Subunit vaccines are commonly used against influenza viruses. The epitope of the viral antigen is administered alongside immunostimulant adjuvant. Adjuvants are used to increase the efficacy of some drugs and are responsible for inhibiting the progression of virus-induced symptoms by stimulating the production of antibodies against the virus. There are many adjuvants for influenza vaccines. They include Freund’s adjuvant and MF59, also known as emulsion adjuvants, because they contain surfactants used to solubilize membrane proteins. In some cases, emulsion adjuvants may denature the antigen proteins.
Surfactant-induced denaturation of antigens could be beneficial to immunostimulatory effects. This suggests the importance of understanding a substance’s effect on the antigen’s steric structure when looking for adjuvant candidates. Additionally, knowledge of the conformational changes of antigens could provide more insights into the action mechanism of adjuvants, whose mechanisms are still unclear. For example, knowledge of the adjuvant mechanism, which converts non-antigenic proteins into antigens, is important in understanding the pathogenesis of allergies.
Bile salts (sodium deoxycholate, NaDC), is a promising adjuvant candidate owing to their favorable gelation properties. Like surfactant Quillaja saponaria, NaDC has a similar steroid skeleton and intestinal absorption-promoting effect and is also a potential candidate for oral vaccine components. Additionally, NaDC is a valuable membrane permeation enhancer for oral vaccines. The 3D structure and antigenicity of Bovine serum albumin (BSA) have been extensively studied. BSA comprises three distinct drug-binding domains: domain I containing tryptophan (Trp) 134 and domain II containing Trp213, from which the BSA intrinsic fluorescence is commonly derived from. Therefore, separating the fluorescence of these two Trps would provide more insights into the conformational behavior of BSA.
Herein, Mr. Yuya Kurosawa, Assistant Professor Yuta Otsuka and Professor Satoru Goto from Tokyo University of Science investigated the effects of NaDC on the conformation of globular proteins. In a similar study, nuclear magnetic resonance, thermograms, fluorescence spectra and circular dichroism spectra were measured to elucidate the structural changes in the proteins. Specifically, excitation–emission matrice was adopted here owing to its ability to scan the excitation wavelength and reveal the local environment of the amino acid residues in the protein. It is also suitable for characterizing multiple fluorescent molecules.
In their approach, BSA was chosen as the model antigen. The NaDC concentration was set to cross the critical micelle concentration due to the expected differences in the effects of surfactants on proteins depending on the aggregate. A ratio of the micelle concentration was used as a unit to establish the relationship between the surfactant concentration and the critical micelle concentration. The elements in the fluorescence spectra were separated through singular value decomposition (SVD). Their work is currently published in the journal, Colloids and Surfaces B: Biointerfaces.
The authors observed that the Trp residues of BSA and the fluorescence energy of NaDC were in a three-way relationship, with each element in the fluorescence spectra being effectively separated via SVD. Besides having a large effect on the microenvironment around Trp213, NaDC also enhanced the selective confirmation of Trp213 in the BSA. These results were confirmed by experiments using ketoprofen specific domain II and warfarin specific domain I, where NaDC induced selectivity in domain II that mostly consisted of Trp213. Additionally, micellization improved the selectivity of NaDC to Trp213 while selectively was highly influenced by the aggregation state of the NaDC.
In summary, the research team successfully separated the fluorescent components, NaDC, and Trp residues in BSA by applying SVD to excitation–emission matrices. NaDC induced selective and localized conformational changes in BSA. Furthermore, this method is applicable to the dilution of protein solutions to provide more insights into the interaction between surfactants and proteins without the need for NMR. In a joint statement the authors told Advances in Engineering, that their findings would contribute to the formulation of NaDC as a membrane permeation enhancer or adjuvant in oral vaccines.
Yuya Kurosawa obtained Bachelor’s Degree in Pharmaceutical Sciences from Tokyo University of Science in 2021, and Master’s Degree in 2023, the author is engaged in drug development research at a pharmaceutical company in Japan. His research interests include molecular interactions related to immune responses. The research focuses on the interaction of surfactants as components of vaccine adjuvants with proteins, cyclodextrins, and lipid bilayers. Based on quantitative analysis using NMR, UV-visible, and FTIR spectra, he has contributed to the molecular theoretical analysis of the mechanism of action of drugs and surfactants on proteins and lipid aggregates. In particular, this research has enabled the development of informatics methods that can be applied to linear data containing non-linear elements using singular value decomposition. In addition, mathematical models such as Activator-Inhibitor model are utilized in the analysis of fluorescence to evaluate fluorescence intensity increase and quenching separately. He received the “Best Oral Presentation” at 9th International Postgraduate Conference on Pharmaceutical Sciecnce (iPoPS) 2022 organized by the School of Pharmacy, International Medical University for his presentation on “Increased selectivity of sodium deoxycholate to around Tryptophan213 in bovine serum albumin upon micellization as revealed by singular value decomposition for excitation emission matrix” featured in this issue.
Dr. Yuta Otsuka received Ph.D. in the field of pharmaceutical sciences. In the first 4 years of his professional career, he worked in Faculty of Pharmaceutical sciences, the Tokyo University of Sciences, where he joint managed laboratory as assistant professor. He is engaged in the development of bioceramics as an assistant professor at the Graduate School of Dentistry, Kagoshima University. Since then, he focused on development of bioceramics based mechanochemical synthesis and machine learning system for spectra data. He focused on machine learning for chemical data called chemometrics. The data he is interested in are UV-vis spectra, EDX spectra, XRD patterns, FTIR spectra, NIR spectra, Raman spectra, etc. A novel analysis method was developed by combining XRD patterns and NIR spectra. This was useful for monitoring the crystallization of rebamipide solid dispersions under high humidity storage conditions.
Satoru Goto received his Ph. D. in 1993, after which he was appointed Research Associate (1993–2006) at the Faculty of Pharmaceutical Sciences, Tokushima University. He became Associate Professor (2006–2012) at International University of Health and Welfare, he has been at Tokyo University of Science (2012-), and attempts to improve applications of the linear combination algebra and topology into QSAR studies, physical chemistry and pharmaceutical sciences. Recently, his group claims that solution of pharmaceutical ingredients might behave as rather the equilibrated molecules and associated colloids. Treatments of observed spectra-matrices via a singular value/vector decomposition (SVD) divide them into basis-vectors of spectra (set of finite spectral elements shared by the individual observed spectra), into singular-values (corresponding to intensity/standard deviation on each contribution of basis-vector), and into singular-vectors (set of coefficient vectors on the linear combination of the basis-vectors rearranged the observed spectra). The latter singular-vectors are able to give their CONFIGULATION SPACE reflected constitution of the observed spectra along the experimentally conditional valuables, visualizing their INTERCONVERSION PATHWAYs that depend on gradual change of the contained and/or hidden parameters. In other words, the SVD treatment for the obtained instrumental data not only involve both trend analysis for data and noise reduction but also could provide DISCOVERY of scientific law in the spontaneous phenomena.
Reference
Kurosawa, Y., Otsuka, Y., & Goto, S. (2022). Increased selectivity of sodium deoxycholate to around Tryptophan213 in bovine serum albumin upon micellization as revealed by singular value decomposition for excitation emission matrix. Colloids and Surfaces B: Biointerfaces, 212, 112344.