PopCover-2.0. Improved Selection of Peptide Sets With Optimal HLA and Pathogen Diversity Coverage

In Silico Tools for Predicting Novel Epitopes

Identifying antigens within a pathogen is a critical task to develop effective vaccines and diagnostic methods, as well as understanding the evolution and adaptation to host immune responses. Historically, antigenicity was studied with experiments that evaluate the immune response against selected fragments of pathogens. Using this approach, the scientific community has gathered abundant information regarding which pathogenic fragments are immunogenic. The systematic collection of this data has enabled unraveling many of the fundamental rules underlying the properties defining epitopes and immunogenicity, and has resulted in the creation of a large panel of immunologically relevant predictive (in silico) tools. The development and application of such tools have proven to accelerate the identification of novel epitopes within biomedical applications reducing experimental costs. This chapter introduces some basic concepts about MHC presentation, T cell and B cell epitopes, the experimental efforts to determine those, and focuses on state-of-the-art methods for epitope prediction, highlighting their strengths and limitations, and catering instructions for their rational use.

The MegaPool Approach to Characterize Adaptive CD4+ and CD8+ T Cell Responses

Epitopes recognized by T cells are a collection of short peptide fragments derived from specific antigens or proteins. Immunological research to study T cell responses is hindered by the extreme degree of heterogeneity of epitope targets, which are usually derived from multiple antigens; within a given antigen, hundreds of different T cell epitopes can be recognized, differing from one individual to the next because T cell epitope recognition is restricted by the epitopes' ability to bind to MHC molecules, which are extremely polymorphic in different individuals. Testing large pools encompassing hundreds of peptides is technically challenging because of logistical considerations regarding solvent-induced toxicity. To address this issue, we developed the MegaPool (MP) approach based on sequential lyophilization of large numbers of peptides that can be used in a variety of assays to measure T cell responses, including ELISPOT, intracellular cytokine staining, and activation-induced marker assays, and that has been validated in the study of infectious diseases, allergies, and autoimmunity. Here, we describe the procedures for generating and testing MPs, starting with peptide synthesis and lyophilization, as well as a step-by-step guide and recommendations for their handling and experimental usage. Overall, the MP approach is a powerful strategy for studying T cell responses and understanding the immune system's role in health and disease. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Generation of peptide pools ("MegaPools") Basic Protocol 2: MegaPool testing and quantitation of antigen-specific T cell responses.

Prevalent and immunodominant CD8 T cell epitopes are conserved in SARS-CoV-2 variants

The emergence of SARS-CoV-2 variants of concern (VOC) is driven by mutations that mediate escape from neutralizing antibodies. There is also evidence that mutations can cause loss of T cell epitopes. However, studies on viral escape from T cell immunity have been hampered by uncertain estimates of epitope prevalence. Here, we map and quantify CD8 T cell responses to SARS-CoV-2-specific minimal epitopes in blood drawn from April to June 2020 from 83 COVID-19 convalescents. Among 37 HLA ligands eluted from five prevalent alleles and an additional 86 predicted binders, we identify 29 epitopes with an immunoprevalence ranging from 3% to 100% among individuals expressing the relevant HLA allele. Mutations in VOC are reported in 10.3% of the epitopes, while 20.6% of the non-immunogenic peptides are mutated in VOC. The nine most prevalent epitopes are conserved in VOC. Thus, comprehensive mapping of epitope prevalence does not provide evidence that mutations in VOC are driven by escape of T cell immunity.

Immunoinformatics Analysis of Citrullinated Antigen as Potential Multi-peptide Lung Cancer Vaccine Candidates for Indonesian Population

Non-small-cell lung cancer (NSCLC) is the most common lung cancer which has the highest mortality rate in Indonesia. One of the trends in treating cancer is by utilizing peptide vaccines, an immunotherapeutic approach that aims to stimulate the cell-mediated adaptive immune system to recognize cancer-associated peptides. Currently, no peptide vaccines are available in the market for NSCLC treatment. Therefore, this project aims to develop a multi-epitope peptide-based vaccine for NSCLC utilizing citrullinated peptides. Citrullination is a post-translational modification that occurs in cancer cells during autophagy that functions to induce immune responses towards modified self-epitopes such as tumor cells, through activation of PAD enzymes within the APC and target cells. It was found that introducing a common citrullinated neo-antigen peptide such as vimentin and enolase to the immune system could stimulate a higher specific CD4⁺ T cell response against NSCLC. Moreover, carcinoembryonic antigen (CEA), an antigen that is highly expressed in cancer cells, is also added to increase the vaccine’s specificity and to mobilize both CD4⁺ and CD8⁺ T cells. These antigens bind strongly to the MHC Class II alleles such as HLA-DRB1*07:01 and HLA-DRB*11:01, which are predominant alleles in Indonesian populations. Through in silico approach, the peptides generated from CEA, citrullinated vimentin and enolase, were analyzed for their MHC binding strength, immunogenicity, ability to induce IFNγ response, and population coverage. It is expected that the immunodominant antigens presentation is able to induce a potent immune response in NSCLC patients in Indonesia, resulting in tumor eradication.

Peptide-Based Vaccines for Tuberculosis

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis. As a result of the coronavirus disease 2019 (COVID-19) pandemic, the global TB mortality rate in 2020 is rising, making TB prevention and control more challenging. Vaccination has been considered the best approach to reduce the TB burden. Unfortunately, BCG, the only TB vaccine currently approved for use, offers some protection against childhood TB but is less effective in adults. Therefore, it is urgent to develop new TB vaccines that are more effective than BCG. Accumulating data indicated that peptides or epitopes play essential roles in bridging innate and adaptive immunity and triggering adaptive immunity. Furthermore, innovations in bioinformatics, immunoinformatics, synthetic technologies, new materials, and transgenic animal models have put wings on the research of peptide-based vaccines for TB. Hence, this review seeks to give an overview of current tools that can be used to design a peptide-based vaccine, the research status of peptide-based vaccines for TB, protein-based bacterial vaccine delivery systems, and animal models for the peptide-based vaccines. These explorations will provide approaches and strategies for developing safer and more effective peptide-based vaccines and contribute to achieving the WHO's End TB Strategy.