The current state of vaccine design
What is systems biology?
The impact of systems biology on vaccine design
What challenges are involved?
What does the future look like for this topic?
References
Further reading
Immunology has undergone a revolution thanks to vaccinations. Systems immunology integrates various experimental and computational approaches to comprehend the intricate interactions between the immune system and pathogens.
By using these methods, researchers in the field of vaccine design have been able to unravel important biochemical pathways involved in the immune responses caused by vaccination and forecast how different formulations may change these immunological responses.
This might result in safer and more efficient vaccines against infectious diseases and cancer.
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The current state of vaccine design
Today, vaccine design makes use of a variety of techniques. Some traditional methods include inactivated or attenuated pathogens, while newer approaches comprehend protein subunit vaccines, DNA and RNA vaccines, and viral vector vaccines.
Despite all the progress made in this field, there are still challenges, such as the need for new and better adjuvants to enhance immune responses and the difficulty in targeting certain pathogens, such as Plasmodium spp. Vaccines may be developed against specific species and antigens at certain parasite life cycle stages. There is also the potential for vaccine-induced immune enhancement.
To address these issues, applying systems biology represents an improvement in vaccine design, moving from the reductionist approach to a more holistic one. An example is the vaccine against high-risk human papillomaviruses (hrHPVs) designed by Khan et al. (2018), using an immunoinformatics approach to select HLA-restricted antigenic epitopes from viral E6 proteins. Their results were tested and validated through systems biology.
What is systems biology?
Systems biology is a computational approach for quantifying and analyzing numerous biomolecules in a specific context; this allows us to gain insights into complex biological systems. Since the immune system has more than 1,500 associated genes and proteins in several interconnected pathways, a systems-level approach is crucial for understanding the immunological responses to vaccination.
Some methods include pathway enrichment, network analysis, and machine learning models to find differences in biological pathways in high-throughput omics datasets (e.g., transcriptomics, proteomics, and metabolomics). Applying multi-omics approaches has become important in discovering novel biological relationships in recent years.
Systems Biology: A Short Overview
The impact of systems biology on vaccine design
The traditional methods for vaccine design take an average of 10–15 years, and only 5-6% of vaccine candidates are introduced in the market after clinical trials. A systems biology approach applied to vaccinology helps to reduce the time and costs associated with vaccine development, which benefits public health.
The main purpose of vaccine design is the identification of appropriate antigens that can generate a protective immune response; traditional approaches rely on time-consuming and costly methodologies.
Systems biology helps solve these issues by providing a comprehensive understanding of the host-pathogen interaction at the molecular level and identifying key pathways or molecules critical for a strong immune response, selecting potential targets for vaccine development. Another aspect is the development of vaccines that protect against multiple strains of a pathogen.
Systems biology solves these problems by analyzing the molecular and cellular pathways conserved in the immune response against different strains or variants of a pathogen.
Selecting, discovering, and optimizing antigens is crucial for designing effective vaccines. The traditional antigen selection process is being replaced by the emerging methodology of Rational Vaccinology (RV), which uses computational analysis of potential pathogen genomes, high-throughput screening, and data-profiling techniques to identify candidate antigens for triggering effective immune responses against a pathogen.
The objective is identifying the structural properties that render an antigen potent without triggering a cytokine storm or immune tolerance. RV software, such as VaxiJen 2.0, Jenner-Predict, VacSol, and Vacceed, use machine learning models to predict protective antigens based on the physicochemical properties of proteins.
Epitope prediction is another important research field in immunoinformatics, which uses in silico tools to study potential B and T cell epitopes. These methods aim to analyze the binding affinity of antigenic peptides to MHC molecules. The most effective method for predicting T cell epitopes is based on a data-driven approach that indicates the peptide-binding property of particular class I or II MHC alleles. In the case of antigen–antibody interactions, the whole antigen molecule has to be analyzed.
What challenges are involved?
The main challenge in applying systems biology for vaccine design is the immune system's complexity. The immune system comprises different cell populations, a wide range of signaling pathways that constantly regulate each other, and molecular interactions that are not fully understood. This makes it difficult to accurately model the immune response and predict a vaccine administration's outcome.
Another challenge is the integration of large amounts of data from different sources. Systems biology relies on integrating data from various omics technologies; however, this data is heterogeneous, and its integration can be difficult, as well as the identification of biomarkers for vaccine efficacy and safety prediction.
The variability of the immune response between individuals complicates biomarkers discovery. Hence, systems biology approaches produce large amounts of data, and their translation into clinical practice requires powerful analytical tools.
What does the future look like for this topic?
Systems biology has been shown to play a critical role in vaccine design. Thanks to advanced computational models and machine learning algorithms, it is now possible to predict potential vaccine targets and improve their efficacy and safety by choosing those eliciting potent immune responses with low adverse effects.
A newer area of this field where systems biology has had a significant impact is the development of personalized vaccines, such as cancer vaccines, where identifying tumor-specific mutations in patients represents a key component of directing T-cell responses to eliminate tumors through vaccination. New experimental data from Moderna Inc. and Merck & Co. have shown promising results in reducing the spreading of skin cancer when compared to immunotherapy alone.
They achieved this by extorting tumors from patients and studying their genetic makeup using NGS. Applying artificial intelligence to predict which mutations will be the most effective targets allowed the designing of an individualized vaccine targeting only mutations in the patient's tumor. This shows that as technology advances and the understanding of the immune system increases, it is likely to find more innovative and effective vaccines developed using these approaches.
References
- Gartlan, C., et al. (2022). Vaccine-associated enhanced disease and pathogenic human coronaviruses. Frontiers in Immunology, 13. http://doi.org/10.3389/fimmu.2022.882972
- Khan, A., et al. (2018) Computational identification, characterization and validation of potential antigenic peptide vaccines from hrHPVs E6 proteins using immunoinformatics and computational systems biology approaches. PLoS ONE 13(5). https://doi.org/10.1371/journal.pone.0196484
- Parvizpour, S., et al. (2020). Epitope-based Vaccine Design: A comprehensive overview of bioinformatics approaches. Drug Discovery Today, 25(6), 1034–1042. http://doi.org/10.1016/j.drudis.2020.03.006
- Six, A., et al. (2011). Systems biology in vaccine design. Microbial Biotechnology, 5(2), 295–304. http://doi.org/10.1111/j.1751-7915.2011.00321.x
- Wang, R., et al. (2009). Advances and challenges in malaria vaccine development. Expert Reviews in Molecular Medicine, 11. http://doi.org/10.1017/s1462399409001318
- Steenhuysen, J. (2023, June 6). Cancer vaccines poised to unlock "New treatment paradigm" with Merck/Moderna Data. [Online] Reuters. https://www.reuters.com/business/healthcare-pharmaceuticals/cancer-vaccines-poised-unlock-new-treatment-paradigm-with-merckmoderna-data-2023-06-05/ (Accessed on 06 June 2023).
Further reading
Cleveland Clinic presents new findings on triple-negative breast cancer vaccine