Leboeuf, D. | Search bioRxiv

bioRxiv2026

Adenine Base Editing Potently Suppresses Hepatitis B Surface Antigen Expression and Inhibits Hepatitis D Virus Release

Background and AimsNovel antiviral approaches capable of permanently inactivating the intrahepatic HBV DNA reservoir, the covalently closed circular DNA (cccDNA) and HBV DNA integrated into the host genome, are urgently needed. This study evaluated adenine base editing as a strategy to disrupt HBV replication by introducing mutations in the overlapping HBs/polymerase open reading frame (ORF). MethodsAn adenine base editor (ABE) and 3 guide RNAs (gS1-gS3) were designed to introduce missense mutations within the HBs/polymerase ORF. ABE mRNA and individual gRNAs were co-transfected into HBV-infected HepG2-hNTCP cells and primary human hepatocytes. Antiviral efficacy was further assessed in HepG2.2.15 and PLC/PRF/5 cells harboring integrated HBV DNA. In vivo, lipid nanoparticles (LNP)-mediated delivery of ABE mRNA and gRNAs was evaluated in HBVcircle DNA-transduced mice and in HBV-infected human liver-chimeric mice. The impact of HBs editing on hepatitis D virus (HDV) release was assessed using PLC/PRF/5 and Huh7 cell-based HDV replication models. ResultsAdenine base editing efficiently reduced HBsAg production and HBV replication in vitro by targeting both cccDNA and integrated HBV DNA. A single LNP injection of ABE-gS2 resulted in undetectable HBsAg in HBVcircle mice, while two injections achieved a 90% reduction in serum HBsAg in HBV-infected human liver chimeric mice. HBV DNA replication was also inhibited in vivo. Furthermore, HBs ORF base editing markedly suppressed HDV release in vitro. ConclusionsAdenine base editing of the HBs ORF effectively impairs HBV replication and HBsAg production in vitro and in vivo and concomitantly inhibits HDV release, highlighting its therapeutic potential.

molecular biology↗

bioRxiv2019

Computationally guided high-throughput design of self-assembling drug nanoparticles

Nanoformulations are transforming our capacity to effectively deliver and treat a myriad of conditions. However, many nanoformulation approaches still suffer from high production complexity and low drug loading. One potential solution relies on harnessing co-assembly of drugs and small molecular excipients to facilitate nanoparticle formation through solvent exchange without the need for chemical synthesis, generating nanoparticles with up to 95% drug loading. However, there is currently no understanding which of the millions of possible combinations of small molecules can result in the formation of these nanoparticles. Here we report the development of a high-throughput screening platform coupled to machine learning to enable the rapid evaluation of such nanoformulations. Our platform identified 101 novel self-assembling drug nanoparticles from 2.1 million pairings derived from 788 candidate drugs with one of 2686 excipients, spanning treatments for multiple diseases and often harnessing well-known food additives, vitamins, or approved drugs as carrier materials - with potential for accelerated approval and translation. Given their long-term stability and potential for clinical impact, we further characterize novel sorafenib-glycyrrhizin and terbinafine-taurocholic acid nanoparticles ex vivo and in vivo. We anticipate that this platform could accelerate the development of safer and more efficacious nanoformulations with high drug loadings for a wide range of therapeutics.

bioengineering↗