WO2018124726A1 - Method for diagnosing renal failure via bacterial metagenomic analysis - Google Patents

Abstract

The present invention relates to a method for diagnosing renal failure via bacterial metagenomic analysis and, more particularly, to a method for diagnosing renal failure by performing bacterial metagenomic analysis using a subject-derived sample, and by analyzing an increase or decrease in the content of a specific bacterium-derived extracellular vesicle. An extracellular vesicle secreted from a microbe, such as a bacterium and an archaeon, present in the environment can be absorbed into the body and directly affect the renal function, and renal failure is difficult to diagnose early on before any symptom appears, which makes efficient treatment difficult. As such, through the metagenomic analysis of a bacterium-derived extracellular vesicle using a human body-derived sample according to the present invention, the risk of the onset of renal failure can be predicted in advance, enabling early diagnosis and prediction of a renal failure risk group and delay of the time of the onset or prevention of the onset with proper care, and early diagnosis is still possible even after the onset, which can lower the incidence rate of renal failure and enhance the treatment effect.

Description

Diagnosis of Kidney Failure through Bacterial Metagenome Analysis

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.

In the case of renal failure, 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. However, 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.

On the other hand, the symbiosis of the human body reaches 100 trillion times 10 times more than human cells, the number of genes of the microorganism is known to be more than 100 times the number of human genes. Microbiota (microbiota or microbiome) 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. However, in the development of renal failure, there has been no report on a method for identifying the cause of renal failure and diagnosing renal failure through metagenomic analysis of bacteria-derived vesicles in human derivatives such as blood, feces or urine.

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.

Accordingly, 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.

However, the technical problem to be achieved by the present invention is not limited to the above-mentioned problem, another task that is not mentioned will be clearly understood by those skilled in the art from the following description.

In order to achieve the object of the present invention as described above, the present invention provides a method for providing information for diagnosing kidney failure, comprising the following steps:

(a) extracting DNA from extracellular vesicles isolated from a subject sample;

(b) performing PCR using the primer pairs of SEQ ID NO: 1 and SEQ ID NO: 2 on the extracted DNA; And

(c) comparing the increase and decrease in the content of the normal-derived sample and the bacteria and / or archaea-derived extracellular vesicles by sequencing the PCR product.

The present invention also provides a renal failure diagnosis method comprising the following steps:

(a) extracting DNA from extracellular vesicles isolated from a subject sample;

(b) performing PCR using the primer pairs of SEQ ID NO: 1 and SEQ ID NO: 2 on the extracted DNA; And

(c) comparing the increase and decrease in the content of the normal-derived sample and the bacteria and / or archaea-derived extracellular vesicles by sequencing the PCR product.

The present invention also provides a method for predicting the risk of developing renal failure, comprising the following steps:

(a) extracting DNA from extracellular vesicles isolated from a subject sample;

(b) performing PCR using the primer pairs of SEQ ID NO: 1 and SEQ ID NO: 2 on the extracted DNA; And

(c) comparing the increase and decrease in the content of the normal-derived sample and the bacteria and / or archaea-derived extracellular vesicles by sequencing the PCR product.

In an embodiment of the present invention, in the 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.

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, Solibacteres, ABS-6, Elusimicrobia, TK10 It may be to diagnose renal failure by comparing the increase or decrease in the content of one or more class bacteria-derived extracellular vesicles selected from the group consisting of, Chthonomonadetes, and TM7-1.

In another embodiment of the present invention, in 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 blood.

In another embodiment of the present invention, in the step (c) Turicibacteraceae (Enteriticoccaceae), Enterococcaceae (Coriobacteriaceae), Coriobacteriaceae (Lactobacillaceae), Ruminococcaceae, Erysipelotrichaceae, Pseudomonadaceae, Lachnospiraceae, Bifidobacteriaceae, Enterobacteriaceae Enterobacteriaceae, Clostridiaceae, Bacteroidaceae, Oxalobacteraceae, Moraxellaceae, Prevotellaceae, Sphingo Monadasi ( Sphingomonadaceae, Caulobacteraceae, Bradyrhizobiaceae, Corynebacteriaceae, Intrasporangiaceae, Streptococcaceae, Zeptococcaceae Tomona Xanthomonadaceae, Chitinophagaceae, Mycobacteriaceae, Microbacteriaceae, Phyllobacteriaceae, Cytophagaceae, Pyrrheulasi (Pirellulaceae), Acetobacteraceae, Comamonadaceae, Chthoniobacteraceae, Isosphaeraceae, Shewanellaceae, Gemmatasi Gemmataceae, Sinobacteraceae, Campylobacteraceae, Hyphomicrobiaceae, Ktedonobacteraceae, Pasteurellaaceae ), Rhodospirillaceae, Myxococcaceae, Thermogemmatisporaceae, Acidobacteriaceae, Syntrophobacteraceae, Gaila Gaieellaceae, Conexibacteraceae, Paramlamydiaceae, Koribacteraceae, Tissierellaceae, Bayericinia Beijerinckiaceae, Burkholderiaceae, Penibacillaceae, Pedosphaeraceae, Solicbacteraceae, Coxiellaceae, Gordonia Gordoniaceae, Methylocystaceae, Micromonosporaceae, Bdellovibrionaceae, Haliangiaceae, Chthonomonadaceae, and Yanni Renal failure may be diagnosed by comparing the increase or decrease in the content of one or more family bacteria-derived extracellular vesicles selected from the group consisting of Elaniellaceae.

In another embodiment of the present invention, in the 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 ), Ralstonia, Rhodoplanes, Alloiococcus, Haemophilus, Candidatus Koribacter, Paenibacillus, Peptoniphilus , Salinispora, Anaerooccus, Candidatus Solibacter, Burgholderia, Campylobacter, Klebsiella, Gordonia ), Palvimonas, Stenotrophomonas, Achromobacter, Pedosphaera, and Bdellovibrio It may be to the diagnosis of renal failure by comparing the amount of increase or decrease in at least one outside (genus) derived from bacterial cell vesicles in the blood.

In another embodiment of the invention, 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. In addition, early diagnosis is possible even after the onset of the disease, thereby reducing the incidence of renal failure and increasing the therapeutic effect. In addition, 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.

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.

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.

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.

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.

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

Thus, the present invention comprises the steps of (a) extracting DNA from the extracellular vesicles isolated from the subject sample;

(b) performing PCR using the primer pairs of SEQ ID NO: 1 and SEQ ID NO: 2 on the extracted DNA; And

(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.

As used herein, 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. In addition, 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.

The term "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. In particular, 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. Technically, 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. In the present invention, metagenome analysis was preferably performed using bacterial-derived extracellular vesicles isolated from serum.

In the present invention, the subject sample may be blood, and the blood may preferably be whole blood, serum, plasma, or blood monocytes, but is not limited thereto.

In an embodiment of the present invention, 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.

More specifically, in one embodiment of the present invention, as a result of analyzing the bacterial metagenome at the gate level for the vesicles present in the blood samples from the subject, Nitrospirae, Chloroflexi, Planctomycetes, Gemmatimonadetes, Acidobacteria, WPS-2, AD3, Chlamydiae, There was a significant difference in the content of Elusimicrobia, OD1, and TM6 door bacteria-derived extracellular vesicles between renal switchers and normal individuals (see Example 4).

More specifically, in one embodiment of the present invention, as a result of analyzing the bacterial metagenome at the level of the vesicles present in the blood samples from the subject, 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, Ph. There was a significant difference in the content of extracellular vesicles derived from TK10, Chthonomonadetes, and TM7-1 strong bacteria between renal switchers and normal individuals (see Example 4).

More specifically, in an embodiment of the present invention, bacterial metagenomes were analyzed at the neck level for vesicles present in a blood sample derived from a subject. Coriobacteriales, Bifidobacteriales, Enterobacteriales, Pseudomonadales, Rhizobiales, Acidimicrobiales, Xanthomonadales, Myxococcales, Rhodocyclales Solirubrobacterales, Pirellulales, Sphingobacteriales, Rhodospirillales, Thermogemmatisporales, Gemmatales, Saprospirales, Chthoniobacterales, Syntrophobacterales, Acidobacteriales, Solibacterales, Pedosphaerales, Cytophagales, Chlamydiales, Legionellales, and Ktedonobacomoales There was a significant difference (see Example 4).

More specifically, in one embodiment of the present invention, 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, Phyllobacteriaceae, Cytophagaceae, Pirellulaceae, Acetobacteraceae, Comamonadaceae, Chthoniobacteraceae, Isosphaeraceae, Shewanellaceae, Gemmataceae, Sinobacteraceae, Campylobacteraceae, Hyphomicrobiaceae, Ktedonobacteraceae, Pasteurellaceae, Rhodospirillaceae, Myxococcaceae, Thermogemmatisporaceae, Acidobacteriaceae, Syntrophobacteraceae, Gaiellaceae, Conexi The content of the bacterium, Parachlamydiaceae, Koribacteraceae, Tissierellaceae, Beijerinckiaceae, Burkholderiaceae, Paenibacillaceae, Pedosphaeraceae, Solibacteraceae, Coxiellaceae, Gordoniaceae, Methylocystaceae, Micromonosporaceae, Bdellovibrionaceae, Haliangiaceae, Chthonomopoaceae, and the bacteria of the cell family. There was a significant difference (see Example 4).

More specifically, in one embodiment of the present invention, as a result of analyzing the bacterial metagenome at the genus level for the vesicles present in the blood samples from the subject, Morganella, Adlercreutzia, Turicibacter, Eubacterium, Catenibacterium, Collinsella, Enterococcus, Cupriavidus, Proteus, Escherichia, Oscillospira, Pseudomonas, Jeotgalicoccus, Lactobacillus, Enhydrobacter, Ruminococcus, Coprococcus, Bifidobacterium, Bacteroides, Acinetobacter, Prevotella, Fusobacterium, Corynebacterium, Rothia, Gemmata, Pedoterus, Streptococcus, Streptococcus , Peptostreptococcus, Ralstonia, Rhodoplanes, Alloiococcus, Haemophilus, Candidatus Koribacter, Paenibacillus, Peptoniphilus, Salinispora, Anaerococcus, Candidatus Solibacter, Burkholderia, Campylobacter, Klebsiella, Gordonia, B. There was a significant difference between the renal inverters and normal subjects (see Example 4).

Through the results of the above example, it was confirmed that the distribution variables of the identified bacteria and archaea-derived extracellular vesicles could be usefully used for predicting renal failure occurrence.

Hereinafter, preferred examples are provided to aid in understanding the present invention. However, the following examples are merely provided to more easily understand the present invention, and the contents of the present invention are not limited by the following examples.

EXAMPLE

Example 1 Analysis of Uptake, Distribution, and Excretion of Intestinal Bacteria and Bacterial-Derived Vesicles

In order to evaluate whether the intestinal bacteria and bacteria-derived vesicles are absorbed systemically through the gastrointestinal tract, experiments were performed as follows. Fluorescently labeled enterobacteriaceae and enteric bacteria-derived vesicles were administered to the gastrointestinal tract at doses of 50 μg, respectively, and the fluorescence was measured after 0, 5, 3, 6 and 12 hours. As a result of observing the entire image of the mouse, as shown in FIG. 1A, the bacteria (Bacteria) were not absorbed systemically, but in the case of bacteria-derived vesicles (EV), they were absorbed systemically 5 minutes after administration and administered. After 3 hours, the bladder was strongly observed, indicating that the vesicles were excreted by the urinary system. In addition, the vesicles were found to exist in the body until 12 hours of administration.

After the systemic absorption of enterobacteriaceae and enteric bacteria-derived vesicles systemically, in order to assess the invasion of various organs, the fluorescently labeled 50 μg 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. As shown in FIG. 1B, 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.

Example 2. Vesicle Separation and DNA Extraction from Blood

To separate the vesicles from the blood and extract the DNA, 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 ㎛ filter, transfer to centripreigugal filters (50 kD) and centrifuged at 1500 xg, 4 ℃ for 15 minutes to discard the material smaller than 50 kD and 10 ml Concentrated until. Once again, remove the bacteria and foreign substances using a 0.22 ㎛ filter, discard the supernatant using ultra-fast centrifugation for 3 hours at 150,000 xg, 4 ℃ with a Type 90ti rotor and dissolve the agglomerated pellet in physiological saline (PBS) Vesicles were obtained.

According to the above method, 100 μl of the vesicles isolated from blood were boiled at 100 ° C. to let the DNA inside the lipid out and then cooled on ice for 5 minutes. Next, in order to remove the remaining suspended matter, centrifugation at 10,000 x g, 4 ℃ for 30 minutes, and collected only the supernatant and quantified the DNA amount using Nanodrop. Thereafter, PCR was performed with the 16s rDNA primer shown in Table 1 to confirm whether the bacteria-derived DNA exists in the extracted DNA, and it was confirmed that the bacteria-derived gene exists in the extracted gene.

primer order SEQ ID NO: 16S rDNA 16S_V3_F 5'-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG-3 ' One 16S_V4_R 5'-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVGGGTATCTAATCC-3 ' 2

Example 3 Metagenomic Analysis Using DNA Extracted from Blood

After the gene was extracted by the method of Example 2, 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. After removing the low quality part, only the lead length was 300 bps or more (Sickle version 1.33), and the Operational Taxonomy Unit (OTU) 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 4 Renal Failure Diagnosis Model Based on Bacterial-Derived Vesicle Metagenome Analysis

In the method of 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. 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.

Analysis of bacteria-derived vesicles in the blood at the phylum level revealed that diagnostic models were developed with Nitrospirae, Chloroflexi, Planctomycetes, Gemmatimonadetes, Acidobacteria, WPS-2, AD3, Chlamydiae, Elusimicrobia, OD1, and TM6 door bacterial biomarkers At that time, the diagnostic performance for renal failure was significant (see Table 2 and FIG. 2).

Control Kidney failure t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity p__Nitrospirae 0.0003 0.0012 0.0019 0.0017 0.0020 6.88 0.87 0.68 0.81 p__Chloroflexi 0.0009 0.0030 0.0151 0.0106 0.0000 16.24 0.96 0.95 0.86 p__Planctomycetes 0.0008 0.0020 0.0225 0.0172 0.0000 27.60 0.97 0.89 0.90 p__Gemmatimonadetes 0.0001 0.0002 0.0032 0.0026 0.0000 59.61 0.94 0.95 0.76 p__Acidobacteria 0.0007 0.0016 0.1093 0.0821 0.0000 145.81 1.00 1.00 1.00 p__WPS-2 0.0000 0.0000 0.0047 0.0035 0.0000 1.00 1.00 1.00 p__AD3 0.0000 0.0000 0.0031 0.0032 0.0002 0.99 0.95 0.90 p__Chlamydiae 0.0000 0.0000 0.0019 0.0015 0.0000 0.98 0.89 0.86 p__Elusimicrobia 0.0000 0.0000 0.0011 0.0011 0.0001 0.93 1.00 0.81 p__OD1 0.0000 0.0000 0.0009 0.0008 0.0001 0.90 1.00 0.71 p__TM6 0.0000 0.0000 0.0005 0.0006 0.0005 0.86 0.84 0.71

Analysis of bacteria-derived vesicles in the blood at the class level showed that Deferribacteres, Coriobacteriia, Erysipelotrichi, Gammaproteobacteria, Clostridia, Actinobacteria, Alphaproteobacteria, Betaproteobacteria, Cytophagia, Thermoleophilia, Chloracidobacteria, Methylacidiphilae, Sphingobacteriia, Saline Diagnosing Epsilonproteobacteria, Spartobacteria, Acidimicrobiia, Chlamydiia, Acidobacteria-6, Phycisphaerae, TM1, Gemmatimonadetes, DA052, Ktedonobacteria, Pedosphaerae, Acidobacteriia, Solibacteres, ABS-6, Elusimicrobia, TK10, Chthonomonadetes, and TM7-1 When developed, the diagnostic performance for renal failure was significant (see Table 3 and FIG. 3).

Control Kidney failure t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity c__Deferribacteres 0.0009 0.0016 0.0000 0.0000 0.0156 0.00 0.89 0.89 0.76 c__Coriobacteriia 0.0107 0.0093 0.0003 0.0005 0.0001 0.03 0.98 0.89 1.00 c__Erysipelotrichi 0.0052 0.0050 0.0005 0.0021 0.0008 0.10 0.92 0.79 0.86 c__Gammaproteobacteria 0.4901 0.1255 0.1726 0.0611 0.0000 0.35 1.00 1.00 1.00 c__Clostridia 0.0906 0.0349 0.0447 0.0261 0.0000 0.49 0.91 0.89 0.81 c__Actinobacteria 0.0589 0.0254 0.1178 0.0430 0.0000 2.00 0.92 0.84 0.90 c__Alphaproteobacteria 0.0418 0.0294 0.0987 0.0575 0.0005 2.36 0.88 0.89 0.67 c__Betaproteobacteria 0.0251 0.0133 0.0736 0.0258 0.0000 2.94 0.99 0.89 0.95 c__Cytophagia 0.0006 0.0012 0.0030 0.0035 0.0085 4.85 0.88 0.63 0.90 c__Thermoleophilia 0.0012 0.0027 0.0066 0.0050 0.0002 5.35 0.94 0.95 0.86 c__Chloracidobacteria 0.0004 0.0012 0.0022 0.0018 0.0008 5.53 0.93 0.79 0.76 c __ [Methylacidiphilae] 0.0001 0.0005 0.0007 0.0007 0.0096 5.71 0.87 1.00 0.67 c__Sphingobacteriia 0.0005 0.0008 0.0032 0.0032 0.0016 5.88 0.88 0.84 0.86 c __ [Saprospirae] 0.0011 0.0021 0.0064 0.0054 0.0003 5.88 0.93 0.95 0.81 c__Anaerolineae 0.0002 0.0006 0.0010 0.0009 0.0019 6.28 0.86 0.68 0.86 c__Ellin6529 0.0002 0.0007 0.0011 0.0011 0.0034 6.65 0.93 1.00 0.76 c__Planctomycetia 0.0023 0.0078 0.0161 0.0138 0.0005 6.95 0.98 0.89 0.95 c__Epsilonproteobacteria 0.0019 0.0038 0.0140 0.0111 0.0001 7.26 0.96 0.84 0.90 c __ [Spartobacteria] 0.0013 0.0059 0.0104 0.0096 0.0011 7.71 1.00 1.00 1.00 c__Acidimicrobiia 0.0008 0.0025 0.0067 0.0047 0.0000 8.23 0.98 1.00 0.90 c__Chlamydiia 0.0002 0.0009 0.0017 0.0015 0.0005 8.37 0.98 0.89 0.86 c__Acidobacteria-6 0.0007 0.0028 0.0065 0.0051 0.0001 9.85 1.00 1.00 1.00 c__Phycisphaerae 0.0003 0.0007 0.0042 0.0039 0.0003 12.63 0.88 0.84 0.81 c__TM1 0.0001 0.0004 0.0011 0.0011 0.0005 12.88 0.90 1.00 0.71 c__Gemmatimonadetes 0.0002 0.0007 0.0021 0.0018 0.0001 13.80 0.96 1.00 0.81 c__DA052 0.0021 0.0092 0.0292 0.0247 0.0001 13.84 1.00 1.00 1.00 c__Ktedonobacteria 0.0006 0.0027 0.0090 0.0074 0.0001 14.30 1.00 1.00 1.00 c __ [Pedosphaerae] 0.0006 0.0027 0.0093 0.0088 0.0003 14.79 1.00 1.00 1.00 c__Acidobacteriia 0.0025 0.0110 0.0377 0.0311 0.0001 14.98 1.00 1.00 1.00 c__Solibacteres 0.0012 0.0047 0.0231 0.0205 0.0001 19.52 1.00 1.00 1.00 c__ABS-6 0.0001 0.0003 0.0019 0.0021 0.0011 25.56 0.97 0.95 0.86 c__Elusimicrobia 0.0000 0.0001 0.0011 0.0011 0.0003 56.06 0.93 1.00 0.81 c__TK10 0.0000 0.0000 0.0010 0.0012 0.0011 191.54 0.95 0.89 0.86 c__Chthonomonadetes 0.0000 0.0000 0.0006 0.0006 0.0003 225.87 0.92 1.00 0.76 c__TM7-1 0.0000 0.0000 0.0014 0.0014 0.0003 255.39 0.89 0.95 0.67

Analysis of Bacterial-derived vesicles in the blood at the order level showed that Coriobacteriales, Bifidobacteriales, Enterobacteriales, Pseudomonadales, Rhizobiales, Acidimicrobiales, Xanthomonadales, Myxococcales, Rhodocyclales, Solirubrobacterales, Pirellulales, Sphingobacteriales, Rhodomatispirs porspores, When diagnostic models were developed with Syntrophobacterales, Acidobacteriales, Solibacterales, Pedosphaerales, Cytophagales, Chlamydiales, Legionellales, Ktedonobacterales, and Chthonomonadales neck bacterial biomarkers, diagnostic performance for renal failure was significant (see Table 4 and Figure 4).

Control Kidney failure t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity o__Coriobacteriales 0.0082 0.0095 0.0006 0.0015 0.0026 0.07 0.95 0.84 0.81 o__Bifidobacteriales 0.0109 0.0128 0.0014 0.0038 0.0051 0.13 0.89 0.79 0.81 o__Enterobacteriales 0.1157 0.0800 0.0322 0.0373 0.0003 0.28 0.95 0.95 0.90 o__Pseudomonadales 0.2081 0.1511 0.0818 0.0678 0.0025 0.39 0.93 0.89 0.86 o__Rhizobiales 0.0210 0.0204 0.0505 0.0312 0.0013 2.40 0.86 0.84 0.71 o__Acidimicrobiales 0.0028 0.0044 0.0068 0.0042 0.0054 2.48 0.87 0.89 0.76 o__Xanthomonadales 0.0084 0.0124 0.0216 0.0131 0.0026 2.57 0.88 0.89 0.81 o__Myxococcales 0.0029 0.0047 0.0076 0.0057 0.0079 2.65 0.85 0.79 0.76 o__Rhodocyclales 0.0003 0.0005 0.0008 0.0007 0.0071 2.71 0.89 0.84 0.86 o__Solirubrobacterales 0.0017 0.0025 0.0048 0.0031 0.0018 2.81 0.88 0.89 0.81 o__Pirellulales 0.0005 0.0010 0.0018 0.0014 0.0036 3.35 0.86 0.74 0.76 o__Sphingobacteriales 0.0010 0.0017 0.0033 0.0030 0.0051 3.42 0.85 0.68 0.81 o__Rhodospirillales 0.0086 0.0149 0.0298 0.0223 0.0013 3.46 0.87 0.89 0.76 o__Thermogemmatisporales 0.0012 0.0028 0.0042 0.0033 0.0043 3.48 0.88 0.79 0.81 o__Gemmatales 0.0037 0.0087 0.0132 0.0104 0.0035 3.61 0.88 0.79 0.71 o __ [Saprospirales] 0.0019 0.0033 0.0069 0.0053 0.0011 3.62 0.89 0.79 0.71 o __ [Chthoniobacterales] 0.0031 0.0073 0.0111 0.0098 0.0058 3.65 0.87 0.79 0.71 o__Syntrophobacterales 0.0007 0.0015 0.0026 0.0023 0.0039 3.75 0.88 0.79 0.81 o__Acidobacteriales 0.0101 0.0213 0.0386 0.0290 0.0012 3.82 0.87 0.84 0.81 o__Solibacterales 0.0059 0.0141 0.0226 0.0184 0.0030 3.83 0.86 0.79 0.81 o __ [Pedosphaerales] 0.0024 0.0056 0.0093 0.0082 0.0041 3.87 0.86 0.79 0.71 o__Cytophagales 0.0007 0.0012 0.0030 0.0034 0.0096 4.32 0.90 0.74 0.86 o__Chlamydiales 0.0004 0.0011 0.0017 0.0014 0.0017 4.53 0.90 0.89 0.81 o__Legionellales 0.0004 0.0012 0.0020 0.0016 0.0010 4.55 0.87 0.79 0.76 o__Ktedonobacterales 0.0005 0.0012 0.0023 0.0024 0.0042 4.82 0.86 0.79 0.71 o__Chthonomonadales 0.0000 0.0001 0.0007 0.0006 0.0003 20.42 0.91 0.79 0.76

Analysis of bacteria-derived vesicles in the blood at the family level revealed that Turicibacteraceae, Enterococcaceae, Coriobacteriaceae, Lactobacillaceae, Ruminococcaceae, Erysipelotrichaceae, Pseudomonadaceae, Lachnospiraceae, Bifidobacteriaceae, Enterobacteriaceae, Clostridiaceae, Bacteroidaceae, Moraxaceae bacteraceae, Bradyrhizobiaceae, Corynebacteriaceae, Intrasporangiaceae, Streptococcaceae, Xanthomonadaceae, Chitinophagaceae, Mycobacteriaceae, Microbacteriaceae, Phyllobacteriaceae, Cytophagaceae, Pirellulaceae, Acetobacteraceae, Comamonadaceae, Chthoniobacteraceae, Isosphaeraceae, Shewanellaceae, Gemmataceae, Sinobacteraceae, Campylobacteraceae, Hyphomicrobiaceae, Ktedonobacteraceae, Pasteurellaceae, Rhodospirillaceae, Myxococcaceae, Thermogemmatisporaceae, Acidobacteriaceae, Syntrophobacteraceae, Gaiellaceae, Conexibacteraceae, Parachlamydiaceae, Koribacteraceae, Tissierellaceae, Beijerinckiaceae, Burkholderiaceae, Paenib When diagnostic models were developed with acillaceae, Pedosphaeraceae, Solibacteraceae, Coxiellaceae, Gordoniaceae, Methylocystaceae, Micromonosporaceae, Bdellovibrionaceae, Haliangiaceae, Chthonomonadaceae, and Yaniellaceae and bacterial biomarkers, diagnostic performance for renal failure was significant (Table 5 and Figure 5). Reference).

Control Kidney failure t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity f__Turicibacteraceae 0.0030 0.0030 0.0000 0.0000 0.0001 0.00 0.97 0.84 0.90 f__Enterococcaceae 0.0080 0.0070 0.0001 0.0003 0.0001 0.01 1.00 1.00 1.00 f__Coriobacteriaceae 0.0107 0.0093 0.0003 0.0005 0.0001 0.03 0.98 0.89 1.00 f__Lactobacillaceae 0.0556 0.0266 0.0039 0.0153 0.0000 0.07 1.00 1.00 1.00 f__Ruminococcaceae 0.0192 0.0081 0.0017 0.0024 0.0000 0.09 1.00 1.00 1.00 f__Erysipelotrichaceae 0.0052 0.0050 0.0005 0.0021 0.0008 0.10 0.92 0.79 0.86 f__Pseudomonadaceae 0.1266 0.0766 0.0136 0.0122 0.0000 0.11 1.00 0.95 1.00 f__Lachnospiraceae 0.0181 0.0119 0.0020 0.0054 0.0000 0.11 0.96 0.84 0.95 f__Bifidobacteriaceae 0.0149 0.0115 0.0017 0.0042 0.0001 0.12 0.95 0.79 0.90 f__Enterobacteriaceae 0.1910 0.0827 0.0276 0.0191 0.0000 0.14 1.00 1.00 1.00 f__Clostridiaceae 0.0058 0.0062 0.0008 0.0007 0.0027 0.15 0.93 0.79 0.81 f__Bacteroidaceae 0.0190 0.0188 0.0028 0.0024 0.0014 0.15 0.92 0.79 0.95 f__Oxalobacteraceae 0.0138 0.0091 0.0036 0.0021 0.0001 0.26 0.93 0.84 0.86 f__Moraxellaceae 0.1585 0.0980 0.0494 0.0362 0.0001 0.31 0.94 0.89 0.95 f__Prevotellaceae 0.0059 0.0041 0.0024 0.0022 0.0031 0.41 0.90 0.79 0.81 f__Sphingomonadaceae 0.0118 0.0102 0.0049 0.0035 0.0100 0.42 0.83 0.63 0.76 f__Caulobacteraceae 0.0015 0.0019 0.0033 0.0014 0.0017 2.19 0.85 0.74 0.81 f__Bradyrhizobiaceae 0.0026 0.0042 0.0084 0.0061 0.0014 3.19 0.90 0.84 0.76 f__Corynebacteriaceae 0.0109 0.0072 0.0367 0.0212 0.0000 3.36 0.95 0.84 0.95 f__Intrasporangiaceae 0.0008 0.0014 0.0037 0.0026 0.0002 4.50 0.93 0.89 0.81 f__Streptococcaceae 0.0208 0.0128 0.1015 0.0786 0.0002 4.89 0.95 0.84 0.86 f__Xanthomonadaceae 0.0009 0.0017 0.0047 0.0026 0.0000 5.15 0.97 0.95 0.95 f__Chitinophagaceae 0.0011 0.0021 0.0059 0.0049 0.0004 5.44 0.93 0.95 0.81 f__Mycobacteriaceae 0.0009 0.0022 0.0053 0.0043 0.0004 5.63 0.91 0.84 0.86 f__Microbacteriaceae 0.0007 0.0014 0.0042 0.0035 0.0003 5.86 0.96 0.89 0.90 f__Phyllobacteriaceae 0.0001 0.0002 0.0004 0.0004 0.0020 6.37 0.90 0.68 0.86 f__Cytophagaceae 0.0004 0.0010 0.0029 0.0035 0.0052 6.63 0.88 0.74 0.90 f__Pirellulaceae 0.0003 0.0008 0.0017 0.0015 0.0006 6.79 0.86 0.79 0.76 f__Acetobacteraceae 0.0010 0.0023 0.0070 0.0055 0.0001 6.89 0.91 0.79 0.81 f__Comamonadaceae 0.0020 0.0024 0.0150 0.0123 0.0001 7.47 0.99 0.95 0.95 f __ [Chthoniobacteraceae] 0.0013 0.0059 0.0104 0.0096 0.0011 7.71 1.00 1.00 1.00 f__Isosphaeraceae 0.0006 0.0024 0.0043 0.0039 0.0010 7.72 0.99 0.89 0.95 f__Shewanellaceae 0.0008 0.0023 0.0063 0.0058 0.0006 7.97 0.97 0.89 0.90 f__Gemmataceae 0.0009 0.0039 0.0087 0.0074 0.0002 9.63 1.00 1.00 1.00 f__Sinobacteraceae 0.0017 0.0068 0.0173 0.0142 0.0001 9.97 1.00 1.00 1.00 f__Campylobacteraceae 0.0013 0.0030 0.0135 0.0109 0.0001 10.41 0.98 0.95 0.95 f__Hyphomicrobiaceae 0.0024 0.0092 0.0265 0.0217 0.0001 10.91 1.00 0.95 0.95 f__Ktedonobacteraceae 0.0002 0.0008 0.0021 0.0023 0.0013 12.15 0.89 1.00 0.71 f__Pasteurellaceae 0.0018 0.0031 0.0230 0.0166 0.0000 12.48 1.00 0.95 0.95 f__Rhodospirillaceae 0.0017 0.0066 0.0216 0.0175 0.0001 12.97 0.99 0.95 0.95 f__Myxococcaceae 0.0000 0.0002 0.0005 0.0005 0.0007 12.99 0.91 1.00 0.71 f__Thermogemmatisporaceae 0.0003 0.0013 0.0042 0.0037 0.0002 13.56 0.99 1.00 0.90 f__Acidobacteriaceae 0.0008 0.0036 0.0114 0.0099 0.0001 13.70 1.00 1.00 1.00 f__Syntrophobacteraceae 0.0002 0.0008 0.0025 0.0023 0.0003 13.92 0.97 1.00 0.90 f__Gaiellaceae 0.0001 0.0005 0.0017 0.0017 0.0004 14.19 0.99 1.00 0.90 f__Conexibacteraceae 0.0001 0.0004 0.0013 0.0010 0.0000 15.22 0.95 1.00 0.81 f__Parachlamydiaceae 0.0001 0.0002 0.0008 0.0011 0.0071 15.22 0.89 1.00 0.67 f__Koribacteraceae 0.0017 0.0073 0.0262 0.0213 0.0001 15.58 1.00 1.00 1.00 f __ [Tissierellaceae] 0.0018 0.0034 0.0280 0.0195 0.0000 15.59 1.00 1.00 1.00 f__Beijerinckiaceae 0.0000 0.0002 0.0007 0.0010 0.0051 15.79 0.93 0.89 0.86 f__Burkholderiaceae 0.0022 0.0066 0.0402 0.0260 0.0000 18.65 1.00 1.00 1.00 f__Paenibacillaceae 0.0000 0.0001 0.0006 0.0006 0.0006 18.84 0.86 0.74 0.71 f __ [Pedosphaeraceae] 0.0001 0.0003 0.0012 0.0012 0.0004 19.75 0.95 0.89 0.86 f__Solibacteraceae 0.0006 0.0026 0.0129 0.0112 0.0001 21.77 1.00 1.00 1.00 f__Coxiellaceae 0.0001 0.0002 0.0013 0.0014 0.0005 24.53 0.92 0.95 0.76 f__Gordoniaceae 0.0000 0.0002 0.0019 0.0019 0.0003 37.84 1.00 1.00 0.95 f__Methylocystaceae 0.0001 0.0004 0.0050 0.0043 0.0001 55.86 1.00 1.00 1.00 f__Micromonosporaceae 0.0000 0.0000 0.0009 0.0009 0.0001 247.23 0.94 0.95 0.76 f__Bdellovibrionaceae 0.0000 0.0000 0.0009 0.0009 0.0000 0.93 0.84 0.71 f__Haliangiaceae 0.0000 0.0000 0.0006 0.0006 0.0006 0.91 0.74 0.90 f__Chthonomonadaceae 0.0000 0.0000 0.0005 0.0006 0.0004 0.87 0.74 0.86 f__Yaniellaceae 0.0000 0.0000 0.0005 0.0008 0.0045 0.86 0.74 0.86

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 Solibacter, Burkholderia, Campylobacter, Klebsiella, Gordonia, Parvimonas, Stenotrophomonas, Achromobacter, Pedosphaera, Table 6 and 6).

Control Kidney failure t-test Taxon Mean SD Mean SD p-value Ratio AUC sensitivity specificity g__Morganella 0.0034 0.0048 0.0000 0.0000 0.0034 0.00 1.00 1.00 1.00 g__Adlercreutzia 0.0022 0.0034 0.0000 0.0000 0.0074 0.00 0.98 0.84 0.90 g__Turicibacter 0.0030 0.0030 0.0000 0.0000 0.0001 0.00 0.97 0.84 0.90 g __ [Eubacterium] 0.0009 0.0013 0.0000 0.0000 0.0049 0.00 0.95 1.00 0.81 g__Catenibacterium 0.0027 0.0042 0.0000 0.0000 0.0060 0.00 0.92 0.74 0.95 g__Collinsella 0.0071 0.0086 0.0000 0.0000 0.0018 0.00 0.98 0.89 0.95 g__Enterococcus 0.0056 0.0046 0.0000 0.0001 0.0000 0.01 1.00 1.00 1.00 g__Cupriavidus 0.0084 0.0073 0.0001 0.0002 0.0001 0.01 1.00 1.00 1.00 g__Proteus 0.0599 0.0323 0.0007 0.0031 0.0000 0.01 1.00 1.00 1.00 g__Escherichia 0.0234 0.0133 0.0005 0.0021 0.0000 0.02 1.00 1.00 1.00 g__Oscillospira 0.0034 0.0021 0.0001 0.0003 0.0000 0.03 0.95 0.84 0.95 g__Pseudomonas 0.1224 0.0760 0.0043 0.0115 0.0000 0.03 1.00 1.00 1.00 g__Jeotgalicoccus 0.0024 0.0029 0.0001 0.0003 0.0031 0.04 0.89 0.79 0.90 g__Lactobacillus 0.0552 0.0268 0.0034 0.0133 0.0000 0.06 1.00 1.00 1.00 g__Enhydrobacter 0.0100 0.0096 0.0008 0.0012 0.0005 0.08 0.91 0.74 0.95 g__Ruminococcus 0.0021 0.0024 0.0002 0.0004 0.0025 0.09 0.90 0.84 0.86 g__Coprococcus 0.0032 0.0032 0.0003 0.0014 0.0013 0.10 0.89 0.84 0.81 g__Bifidobacterium 0.0135 0.0114 0.0017 0.0042 0.0003 0.13 0.94 0.79 0.86 g__Bacteroides 0.0190 0.0188 0.0028 0.0024 0.0014 0.15 0.92 0.79 0.95 g__Acinetobacter 0.1476 0.0975 0.0357 0.0315 0.0001 0.24 0.95 0.89 0.95 g__Prevotella 0.0059 0.0041 0.0024 0.0022 0.0031 0.41 0.90 0.79 0.81 g__Fusobacterium 0.0020 0.0036 0.0065 0.0061 0.0083 3.21 0.88 0.84 0.90 g__Corynebacterium 0.0109 0.0072 0.0367 0.0212 0.0000 3.36 0.95 0.84 0.95 g__Rothia 0.0020 0.0028 0.0088 0.0081 0.0017 4.34 0.91 0.89 0.90 g__Gemmata 0.0002 0.0009 0.0011 0.0009 0.0038 5.25 0.98 0.95 0.90 g__Pedomicrobium 0.0002 0.0009 0.0011 0.0011 0.0054 5.57 0.96 1.00 0.81 g__Mycobacterium 0.0009 0.0022 0.0053 0.0043 0.0004 5.63 0.91 0.84 0.86 g__Streptococcus 0.0155 0.0121 0.1014 0.0785 0.0001 6.53 0.97 0.89 1.00 g__Opitutus 0.0001 0.0003 0.0005 0.0006 0.0066 6.88 0.87 1.00 0.67 g__Kaistobacter 0.0001 0.0003 0.0009 0.0006 0.0001 7.79 0.97 0.95 0.90 g__Shewanella 0.0008 0.0023 0.0063 0.0058 0.0005 8.01 0.97 0.89 0.90 g__Candidatus Xiphinematobacter 0.0005 0.0021 0.0042 0.0041 0.0010 8.81 1.00 1.00 1.00 g__Flavobacterium 0.0001 0.0003 0.0007 0.0007 0.0019 9.41 0.92 0.84 0.81 g__Porphyromonas 0.0019 0.0036 0.0184 0.0154 0.0001 9.75 0.97 0.89 0.90 g__Peptostreptococcus 0.0001 0.0004 0.0009 0.0012 0.0065 10.88 0.99 1.00 0.90 g__Ralstonia 0.0001 0.0004 0.0017 0.0023 0.0073 12.01 0.93 0.95 0.81 g__Rhodoplanes 0.0019 0.0081 0.0232 0.0190 0.0001 12.42 1.00 1.00 1.00 g__Alloiococcus 0.0003 0.0011 0.0048 0.0042 0.0001 14.04 1.00 1.00 1.00 g__Haemophilus 0.0015 0.0029 0.0219 0.0169 0.0000 14.34 1.00 1.00 1.00 g__Candidatus Koribacter 0.0003 0.0013 0.0047 0.0041 0.0002 15.35 1.00 1.00 1.00 g__Paenibacillus 0.0000 0.0001 0.0005 0.0006 0.0026 15.73 0.86 0.74 0.71 g__Peptoniphilus 0.0008 0.0023 0.0141 0.0099 0.0000 18.37 1.00 1.00 1.00 g__Salinispora 0.0000 0.0001 0.0005 0.0006 0.0009 19.41 0.93 1.00 0.76 g__Anaerococcus 0.0003 0.0009 0.0070 0.0048 0.0000 20.10 1.00 1.00 1.00 g__Candidatus Solibacter 0.0006 0.0026 0.0122 0.0107 0.0001 20.63 1.00 1.00 1.00 g__Burkholderia 0.0015 0.0060 0.0386 0.0259 0.0000 26.07 1.00 1.00 1.00 g__Campylobacter 0.0005 0.0022 0.0132 0.0109 0.0000 26.24 1.00 1.00 1.00 g__Klebsiella 0.0001 0.0003 0.0026 0.0030 0.0012 34.86 1.00 1.00 1.00 g__Gordonia 0.0000 0.0002 0.0019 0.0019 0.0003 37.84 1.00 1.00 0.95 g__Parvimonas 0.0000 0.0002 0.0047 0.0047 0.0003 108.25 1.00 1.00 1.00 g__Stenotrophomonas 0.0000 0.0000 0.0018 0.0021 0.0012 390.52 0.96 0.95 0.90 g__Achromobacter 0.0000 0.0000 0.0012 0.0019 0.0094 1236.15 0.99 0.89 0.90 g__Pedosphaera 0.0000 0.0000 0.0010 0.0010 0.0001 0.94 0.89 0.90 g__Bdellovibrio 0.0000 0.0000 0.0009 0.0009 0.0000 0.93 0.84 0.71

The description of the present invention set forth above is for illustrative purposes, and one of ordinary skill in the art may understand that the present invention may be easily modified into other specific forms without changing the technical spirit or essential features of the present invention. There will be. Therefore, it should be understood that the embodiments described above are exemplary in all respects and not restrictive.

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. By early diagnosis and prediction, proper management can delay the onset or prevent the onset, and early diagnosis after the onset can reduce the incidence of renal failure and increase the therapeutic effect.

Claims (16)

(a) extracting DNA from extracellular vesicles isolated from a subject sample; (b) performing PCR using the primer pairs of SEQ ID NO: 1 and SEQ ID NO: 2 on the extracted DNA; And (c) comparing the increase and decrease in the content of the normal-derived sample and the bacterial-derived extracellular vesicles by sequencing the PCR product, information providing method for diagnosing renal failure. The method of claim 1, Nitrospirae, Chlooflexi, Planctomycetes, Gemmatimonadetes, Acidobacteria, WPS-2, AD3, Chlamydiae in step (c) ), Comparing the increase in content of one or more phylum bacteria-derived extracellular vesicles selected from the group consisting of Elusimicrobia, OD1, and TM6. The method of claim 1, Deferribacteres, Corioobacteriia, Erysipelotrichi, Gammaproteobacteria, Clostridia, Actinobacteria, Alpha in the step (c) Alphaproteobacteria, Betaproteobacteria, Cytophagia, Thermolephillia, Chloracidobacteria, Methylacidiphilae, Spingobacteria ), Saprospirae, Anaerolineae, Ellin6529, Planctomycetia, Epsilonproteobacteria, Spartobacteria, Assidi Maitrovia (Chidiybiia), Chlamydiia, Acidobacteria-6, Phycisphaerae, TM1, Gemmatimonadetes, DA05 2, Ktedonobacteria, Pedosphaerae, Acidobacteriia, Solibacteres, ABS-6, Elusimicrobia, TK10, Ktononomonathes (Chthonomonadetes), and an information providing method, characterized by comparing the increase in the content of one or more class bacteria-derived extracellular vesicles selected from the group consisting of TM7-1. The method of claim 1, In step (c), Coriobacteriales, Bifidobacteriales, Enterobacteriales, Pseudomonadales, Rhizobiales, Acidimicrobiales, Acidimicrobiales , Xanthomonadales, Myxococcales, Rhodocyclales, Solirubrobacterales, Pirellulales, Sphingobacteriales, Rhodospi Rhodospirillales, Thermogemmatisporales, Gemmatales, Saprospirales, Chthoniobacterales, Syntrophobacterales, Assido Acidobacteriales, Solibacterales, Pedosphaerales, Cytophagales, Chlamydial es) comparing the increased content of one or more order bacterial-derived extracellular vesicles selected from the group consisting of Legionellales, Ktedonobacterales, and Chthonomonadales. Characterized in that the information providing method. The method of claim 1, In step (c), Turicbacteraceae, Enterococccaceae, Coriobacteriaceae, Coriobacteriaceae, Lactobacillaceae, Luminococcaceae, Ruminococcaceae, Erysipelotrichaceae, Pseudomonadaceae, Lachnospiraceae, Bifidobacteriaceae, Enterobacteriaceae, Clostridiaceae ), Bacteroidaceae, Oxalobacteraceae, Moraxellaceae, Prevotellaceae, Sphingomonadaceae, Kaulobactersia (Caulobacteraceae), Bradyrhizobiaceae, Corynebacteriaceae, Intrasporangiaceae, Streptococcaceae, Xanthomonadaceae, Kitty furnace Chitinophagaceae, Mycobacteriaceae, Microbacteriaceae, Phyllobacteriaceae, Cytophagaceae, Pirellulaceae, Acetobactera si Acetobacteraceae, Comamonadaceae, Chthoniobacteraceae, Isosphaeraceae, Shewanellaceae, Gemmataceae, Sinobactera Sinobacteraceae, Campylobacteraceae, Hyphomicrobiaceae, Ktedonobacteraceae, Pasteurellaaceae, Rhodospirilasi ( Rhodospirillaceae, Myxococcaceae, Thermogemmatisporaceae, Acidobacteriaceae, Syntrophobacteraceae, Gaielellaceae, Connexy Terra Conexibacteraceae, Paramlamididiaceae, Koribacteraceae, Tissierellaceae, Beijerinckiaceae, Burkholderiaceae ), Peenibacillaceae, Pedosphaeraceae, Solibacteraceae, Coxiellaceae, Gordoniaaceae, Methylosistaci ( Methylocystaceae, Micromonosporaceae, Bdellovibrionaceae, Haliangiaceae, Chthonomonadaceae, and Yanielas An information providing method, characterized by comparing the increase in the content of one or more family bacteria-derived extracellular vesicles selected. The method of claim 1, Morganella, Adlercreutzia, Turicibacter, Eubacterium, Catinibacterium, Collinsella, Enterella in the step (c). Enterococcus, Cupriavidus, Proteus, Escherichia, Oscillospira, Pseudomonas, Jeotgalicoccus, Lactobacillus, Lactobacillus Enhydrobacter, Ruminococcus, Coprococcus, Bifidobacterium, Bacteroides, Acinetobacter, Prevotella, Prevotella, Fusobacterium, Corynebacterium, Rothia, Gemmata, Pedomicrobium, Mycobacterium, Steptococcus, Streptococcus Opitutus, Kaisto Kaistobacter, Shewanella, Candidatus Xiphinematobacter, Flavoacterium, Porphyromonas, Peptostreptococcia, Ralstonal , Rhodoplanes, Alloiococcus, Haemophilus, Candidatus Koribacter, Paenibacillus, Peptoniphilus, Salinispora, Salinispora Anaerococcus, Candidatus Solibacter, Burgholderia, Campylobacter, Klebsiella, Gordonia, Parvimonas, Parvimonas, One or more genus bacteria selected from the group consisting of Stenotrophomonas, Achromobacter, Pedosphaera, and Bdellovibrio , Information providing method characterized in that below compares the content of the increase in extracellular vesicles. The method of claim 1, The subject sample is blood, characterized in that the information providing method. The method of claim 7, wherein The blood is characterized in that the whole blood, serum, plasma, or blood monocytes, information providing method. (a) extracting DNA from extracellular vesicles isolated from a subject sample; (b) performing PCR using the primer pairs of SEQ ID NO: 1 and SEQ ID NO: 2 on the extracted DNA; And (c) comparing the increase and decrease of the content of the normal-derived sample and the bacterial-derived extracellular vesicles by sequencing the PCR product, renal failure diagnostic method. The method of claim 9, Nitrospirae, Chlooflexi, Planctomycetes, Gemmatimonadetes, Acidobacteria, WPS-2, AD3, Chlamydiae in step (c) , Elusimicrobia, OD1, and TM6, characterized in comparing the increase in the content of the extracellular vesicles derived from one or more phylum bacteria selected from the group consisting of. The method of claim 9, Deferribacteres, Corioobacteriia, Erysipelotrichi, Gammaproteobacteria, Clostridia, Actinobacteria, Alpha in the step (c) Alphaproteobacteria, Betaproteobacteria, Cytophagia, Thermolephillia, Chloracidobacteria, Methylacidiphilae, Spingobacteria ), Saprospirae, Anaerolineae, Ellin6529, Planctomycetia, Epsilonproteobacteria, Spartobacteria, Assidi Maitrovia (Chidiybiia), Chlamydiia, Acidobacteria-6, Phycisphaerae, TM1, Gemmatimonadetes, DA05 2, Ktedonobacteria, Pedosphaerae, Acidobacteriia, Solibacteres, ABS-6, Elusimicrobia, TK10, Ktononomonathes (Chthonomonadetes), and diagnostic methods, characterized in that the increase in the content of one or more class bacteria-derived extracellular vesicles selected from the group consisting of TM7-1. The method of claim 9, In step (c), Coriobacteriales, Bifidobacteriales, Enterobacteriales, Pseudomonadales, Rhizobiales, Acidimicrobiales, Acidimicrobiales , Xanthomonadales, Myxococcales, Rhodocyclales, Solirubrobacterales, Pirellulales, Sphingobacteriales, Rhodospi Rhodospirillales, Thermogemmatisporales, Gemmatales, Saprospirales, Chthoniobacterales, Syntrophobacterales, Assido Acidobacteriales, Solibacterales, Pedosphaerales, Cytophagales, Chlamydial es) comparing the increased content of one or more order bacterial-derived extracellular vesicles selected from the group consisting of Legionellales, Ktedonobacterales, and Chthonomonadales. A diagnostic method, characterized in that. The method of claim 9, In step (c), Turicbacteraceae, Enterococccaceae, Coriobacteriaceae, Coriobacteriaceae, Lactobacillaceae, Luminococcaceae, Ruminococcaceae, Erysipelotrichaceae, Pseudomonadaceae, Lachnospiraceae, Bifidobacteriaceae, Enterobacteriaceae, Clostridiaceae ), Bacteroidaceae, Oxalobacteraceae, Moraxellaceae, Prevotellaceae, Sphingomonadaceae, Kaulobactersia (Caulobacteraceae), Bradyrhizobiaceae, Corynebacteriaceae, Intrasporangiaceae, Streptococcaceae, Xanthomonadaceae, Kitty furnace Chitinophagaceae, Mycobacteriaceae, Microbacteriaceae, Phyllobacteriaceae, Cytophagaceae, Pirellulaceae, Acetobactera si Acetobacteraceae, Comamonadaceae, Chthoniobacteraceae, Isosphaeraceae, Shewanellaceae, Gemmataceae, Sinobactera Sinobacteraceae, Campylobacteraceae, Hyphomicrobiaceae, Ktedonobacteraceae, Pasteurellaaceae, Rhodospirilasi ( Rhodospirillaceae, Myxococcaceae, Thermogemmatisporaceae, Acidobacteriaceae, Syntrophobacteraceae, Gaielellaceae, Connexy Terra Conexibacteraceae, Paramlamididiaceae, Koribacteraceae, Tissierellaceae, Beijerinckiaceae, Burkholderiaceae ), Peenibacillaceae, Pedosphaeraceae, Solibacteraceae, Coxiellaceae, Gordoniaaceae, Methylosistaci ( Methylocystaceae, Micromonosporaceae, Bdellovibrionaceae, Haliangiaceae, Chthonomonadaceae, and Yanielas A diagnostic method, characterized by comparing the increase in the content of one or more family bacteria-derived extracellular vesicles selected. The method of claim 9, Morganella, Adlercreutzia, Turicibacter, Eubacterium, Catinibacterium, Collinsella, Enterella in the step (c). Enterococcus, Cupriavidus, Proteus, Escherichia, Oscillospira, Pseudomonas, Jeotgalicoccus, Lactobacillus, Lactobacillus Enhydrobacter, Ruminococcus, Coprococcus, Bifidobacterium, Bacteroides, Acinetobacter, Prevotella, Prevotella, Fusobacterium, Corynebacterium, Rothia, Gemmata, Pedomicrobium, Mycobacterium, Steptococcus, Streptococcus Opitutus, Kaisto Kaistobacter, Shewanella, Candidatus Xiphinematobacter, Flavoacterium, Porphyromonas, Peptostreptococcia, Ralstonal , Rhodoplanes, Alloiococcus, Haemophilus, Candidatus Koribacter, Paenibacillus, Peptoniphilus, Salinispora, Salinispora Anaerococcus, Candidatus Solibacter, Burgholderia, Campylobacter, Klebsiella, Gordonia, Parvimonas, Parvimonas, One or more genus bacteria selected from the group consisting of Stenotrophomonas, Achromobacter, Pedosphaera, and Bdellovibrio Diagnostic method, characterized in that below compares the content of the increase in extracellular vesicles. The method of claim 9, The subject sample is a diagnostic method, characterized in that the blood. The method of claim 15, Wherein said blood is whole blood, serum, plasma, or blood monocytes.

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