Background/Objectives: Lipid nanoparticles (LNPs) are leading mRNA delivery vehicles, with ionizable lipids (ILs) as their key component. However, the relationship between the IL structure and LNP endogenous organ-targeting is not well understood. In this study, we developed a novel library of biodegradable ILs featuring beta-propionate linkers, which, when incorporated into a four-component LNP formulation, show excellent extrahepatic selectivity and high protein expression. Methods: We explored the impact of structural modifications in the hydrophobic chains and polar-head groups in the ILs while keeping the linkers unchanged. In vivo results were evaluated to examine how structural changes influence the biodistribution to spleen or lungs. LNP formulations were assessed for their protein expression levels and organ-specific targeting. Additionally, protein corona formation by the best-performing LNPs was examined to provide further mechanistic insights. Results: Organ targeting was significantly influenced by structural changes in the ILs, allowing for precise control of the biodistribution between the spleen and lungs. Branched hydrophobic chains demonstrated a higher propensity for spleen targeting, while modifications in the polar-head group could drastically shift biodistribution from the lung to the spleen. This led to the identification of LNPs’ zeta potential as a key determinant of their extrahepatic targeting properties. Notably, ionizable lipid A3T2C7, also known as CP-LC-1495, displayed strong lung selectivity (97%) and high protein expression in lung tissue (1.21 × 10⁸ p/s). Similarly, several promising candidates for spleen-targeting LNPs displayed protein expression levels exceeding 1 × 10⁷ p/s (selectivity >80%). Conclusions: This study elucidates the structure–function relationships of ILs in passive organ-specific mRNA delivery, highlighting how the fine-tuning of hydrophobic chains, polar-head groups, and surface charge (zeta potential) allows for the precise control of LNP endogenous biodistribution, a mechanism influenced by protein corona formation. These findings enable the rational design of targeted LNP systems, enhancing their therapeutic potential for specific organs, such as the spleen and lungs.

Circular RNA (circRNA) has gained significant attention as a potential therapeutic tool due to its remarkable stability and resistance to degradation by exonucleases. However, scalable and efficient methods for purification and delivery remain critical challenges that must be addressed. In this study, we developed and evaluated an optimized affinity chromatography method using Oligo (dT) columns for the purification of circRNA, achieving high yield and purity compared with high-performance liquid chromatography. Additionally, we investigated the in vivo efficacy of circRNA-Oligo (dT) encapsulated in lipid nanoparticles (LNPs) formulated with emerging ionizable lipids, including CP-LC-0867 and CP-LC-0729. Our results showed that LNPs formulated with CP-LC-0867 consistently produced higher protein expression compared to SM-102, with sustained luciferase activity observed over a 14-day period. Furthermore, we assessed the lyophilization potential of LNP-circRNA-Oligo (dT) using CP-LC-0729 to extend the shelf life and eliminate the need for ultra-low-temperature storage. Remarkably, the lyophilized LNPs exhibited no significant differences in protein expression compared to their non-lyophilized counterparts, demonstrating that lyophilization is a viable strategy for extending the storage and transport of circRNA therapies. These findings underscore the potential of optimized new ionizable lipids, improved purification strategies, and lyophilization techniques to enhance the scalability, stability, and practical application of circRNA therapies.

Novel antibiotics are urgently needed since bacteria are becoming increasingly resistant to existing antimicrobial drugs. Furthermore, available antibiotics are broad spectrum, often causing off-target effects on host cells and the beneficial microbiome. To overcome these limitations, we used structure-guided design to generate synthetic peptides derived from Andersonin-D1, an antimicrobial peptide (AMP) produced by the odorous frog Odorrana andersonii. We found that both hydrophobicity and net charge were critical for its bioactivity, enabling the design of novel, optimized synthetic peptides. These peptides selectively targeted Gram-negative pathogens in single cultures and complex microbial consortia, showed no off-target effects on human cells or beneficial gut microbes, and did not select for bacterial resistance. Notably, they also exhibited in vivo activity in two preclinical murine models. Overall, we present synthetic peptides that selectively target pathogenic infections and offer promising preclinical antibiotic candidates.

The Bacillus Calmette-Guérin (BCG), the only vaccine against tuberculosis (TB) currently in use, has shown beneficial effects against unrelated infections and to enhance immune responses to vaccines. However, there is little evidence regarding the influence of BCG vaccination on pertussis. Here, we studied the ability of BCG to improve the immune responses to diphtheria, tetanus, and acellular (DTaP) or whole-cell pertussis (DTwP) vaccination in a mouse model. We included MTBVAC, an experimental live-attenuated vaccine derived from Mycobacterium tuberculosis, in our studies to explore if it presents similar heterologous immunity as BCG. Furthermore, we explored the potential effect of routine BCG vaccination on pertussis incidence worldwide. We found that both BCG and MTBVAC when administered before DTaP, triggered Th1 immune responses against diphtheria, tetanus, and pertussis in mice. Immunization with DTaP alone failed to trigger a Th1 response, as measured by the production of IFN-γ. Humoral responses against DTaP antigens were also enhanced by previous immunization with BCG or MTBVAC. Furthermore, exploration of human epidemiological data showed that pertussis incidence was 10-fold lower in countries that use DTaP and BCG compared to countries that use only DTaP. BCG vaccination may have a beneficial impact on the protection against pertussis conferred by DTaP. Further randomized controlled trials are needed to properly define the impact of BCG on pertussis incidence in a controlled setting. This could be a major finding that would support changes in immunization policies. This work was supported by the Ministry of "Economía y Competitividad"; European Commission H2020 program, "Gobierno de Aragón"; CIBERES; "Fundação Butantan"; Instituto de Salud Carlos III and "Fondo FEDER".

The concept of “codon optimisation” involves adjusting the coding sequence of a target protein to account for the inherent codon preferences of a host species and maximise protein expression in that species. However, there is still a lack of consensus on the most effective approach to achieve optimal results. Existing methods typically depend on heuristic combinations of different variables, leaving the user with the final choice of the sequence hit. In this study, we propose a new statistical-physics model for codon optimisation. This model, called the Nearest-Neighbour interaction (NN) model, links the probability of any given codon sequence to the “interactions” between neighbouring codons. We used the model to design codon sequences for different proteins of interest, and we compared our sequences with the predictions of some commercial tools. In order to assess the importance of the pair interactions, we additionally compared the NN model with a simpler method (Ind) that disregards interactions. It was observed that the NN method yielded similar Codon Adaptation Index (CAI) values to those obtained by other commercial algorithms, despite the fact that CAI was not explicitly considered in the algorithm. By utilising both the NN and Ind methods to optimise the reporter protein luciferase, and then analysing the translation performance in human cell lines and in a mouse model, we found that the NN approach yielded the highest protein expression in vivo . Consequently, we propose that the NN model may prove advantageous in biotechnological applications, such as heterologous protein expression or mRNA-based therapies.