CN112951326A

CN112951326A - Bacterial dominance network triangle motif for risk prediction, diagnosis, personalized treatment and post-cure monitoring of bacterial vaginitis

Info

Publication number: CN112951326A
Application number: CN201911299315.XA
Authority: CN
Inventors: 马占山; 埃伦·M·埃里森
Original assignee: Kunming Institute of Zoology of CAS
Current assignee: Kunming Institute of Zoology of CAS
Priority date: 2019-12-11
Filing date: 2019-12-11
Publication date: 2021-06-11

Abstract

The invention relates to the fields of bioinformatics technology and medical health, and discloses a network triangular motif (trio motif) consisting of vaginal Bacteria and application thereof, aiming at personalized risk assessment, accurate diagnosis, treatment and post-cure (re-diagnosis monitoring) of female Bacterial Vaginitis (BV). Based on the dominance network analysis framework, the inventors analyzed the vaginal microbial flora aligned to healthy individuals and BV patients, and screened fifteen specific bacterial network triangle motifs of BV patients, twelve of which were specific to "symptomatic BV" (symptomatic BV) patients and the other three of which were present in both "symptomatic" and "asymptomatic BV" (asymptomatic BV). Each network motif consists of three vaginal bacterial species linked by a specific interaction relationship. The network triangle motif formed by the vaginal bacteria can be used for diagnosing and evaluating risks of BV, and provides a brand new target point for personalized accurate treatment and post-cure monitoring of BV.

Description

Bacterial dominance network triangle motif for risk prediction, diagnosis, personalized treatment and post-cure monitoring of bacterial vaginitis

Technical Field

The invention relates to the fields of bioinformatics technology and medical health, in particular to a network triangle motif consisting of vaginal bacteria and application of the motif in risk assessment, accurate diagnosis, personalized treatment and post-cure review monitoring of female bacterial vaginitis.

Background

Bacterial Vaginosis (BV) is a highly progressive vaginal disease affecting 20-40% of women. It is associated with genital tract infections and many pregnancy complications, such as pelvic inflammatory disease, premature rupture of membranes, intrauterine fetal death, chorioamnionitis, endometritis, premature birth, postpartum infection, ectopic pregnancy, etc. Starting in the late 90 s of the 20 th century, clinical microbiologists studied vaginal microorganisms using microbial culture technology (only a limited number of bacteria can be cultured and identified) and applied ecological theories and methods (especially community diversity-stability relationships and species dominance) to explain the etiology of BV. The advent of metagenomics has enabled researchers to study vaginal microflora and those microorganisms that cannot be cultured therein on a large scale, providing a more systematic and comprehensive understanding of BV.

Much of the research on BV has focused on a single or several pathogens, such as Gardnerella or some gram-negative coccobacillus, which are both diagnostic and therapeutic targets. In addition, studies have shown that the absence of the dominant species of lactobacilli (particularly the species Lactobacillus iners) in the vaginal flora is a significant cause of BV. However, some BV patients do not have high abundance of Gardnerella in the genital flora while the Lactobacillus content is still quite abundant. Studies have also shown that the causative cause of BV is closely related to loss of vaginal flora stability, in addition to increased or decreased abundance of certain bacteria. Therefore, there is no clear theory on the pathogenesis of BV, and a treatment strategy targeting individual species often fails to completely eradicate BV, and there is still a high risk of relapse when the resistance in physiological cycles is low. In addition, there is no more complete system for risk assessment and post-cure monitoring for BV.

The dominance degree interaction network is an emerging analysis technology for researching ecological stability of the community in recent years, triangular motifs are basic elements formed by the network, and in the flora network, some triangular motifs are more closely related to the function of the community. The invention aims to search a specific network triangle motif of a BV patient based on a vaginal flora dominance interaction network, and provides a theoretical basis and a possible biological target for risk prediction, accurate diagnosis, personalized treatment and post-cure review monitoring of BV.

Disclosure of Invention

The invention aims to:

based on the dominance degree interaction network analysis technology, a specific bacterial network triangular motif of a BV patient is searched, and a theoretical basis and possible biological targets are provided for BV risk prediction, accurate diagnosis, personalized treatment and post-cure review monitoring

In order to achieve the purpose, the technical scheme of the invention is as follows:

by utilizing the female vaginal microbial flora data reported for the first time in 2013 by Ravel et al, an advantage network is constructed for the vaginal flora of healthy females, asymptomatic BV patients and symptomatic BV patients respectively by an advantage network analysis technology. Second, based on triangle motif analysis techniques and intertriad motif comparisons, 15 bacterial network triangle motifs specific to BV patients were selected, 12 of which were specific to symptomatic BV patients (motif numbers 1-12) and 3 of which were present in both symptomatic and asymptomatic BV patients (motif numbers 13-15). Each network triangle motif is formed by three vaginal bacteria connected through specific interaction relationship, and the specific information is shown in table 1.

TABLE 1 bacterial network triangle motifs specific to a class of BV patients

The invention has the following effects:

provides a special vaginal bacterial network triangle motif of BV patients, and the motif can provide a brand-new biological target and reliable theoretical support for risk assessment, accurate diagnosis, personalized treatment and post-cure review monitoring of BV.

Drawings

FIG. 1 is a flow chart of an embodiment of the method of the present invention.

Detailed Description

The present invention will be further described with reference to the following examples, but is not limited thereto.

Data source

The invention is based on the 16S rRNA data of the female vaginal microbial flora first reported by Ravel et al in 2013, which is collected from 25 females, including 15 symptomatic BV patients, 6 asymptomatic BV patients and 4 healthy females. Each person was sampled for 10 weeks continuously, and 67 flora samples were collected on average from each person. A sequencing platform is utilized to obtain 16S rRNA fragments, and subsequent bioinformatics analysis is utilized to obtain 97% similarity microbial classification operation units (OTUs), wherein each OTU represents a bacterial species in the patent.

Dominance network and triangle motif analysis technology

The dominance index of the species level was calculated by applying the dominance index invented by the inventor in 2017 (patent acceptance number: 201710063855.2) and applying the following formula.

Wherein the content of the first and second substances,

m_crepresents the average of the Abundance (Abundance) of all species in a microbial sample,

for the corresponding variance, m_sIs a multiple of each microbial species. And calculating Spearman correlation based on the index, and selecting statistically significant correlation (p is less than or equal to 0.05) to construct an dominance interaction network. A method (patent number: 201611126939.8) invented by the inventor 2016 for analyzing and evaluating the health of organisms and diagnosing diseases based on a human flora interaction network is used for searching dominant interaction networks of vaginal flora of healthy women, asymptomatic BV patients and symptomatic BV patients respectively, and determining special triangular motifs in the networks. By comparing network motifs of three groups of healthy women, asymptomatic BV patients, and symptomatic BV patients, it was found that 12 triangular motifs occur in more than half of the symptomatic BV patients, but not in healthy women and asymptomatic BV patients, and that 12 motifs were numbered 1 to 12 (as shown in table 1). In addition, 3 trigonal motifs were found to occur in more than 50% of patients with BV (including asymptomatic and symptomatic BV patients), but in healthy women andthese 3 motifs were not found and numbered 13-15. The bacterial species composition of the network triangle motif and its inter-species interactions, characteristic of these 15 BV patients, are listed in table 1.

Claims

1. A class (15 types) of network triangle motif consisting of vaginal bacteria and application thereof in risk prediction, accurate diagnosis, personalized treatment and post-cure review monitoring of female bacterial vaginitis.

2. The bacterial network motif according to claim 1, characterized in that the motif comprises fifteen Bacterial Vaginosis (BV) patient-specific network motif, the information being shown in Table 1, each motif consisting of three bacterial species linked by specific interaction relationships.

TABLE 1 bacterial network triangle motifs specific to a class of BV patients

3. Use according to claim 1, characterized in that the risk of developing BV is predicted in healthy women by detecting fifteen bacterial network trigonometric motifs of vaginal bacterial microorganisms, while providing targets for the diagnosis, personalized treatment and post-cure monitoring of BV.

4. Use according to any one or more of claims 1-3, characterized in that: products whose concepts and functions are applied in any form of software, firmware, and/or hardware, including various medical instruments, scopes, and the like, to provide services.