COMPOSITION CONTAINING INTRAVAGINAL MICROORGANISMS

Abstract

The present invention relates to a biomarker of predicting or diagnosing female genital disease or obesity. More specifically, the present invention relates to a composition for predicting or diagnosing risk of female genital disease or obesity, including detecting Prevotella spp., Sneathia spp. Megasphaera spp., Gardnerella spp., and Lactobacillus spp.

Claims

1. A composition for predicting or diagnosing presence or risk of female genital diseases or female obesity, comprising a detectable agent of at least a vaginal microorganism selected from the group consisting of Prevotella spp., Sneathia spp. Megasphaera spp., Gardnerella spp., and Lactobacillus spp.

2. The composition according to claim 1, wherein the female genital diseases are at least one selected from vaginitis, menopause, cervical inflammation and cervical cancer.

3. The composition according to claim 1, wherein the detectable agent of microorganism is a primer, a probe, an antisense oligonucleotide, an aptamer or an antibody which is specific to the microorganism.

4. A kit for predicting or diagnosing risk of female genital diseases or female obesity, using a vaginal microorganism, comprising a composition of claim 1.

5. The kit according to claim 4, wherein the kit is applied to a sample collected from the vagina of a subject.

6. The kit according to claim 5, wherein the sample collected from the vagina is vaginal secretion or amniotic fluid.

7. The kit according to claim 6, wherein the vaginal secretion is obtained from vagina or cervix.

8. The kit according to claim 6, wherein the kit further comprises a sample collection device for taking a sample from an vaginal secretion or an amniotic fluid of a subject, and the sample collection device is selected from the group consisting of a brush, an absorbent pad, a swab, a syringe, a spoon, and an amniotic fluid collector.

9. A method of prediction or diagnosis of presence or risk of female genital diseases or female obesity, comprising a step of detecting at least a vaginal microorganism selected from the group consisting of Prevotella spp., Sneathia spp. Megasphaera spp., Gardnerella spp., and Lactobacillus spp.

10. The method according to claim 9, wherein the method comprises the steps of: (a) collecting test sample in the vagina of the subject; (b) extracting genomic DNA from the sample (c) reacting the extracted genomic DNA with a specific primer to at least a vaginal microorganism selected from the group consisting of Prevotella spp., Sneathia spp. Megasphaera spp., Gardnerella spp., and Lactobacillus spp. and (d) amplifying the reaction product.

11. The method according to claim 10, wherein the sample collected from the vagina is vaginal secretion or amniotic fluid.

12. The method according to claim 10, further comprising step (e) of comparing the amplification product amount of the genomic DNA of the sample with the amplification product amount of the normal control sample, after step (d).

13. The method according to claim 12, wherein the presence of occurrence or risk of female genital diseases is determined, when the amplification product amount of at least a vaginal microorganism selected from the group consisting of Prevotella spp., Sneathia spp. Megasphaera spp. and Gardnerella spp. in a test sample is higher than that of normal control sample.

14. The method according to claim 12, wherein the presence of occurrence or risk of female genital diseases is determined, when the amplification product amount of Lactobacillus spp. in a test sample is lower than that of normal control sample.

15. A method of screening a prophylactic or therapeutic agent for female genital diseases or female obesity, comprising: treating with a candidate substance for the therapeutic or prophylactic agent, detecting change in at least a vaginal microorganism selected from the group consisting of Prevotella spp., Sneathia spp. Megasphaera spp., Gardnerella spp. and Lactobacillus spp. in samples obtained from vagina before and after treating with a candidate substance, and determining the candidate substance as a therapeutic or prophylactic agent, when the detecting amount of at least a vaginal microorganism selected from the group consisting of Prevotella spp., Sneathia spp. Megasphaera spp., and Gardnerella spp. in a test sample decreases, or the detecting amount of Lactobacillus spp. increase, after treating with a candidate substance.

16-29. (canceled)

30. The kit according to claim 4, wherein the female genital diseases are at least one selected from vaginitis, menopause, cervical inflammation and cervical cancer.

31. The kit according to claim 4, wherein the detectable agent of microorganism is a primer, a probe, an antisense oligonucleotide, an aptamer or an antibody which is specific to the microorganism.

32. The method according to claim 11, wherein the sample collected from the vagina is vaginal secretion or amniotic fluid.

Description

BRIEF DESCRIPTION OF DRAWINGS

[0050] FIG. 1 shows the change in the distribution of vaginal microflora according to pre-menopausal/post-menopause, vaginitis (BV), cervical inflammation (Cervicits), cervical cancer (HPV) and obesity (BMI>30), on the basis of 16S rRNA-based analysis.

[0051] FIG. 2 shows NMDS plots of clinical indices that can significantly change the structure of microbiota in vagina.

[0052] FIG. 3 shows the result of evaluating the diversity of vaginal flora in obesity in pre-menopausal and post-menopausal vagina.

[0053] FIG. 4 shows the change in specific vaginal bacteria according to menopausal status.

[0054] FIG. 5 shows the change in specific vaginal bacteria according to vaginitis infection.

[0055] FIG. 6 shows the change in specific vaginal bacteria according to obesity.

[0056] FIG. 7 shows the change in specific vaginal bacteria according to the treatment of female hormone.

[0057] FIG. 8 shows the change in specific vaginal bacteria according to cervical cancer.

[0058] FIG. 9 shows the result confirming the occurrence pattern of vaginal microflora in the pre-menopausal vagina using SparCC software.

[0059] FIG. 10 shows the result confirming the occurrence pattern of vaginal microflora in post-menopausal vagina using SparCC software.

[0060] FIG. 11 shows the result of analyzing the diversity in the vaginal microflora of the rats fed the normal diet and the obese rats fed the high-fat diet.

[0061] FIG. 12 shows the result of univariate analysis of vaginal microflora according to the diet.

[0062] FIG. 13 shows the change in the blood lipopolysaccharide of the rats fed with a normal diet, which was administered by the vaginal microflora obtained from the rats fed with high-fat diet.

MODE OF INVENTION

[0063] Hereinafter, the present invention will be described in detail with reference to examples. However, the following examples illustrate the present invention, and the present invention is not limited by the following examples.

Example 1. Study Subject and Sample Collection

[0064] For the present invention, samples in the endocervix were collected with brush from 542 female identical tweens sand fraternal twins from Korean tween cohorts, and their families, and stored in a frozen state at 80 C. degrees. The cryopreserved samples were transferred to the laboratory and genomic DNA was extracted using a kit.

Example 2. Analysis of Vaginal Microflora Using 16S rRNA

[0065] The genomic DNA extracted from Example 1 was amplified using the 515F/806R primers (SEQ ID NOs: 1 and 2) shown in Table 1, targeting the V4 region of the bacteria, and followed by nucleotide sequence data using Illumina's MiSeq instrument.

TABLE-US-00002 TABLE2 SEQ ID Item NO Nucleotidesequence Forward 1 5-AATGATACGGCGACCACCGAGATCTACACTATGGT primer AATTGTGTGCCAGCMGCCGCGGTAA-3 Reverse 2 5-CAAGCAGAAGACGGCATACGAGATAGTCAGTCAGC primer CGGACTACHVGGGTWTCTAAT-3

[0066] By using the QIIME pipeline, the analysis of nucleotide sequence data were performed to confirm the genetic information and the structure of vaginal microflora, and then the relationship between the vaginal microflora and the various female health markers were observed.

[0067] The vaginal microflora information obtained by 16S rRNA-based analysis confirms the changes in the vaginal microflora according to menopausal status, vaginitis, cervical inflammation, cervical cancer and obesity. The results are shown in FIG. 1. As a result of analyzing the association of factors, it was confirmed that clinical indicators that can significantly change the structure of the vesicles in vagina were menopause, vaginitis, and obesity (FIG. 2). As a result of analyzing the correlation of indicators affecting health with the vaginal microflora by using NMDS plots, the clinical indictors that can significantly change the structure of microbiota in vagina were post-menopausal status, vaginitis infection, and obesity (FIG. 2) In addition, it was confirmed that the obesity increased the diversity vaginal microflora (FIG. 3). That suggests that the harmful vaginal microorganisms induced by the obesity may have a negative influence on female genital health, by considering that the beneficial bacteria, Lactobacillus is dominant species in the vaginal microflora.

Example 3. Analysis of Correlation Between Vaginal Microflora and Female Genital Diseases or Obesity

[0068] The result of multivariate analysis with MaAsLin software, which can control confounding variables, vaginal bacteria identifying female genital diseases or obesity was defined.

[0069] Using the MaAsLin software, the twin and family relationships were assigned as random variables and other health factors as calibration variables, and the correlation between each health factor and vaginal microflora was analyzed. The results are shown in FIGS. 4 to 8.

[0070] As can be seen from FIGS. 4, 5 and 8, it was found that Prevotella spp. was highest correlation with the female genital diseases, especially menopause, vaginitis and cervical cancer. In the case of obesity, P. copri, one of the species of Prevotella spp. was found to be the secondly-high correlation to the obesity (FIG. 6).

[0071] Besides the post-menopausal status, vaginitis infection, and obesity showing the significant correlation in NMDS plot, the female hormone therapy had a negative correlation (r correlation coefficient=0.004, q-value: 0.18) (FIG. 7) and HPV infection had a positive correlation (r correlation coefficient=0.1, q-value: 0.16).

Example 4. Network Analysis of Vaginal Microflora

[0072] The network analysis was performed using Sparse Correlations for Compositional Data (SparCC) software to determine the pattern of occurrence of vaginal microflora in female genital or obesity groups and normal groups.

[0073] As a result, the inter-relationship between vaginal microflora was observed through additional network analysis. It was found that Prevotella spp. was highest correlation with Lactobacillus spp. in both pre-menopausal (FIG. 9) and post-menopausal (FIG. 10).

Example 5. Animal Experiments to Confirm the Relationship Between Female Vaginal Microflora and Obesity

[0074] Animal experiments were conducted to investigate the relationship between obesity and female vaginal microflora. Six week old C57BL/6J rats were fed high fat diets for 12 weeks and the vaginal microflora were analyzed.

[0075] Analysis of vaginal microflora in obese rats fed with high-fat diets resulted in increased diversity of vaginal microflora (FIG. 11). Specifically, the univariate analysis of vaginal microflora depending on the diet showed that the Gram-negative bacteria, Prevotella spp., Sneathia spp. Megasphaera spp. and Gardnerella spp. which are known as the harmful group to the human vaginal environment have been significantly increased (FIG. 12).

[0076] In addition, in order to investigate the effect of the obesity-altered vaginal microflora on the host, the vaginal microflora of obese rats fed with high fat diet were obtained and administered five times into the vagina of normal rats fed with general diet. The blood was obtained from the administered normal rats and was measured for the lipopolysaccharide constituting the cell wall of Gram-negative bacteria to show the result in FIG. 13. As a result, the lipopolysaccharide was significantly increased in the blood of the normal rats administered by the vaginal microflora of obese rats fed with high fat diet. This suggests that Gram-negative organisms induced by obesity may have deleterious effects on the whole body.