Dataset Information

Immunoinformatic Approach to Contrive a Next Generation Multi-Epitope Vaccine Against Achromobacter xylosoxidans Infections.

ABSTRACT: Achromobacter xylosoxidans, previously identified as Alcaligenes xylosoxidans, is a rod-shaped, flagellated, non-fermenting Gram-negative bacterium that has the ability to cause diverse infections in humans. As a part of its intrinsic resistance to different antibiotics, Achromobacter spp. is also increasingly becoming resistant to Carbapenems. Lack of knowledge regarding the pathogen's clinical features has led to limited efforts to develop countermeasures against infection. The current study utilized an immunoinformatic method to map antigenic epitopes (Helper T cells, B-cell and Cytotoxic-T cells) to design a vaccine construct. We found that 20 different epitopes contribute significantly to immune response instigation that was further supported by physicochemical analysis and experimental viability. The safety profile of our vaccine was tested for antigenicity, allergenicity, and toxicity against all the identified epitopes before they were used as vaccine candidates. The disulfide engineering was carried out in an area of high mobility to increase the stability of vaccine proteins. In order to determine if the constructed vaccine is compatible with toll-like receptor, the binding affinity of vaccine was investigated via molecular docking approach. With the in silico expression in host cells and subsequent immune simulations, we were able to detect the induction of both arms of the immune response, i.e., humoral response and cytokine induced response. To demonstrate its safety and efficacy, further experimental research is necessary.

SUBMITTER: Khalid K

PROVIDER: S-EPMC9309517 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:COVID-19 caused by SARS-CoV-2 was declared a global pandemic by WHO (World Health Organization) in March, 2020. Within 6 months, nearly 750,000 deaths are claimed by COVID-19 across the globe. This called for immediate social, scientific, technological, public and community interventions. Considering the severity of infection and the associated mortalities, global efforts are underway to develop preventive measures against SARS-CoV-2. Among the SARS-CoV-2 target proteins, Spike (S) glycoprotein (a.k.a S Protein) is the most studied target known to trigger strong host immune response. A detailed analysis of S protein-based epitopes enabled us to design a novel B-cell-derived T-cell Multi-epitope-based peptide (MEBP) vaccine candidate. This involved a systematic and comprehensive computational protocol consisting of prediction of dual-purpose epitopes and designing an MEBP vaccine construct. This was followed by 3D structure validation, MEBP complex interaction studies, in silico cloning and vaccine dose-based immune response simulation to evaluate the immunogenic potency of the vaccine construct. The dual-purpose epitope prediction protocol was designed such that the same epitope elicits both humoral and cellular immune response unlike the earlier designs. Further, the epitopes predicted were screened against stringent criteria to ensure selection of a potent candidate with maximum antigen coverage and best immune response. The vaccine dose-based immune response simulation studies revealed a rapid antigen clearance through antibody generation and elevated levels of cell-mediated immunity during repeated exposure of the vaccine. The favourable results of the analysis strongly indicate that the vaccine construct is indeed a potent vaccine candidate and ready to proceed to the next steps of experimental validation and efficacy studies.Supplementary informationThe online version contains supplementary material available at 10.1007/s13205-020-02574-x.

Project description:Bacterial pathogens evolve during chronic colonization of the human host by selection for pathoadaptive mutations. One of the emerging and understudied bacterial species causing chronic airway infections in patients with cystic fibrosis (CF) is Achromobacter xylosoxidans. It can establish chronic infections in patients with CF, but the genetic and phenotypic changes associated with adaptation during these infections are not completely understood. In this study, we analyzed the whole-genome sequences of 55 clinical A. xylosoxidans isolates longitudinally collected from the sputum of 6 patients with CF. Four genes encoding regulatory proteins and two intergenic regions showed convergent evolution, likely driven by positive selection for pathoadaptive mutations, across the different clones of A. xylosoxidans. Most of the evolved isolates had lower swimming motility and were resistant to multiple classes of antibiotics, while fewer of the evolved isolates had slower growth or higher biofilm production than the first isolates. Using a genome-wide association study method, we identified several putative genetic determinants of biofilm formation, motility and β-lactam resistance in this pathogen. With respect to antibiotic resistance, we discovered that a combination of mutations in pathoadaptive genes (phoQ and bigR) and two other genes encoding regulatory proteins (spoT and cpxA) were associated with increased resistance to meropenem and ceftazidime. Altogether, our results suggest that genetic changes within regulatory loci facilitate within-host adaptation of A. xylosoxidans and the emergence of adaptive phenotypes, such as antibiotic resistance or biofilm formation. IMPORTANCE A thorough understanding of bacterial pathogen adaptation is essential for the treatment of chronic bacterial infections. One unique challenge in the analysis and interpretation of genomics data is identifying the functional impact of mutations accumulated in the bacterial genome during colonization in the human host. Here, we investigated the genomic and phenotypic evolution of A. xylosoxidans in chronic airway infections of patients with CF and identified several mutations associated with the phenotypic evolution of this pathogen using genome-wide associations. Identification of phenotypes under positive selection and the associated mutations can enlighten the adaptive processes of this emerging pathogen in human infections and pave the way for novel therapeutic interventions.

Dataset Information

Immunoinformatic Approach to Contrive a Next Generation Multi-Epitope Vaccine Against Achromobacter xylosoxidans Infections.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets