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Computational tools and data integration to accelerate vaccine development: challenges, opportunities, and future directions

The development of effective vaccines is crucial for combating current and emerging pathogens. Despite significant advances in the field of vaccine development there remain numerous challenges including the lack of standardized data reporting and curation practices, making it difficult to determine correlates of protection from experimental and clinical studies. Significant gaps in data and knowledge integration can hinder vaccine development which relies on a comprehensive understanding of the interplay between pathogens and the host immune system. In this review, we explore the current landscape of vaccine development, highlighting the computational challenges, limitations, and opportunities associated with integrating diverse data types for leveraging artificial intelligence (AI) and machine learning (ML) techniques in vaccine design. We discuss the role of natural language processing, semantic integration, and causal inference in extracting valuable insights from published literature and unstructured data sources, as well as the computational modeling of immune responses. Furthermore, we highlight specific challenges associated with uncertainty quantification in vaccine development and emphasize the importance of establishing standardized data formats and ontologies to facilitate the integration and analysis of heterogeneous data. Through data harmonization and integration, the development of safe and effective vaccines can be accelerated to improve public health outcomes. Looking to the future, we highlight the need for collaborative efforts among researchers, data scientists, and public health experts to realize the full potential of AI-assisted vaccine design and streamline the vaccine development process.

60 APPLIED LIFE SCIENCES↗

Protein Factory on a Chip for Rapid Therapeutics

The potential for new, re-emerging, or engineered pandemic threats could challenge our nation's biosecurity, requiring rapid and flexible countermeasure development platforms. In healthcare, one of the main hindrances to the timely development of protein-based therapeutics for cancer, infectious disease, and other diseases has been a slow and expensive quality-controlled production stage. We present a protein-based technology that has the potential to address these crucial problems in biosecurity and healthcare by maximizing protein production and system portability, while minimizing production latency and cost. Specifically, we have developed a reusable, portable first-generation platform that leverages the advantages of cell-free protein synthesis (CFPS) and flow cells to create practical amounts of clinically relevant therapeutics. We have demonstrated that this technology is reusable and programmable, enabling a single platform that can synthesize multiple dosages of various therapeutics and vaccine in the field. Implementing this technology could mitigate pandemic threats by providing a rapidly-deployable (just-in-time), versatile (precision medicine) production of biologic therapeutics to the infected patient’s locale (point-of-care). In drug development, once promising drug variations are identified, the platform can be scaled to quickly produce practical amounts of protein for patient testing in the matter of days (vs. months) at a fraction of the cost of existing technology.

59 BASIC BIOLOGICAL SCIENCES↗

A modular vaccine platform enabled by decoration of bacterial outer membrane vesicles with biotinylated antigens

Engineered outer membrane vesicles (OMVs) derived from Gram-negative bacteria are a promising technology for the creation of non-infectious, nanoparticle vaccines against diverse pathogens. However, antigen display on OMVs can be difficult to control and highly variable due to bottlenecks in protein expression and localization to the outer membrane of the host cell, especially for bulky and/or complex antigens. Here, we describe a universal approach for avidin-based vaccine antigen crosslinking (AvidVax) whereby biotinylated antigens are linked to the exterior of OMVs whose surfaces are remodeled with multiple copies of a synthetic antigen-binding protein (SNAP) comprised of an outer membrane scaffold protein fused to a biotin-binding protein. We show that SNAP-OMVs can be readily decorated with a molecularly diverse array of biotinylated subunit antigens, including globular and membrane proteins, glycans and glycoconjugates, haptens, lipids, and short peptides. When the resulting OMV formulations are injected in mice, strong antigen-specific antibody responses are observed that depend on the physical coupling between the antigen and SNAP-OMV delivery vehicle. Overall, these results demonstrate AvidVax as a modular platform that enables rapid and simplified assembly of antigen-studded OMVs for application as vaccines against pathogenic threats.

60 APPLIED LIFE SCIENCES↗

mRNA vaccine platforms to prevent bacterial infections

Bacterial infections are an urgent public health priority. The application of mRNA vaccine technology to prevent bacterial infections is a promising therapeutic strategy undergoing active development. Here, this article discusses recent advances and limitations of mRNA vaccines to prevent bacterial diseases and provides perspectives on future research directions.

60 APPLIED LIFE SCIENCES↗

Recommendations for Uniform Variant Calling of SARS-CoV-2 Genome Sequence across Bioinformatic Workflows

Genomic sequencing of clinical samples to identify emerging variants of SARS-CoV-2 has been a key public health tool for curbing the spread of the virus. As a result, an unprecedented number of SARS-CoV-2 genomes were sequenced during the COVID-19 pandemic, which allowed for rapid identification of genetic variants, enabling the timely design and testing of therapies and deployment of new vaccine formulations to combat the new variants. However, despite the technological advances of deep sequencing, the analysis of the raw sequence data generated globally is neither standardized nor consistent, leading to vastly disparate sequences that may impact identification of variants. Here, we show that for both Illumina and Oxford Nanopore sequencing platforms, downstream bioinformatic protocols used by industry, government, and academic groups resulted in different virus sequences from same sample. These bioinformatic workflows produced consensus genomes with differences in single nucleotide polymorphisms, inclusion and exclusion of insertions, and/or deletions, despite using the same raw sequence as input datasets. Here, we compared and characterized such discrepancies and propose a specific suite of parameters and protocols that should be adopted across the field. Consistent results from bioinformatic workflows are fundamental to SARS-CoV-2 and future pathogen surveillance efforts, including pandemic preparation, to allow for a data-driven and timely public health response.

60 APPLIED LIFE SCIENCES↗

Editorial: Towards the rapid and systematic assessment of vaccine technologies

The COVID-19 pandemic highlighted both the extraordinary potential of modern vaccinology and persistent challenges in how vaccine technologies are assessed. While vaccines can be developed and deployed at unprecedented speed, our ability to predict efficacy in a population is constrained by methodological difficulties, underreporting of negative results, and limited comparability across studies. This editorial introduces a Research Topic that brings together an interdisciplinary collection of experimental, computational, and theoretical contributions spanning multiple pathogens and vaccine platforms. Across these contributions, emerging themes emphasize the need for standardized immunogenicity metrics, transparent reporting including negative findings, and harmonized experimental protocols to support meaningful comparisons. This editorial highlights community practices and shared commitments – supported by researchers, funders, and journals – that could strengthen reproducibility, transparency, and cumulative learning in vaccine research.

59 BASIC BIOLOGICAL SCIENCES↗

Drug discovery efforts at George Mason University

With over 39,000 students, and research expenditures in excess of $200 million, George Mason University (GMU) is the largest R1 (Carnegie Classification of very high research activity) university in Virginia. Mason scientists have been involved in the discovery and development of novel diagnostics and therapeutics in areas as diverse as infectious diseases and cancer. Below are highlights of the efforts being led by Mason researchers in the drug discovery arena. To enable targeted cellular delivery, and non-biomedical applications, Veneziano and colleagues have developed a synthesis strategy that enables the design of self-assembling DNA nanoparticles (DNA origami) with prescribed shape and size in the 10 to 100 nm range. The nanoparticles can be loaded with molecules of interest such as drugs, proteins and peptides, and are a promising new addition to the drug delivery platforms currently in use. The investigators also recently used the DNA origami nanoparticles to fine tune the spatial presentation of immunogens to study the impact on B cell activation. These studies are an important step towards the rational design of vaccines for a variety of infectious agents. To elucidate the parameters for optimizing the delivery efficiency of lipid nanoparticles (LNPs), Buschmann, Paige and colleagues have devised methods for predicting and experimentally validating the pKa of LNPs based on the structure of the ionizable lipids used to formulate the LNPs. These studies may pave the way for the development of new LNP delivery vehicles that have reduced systemic distribution and improved endosomal release of their cargo post administration. To better understand protein-protein interactions and identify potential drug targets that disrupt such interactions, Luchini and colleagues have developed a methodology that identifies contact points between proteins using small molecule dyes. The dye molecules noncovalently bind to the accessible surfaces of a protein complex with very high affinity, but are excluded from contact regions. When the complex is denatured and digested with trypsin, the exposed regions covered by the dye do not get cleaved by the enzyme, whereas the contact points are digested. The resulting fragments can then be identified using mass spectrometry. The data generated can serve as the basis for designing small molecules and peptides that can disrupt the formation of protein complexes involved in disease processes. For example, using peptides based on the interleukin 1 receptor accessory protein (IL-1RAcP), Luchini, Liotta, Paige and colleagues disrupted the formation of IL-1/IL-R/IL-1RAcP complex and demonstrated that the inhibition of complex formation reduced the inflammatory response to IL-1B. Working on the discovery of novel antimicrobial agents, Bishop, van Hoek and colleagues have discovered a number of antimicrobial peptides from reptiles and other species. DRGN-1, is a synthetic peptide based on a histone H1-derived peptide that they had identified from Komodo Dragon plasma. DRGN-1 was shown to disrupt bacterial biofilms and promote wound healing in an animal model. The peptide, along with others, is being developed and tested in preclinical studies. Other research by van Hoek and colleagues focuses on in silico antimicrobial peptide discovery, screening of small molecules for antibacterial properties, as well as assessment of diffusible signal factors (DFS) as future therapeutics. The above examples provide insight into the cutting-edge studies undertaken by GMU scientists to develop novel methodologies and platform technologies important to drug discovery.

59 BASIC BIOLOGICAL SCIENCES↗