Department of Biological Sciences, Sunway University, Petaling Jaya, Malaysia.
Department of Bioinformatics, University of Mumbai, Mumbai, India.
Front Cell Infect Microbiol. 2019 Jun 20;9:203. doi: 10.3389/fcimb.2019.00203. eCollection 2019.
Nosocomial infections have become alarming with the increase of multidrug-resistant bacterial strains of . Being the causative agent in ~80% of the cases, these pathogenic gram-negative species could be deadly for hospitalized patients, especially in intensive care units utilizing ventilators, urinary catheters, and nasogastric tubes. Primarily infecting an immuno-compromised system, they are resistant to most antibiotics and are the root cause of various types of opportunistic infections including but not limited to septicemia, endocarditis, meningitis, pneumonia, skin, and wound sepsis and even urinary tract infections. Conventional experimental methods including typing, computational methods encompassing comparative genomics, and combined methods of reverse vaccinology and proteomics had been proposed to differentiate and develop vaccines and/or drugs for several outbreak strains. However, identifying proteins suitable enough to be posed as drug targets and/or molecular vaccines against the multidrug-resistant pathogenic bacterial strains has probably remained an open issue to address. In these cases of novel protein identification, the targets either are uncharacterized or have been unable to confer the most coveted protection either in the form of molecular vaccine candidates or as drug targets. Here, we report a strategic approach with the 3,766 proteins from the whole genome of ATCC19606 (AB) to rationally identify plausible candidates and propose them as future molecular vaccine candidates and/or drug targets. Essentially, we started with mapping the vaccine candidates (VaC) and virulence factors (ViF) of strain AYE onto strain ATCC19606 to identify them in the latter. We move on to build small networks of VaC and ViF to conceptualize their position in the network space of the whole genomic protein interactome (GPIN) and rationalize their candidature for drugs and/or molecular vaccines. To this end, we propose new sets of known proteins unearthed from interactome built using key factors, KeF, potent enough to compete with VaC and ViF. Our method is the first of its kind to propose, theoretically, a rational approach to identify crucial proteins and pose them for candidates of vaccines and/or drugs effective enough to combat the deadly pathogenic threats of .
医院感染随着耐多药细菌菌株的增加而变得令人担忧。这些致病革兰氏阴性菌在~80%的病例中是病原体,对住院患者,特别是在使用呼吸机、导尿管和鼻胃管的重症监护病房的患者来说,可能是致命的。它们主要感染免疫受损的系统,对大多数抗生素具有耐药性,是各种机会性感染的根源,包括但不限于败血症、心内膜炎、脑膜炎、肺炎、皮肤和伤口脓毒症,甚至尿路感染。已经提出了包括分型在内的常规实验方法、包含比较基因组学的计算方法以及反向疫苗学和蛋白质组学相结合的方法,以区分和开发几种暴发菌株的疫苗和/或药物。然而,确定足够适合作为药物靶点和/或针对多药耐药病原菌的分子疫苗的蛋白质可能仍然是一个悬而未决的问题。在这些新型蛋白质鉴定的情况下,这些靶点要么是未知的,要么要么不能以分子疫苗候选物的形式提供最令人垂涎的保护,要么不能作为药物靶点提供最令人垂涎的保护。在这里,我们报告了一种从 ATCC19606(AB)的全基因组中 3766 种蛋白质出发的策略性方法,以合理地识别有希望的候选物,并将其作为未来的分子疫苗候选物和/或药物靶点。从本质上讲,我们从菌株 AYE 的疫苗候选物(VaC)和毒力因子(ViF)开始,将其映射到菌株 ATCC19606 上,以在后者中识别它们。我们继续构建 VaC 和 ViF 的小网络,以概念化它们在全基因组蛋白质互作网络(GPIN)的网络空间中的位置,并合理化它们作为药物和/或分子疫苗的候选资格。为此,我们提出了从使用关键因素 KeF 构建的互作组中挖掘出的一组新的已知蛋白质,这些蛋白质足够强大,可以与 VaC 和 ViF 竞争。我们的方法是第一个从理论上提出一种合理的方法来识别关键蛋白质,并将其作为疫苗和/或药物的候选物,以有效对抗致命的病原菌威胁。