WO2018155967A1 - Procédé de diagnostic d'une maladie respiratoire obstructive chronique par analyse du métagénome bactérien - Google Patents
Procédé de diagnostic d'une maladie respiratoire obstructive chronique par analyse du métagénome bactérien Download PDFInfo
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- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
- C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
- C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
- C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
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- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
- C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
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- C12Q1/6888—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for detection or identification of organisms
- C12Q1/689—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for detection or identification of organisms for bacteria
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- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
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- Y02A50/00—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE in human health protection, e.g. against extreme weather
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Definitions
- the present invention relates to a method for diagnosing chronic obstructive pulmonary disease such as chronic obstructive pulmonary disease and asthma through bacterial metagenome analysis, and more specifically, by performing a bacterial metagenome analysis using a sample derived from a specific cell-derived cell.
- the present invention relates to a method for diagnosing chronic obstructive airway disease by analyzing the increase and decrease of the content of external vesicles.
- Chronic obstructive airway disease is a chronic lung disease characterized by chronic respiratory distress caused by airway obstruction, and is characterized by asthma and irreversible airway obstruction, which are largely characterized by reversible airway obstruction. It can be roughly classified as a chronic obstructive pulmonary disease (COPD).
- COPD chronic obstructive pulmonary disease
- COPD chronic bronchitis, chronic bronchiolitis, and emphyema caused by chronic inflammation in the lung.
- COPD is a disease pathologically characterized by neutrophil inflammation, which is immunologically characterized by hypersensitivity by Th17 cells.
- asthma is a disease characterized by airway hypersensitivity to a nonspecific stimulus and chronic inflammatory reactions, hypersensitivity by Th2 cells by allergens such as protein antigens derived from house dust mites, etc. and eosinophilic inflammation that occurs as a result It is characterized by.
- microbiota refers to a microbial community including bacteria, archaea and eukarya that exist in a given settlement.Intestinal microbiota is an important role in human physiology. It is known to have a great effect on human health and disease through interaction with human cells.
- the symbiotic bacteria secrete nanometer-sized vesicles to exchange information about genes and proteins in other cells.
- the mucous membrane forms a physical protective film that particles larger than 200 nanometers (nm) in size can't pass through, so that the symbiotic bacteria cannot pass through the mucosa, but bacterial-derived vesicles are usually less than 100 nanometers in size. It freely speaks to the mucous membrane and is absorbed by our body.
- Metagenomics also called environmental genomics, can be said to be an analysis of metagenomic data obtained from samples taken from the environment (Korean Patent Publication No. 2011-0073049). Recently, it has become possible to list the bacterial composition of the human microflora by a method based on 16s ribosomal RNA (16s rRNA) sequencing. Next generation sequencing of 16s rDNA sequencing gene of 16s ribosomal RNA is performed. , NGS) platform to analyze.
- the present inventors In order to diagnose chronic obstructive airway disease based on COPD and the causes of asthma, the present inventors extracted genes from extracellular vesicles derived from bacteria from blood samples, and performed metagenome analysis on them. And it was identified a bacterial-derived extracellular vesicles that can act as a causative agent of chronic obstructive airway disease, such as asthma, the present invention was completed based on this.
- an object of the present invention is to provide an information providing method for diagnosing chronic obstructive airway disease through metagenomic analysis of bacterial derived extracellular vesicles.
- the present invention provides a method for providing information for diagnosing chronic obstructive airway disease, comprising the following steps:
- the present invention provides a method for diagnosing chronic obstructive airway disease, comprising the following steps:
- the present invention provides a method for predicting the risk of developing chronic obstructive airway disease, comprising the following steps:
- the subject sample may be blood.
- COPD may be diagnosed by comparing the increase and decrease of the content of the Tenericutes phylum bacteria-derived extracellular vesicles in comparison to the normal-derived sample in step (c).
- COPD by comparing the increase or decrease in the content of one or more class bacteria-derived extracellular vesicles selected from the group consisting of Mollicutes, and Solibacteres compared to the sample derived from normal in step (c) It may be to diagnose.
- At least one order bacterial-derived extracellular selected from the group consisting of Stramenopiles, Rubrobacterales, Turicibacterales, Rhodocyclales, RF39, and Solibacterales compared to a sample derived from a normal person in step (c). It may be to diagnose COPD by comparing the increase and decrease of the contents of the vesicles.
- At least one selected from the group consisting of Rubrobacteraceae, Turicibacteraceae, Rhodocyclaceae, Nocardiaceae, Clostridiaceae, S24-7, Staphylococcaceae, and Gordoniaceae compared to the sample derived from the normal human in step (c) ( family) may be to diagnose COPD by comparing the increase and decrease in the content of bacterial-derived extracellular vesicles.
- Hydrogenophilus, Proteus, Geobacillus, Chromohalobacter, Rubrobacter, Megamonas, Turicibacter, Rhodococcus, Phascolarctobacterium, SMB53, Desulfovibrio, Jeotgalicoccus, Escherilobacterium, Escheribulacterium Increase in the amount of extracellular vesicles derived from one or more genus bacteria derived from the group consisting of Cupriavidus, Adlercreutzia, Clostridium, Faecalibacterium, Stenotrophomonas, Staphylococcus, Gordonia, Micrococcus, Coprococcus, Novosphingobium, Enhydrobacter, Citrobacter, and Brevundimonas To diagnose COPD.
- At least one door selected from the group consisting of Chloroflexi, Armatimonadetes, Fusobacteria, Cyanobacteria, Planctomycetes, Thermi, Verrucomicrobia, Acidobacteria, and TM7 compared to the sample derived from the normal in step (c) phylum)
- Rubrobacteria Fimbriimonadia, Cytophagia, Chloroplast, Fusobacteriia, Saprospirae, Sphingobacteriia, Deinococci, Verrucomicrobiae, TM7-3, Alphaproteobacteria, Flavobacteriia, Bacilli, and By comparing the increase or decrease in the content of one or more class bacteria-derived extracellular vesicles selected from the group consisting of 4C0d-2 may be to diagnose asthma.
- Rubrobacterales In another embodiment, Rubrobacterales, Stramenopiles, Bacillales, Rhodocyclales, Fimbriimonadales, Cytophagales, Rickettsiales, Alteromonadales, Actinomycetales, Streptophyta, Fusobacteriales, CW040, Saprospirales, Aeromonaales Changes in the amount of extracellular vesicles derived from one or more ordered bacteria-derived vesicles selected from the group consisting of Rhizobiales, Pseudomonadales, Deinococcales, Xanthomonadales, Sphingomonadales, Sphingobacteriales, Verrucomicrobiales, Flavobacteriales, Caulobacterales, Enterobacteriales, Bifidobacteriales, and YS2 It may be to diagnose.
- Rubrobacteraceae Exiguobacteraceae, Nocardiaceae, F16, Pseudonocardiaceae, Dermabacteraceae, Brevibacteriaceae, Microbacteriaceae, Staphylococcaceae, Cytophagaceae, Planococcaceae, Tissierellaceae, Fibroiaceae , Campylobacteraceae, Dermacoccaceae, Burkholderiaceae, Rhizobiaceae, Bacillaceae, Corynebacteriaceae, mitochondria, Fusobacteriaceae, Leptotrichiaceae, Pseudomonadaceae, Bradyrhizobiaceae, Aeromonadaceae, Neisseriaceae, Methylobacteriaceae, Carnobacteriaceae, Xanthomonadaceae, Geodermatophilaceae, Mycobacteriaceae, Gordoniaceae, Micrococcaceae, Hypho
- step (c) in the step (c) comparing the asthma patient and COPD patient-derived sample Bacteroidetes, Tenericutes, Thermi, TM7, Cyanobacteria, Verrucomicrobia, Fusobacteria, Acidobacteria, Planctomycetes, Armatimonadetes, Chloroflexi
- Bacteroidetes, Tenericutes, Thermi, TM7, Cyanobacteria, Verrucomicrobia, Fusobacteria, Acidobacteria, Planctomycetes, Armatimonadetes, Chloroflexi By comparing the increase or decrease in the content of one or more phylum bacteria-derived extracellular vesicles selected from may be differential diagnosis between asthma and COPD.
- Bacteroidia, 4C0d-2, Mollicutes, Bacilli, Deinococci, TM7-3, Flavobacteriia, Alphaproteobacteria, Verrucomicrobiae, Fusobacteriia, Saprospirae by comparing the samples derived from asthma patients and COPD patients in step (c)
- Differential diagnosis of asthma and COPD may be performed by comparing the increase or decrease in the content of one or more class bacterial-derived extracellular vesicles selected from the group consisting of Sphingobacteriia, Chloroplast, Cytophagia, Fimbriimonadia, Thermomicrobia, and Solibacteres.
- comparing the sample derived from asthma patients and COPD patients in step (c), YS2, Bifidobacteriales, Turicibacterales, Bacteroidales, RF39, Enterobacteriales, Rhodobacterales, Neisseriales, Gemellales, Deinococcales, Flavobacteriales, Xanthomonadales, Verrucomicrobi A group consisting of Sphingomonadales, Caulobacterales, Fusobacteriales, Saprospirales, Pseudomonadales, Sphingobacteriales, Rhizobiales, Actinomycetales, CW040, Streptophyta, Rickettsiales, Alteromonadales, Cytophagales, Aeromonadales, Fimbriimonadales, JG30-KcillaF, CM and Baso, Differential diagnosis of asthma and COPD may be performed by comparing the increase or decrease of the contents of the order bacteria-derived extra
- Helicobacteraceae Bacteroidaceae, Bifidobacteriaceae, Turicibacteraceae, Rikenellaceae, Odoribacteraceae, Clostridiaceae, Barnesiellaceae, Veillonellaceae, Porphyromonadaceae, Entercillobacteriaceae, Christensenellaceae , Rhodobacteraceae, Nocardiaceae, Neisseriaceae, Gemellaceae, Carnobacteriaceae, Aerococcaceae, Weeksellaceae, Deinococcaceae, Leptotrichiaceae, Mycobacteriaceae, Dietziaceae, Xanthomonadaceae, Pseudomonadaceae, Verrucomicrobiaceae, Methylobacteriaceae, Flavobacteriaceaceae, Nocaceae bacteriabacteriaaceae , Sphingobacteriaceae, Fusobacteriaceae, Moraxel
- Enterobacter, Trabulsiella, Phascolarctobacterium, Klebsiella, Bifidobacterium, Bacteroides, Turicibacter, Sutterella, Butyricimonas, Parabacteroides, Ruminococcus, Veillonella by comparing the sample derived from asthma and COPD patient in step (c) Desulfovibrio SMB53 Roseburia Odoribacter Dialister Escherichia Sphingobium Rothia Paracoccus Lactobacillus Rhodococcus Eubacterium Granulicatella Kaistobacter , Coprococcus, Peptoniphilus, Neisseria, Corynebacterium, Anaerococcus, Acinetobacter, Rubellimicrobium, Sphingobacterium, Sphingomonas, Pedobacter, Finegoldia, Fusobacterium, Lautropia, Moraxella, Enhydrobacter, Dermacoccus, Thermus Bacillus bacterium Bacillus bacterium bacterium bacterium
- the blood may be whole blood, serum, plasma, or blood monocytes.
- Extracellular vesicles secreted by the bacteria present in the environment can be absorbed directly into the body and directly affect the inflammatory response.
- Chronic obstructive airway diseases such as asthma and COPD are difficult to diagnose effectively because they are difficult to diagnose early.
- Predicting the risk of developing chronic obstructive airway disease through metagenomic analysis of bacterial-derived extracellular vesicles using human-derived samples according to the present invention, early diagnosis and prediction of risk groups of chronic obstructive airway disease occur through appropriate management It can delay the timing or prevent the onset, and early diagnosis can also reduce the incidence and treatment effect of chronic obstructive airway disease.
- metagenome analysis predicts causative factors in patients diagnosed with asthma or COPD, thereby avoiding exposure to causative factors and improving disease progression or preventing recurrence.
- Figure 1 is for evaluating the distribution of bacteria-derived extracellular vesicles in the body
- Figure 1a after the administration of oral intestinal bacteria (Bacteria) and bacteria-derived vesicles (EV) in the mouth hourly (0, 5min, 3h, 6h, and 12h) is a photograph taken of their distribution
- Figure 1b is 12 hours after the oral administration of intestinal bacteria (Bacteria) and bacteria-derived extracellular vesicles (EV) to the blood and various organs (heart, Lung, liver, kidney, spleen, adipose tissue, and muscles), and the photographs of the distribution of the bacterial and extracellular vesicles.
- FIG. 2 shows the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the phylum level by separating bacterial-derived vesicles from COPD patients and normal blood, and performing a metagenome analysis.
- EVs bacteria-derived vesicles
- FIG. 3 shows the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at a class level by separating bacterial-derived vesicles from COPD patients and normal blood, and performing a metagenome analysis.
- EVs bacteria-derived vesicles
- EVs bacteria-derived vesicles
- FIG. 5 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the family level by separating bacteria-derived vesicles from COPD patients and normal blood, and performing a metagenome analysis.
- EVs bacteria-derived vesicles
- FIG. 6 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the genus level by separating bacteria-derived vesicles from COPD patients and normal blood, and performing a metagenome analysis.
- EVs bacteria-derived vesicles
- EVs bacteria-derived vesicles
- EVs bacteria-derived vesicles
- FIG. 9 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the order level by separating the bacteria-derived vesicles in asthma patients and normal blood, and performing a metagenome analysis.
- EVs bacteria-derived vesicles
- FIG. 10 shows the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the family level by separating bacteria-derived vesicles from asthmatic patients and normal blood, and performing metagenome analysis.
- EVs bacteria-derived vesicles
- 11 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the genus level by separating bacteria-derived vesicles from asthma and normal blood, and performing a metagenome analysis.
- EVs bacteria-derived vesicles
- EVs bacteria-derived vesicles
- FIG. 13 shows the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at a class level by separating bacteria-derived vesicles from blood of COPD and asthma patients and performing a metagenome analysis.
- EVs bacteria-derived vesicles
- EVs bacteria-derived vesicles
- EVs bacteria-derived vesicles
- FIG. 16 shows the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at genus level after separation of bacteria-derived vesicles from blood of COPD and asthma patients.
- EVs bacteria-derived vesicles
- the present invention relates to a method for diagnosing chronic obstructive airway diseases such as COPD and asthma through bacterial metagenome analysis.
- the present inventors extract a gene from a bacterial-derived extracellular vesicle using a sample derived from a subject and perform a metagenomic analysis on it. Bacterial-derived extracellular vesicles that could act as causative factors of COPD and asthma were identified.
- the present invention comprises the steps of (a) extracting DNA from the extracellular vesicles isolated from the subject sample;
- Providing an information providing method for diagnosing chronic obstructive airway disease comprising the step of differential diagnosis between asthma and COPD by comparing the increase and decrease of bacterial extracellular vesicle content in asthma and COPD patient-derived samples by sequencing the PCR product do.
- chronic obstructive airway disease is a concept including, but not limited to, asthma and COPD.
- COPD chronic bronchitis
- chronic bronchiolitis chronic bronchiolitis
- emphysema emphysema
- the term "diagnosis of chronic obstructive airway disease” refers to whether there is a possibility of developing chronic obstructive airway disease, relatively high chance of developing chronic obstructive airway disease, or chronic obstructive airway disease It means to determine whether or not.
- the method of the present invention can be used to prevent or delay the onset of the disease through special and appropriate management as a patient at high risk of developing chronic obstructive airway disease for any particular patient.
- the methods of the present invention can be used clinically to determine treatment by early diagnosis of chronic obstructive airway disease and selecting the most appropriate treatment regimen.
- metagenome used in the present invention, also referred to as “metagenome”, refers to the total of the genome including all viruses, bacteria, fungi, etc. in an isolated area such as soil, animal intestine, It is mainly used as a concept of genome explaining the identification of many microorganisms at once using sequencer to analyze microorganisms which are not cultured.
- metagenome does not refer to one species of genome or genome, but refers to a kind of mixed dielectric as the genome of all species of one environmental unit. This is a term from the point of view of defining a species in the course of the evolution of biology in terms of functional species as well as various species that interact with each other to create a complete species.
- rapid sequencing is used to analyze all DNA and RNA, regardless of species, to identify all species in one environment, and to identify interactions and metabolism.
- metagenome analysis was preferably performed using bacterial-derived extracellular vesicles isolated from serum.
- the subject sample may be blood, and the blood may preferably be whole blood, serum, plasma, or blood monocytes, but is not limited thereto.
- metagenome analysis was performed on bacteria-derived extracellular vesicles in the blood of normal, asthmatic, and COPD patients, and the phylum, class, order, and family. Analyzes at the,, and genus levels were respectively identified to identify bacterial derived vesicles that could actually cause COPD and asthma development.
- stramenopiles as a result of analyzing the bacteria-derived metagenome at the neck level, stramenopiles, Rubrobacterales, Turicibacterales, Rhodocyclales, RF39, and Solibacterales-derived vesicles derived from neck bacteria have a significant difference between patients with COPD and normal (See Example 4).
- the bacteria-derived metagenome at the level of analysis Rubrobacteraceae, Turicibacteraceae, Rhodocyclaceae, Nocardiaceae, Clostridiaceae, S24-7, Staphylococcaceae, Gordoniaceae and bacteria-derived vesicles are normal to COPD patients There was a significant difference between them (see Example 4).
- the bacteria-derived metagenome at the gate level Chloroflexi, Armatimonadetes, Fusobacteria, Cyanobacteria, Planctomycetes, Thermi, Verrucomicrobia, Acidobacteria, and TM7 door bacteria-derived vesicles are asthmatic and normal There was a significant difference between them (see Example 5).
- Rubrobacterales as a result of analyzing the bacteria-derived metagenome at the neck level, Rubrobacterales, Stramenopiles, Bacillales, Rhodocyclales, Fimbriimonadales, Cytophagales, Rickettsiales, Alteromonadales, Actinomycetales, Streptophyta, Fusobacteriales, CW040, Saprospirales, Aeromonadale
- Rubrobacterales Bacillales, Rhodocyclales, Fimbriimonadales, Cytophagales, Rickettsiales, Alteromonadales, Actinomycetales, Streptophyta, Fusobacteriales, CW040, Saprospirales, Aeromonadale
- Rhizobiales Pseudomonadales, Deinococcales, Xanthomonadales, Sphingomonadales, Sphingobacteriales, Verrucomicrobiales, Flavobacteriales, Caulobacterales
- the bacteria-derived metagenomic at the level of analysis Rubrobacteraceae, Exiguobacteraceae, Nocardiaceae, F16, Pseudonocardiaceae, Dermabacteraceae, Brevibacteriaceae, Microbacteriaceae, Staphylococcaceae, Cytophagaceae, Planococcaceae, Tissierellceae, Rhoaceae , Fimbriimonadaceae, Campylobacteraceae, Dermacoccaceae, Burkholderiaceae, Rhizobiaceae, Bacillaceae, Corynebacteriaceae, mitochondria, Fusobacteriaceae, Leptotrichiaceae, Pseudomonadaceae, Bradyrhizobiaceae, Aeromonadaceae, Neisseriaceae, Methylobacteriaceae, Carnobacteriaceae, Xanthomonadaceae, Geo
- the results of analyzing the bacteria-derived metagenome at the genus level Geobacillus, Rubrobacter, Exiguobacterium, Ralstonia, Sporosarcina, Hydrogenophilus, Rhodococcus, Proteus, Leptotrichia, Brevibacterium, Brachybacterium, Staphylococcus, Peptoniphilus Finegoldia Anaerococcus Sphingobacterium Propionibacterium Micrococcus Fimbriimonas Dermacoccus Campylobacter Agrobacterium Neisseria Acinetobacter Thermus Corynebacterium , Methylobacterium, Gordonia, Burkholderia, Kocuria, Lactobacillus, Deinococcus, Kaistobacter, Akkermansia, Actinomyces, Brevundimonas, Virgibacillus, Bacillus, Eubacterium, Rothia, Chryseobacterium, Faecalibacter
- the bacterium-derived metagenome was analyzed at the gate level, and as a result, Bacteroidetes, Tenericutes, Thermi, TM7, Cyanobacteria, Verrucomicrobia, Fusobacteria, Acidobacteria, Planctomycetes, Armatimonadetes, and Chloroflexi door bacteria-derived vesicles There was a significant difference between asthma and COPD patients (see Example 6).
- the bacterium-derived metagenome was analyzed at a strong level, and as a result, Bacteroidia, 4C0d-2, Mollicutes, Bacilli, Deinococci, TM7-3, Flavobacteriia, Alphaproteobacteria, Verrucomicrobiae, Fusobacteriia, Saprospirae, Sphingobacteriia , Chloroplast, Cytophagia, Fimbriimonadia, Thermomicrobia, and Solibacteres strong bacterial vesicles showed significant differences between asthma and COPD patients (see Example 6).
- the bacteria-derived metagenome at the neck level YS2, Bifidobacteriales, Turicibacterales, Bacteroidales, RF39, Enterobacteriales, Rhodobacterales, Neisseriales, Gemellales, Deinococcales, Flavobacteriales, Xanthomonadales, Verrucomicrobiales, Sphingo , Caulobacterales, Fusobacteriales, Saprospirales, Pseudomonadales, Sphingobacteriales, Rhizobiales, Actinomycetales, CW040, Streptophyta, Rickettsiales, Alteromonadales, Cytophagales, Aeromonadales, Fimbriimonadales, JG30-KF-CM45, Bacillales from Bacillus sp. There was a significant difference (see Example 6).
- the bacterium-derived metagenome was analyzed at an excessive level.
- Helicobacteraceae Bacteroidaceae, Bifidobacteriaceae, Turicibacteraceae, Rikenellaceae, Odoribacteraceae, Clostridiaceae, Barnesiellaceae, Veillonellaceae, Porphyromonadaceae, Enterobacteriaceae, Lactobacillusaceae, Lhooba , Nocardiaceae, Neisseriaceae, Gemellaceae, Carnobacteriaceae, Aerococcaceae, Weeksellaceae, Deinococcaceae, Leptotrichiaceae, Mycobacteriaceae, Dietziaceae, Xanthomonadaceae, Pseudomonadaceae, Verrucomicrobiaceae, Methylobacteriaceae, Flavobacteriaceae, Actinomycetaceae, Actinomycetaceae, Actinomy
- bacteria-derived metagenomes were analyzed at the level of genus, and Enterobacter, Trabulsiella, Phascolarctobacterium, Klebsiella, Bifidobacterium, Bacteroides, Turicibacter, Sutterella, Butyricimonas, Parabacteroides, Ruminococcus, Veillonus, Peulfov, Dediov , SMB53, Roseburia, Odoribacter, Dialister, Escherichia, Sphingobium, Rothia, Paracoccus, Lactobacillus, Rhodococcus, Eubacterium, Granulicatella, Kaistobacter, Capnocytophaga, Deinococcus, Mycobacterium, Microbispora, Methylobacterium, Chphyin abacus bacterium, Actphyinosa bacterus , Peptoniphilus, Neisseria, Corynebacterium, Anaerococcus, A
- the present invention through the results of the above embodiment, by performing a metagenome analysis on the bacterial-derived extracellular vesicles isolated from the blood, the bacteria-derived vesicles significantly changed in the blood content of normal, asthmatic and COPD patients
- the metagenomic analysis confirmed that COPD and asthma can be diagnosed simultaneously with COPD and asthma by analyzing the increase and decrease of the content of bacterial-derived vesicles at each level.
- the fluorescently labeled 50 ⁇ g of bacteria and bacteria-derived vesicles were administered in the same manner as above 12 hours.
- Blood, Heart, Lung, Liver, Kidney, Spleen, Adipose tissue, and Muscle were extracted from mice.
- the intestinal bacteria (Bacteria) were not absorbed into each organ, whereas the intestinal bacteria-derived extracellular vesicles (EV) were detected in the tissues, as shown in FIG. And distribution in liver, kidney, spleen, adipose tissue, and muscle.
- the blood was first placed in a 10 ml tube and centrifuged (3,500 ⁇ g, 10 min, 4 ° C.) to settle the suspended solids to recover only the supernatant and then transferred to a new 10 ml tube. After removing the bacteria and foreign substances from the recovered supernatant using a 0.22 ⁇ m filter, transfer to centripreigugal filters (50 kD) and centrifuged at 1500 xg, 4 °C for 15 minutes to discard the material smaller than 50 kD and 10 ml Concentrated until.
- centripreigugal filters 50 kD
- PCR was performed using the 16S rDNA primer shown in Table 1 to amplify the gene and perform sequencing (Illumina MiSeq sequencer). Output the result as a Standard Flowgram Format (SFF) file, convert the SFF file into a sequence file (.fasta) and a nucleotide quality score file using GS FLX software (v2.9), check the credit rating of the lead, and window (20 bps) The part with the average base call accuracy of less than 99% (Phred score ⁇ 20) was removed.
- SFF Standard Flowgram Format
- the Operational Taxonomy Unit performed UCLUST and USEARCH for clustering according to sequence similarity. Specifically, the clustering is based on 94% genus, 90% family, 85% order, 80% class, and 75% sequence similarity. OTU's door, river, neck, family and genus level classifications were performed, and bacteria with greater than 97% sequence similarity were analyzed using BLASTN and GreenGenes' 16S DNA sequence database (108,453 sequences) (QIIME).
- Example 3 By the method of Example 3, the vesicles were isolated from the blood of 205 patients with COPD and 231 healthy subjects matched with age and sex, and then metagenome sequencing was performed. In the development of the diagnostic model, the strains whose p-value between the two groups is 0.05 or less and more than two times different between the two groups are selected in the t-test. under curve), sensitivity, and specificity.
- Example 3 the vesicles were isolated from the blood of 219 asthma patients and 236 normal subjects who matched age and sex, and then metagenome sequencing was performed.
- the strains whose p-value between the two groups is 0.05 or less and more than two times different between the two groups are selected in the t-test. under curve), sensitivity, and specificity.
- Bacterial-derived vesicles in the blood were analyzed at the order level, and Rubrobacterales, Stramenopiles, Bacillales, Rhodocyclales, Fimbriimonadales, Cytophagales, Rickettsiales, Alteromonadales, Actinomycetales, Streptophyta, Fusobacteriales, CW040, Saprospirales, Aeromonadales, Riseobiss
- diagnostic models were developed with one or more biomarkers in Deinococcales, Xanthomonadales, Sphingomonadales, Sphingobacteriales, Verrucomicrobiales, Flavobacteriales, Caulobacterales, Enterobacteriales, Bifidobacteriales, and YS2 neck bacteria, the diagnostic performance against asthma was significant (Table 9 and FIG. 9).
- Rubrobacteraceae Exiguobacteraceae, Nocardiaceae, F16, Pseudonocardiaceae, Dermabacteraceae, Brevibacteriaceae, Microbacteriaceae, Staphylococcaceae, Cytophagaceae, Planococcaceae, Tissierellaceae, Rhodocyclceaceae, Burkholderiaceae, Rhizobiaceae, Bacillaceae, Corynebacteriaceae, mitochondria, Fusobacteriaceae, Leptotrichiaceae, Pseudomonadaceae, Bradyrhizobiaceae, Aeromonadaceae, Neisseriaceae, Methylobacteriaceae, Carnobacteriaceae, Xanthomonadaceae, Geodermatophilaceae, Mycobacteriaceae, Gordoniaceae, Micrococcaceae, Hypho
- Bacterial-derived vesicles in the blood were analyzed at the genus level, and Geobacillus, Rubrobacter, Exiguobacterium, Ralstonia, Sporosarcina, Hydrogenophilus, Rhodococcus, Proteus, Leptotrichia, Brevibacterium, Brachybacterium, Staphylococcus, Peptoniphilus, Lautropia, Psetoniobactus, Lautropia, Propionibacterium, Micrococcus, Fimbriimonas, Dermacoccus, Campylobacter, Agrobacterium, Neisseria, Acinetobacter, Thermus, Corynebacterium, Fusobacterium, Pseudomonas, Jeotgalicoccus, Dietzia, Rubellimicrobium, Flavobacterium lobium Phosphorium Kocuria, Lactobacillus, Deinococcus, Kaistobacter, Akkermansia, Actinomyces, Brevundimon
- Example 3 By the method of Example 3, vesicles were isolated from the blood of 205 COPD patients and 219 asthma patients, and then metagenome sequencing was performed. In the development of the diagnostic model, the strains whose p-value between the two groups is 0.05 or less and more than two times different between the two groups are selected in the t-test. under curve), sensitivity, and specificity.
- asthma COPD t-test Training set Test set Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity AUC sensitivity specificity o__YS2 0.0007 0.0014 0.0000 0.0002 0.0000 0.04 0.88 0.74 0.93 0.87 0.78 0.92 o__Bifidobacteriales 0.0627 0.0335 0.0127 0.0101 0.0000 0.20 0.97 0.89 0.95 1.00 0.99 0.93 o__Turicibacterales 0.0017 0.0053 0.0004 0.0014 0.0005 0.22 0.87 0.70 0.90 0.81 0.75 0.80 o__Bacteroidales 0.1736 0.0514 0.0585 0.0261 0.0000 0.34 0.98 0.94 0.97 0.99 0.99 0.93 o__RF39 0.0010 0.0016 0.0004 0.0011 0.0000 0.36 0.85 0.72 0.88 0.82 0.75 0.77 o__Enterobacteriales 0.2091 0.0878 0.0932 0.0398 0.0000 0.45 0.94 0.
- asthma COPD t-test Training set Test set Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity AUC sensitivity specificity f__Helicobacteraceae 0.0005 0.0022 0.0000 0.0004 0.0040 0.09 0.84 0.67 0.90 0.82 0.74 0.85 f__Bacteroidaceae 0.1140 0.0469 0.0209 0.0143 0.0000 0.18 0.98 0.93 0.96 0.99 0.97 0.95 f__Bifidobacteriaceae 0.0627 0.0335 0.0127 0.0101 0.0000 0.20 0.97 0.89 0.95 1.00 0.99 0.93 f__Turicibacteraceae 0.0017 0.0053 0.0004 0.0014 0.0005 0.22 0.87 0.70 0.90 0.81 0.75 0.80 f__Rikenellaceae 0.0070 0.0087 0.0017 0.0029 0.0000 0.24 0.90 0.75 0.89 0.88 0.78 0.90 f __ [Odoribacteraceae] 0.00
- Bacterial-derived vesicles in the blood were analyzed at genus level. Dialister, Escherichia, Sphingobium, Rothia, Paracoccus, Lactobacillus, Rhodococcus, Eubacterium, Granulicatella, Kaistobacter, Capnocytophaga, Deinococcus, Mycobacterium, Microbispora, Methylobacterium, Chryseobacterium, Actinomyces, Porphyro cessocus Nexaceus Cosacea Coccus, Anaerococcus, Acinetobacter, Rubellimicrobium, Sphingobacterium, Sphingomonas, Pedobacter, Finegoldia, Fusobacterium, Lautropia, Moraxella, Enhydrobacter, Dermacoccus, Thermus, Citrobacter, Bacillus, Stenotrophomonas, Hymenactact, Propion, Lepoxybacterium Breccibacterium Breccibacterium The diagnostic performance of differenti
- asthma COPD t-test Training set Test set Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity AUC sensitivity specificity g__Enterobacter 0.0016 0.0013 0.0001 0.0005 0.0000 0.08 0.96 0.91 0.94 0.95 0.94 0.85 g__Trabulsiella 0.0007 0.0012 0.0001 0.0004 0.0000 0.08 0.93 0.82 0.93 0.95 0.96 0.87 g__Phascolarctobacterium 0.0024 0.0101 0.0003 0.0010 0.0026 0.12 0.88 0.72 0.90 0.89 0.78 0.90 g__Klebsiella 0.0018 0.0012 0.0003 0.0006 0.0000 0.16 0.96 0.87 0.92 0.97 0.94 0.90 g___Bifidobacterium 0.0623 0.0336 0.0105 0.0083 0.0000 0.17 0.97 0.89 0.96 1.00 0.99 0.95 g__Bacteroides 0.1140 0.0469 0.0209 0.0143 0.000
- the method for diagnosing chronic obstructive airway disease through bacterial metagenomic analysis is performed by performing a bacterial metagenomic analysis using a sample derived from a subject to analyze the increase or decrease in the content of specific bacterial-derived extracellular vesicles such as asthma and COPD. It can be used to predict and diagnose the risk of developing obstructive airway disease. Extracellular vesicles secreted by the bacteria present in the environment can be absorbed directly into the body and directly affect inflammation. Chronic obstructive airway diseases such as asthma and COPD are difficult to diagnose effectively because they are difficult to diagnose early.
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Abstract
La présente invention concerne un procédé de diagnostic d'une maladie respiratoire obstructive chronique telle que l'asthme et la BPCO par l'analyse du métagénome bactérien et, plus particulièrement, concerne un procédé permettant d'effectuer une analyse du métagénome bactérien à l'aide d'un échantillon issu d'un sujet de façon à analyser les augmentations et les diminutions de la quantité de vésicules extracellulaires issues de bactéries spécifiques, ce qui permet de diagnostiquer une maladie pulmonaire obstructive chronique et l'asthme. Les vésicules extracellulaires sécrétées par les bactéries présentes dans l'environnement sont absorbées dans le corps de façon à influencer directement l'apparition d'une inflammation, et étant donné que le diagnostic précoce d'une maladie respiratoire obstructive chronique, telle que l'asthme et la BPCO, avant que les symptômes ne se produisent est difficile, un traitement efficace a été difficile. Par l'analyse du métagénome, à l'aide d'un échantillon d'origine humaine, pour des gènes présents dans des vésicules extracellulaires d'origine bactérienne, conformément à la présente invention, le risque d'apparition d'une maladie respiratoire obstructive chronique, telle que l'asthme et la BPCO, peut être prédit à l'avance de telle sorte que des groupes à risque de maladie respiratoire obstructive chronique sont diagnostiqués et prédit à un stade précoce, ce qui permet de retarder le moment de l'apparition de la maladie ou de retarder l'apparition de la maladie à prévenir par l'intermédiaire d'une gestion appropriée, et le diagnostic précoce est possible même après l'apparition de maladies respiratoires obstructives chroniques telles que l'asthme et la BPCO, ce qui permet d'abaisser l'incidence de la maladie et d'augmenter les effets thérapeutiques.
Priority Applications (4)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2019546145A JP6914553B2 (ja) | 2017-02-24 | 2018-02-23 | 細菌メタゲノム分析を通した慢性閉塞性気道疾患の診断方法 |
| CN201880026878.9A CN110546278B (zh) | 2017-02-24 | 2018-02-23 | 通过细菌宏基因组分析来诊断慢性阻塞性呼吸道疾病的方法 |
| EP18757726.7A EP3587596B1 (fr) | 2017-02-24 | 2018-02-23 | Procédé de diagnostic d'une maladie respiratoire obstructive chronique par analyse du métagénome bactérien |
| US16/488,258 US20200056225A1 (en) | 2017-02-24 | 2018-02-23 | Method for diagnosing chronic obstructive airway disease through bacterial metagenome analysis |
Applications Claiming Priority (6)
| Application Number | Priority Date | Filing Date | Title |
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| KR20170025084 | 2017-02-24 | ||
| KR10-2017-0025084 | 2017-02-24 | ||
| KR20170059081 | 2017-05-12 | ||
| KR10-2017-0059081 | 2017-05-12 | ||
| KR1020180021708A KR101944665B1 (ko) | 2017-02-24 | 2018-02-23 | 세균 메타게놈 분석을 통한 만성폐쇄성기도질환 진단 방법 |
| KR10-2018-0021708 | 2018-02-23 |
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| WO2018155967A1 true WO2018155967A1 (fr) | 2018-08-30 |
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| Application Number | Title | Priority Date | Filing Date |
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| PCT/KR2018/002290 WO2018155967A1 (fr) | 2017-02-24 | 2018-02-23 | Procédé de diagnostic d'une maladie respiratoire obstructive chronique par analyse du métagénome bactérien |
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| WO (1) | WO2018155967A1 (fr) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| EP3760742A4 (fr) * | 2018-02-28 | 2021-12-01 | MD Healthcare Inc. | Nanovésicules issues de bactéries micrococcus et leur utilisation |
| JP2022516988A (ja) * | 2019-01-09 | 2022-03-03 | エムディー ヘルスケア インコーポレイテッド | デイノコッカス属細菌由来ナノ小胞及びその用途 |
| CN115518079A (zh) * | 2022-09-15 | 2022-12-27 | 中南大学湘雅医院 | 一种益生菌及其外膜囊泡在制备防治支气管哮喘制剂中的应用 |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP3760742A4 (fr) * | 2018-02-28 | 2021-12-01 | MD Healthcare Inc. | Nanovésicules issues de bactéries micrococcus et leur utilisation |
| JP2022516988A (ja) * | 2019-01-09 | 2022-03-03 | エムディー ヘルスケア インコーポレイテッド | デイノコッカス属細菌由来ナノ小胞及びその用途 |
| JP7291424B2 (ja) | 2019-01-09 | 2023-06-15 | エムディー ヘルスケア インコーポレイテッド | デイノコッカス属細菌由来ナノ小胞及びその用途 |
| CN115518079A (zh) * | 2022-09-15 | 2022-12-27 | 中南大学湘雅医院 | 一种益生菌及其外膜囊泡在制备防治支气管哮喘制剂中的应用 |
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