROC curve constructed by the state information of healthy individuals and MASLD with gene copy number / relative quantitative value is recorded as the critical value (Ca); the cutoff value obtained from the ROC curve constructed by the state information of simple MASL and MASH with gene copy number / relative quantitative value is recorded as the second critical value (Cb); the cutoff value obtained from the ROC curve constructed by the state information of the presence or absence of liver fibrosis with gene copy number / relative quantitative value is recorded as the third critical value (Cc). Step 4: The plc gene copy number or nirA relative quantitative value obtained in Step 1, denoted as X, is compared with the critical value (Ca), second critical value (Cb), and third critical value (Cc) in Step 3 to output the graded diagnostic result. If X≤Ca, then it is interpreted as "healthy"; If Ca < X ≤ Cb, then it is interpreted as "simple fatty liver (MASL)"; If X > Cb, then it is interpreted as "metabolic steatohepatitis (MASH)"; If X > Cc, then it is interpreted as "liver fibrosis exists".

[0019] The advantages of this invention are: 1. This invention uses the plc gene of Clostridium perfringens as a molecular marker for MASLD grading, which has advantages such as high conservation, coverage of different toxin-type strains, and strong detection stability. plc can be absolutely quantified using real-time quantitative PCR, with high sensitivity and good reproducibility. Its expression level varies between different stages of MASLD, allowing for the establishment of cutoff values ​​for disease grading, demonstrating significant application value.

[0020] 2. This invention provides a method for quantitative detection of Clostridium perfringens based on fecal samples, combined with its ammonia-related molecular characteristics, for determining or assisting in the determination of different disease stages of MASLD. This method can achieve stable detection of Gram-positive Clostridium perfringens under complex fecal matrix conditions, improve detection sensitivity, repeatability and result consistency, and make the obtained detection results reflect the changing trend of intestinal ammonia-producing microbial status and correlate with the disease grading of MASLD.

[0021] In summary, the method provided by this invention has the advantages of being non-invasive, easy to operate, and capable of repeatable monitoring. It is applicable to fecal samples from different sources, and is particularly suitable for the dynamic assessment of different stages of MASLD in non-human primate models. It can provide new technical means and judgment criteria for the graded diagnosis, disease progression monitoring, and intervention effect evaluation of MASLD. Furthermore, this method can be used in conjunction with existing biochemical indicators, imaging examinations, or histological evaluation results to improve the accuracy and comprehensiveness of MASLD graded diagnosis. Attached Figure Description

[0022] Figure 1 NAS scores for liver specimens from healthy cynomolgus monkeys and MASLD model cynomolgus monkeys.

[0023] Figure 2 The study aimed to detect differences in fecal plc gene expression levels in healthy, simple MASL, and MASH cynomolgus monkeys.

[0024] Figure 3 The study aimed to detect differences in fecal nirA gene expression levels among healthy, simple MASL, and MASH cynomolgus monkeys.

[0025] Figure 4 This is an ROC curve showing the expression of the plc gene in cynomolgus feces in distinguishing between healthy individuals and those with MASLD.

[0026] Figure 5 This is a ROC curve showing the expression of the nirA gene in the feces of cynomolgus monkeys in identifying healthy individuals and those with MASLD.

[0027] Figure 6This is the ROC curve of plc gene expression in cynomolgus feces to identify healthy and simple MASL.

[0028] Figure 7 This is the ROC curve of nirA gene expression in cynomolgus feces to identify healthy and simple MASL.

[0029] Figure 8 This is the ROC curve of plc gene expression in cynomolgus feces to identify simple MASL and MASH.

[0030] Figure 9 This is the ROC curve of nirA gene expression in cynomolgus feces recognizing simple MASL and MASH.

[0031] Figure 10 This is an ROC curve of plc gene expression in cynomolgus feces to identify the presence of liver fibrosis.

[0032] Figure 11 This is a ROC curve of nirA gene expression in cynomolgus feces to identify the presence of liver fibrosis. Detailed Implementation

[0033] The present invention will be further described below with reference to the embodiments.

[0034] Example 1 Example 1: Constructing a core hierarchical interpretation module for cynomolgus monkeys using the MASLD / MASH model. (1) Screening of spontaneous MASLD cynomolgus monkeys All experimental protocols involving non-human primates were approved by the Experimental Animal Use and Management Committee of Xi'an Jiaotong University. Forty-one cynomolgus monkeys were selected from the Guangdong Landao Biotechnology Base and housed individually with free access to food and water. The rearing environment was a temperature-controlled room (22℃ to 26℃) with a 12-hour light-dark cycle.

[0035] Under ultrasound guidance, liver biopsies were performed on all cynomolgus monkeys using a Bard Magnum biopsy gun equipped with a 17G biopsy needle. The obtained liver tissue samples were fixed in formalin for subsequent pathological analysis. Simultaneously, corresponding fecal samples were collected, and fecal genomic DNA was extracted according to standardized procedures. The expression levels of plc and nirA were also detected.

[0036] (2) Fecal DNA extraction Collect frozen or fresh fecal samples, weigh 50–200 mg, and add them together with the grinding beads into a grinding tube. Add 500 μL of lysis buffer and 20–50 μL of lysozyme, and perform mechanical grinding. After grinding, incubate the sample in a 37°C water bath for 2–5 hours, inverting and mixing every 15 minutes to ensure complete lysis of bacterial cells.

[0037] After lysis, 15 μL of Proteinase K was added to the sample, vortexed thoroughly, and heated in a 70°C water bath for 15 minutes to further digest the protein. Then, the sample was centrifuged at 12,000 rpm for 3 minutes, and the supernatant was transferred to a new centrifuge tube. 10 μL of RNase A was added, vortexed for 30 seconds, and incubated at room temperature for 5 minutes.

[0038] Add 200 μL of binding buffer PS to the above mixture to adjust the salt concentration and ionic strength of the solution to facilitate the binding of DNA to the silica membrane. Vortex mix for 30 seconds, place on ice for 5 minutes, and then centrifuge at 12,000 rpm for 5 minutes. Transfer the supernatant to a new centrifuge tube and add an equal volume of washing buffer BS-5 to remove non-DNA impurities.

[0039] The resulting solution was then added entirely to the DNA binding column. After standing for 1 minute, the column was centrifuged at 12,000 rpm for 1 minute, and the filtrate was discarded. 500 μL of protein washing buffer and 750 μL of salt ion washing buffer were added sequentially to the binding column for washing. After each wash, the column was centrifuged at 12,000 rpm for 1 minute, and the filtrate was discarded. The salt ion washing was repeated once. Finally, the binding column was placed in a new collection tube and centrifuged at 12,000 rpm for 2 minutes to remove residual washing buffer. The column was then allowed to air dry at room temperature for 5–10 minutes to allow the washing buffer to evaporate.

[0040] Place the DNA binding column in a new centrifuge tube, add 40-60 μL of preheated elution buffer to the center of the adsorption membrane, let it stand at room temperature for 2 minutes, then centrifuge at 12,000 rpm for 2 minutes. Add the resulting elution buffer back to the center of the adsorption membrane and repeat the elution once. This method significantly increases the concentration of DNA extracted compared to that extracted by a general kit, thus obtaining high-concentration fecal genomic DNA.

[0041] To overcome the presence of a large amount of PCR inhibitors in the monkey fecal samples mentioned above, we serially diluted the DNA and found that a 10-fold dilution was the most effective, resulting in a suitable ct value for qPCR.

[0042] (3) Detecting PLC expression levels Using qPCR with TaqMan probes (TaqMan-PCR) technology, the Ct value of gene plc was obtained. A standard curve was established based on the Ct value of the standard, and the plc gene copy number of each sample was obtained based on the standard curve. Using qPCR technology, the Ct values ​​of the amino-producing gene nirA and the internal reference gene rrs were obtained respectively. The Ct value of nirA was subtracted from the Ct value of rrs to obtain ΔCt, and the relative quantitative value of nirA, 2^(-ΔCt), was obtained. qPCR reactions were performed using the TaqMan method on a CFX96 system. A 20 μL reaction mixture contained 2×TaqMan FastqPCR Master Mix, forward and reverse primers, and DNA template. The reaction program was 94°C pre-denaturation for 3 minutes, followed by 40 cycles of amplification at 94°C for 5 seconds, 50°C for 15 seconds, and 72°C for 30 seconds. The absolute expression level of the target gene was calculated based on the standard curve.

[0043] (4) Detecting nirA expression level qPCR reactions were performed using the SYBR Green assay on a CFX96 system. A 20 μL reaction mixture contained 2×SYBR Premix, forward and reverse primers, and DNA template. The reaction program was 95°C pre-denaturation for 30 seconds, followed by 40 cycles of amplification at 95°C for 5 seconds and 60°C for 30 seconds. The relative expression levels of the target gene compared to the internal control gene were calculated using the 2^(-ΔCt) method, or further, the relative expression levels compared to the healthy control group were calculated using the 2^(-ΔΔCt) method.

[0044] (5) Liver pathological staining and scoring Cynomolgus monkey liver tissue was fixed in 4% paraformaldehyde, embedded in paraffin, and sectioned. Sections were then subjected to hepatological staining, specifically H&E staining and Sirius red staining. Nonalcoholic fatty liver disease activity (NAS) was assessed based on histological characteristics, including hepatocellular steatosis, intralobular inflammation, and hepatocellular ballooning degeneration, and liver fibrosis was staged according to the METAVIR scoring system. All sections were independently reviewed by at least two pathologists unaware of their grouping information.

[0045] Table 1 shows the results of the crab consumption group as determined by the PLC gene core grading interpretation module. The results in parentheses are the pathological results determined by pathology experts based on liver biopsy.

[0046] serial number Copy / ul MASLD status Liver fibrosis is present. NO.1 0.2695 Health No (No) NO.2 4.6960 MASL (MASL) No (No) NO.3 1.1356 MASL (Health) No (No) NO.4 2.5154 MASL (MASL) No (No) NO.5 11.8575 MASH (MASH) Yes (Yes) NO.6 6.1334 MASL (MASL) No (Yes) NO.7 0.1564 Health No (No) NO.8 22.5570 MASH (MASH) Yes (Yes) NO.9 1.8465 MASL (MASL) No (No) NO.10 0.3249 Health No (No) NO.11 2.2055 MASL (MASL) No (No) NO.12 2.2457 MASL (MASL) No (No) NO.13 1.3781 Health (MASL) No (No) NO.14 0.3647 Health No (No) NO.15 5.2432 MASL (MASL) No (No) NO.16 23.5177 MASH (MASH) Yes (Yes) NO.17 10.7092 MASH (MASH) Yes (Yes) NO.18 0.6124 Health No (No) NO.19 0.0916 Health No (No) NO.20 5.9090 MASL (MASL) No (No) Table 2 shows the results of the crab consumption in the validation group as determined by the nirA gene core grading interpretation module. The results in parentheses are the pathological results determined by pathologists based on liver biopsy.

[0047] serial number 2^(-ΔCt) MASLD status Liver fibrosis is present NO.1 0.119856 Health No (No) NO.2 0.41448 Health No (No) NO.3 2.850601 MASL (MASL) No (No) NO.4 2.132393 MASL (MASL) No (No) NO.5 0.570135 Health No (No) NO.6 7.461031 MASH (MASL) No (No) NO.7 0.582115 Health (MASL) No (No) NO.8 2.023895 MASL (MASL) No (No) NO.9 4.592803 MASL (MASL) No (No) NO.10 0.084751 Health No (No) NO.11 8.99657 MASH (MASH) No (No) NO.12 3.071309 MASL (MASH) No (No) NO.13 4.226241 MASL (MASH) No (No) NO.14 5.773215 MASH (MASH) No (No) NO.15 4.026078 MASL (Health) No (No) NO.16 233.8395 MASH (MASH) whether) NO.17 17.02255 MASH (MASH) Yes (Yes) NO.18 28.82752 MASH (MASH) Yes (Yes) NO.19 9.509536 MASH (MASH) No (Yes) NO.20 13.92278 MASH (MASH) Yes (Yes) (5) Data Analysis In cynomolgus monkey studies, cynomolgus monkeys were divided into healthy, simple MASL, and MASH groups based on pathological staining, NAS scores, and liver fibrosis staging. Figure 1 Meanwhile, the relative expression levels of the plc and nirA genes in the feces of MASL and MASH cynomolgus monkeys compared to those in healthy cynomolgus monkeys were calculated using standard curves. Significant differences in the expression of plc and nirA in the tested feces were observed among the three states. Figure 2 , Figure 3 ), of which the expression of the plc gene p <0.001, positively correlated with the severity of MASLD, and statistically significant.

[0048] The plc gene in the feces of cynomolgus monkeys was analyzed using SPSS software. Figure 4 ) and nirA gene ( Figure 5 The ROC curves of plc gene expression for identifying healthy individuals and those with MASLD were plotted. The area under the ROC curve (AUC) for plc gene was 0.903, with a specificity of 73.3% and a sensitivity of 95.8%. p <0.001, statistically significant; the area under the ROC curve (AUC) of the nirA gene was 0.862, with a specificity of 75% and a sensitivity of 87%. p A value <0.001 is statistically significant, indicating that the expression levels of fecal plc and nirA can be used to distinguish between healthy individuals and those with MASLD. (Note: The reference line is the opportunity diagonal; the area under the reference line (AUC) is 0.5. Below this value, the diagnostic method has no diagnostic value whatsoever.) Furthermore, the plc gene in cynomolgus feces was analyzed using SPSS software. Figure 6 ) and nirA gene ( Figure 7 ROC curves for identifying healthy and simple MASL were plotted. The area under the ROC curve for the plc gene was 0.821, with a specificity of 66.7%, a sensitivity of 100%, and a cutoff value of 1.05. p <0.001, statistically significant; the area under the ROC curve for the nirA gene was 0.785, with a specificity of 75%, a sensitivity of 100%, and a cutoff value of 1.98. p =0.018, which is statistically significant, indicating that the expression levels of fecal PLC and NirA can be used to distinguish between healthy and simple MASL. (Note: The reference line is the chance diagonal; AUC is 0.5. Below this line, the diagnostic method has no diagnostic value.) Furthermore, the plc gene in cynomolgus feces was analyzed using SPSS software. Figure 8 ) and nirA gene ( Figure 9 ROC curves for identifying simple MASL and MASH were plotted. The area under the ROC curve for the plc gene was 0.946, with a specificity of 84.6%, a sensitivity of 100%, and a cutoff value of 6.65. p <0.001; the area under the ROC curve for the nirA gene was 0.825, with a specificity of 70%, a sensitivity of 100%, and a cutoff value of 4.822. p= 0.066, indicating that the expression levels of fecal plc and nirA can be used to identify simple MASL and MASH. (Note: The reference line is the chance diagonal, with an AUC of 0.5. Below this line, the diagnostic method has no diagnostic value.) Furthermore, the ROC curve for analyzing the plc gene ( Figure 10 ) and the nirA gene ( Figure 11 ) in the feces of cynomolgus monkeys to identify the presence of liver fibrosis was generated using SPSS software. The area under the ROC curve for the plc gene was 0.99, the specificity was 97%, the sensitivity was 100%, and the cut-off value was 9.25, p <0.001; the area under the ROC curve for the nirA gene was 0.882, the specificity was 100%, the sensitivity was 75.9%, and the cut-off value was 11.5, p <0.001. This indicates that the expression levels of fecal plc and nirA can be used to identify the presence of liver fibrosis. (Note: The reference line is the chance diagonal, with an AUC of 0.5. Below this line, the diagnostic method has no diagnostic value.) Furthermore, the cut-off values obtained from the ROC curves constructed with the status information of health and MASLD and the gene copy number / relative quantification values were denoted as the critical value (C-a); the cut-off values obtained from the ROC curves constructed with the status information of simple MASL and MASH and the gene copy number / relative quantification values were denoted as the second critical value (C-b); the cut-off values obtained from the ROC curves constructed with the status information of the presence or absence of liver fibrosis and the gene copy number / relative quantification values were denoted as the third critical value (C-c); For plc quantification: The absolute quantification value of plc (copies / μL) obtained from the standardized detection (denoted as Xp) was compared with the preset first critical value (1.05), second critical value (***6.65***), and third critical value (9.25) to output a graded diagnostic result: If Xp ≤ 1.05, it was interpreted as "healthy"; If 1.05 < Xp ≤ 6.65, it was interpreted as "simple MASL"; If Xp > 6.65, it was interpreted as "metabolic associated steatohepatitis (MASH)"; If Xp > 9.25, it was interpreted as "liver fibrosis present" For nirA quantification: The module compared the relative quantification value of nirA, 2^(-ΔCt) (denoted as Xn), obtained from the standardized detection with the preset first critical value (1.98), second critical value (4.822), and third critical value (11.5) to output a graded diagnostic result: If Xn ≤ 1.98, it was interpreted as "healthy"; It should be noted that there seems to be a formatting issue in the original text where "***6.65***" is presented in an unusual way. I've left it as it is in the translation for consistency with the provided text. If this is an error, it might need to be corrected in the original source for a more accurate translation.If 1.98 < Xn ≤ 4.822, it is judged as "simple MASL"; If Xn > 4.822, it is judged as "metabolic associated steatohepatitis (MASH)"; If Xn > 11.5, it is judged as "liver fibrosis exists" Example 2: Verification of the core grading and interpretation module Forty cynomolgus monkeys were randomly selected outside the group used for constructing the scheme, and the absolute quantitative values of the corresponding feces were obtained through standardized sample processing and detection. The status of each cynomolgus monkey was interpreted according to the core grading and interpretation module. In addition, 40 cynomolgus monkeys were subjected to liver biopsy, and liver tissue specimens were taken for pathological staining and pathological diagnosis according to NAS score and fibrosis stage. The status of cynomolgus monkeys obtained through the core grading and interpretation module was compared with the pathological diagnosis to verify the accuracy of the scheme.

[0049] Specifically: Forty cynomolgus monkeys were randomly selected from the Guangdong Blue Island Biotechnology Base as the verification group. Two researchers each detected the expression levels of plc and nirA in the feces of 20 cynomolgus monkeys through standardized sample processing. At the same time, two other pathologists who were unaware of the grouping independently reviewed the liver pathology of the 40 cynomolgus monkeys in the verification group. The results showed that according to the above-mentioned plc gene core interpretation module (Table 1), the accuracy rate of identifying whether MASLD is diseased was 92%, the accuracy rate of identifying health was 85%, the accuracy rate of identifying simple MASL was 89%, the accuracy rate of identifying MASH was 100%, and the accuracy rate of identifying whether liver fibrosis exists was 95%. According to the above-mentioned nirA gene core interpretation module (Table 2), the accuracy rate of identifying whether MASLD is diseased was 93%, the accuracy rate of identifying health was 80%, the accuracy rate of identifying simple MASL was 83%, the accuracy rate of identifying MASH was 89%, and the accuracy rate of identifying whether liver fibrosis exists was 90%.

[0050] Based on Example 1 and Example 2, the following conclusions are drawn: Clostridium perfringens in feces is used as a molecular marker for grading metabolic dysfunction-related fatty liver disease. The Clostridium perfringens includes at least five toxin typing, namely A, B, C, D, and E, according to the main toxin types it produces. The five toxin typing strains all contain α-toxin CPA, and the coding gene of α-toxin CPA is the plc gene. By quantitatively detecting the plc gene, the molecular level detection of Clostridium perfringens in fecal samples is achieved. In addition, the Clostridium perfringens also contains the nirA gene related to nitrogen metabolism. This nirA gene participates in the metabolic process related to microbial ammonia production. By detecting the expression level of the nirA gene, the functional status of ammonia-producing microorganisms in the intestine is reflected, providing a molecular basis for analyzing the association between abnormal ammonia metabolism and the occurrence and development of MASLD.

[0051] The nucleotide sequence of the forward amplification primer for the plc gene is SEQ ID NO.1, the nucleotide sequence of the reverse amplification primer is SEQ ID NO.2, and the probe sequence is SEQ ID NO.3.

[0052] The nucleotide sequence of the forward amplification primer for the aminogenin nirA is SEQ ID NO.4, and the nucleotide sequence of the reverse amplification primer is SEQ ID NO.5; the nucleotide sequence of the forward amplification primer for the internal reference gene rrs is SEQ ID NO.6, and the nucleotide sequence of the reverse amplification primer is SEQ ID NO.7.

[0053] The application of Clostridium perfringens in feces as a molecular marker for grading metabolic dysfunction-related fatty liver disease (MASLD), wherein the expression of the amino-producing factor nirA contained in Clostridium perfringens is positively correlated with the pathological severity of MASLD; and the toxin CPA contained in Clostridium perfringens is associated with the gene plc, the expression of the gene plc is positively correlated with the pathological severity of MASLD.

[0054] In summary, this invention relates to the extraction, identification, and quantitative analysis of intestinal microbiota DNA in non-human primate fecal samples, establishes a nucleic acid extraction and detection system suitable for complex fecal matrix conditions, achieves stable acquisition of intestinal microbial molecular characteristics related to MASLD, and provides technical support for the assessment of different disease stages of MASLD and related research.

Claims

1. A fecal Clostridium perfringens molecular marker for grading metabolic dysfunction-related fatty liver disease, characterized in that, The *Clostridium perfringens* strain is classified into at least five toxin types—A, B, C, D, and E—based on the main toxins it produces. All five toxin-typed strains contain the α-toxin CPA, encoded by the plc gene. Quantitative detection of the plc gene allows for molecular-level detection of *Clostridium perfringens* in fecal samples. Furthermore, *Clostridium perfringens* also contains the nirA gene, which is involved in nitrogen metabolism and participates in microbial ammonia production-related metabolic processes. Detection of the nirA gene expression level reflects the functional status of intestinal ammonia-producing microorganisms, providing molecular evidence for analyzing the association between abnormal ammonia metabolism and the development of MASLD.

2. The method according to claim 1, using *Clostridium perfringens* in feces as a molecular marker for grading metabolic dysfunction-related fatty liver disease, is characterized in that... The nucleotide sequence of the forward amplification primer for the plc gene is SEQ ID NO.1, the nucleotide sequence of the reverse amplification primer is SEQ ID NO.2, and the probe sequence is SEQ ID NO.

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3. The method according to claim 1, using *Clostridium perfringens* in feces as a molecular marker for grading metabolic dysfunction-related fatty liver disease, is characterized in that... The nucleotide sequence of the forward amplification primer for the aminogenin nirA is SEQ ID NO.4, and the nucleotide sequence of the reverse amplification primer is SEQ ID NO.5; the nucleotide sequence of the forward amplification primer for the internal reference gene rrs is SEQ ID NO.6, and the nucleotide sequence of the reverse amplification primer is SEQ ID NO.

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4. The application of *Clostridium perfringens* in feces as a molecular marker for grading metabolic dysfunction-related fatty liver disease according to claim 1, characterized in that... The expression of the amino-producing factor nirA in Clostridium perfringens is positively correlated with the pathological severity of MASLD; Clostridium perfringens contains toxin CPA associated with gene plc, and the expression of gene plc is positively correlated with the pathological severity of MASLD.

5. The application of *Clostridium perfringens* in feces as a molecular marker for grading metabolic dysfunction-related fatty liver disease according to claim 4, characterized in that... The specific application is as follows: Step 1: Using qPCR with TaqMan probe technology, obtain the Ct value of gene plc. Establish a standard curve based on the Ct value of the standard. Obtain the plc gene copy number of each sample based on the standard curve. Using qPCR, obtain the Ct values ​​of the amino-producing gene nirA and the internal reference gene rrs, respectively. Subtract the Ct value of rrs from the Ct value of nirA to obtain ΔCt, and obtain the relative quantitative value of nirA 2^(-ΔCt). Step 2: Construct an ROC curve by incorporating the obtained plc gene copy number or relative quantitative value of nirA 2^(-ΔCt) and the MASLD state to be identified into variables. Select the point corresponding to the maximum sum of sensitivity and specificity in the coordinate correspondence table as the cut-off point of the ROC curve, which is the critical point used to determine whether the sample is in the first or second state. The MASLD state to be identified is obtained based on liver pathological staining and NAS scoring and fibrosis staging. Step 3: The cutoff value obtained from the ROC curve constructed by the state information of healthy individuals and MASLD with gene copy number / relative quantitative value is recorded as the critical value (Ca); the cutoff value obtained from the ROC curve constructed by the state information of simple MASL and MASH with gene copy number / relative quantitative value is recorded as the second critical value (Cb); the cutoff value obtained from the ROC curve constructed by the state information of the presence or absence of liver fibrosis with gene copy number / relative quantitative value is recorded as the third critical value (Cc). Step 4: The plc gene copy number or nirA relative quantitative value obtained in Step 1, denoted as X, is compared with the critical value (Ca), second critical value (Cb), and third critical value (Cc) in Step 3 to output the graded diagnostic result. If X≤Ca, then it is interpreted as "healthy"; If Ca < X ≤ Cb, then it is interpreted as "simple fatty liver (MASL)"; If X > Cb, then it is interpreted as "metabolic steatohepatitis (MASH)"; If X > Cc, then it is interpreted as "liver fibrosis exists".

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