CN111647673A - Application of microbial flora in acute pancreatitis - Google Patents

Abstract

The invention discloses the application of microbial flora in acute pancreatitis, and the microorganism flora is Ruminococcus_gauvreauii_group. The microbial marker of the present invention has high sensitivity and strong specificity for predicting acute pancreatitis, and can be used to warn subjects by detecting the abundance of the microbial marker, and further reduce the risk by adjusting diet or medical intervention.

Description

Application of microbial flora in acute pancreatitis

technical field

The invention belongs to the field of biotechnology, and relates to the application of microbial flora in acute pancreatitis.

Background technique

Acute pancreatitis (AP) is an inflammatory disease that can lead to local damage, systemic inflammatory response syndrome (SIRS), and organ failure. With the continuous development and progress of society, the improvement of people's living standards, high-fat diet, low physical activity, excessive work pressure, alcohol abuse and other reasons, the incidence of pancreatitis has increased, resulting in an increase in the incidence of acute pancreatitis. Acute pancreatitis accounts for 3%-10% of acute abdomen, which is a common clinical acute abdomen. The disease is very disruptive to physiology. It has the characteristics of rapid onset, rapid development, high risk and high mortality. It is relatively difficult to differentiate acute pancreas from other non-acute pancreatitis-type acute abdomens in the acute phase, which may delay or delay the diagnosis and treatment, which will threaten the life safety of patients. The specific mechanism that triggers the inflammatory response and necrotic process of the pancreas remains unclear.

The Pancreatic Surgery Society of the Chinese Medical Association revised the "Guidelines for the diagnosis and treatment of acute pancreatitis", (2014), and clarified the diagnostic definition of acute pancreatitis: Acute pancreatitis is diagnosed by meeting or meeting the following conditions: abdominal pain consistent with AP; serum amylase and/or lipase activity more than three times the upper limit of normal; imaging studies are consistent with AP imaging changes (LiPinski M, Rydzewska-Rosolowska A, Rydzewski A, et al. Fluid resuscitation in acutePancreatitis:normal saline or lactatedRinger7S solution.Wor1dJ Gastroenterol, 2015, 21(31): 9367-9372.). Traditional diagnostic methods (such as CT) take a long time, and the process is complicated, which is not conducive to timely and dynamic monitoring of disease changes. Especially in the clinical application of primary hospitals, it is subject to conditions. Limitations, CT scans have higher requirements for imaging doctors to read pictures, and it is necessary to combine the corresponding clinical symptoms to diagnose the disease. There are many scoring systems that have been used in clinical prognosis, such as the Glasgow scoring system and the Apache Comprehensive Obesity Score (APACHE). -O), Prognostic Pancreatitis (POP), Acute Physiological and Chronic Health Assessment II (APACHEII), Harmless Acute Pancreatitis Score (HAPS), Bedside Indicators of Acute Pancreatitis Severity, E-Pancreatitis (BISAP), Japanese Severity Score (JSS), etc. However, these scoring systems are complex, cumbersome, and have a high false positive rate, and are not often used by clinicians. Therefore, in clinical diagnosis and treatment, it is necessary to find a suitable and convenient prediction AP Patient biological indicators are of great significance.

The intestinal flora is called the "second fingerprint" of human beings. Under normal circumstances, the intestinal flora and the host are in a peaceful symbiosis and are in a state of balance. Once the balance is broken, the structure of the intestinal flora is disordered, and the intestinal microorganisms can Affects human health through multiple pathways (Janssen AW, Kersten S, et al. The role of the gut microbiota in metabolic health [J]. FASEB Journa1, 2015, 29(8): 3111-3123.), such as gastrointestinal diseases Such as inflammatory bowel disease, irritable bowel syndrome, colon cancer, etc. and parenteral diseases such as Alzheimer's disease, coronary heart disease, obesity, diabetes, etc. At present, the research on the characteristics of the microbiome of patients with acute pancreatitis is very limited. In this application, by studying the characteristics of the microbiome of patients with acute pancreatitis and healthy subjects, it is found that there are significant differences in the microbial flora, in order to realize the diagnosis and treatment of acute pancreatitis. Diagnosis and treatment.

SUMMARY OF THE INVENTION

In view of the deficiencies of the prior art and the actual needs, the purpose of the present invention is to provide a microbial marker for evaluating acute pancreatitis and its application. The microbial marker of the present invention has good sensitivity for predicting the risk of acute pancreatitis, only The relative content of microbial markers needs to be obtained to assist diagnosis, guide the adjustment of the microbial environment, and reduce the risk of acute pancreatitis.

For achieving the above object, the present invention adopts the following technical solutions:

In a first aspect, the present invention provides a microbial marker for acute pancreatitis, wherein the microbial marker is g_Ruminococcus_gauvreauii_group.

In a second aspect, the present invention provides a reagent for detecting the microbial marker described in the first aspect.

In a third aspect, the present invention provides a use of the microbial marker according to the first aspect or the reagent according to the second aspect, the use includes building a model for predicting the risk of acute pancreatitis, preparing and diagnosing acute pancreatitis The product.

Preferably, the product includes a chip, a kit, and a test paper.

Preferably, the input variable of the model is the abundance of the microbial marker described in the first aspect.

Preferably, the method for determining the abundance of microbial markers includes any one or more of metagenomic sequencing, 16S sequencing or quantitative qPCR detection.

In a fourth aspect, the present invention provides a product for diagnosing acute pancreatitis, the product comprising the reagent described in the second aspect.

Preferably, the reagents include primers, probes, antisense oligonucleotides, aptamers or antibodies that detect the specificity of the microbial markers described in the first aspect.

In a fifth aspect, the present invention provides the use of the microbial marker described in the first aspect in preparing a medicine or food for preventing acute pancreatitis.

Preferably, the drug or food includes an agent that promotes an increase in the abundance of the microbial marker.

Advantages and beneficial effects of the present invention:

The present invention finds for the first time that g_Ruminococcus_gauvreauii_group is related to acute pancreatitis, and the abundance of Ruminococcus_gauvreauii_group is significantly reduced in patients with acute pancreatitis, indicating that Ruminococcus_gauvreauii_group can be used as a detection target for the diagnosis and prediction of acute pancreatitis.

The invention provides a product for diagnosing acute pancreatitis, which can be diagnosed at an early stage of the disease, realize early warning, and improve the quality of life of patients.

Description of drawings

Figure 1 is a map of the abundance of Ruminococcus_gauvreauii_group in patients with acute pancreatitis.

Figure 2 is a graph of diagnostic efficacy of Ruminococcus_gauvreauii_group as a detection variable.

Detailed ways

By taking healthy people and people with acute pancreatitis as objects, the present invention finds out the correlation between bacteria and the clinical medical indexes of acute pancreatitis for the first time, and provides an early diagnosis technology of acute pancreatitis based on this. In order to evaluate whether microbial flora can be used as a predictor of acute pancreatitis, the present invention comprehensively analyzes 16S rRNA sequencing, metagenomic sequencing and quantitative polymerase chain for specific flora by collecting rectal swabs from normal people and acute pancreatitis. As a result of the reaction, it was found that microbial flora related to acute pancreatitis was found. The present invention, through 16S rRNA sequencing, found for the first time that the abundance of g_Ruminococcus_gauvreauii_group was significantly different between acute pancreatitis and normal people, indicating that g_Ruminococcus_gauvreauii_group can be used as a diagnostic tool for acute pancreatitis. Biomarkers.

In an embodiment of the present invention, the present invention diagnoses acute pancreatitis by the following steps: in a nucleic acid sample from an individual, detecting one or more nucleic acid fragments corresponding to bacterial species relevant for the diagnosis of acute pancreatitis. In a specific embodiment, nucleic acid fragments corresponding to Ruminococcus_gauvreauii_group are detected. In carrying out the methods described herein, many conventional techniques in molecular biology, protein biochemistry, cell biology, immunology, microbiology and recombinant DNA, which are well known, are used.

Definitions of some terms used in this specification are provided below. Unless otherwise defined, all technical and scientific terms used herein generally have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

The term "OTU" (Operational Taxonomic Unit) herein refers to the terminal leaf in a phylogenetic tree consisting of a particular genetic sequence and the ensemble that shares sequence identity with that sequence at the family, genus, species or strain level sequence to define. The specific genetic sequence may be a 16S sequence or a portion of a 16S sequence, or may be a functionally conserved housekeeping gene that is widespread throughout the Eubacterial kingdom. There is at least 70%, 75%, 80%, 85%, 90%, 95%, 96%, 97%, 98% or 99% sequence identity between OTUs. OTUs are often defined by comparing sequences between organisms, sequences with sequence identity less than 95% are not considered to form part of the same OTU, however as used herein, an OTU identifier may contain sequence identities ranging from 0 to 100%, 25% to 100% and 50% to 100%, preferably 70% to 100%, 75% to 100%, 77% to 100%, 80% to 100%, 81% to 100%, 82% to 100%, 83 % to 100%, 84%, to 100%, more preferably 85% to 100%, 86% to 100%, 87% to 100%, 88% to 100%, 89% to 100%, 90% to 100%, 91% to 100%, 92% to 100%, 93% to 100%, 94% to 100%, 95% to 100%, 96% to 100%, 97% to 100%, 98% to 100% and 99% to 100% sequence.

In this paper, OTU represents bacteria that have been classified or have not been classified into genus, species and/or strain names before, that is, OTU or OTU identification is equivalent to the order, family, genus, species or strain of bacteria, which is used for bioinformatics analysis. In the process, through OUT clustering, the content of bacteria represented by it was analyzed.

The "V1-V9 region" of 16S rRNA refers to the first to ninth hypervariable regions of the 16S rRNA gene, used for genotyping of bacterial samples, as is well known to those of ordinary skill. In some embodiments, at least one of the Vl, V2, V3, V4, V5, V6, V7, V8, and V9 regions is used to characterize the microbial marker. In some embodiments, V3 and V4 regions are used to characterize microbial markers.

Probes for the detection of microbial markers herein are oligonucleotides that "specifically hybridize" to microbial marker polynucleotides, having sufficiently complementary sequences to allow hybridization to target nucleotide sequences under predetermined conditions commonly used in the art Oligonucleotides (sometimes referred to as "substantially complementary"). In particular, the expression includes an oligonucleotide that hybridizes to a substantially complementary sequence contained within a single-stranded DNA or RNA molecule described herein, and substantially excludes that the oligonucleotide hybridizes to a single-stranded nucleic acid that is not a complementary sequence. The specific lengths and sequences of probes and primers depend on the complexity of the desired nucleic acid target and reaction conditions (eg, temperature and ionic strength). Generally, hybridization conditions are stringent hybridization conditions known in the art. "Stringent" refers to the conditions under which a nucleotide sequence is capable of binding a related or nonspecific sequence. For example, high temperature and low salt increase stringency, allowing dissociation of nonspecific binding or low melting temperature binding. In some embodiments, the oligonucleotide complementary to the microbial marker polynucleotide is at least 95%, 96%, 97%, 98%, 99%, or 100% complementary to the microbial marker polynucleotide.

As an alternative embodiment, a method for diagnosing acute pancreatitis in a subject comprises: analyzing nucleic acid of a test sample of the subject; detecting the level of one or more microorganisms and/or OTUs in the nucleic acid of the test sample; The subject is diagnosed as at risk of developing acute pancreatitis when the level of one or more microorganisms and/or OTUs in the sample is lower than that of the control sample; preferably, the microbial marker is g_Ruminococcus_gauvreauii_group.

In another embodiment, a method for diagnosing acute pancreatitis in a subject comprises: obtaining a sample from the subject; processing the sample from the subject to obtain 16S rRNA gene sequence data; detecting the level of one or more microorganisms and/or OTUs in the sample , including analyzing 16S rRNA gene sequence data with bioinformatics software; and diagnosing that the subject is at risk of developing acute pancreatitis when the level of one or more microorganisms and/or OTUs in the sample is lower than that of the control sample; preferably, The microbial marker is g_Ruminococcus_gauvreauii_group.

As used herein, "significantly different" refers to when the level of one or more microorganisms or OTUs in a test sample is changed by a factor of at least about 1.2 in terms of log ₂ fold difference compared to a control sample. The term "change" includes an increase or decrease in the aqueous microbial or OTU of a test sample compared to a control sample. In some embodiments, the change in the level of one or more microorganisms or one or more OTUs between the test sample and the control sample can be about 1.2-fold, 1.3-fold, 1.4-fold, relative to the control sample in terms of log ₂ -fold difference 1.5 times, 1.6 times, 1.7 times, 1.8 times, 1.9 times, 2 times, 2.1 times, 2.2 times, 2.3 times, 2.4 times, 2.5 times, 2.6 times, 2.7 times, 2.8 times, 2.9 times, 3 times, 3.1 times , 3.2 times, 3.3 times, 3.4 times, 3.5 times, 3.6 times, 3.7 times, 3.8 times, 3.9 times, 4 times, 4.1 times, 4.2 times, 4.3 times, 4.4 times, 4.5 times, 4.6 times, 4.7 times, 4.8 times times, 4.9 times, or 5 times and above.

In some embodiments, when the level of one or more microorganisms or one or more OTUs in the test sample is about 1.2-fold, 1.3-fold, 1.4-fold, 1.5-fold, 1.6-fold higher than that of the control sample in terms of log ₂ -fold difference, 1.7 times, 1.8 times, 1.9 times, 2 times, 2.1 times, 2.2 times, 2.3 times, 2.4 times, 2.5 times, 2.6 times, 2.7 times, 2.8 times, 2.9 times, 3 times, 3.1 times, 3.2 times, 3.3 times , 3.4 times, 3.5 times, 3.6 times, 3.7 times, 3.8 times, 3.9 times, 4 times, 4.1 times, 4.2 times, 4.3 times, 4.4 times, 4.5 times, 4.6 times, 4.7 times, 4.8 times, 4.9 times, or 5 times times and above.

In some embodiments, when the level of one or more microorganisms or one or more OTUs in a test sample is about _1.2 -fold, 1.3-fold, 1.4-fold, 1.5-fold, 1.6-fold, 1.7 times, 1.8 times, 1.9 times, 2 times, 2.1 times, 2.2 times, 2.3 times, 2.4 times, 2.5 times, 2.6 times, 2.7 times, 2.8 times, 2.9 times, 3 times, 3.1 times, 3.2 times, 3.3 times , 3.4 times, 3.5 times, 3.6 times, 3.7 times, 3.8 times, 3.9 times, 4 times, 4.1 times, 4.2 times, 4.3 times, 4.4 times, 4.5 times, 4.6 times, 4.7 times, 4.8 times, 4.9 times, or 5 times times and above.

The term "sample" or "test sample" as used herein refers to any liquid or solid material containing nucleic acid. In suitable embodiments, the test sample is obtained from a biological source (ie, a "biological sample"), such as cells in culture, or a tissue sample from an animal and most preferably from a human. In an exemplary embodiment, the sample is a rectal swab.

The methods and products of the present invention can be used to detect nucleic acids associated with various bacteria using biological samples obtained from individuals. The nucleic acid (DNA or RNA) can be isolated from the sample according to any method known to those skilled in the art. The biological sample can be obtained by standard procedures and can be used immediately, or it can be stored for subsequent use under conditions suitable for the type of biological sample.

Embodiment 1 Detection of microbial flora related to acute pancreatitis

1. Collection of samples

Rectal cotton swab samples were collected from 20 healthy individuals and 60 patients with acute pancreatitis. The patient data statistics are shown in Table 1.

Inclusion criteria for patients: meeting the new 2012 Atlanta classification of acute pancreatitis.

Exclusion criteria for patients: absence of immunodeficiency, allergy, asthma, colon cancer, diabetes, HIV, inflammatory bowel disease, irritable bowel syndrome, gastroenteritis, anesthesia enterocolitis, and arthritis.

Inclusion criteria for healthy controls: no metabolic, cardiovascular, and intestinal diseases; no pregnancy, no known allergens; no medication that affects bowel function; no diet for weight loss or other specific purposes.

Exclusion criteria for patients and healthy controls: taking antibiotics, probiotics, Chinese herbal medicines and other substances that may affect the structure of intestinal flora.

Table 1 Patient Information

2. 16S rRNA sequencing

2.1 DNA extraction

Bacterial DNA was extracted from the sample using a DNA extraction kit, and the operation steps were carried out according to the instructions.

2.2 DNA sample purity and concentration determination

Genomic DNA was detected by 1% agarose gel electrophoresis.

2.3 PCR amplification and product purification

According to the designated sequencing region, synthesize specific primers with barcodes, or synthesize fusion primers with misplaced bases.

In order to ensure the accuracy and reliability of subsequent data analysis, two conditions need to be met: 1) Use low cycle number amplification as much as possible; 2) Ensure that the cycle number of each sample is the same. Randomly select representative samples for pre-experimentation to ensure that the majority of samples can amplify the appropriate concentration of product in the minimum number of cycles.

PCR uses TransGen AP221-02: TransStart Fastpfu DNA Polymerase;

9700型；PCR machine: ABI

Type 9700;

All samples were carried out according to the formal experimental conditions, each sample was repeated 3 times, the PCR products of the same sample were mixed and detected by 2% agarose gel electrophoresis, and the PCR products were recovered by cutting the gel using the AxyPrep DNA Gel Recovery Kit (AXYGEN Company). Tris_HCl elution; 2% agarose electrophoresis detection.

2.4 Fluorescence quantification

The PCR products were detected and quantified by QuantiFluor ^™ -ST blue fluorescence quantitative system (Promega Company), and then mixed in corresponding proportions according to the requirement of sequencing quantity of each sample.

2.5 Miseq library construction

1) Add the official Illumina adapter sequence to the outer end of the target region by PCR;

2) Use the gel recovery kit to cut the gel to recover the PCR product;

3) Tris-HCl buffer elution, 2% agarose electrophoresis detection;

4) Sodium hydroxide denaturation, resulting in single-stranded DNA fragments.

Reagents: TruSeqTM DNA Sample Prep Kit

2.6 Miseq sequencing

1) One end of the DNA fragment is complementary to the primer base and fixed on the chip;

2) using the DNA fragment as a template, the base sequences fixed on the chip as primers to carry out PCR synthesis, and synthesizing the target DNA fragment to be tested on the chip;

3) After denaturation and annealing, the other end of the DNA fragment on the chip is randomly complementary to another nearby primer, and is also fixed to form a "bridge";

4) PCR amplification to generate DNA clusters;

5) The DNA amplicon is linearized into a single strand;

6) Add the modified DNA polymerase and dNTPs with 4 kinds of fluorescent labels, and synthesize only one base per cycle;

7) Scan the surface of the reaction plate with a laser to read the nucleotide species polymerized in the first round of reaction of each template sequence;

8) Chemically cleave the "fluorescent group" and "termination group" to restore the viscosity of the 3' end, and continue to polymerize the second nucleotide;

9) Count the fluorescent signal results collected in each round to know the sequence of the template DNA fragment.

3. Data analysis

3.1 Data preprocessing

MiSeq sequencing obtains paired-end sequence data. First, according to the overlap relationship between PE reads, the paired reads are merged into one sequence, and the quality of the reads and the effect of the merge are filtered for quality control. The barcode at the end and the primer sequence distinguish the sample to obtain an effective sequence, and correct the sequence direction, which is the optimization data.

Data decluttering methods and parameters:

1) Filter the bases with a tail quality value below 20 of the reads, and set a 50bp window. If the average quality value in the window is lower than 20, truncate the back-end bases from the window, filter the reads below 50bp after quality control, and remove the content containing N base reads;

2) According to the overlap relationship between PE reads, the paired reads are spliced (merge) into a sequence, and the minimum overlap length is 10bp;

3) The maximum mismatch ratio allowed in the overlap region of the spliced sequence is 0.2, and the screening does not conform to the sequence;

4) Distinguish the samples according to the barcodes and primers at the beginning and end of the sequence, and adjust the sequence direction. The number of mismatches allowed by barcode is 0, and the maximum number of primer mismatches is 2;

Software used: FLASH, Trimmomatic.

3.2 Species annotation and assessment

Use Usearch for OTU cluster analysis. OTU (Operational Taxonomic Units) is a unified set of artificially set a taxonomic unit (strain, genus, species, grouping, etc.) in order to facilitate analysis in phylogenetic or population genetics research. logo. To understand the number of species, genera and other information in the sequencing result of a sample, it is necessary to cluster the sequences. Through the clustering operation, the sequences are divided into many groups according to their similarity with each other, and a group is an OTU. All sequences can be divided into OTUs according to different similarity levels, and bioinformatics statistical analysis is usually performed on OTUs at a similarity level of 97%.

Software platform: Usearch (vsesion 7.0 http://drive5.com/uparse/)

The analysis steps are as follows:

Extract non-repetitive sequences from the optimized sequence, which is convenient to reduce the redundant calculation amount in the intermediate process of analysis;

Remove single sequences without repeats;

Perform OTU clustering on non-repetitive sequences (without single sequences) according to 97% similarity, and remove chimeras during the clustering process to obtain representative sequences of OTUs.

The RDP classifier Bayesian algorithm is used to perform taxonomic analysis on the representative sequences of OTUs with 97% similarity level, and at each taxonomic level: domain (domain), kingdom (boundary), phylum (door), class (class), order (order), family (family), genus (genus), species (species) to count the community composition of each sample.

3.3 Species Difference Analysis

Using bioinformatics analysis methods to analyze species differences analysis According to the obtained community abundance data, the abundance differences exhibited by different groups (or samples) of microbial communities were detected. The contents of species difference analysis include: significant difference test between groups, Lefse multi-level species difference discriminant analysis. This project uses the significance test of differences between groups to screen for different species.

Based on the obtained community abundance data, strict statistical methods can be used to detect species with differences in abundance in the microbial communities of different groups (samples), and perform hypothesis testing to evaluate the observed differences. salience. Different classification levels such as domain, kingdom, phylum, class, order, family, genus, species, and OTU can be selected for analysis.

1) Wilcox rank-sum test (Wilcoxon rank-sum test), also known as Mann-Whitney U test (Mann-Whitney U test), is a method of non-parametric test of two independent samples. The null hypothesis is that there is no significant difference in the distributions of the two populations from which the two groups of independent samples come from. The study of the average rank of the two groups of samples can be used to determine whether there is a difference in the distribution of the two populations. This analysis can make significant differences in the species of the two groups of samples. analysis, and the P values were corrected in a variety of ways.

2) Multiple testing correction, that is, the multiple testing correction method for the P value is "fdr".

3) Two-tailed test, used to specify the type of confidence interval to be sought, select two-tailed test (for confidence interval).

4) CI calculation method, that is, the method of calculating the confidence interval, the method is DP: Welch's confidenceinverted. Confidence selection: 0.95.

The effect size was calculated by the DP method, namely mean1–mean2; the confidence interval was calculated by the Welch T test, and the screening criterion was P<0.05.

Software: stats package for R and scipy package for python.

4. Results

The results showed that compared with the control group, the abundance of Ruminococcus_gauvreauii_group was significantly down-regulated in patients with acute pancreatitis, and the difference was statistically significant (P<0.0001), suggesting that Ruminococcus_gauvreauii_group could be used as a biomarker for the diagnosis of acute pancreatitis.

Example 2 Diagnostic efficacy of Ruminococcus_gauvreauii_group

According to the relative content of Ruminococcus_gauvreauii_group, use SPSS to draw receiver operating characteristic curve (ROC), calculate the binomial exact confidence space, and analyze the sensitivity and specificity of Ruminococcus_gauvreauii_group for the diagnosis of acute pancreatitis.

The ROC curve and characteristic parameters are shown in Figure 2 and Tables 2-3 respectively, the area under the curve is 0.904, the threshold of the optimal critical point is 109.5, the sensitivity of this point is 0.833, and the specificity is 0.85, which has a high sensitivity It shows that the Ruminococcus_gauvreauii_group has high sensitivity, specificity and accuracy in the diagnosis of acute pancreatitis. Based on the findings of this study, acute pancreatitis can be prevented or treated by adjusting the abundance of Ruminococcus_gauvreauii_group.

Table 2 Area under the curve test result variable: Ruminococcus_gauvreauii_group

a. Under the nonparametric assumptions

b. Null hypothesis: real area = 0.5

Table 3 Coordinate test result variable of curve: Ruminococcus_gauvreauii_group

Note: a. The minimum limit value is the minimum observed test value minus 1, and the maximum limit value is the maximum observed test value plus 1. All other thresholds are the average of two adjacent observed test values.

The description of the above embodiment is only for understanding the method and the core idea of the present invention. It should be pointed out that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and modifications can also be made to the present invention, and these improvements and modifications will also fall within the protection scope of the claims of the present invention.

Claims (10)

1. A microbial marker of acute pancreatitis, wherein the microbial marker is Ruminococcus _ gauvreauii _ group.

2. A reagent for detecting the microbial marker of claim 1.

3. Use of a microbial marker according to claim 1 or an agent according to claim 2 for constructing a model for predicting the risk of acute pancreatitis, for preparing a product for diagnosing acute pancreatitis.

4. Use according to claim 3, wherein the product comprises a chip, a kit, a strip.

5. Use according to claim 3, wherein the input variable of the model is the abundance of the microbial marker of claim 1.

6. The use according to claim 5, wherein the determination method of the abundance of the microbial marker comprises any one or more of metagenomic sequencing, 16S sequencing or qPCR quantitative detection.

7. A product for diagnosing acute pancreatitis, comprising the agent of claim 2.

8. The product of claim 7, wherein the reagents comprise primers, probes, antisense oligonucleotides, aptamers, or antibodies that detect the specificity of the microbial markers of claim 1.

9. Use of the microbial marker of claim 1 in the manufacture of a medicament or food product for the prevention of acute pancreatitis.

10. The use according to claim 9, wherein the medicament or food comprises an agent that promotes an increase in the abundance of the microbial marker of claim 1.

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