Interferon-γ (IFN-γ) is a cytokine that plays an important role in immune regulation, especially in the activation and differentiation of immune cells. Toll-like receptors (TLRs) are a family of pattern-recognition receptors that sense structural motifs related to pathogens and alert immune cells to the invasion. Both IFN-γ and TLR agonists have been used as immunoadjuvants to augment the efficacy of cancer immunotherapies and vaccines against infectious diseases or psychoactive compounds. In this study, we aimed to explore the potential of IFN-γ and TLR agonists being applied simultaneously to boost dendritic cell activation and the subsequent antigen presentation. In brief, murine dendritic cells were treated with IFN-γ and/or the TLR agonists, polyinosinic–polycytidylic acid (poly I:C), or resiquimod (R848). Next, the dendritic cells were stained for an activation marker, a cluster of differentiation 86 (CD86), and the percentage of CD86-positive cells was measured by flow cytometry. From the cytometric analysis, IFN-γ efficiently stimulated a considerable number of the dendritic cells, while the TLR agonists by themselves could merely activate a few compared to the control. The combination of IFN-γ with poly I:C or R848 triggered a higher amount of dendritic cell activation than IFN-γ alone. For instance, 10 ng/mL IFN-γ with 100 µg/mL poly I:C achieved 59.1% cell activation, which was significantly higher than the 33.4% CD86-positive cells obtained by 10 ng/mL IFN-γ. These results suggested that IFN-γ and TLR agonists could be applied as complementary systems to promote dendritic cell activation and antigen presentation. There might be a synergy between the two classes of molecules, but further investigation is warranted to ascertain the interaction of their promotive activities.

The human leukocyte antigen (HLA) gene complex, one of the most diverse gene complexes found in the human genome, largely dictates how our immune systems recognize pathogens. Specifically, HLA genetic variability has been linked to vaccine effectiveness in humans and it has likely played some role in the shortcomings of the numerous human vaccines that have failed clinical trials. This variability is largely impossible to evaluate in animal models, however, as their immune systems generally 1) lack the diversity of the HLA complex and/or 2) express major histocompatibility complex (MHC) receptors that differ in specificity when compared to human MHC. In order to effectively engage the majority of human MHC receptors during vaccine design, here, we describe the use of HLA population frequency data from the USA and MHC epitope prediction software to facilitate the in silico mining of universal helper T cell epitopes and the subsequent design of a universal human immunogen using these predictions. This research highlights a novel approach to using in silico prediction software and data processing to direct vaccine development efforts.