Exploring structural engineering approach to formulate and characterize next-generation adjuvants.

It is critical to emphasize the importance of vaccination as it protects us against harmful pathogens. Despite significant progress in vaccine development, there is an ongoing need to develop vaccines that are not only safe but also highly effective in protecting against severe infections. Subunit vaccines are generally safe, but they frequently fail to elicit strong immune responses. As a result, there is a need to improve vaccine effectiveness by combining them with adjuvants, which have the potential to boost the immune system many folds. The process of developing these adjuvants requires searching for molecules capable of activating the immune system, combining these promising compounds with an antigen, and then testing this combination using animal models before approving it for clinical use. Liposomal adjuvants work as delivery adjuvants and its activity depends on certain parameters such as surface charge, vesicle size, surface modification and route of administration. Self-assembly property of peptide adjuvants and discovery of hybrid peptides have widened the scope of peptides in vaccine formulations. Since most pathogenic molecules are not peptide based, phage display technique allows for screening peptide mimics for such pathogens that have potential as adjuvants. This chapter discusses about peptide and liposome-based adjuvants focusing on their properties imparting adjuvanticity along with the methods of formulating them. Methods of adjuvant characterization important for an adjuvant to be approved for clinical trials are also discussed. These include assays for cytotoxicity, T-lymphocyte proliferation, dendritic cell maturation, cytokine and antibody production, toll-like receptor dependent signaling and adjuvant half-life.

Decoding macrophage immunometabolism in human viral infection.

Immune-metabolic interactions play a pivotal role in both host defense and susceptibility to various diseases. Immunometabolism, an interdisciplinary field, seeks to elucidate how metabolic processes impact the immune system. In the context of viral infections, macrophages are often exploited by viruses for their replication and propagation. These infections trigger significant metabolic reprogramming within macrophages and polarization of distinct M1 and M2 phenotypes. This metabolic reprogramming involves alterations in standard- pathways such as the Krebs cycle, glycolysis, lipid metabolism, the pentose phosphate pathway, and amino acid metabolism. Disruptions in the balance of key intermediates like spermidine, itaconate, and citrate within these pathways contribute to the severity of viral diseases. In this chapter, we describe the manipulation of metabolic pathways by viruses and how they crosstalk between signaling pathways to evade the immune system. This intricate interplay often involves the upregulation or downregulation of specific metabolites, making these molecules potential biomarkers for diseases like HIV, HCV, and SARS-CoV. Techniques such as Nuclear Magnetic Resonance (NMR) and Mass Spectrometry, are the evaluative ways to analyze these metabolites. Considering the importance of macrophages in the inflammatory response, addressing their metabolome holds great promise for the creating future therapeutic targets aimed at combating a wide spectrum of viral infections.

Technological advancements in viral vector designing and optimization for therapeutic applications.

Viral vector engineering is critical to the advancement of several sectors of biotechnology, gene therapy, and vaccine development. These vectors were produced from viruses, were employed to deliver therapeutic genes or to alter biological processes. The potential for viral vectors to improve the precision, safety, and efficiency of therapeutic interventions has boosted their demand. The dynamic interplay between technological advancements and computational tools in establishing the landscape of viral vector engineering and vector optimization for therapeutic reasons is discussed in this chapter. It also emphasizes the importance of in silico techniques in maximizing vector potential for therapeutics and many phases of viral vector engineering, from genomic analysis to computer modelling and advancements to improve precise gene delivery. High-throughput screening propels the expedited process of vector selection, and computational techniques to analyze complex omics data to further enhance vector capabilities have been discussed. As in silico models reveal insights into off-target effects and integration sites, vector safety (biodistribution and toxicity) remains a crucial part and bridges the gap between preclinical and clinical investigations. Despite the limitations, this chapter depicts a future in which technology and computing merge to catapult viral vector therapy into an era of boundless possibilities.