Delineating the Plausible Molecular Vaccine Candidates and Drug Targets of Multidrug-Resistant Acinetobacter baumannii

Abstract

Nosocomial infections have become alarming with the increase of multidrug-resistant bacterial strains of Acinetobacter baumannii. 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 A. baumannii 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 A. baumannii 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, albeit 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 A. baumannii.

Keywords: Acinetobacter baumannii; drug targets; network analysis; nosocomial infection; vaccine candidates.

Figure 1

The flow chart for the whole process of the present study.

Figure 2

The three SPINs and GPINs of A. baumannii reflecting the degree of connectivity. SPINs are represented in blue spheres connected through blue-colored curved lines for (A) VaCAB, having vaccine candidates; (B) ViFAB, with virulent factors; and (C) KeFAB, with key factors each with their interactors. (D) GPIN with proteins represented in black spheres connected with black curved lines to form the interactome.

Figure 3

Venn diagram representation for the top-ranking network centrality measures of SPIN and GPIN of A. baumannii. (A,B) VaCAB, (C,D) ViFAB, (E,F) KeFAB, and (G) GPIN. Measures of four types of centrality are from CytoNCA and three types are from Network Analyzer. BC, CC, DC, and EC denote betweenness centrality, closeness centrality, degree centrality, and eigenvector centrality, respectively.

Figure 4

Network topological measures for the set of proteins from the GPIN of A. baumannii. (A) The degree distribution, (B) k-core distribution, and (C) K-shell sizes. CCDF denotes Complementary Cumulative Distribution Function.

Figure 5

Cartographic representation for the set of classified proteins from the GPIN of A. baumannii. Designated quadrants from R1 to R7 (in random colors) comprise nodes in each representing different classes of proteins. Selected Vaccine Candidates, VaC (V), Virulent Factors, ViF (F), and Key Factors, KeF (K) proteins from network centrality analyzed SPIN (Small PIN) are mapped onto different quadrants as deemed fit in GPIN (Genome PIN). ^∧ and ^* represent proteins shared between different centralities only and those also between different categories, respectively.