Related Experiment Video
Updated: May 29, 2025
Label-Free Quantitative Proteomics Workflow for Discovery-Driven Host-Pathogen Interactions
Published on: October 20, 2020
Utilizing the subtractive proteomics approach to design ensemble vaccine against Candida lusitaniae for immune
Habiba Naz1, Rimsha Timotheous1, Muhammad Farhan Sarwar1
1Department of Biotechnology, Knowledge Unit of Science (KUSC), University of Management and Technology Sialkot, Sialkot, Pakistan.
Abstract:
Vaccines have always been one of the promising therapeutic sources against many pathogens including infectious fungi. Candida lusitaniae is also one of those fungi which is responsible for different infections in human beings including vaginitis, endocarditis, endophthalmitis and blood stream infections. There is thus, a need to adopt effective therapeutic strategies to tackle such infections. Vaccine is one of those efficient therapeutic agents which stimulates immune response and prevents a certain infection to get hazardous. Keeping in view this very important concept, we have designed in-silico vaccine against C. lusitaniae by following the subtractive proteomics approach. Initially, the screening of therapeutic targets was performed to identify potent vaccine candidates from the whole proteome of C. lusitaniae. Several significant factors were taken into account in this context, such as stability index, IFN status, allergenicity, and antigenicity. As a result, four distinct proteins that were both antigenic and non-allergenic, were selected from the whole proteome. Furthermore, physiochemical investigation revealed that these vaccine candidates were stable and that their IFN status was positive. Notably, each of these proteins was non-homologous to human beings. This particular attribute of the selected proteins i.e., to be non-homologous, was made in order to possess the ability to trigger an immunological response in host (humans). Furthermore, the whole proteome (WP) vaccine was constructed accordingly. The structural modelling of all the selected vaccine candidates was then performed to proceed them further for docking with the human toll-like receptor 2 (TLR2). Afterwards, the codon optimization was executed, followed by in-silico cloning of the final vaccine construct. The pet28A plasmid was incorporated for this purpose while, the SnapGene tool was utilized for this particular analysis. Ultimately, the immune simulations were executed to assess the immune response of the designed vaccine (WP). Upon final results, it was found that highest count of IgG and IgM was achieved i.e., up to 700000 between the days 8 to 13 and then slowly neutralized till the day 30. These results signified that the designed vaccine possessed the potential to stimulate the required immune response.
Insights
This study designed an in-silico vaccine against Candida lusitaniae using subtractive proteomics. The vaccine effectively stimulated a strong immune response, indicated by high IgG and IgM levels, showing potential for treating fungal infections.
Area of Science:
- * Computational vaccinology and bioinformatics
- * Infectious disease research
- * Mycology and immunology
Background:
- * Candida lusitaniae causes serious human infections like bloodstream infections and vaginitis.
- * Effective therapeutic strategies, including vaccines, are needed to combat C. lusitaniae.
- * Subtractive proteomics offers a method for identifying potential vaccine targets.
Purpose of the Study:
- * To design an in-silico whole proteome (WP) vaccine against Candida lusitaniae.
- * To identify and select non-allergenic, antigenic, stable, and non-homologous proteins as vaccine candidates.
- * To evaluate the vaccine's immunogenicity and potential to elicit an immune response.
Main Methods:
- * Subtractive proteomics approach for screening C. lusitaniae proteome.
- * In-silico analysis including stability, IFN status, allergenicity, antigenicity, and human homology checks.
- * Structural modeling, docking with human toll-like receptor 2 (TLR2), codon optimization, in-silico cloning, and immune simulations.
Main Results:
- * Four antigenic, non-allergenic, stable, and non-human homologous proteins were identified.
- * The in-silico vaccine construct demonstrated positive IFN status.
- * Immune simulations showed a significant increase in IgG and IgM levels between days 8-13, indicating a robust immune response.
Conclusions:
- * The designed in-silico vaccine against C. lusitaniae shows promise for stimulating a protective immune response.
- * The subtractive proteomics approach is effective for identifying potent vaccine candidates.
- * Further research and experimental validation are warranted to develop a viable vaccine against C. lusitaniae infections.
