Skip to content
naulon
Not checkedNot checked for notices yet.

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

Kashaf Khalid, Umar Saeed, Mohammad Aljuaid and 4 more

Frontiers in Medicine · 2022

doi:10.3389/fmed.2022.902611 (opens in a new tab)

We email you when a new notice or a question about this paper appears.

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.

Abstract licence: CC BY

Reads

Read by people on this page

None yet.

Checked or read by AI through naulon

None yet.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

Are you an author?

Is this your paper?

Claim it to add your note and be paid when agents cite it. Free.