Bacterial dominance network trio motif for risk prediction, diagnosis, personalized treatment and post-healing monitoring of bacteria vaginosis

Abstract

The invention relates to the field of biological information technology and medical health, and discloses a network trio motif consisting of vaginal bacteria and application of the network triangular motif aiming at personalized risk assessment, precise diagnosis, treatment and post-healing (return visit monitoring) of female Bacteria Vaginosis (BV). Based on a dominance network analysis framework, the inventor analyzes and compares vaginal microbial florae of healthy individuals and BV patients, 15 bacterial network trio motifs specific to the BV patients are screened from the vaginal microbial florae, twelve trio motifs are specific to symptomatic BV patients, and the other three trio motifs appear in both symptomatic and asymptomatic BV patients. Each network motif is formed by connecting three vaginal bacteria species through a specific interaction relationship. The network trio motif composed of the vaginal bacteria can be used for diagnosis and risk assessment of the BV, and provides a brand new target for personalized precise treatment and post-healing monitoring of the BV.

Description

technical field [0001] The present invention relates to the fields of bioinformatics and medical health, in particular to a class of network triangular motifs composed of vaginal bacteria, and the use of such motifs in risk assessment, accurate diagnosis, personalized treatment and follow-up visits after recovery of female bacterial vaginosis applications in monitoring. Background technique [0002] Bacterial vaginosis (BV) is a highly prevalent vaginal disorder affecting 20-40% of women. It is associated with reproductive tract infections as well as many pregnancy complications such as pelvic inflammatory disease, premature rupture of membranes, intrauterine fetal death, chorioamnionitis, endometritis, premature labor, postpartum infection, ectopic pregnancy, etc. Since the late 1990s, clinical microbiologists have used microbial culture techniques (which can only culture and identify a limited number of bacteria) to study vaginal microbes and applied ecological theories a...

AI Technical Summary

Problems solved by technology

Therefore, there is still no clear conclusion on the etiology of BV. Treatment strategies targeting individual species often cannot completely eradicate BV, and there is still a high risk of recurrence when the resistance is low during the menstrual cycle.

In addition, there is no relatively complete risk assessment and prognosis monitoring system for BV

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