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Genome-wide scan for potential CD4+ T-cell vaccine candidates in Candida auris by exploiting reverse vaccinology and evolutionary information

Please always quote using this URN: urn:nbn:de:bvb:20-opus-293953
  • Candida auris is a globally emerging fungal pathogen responsible for causing nosocomial outbreaks in healthcare associated settings. It is known to cause infection in all age groups and exhibits multi-drug resistance with high potential for horizontal transmission. Because of this reason combined with limited therapeutic choices available, C. auris infection has been acknowledged as a potential risk for causing a future pandemic, and thus seeking a promising strategy for its treatment is imperative. Here, we combined evolutionary informationCandida auris is a globally emerging fungal pathogen responsible for causing nosocomial outbreaks in healthcare associated settings. It is known to cause infection in all age groups and exhibits multi-drug resistance with high potential for horizontal transmission. Because of this reason combined with limited therapeutic choices available, C. auris infection has been acknowledged as a potential risk for causing a future pandemic, and thus seeking a promising strategy for its treatment is imperative. Here, we combined evolutionary information with reverse vaccinology approach to identify novel epitopes for vaccine design that could elicit CD4+ T-cell responses against C. auris. To this end, we extensively scanned the family of proteins encoded by C. auris genome. In addition, a pathogen may acquire substitutions in epitopes over a period of time which could cause its escape from the immune response thus rendering the vaccine ineffective. To lower this possibility in our design, we eliminated all rapidly evolving genes of C. auris with positive selection. We further employed highly conserved regions of multiple C. auris strains and identified two immunogenic and antigenic T-cell epitopes that could generate the most effective immune response against C. auris. The antigenicity scores of our predicted vaccine candidates were calculated as 0.85 and 1.88 where 0.5 is the threshold for prediction of fungal antigenic sequences. Based on our results, we conclude that our vaccine candidates have the potential to be successfully employed for the treatment of C. auris infection. However, in vivo experiments are imperative to further demonstrate the efficacy of our design.show moreshow less

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Metadaten
Author: Shishir K. Gupta, Özge Osmanoglu, Rashmi Minocha, Sourish Reddy Bandi, Elena Bencurova, Mugdha Srivastava, Thomas Dandekar
URN:urn:nbn:de:bvb:20-opus-293953
Document Type:Journal article
Faculties:Fakultät für Biologie / Theodor-Boveri-Institut für Biowissenschaften
Medizinische Fakultät / Institut für Experimentelle Biomedizin
Fakultät für Biologie / Center for Computational and Theoretical Biology
Language:English
Parent Title (English):Frontiers in Medicine
ISSN:2296-858X
Year of Completion:2022
Volume:9
Article Number:1008527
Source:Frontiers in Medicine (2022) 9:1008527. doi: 10.3389/fmed.2022.1008527
DOI:https://doi.org/10.3389/fmed.2022.1008527
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Tag:T-cell epitope; epitope prediction; evolution; immune-informatics; positive selection
Release Date:2023/04/20
Date of first Publication:2022/11/03
Open-Access-Publikationsfonds / Förderzeitraum 2022
Licence (German):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International