Clostridium difficile infection-related intestinal flora marker and application thereof
By discovering and using Lachnoclostridium, Fusobacterium, and Clostridioides associated with Clostridium difficile infection as intestinal flora markers, the diagnosis of Clostridioides in the prior art was solved. The deficiency has achieved high sensitivity and high specificity diagnostic effects.
Patent Information
- Application Number
- CN202411477631.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-22
- Publication Date
- 2025-02-07
AI Technical Summary
The prior art is difficult to effectively diagnose and predict C. difficile infection, especially in recurrence, and there is a lack of diagnostic methods with high sensitivity and high specificity.
By collecting intestinal samples from patients with C. difficile infected patients and healthy people, 16S V3-V4 rRNA gene amplicon sequencing and bioinformatics analysis, it was found that Lachnoclostridium, Fusobacterium, and Clostridium spores were found. Clostridioides of the genus Clostridioides are associated with Clostridioides infection and are used as a marker of intestinal flora to predict Clostridioides infection.
High sensitivity and high specificity diagnosis for C. difficile infection has been achieved. By detecting the abundance changes of these bacterial genus, infection can be accurately predicted, providing a new basis for diagnosis and treatment.
Smart Images
Figure CN119391881A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the field of biomedical technology, and specifically relates to an intestinal flora marker associated with Clostridium difficile infection and its application in the diagnosis and treatment of Clostridium difficile infection. Background Art
[0002] Clostridium difficile (C. difficile) is an anaerobic, spore-forming Gram-positive bacillus. The spores of C. difficile are transmitted through the fecal-oral route, and the pathogen is widely distributed in the intestines of humans and animals and the environment. Currently, the frequency and severity of Clostridium difficile infection (CDI) are increasing worldwide and has become one of the most common hospital-acquired infections. The clinical manifestations of C. difficile infection are diverse, ranging from asymptomatic carrier status to varying degrees of diarrhea to the most severe life-threatening colitis, ultimately leading to death. Clinically, approximately 50% to 75% of antibiotic-associated colitis and 95% to 100% of pseudomembranous colitis are caused by C. difficile.
[0003] Although C. difficile infection can be alleviated with oral metronidazole, vancomycin, and fidaxomicin, the recurrence rate is high. Recurrence of CDI symptoms most commonly occurs in the first week after treatment. After effective treatment of the first CDI episode, 10-25% of patients experience at least one new recurrent episode, and up to 65% of patients with more than one recurrent CDI episode. Impaired immune response to C. difficile toxins and new exposure to spores are thought to contribute to recurrence.
[0004] The clinical diagnosis of CDI is usually based on direct detection of Clostridium difficile toxins in stool, most commonly using EIA, but no single test is suitable as a single test to confirm CDI. Therefore, there is an urgent need to develop more diagnostic methods to predict CDI and provide a basis for disease treatment. Summary of the invention
[0005] In view of the problems in the prior art, the present invention provides an intestinal flora marker associated with Clostridium difficile infection. The intestinal flora marker has high sensitivity and specificity and can be used as a predictive factor for Clostridium difficile infection.
[0006] The technical solution of the present invention is as follows: The first aspect of the present invention provides an intestinal flora marker associated with Clostridium difficile infection, wherein the intestinal flora marker is specifically composed of Clostridium laxative Lachnoclostridium Fusobacterium Fusobacterium , Clostridium Clostridioides composition.
[0007] The present invention collects intestinal samples from patients with Clostridium difficile infection and healthy people, performs 16S V3-V4 rRNA gene amplicon sequencing and bioinformatics analysis, and discovers Clostridium laxative bacteria of the genus Lachnoclostridium Fusobacterium Fusobacterium , Clostridium Clostridioides Related to Clostridium difficile infection; the present invention integrates intestinal flora with disease information to obtain intestinal flora markers that can predict Clostridium difficile infection in patients.
[0008] The second aspect of the present invention provides the use of the intestinal flora marker associated with Clostridium difficile infection in detecting Clostridium difficile infection in an individual, specifically: detecting Clostridium laxigera Lachnoclostridium Fusobacterium Fusobacterium , Clostridium Clostridioides The abundance changes in the intestine of the test subjects were significantly increased (p < 0.05, FDR < 0.05) when the test subjects had Clostridium laxemii spp. compared with healthy subjects. Lachnoclostridium Fusobacterium Fusobacterium and Clostridium Clostridioides Abundance ， The individual to be tested suffers from Clostridium difficile infection.
[0009] The Clostridium laxemii of the present invention Lachnoclostridium Fusobacterium Fusobacterium , Clostridium Clostridioides It was first discovered to be associated with Clostridium difficile infection, and the experimental results showed that when the ROC curve was used to analyze the above three bacterial genera as detection variables, it had very high specificity (100%) and sensitivity (100%). Therefore, the three bacterial genera described in the present invention can be used as detection markers for the accurate diagnosis of patients with Clostridium difficile infection.
[0010] The third aspect of the present invention provides the use of the intestinal flora markers associated with Clostridium difficile infection in the preparation of Clostridium difficile infection diagnostic products, the products including but not limited to primers, reagents, detection kits, gene chips and Clostridium difficile infection prediction systems, etc., the products are used to detect the abundance of intestinal flora markers in subjects and / or predict the possibility of Clostridium difficile infection based on the abundance of intestinal flora markers.
[0011] Preferably, in the above application, the Clostridium difficile infection diagnostic product is a detection kit, which includes reagents for detecting the abundance of the intestinal flora markers in the fecal samples of subjects; wherein, the reagents can analyze the abundance of the intestinal flora markers by polymerase chain reaction, sequencing, isothermal amplification, bioinformatics or a combination thereof.
[0012] More preferably, in the above application, the reagent is a primer for detecting 16SrRNA, a marker of intestinal flora.
[0013] Preferably, in the above application, the Clostridium difficile infection diagnostic product is a Clostridium difficile infection prediction system, and the prediction system uses the abundance of the intestinal flora marker in the subject's fecal sample as a detection variable.
[0014] A fourth aspect of the present invention provides a method for establishing a prediction system for Clostridium difficile infection derived from intestinal flora, comprising the following steps: S1. Determine the inclusion criteria for patients with Clostridium difficile infection and healthy subjects; S2. Collect stool samples from patients with Clostridium difficile infection and healthy people, extract, amplify, build libraries and perform metagenomic sequencing on the microbial genomic DNA in the stool samples to obtain raw data; S3. Use the same quality control and analysis methods to perform quality control on the original data; S4. Use the same method to analyze the relative abundance of intestinal microbial flora; S5. Screen out differential bacteria and analyze the effect size through rank sum test and linear discriminant analysis; S6. Binary logistic regression test of the true positive rate and true negative rate of the differential bacteria.
[0015] The fifth aspect of the present invention provides an application of an intestinal flora marker associated with Clostridium difficile infection in screening drugs for treating Clostridium difficile infection or health foods for alleviating Clostridium difficile infection, specifically: screening out Clostridium laxellii in the intestines of patients with Clostridium difficile infection Lachnoclostridium Fusobacterium Fusobacterium Clostridium Clostridioides The substance with reduced abundance is used as the medicine or health food.
[0016] Compared with the prior art, the beneficial effects of the present invention are: (1) The present invention discovered for the first time the genus Clostridium laxemi Lachnoclostridium Fusobacterium Fusobacterium and Clostridium Clostridioides In association with C. difficile infection, these 3 genera were significantly increased in the C. difficile infected patient population.
[0017] (2) The present invention has established a prediction system for the possibility of Clostridium difficile infection using the above three bacterial genera, verified the prediction effect of these three bacterial genera, and the results of ROC curve analysis showed that the three bacterial genera combined as detection variables have very high specificity and sensitivity. Therefore, they can be used as detection markers for the diagnosis of patients with Clostridium difficile infection. The detection is completely non-invasive and highly accurate.
[0018] (3) Compared with the existing patents 201520382937.X, 202023052163.4, and 202111080946.X which only detect Clostridium difficile nucleic acid, the present invention integrates intestinal flora with disease information and uses intestinal symbiotic flora as a detection marker for Clostridium difficile infection. The detection results are not only reliable, but also can reflect the disordered state of intestinal flora. BRIEF DESCRIPTION OF THE DRAWINGS
[0019] Figure 1 A technical roadmap for the method of establishing a prediction system for Clostridium difficile infection derived from intestinal flora for the present invention.
[0020] Figure 2 This is an experimental flow chart for screening and verifying intestinal flora markers associated with Clostridium difficile infection in Example 1 of the present invention.
[0021] Figure 3 This is the LEfSe score diagram of the three bacterial genera in Example 1.
[0022] Figure 4 This is a box scatter plot of the three bacterial genera in Example 1.
[0023] Figure 5 This is the ROC curve diagram in Example 1. DETAILED DESCRIPTION
[0024] In order to better understand the present invention, the content of the present invention is further explained below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to illustrate and explain the present invention and are not intended to limit the present invention. Unless otherwise defined, all technical and scientific terms used in the present invention have the same meaning as those generally understood by those skilled in the art.
[0025] The term "abundance" of the present invention refers to a measure of the number of target microorganisms in a biological sample. The quantification of the abundance of a target nucleic acid sequence in a biological sample may be absolute or relative. "Relative abundance" is usually based on one or more internal reference genes, i.e., from a reference strain 16SrRNA gene, such as using universal primers and expressing the abundance of the target nucleic acid sequence as a percentage of total bacterial 16SrRNA gene copies or measured by normalization of Escherichia coli 16SrRNA gene copies. "Absolute abundance" gives the exact number of target molecules by comparison with a DNA standard or by normalization of DNA concentration.
[0026] In order to enrich the detection methods of Clostridium difficile infection, the present invention has mined microbial genera related to Clostridium difficile infection from the intestinal symbiotic microbial flora, obtained markers and methods capable of detecting Clostridium difficile infection, and provided a new approach for the diagnosis of Clostridium difficile infection.
[0027] likeFigure 1 As shown, the present invention obtains intestinal flora markers that can be used as Clostridium difficile infection through the following steps: (1) Determine the inclusion criteria for patients with C. difficile infection and healthy subjects; (2) Collect stool samples from patients with Clostridium difficile infection and healthy people, extract, amplify, build libraries and perform metagenomic sequencing on the microbial genomic DNA in the stool samples to obtain raw data; (3) Use the same quality control and analysis methods to perform quality control on the original data; (4) Use the same method to analyze the relative abundance of intestinal microbial flora; (5) Screen out differentially expressed bacteria and analyze their effect size using rank sum test and linear discriminant analysis; (6) Binary logistic regression was used to test the true positive rate and true negative rate of the differential bacteria.
[0028] The present invention discovered that Clostridium laxemii Lachnoclostridium Fusobacterium Fusobacterium , Clostridium Clostridioides Related to Clostridium difficile infection, the training set data showed that these intestinal bacteria genera showed a significant increase in patients with Clostridium difficile infection and a significant decrease in healthy people through differential bacteria and linear discriminant analysis. Further validation set data showed that ROC curve analysis showed high specificity and sensitivity as detection variables. It can be seen that the above three bacterial genera can be used as detection markers for the diagnosis of patients with Clostridium difficile infection.
[0029] If no specific techniques or conditions are specified in the following examples, all of them are carried out according to the techniques or conditions described in the literature in the field or according to the product instructions; if the manufacturer of the reagents or instruments is not specified, they are all conventional products that can be obtained commercially.
[0030] Example 1 In this case, we screened and validated intestinal flora markers that can be used to detect Clostridium difficile infection. The experimental process is as follows: Figure 2 As shown, the specific operations are as follows: (1) Sample collection.
[0031] Stool samples were collected from 80 patients with Clostridium difficile infection and 160 healthy subjects: The samples of the Clostridium difficile infection group came from 80 families, and the inclusion criteria were: ① Age distribution 40-80 years old; ② Patients clinically diagnosed with Clostridium difficile infection. The exclusion criteria of the Clostridium difficile infection group were: ① Suffering from other acute or chronic infectious diseases, severe trauma, malnutrition, diabetes, malignant tumors, grade 4 heart failure, etc.; ② Suffering from other mental illnesses (such as schizophrenia) and other neurodevelopmental disorders; ③ Diagnosed with cardiovascular and cerebrovascular diseases; ④ Patients with liver dysfunction; ⑤ Patients with chronic kidney disease or abnormal renal function; ⑥ Alcoholism; ⑦ Patients deemed unsuitable for inclusion in this study by researchers.
[0032] The samples of the control group were from 160 families, and the inclusion criteria were: ① age distribution 40-75 years old; ② good health, no various diseases; ③ no antibiotics or probiotics taken in the past month. The exclusion criteria were the same as the Clostridium difficile infection group.
[0033] The above data comes from stool samples collected by Wuhan hospitals.
[0034] (2) DNA extraction, library construction and sequencing.
[0035] The microbial genomic DNA of the sample was extracted by the CTAB (cetyltrimethylammonium bromide) method. After the extraction, the DNA concentration was detected by Qubit fluorescence quantification instrument, and the integrity of the extracted genomic DNA was detected by 1% agarose gel electrophoresis. PCR amplification was then performed (primer sequences were 341F: 5'-CCTACGGGNGGCWGCAG-3' (SEQ ID NO.1); 805R: 5'-GACTACHVGGGTATCTAATCC-3' (SEQ ID NO.2)). The PCR reaction conditions were: 95℃ pre-denaturation for 3min; 95℃ 30s, 55℃ 30s, 72℃ 15s, 25 cycles starting from the second step; 72℃ extension for 5min, and storage at 4℃. The amplification primers were used to construct the library using the TruSeq@DNA PCR-Free Sample Preparation Kit, and the sequencing adapters were added. After PCR amplification, small fragments such as primer dimers were removed by magnetic bead sorting, and the library index information was recorded. The reaction conditions were 98℃ pre-denaturation for 45s; 98℃ 15s, 60℃ 30s, 72℃ 30s, 8 cycles; 72℃ extension for 10min, and storage at 4℃. After the library was qualified, different libraries were pooled and sequenced according to the effective concentration and target data volume. The sequencing platform was Illumina Miseq, and the sequencing strategy was double-end PE250.
[0036] (3) LEfSe analysis and screening of biomarkers.
[0037] The data was filtered, denoised and spliced to obtain high-quality sequencing data. The Identity standard was set to 100% for clustering and ASV feature sequences were divided. The feature sequences were annotated using the qiime2 plug-in feature-classifier classify-sklearn to generate taxonomic abundance data. 80% of the abundance data was randomly selected for analysis using LEfSe software. The default LDA Score screening value was set to 4. The results are as follows: Figure 2 As shown in Figure 2, Lachnoclostridium, Fusobacterium, and Clostridioides were screened out, which were significantly increased in the Clostridium difficile infection group. The box scatter plot of the three markers is shown in Figure 2. Figure 3 .
[0038] (4) Establishment of a predictive scoring system.
[0039] The remaining 20% abundance data were first subjected to binary logistic regression, and then to receiver operating characteristic curve (ROC) analysis to obtain the cutoff value (optimal cutoff value). The sample information table involved in steps (3) and (4) is shown in Table 1.
[0040] Table 1 Sample information table
[0041] The specificity and sensitivity calculation and ROC curve drawing were completed using IBM SPSS Statistics (v27) statistical software. The software first calculated the threshold of the actual measurement value, and then calculated the true positive cases (TP), false positive cases (FP), true negative cases (TN), and false negative cases (FN) corresponding to the threshold. Specificity (true negative rate) = TN / (TN+FP), sensitivity (true positive rate) = TP / (TP+FN), and the ROC curve can be constructed by 1-specificity and sensitivity. The integral of the ROC curve is AUC. In order to calculate the specificity and sensitivity of a certain indicator, we first calculated the Youden coefficient (Youden index = sensitivity + specificity-1). The specificity and sensitivity corresponding to the maximum value of the Youden coefficient are the specificity and sensitivity of a certain indicator.
[0042] The relative abundance values of individual microbial markers were directly analyzed by receiver operating characteristic curve test (ROC curve) to obtain the cutoff value (optimal cutoff value). The AUC of the three-bacteria combined prediction scoring method was 1.000, the optimal cutoff value was 0.4999, the sensitivity was 100%, and the specificity was 100%. The ROC curve of the prediction score is shown in Figure 2. Figure 5The AUC, optimal cutoff value, sensitivity, and specificity of the three-bacteria combined and single-bacteria prediction scoring methods are shown in Table 2.
[0043] Table 2 ROC diagnostic curve results
[0044] From the above results, it can be seen that the predictive ability of Clostridium spp. for C. difficile infection is significantly higher than that of the other two genera, but the predictive effect of the combination of the three bacteria is the highest. When the three bacteria are combined, the sensitivity is 80.6% and the specificity is 100.0%.
[0045] In summary, the present invention discovered for the first time that Clostridium (Lachnoclostridium, Fusobacterium, and Clostridioide) are associated with patients with Clostridium difficile infection, specifically showing that their abundance is significantly higher than that in healthy people. When these three genera are used as predictive factors for Clostridium difficile infection, the accuracy is high and the prediction method is non-invasive. The present invention provides a new approach for the diagnosis of patients with Clostridium difficile infection.
[0046] The above implementation cases are only for illustrating the technical solutions and features of the present invention, and their purpose is to enable people familiar with the technology to implement them better. They cannot be used to limit the protection scope of the present invention. All equivalent changes or modifications made according to the spirit of the present invention are within the protection scope of the present invention, and those not described in detail are prior art.
Claims
1. A marker of intestinal flora associated with Clostridium difficile infection, characterized in that: The intestinal flora marker is composed of Clostridium laxative Lachnoclostridium Fusobacterium Fusobacterium , Clostridium Clostridioides composition.
2. Use of the intestinal flora marker associated with Clostridium difficile infection as claimed in claim 1 in detecting Clostridium difficile infection in an individual.
3. The use according to claim 2, characterized in that: When the tested individuals were compared with healthy individuals, they had increased Clostridium laxigera Lachnoclostridium Fusobacterium Fusobacterium and Clostridium Clostridioides Horizontal ， The individual to be tested suffers from Clostridium difficile infection.
4. Use of the intestinal flora marker associated with Clostridium difficile infection as claimed in claim 1 in the preparation of a diagnostic product for Clostridium difficile infection.
5. The use according to claim 4, characterized in that: The Clostridium difficile infection diagnostic product is a detection kit, which includes reagents for detecting the abundance of the intestinal flora markers in the fecal samples of subjects.
6. The use according to claim 5, characterized in that: The reagent analyzes the abundance of the intestinal flora marker by polymerase chain reaction, sequencing, isothermal amplification, bioinformatics or a combination thereof.
7. The use according to claim 6, characterized in that: The reagent is a primer for detecting 16SrRNA of the intestinal flora marker.
8. The use according to claim 4, characterized in that: The Clostridium difficile infection diagnostic product is a Clostridium difficile infection prediction system, which uses the abundance of the intestinal flora marker in the subject's fecal sample as a detection variable.
9. Use of the intestinal flora marker associated with Clostridium difficile infection as claimed in claim 1 in screening drugs for treating Clostridium difficile infection.
10. Use of the intestinal flora marker associated with Clostridium difficile infection as claimed in claim 1 in screening health foods for alleviating Clostridium difficile infection.