WO2018124742A1 - Method for diagnosing prostatic disease via bacterial metagenomic analysis - Google Patents

Abstract

The present invention relates to a method for diagnosing a prostatic disease, such as prostate cancer and prostatic hypertrophy, via bacterial metagenomic analysis and, more particularly, to a method for diagnosing prostate cancer and prostatic hypertrophy by performing bacterial metagenomic analysis by using a subject-derived sample, and analyzing an increase or decrease in the content of a specific bacterium-derived extracellular vesicle. An extracellular vesicle secreted from a bacterium present in the environment can be absorbed into the body and directly affect the occurrence of inflammation and cancer, and a prostatic disease, such as prostate cancer and prostatic hypertrophy, is difficult to diagnose early on before any symptom appears, which makes efficient treatment difficult. As such, through the metagenomic analysis of a gene present in a bacterium-derived extracellular vesicle using a human body-derived sample according to the present invention, the risk of the onset of prostate cancer and prostatic hypertrophy can be predicted in advance, enabling early diagnosis and prediction of a prostatic disease 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 of prostatic hypertrophy or prostate cancer, which can lower the incidence rate of the prostatic disease and enhance the treatment effect.

Description

Prostate Disease Diagnosis Using Bacterial Metagenome Analysis

The present invention relates to a method for diagnosing prostate diseases such as prostate cancer and prostatic hyperplasia through bacterial metagenomic analysis, and more specifically, by performing a bacterial metagenomic analysis using a sample derived from a subject, The present invention relates to a method for diagnosing prostate disease by analyzing the increase or decrease in content.

The prostate gland, part of the male reproductive system, is an organ that mixes with sperm and creates a fluid that makes semen. Prostatic hyperplasia is a condition in which the urinary flow in the urethra is blocked or decreased due to enlargement of the prostate gland, and the urinary flow in the urethra is blocked or reduced.Benign protstate hyperplasia (BPH) is a male urination disorder that increases the size of the prostate gland. Difficulty in urination. The prostate surrounds the tube (ureter) that carries urine out of the bladder. During puberty, the prostate expands evenly, and as you age, the prostate enlarges, focusing on the side of the urethra of the gland. The cause of benign prostatic hyperplasia is not yet clear, but as with other chronic diseases, several factors are known to work. Since the prostate is a testosterone dependent organ, it requires a constant male hormone to maintain its growth and function.If male hormone is not produced due to castration, the prostate may contract, and genetic factors and family history may also be associated with prostatic hyperplasia. It is known that this is.

Prostate carcinoma is a malignant tumor of the prostate gland, most of which is adenocarcinoma (adenocarcinoma of the gland cell) occurring in prostate cells. Risk factors for prostate cancer increase rapidly in old age (50 years and older). According to race, Asians have the lowest incidence, genetic predisposition, family history, male hormones, diabetes, obesity, westernized diet (increase in animal fat intake), and infections. There is no clear evidence that early screening can prevent death from prostate cancer, but blood pressure (serum) prostate-specific antigen (PSA) tests and rectal balance are reported annually for men 50 years of age and older who are generally expected to live longer than 10 years. It is recommended to have a test. However, despite many advances in modern western medicine, there is no method of predicting prostate cancer in a non-invasive way, and conventional diagnostic methods are often found when solid cancer such as prostate cancer is advanced. In order to prevent medical costs and death due to prostate cancer, it is an efficient way to predict the occurrence of prostate cancer and its causative factors, and to provide a method for preventing the occurrence of prostate cancer in high risk groups.

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 prostate diseases such as prostatic hyperplasia and prostate cancer, the method of identifying the causative factors of prostate disease and diagnosing the risk of prostate disease by analyzing metagenomes present in bacteria-derived vesicles in human derivatives such as urine None reported.

In order to diagnose prostate disease based on the causes of prostatic hyperplasia and prostate cancer, the present inventors extracted a gene from a bacterial-derived extracellular vesicle in a sample-derived urine and performed a metagenome analysis on it. Bacterial-derived extracellular vesicles that can act as causative factors of prostate diseases such as cancer and prostatic hyperplasia have been identified, and thus the present invention has been completed.

Accordingly, an object of the present invention is to provide an information providing method for diagnosing prostate cancer through metagenomic analysis of bacterial extracellular vesicles. In addition, an object of the present invention is to provide a method for providing information for diagnosing prostate cancer in patients with enlarged prostate through metagenomic analysis of bacterial extracellular vesicles. In addition, an object of the present invention is to provide an information providing method for diagnosing prostatic hyperplasia through metagenomic 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 prostate disease, 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 of the bacterial-derived extracellular vesicles in the sample derived from normal and prostate cancer patients by sequencing the PCR product; or

Comparing the increase or decrease of bacterial extracellular vesicles in the sample from the prostatic hyperplasia and the prostate cancer patient by sequencing the PCR product; or

Comparing the increase and decrease of the content of bacterial-derived extracellular vesicles in the sample derived from normal and prostatic hypertrophy patients by sequencing the PCR product.

The present invention also provides a prostate disease diagnostic 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 of the bacterial-derived extracellular vesicles in the sample derived from normal and prostate cancer patients by sequencing the PCR product; or

Comparing the increase or decrease of bacterial extracellular vesicles in the sample from the prostatic hyperplasia and the prostate cancer patient by sequencing the PCR product; or

Comparing the increase and decrease of the content of bacterial-derived extracellular vesicles in the sample derived from normal and prostatic hypertrophy patients by sequencing the PCR product.

The present invention also provides a method for predicting the risk of developing a prostate disease, 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 of the bacterial-derived extracellular vesicles in the sample derived from normal and prostate cancer patients by sequencing the PCR product; or

Comparing the increase or decrease of bacterial extracellular vesicles in the sample from the prostatic hyperplasia and the prostate cancer patient by sequencing the PCR product; or

Comparing the increase and decrease of the content of bacterial-derived extracellular vesicles in the sample derived from normal and prostatic hypertrophy patients by sequencing the PCR product.

In one embodiment of the present invention, at least one phylum bacteria-derived extracellular vesicle selected from the group consisting of Tenericutes, Euryarchaeota, Verrucomicrobia, Gemmatimonadetes, Acidobacteria, and Planctomycetes compared to the sample derived from the normal person in the step (c) By comparing the increase and decrease in the amount of prostate cancer may be to diagnose.

In one embodiment of the present invention, at least one steel selected from the group consisting of Mollicutes, Methanobacteria, Verrucomicrobiae, Acidimicrobiia, Spartobacteria, Acidobacteria-6, Gemmatimonadetes, Acidobacteriia, and Pedosphaerae compared to the samples derived from normal persons in the step (c) It may be to diagnose prostate cancer by comparing the increase or decrease in the content of (class) bacteria-derived extracellular vesicles.

In one embodiment, Stramenopiles, Alteromonadales, RF39, Rickettsiales, Neisseriales, Methanobacteriales, Verrucomicrobiales, Myxococcales, Acidimicrobiales, Chthoniobacterales, iii1-15, Acidobacteriales, Ellin3ales, and Pedospha It may be to diagnose prostate cancer by comparing the increase or decrease in the content of one or more order bacteria-derived extracellular vesicles selected from the group consisting of.

In another embodiment of the present invention, Peptococcaceae, Exiguobacteraceae, Actinomycetaceae, Cellulomonadaceae, mitochondria, Fusobacteriaceae, S24-7, Porphyromonadaceae, Flavobacteriaceae, Moraxellaceae, Neisseriaceae, Methanobacteriabiaceae, Verrucomicrobiaceae Prostate cancer 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 Weeksellaceae, Streptomycetaceae, Helicobacteraceae, Chthoniobacteraceae, and Koribacteraceae.

In another embodiment, Rhizobium, Tetragenococcus, Proteus, Morganella, Exiguobacterium, Oribacterium, Porphyromonas, Actinomyces, Cellulomonas, Jeotgalicoccus, Acinetobacter, Fusobacterium, Enterobacter, Neissezi SMB53, Parabacteroides, Faecalibacterium, Catenibacterium, Roseburia, Akkermansia, Methanobrevibacter, Clostridium, Klebsiella, Chryseobacterium, Halomonas, Aggregatibacter, Rhodoplanes, Thermoanaerobacterium, Candidatus Koribacter, and the genus Bacteria from the genus of the genus (i. It may be to diagnose prostate cancer by comparing the increase and decrease in the amount of vesicles.

In another embodiment of the present invention, prostate cancer may be diagnosed by comparing the increase or decrease in the content of Verrucomicrobia phylum bacteria-derived extracellular vesicles compared to the sample from the prostatic hyperplasia in step (c).

In another embodiment of the present invention, the content of at least one class bacteria-derived extracellular vesicles selected from the group consisting of Verrucomicrobiae, Acidimicrobiia, Saprospirae, and Pedosphaerae as compared to the prostatic hypertrophy-derived sample in step (c) It may be to diagnose prostate cancer by comparing the increase and decrease.

In another embodiment of the present invention, at least one order bacterial-derived extracellular vesicle selected from the group consisting of Verrucomicrobiales, Acidimicrobiales, Saprospirales, Pedosphaerales, and Ellin329 compared to the sample from the prostatic hyperplasia patient in step (c) By comparing the increase and decrease in the amount of prostate cancer may be to diagnose.

In another embodiment of the present invention, the amount of the extracellular vesicles derived from one or more family bacteria selected from the group consisting of Verrucomicrobiaceae, Chitinophagaceae, and Helicobacteraceae in the step (c) compared to the sample from the prostatic hyperplasia In comparison, it may be to diagnose prostate cancer.

In another embodiment of the present invention, the amount of one or more genus bacteria-derived extracellular vesicles selected from the group consisting of Ruminococcus, Akkermansia, and Flexispira is increased compared to the sample from the prostatic hyperplasia in step (c). In comparison, it may be to diagnose prostate cancer.

In another embodiment of the present invention, prostate hyperplasia by comparing the increase or decrease of the content of one or more phylum bacteria-derived extracellular vesicles selected from the group consisting of Euryarchaeota, and Acidobacteria in comparison to the sample derived from normal in step (c) It may be to diagnose.

In another embodiment of the present invention, compared to the normal sample derived from the step (c) compared to increase or decrease the content of one or more class bacteria-derived extracellular vesicles selected from the group consisting of Methanobacteria, Acidobacteria, and Acidobacteriia It may be to diagnose an enlarged prostate.

In another embodiment, extracellular vesicles derived from at least one order bacterium selected from the group consisting of Stramenopiles, RF39, Saprospirales, Pseudomonadales, Methanobacteriales, and Acidobacteriales compared to the samples derived from normal humans in step (c). By comparing the increase and decrease of the content may be to diagnose prostatic hyperplasia.

In another embodiment of the present invention, at least one family bacteria selected from the group consisting of Exiguobacteraceae, Flavobacteriaceae, Actinomycetaceae, Moraxellaceae, Ruminococcaceae, Rikenellaceae, Methanobacteriaceae, and Koribacteraceae compared to a sample derived from a normal person in step (c). By comparing the increase or decrease in the content of the derived extracellular vesicles may be to diagnose prostatic hyperplasia.

In another embodiment, Rhizobium, Proteus, Acinetobacter, SMB53, Halomonas, Ruminococcus, Faecalibacterium, Klebsiella, Roseburia, Leuconostoc, Bilophila, Chromohalobacter, and Methanobrevibacter, By comparing the increase or decrease in the content of one or more genus bacteria-derived extracellular vesicles selected may be to diagnose prostatic hyperplasia.

In another embodiment of the invention, the sample may be urine.

Extracellular vesicles secreted from the bacteria present in the environment may be absorbed directly into the body and directly affect cancer development, and prostatic hyperplasia and prostate cancer are difficult to diagnose early because symptoms are difficult, so effective treatment is difficult. Meta-genomic analysis of bacterial or bacterial-derived extracellular parcels using human-derived samples to predict the risk of developing prostate diseases such as prostatic hyperplasia and prostate cancer in advance to diagnose and predict risk groups of prostate diseases early It can delay the onset or prevent the onset, and early diagnosis after the onset can reduce the incidence of prostate disease and enhance the treatment effect. In addition, metastatic genome analysis predicts causative factors in patients diagnosed with prostatic hyperplasia or prostate cancer, thereby preventing prostate hypertrophy and prostate cancer, 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 a 12 hours after oral administration of intestinal bacteria (Bacteria) and bacteria-derived extracellular vesicles (EV) to the urine and various organs (heart, Lung, liver, kidney, spleen, adipose tissue, and muscles), and the photographs of the distribution of the bacterial and extracellular vesicles.

Figure 2 shows the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the phylum level by separating the bacteria-derived vesicles in prostate cancer patients and normal urine.

Figure 3 shows the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the class level by separating bacteria-derived vesicles from prostate cancer patients and normal urine, and performing a metagenome analysis.

Figure 4 shows the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the order (order) level by separating the bacteria-derived vesicles in prostate cancer patients and normal urine.

Figure 5 shows the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the family level by separating bacteria-derived vesicles from prostate cancer patients and normal urine, and performing a metagenome analysis.

Figure 6 shows the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the genus level after the isolation of bacteria-derived vesicles in prostate cancer patients and normal urine.

7 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the phylum level by separating the bacteria-derived vesicles in the urine of patients with prostate cancer and enlarged prostate gland .

8 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the class level by separating the bacteria-derived vesicles in the urine of patients with prostate cancer and enlarged prostate gland. .

9 is a result showing the distribution of bacteria-derived vesicles (EVs) of significant diagnostic performance at the order level by separating the bacteria-derived vesicles in the urine of patients with prostate cancer and enlarged prostate .

10 is a result showing the distribution of bacteria-derived vesicles (EVs) of significant diagnostic performance at the family level by separating the bacteria-derived vesicles in the urine of patients with prostate cancer and enlarged prostate gland .

11 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the genus level after separating the bacteria-derived vesicles in the urine of patients with prostate cancer and enlarged prostate gland .

12 is a result showing the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the phylum level by separating the bacteria-derived vesicles in prostate hypertrophy cancer patients and normal urine.

FIG. 13 shows the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the class level after isolation of bacteria-derived vesicles from prostatic hyperplasia cancer patients and normal urine.

FIG. 14 shows the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the neck level after isolation of bacteria-derived vesicles from prostatic hypertrophy cancer patients and normal urine.

FIG. 15 shows the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the family level after isolation of bacteria-derived vesicles from prostatic hypertrophy cancer patients and normal urine.

FIG. 16 shows the distribution of bacteria-derived vesicles (EVs) with significant diagnostic performance at the genus level after isolation of bacteria-derived vesicles from prostatic hypertrophy cancer patients and normal urine.

The present invention relates to a method for diagnosing prostate diseases such as prostate hyperplasia and prostate cancer through bacterial metagenomic analysis, the present inventors extract a gene from a bacterial-derived extracellular vesicles using a sample derived from the subject and metagenomic analysis And extracellular vesicles derived from bacteria that can act as a causative agent of prostate disease.

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) comparing the increase and decrease of the bacterial-derived extracellular vesicles in the sample derived from normal and prostate cancer patients by sequencing the PCR product; or

Comparing the increase or decrease of bacterial extracellular vesicles in the sample from the prostatic hyperplasia and the prostate cancer patient by sequencing the PCR product; or

Provides an information providing method for diagnosing prostate disease, comprising the step of comparing the increase and decrease of the bacterial-derived extracellular vesicles in the sample derived from normal and prostatic hypertrophy patients by sequencing the PCR product.

As used herein, the term "diagnosis of prostate cancer" means to determine whether a patient is likely to develop prostate cancer, a relatively high probability of developing prostate cancer, or whether prostate cancer 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 prostate cancer for any particular patient. In addition, the methods of the present invention can be used clinically to determine treatment by early diagnosis of prostate cancer and selection of the most appropriate treatment regimen.

As used herein, the term "diagnosis of prostatic hyperplasia" means determining whether there is a possibility of developing prostatic hyperplasia, a relatively high probability of developing prostatic hyperplasia, or whether an enlarged prostate 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 prostatic hyperplasia for any particular patient. In addition, the methods of the present invention can be used clinically to determine treatment by early diagnosis of prostatic hyperplasia and 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 an embodiment of the present invention, metagenome analysis was performed on genes present in bacteria-derived extracellular vesicles in the urine of normal, prostatic hyperplasia, and prostate cancer patients. Analysis at the levels of), family, and genus, respectively, identified bacterial vesicles that could actually contribute to the development of prostate cancer and prostatic hyperplasia.

More specifically, in one embodiment of the present invention, bacteria-derived metagenomes were analyzed at the gate level, and as a result, Tenericutes, Euryarchaeota, Verrucomicrobia, Gemmatimonadetes, Acidobacteria, and Planctomycetes 믄 bacteria-derived vesicles were significantly different between prostate cancer patients and normal people. (See Example 4).

More specifically, in one embodiment of the present invention, as a result of analyzing the bacteria-derived metagenome at the river level, Mollicutes, Methanobacteria, Verrucomicrobiae, Acidimicrobiia, Spartobacteria, Acidobacteria-6, Gemmatimonadetes, Acidobacteriia, and Pedosphaerae river bacteria-derived vesicles There was a significant difference between the patient and the normal (see Example 4).

More specifically, in one embodiment of the present invention, the bacterial-derived metagenome was analyzed at the neck level. As a result, Stramenopiles, Alteromonadales, RF39, Rickettsiales, Neisseriales, Methanobacteriales, Verrucomicrobiales, Myxococcales, Acidimicrobiales, Chthoniobacterales, iii1-15, Acidobacteriales, Ellin329 Vesicle-derived vesicles derived from,, and Pedosphaerales were significantly different between prostate cancer patients and normal individuals (see Example 4).

More specifically, in an embodiment of the present invention, the bacteria-derived metagenome was analyzed at an excessive level. , Rikenellaceae, Weeksellaceae, Streptomycetaceae, Helicobacteraceae, Chthoniobacteraceae, and Bacterial-derived vesicles were significantly different between prostate cancer patients and normal individuals (see Example 4).

More specifically, in one embodiment of the present invention, the bacteria-derived metagenome at the genus level, Rhizobium, Tetragenococcus, Proteus, Morganella, Exiguobacterium, Oribacterium, Porphyromonas, Actinomyces, Cellulomonas, Jeotgalicoccus, Acinetobacter, Fusobacterium, Enterobacter , Adlercreutzia, SMB53, Parabacteroides, Faecalibacterium, Catenibacterium, Roseburia, Akkermansia, Methanobrevibacter, Clostridium, Klebsiella, Chryseobacterium, Halomonas, Aggregatibacter, Rhodoplanes, Thermoanaerobacterium, and Candidatus Kosibacterium genus There was a difference (see Example 4).

In another embodiment of the present invention, metagenome analysis of extracellular vesicles derived from bacteria in the urine of prostatic hyperplasia and prostate cancer patients was carried out, and phylum, class, order, family ), And genus levels were analyzed to identify bacterial vesicles that could actually cause prostate cancer in patients with enlarged prostate.

More specifically, in one embodiment of the present invention, as a result of analyzing the bacteria-derived metagenome at the genus level, there was a significant difference between the prostate cancer patients and prostatic hypertrophy patients with Verrucomicrobia door bacteria-derived vesicles (see Example 5).

More specifically, in one embodiment of the present invention, as a result of analyzing the bacteria-derived metagenome at the river level, the vesicles derived from Verrucomicrobiae, Acidimicrobiia, Saprospirae, and Pedosphaerae river bacteria showed a significant difference between patients with prostate cancer and hypertrophy. (See Example 5).

More specifically, in one embodiment of the present invention, as a result of analyzing the bacteria-derived metagenome at the neck level, Verrucomicrobiales, Acidimicrobiales, Saprospirales, Pedosphaerales, and Ellin329 neck bacteria-derived vesicles significant difference between prostate cancer patients and prostatic hyperplasia patients (See Example 5).

More specifically, in one embodiment of the present invention, as a result of analyzing the bacteria-derived metagenome at the excessive level, there was a significant difference between the prostate cancer patients and prostatic hyperplasia patients with Verrucomicrobiaceae, Chitinophagaceae, Helicobacteraceae and bacteria-derived vesicles (Example 5).

More specifically, in one embodiment of the present invention, as a result of analyzing the bacteria-derived metagenome at the excessive level, there was a significant difference between the prostate cancer patients and prostatic hypertrophy patients with bacteria derived from Ruminococcus, Akkermansia, Flexispira genus (Example 5).

In another embodiment of the present invention, metagenome analysis was performed on bacteria-derived extracellular vesicles in the urine of normal and prostatic hypertrophy patients, including phylum, class, order, family, Analyzes at the genus and genus levels, respectively, identified bacterial vesicles that can actually cause prostate cancer in asthma patients.

More specifically, in one embodiment of the present invention, as a result of analyzing the bacteria-derived metagenome at the gate level, the vesicles derived from Euryarchaeota, and Acidobacteria gate bacteria showed a significant difference between patients with prostatic hyperplasia and normal people (see Example 6). .

More specifically, in one embodiment of the present invention, as a result of analyzing the bacteria-derived metagenome at the river level, the vesicles derived from Methanobacteria, Acidobacteria, and Acidobacteriia strong bacteria had a significant difference between patients with prostatic hyperplasia and normal people (Example 6 Reference).

More specifically, in one embodiment of the present invention, the bacterial-derived metagenome was analyzed at the neck level. As a result, stramenopiles, RF39, Saprospirales, Pseudomonadales, Methanobacteriales, and Acidobacteriales-derived vesicle-derived vesicles were significantly different between prostate hyperplasia and normal people (See Example 6).

More specifically, in an embodiment of the present invention, the bacterial-derived metagenome is analyzed at an exaggerated level, and Exiguobacteraceae, Flavobacteriaceae, Actinomycetaceae, Moraxellaceae, Ruminococcaceae, Rikenellaceae, Methanobacteriaceae, and Koribacteraceae are bacteria-derived vesicles between the prostate hypertrophy and the normal There was a significant difference (see Example 6).

More specifically, in one embodiment of the present invention, bacteria-derived metagenome was analyzed at the genus level, and Rhizobium, Proteus, Acinetobacter, SMB53, Halomonas, Ruminococcus, Faecalibacterium, Klebsiella, Roseburia, Leuconostoc, Bilophila, Chromohalobacter, and Methanobrevibacter Bacterial-derived vesicles were significantly different between prostate hypertrophy patients and normal subjects (see Example 6).

According to the present invention, the bacterial-derived vesicles whose contents were significantly changed in prostate cancer patients compared to normal and prostatic hypertrophy patients by performing metagenomic analysis on bacterial-derived extracellular vesicles isolated from urine. The metagenome analysis confirmed that prostate cancer can be diagnosed by analyzing the increase and decrease of the contents of the bacteria-derived vesicles at each level.

In addition, the present invention, through the results of the above embodiment, by identifying the bacteria-derived extracellular vesicles isolated from urine by metagenomic analysis of bacteria-derived vesicles significantly changed in the content of prostate hypertrophy patients compared to normal people Meta-genomic analysis confirmed that prostatic hyperplasia can be diagnosed by analyzing the increase and decrease of the contents of the bacteria-derived vesicles at each level.

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 absorption, 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 in each organ, whereas the intestinal bacteria-derived extracellular vesicles (EVs) were urine, heart, lung as shown in FIG. And distribution in liver, kidney, spleen, adipose tissue, and muscle.

Example  2. Isolation of Vesicles and DNA Extraction from Urine

To separate the vesicles from the urine and extract the DNA, the urine was first placed in a 10 ml tube and centrifuged (3,500 x 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.

100 μl of the vesicles isolated from the urine according to the above method was boiled at 100 ° C. to let the DNA inside the lipid out of the lipid and 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. Using DNA extracted from urine vesicles Metagenome  analysis

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. Isolation from Urine of Normal and Prostate Cancer Patients Germ-derived  parcel Metagenome  Analysis-based Prostate Cancer Diagnosis Model

By the method of Example 3, vesicles were isolated from urine of 53 prostate cancer patients and 159 normal humans whose age and sex were matched, followed by metagenome sequencing. 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 vesicle-derived vesicles in the urine at the phylum level showed diagnostic performance for prostate cancer when developing a diagnostic model with one or more biomarkers in Tenericutes, Euryarchaeota, Verrucomicrobia, Gemmatimonadetes, Acidobacteria, and Planctomycetes portal bacteria. This was significant (see Table 2 and FIG. 2).

	Normal people		Prostate cancer		t-test
Taxon	Mean	SD	Mean	SD	p-value	Ratio	AUC	sensitivity	specificity
p__Tenericutes	0.0023	0.0068	0.0008	0.0016	0.0096	0.35	0.88	0.93	0.58
p__Euryarchaeota	0.0006	0.0013	0.0014	0.0017	0.0032	2.38	0.87	0.91	0.55
p__Verrucomicrobia	0.0208	0.0283	0.0588	0.0564	0.0000	2.83	0.91	0.94	0.60
p__Gemmatimonadetes	0.0002	0.0007	0.0014	0.0021	0.0001	6.73	0.90	0.92	0.58
p__Acidobacteria	0.0005	0.0017	0.0036	0.0037	0.0000	7.19	0.91	0.92	0.58
p__Planctomycetes	0.0002	0.0010	0.0020	0.0046	0.0088	9.34	0.88	0.92	0.49

Analysis of vesicle-derived vesicles in urine at the class level revealed that diagnostic models were developed with one or more biomarkers in Mollicutes, Methanobacteria, Verrucomicrobiae, Acidimicrobiia, Spartobacteria, Acidobacteria-6, Gemmatimonadetes, Acidobacteriia, and Pedosphaerae river bacteria. , The diagnostic performance for prostate cancer was significant (see Table 3 and Figure 3).

	Normal people		Prostate cancer		t-test
Taxon	Mean	SD	Mean	SD	p-value	Ratio	AUC	sensitivity	specificity
c__Mollicutes	0.0023	0.0068	0.0008	0.0015	0.0066	0.32	0.88	0.93	0.58
c__Methanobacteria	0.0006	0.0012	0.0014	0.0017	0.0028	2.45	0.87	0.91	0.55
c__Verrucomicrobiae	0.0206	0.0281	0.0570	0.0551	0.0000	2.76	0.91	0.94	0.60
c__Acidimicrobiia	0.0002	0.0010	0.0009	0.0017	0.0043	5.00	0.85	0.91	0.43
c __ [Spartobacteria]	0.0001	0.0004	0.0005	0.0008	0.0002	9.75	0.89	0.92	0.57
c__Acidobacteria-6	0.0001	0.0003	0.0009	0.0017	0.0013	16.28	0.89	0.92	0.53
c__Gemmatimonadetes	0.0000	0.0002	0.0005	0.0011	0.0023	16.65	0.87	0.93	0.51
c__Acidobacteriia	0.0000	0.0002	0.0014	0.0018	0.0000	33.12	0.92	0.93	0.60
c __ [Pedosphaerae]	0.0000	0.0000	0.0010	0.0017	0.0001	2689.17	0.93	0.95	0.68

Analysis of vesicle-derived vesicles in the urine at the order level showed stramenopiles, Alteromonadales, RF39, Rickettsiales, Neisseriales, Methanobacteriales, Verrucomicrobiales, Myxococcales, Acidimicrobiales, Chthoniobacterales, iii1-15, Acidobacteriales, Ellin329, and one of the Pedosphaerales bacteria. When developing a diagnostic model with the above biomarkers, the diagnostic performance for prostate cancer was significant (see Table 4 and Figure 4).

	Normal people		Prostate cancer		t-test
Taxon	Mean	SD	Mean	SD	p-value	Ratio	AUC	sensitivity	specificity
o__Stramenopiles	0.0026	0.0059	0.0000	0.0000	0.0000	0.00	0.87	0.86	0.49
o__Alteromonadales	0.0008	0.0020	0.0002	0.0008	0.0015	0.28	0.85	0.90	0.40
o__RF39	0.0023	0.0068	0.0007	0.0015	0.0077	0.32	0.88	0.93	0.58
o__Rickettsiales	0.0012	0.0027	0.0004	0.0008	0.0042	0.38	0.84	0.91	0.40
o__Neisseriales	0.0040	0.0066	0.0020	0.0025	0.0011	0.49	0.86	0.88	0.43
o__Methanobacteriales	0.0006	0.0012	0.0014	0.0017	0.0028	2.45	0.87	0.91	0.55
o__Verrucomicrobiales	0.0206	0.0281	0.0570	0.0551	0.0000	2.76	0.91	0.94	0.60
o__Myxococcales	0.0002	0.0008	0.0007	0.0010	0.0044	2.87	0.85	0.89	0.49
o__Acidimicrobiales	0.0002	0.0010	0.0009	0.0017	0.0043	5.00	0.85	0.91	0.43
o __ [Chthoniobacterales]	0.0001	0.0004	0.0005	0.0008	0.0002	9.75	0.89	0.92	0.57
o__iii1-15	0.0000	0.0003	0.0008	0.0017	0.0014	18.60	0.89	0.92	0.53
o__Acidobacteriales	0.0000	0.0002	0.0014	0.0018	0.0000	33.12	0.92	0.93	0.60
o__Ellin329	0.0000	0.0000	0.0012	0.0018	0.0000	365.18	0.91	0.96	0.58
o __ [Pedosphaerales]	0.0000	0.0000	0.0010	0.0017	0.0001	2689.17	0.93	0.95	0.68

Analysis of bacteria-derived vesicles in urine at the family level revealed that Peptococcaceae, Exiguobacteraceae, Actinomycetaceae, Cellulomonadaceae, mitochondria, Fusobacteriaceae, S24-7, Porphyromonadaceae, Flavobacteriaceae, Moraxellaceae, Neisseriaceae, Methanobacteriaceae, Verrucomicrobibiaceae When diagnostic models were developed with one or more biomarkers in Helicobacteraceae, Chthoniobacteraceae, and Koribacteraceae, the diagnostic performance for prostate cancer was significant (see Table 5 and Figure 5).

	Normal people		Prostate cancer		t-test
Taxon	Mean	SD	Mean	SD	p-value	Ratio	AUC	Accuracy	sensitivity	specificity
f__Peptococcaceae	0.0005	0.0018	0.0000	0.0000	0.0002	0.03	0.88	0.80	0.91	0.49
f __ [Exiguobacteraceae]	0.0019	0.0065	0.0003	0.0008	0.0027	0.14	0.84	0.77	0.90	0.38
f__Actinomycetaceae	0.0043	0.0102	0.0010	0.0015	0.0001	0.23	0.89	0.80	0.87	0.58
f__Cellulomonadaceae	0.0008	0.0021	0.0002	0.0005	0.0011	0.25	0.86	0.77	0.89	0.40
f__mitochondria	0.0011	0.0027	0.0003	0.0007	0.0016	0.31	0.84	0.78	0.92	0.38
f__Fusobacteriaceae	0.0032	0.0095	0.0011	0.0018	0.0070	0.33	0.85	0.77	0.91	0.38
f__S24-7	0.0104	0.0319	0.0036	0.0042	0.0098	0.35	0.83	0.78	0.92	0.38
f__Porphyromonadaceae	0.0142	0.0158	0.0053	0.0045	0.0000	0.37	0.85	0.77	0.88	0.45
f__Flavobacteriaceae	0.0019	0.0030	0.0009	0.0016	0.0035	0.48	0.85	0.76	0.89	0.38
f__Moraxellaceae	0.0532	0.0884	0.0260	0.0275	0.0008	0.49	0.89	0.81	0.91	0.51
f__Neisseriaceae	0.0040	0.0066	0.0020	0.0025	0.0011	0.49	0.86	0.77	0.88	0.43
f__Methanobacteriaceae	0.0006	0.0012	0.0014	0.0017	0.0028	2.45	0.87	0.82	0.91	0.55
f__Verrucomicrobiaceae	0.0206	0.0281	0.0570	0.0551	0.0000	2.76	0.91	0.85	0.94	0.60
f__Rikenellaceae	0.0016	0.0026	0.0046	0.0043	0.0000	2.98	0.89	0.81	0.90	0.53
f __ [Weeksellaceae]	0.0013	0.0022	0.0040	0.0049	0.0003	3.06	0.88	0.83	0.92	0.53
f__Streptomycetaceae	0.0002	0.0008	0.0011	0.0022	0.0075	5.21	0.85	0.77	0.89	0.42
f__Helicobacteraceae	0.0002	0.0011	0.0009	0.0020	0.0092	6.08	0.86	0.81	0.92	0.47
f __ [Chthoniobacteraceae]	0.0001	0.0004	0.0005	0.0008	0.0002	9.75	0.89	0.83	0.92	0.57
f__Koribacteraceae	0.0000	0.0002	0.0014	0.0018	0.0000	43.84	0.92	0.85	0.94	0.60

Analysis of bacteria-derived vesicles in the urine at genus level showed Rhizobium, Tetragenococcus, Proteus, Morganella, Exiguobacterium, Oribacterium, Porphyromonas, Actinomyces, Cellulomonas, Jeotgalicoccus, Acinetobacter, Fusobacterium, Enterobacter, Neissezi, Adissemb, Diagnosis and development of one or more biomarkers for the development of one or more biomarkers for Faecalibacterium, Catenibacterium, Roseburia, Akkermansia, Methanobrevibacter, Clostridium, Klebsiella, Chryseobacterium, Halomonas, Aggregatibacter, Rhodoplanes, Thermoanaerobacterium, Candidatus Koribacter, and Flexispira genus Performance was significant (see Table 6 and FIG. 6).

	Normal people		Prostate cancer		t-test
Taxon	Mean	SD	Mean	SD	p-value	Ratio	AUC	sensitivity	specificity
g__Rhizobium	0.0032	0.0050	0.0000	0.0000	0.0000	0.00	0.98	0.98	0.94
g__Tetragenococcus	0.0007	0.0020	0.0000	0.0000	0.0000	0.01	0.86	0.90	0.42
g__Proteus	0.0115	0.0202	0.0009	0.0013	0.0000	0.07	0.92	0.90	0.68
g__Morganella	0.0042	0.0169	0.0004	0.0010	0.0050	0.09	0.85	0.91	0.38
g__Exiguobacterium	0.0019	0.0065	0.0002	0.0008	0.0026	0.13	0.84	0.90	0.38
g__Oribacterium	0.0005	0.0014	0.0001	0.0004	0.0016	0.13	0.85	0.91	0.42
g__Porphyromonas	0.0022	0.0062	0.0004	0.0010	0.0005	0.18	0.86	0.89	0.43
g__Actinomyces	0.0041	0.0099	0.0009	0.0015	0.0001	0.21	0.89	0.87	0.58
g__Cellulomonas	0.0006	0.0017	0.0002	0.0005	0.0045	0.27	0.86	0.89	0.38
g__Jeotgalicoccus	0.0009	0.0020	0.0003	0.0007	0.0007	0.30	0.85	0.91	0.36
g__Acinetobacter	0.0431	0.0871	0.0136	0.0185	0.0001	0.32	0.89	0.90	0.64
g__Fusobacterium	0.0032	0.0095	0.0011	0.0018	0.0073	0.33	0.85	0.91	0.38
g__Enterobacter	0.0005	0.0013	0.0002	0.0004	0.0050	0.37	0.83	0.92	0.38
g__Neisseria	0.0023	0.0044	0.0009	0.0013	0.0003	0.37	0.86	0.88	0.43
g__Adlercreutzia	0.0041	0.0076	0.0016	0.0021	0.0004	0.40	0.84	0.92	0.38
g__SMB53	0.0018	0.0029	0.0007	0.0007	0.0000	0.41	0.90	0.94	0.55
g__Parabacteroides	0.0118	0.0148	0.0049	0.0044	0.0000	0.41	0.84	0.90	0.42
g__Faecalibacterium	0.0269	0.0355	0.0544	0.0408	0.0000	2.02	0.90	0.91	0.58
g__Catenibacterium	0.0017	0.0032	0.0034	0.0038	0.0013	2.05	0.84	0.89	0.43
g__Roseburia	0.0021	0.0040	0.0049	0.0059	0.0027	2.30	0.87	0.91	0.57
g__Akkermansia	0.0205	0.0280	0.0566	0.0550	0.0000	2.76	0.91	0.94	0.62
g__Methanobrevibacter	0.0004	0.0009	0.0013	0.0017	0.0003	3.59	0.88	0.91	0.55
g__Clostridium	0.0016	0.0039	0.0065	0.0064	0.0000	4.08	0.90	0.91	0.60
g__Klebsiella	0.0024	0.0046	0.0103	0.0123	0.0000	4.30	0.94	0.91	0.72
g__Chryseobacterium	0.0006	0.0016	0.0026	0.0031	0.0000	4.33	0.88	0.91	0.53
g__Halomonas	0.0003	0.0007	0.0015	0.0031	0.0097	4.41	0.87	0.92	0.51
g__Aggregatibacter	0.0001	0.0004	0.0011	0.0025	0.0067	8.42	0.85	0.92	0.47
g__Rhodoplanes	0.0000	0.0002	0.0006	0.0014	0.0075	18.08	0.87	0.92	0.49
g__Thermoanaerobacterium	0.0002	0.0011	0.0033	0.0050	0.0000	20.92	0.91	0.95	0.57
g__Candidatus Koribacter	0.0000	0.0001	0.0007	0.0012	0.0002	45.87	0.90	0.94	0.55
g__Flexispira	0.0000	0.0000	0.0008	0.0019	0.0000		0.91	0.96	0.60

Example  5. Isolation from Urine of Patients with Prostatic Hyperplasia and Prostate Cancer Germ-derived  parcel Metagenome  Analysis-based Prostate Cancer Diagnosis Model

By the method of Example 3, the vesicles were isolated from the urine of 53 patients with prostate cancer and 55 patients with enlarged prostate gland, and 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.

As a result of analyzing the vesicle-derived vesicles in the urine at the phylum level, the diagnostic performance of prostate cancer was significant when developing a diagnostic model with Verrucomicrobia cultivars as a biomarker (see Table 7 and FIG. 7).

	Enlarged prostate		Prostate cancer		t-test
Taxon	Mean	SD	Mean	SD	p-value	Ratio	AUC	sensitivity	specificity
p__Verrucomicrobia	0.0286	0.0414	0.0588	0.0573	0.0023	2.06	0.85	0.84	0.83

Analysis of vesicle-derived vesicles in the urine at the class level showed significant diagnostic performance for prostate cancer when developing diagnostic models with more than one biomarker in Verrucomicrobiae, Acidimicrobiia, Saprospirae, and Pedosphaerae river bacteria. (See Table 8 and FIG. 8).

	Enlarged prostate		Prostate cancer		t-test
Taxon	Mean	SD	Mean	SD	p-value	Ratio	AUC	sensitivity	specificity
c__Verrucomicrobiae	0.0281	0.0405	0.0570	0.0561	0.0028	2.03	0.85	0.82	0.83
c__Acidimicrobiia	0.0002	0.0007	0.0009	0.0017	0.0086	3.97	0.84	0.75	0.77
c __ [Saprospirae]	0.0002	0.0005	0.0008	0.0011	0.0006	5.00	0.84	0.76	0.79
c __ [Pedosphaerae]	0.0002	0.0005	0.0010	0.0017	0.0009	6.03	0.85	0.78	0.81

At the order level of bacterial vesicles in urine, the diagnostic performance of prostate cancer was significant when developing a diagnostic model with one or more biomarkers in Verrucomicrobiales, Acidimicrobiales, Saprospirales, Pedosphaerales, and Ellin329 throat bacteria. (See Table 9 and FIG. 9).

	Enlarged prostate		Prostate cancer		t-test
Taxon	Mean	SD	Mean	SD	p-value	Ratio	AUC	sensitivity	specificity
o__Verrucomicrobiales	0.0281	0.0405	0.0570	0.0561	0.0028	2.03	0.85	0.82	0.83
o__Acidimicrobiales	0.0002	0.0007	0.0009	0.0017	0.0086	3.97	0.84	0.75	0.77
o __ [Saprospirales]	0.0002	0.0005	0.0008	0.0011	0.0006	5.00	0.84	0.76	0.79
o __ [Pedosphaerales]	0.0002	0.0005	0.0010	0.0017	0.0009	6.03	0.85	0.78	0.81
o__Ellin329	0.0001	0.0004	0.0012	0.0018	0.0001	14.59	0.87	0.85	0.77

Analysis of bacteria-derived vesicles in the urine at the family level revealed significant diagnostic performance for prostate cancer when developing a diagnostic model with more than one biomarker in Verrucomicrobiaceae, Chitinophagaceae, and Helicobacteraceae. 10 and FIG. 10).

	Enlarged prostate		Prostate cancer		t-test
Taxon	Mean	SD	Mean	SD	p-value	Ratio	AUC	sensitivity	specificity
f__Verrucomicrobiaceae	0.0281	0.0405	0.0570	0.0561	0.0028	2.03	0.85	0.82	0.83
f__Chitinophagaceae	0.0002	0.0005	0.0007	0.0010	0.0007	4.70	0.84	0.76	0.79
f__Helicobacteraceae	0.0001	0.0005	0.0009	0.0020	0.0070	6.76	0.83	0.73	0.79

Analysis of bacterial vesicles in the urine at genus level showed significant diagnostic performance for prostate cancer when a diagnostic model was developed with one or more biomarkers in the genus Ruminococcus, Akkermansia, and Flexispira. 11 and FIG. 11).

	Enlarged prostate		Prostate cancer		t-test
Taxon	Mean	SD	Mean	SD	p-value	Ratio	AUC	sensitivity	specificity
g__Ruminococcus	0.0292	0.0371	0.0129	0.0137	0.0035	0.44	0.84	0.78	0.83
g__Akkermansia	0.0280	0.0404	0.0566	0.0560	0.0031	2.02	0.85	0.82	0.83
g__Flexispira	0.0001	0.0004	0.0008	0.0019	0.0084	7.71	0.83	0.73	0.79

Example  6. Isolation from Urinary and Prostatic Hypertrophy Urine Germ-derived  parcel Metagenome  Analysis-based Prostatic Hyperplasia Diagnosis Model

By the method of Example 3, the vesicles were isolated from the urine of 55 prostate cancer patients and 159 normal people, 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 vesicle-derived vesicles in the urine at the phylum level revealed significant diagnostic performance for prostatic hyperplasia when developing a diagnostic model with one or more biomarkers in Euryarchaeota and Acidobacteria portal bacteria (Table 12 and 12).

	Normal people		Enlarged prostate		t-test
Taxon	Mean	SD	Mean	SD	p-value	fold	AUC	Accuracy	sensitivity	specificity
p__Euryarchaeota	0.0006	0.0013	0.0032	0.0064	0.0044	5.50	0.69	0.77	0.96	0.20
p__Acidobacteria	0.0005	0.0017	0.0023	0.0043	0.0032	4.61	0.69	0.77	0.98	0.15

The analysis of vesicle-derived vesicles in urine at the class level showed that diagnostic performance of prostatic hypertrophy was significant when Methanobacteria, Acidobacteria, and Acidobacteriia ganglia bacteria were developed with one or more biomarkers. 13 and FIG. 13).

	Normal people		Enlarged prostate		t-test
Taxon	Mean	SD	Mean	SD	p-value	fold	AUC	Accuracy	sensitivity	specificity
c__Methanobacteria	0.0006	0.0012	0.0032	0.0064	0.0042	5.68	0.69	0.77	0.96	0.20
c__Acidobacteria-6	0.0001	0.0003	0.0004	0.0009	0.0070	7.75	0.64	0.76	0.97	0.15
c__Acidobacteriia	0.0000	0.0002	0.0013	0.0029	0.0021	31.00	0.69	0.79	0.99	0.20

Analysis of urine-derived vesicles at the order level showed diagnostic performance of prostatic hyperplasia when one or more biomarkers were developed for stramenopiles, RF39, Saprospirales, Pseudomonadales, Methanobacteriales, and Acidobacteriales neck bacteria. This was significant (see Table 14 and Figure 14).

	Normal people		Enlarged prostate		t-test
Taxon	Mean	SD	Mean	SD	p-value	fold	AUC	Accuracy	sensitivity	specificity
o__Stramenopiles	0.0026	0.0059	0.0000	0.0000	0.0013	0.00	0.77	0.72	0.95	0.07
o__RF39	0.0023	0.0068	0.0006	0.0012	0.0027	0.26	0.65	0.75	0.98	0.07
o __ [Saprospirales]	0.0006	0.0016	0.0002	0.0005	0.0033	0.27	0.64	0.74	1.00	0.00
o__Pseudomonadales	0.1154	0.1282	0.0573	0.0344	0.0000	0.50	0.73	0.79	0.96	0.27
o__Methanobacteriales	0.0006	0.0012	0.0032	0.0064	0.0042	5.68	0.69	0.77	0.96	0.20
o__Acidobacteriales	0.0000	0.0002	0.0013	0.0029	0.0021	31.00	0.69	0.79	0.99	0.20

Family-level analysis of bacterial vesicles in urine revealed prostatic hyperplasia when one or more biomarkers were developed in Exiguobacteraceae, Flavobacteriaceae, Actinomycetaceae, Moraxellaceae, Ruminococcaceae, Rikenellaceae, Methanobacteriaceae, and Koribacteraceae. Diagnostic performance was significant (see Table 15 and FIG. 15).

	Normal people		Enlarged prostate		t-test
Taxon	Mean	SD	Mean	SD	p-value	fold	Auc	Accuracy	sensitivity	specificity
f __ [Exiguobacteraceae]	0.0019	0.0065	0.0001	0.0003	0.0008	0.05	0.66	0.74	1.00	0.00
f__Flavobacteriaceae	0.0019	0.0030	0.0004	0.0007	0.0000	0.20	0.70	0.75	0.99	0.05
f__Actinomycetaceae	0.0043	0.0102	0.0016	0.0020	0.0016	0.36	0.67	0.75	1.00	0.02
f__Moraxellaceae	0.0532	0.0884	0.0231	0.0187	0.0001	0.43	0.69	0.75	0.97	0.11
f__Ruminococcaceae	0.0867	0.0797	0.1921	0.1608	0.0000	2.22	0.75	0.80	0.98	0.27
f__Rikenellaceae	0.0016	0.0026	0.0062	0.0079	0.0001	3.97	0.79	0.79	0.96	0.31
f__Methanobacteriaceae	0.0006	0.0012	0.0032	0.0064	0.0042	5.68	0.69	0.77	0.96	0.20
f__Koribacteraceae	0.0000	0.0002	0.0013	0.0029	0.0022	40.87	0.69	0.79	0.99	0.20

Analysis of bacteria-derived vesicles in the urine at genus level showed that Rhizobium, Proteus, Acinetobacter, SMB53, Halomonas, Ruminococcus, Faecalibacterium, Klebsiella, Roseburia, Leuconostoc, Bilophila, Chromohalobacter, and Methanobrevibacter genus When the diagnostic model was developed, the diagnostic performance for prostatic hyperplasia was significant (see Table 16 and Figure 16).

	Normal people		Enlarged prostate		t-test
Taxon	Mean	SD	Mean	SD	p-value	fold	Auc	Accuracy	sensitivity	specificity
g__Rhizobium	0.0032	0.0050	0.0000	0.0000	0.0000	0.00	0.92	0.89	0.97	0.67
g__Proteus	0.0115	0.0202	0.0006	0.0010	0.0000	0.05	0.83	0.79	0.93	0.36
g__Acinetobacter	0.0431	0.0871	0.0113	0.0086	0.0000	0.26	0.71	0.75	0.96	0.15
g__SMB53	0.0018	0.0029	0.0005	0.0007	0.0000	0.30	0.70	0.75	0.97	0.11
g__Halomonas	0.0003	0.0007	0.0010	0.0016	0.0050	2.90	0.68	0.76	0.97	0.16
g__Ruminococcus	0.0098	0.0156	0.0292	0.0371	0.0004	2.98	0.69	0.78	0.98	0.20
g__Faecalibacterium	0.0269	0.0355	0.0813	0.0841	0.0000	3.02	0.73	0.81	0.99	0.31
g__Klebsiella	0.0024	0.0046	0.0075	0.0086	0.0001	3.14	0.80	0.78	0.96	0.25
g__Roseburia	0.0021	0.0040	0.0085	0.0085	0.0000	4.04	0.81	0.79	0.94	0.35
g__Leuconostoc	0.0003	0.0007	0.0011	0.0019	0.0017	4.28	0.68	0.78	0.98	0.20
g__Bilophila	0.0002	0.0008	0.0009	0.0018	0.0064	4.29	0.70	0.77	0.99	0.13
g__Chromohalobacter	0.0001	0.0006	0.0006	0.0012	0.0066	5.06	0.67	0.77	0.99	0.13
g__Methanobrevibacter	0.0004	0.0009	0.0028	0.0063	0.0067	7.55	0.68	0.78	0.96	0.25

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.

Predicting the risk of developing prostate cancer and prostatic hyperplasia through metagenomic analysis on genes present in bacteria-derived extracellular vesicles using a human-derived sample according to the present invention, by early diagnosis and prediction of risk groups of prostate disease, appropriate management It can delay the onset or prevent the onset of the disease, and can be diagnosed early after the enlargement of the prostate or prostate cancer, thereby reducing the incidence of prostate disease and improving the treatment effect.

Claims (14)

1. (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 bacterial-derived extracellular vesicles in the sample derived from normal and prostate cancer patients by sequencing the PCR product; or

   Comparing the increase or decrease of bacterial extracellular vesicles in the sample from the prostatic hyperplasia and the prostate cancer patient by sequencing the PCR product; or

   Comparing the increase and decrease of the content of the bacteria-derived extracellular vesicles in the sample derived from normal and prostatic hypertrophy patients by sequencing the PCR product, Information providing method for diagnosing prostate disease.
2. The method of claim 1,

   In the step (c), prostate cancer diagnosis, characterized in that to diagnose the prostate cancer through the step of comparing the increase and decrease of the bacterial-derived extracellular vesicles in the sample derived from normal people and prostate cancer patients by sequencing the PCR product How to Provide Information.
3. The method of claim 2,

   In the step (c), the group consisting of Tenericutes, Euryarchaeota, Vermicobacteria, Verrucomicrobia, Gemmatimonadetes, Acidobacteria, and Planctomycetes One or more phylum bacteria-derived extracellular vesicles selected from

   Mollicutes, Methanobacteria, Verrucomicrobiae, Acidimicrobiia, Spartobacteria, Acidobacteria-6, Gemmamati One or more class bacterial-derived extracellular vesicles selected from the group consisting of Gemmatimonadetes, Acidobacteriia, Pedosphaerae, and Saprospirae,

   Stramenopiles, Alteromonadales, Rickettsiales, Neisseriales, Methanobacteriales, Verrucomicrobiales, Myxococcales, Acidimicrobiales, Chthoniobacterales, Acidobacteriales, Pedosphaerales, Saprospirales, Pseudomonadales, RF39 at least one order bacterial derived extracellular vesicle selected from the group consisting of iii1-15, and Ellin329,

   Peptocococaceae, Exiguobacteraceae, Actinomycetaceae, Cellulomonadaceae, Mitochondria, Fusobacteriaceae, Porphyromonaroaceae ), Flavobacteriaceae, Moraxellaceae, Neisseriaceae, Metanobacteriaceae, Verrucomicrobiaceae, Rikenellaaceae, Wickelacie (Weeksellaceae), Streptomycetaceae, Helicobacter, Chthoniobacteraceae, Koribacteraceae Chitinophagaceae, Ruminococcaceae, and Sino24cc. Extracellular vesicles derived from one or more family bacteria selected from the group consisting of -7, or

   Rhizobium, Teteragenococcus, Proteus, Morganella, Exiguobacterium, Orribacterium, Bacteroides, Actinomycetes (Actinomyces), Cellulomonas, Jeotgalicoccus, Acinetobacter, Fusobacterium, Enterobacter, Neisseria, Adlercrechia Adlercreutzia, Parabacteroides, Facalcalibacterium, Catenibacterium, Roseburia, Akkermansia, Metanobrevibacter, Clostridium, Klebsiella, Chryseobacterium, Halomonas, Aggregatibacter, Rhodoplanes, Thermoanaerobacterium ), Khan Consist of Candidatus Koribacter, Flexispira, Luminococcus, Leuconostoc, Bilophila, Chromohalobacter, and SMB53 Comparing the increase or decrease of the content of one or more genus bacteria-derived extracellular vesicles selected from the group, Information providing method for diagnosing prostate disease.
4. The method of claim 1,

   In the step (c), prostate disease, characterized in that by comparing the increase or decrease in the content of bacterial-derived extracellular vesicles in the sample from the prostatic hyperplasia patients and prostate cancer patients by sequencing the PCR product, prostate disease How to provide information for diagnosis.
5. The method of claim 4, wherein

   In the step (c), the group consisting of Tenericutes, Euryarchaeota, Vermicobacteria, Verrucomicrobia, Gemmatimonadetes, Acidobacteria, and Planctomycetes One or more phylum bacteria-derived extracellular vesicles selected from

   Mollicutes, Methanobacteria, Verrucomicrobiae, Acidimicrobiia, Spartobacteria, Acidobacteria-6, Gemmamati One or more class bacterial-derived extracellular vesicles selected from the group consisting of Gemmatimonadetes, Acidobacteriia, Pedosphaerae, and Saprospirae,

   Stramenopiles, Alteromonadales, Rickettsiales, Neisseriales, Methanobacteriales, Verrucomicrobiales, Myxococcales, Acidimicrobiales, Chthoniobacterales, Acidobacteriales, Pedosphaerales, Saprospirales, Pseudomonadales, RF39 at least one order bacterial derived extracellular vesicle selected from the group consisting of iii1-15, and Ellin329,

   Peptocococaceae, Exiguobacteraceae, Actinomycetaceae, Cellulomonadaceae, Mitochondria, Fusobacteriaceae, Porphyromonaroaceae ), Flavobacteriaceae, Moraxellaceae, Neisseriaceae, Metanobacteriaceae, Verrucomicrobiaceae, Rikenellaaceae, Wickelacie (Weeksellaceae), Streptomycetaceae, Helicobacter, Chthoniobacteraceae, Koribacteraceae Chitinophagaceae, Ruminococcaceae, and Sino24cc. Extracellular vesicles derived from one or more family bacteria selected from the group consisting of -7, or

   Rhizobium, Teteragenococcus, Proteus, Morganella, Exiguobacterium, Orribacterium, Bacteroides, Actinomycetes (Actinomyces), Cellulomonas, Jeotgalicoccus, Acinetobacter, Fusobacterium, Enterobacter, Neisseria, Adlercrechia Adlercreutzia, Parabacteroides, Facalcalibacterium, Catenibacterium, Roseburia, Akkermansia, Metanobrevibacter, Clostridium, Klebsiella, Chryseobacterium, Halomonas, Aggregatibacter, Rhodoplanes, Thermoanaerobacterium ), Khan Consist of Candidatus Koribacter, Flexispira, Luminococcus, Leuconostoc, Bilophila, Chromohalobacter, and SMB53 Comparing the increase or decrease of the content of one or more genus bacteria-derived extracellular vesicles selected from the group, Information providing method for diagnosing prostate disease.
6. The method of claim 1,

   In the step (c), prostate disease diagnosis, characterized in that to diagnose the prostate hyperplasia by comparing the increase and decrease in the content of bacteria-derived extracellular vesicles in the sample derived from normal and prostatic hyperplasia patients by sequencing PCR products How to Provide Information.
7. The method of claim 6,

   In the step (c), the group consisting of Tenericutes, Euryarchaeota, Vermicobacteria, Verrucomicrobia, Gemmatimonadetes, Acidobacteria, and Planctomycetes One or more phylum bacteria-derived extracellular vesicles selected from

   Mollicutes, Methanobacteria, Verrucomicrobiae, Acidimicrobiia, Spartobacteria, Acidobacteria-6, Gemmamati One or more class bacterial-derived extracellular vesicles selected from the group consisting of Gemmatimonadetes, Acidobacteriia, Pedosphaerae, and Saprospirae,

   Stramenopiles, Alteromonadales, Rickettsiales, Neisseriales, Methanobacteriales, Verrucomicrobiales, Myxococcales, Acidimicrobiales, Chthoniobacterales, Acidobacteriales, Pedosphaerales, Saprospirales, Pseudomonadales, RF39 at least one order bacterial derived extracellular vesicle selected from the group consisting of iii1-15, and Ellin329,

   Peptocococaceae, Exiguobacteraceae, Actinomycetaceae, Cellulomonadaceae, Mitochondria, Fusobacteriaceae, Porphyromonaroaceae ), Flavobacteriaceae, Moraxellaceae, Neisseriaceae, Metanobacteriaceae, Verrucomicrobiaceae, Rikenellaaceae, Wickelacie (Weeksellaceae), Streptomycetaceae, Helicobacter, Chthoniobacteraceae, Koribacteraceae Chitinophagaceae, Ruminococcaceae, and Sino24cc. Extracellular vesicles derived from one or more family bacteria selected from the group consisting of -7, or

   Rhizobium, Teteragenococcus, Proteus, Morganella, Exiguobacterium, Orribacterium, Bacteroides, Actinomycetes (Actinomyces), Cellulomonas, Jeotgalicoccus, Acinetobacter, Fusobacterium, Enterobacter, Neisseria, Adlercrechia Adlercreutzia, Parabacteroides, Facalcalibacterium, Catenibacterium, Roseburia, Akkermansia, Metanobrevibacter, Clostridium, Klebsiella, Chryseobacterium, Halomonas, Aggregatibacter, Rhodoplanes, Thermoanaerobacterium ), Khan Consist of Candidatus Koribacter, Flexispira, Luminococcus, Leuconostoc, Bilophila, Chromohalobacter, and SMB53 Comparing the increase or decrease of the content of one or more genus bacteria-derived extracellular vesicles selected from the group, Information providing method for diagnosing prostate disease.
8. (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 bacterial-derived extracellular vesicles in the sample derived from normal and prostate cancer patients by sequencing the PCR product; or

   Comparing the increase or decrease of bacterial extracellular vesicles in the sample from the prostatic hyperplasia and the prostate cancer patient by sequencing the PCR product; or

   Comprising the step of comparing the increase and decrease of the content of bacteria-derived extracellular vesicles in the sample derived from normal and prostatic hyperplasia patients by sequencing the PCR product.
9. The method of claim 8,

   In the step (c), prostate cancer diagnosis method, characterized in that the prostate cancer through the step of comparing the increase and decrease of the bacterial-derived extracellular vesicle content in the sample derived from normal people and prostate cancer patients by sequencing PCR products .
10. The method of claim 9,

    In the step (c), the group consisting of Tenericutes, Euryarchaeota, Vermicobacteria, Verrucomicrobia, Gemmatimonadetes, Acidobacteria, and Planctomycetes One or more phylum bacteria-derived extracellular vesicles selected from

    Mollicutes, Methanobacteria, Verrucomicrobiae, Acidimicrobiia, Spartobacteria, Acidobacteria-6, Gemmamati One or more class bacterial-derived extracellular vesicles selected from the group consisting of Gemmatimonadetes, Acidobacteriia, Pedosphaerae, and Saprospirae,

    Stramenopiles, Alteromonadales, Rickettsiales, Neisseriales, Methanobacteriales, Verrucomicrobiales, Myxococcales, Acidimicrobiales, Chthoniobacterales, Acidobacteriales, Pedosphaerales, Saprospirales, Pseudomonadales, RF39 at least one order bacterial derived extracellular vesicle selected from the group consisting of iii1-15, and Ellin329,

    Peptocococaceae, Exiguobacteraceae, Actinomycetaceae, Cellulomonadaceae, Mitochondria, Fusobacteriaceae, Porphyromonaroaceae ), Flavobacteriaceae, Moraxellaceae, Neisseriaceae, Metanobacteriaceae, Verrucomicrobiaceae, Rikenellaaceae, Wickelacie (Weeksellaceae), Streptomycetaceae, Helicobacter, Chthoniobacteraceae, Koribacteraceae Chitinophagaceae, Ruminococcaceae, and Sino24cc. Extracellular vesicles derived from one or more family bacteria selected from the group consisting of -7, or

    Rhizobium, Teteragenococcus, Proteus, Morganella, Exiguobacterium, Orribacterium, Bacteroides, Actinomycetes (Actinomyces), Cellulomonas, Jeotgalicoccus, Acinetobacter, Fusobacterium, Enterobacter, Neisseria, Adlercrechia Adlercreutzia, Parabacteroides, Facalcalibacterium, Catenibacterium, Roseburia, Akkermansia, Metanobrevibacter, Clostridium, Klebsiella, Chryseobacterium, Halomonas, Aggregatibacter, Rhodoplanes, Thermoanaerobacterium ), Khan Consist of Candidatus Koribacter, Flexispira, Luminococcus, Leuconostoc, Bilophila, Chromohalobacter, and SMB53 A method for diagnosing prostate disease, characterized by comparing the increase or decrease of the content of one or more genus bacteria-derived extracellular vesicles selected from the group.
11. The method of claim 8,

    In the step (c), prostate disease, characterized in that by comparing the increase or decrease in the content of bacterial-derived extracellular vesicles in the sample from the prostatic hyperplasia patients and prostate cancer patients by sequencing the PCR product, prostate disease Diagnostic method.
12. The method of claim 11,

    In the step (c), the group consisting of Tenericutes, Euryarchaeota, Vermicobacteria, Verrucomicrobia, Gemmatimonadetes, Acidobacteria, and Planctomycetes One or more phylum bacteria-derived extracellular vesicles selected from

    Mollicutes, Methanobacteria, Verrucomicrobiae, Acidimicrobiia, Spartobacteria, Acidobacteria-6, Gemmamati One or more class bacterial-derived extracellular vesicles selected from the group consisting of Gemmatimonadetes, Acidobacteriia, Pedosphaerae, and Saprospirae,

    Stramenopiles, Alteromonadales, Rickettsiales, Neisseriales, Methanobacteriales, Verrucomicrobiales, Myxococcales, Acidimicrobiales, Chthoniobacterales, Acidobacteriales, Pedosphaerales, Saprospirales, Pseudomonadales, RF39 at least one order bacterial derived extracellular vesicle selected from the group consisting of iii1-15, and Ellin329,

    Peptocococaceae, Exiguobacteraceae, Actinomycetaceae, Cellulomonadaceae, Mitochondria, Fusobacteriaceae, Porphyromonaroaceae ), Flavobacteriaceae, Moraxellaceae, Neisseriaceae, Metanobacteriaceae, Verrucomicrobiaceae, Rikenellaaceae, Wickelacie (Weeksellaceae), Streptomycetaceae, Helicobacter, Chthoniobacteraceae, Koribacteraceae Chitinophagaceae, Ruminococcaceae, and Sino24cc. Extracellular vesicles derived from one or more family bacteria selected from the group consisting of -7, or

    Rhizobium, Teteragenococcus, Proteus, Morganella, Exiguobacterium, Orribacterium, Bacteroides, Actinomycetes (Actinomyces), Cellulomonas, Jeotgalicoccus, Acinetobacter, Fusobacterium, Enterobacter, Neisseria, Adlercrechia Adlercreutzia, Parabacteroides, Facalcalibacterium, Catenibacterium, Roseburia, Akkermansia, Metanobrevibacter, Clostridium, Klebsiella, Chryseobacterium, Halomonas, Aggregatibacter, Rhodoplanes, Thermoanaerobacterium ), Khan Consist of Candidatus Koribacter, Flexispira, Luminococcus, Leuconostoc, Bilophila, Chromohalobacter, and SMB53 A method for diagnosing prostate disease, characterized by comparing the increase or decrease of the content of one or more genus bacteria-derived extracellular vesicles selected from the group.
13. The method of claim 8,

    In step (c), the prostate disease diagnosis method, characterized in that to diagnose the prostate hyperplasia by comparing the increase and decrease of the content of bacteria-derived extracellular vesicles in the sample derived from normal and prostatic hyperplasia patients by sequencing PCR products .
14. The method of claim 13,

    In the step (c), the group consisting of Tenericutes, Euryarchaeota, Vermicobacteria, Verrucomicrobia, Gemmatimonadetes, Acidobacteria, and Planctomycetes One or more phylum bacteria-derived extracellular vesicles selected from

    Mollicutes, Methanobacteria, Verrucomicrobiae, Acidimicrobiia, Spartobacteria, Acidobacteria-6, Gemmamati One or more class bacterial-derived extracellular vesicles selected from the group consisting of Gemmatimonadetes, Acidobacteriia, Pedosphaerae, and Saprospirae,

    Stramenopiles, Alteromonadales, Rickettsiales, Neisseriales, Methanobacteriales, Verrucomicrobiales, Myxococcales, Acidimicrobiales, Chthoniobacterales, Acidobacteriales, Pedosphaerales, Saprospirales, Pseudomonadales, RF39 at least one order bacterial derived extracellular vesicle selected from the group consisting of iii1-15, and Ellin329,

    Peptocococaceae, Exiguobacteraceae, Actinomycetaceae, Cellulomonadaceae, Mitochondria, Fusobacteriaceae, Porphyromonaroaceae ), Flavobacteriaceae, Moraxellaceae, Neisseriaceae, Metanobacteriaceae, Verrucomicrobiaceae, Rikenellaaceae, Wickelacie (Weeksellaceae), Streptomycetaceae, Helicobacter, Chthoniobacteraceae, Koribacteraceae Chitinophagaceae, Ruminococcaceae, and Sino24cc. Extracellular vesicles derived from one or more family bacteria selected from the group consisting of -7, or

    Rhizobium, Teteragenococcus, Proteus, Morganella, Exiguobacterium, Orribacterium, Bacteroides, Actinomycetes (Actinomyces), Cellulomonas, Jeotgalicoccus, Acinetobacter, Fusobacterium, Enterobacter, Neisseria, Adlercrechia Adlercreutzia, Parabacteroides, Facalcalibacterium, Catenibacterium, Roseburia, Akkermansia, Metanobrevibacter, Clostridium, Klebsiella, Chryseobacterium, Halomonas, Aggregatibacter, Rhodoplanes, Thermoanaerobacterium ), Khan Consist of Candidatus Koribacter, Flexispira, Luminococcus, Leuconostoc, Bilophila, Chromohalobacter, and SMB53 A method for diagnosing prostate disease, characterized by comparing the increase or decrease of the content of one or more genus bacteria-derived extracellular vesicles selected from the group.

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