Porphyromonas gingivalis resistance and virulence: An integrated functional network analysis

毒力 生物 流出 牙龈卟啉单胞菌 微生物学 毒力因子 抗生素耐药性 多重耐药 牙周炎 抵抗性 抗药性 抗生素 细菌 遗传学 基因 医学 内科学 整合子
作者
Prachi Sao,Siddharth Vats,Sachidanand Singh
出处
期刊:Gene [Elsevier]
卷期号:839: 146734-146734 被引量:7
标识
DOI:10.1016/j.gene.2022.146734
摘要

The gram-negative bacteria Porphyromonas gingivalis (PG) is the most prevalent cause of periodontal diseases and multidrug-resistant (MDR) infections. Periodontitis and MDR infections are severe due to PG's ability to efflux antimicrobial and virulence factors. This gives rise to colonisation, biofilm development, evasion, and modulation of the host defence system. Despite extensive studies on the MDR efflux pump in other pathogens, little is known about the efflux pump and its association with the virulence factor in PG. Prolonged infection of PG leads to complete loss of teeth and other systemic diseases. This necessitates the development of new therapeutic interventions to prevent and control MDR. The study aims to identify the most indispensable proteins that regulate both resistance and virulence in PG, which could therefore be used as a target to fight against the MDR threat to antibiotics. We have adopted a hierarchical network-based approach to construct a protein interaction network. Firstly, individual networks of four major efflux pump proteins and two virulence regulatory proteins were constructed, followed by integrating them into one. The relationship between proteins was investigated using a combination of centrality scores, k-core network decomposition, and functional annotation, to computationally identify the indispensable proteins. Our study identified four topologically significant genes, PG_0538, PG_0539, PG_0285, and PG_1797, as potential pharmacological targets. PG_0539 and PG_1797 were identified to have significant associations between the efflux pump and virulence genes. This type of underpinning research may help in narrowing the drug spectrum used for treating periodontal diseases, and may also be exploited to look into antibiotic resistance and pathogenicity in bacteria other than PG.

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