摘要

导管相关性尿路感染（CAUTI）是一种令人担忧的基于医院的疾病，奇异变形杆菌的多药耐药性（MDR）菌株增加。据报道，长期住院患者多次接受抗生素治疗以及尿路梗阻和/或接受导尿治疗的病例与CAUTI有关。由于病原体的机会主义方法具有强大的游泳和群集能力，因此病例复杂。后者产生生物膜并且可能通过自动诱导剂诱导，使得情景非常复杂。基于CARTI的长期住院患者的高患病率以及中等百分比的发病率，由于对药物使用的无知以及由于MDR而无法治愈，需要立即采取有效措施来对抗致命疾病的干预策略。一些报告和评论侧重于揭示重要的基因和蛋白质，这是解决由奇异变形杆菌引起的CAUTI所必需的。尽管纵向全国范围的研究和规避策略以避免这些问题，但是用于发掘最不可缺少的蛋白质以用于治疗用途的有效方法已经很少了。在这里，我们报告了一种从奇异变形杆菌菌株HI4320的基因组中鉴定最不可缺少的蛋白质的战略方法，除了比较包含自诱导剂-2（AI-2）生物合成途径的相互作用体以及参与生物膜形成的其他蛋白质并负责毒力。基本上，我们采用了基于理论网络模型的方法来构建一组小蛋白质相互作用网络（SPIN）以及全基因组（GPIN），以计算识别参与群体感应（QS）和生物膜形成现象的关键蛋白质。因此，可以在治疗上针对对抗奇异变形杆菌抗生素的MDR威胁。我们的方法利用功能模块性结合k核分析和特征向量的中心性分数作为解决紧迫问题的措施。

Catheter-associated urinary tract infections (CAUTI) is an alarming hospital based disease with the increase of multidrug resistance (MDR) strains of Proteus mirabilis. Cases of long term hospitalized patients with multiple episodes of antibiotic treatments along with urinary tract obstruction and/or undergoing catheterization have been reported to be associated with CAUTI. The cases are complicated due to the opportunist approach of the pathogen having robust swimming and swarming capability. The latter giving rise to biofilms and probably inducible through autoinducers make the scenario quite complex. High prevalence of long-term hospital based CAUTI for patients along with moderate percentage of morbidity, cropping from ignorance about drug usage and failure to cure due to MDR, necessitates an immediate intervention strategy effective enough to combat the deadly disease. Several reports and reviews focus on revealing the important genes and proteins, essential to tackle CAUTI caused by P. mirabilis. Despite longitudinal countrywide studies and methodical strategies to circumvent the issues, effective means of unearthing the most indispensable proteins to target for therapeutic uses have been meager. Here, we report a strategic approach for identifying the most indispensable proteins from the genome of P. mirabilis strain HI4320, besides comparing the interactomes comprising the autoinducer-2 (AI-2) biosynthetic pathway along with other proteins involved in biofilm formation and responsible for virulence. Essentially, we have adopted a theoretical network model based approach to construct a set of small protein interaction networks (SPINs) along with the whole genome (GPIN) to computationally identify the crucial proteins involved in the phenomenon of quorum sensing (QS) and biofilm formation and thus, could be therapeutically targeted to fight out the MDR threats to antibiotics of P. mirabilis. Our approach utilizes the functional modularity coupled with k-core analysis and centrality scores of eigenvector as a measure to address the pressing issues.

https://www.ncbi.nlm.nih.gov/pubmed/30131943