KR20220026457A - Composition for predicting or diagnosing irritable bowel syndrome comprising detection agent for microorganism - Google Patents

Abstract

The present disclosure relates to a composition, kit, and information providing method capable of predicting or diagnosing irritable bowel syndrome, and the composition according to one aspect of the present invention can predict or diagnose irritable bowel syndrome by detecting intestinal microorganisms.

Description

Composition for predicting or diagnosing irritable bowel syndrome comprising a microorganism detection agent

The present specification discloses a microorganism detection agent for predicting or diagnosing irritable bowel syndrome, a composition and kit for predicting or diagnosing irritable bowel syndrome including the same.

Irritable bowel syndrome (IBS) is a functional bowel disease characterized by recurrent abdominal pain associated with changes in bowel habits or defecation [Mearin F, Lacy BE, Chang L, et al. Bowel disorders. Gastroenterology 2016:150; 1393-1407]. Several pathophysiological mechanisms have been proposed as inducers of IBS, including gut-brain dysregulation, alterations in bile acid metabolism, alterations in intestinal permeability, immune dysfunction and alterations in the gut microbiota [Camilleri M, Ford AC. Irritable bowel syndrome: pathophysiology and current therapeutic approaches. Handb Exp Pharmacol 2017; 239:75-113., Bhattarai Y, Muniz Pedrogo DA, Kashyap PC. Irritable bowel syndrome: a gut microbiota-related disorder Am J Physiol Gastrointest Liver Physiol 2017; 312:G52-G62.]

IBS symptoms are associated with the composition of the fecal microbiota [Saulnier DM, Riehle K, Mistretta TA, et al. Gastrointestinal microbiome signatures of pediatric patients with irritable bowel syndrome. Gastroenterology 2011; 141:1782-1791., Jeffery IB, O'Toole PW, Ohman L, et al. An irritable bowel syndrome subtype defined by species-specific alterations in faecal microbiota. Gut 2012; 61:997-1006., Tap J, Derrien M, Tornblom H, et al. Identification of an intestinal microbiota signature associated with severity of irritable bowel syndrome. Gastroenterology 2017;152:111-123., Rajiliζ-Stojanovic M, Biagi E, Heilig HG, et al. Global and deep molecular analysis of microbiota signatures in fecal samples from patients with irritable bowel syndrome. Gastroenterology 2011; 141:1792-1801.] Several groups of Firmicutes and Proteobacteria have been reported to correlate with IBS symptom scores in patients [Rajilic-Stojanovic M, Biagi E, Heilig HG, et al. Global and deep molecular analysis of microbiota signatures in fecal samples from patients with irritable bowel syndrome. Gastroenterology 2011; 141:1792-1801.]. In addition, the severity of IBS symptoms may be related to the abundance of microorganisms, the presence of methanogens, and the abundance of Clostridiales or Prevotella species [Tap J, Derrien M, Tornblom H, et al. Identification of an intestinal microbiota signature associated with severity of irritable bowel syndrome. Gastroenterology 2017; 152:111-123.]. However, conventional studies have limitations in functional analysis.

The gut microbiota is associated with bile acid modifications associated with the development of IBS. The gut microbiota influences the metabolism of bile acids and increases excretion [Sayin SI, Wahlstrom A, Felin J, et al. Gut microbiota regulates bile acid metabolism by reducing the levels of tauro-beta-muricholic acid, a naturally occurring FXR antagonist. Cell Metab 2013; 17: 225-235.]. Modification of the bile acid profile has been proposed as one of the symptom-generating mechanisms in IBS patients and is therefore a potential therapeutic target for IBS. Therefore, it is necessary to determine whether changes in the composition of the microbiota in IBS are related to the bile acid profile. In relation to this problem, previous studies have suggested that alteration of bile acid profile in IBS may be secondary to dysbiosis [Dior M, Delagreverie H, Duboc H, et al. Interplay between bile acid metabolism and microbiota in irritable bowel syndrome. Neurogastroenterol Motil 2016; 28:1330-1340.].

In view of this background, the present inventors hypothesized that changes in the intestinal microflora and consequent changes in bacterial function may contribute to the development and progression of IBS, characterizing the changes in the intestinal microflora in IBS, and consequently changing the bacterial function. studied.

In one aspect, the present invention is to provide a composition for predicting or diagnosing irritable bowel syndrome.

In another aspect, the present invention is to provide an information providing method for predicting or diagnosing irritable bowel syndrome.

In one aspect, the present invention includes a microorganism detection agent, wherein the microorganism is Acidaminococcaceae , Sutterellaceae , Desulfovibrionaceae , Enterococcaceae , Leuconostocaceae , Clostridiaceae , Peptostreptococcaceae and Lachnospiraceae for predicting or diagnosing one or more compositions selected from the group consisting of irritable bowel syndrome provides

In another aspect, the present invention provides a kit for predicting or diagnosing irritable bowel syndrome comprising the composition.

In another aspect, the present invention provides a method comprising the steps of: (a) extracting DNA from a stool sample of a subject; (b) analyzing the abundance of intestinal microorganisms from the DNA extracted in step (a); And (c) provides an information providing method for predicting or diagnosing irritable bowel syndrome, comprising the step of comparing the abundance of intestinal microorganisms analyzed in step (b) with a stool sample derived from a normal person.

In one aspect, the composition, kit or method according to an embodiment of the present invention is excellent in the effect of predicting or diagnosing irritable bowel syndrome by detecting intestinal microorganisms.

In one aspect, the composition, kit or method according to an embodiment of the present invention can be used to delay the onset or prevent the onset of the onset through special and appropriate management as a patient with a high risk of developing irritable bowel syndrome for any patient. .

In one aspect, the composition, kit or method according to an embodiment of the present invention can be used clinically to determine treatment by diagnosing irritable bowel syndrome early and selecting the most appropriate treatment method.

1 is a clustering of samples according to an irritable bowel syndrome (IBS) situation of an aspect of the present invention, and shows a principal coordinates analysis (PCoA) of 19 samples. In FIG. 1 , CON denotes a control group and IBS denotes irritable bowel syndrome.
Figure 2 shows the diversity index of the intestinal microflora according to an aspect of the present invention. In FIG. 2, A represents the number of observed operational taxonomic units (OUT), B represents the Chao1 index, C represents the Shannon index, and D represents the phylogenetic diversity index.
3 shows the difference in the composition of microbiota between irritable bowel syndrome (IBS) samples and normal control samples. 3A shows the linear discriminant analysis (LDA) effect size (LEfSe) of the intestinal microflora at the family level. 3, B to I show the abundance ratios of different families between IBS and normal controls according to LEfSe, where B is Acidaminococcaceae , C is Sutterellaceae , D is Desulfovibrionaceae , E is En nterococcaceae , F is Leuconostocaceae , G denotes Clostridiaceae , H denotes Peptostreptococcaceae , and I denotes Lachnospiraceae . Here, the p-value was evaluated by Wilcoxon rank sum test.

Hereinafter, the present invention will be described in detail.

In one aspect, the present invention includes a microorganism detection agent, wherein the microorganism is Acidaminococcaceae , Sutterellaceae , Desulfovibrionaceae , Enterococcaceae , Leuconostocaceae , Clostridiaceae , Peptostreptococcaceae and Lachnospiraceae for predicting or diagnosing one or more compositions selected from the group consisting of irritable bowel syndrome to provide. In addition, in one aspect of the present invention, "Irritable Bowel Syndrome Prediction" refers to whether there is a possibility of irritable bowel syndrome for the subject, whether the possibility of irritable bowel syndrome is relatively high, and what is the causative factor of irritable bowel syndrome. , or may mean predicting or diagnosing whether irritable bowel syndrome has already occurred. Also, in one aspect of the present invention, "diagnosing irritable bowel syndrome" means confirming the presence or characteristics of a pathological condition for a subject, and for the purpose of one aspect of the present invention, the diagnosis is whether irritable bowel syndrome occurs It may mean to check The composition, kit or method according to one aspect of the present invention can be used to delay the onset or prevent the onset of the onset through special and appropriate management as a patient with a high risk of developing irritable bowel syndrome for any specific patient. In addition, the composition, kit or method according to one aspect of the present invention can be used clinically to determine treatment by diagnosing irritable bowel syndrome early and selecting the most appropriate treatment method.

In one embodiment, the microorganism detection agent is Acidaminococcaceae , Sutterellaceae , Desulfovibrionaceae , Enterococcaceae , Leuconostocaceae , Clostridiaceae , Peptostreptococcaceae , and Lachnospiraceae for the prediction or diagnosis of irritable bowel syndrome in the sample To detect the presence of one or more selected from the group consisting of It may contain materials that can be used. For example, the microorganism detection agent may include one or more selected from the group consisting of antisense oligonucleotides, primer pairs, probes, antibodies, peptides, and polynucleotides that specifically bind to 16S rRNA of the microorganism. That is, the detection of a nucleic acid may be performed by an amplification reaction using one or more oligonucleotide primers that hybridize to a nucleic acid molecule encoding a gene or a complement of the nucleic acid molecule. For example, the detection of a nucleic acid using a primer may be performed by amplifying a gene sequence using an amplification method such as PCR, and then confirming whether the gene is amplified by a method known in the art.

As used herein, the term "primer" refers to a polynucleotide having a base of a sequence capable of complementary binding to the end of a specific region of a gene used to amplify a specific region corresponding to a target site of a gene using PCR, or means that variant. The primer is not required to be completely complementary to the end of a specific region, and may be used as long as it is complementary enough to hybridize to the end to form a double-stranded structure.

As used herein, "probe" means a polynucleotide having a base of a sequence capable of complementary binding to a target site of a gene, a variant thereof, or a polynucleotide and a labeling material bound thereto.

As used herein, "hybridization" means that two single-stranded nucleic acids form a duplex structure by pairing complementary nucleotide sequences. Hybridization can occur not only when the complementarity between single-stranded nucleic acid sequences is perfect, but also when some mismatched bases are present.

In one embodiment, the antibody may be one or more selected from the group consisting of polyclonal antibodies, monoclonal antibodies, recombinant antibodies, and combinations thereof. Specifically, the antibody is a polyclonal antibody, a monoclonal antibody, a recombinant antibody and a complete form having two full-length light chains and two full-length heavy chains, as well as functional fragments of the antibody molecule, e.g., Fab, F It may include all of (ab'), F(ab')2 and Fv. Antibody production can be easily prepared using techniques well known in the art to which the present invention pertains, and commercially available antibodies can be used.

In one embodiment, the composition according to one aspect of the present invention is not only an agent for measuring the presence of the microorganism, but also a label that enables quantitative or qualitative measurement of the formation of an antigen-antibody complex, used for immunological analysis It may further include conventional tools, reagents, and the like.

In one embodiment, the label capable of qualitatively or quantitatively measuring the formation of the antigen-antibody complex includes enzymes, fluorescent substances, ligands, luminescent substances, microparticles, redox molecules, and radioactive isotopes. , but not necessarily limited thereto. Enzymes available as detection labels include β-glucuronidase, β-glucosidase, β-galactosidase, urease, peroxidase, alkaline phosphatase, acetylcholinesterase, glucose oxidase, hexokinase and GDPase, RNase, glucose oxidase and luciferase, phosphofructokinase, phosphoenolpyruvate carboxylase, aspartate aminotransferase, phosphoenolpyruvate decarboxylase, β-latamase, and the like. doesn't happen Fluorescent materials include, but are not limited to, fluorescein, isothiocyanate, rhodamine, phycoerythrine, phycocyanin, allophycocyanin, o-phthalaldehyde, fluorescamine, and the like. Ligands include, but are not limited to, biotin derivatives. The luminescent material includes, but is not limited to, acridinium ester, luciferin, luciferase, and the like. Microparticles include, but are not limited to, colloidal gold, colored latex, and the like. Redox molecules include ferrocene, ruthenium complex, viologen, quinone, Ti ion, Cs ion, diimide, 1,4-benzoquinone, hydroquinone, K ₄ W(CN) ⁸ , [Os(bpy) ₃ ] ²⁺ , [RU(bpy) ₃ ] ²⁺ , [MO(CN) ₈ ] ^4- , and the like, but are not limited thereto. Radioisotopes include, but are not limited to, ³ H, ¹⁴ C, ³² P, ³⁵ S, ³⁶ Cl, ⁵¹ Cr, ⁵⁷ Co, ⁵⁸ Co, ⁵⁹ Fe, ⁹⁰ Y, ¹²⁵ I, ¹³ 1I, ¹⁸⁶ Re, and the like.

In one embodiment, examples of the tool or reagent include, but are not limited to, suitable carriers, solubilizers, detergents, buffers, stabilizers, and the like. When the labeling material is an enzyme, it may include a substrate capable of measuring enzyme activity and a reaction terminator. The carrier includes a soluble carrier and an insoluble carrier, and an example of the soluble carrier is a physiologically acceptable buffer known in the art, for example, PBS, and an example of the insoluble carrier is polystyrene, polyethylene, polypropylene, polyester, poly acrylonitrile, fluororesin, crosslinked dextran, polysaccharide, other paper, glass, metal, agarose, and combinations thereof.

In one embodiment, the composition according to one aspect of the present invention may be applied to a sample of a subject, and the sample is, for example, saliva, biopsy, blood, skin tissue, liquid culture It may be one or more selected from the group consisting of water, feces, and urine, but is not limited thereto, and may be prepared by treatment by a method commonly used in the art.

In another aspect, the present invention provides a kit for predicting or diagnosing irritable bowel syndrome comprising a composition for predicting or diagnosing irritable bowel syndrome comprising the microorganism detection agent. Descriptions of the microorganism, detection agent, subject, sample, and the like are the same as described above.

In one embodiment, the kit has an increased abundance of Acidaminococcaceae , Sutterellaceae and Desulfovibrionaceae , and Enterococcaceae , Leuconostocaceae , Clostidiaceae , Peptostreptococcaceae , and Lachnospiraceae when the abundance of Peptostreptococcaceae and Lachnospiraceae is reduced when compared to a sample derived from a normal person. may be doing For example, the kit may further include instructions, in which the abundance of Acidaminococcaceae , Sutterellaceae and Desulfovibrionaceae is increased, and the abundance of Enterococcaceae , Leuconostocaceae , Clostridiaceae , Peptostreptococcaceae and Lachnospiraceae is decreased compared to a sample derived from a normal human being. Diagnosis of irritable bowel syndrome may be described if there is.

In another aspect, the present invention provides a method comprising: (a) extracting DNA from a sample of a subject; (b) analyzing the abundance of intestinal microorganisms from the DNA extracted in step (a); And (c) provides an information providing method for predicting or diagnosing irritable bowel syndrome, comprising the step of comparing the abundance of intestinal microorganisms analyzed in step (b) with a sample derived from a normal person.

In one embodiment, the microorganism may include at least one selected from the group consisting of Acidaminococcaceae, Sutterellaceae , Desulfovibrionaceae , Enterococcaceae , Leuconostocaceae , Clostridiaceae , Peptostreptococcaceae and Lachnospiraceae .

In one embodiment, the step (b) may be a step of analyzing the abundance of intestinal microorganisms using the microorganism detection agent according to an aspect of the present invention, for example, for 16S rRNA of the microorganism The PCR primer pair may be used, but is not limited thereto.

In one embodiment, in step (c), the abundance of Acidaminococcaceae, Sutterellaceae and Desulfovibrionaceae is increased by comparing the abundance of intestinal microorganisms analyzed in step (b) with a sample derived from a normal person , Enterococcaceae , Leuconostocaceae , Clostidiaceae , when the abundance of Peptostreptococcaceae and Lachnospiraceae is reduced, irritable bowel syndrome can be diagnosed.

Hereinafter, the configuration and effect of the present invention will be described in more detail by way of examples. However, the following examples are provided for illustrative purposes only to aid understanding of the present invention, and the scope and scope of the present invention are not limited thereto.

[Example 1] Subject selection

From September 2013 to September 2017, patients who visited the Department of Gastroenterology at Seoul National University Bundang Hospital were enrolled as subjects in the study according to an embodiment of the present invention. All subjects were subjected to colonoscopy and questionnaires about irritable bowel syndrome (IBS) symptoms, and they were classified into an irritable bowel syndrome group and a control group according to Rome III criteria. The control group was defined as those without gastrointestinal symptoms and no colonoscopy lesions. Among those classified as irritable bowel syndrome, patients with post-infectious bowel syndrome (IBS) and those who took antibiotics or probiotics within 3 months were excluded from the study. Patients with a medical history were also excluded from the subject. The detailed contents of the questionnaire on the symptoms of irritable bowel syndrome are as follows.

Irritable Bowel Syndrome Symptom Assessment Questionnaire

The Irritable Bowel Syndrome Symptom Assessment Questionnaire was based on Rome III criteria to evaluate the frequency and severity of symptoms experienced during the past 3 months prior to the study. Irritable Bowel Syndrome was judged as irritable bowel syndrome if there was abdominal pain or discomfort recurring for at least 3 days per month with at least two symptoms: symptom improvement after defecation, onset associated with change in stool frequency, and onset associated with change in stool pattern during the past 3 months. .

[Example 2] Microbiota analysis and diagnosis of irritable bowel syndrome in subjects

The microbiota of the subjects of Example 1 was analyzed for predicting or diagnosing irritable bowel syndrome.

Microbiota analysis

Subjects were allowed to collect fecal samples (≥5 g per subject) at home the day before their visit to the hospital and immediately frozen at -20°C, then brought to the laboratory and stored frozen at -80°C until analysis. Total DNA was extracted from the stool samples using the QIAamp® DNA Feces Mini Kit (Qiagen, Venlo, Netherlands) according to the manufacturer's instructions. The V3-V4 region of the 16S rRNA gene was amplified by PCR using primer 341F of SEQ ID NO: 1 (5'-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG-3') and primer 805R of SEQ ID NO: 2 (5'-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVGGGTATCTAATCC-3'). The amplified PCR product was confirmed by electrophoresis and purified using a QIAquick PCR purification kit (Qiagen). Purified PCR products were tagged with llumina indices and adapters from the Nextera® XT index kit (Illumina, San Diego, CA, USA). Short DNA fragments were removed using FavorPrep™ DNA purification kit (Favorgen, Ping-Tung, Taiwan). The PCR amplification products were quantified using the Quant-iTTM PicoGreen™ dsDNA Assay kit (Thermo Fisher Scientific, Waltham, MA, USA). After collecting 300 ng of DNA per sample, the PCR product was purified with Favor-Prep™ DNA gel extraction kit (Favorgen). In the same manner, DNA was extracted from the control sample and PCR was performed.

Quality evaluation for DNA integrity and product size confirmation was performed on a Bioanalyzer 2100 instrument (Agilent, Santa Clara, CA, USA) using a DNA 7500 chip of ChunLab, Inc. (Seoul, Korea). Metagenomic sequencing was performed using ChunLab, Inc.'s Illumina MiSeq platform.

Raw reads started with quality checks using a Trimmomatic 0.32 and progressed to filtering of low quality (<Q25) reads [Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 2014;30:2114-2120.]. Paired-end sequence data were merged using ANDAseq [Masella AP, Bartram AK, Truszkowski JM, Brown DG, Neufeld JD. PANDAseq: paired-end assembler for illumina sequences. BMC Bioinformatics 2012;13:31.]. Primer sequences were trimmed with ChunLab, Inc.'s in-house program at a similarity cutoff of 0.8. Non-specific amplicons not encoding 16S rRNA were identified using the HMMER program hmmsearch with 16S rRNA profile [Eddy SR. Accelerated profile HMM searches. PLoS Comput Biol 2011;7:e1002195]. Sequences were denoised using DUDE-Seq [Lee B, Moon T, Yoon S, Weissman T. DUDE-Seq: fast, flexible, and robust denoising for targeted amplicon sequencing. PLoS One 2017;12:e0181463.], non-redundant reads were extracted via UCLUST clustering [Edgar RC. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 2010;26:2460-2461]. The EzBioCloud database was utilized for classification assignment using USEARCH (8.1.1861_i86linux32) [Edgar RC. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 2010;26:2460-2461] followed by more accurate sequence pair alignments [Myers EW, Miller W. Optimal alignments in linear space. ComputAppl Biosci 1988;4:11-17]. UCHIME [Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 2011;27:2194-2200] and EzBioCloud's non-chimeric 16s rRNA database were used to detect chimeras for reads containing the highest hit similarity of less than 97%. CDHIT [Fu L, Niu B, Zhu Z, Wu S, Li W. CD-HIT: accelerated for clustering the next-generation sequencing data. Bioinformatics 2012;28:3150-3152] and UCLUST were used to cluster the sequence data.

To visualize sample differences, principal coordinate analysis was performed with unweighted UniFrac [Lozupone C, Knight R. UniFrac: a new phylogenetic method for comparing microbial communities. Appl Environ Microbiol 2005; 71:8228-8235]. Principal coordinate analysis plots were generated using R's ade4 package and the s.class function. Microbial diversity (observed OUT number, Chao1, Shannon index, and phylogenetic diversity) was investigated using BIOiPLUG (Chunlab, Inc.).

Phylogenetic investigation of communities through reconstruction of unobserved states

To predict the functional capacity of microbial communities, phylogenetic investigation of communities by reconstruction of unobserved states, PICRUSt) [Langille MG, Zaneveld J, Caporaso JG, et al. al. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat Biotechnol 2013;31:814-821]. This analysis allowed us to infer alterations in the functional markers of the microbiota based on the Kyoto Encyclopedia of Genes and Genomes database.

Linear Discriminant Analysis Effect Size Analysis

A linear discriminant analysis effect size (LEfSe) analysis (http://huttenhower.sph.harvard.edu/galaxy/) was performed to confirm a taxonomic composition that was significantly different between the control group and the IBS group [Segata N, Izard J, Waldron L, et al. Metagenomic biomarker discovery and explanation. Genome Biol 2011;12:R60]. The conditions of the LEfSe analysis were as follows: (1) a value of less than 0.05 for the factorial Kruskal-Wallis test between the control group and the IBS group; (2) a value of less than 0.05 for the pairwise Wilcoxon test among taxonomic constructs; (3) a threshold of logarithmic linear discriminant analysis scores for discriminative features less than 2.0; and (4) a set of multiclass analyzes comparing all to all.

statistical analysis

Statistical analysis was performed using PASW Statistics version 18.0 (2019; SPSS Inc., Chicago, IL, USA). Data were expressed as mean ± standard error of the mean. Wilcoxon rank sum test was performed to compare continuous variables between control and IBS groups. A p-value <0.05 was considered statistically significant.

Sequencing Results

Fecal samples from subjects (Table 1) including IBS group (n=7) and control group (n=12) were sequenced. The subjects included 13 males and 6 females, and the average age was 48.2 years old, showing no significant difference according to gender (male 46.1 years, female 52.7 years old (p=0.455)).

[Table 1]

Baseline characteristics of subjects and samples

After data processing, on average, each sample had effective readings of 65,470±6,481 and operational classification units (OTUs) of 502±48 (normalized to 25,592 readings) (Table 1). Rarefaction curve analysis showed that the depth of sequencing was sufficient to recover most microbial community diversity (see Fig. 1).

According to the principal coordinate analysis based on the number of OTUs, samples were significantly separated according to the presence or absence of IBS (UniFrac, P=0.003) (Fig. 1).

Diversity of Fecal Microbiota

The number of observed OTUs, Chao1 index, Shannon index and phylogenetic diversity index were used to assess bacterial diversity in different disease states. However, the difference between IBS patients and normal controls was not significant (Fig. 2).

Composition of the fecal microflora

The fecal microbiota of normal control and IBS samples consisted mainly of Firmicutes (control, 72.796%±4.936%; IBS, 56.643%±10.453%) and Bacteroidetes (20.446%±4.866%; IBS, 36.329%±11.369%) ( See Table 2A). Other OTUs included Verrucomicrobia (control, 1.805%±1.713%; IBS, 0.764%±0.579%), Proteobacteria (control, 0.507%±0.133%; IBS, 3.139%±1.969%), Fusobacteria (control, 0.364%±0.184%). ; IBS, 2.273%±2.270%), and Actinobacteria (control, 4.074%±1.471%; IBS, 0.818%±0.307%). The Firmicutes / Bacteroidetes ratio (control, 43.781±33.594; IBS, 15.568±10.511), and the abundance of Firmicutes, Verrucomicrobia and Actinobacteria were decreased for the mean of each group in the IBS samples (see FIGS. 2B, C, E, H). ). In contrast, Bacteroidetes, Proteobacteria and Fusobacteria became relatively abundant in IBS samples compared to normal controls (Fig. 2D, F, G). However, these differences were not significant.

Changes in the fecal microbiota in IBS

Comparison of phyla composition did not reveal significant differences, but analysis at the family level confirmed significant changes in microbial composition in IBS patients. According to the LEfSe analysis result, the relative abundance of Desulfovibrionaceae, Sutterellaceae and Acidaminococcaceae in the IBS sample was significantly increased (FIG. 3A). In contrast, the relative abundances of Lachnospiraceae, Peptostreptococcaceae, Erysipelotrichaceae, Clostridiaceae, Leuconostocaceae, Enterococcaceae and Actinomycetaceae were significantly decreased in IBS samples (Fig. 3A). Acidaminococcaceae were significantly enriched in IBS samples (9.886%±4.01%) compared to normal controls (0.387%±0.211%, p=0.037) ( FIG. 3B ). In addition, Sutterellaceae and Desulfovibrionaceae present at low abundance (mean <1%) were significantly more abundant in IBS ( Sutterellaceae , 0.040%±0.015% in normal controls and 0.429%±0.128% in IBS patients, p=0.007; Desulfovibrionaceae , 0.052%±0.035% in normal controls and 0.174%±0.116% in IBS patients, p=0.020) (Figures 3C and D). On the other hand, low abundance ratios (<1%) of Enterococcaceae and Leuconostocaceae were significantly reduced in IBS patients ( Enterococcaceae , 0.054%±0.026% in normal controls and 0.001%±0.001% in IBS patients, p=0.043; Leuconostocaceae , 0.093%±0.060% in normal controls and 0.000%±0.000% in IBS patients, p=0.004) ( FIGS. 3E and F ). Clostridiaceae decreased from 2.134%±1.311% of normal controls to 0.013%±0.007% of IBS patients (P=0.003) ( FIG. 3G ). Similarly, Peptostreptococcaceae was depleted in IBS patients (7.782%±5.631% in normal controls and 0.056%±0.024% in IBS patients, p=0.020) ( FIG. 3H ). In addition, Lachnospiraceae was significantly reduced in IBS patients (34.397%±4.899% in normal controls and 9.798%±2.935% in IBS patients, p=0.009) ( FIG. 3I ).

Changes in functional capacity associated with bile acids

Two orthologues related to secondary bile acid biosynthesis (path ko00121) were significantly reduced in patients with IBS. 3-dehydro-bile acid delta 4,6-reductase (baiN), KO7007, was significantly decreased in IBS patients (p=0.043) ( FIG. 4 ). In addition, K15874, a bile acid 7 beta-dehydratase (baiI), was significantly decreased in IBS patients (p=0.010).

Overall, according to an embodiment of the present invention, the abundance of Acidaminococcaceae , Sutterellaceae and Desulfovibrionaceae was increased in the IBS group compared to the normal control group, and the abundance of Enterococcaceae , Leuconostocaceae , Clostridiaceae , Peptostreptococcaceae and Lachnospiraceae was decreased. Through this, it was found that irritable bowel syndrome can be predicted or diagnosed by using the detection agent of the microorganism.

<110> SEOUL NATIONAL UNIVERSITY HOSPITAL <120> COMPOSITION FOR PREDICTING OR DIAGNOSING IRRITABLE BOWEL SYNDROME COMPRISING MICROORGANISM DETECTION AGENT <130> 20P349IND <150> KR 10-2020-0107347 <151> 2020-08-25 <160> 2 <170> KoPatentIn 3.0 <210> 1 <211> 50 <212> DNA <213> Artificial Sequence <220> <223> primer 341F <400> 1 tcgtcggcag cgtcagatgt gtataagaga cagcctacgg gnggcwgcag 50 <210> 2 <211> 55 <212> DNA <213> Artificial Sequence <220> <223> primer 805R <400> 2 gtctcgtggg ctcggagatg tgtataagag acaggactac hvgggtatct aatcc 55

Claims (9)

a microorganism detection agent;
The microorganism is Acidaminococcaceae , Sutterellaceae , Desulfovibrionaceae , Enterococcaceae , Leuconostocaceae , Clostridiaceae , Peptostreptococcaceae and Lachnospiraceae comprising at least one selected from the group consisting of, irritable bowel syndrome prediction or diagnosis composition. According to claim 1,
Wherein the microorganism detection agent comprises an antisense oligonucleotide, primer pair, probe, antibody, peptide or nucleotide that specifically binds to 16S rRNA of the microorganism. According to claim 1,
The composition of claim 1, wherein the microorganism detection agent comprises primer 341F of SEQ ID NO: 1 and primer 805R of SEQ ID NO: 2. A kit for predicting or diagnosing irritable bowel syndrome, comprising the composition of any one of claims 1 to 3. 5. The method of claim 4,
The kit is compared with a sample derived from a normal person, Acidaminococcaceae , Sutterellaceae and Desulfovibrionaceae have increased abundance, Enterococcaceae , Leuconostocaceae , Clostridiaceae , Peptostreptococcaceae and Lachnospiraceae irritable bowel syndrome for diagnosing when the abundance is reduced, the kit. (a) extracting DNA from the subject's sample;
(b) analyzing the abundance of intestinal microorganisms from the DNA extracted in step (a); and
(c) Comprising the step of comparing the abundance of intestinal microorganisms analyzed in step (b) with a sample derived from a normal person, an information providing method for predicting or diagnosing irritable bowel syndrome. 7. The method of claim 6,
(b) step is to use a PCR primer pair for 16S rRNA of the microorganism. 7. The method of claim 6,
The microorganism comprises at least one selected from the group consisting of Acidaminococcaceae, Sutterellaceae , Desulfovibrionaceae , Enterococcaceae , Leuconostocaceae , Clostridiaceae , Peptostreptococcaceae and Lachnospiraceae . 9. The method of claim 8,
In step (c), the abundance of Acidaminococcaceae , Sutterellaceae and Desulfovibrionaceae is increased, and the abundance of Enterococcaceae , Leuconostocaceae , Clostridiaceae , Peptostreptococcaceae and Lachnospiraceae is reduced compared to the sample derived from a normal person in step (c). How to do it.

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