WO2018124726A1 - Procédé de diagnostic d'une insuffisance rénale par analyse métagénomique bactérienne - Google Patents

Procédé de diagnostic d'une insuffisance rénale par analyse métagénomique bactérienne Download PDF

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WO2018124726A1
WO2018124726A1 PCT/KR2017/015537 KR2017015537W WO2018124726A1 WO 2018124726 A1 WO2018124726 A1 WO 2018124726A1 KR 2017015537 W KR2017015537 W KR 2017015537W WO 2018124726 A1 WO2018124726 A1 WO 2018124726A1
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derived
extracellular vesicles
renal failure
bacteria
content
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PCT/KR2017/015537
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Korean (ko)
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김윤근
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주식회사 엠디헬스케어
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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
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A50/00—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE in human health protection, e.g. against extreme weather
    • Y02A50/30—Against vector-borne diseases, e.g. mosquito-borne, fly-borne, tick-borne or waterborne diseases whose impact is exacerbated by climate change

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  • the present invention relates to a method for diagnosing renal failure through bacterial metagenome analysis, and more specifically, to diagnose kidney failure by performing bacterial metagenomic analysis using a sample derived from a subject, analyzing the increase or decrease in the content of specific bacterial-derived extracellular vesicles. It is about how to.
  • Renal failure refers to the loss of kidney (renal) function and is classified into acute and chronic renal failure according to the time of occurrence.
  • Acute renal failure occurs due to bacterial infections such as pyelonephritis and nephritis, ingestion of external drugs, kidney damage caused by poisons, and insufficient blood volume.
  • Chronic renal failure is often caused by complications of chronic diseases such as hypertension and diabetes. Kidney function is often lost and progresses slowly over a period of 3-12 months.
  • the urinary tract does not produce systemic symptoms, including memory and concentration problems, sleep disorders, headaches, consciousness disorders, loss of coordination, confusion, convulsions, coma, central nervous system symptoms, anxiety-leg syndrome, hiccups, tingling, Peripheral nervous system symptoms such as autologous abnormalities, dizziness, orthostatic hypotension, decreases in tom and saliva, autonomic nervous system symptoms such as abnormal thermoregulation, swelling, cokalemia, metabolic fluids and electrolyte abnormalities.
  • Diagnosis of renal failure is done through a medical test, such as a blood test.
  • a medical test such as a blood test.
  • most cases of renal failure are difficult to treat when the disease is already advanced. Therefore, it is effective to provide a method for preventing the occurrence of renal failure in the high-risk group by predicting the occurrence and causes of renal failure in advance.
  • 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.
  • NGS 16s ribosomal RNA
  • the present inventors extracted the genes from the extracellular vesicles derived from bacteria present in the blood, which is a sample derived from the sample, and performed a metagenome analysis on them in order to diagnose the cause factors and risk of renal failure in advance. To identify a bacterial-derived extracellular vesicle that can act as a bar, the present invention was completed based on this.
  • an object of the present invention is to provide a method for providing information for diagnosing renal failure through metagenome analysis of bacterial extracellular vesicles.
  • the present invention provides a method for providing information for diagnosing kidney failure, comprising the following steps:
  • the present invention also provides a renal failure diagnosis method comprising the following steps:
  • the present invention also provides a method for predicting the risk of developing renal failure, comprising the following steps:
  • step (c) Nitrospirae, Nitrospirae, Chlooflexi, Planctomycetes, Gemmatimonadetes, Acidobacteria, Acidobacteria, WPS-2 Diagnosing renal failure by comparing the increase in the amount of one or more phylum bacterial-derived extracellular vesicles selected from the group consisting of, AD3, Chlamydiae, Elusimicrobia, OD1, and TM6 It may be.
  • deferribacteres In another embodiment, deferribacteres, Coriobacacteriia, Erysipelotrichi, Gamma proteobacteria, Clostridia in step (c) , Actinbacteria, Alphaproteobacteria, Betaproteobacteria, Cytophagia, Thermomephilia, Chloracidobacteria, Methylacididibacteria Methylacidiphilae, Sphingobacteriia, Saprospirae, Anaerolineae, Elin 6529, Planctomycetia, Epsilonproteobacteria, Spaniproproteobacteria Spartobacteria, Acidimicrobiia, Chlamydiia, Acidobacteria-6, Phycisphaerae, TM1, Gemmamati Gemmatimonadetes, DA052, Ktedonobacteria, Pedosphaerae, Acidobacteriia, Soli
  • step (c) Coriobacteriales, Bifidobacteriales, Enterobacteriales, Pseudomonadales, Pseudomonadales, Rizobiales , Acidimicrobiales, Acantimicrobiales, Xanthomonadales, Myxococcales, Rhodocyclales, Solirubrobacterales, Pirellulales, Sphingobacteriales, Rhodospirillales, Thermogemmatisporales, Gemmatales, Saprospirales, Chthoniobacterales, Scintropore Syntrophobacterales, Acidobacteriales, Solibacterales, Pedosphaerales, Cytophag extracellular vesicles derived from one or more order bacteria selected from the group consisting of ales, Chlamydiales, Legionellales, Ktedonobacterales, and Chthonomonadales. It may be to diagnose renal failure by comparing the increase and decrease of the content in the group consisting of ales, Chla
  • Turicibacteraceae Enteriticoccaceae
  • Enterococcaceae Enterobacteriaceae
  • Coriobacteriaceae Coriobacteriaceae
  • Ruminococcaceae Ruminococcaceae
  • Erysipelotrichaceae Pseudomonadaceae
  • Lachnospiraceae Bifidobacteriaceae, Enterobacteriaceae Enterobacteriaceae, Clostridiaceae, Bacteroidaceae, Oxalobacteraceae, Moraxellaceae, Prevotellaceae
  • Sphingo Monadasi Sphingomonadaceae, Caulobacteraceae, Bradyrhizobiaceae, Corynebacteriaceae, Intrasporangiaceae, Streptococcaceae, Zeptococcaceae Tomona Xanthomonadaceae, Chitinophagaceae,
  • step (c) Morganella (Morganella), Adlercreutzia (Adlercreutzia), Turicibacter, Eubacterium (Eubacterium), Cardenibacterium (Catenibacterium) ), Collinsella, Enterococcus, Cupriavidus, Proteus, Escherichia, Osscillospira, Pseudomonas, Yacht Gallicocus () Jeotgalicoccus, Lactobacillus, Enhydrobacter, Luminococcus, Coprococcus, Bifidobacterium, Bacteroides, Acinetobacter ), Prevotella, Fusobacterium, Corynebacterium, Rothia, Gemmata, Pedomicrobium, Mycobacterium , Streptococcus, Opitutus, Kaistobacter, Shewanella, Candidatus Xiphinematobacter, Flavoacterium, Porphyromonas, Peptopteptococcus
  • the blood may be whole blood, serum, plasma, or blood monocytes.
  • Extracellular vesicles secreted by microorganisms, such as bacteria, archaea, etc. present in the environment can be absorbed directly into the body and directly affect cancer development, kidney failure is difficult to diagnose early, so the efficient treatment is difficult, so the present invention
  • Meta-genomic analysis of bacterial-derived extracellular parcel vesicles using human-derived samples according to the pre-diagnosis of the risk of renal failure in advance by early diagnosis and prediction of the risk group of renal failure can be delayed or prevented by proper management.
  • early diagnosis is possible even after the onset of the disease, thereby reducing the incidence of renal failure and increasing the therapeutic effect.
  • metagenome analysis avoids causative agents in patients diagnosed with renal failure, thereby improving cancer progression and preventing recurrence.
  • Figure 1a is a photograph of the distribution of bacteria and vesicles by time after the oral administration of enteric bacteria and bacterial derived vesicles (EV) to the mouse
  • Figure 1b is 12 hours after oral administration, blood And several organs were extracted to evaluate the distribution of bacteria and vesicles in the body.
  • FIG. 2 shows the distribution of bacterial derived vesicles (EVs) with significant diagnostic performance at the phylum level by separating bacteria-derived vesicles from renal inverters and normal blood.
  • EVs bacterial derived vesicles
  • FIG. 3 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at a class level by separating bacteria-derived vesicles from renal inverters and normal blood, and performing a metagenome analysis.
  • EVs bacteria-derived vesicles
  • FIG. 4 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 from renal inverters and normal blood, and performing a metagenome analysis.
  • 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 the renal inverter and normal blood, and performing a metagenome analysis.
  • EVs bacteria-derived vesicles
  • FIG. 6 shows the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at genus level after separation of bacterial-derived vesicles from renal inverters and normal blood.
  • EVs bacteria-derived vesicles
  • the present invention relates to a method for diagnosing renal failure through bacterial metagenome analysis.
  • the present inventors extracted a gene from a bacterial-derived extracellular vesicle using a sample derived from a subject, and performed a metagenome analysis on it.
  • Bacterial-derived extracellular vesicles that can act as
  • the present invention comprises the steps of (a) extracting DNA from the extracellular vesicles isolated from the subject sample;
  • (c) provides an information providing method for diagnosing renal failure, comprising comparing the increase and decrease of the content of bacteria and archaea-derived extracellular vesicles with normal-derived samples by sequencing the PCR product.
  • the term "diagnosis of renal failure” refers to determining whether a kidney failure is likely to occur in a patient, whether the kidney failure is relatively high, or whether renal failure has already occurred.
  • 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 renal failure for any particular patient.
  • the methods of the present invention can be used clinically to determine treatment by early diagnosis of renal failure and by 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.
  • the metagenome analysis of the extracellular vesicles derived from bacteria and archaea was performed, and at the level of phylum, class, order, family, and genus, Each analysis was performed to identify bacterial-derived vesicles that could actually cause kidney failure.
  • Deferribacteres Coriobacteriia, Erysipelotrichi, Gammaproteobacteria, Clostridia, Actinobacteria, Alphaproteobacteria, Betaproteobacteria, Cytophagia Thermoleophilia, Chloracidobacteria, Methylacidiphilae, Sphingobacteriia, Saprospirae, Anaerolineae, Ellin6529, Planctomycetia, Epsilonproteobacteria, Spartobacteria, Acidimicrobiia, Chlamydiia, Acidobacteria-6, Phycisphaerae, TM1, Gemmatiactadetesono, DAbacteria Acid, Peaeroceobacerii, Peaerceoerta,
  • bacterial metagenomes were analyzed at the neck level for vesicles present in a blood sample derived from a subject.
  • Solirubrobacterales Pirellulales, Sphingobacteriales, Rhodospirillales, Thermogemmatisporales, Gemmatales, Saprospirales, Chthoniobacterales, Syntrophobacterales, Acidobacteriales, Solibacterales, Pedosphaerales, Cytophagales, Chlamydiales, Legionellales, and Ktedonobacomoales
  • Example 4 There was a significant difference (see Example 4).
  • Turicibacteraceae as a result of analyzing the bacterial metagenome at the excessive level for the vesicles present in the blood samples from the subject, Turicibacteraceae, Enterococcaceae, Coriobacteriaceae, Lactobacillaceae, Ruminococcaceae, Erysipelotrichaceae, Pseudomonadaceae, Lachnospiraceae, Bifidobacteriaceae, Enterobacteriaceae, Clostridiaceae, Bacteroidaceae, Oxalobacteraceae, Moraxellaceae, Prevotellaceae, Sphingomonadaceae, Caulobacteraceae, Bradyrhizobiaceae, Corynebacteriaceae, Intrasporangiaceae, Streptococcaceae, Xanthomonadaceae, Chitinophagaceae, Mycobacteriaceae, Microbacteriaceae
  • 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 the vesicles were isolated from the blood of 21 renal inverters and 19 healthy subjects matched with 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 genus level, Morganella, Adlercreutzia, Turicibacter, Eubacterium, Catenibacterium, Collinsella, Enterococcus, Cupriavidus, Proteus, Escherichia, Oscillospira, Pseudomonas, Jeotgalicoccus, Lactobacillus, Cocusoccoco, Bifidobacterium, Bacteroides, Acinetobacter, Prevotella, Fusobacterium, Corynebacterium, Rothia, Gemmata, Pedomicrobium, Mycobacterium, Streptococcus, Opitutus, Kaistobacter, Shewanella, Candidatus Xiphinematobacter, Flavobacterium, Porphyr opococtuscoccus When diagnostic models were developed with bacterial biomarkers of the genus Peptoniphilus, Salinispora, Anaerococcus, Candidatus
  • the present invention relates to a method for diagnosing renal failure through analysis of bacterial metagenome, wherein the risk group of renal failure is predicted by predicting the risk of renal failure in advance through metagenomic analysis of bacterial extracellular vesicles using a human-derived sample according to the present invention.

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Abstract

La présente invention concerne un procédé de diagnostic d'une insuffisance rénale par analyse métagénomique bactérienne et, plus particulièrement, un procédé de diagnostic d'une insuffisance rénale par la réalisation d'une analyse métagénomique bactérienne à l'aide d'un échantillon dérivé d'un sujet et par l'analyse d'une augmentation ou d'une diminution de la teneur en une vésicule extracellulaire dérivée d'une bactérie spécifique. Une vésicule extracellulaire sécrétée par un microbe, tel qu'une bactérie et une archée, présente dans l'environnement peut être absorbée dans le corps et influencer directement la fonction rénale et le diagnostic précoce d'une insuffisance rénale est difficile avant l'apparition d'un quelconque symptôme, ce qui complique un traitement efficace. Ainsi, par l'intermédiaire de l'analyse métagénomique d'une vésicule extracellulaire dérivée d'une bactérie à l'aide d'un échantillon dérivé du corps humain selon la présente invention, le risque d'apparition d'une insuffisance rénale peut être prédit à l'avance, ce qui permet un diagnostic précoce et la prédiction d'un groupe à risque d'une insuffisance rénale et de retarder le moment d'apparition ou de prévenir l'apparition par des soins appropriés et un diagnostic précoce est encore possible même après l'apparition, ce qui peut abaisser le taux d'incidence de l'insuffisance rénale et améliorer l'effet de traitement.
PCT/KR2017/015537 2016-12-28 2017-12-27 Procédé de diagnostic d'une insuffisance rénale par analyse métagénomique bactérienne WO2018124726A1 (fr)

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KR1020170180003A KR101940424B1 (ko) 2016-12-28 2017-12-26 세균 메타게놈 분석을 통한 신부전 진단방법

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Citations (3)

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KR20060019700A (ko) * 2004-08-28 2006-03-06 김철민 모든 세균의 감별을 위한 세균 특이적, 속 특이적 및 종특이적 올리고뉴클레오티드, 이를 포함하는 진단 키트, 및이를 이용한 검출 방법
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KR20160073157A (ko) * 2014-12-16 2016-06-24 이화여자대학교 산학협력단 세균 유래의 나노소포체를 이용한 세균성 감염질환 원인균 동정방법

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