Identification of Novel Vaccine Candidates against Campylobacter through Reverse Vaccinology

Antibiotic Resistance Determinant-Focused Acinetobacter baumannii Vaccine Designed Using Reverse Vaccinology

As one of the most influential and troublesome human pathogens, Acinetobacter baumannii (A. baumannii) has emerged with many multidrug-resistant strains. After collecting 33 complete A. baumannii genomes and 84 representative antibiotic resistance determinants, we used the Vaxign reverse vaccinology approach to predict classical type vaccine candidates against A. baumannii infections and new type vaccine candidates against antibiotic resistance. Our genome analysis identified 35 outer membrane or extracellular adhesins that are conserved among all 33 genomes, have no human protein homology, and have less than 2 transmembrane helices. These 35 antigens include 11 TonB dependent receptors, 8 porins, 7 efflux pump proteins, and 2 fimbrial proteins (FilF and CAM87009.1). CAM86003.1 was predicted to be an adhesin outer membrane protein absent from 3 antibiotic-sensitive strains and conserved in 21 antibiotic-resistant strains. Feasible anti-resistance vaccine candidates also include one extracellular protein (QnrA), 3 RND type outer membrane efflux pump proteins, and 3 CTX-M type β-lactamases. Among 39 β-lactamases, A. baumannii CTX-M-2, -5, and -43 enzymes are predicted as adhesins and better vaccine candidates than other β-lactamases to induce preventive immunity and enhance antibiotic treatments. This report represents the first reverse vaccinology study to systematically predict vaccine antigen candidates against antibiotic resistance for a microbial pathogen.

Mathematical modeling based on ordinary differential equations: A promising approach to vaccinology

New contributions that aim to accelerate the development or to improve the efficacy and safety of vaccines arise from many different areas of research and technology. One of these areas is computational science, which traditionally participates in the initial steps, such as the pre-screening of active substances that have the potential to become a vaccine antigen. In this work, we present another promising way to use computational science in vaccinology: mathematical and computational models of important cell and protein dynamics of the immune system. A system of Ordinary Differential Equations represents different immune system populations, such as B cells and T cells, antigen presenting cells and antibodies. In this way, it is possible to simulate, in silico, the immune response to vaccines under development or under study. Distinct scenarios can be simulated by varying parameters of the mathematical model. As a proof of concept, we developed a model of the immune response to vaccination against the yellow fever. Our simulations have shown consistent results when compared with experimental data available in the literature. The model is generic enough to represent the action of other diseases or vaccines in the human immune system, such as dengue and Zika virus.

Excavating the surface-associated and secretory proteome of Mycobacterium leprae for identifying vaccines and diagnostic markers relevant immunodominant epitopes

For centuries, Mycobacterium leprae, etiological agent of leprosy, has been afflicting mankind regardless of extensive use of live-attenuated vaccines and antibiotics. Surface-associated and secretory proteins (SASPs) are attractive targets against bacteria. We have integrated biological knowledge with computational approaches and present a proteome-wide identification of SASPs. We also performed computational assignment of immunodominant epitopes as coordinates of prospective antigenic candidates in most important class of SASPs, the outer membrane proteins (OMPs). Exploiting the known protein sequence and structural characteristics shared by the SASPs from bacteria, 17 lipoproteins, 11 secretory and 19 novel OMPs (including 4 essential proteins) were identified in M. leprae As OMPs represent the most exposed antigens on the cell surface, their immunoinformatics analysis showed that the identified 19 OMPs harbor T-cell MHC class I epitopes and class II epitopes against HLA-DR alleles (54), while 15 OMPs present potential T-cell class II epitopes against HLA-DQ alleles (6) and 7 OMPs possess T-cell class II epitopes against HLA-DP alleles (5) of humans. Additionally, 11 M. leprae OMPs were found to have B-cell epitopes and these may be considered as prime candidates for the development of new immunotherapeutics against M. leprae.