The biologic actions of interferons (IFNs) are complex and involve multiple biochemical mechanisms, including the 2-5A system, a regulated RNA decay pathway. The 2-5A system is implicated in the antipicornavirus activity of IFN and in the control of apoptosis. To further investigate involvement of the 2-5A system in the control of viral and cellular growth and death, human RNase L cDNA was stably expressed in murine 3T3 cells from a constitutive cytomegalovirus (CMV) promoter. A clonal cell line, 3T3/pLZ, was isolated that overexpressed RNase L by >100-fold compared with levels of the endogenous murine RNase L. Interestingly, human RNase L levels in 3T3/pLZ cells decreased 3-fold as cells entered a confluent, growth arrest state, suggesting autoregulation. Overexpression of human RNase L greatly enhanced both the cell growth inhibitory activity of IFN and the proapoptotic activity of staurosporine. Furthermore, high levels of RNase L suppressed the replication of diverse viruses: encephalomyocarditis virus, vesicular stomatitis virus, human parainfluenza virus-3, and vaccinia virus. Additional reductions in viral growth were obtained by treating 3T3/pLZ cells with IFN (a + beta) before infections. These results directly demonstrate the anticellular and antiviral potential of the 2-5A system.

No abstract

No abstract

Lipid nanoparticles (LNPs) have been used to successfully deliver small interfering RNAs (siRNAs) to target cells in both preclinical and clinical studies and currently are the leading systems for in vivo delivery. Here, we propose the use of an ordinary differential equation (ODE)-based model as a tool for optimizing LNP-mediated delivery of siRNAs. As a first step, we have used a combination of experimental and computational approaches to develop and validate a mathematical model that captures the critical features for efficient siRNA-LNP delivery in vitro. This model accurately predicts mRNA knockdown resulting from novel combinations of siRNAs and LNPs in vitro. As demonstrated, this model can be effectively used as a screening tool to select the most efficacious LNPs, which can then further be evaluated in vivo. The model serves as a starting point for the future development of next generation models capable of capturing the additional complexity of in vivo delivery.

Drug combinations can improve the control of diseases involving redundant and highly regulated pathways. Validating a multi-target therapy early in drug development remains difficult. Small interfering RNAs (siRNAs) are routinely used to selectively silence a target of interest. Owing to the ease of design and synthesis, siRNAs hold promise for combination therapies. Combining siRNAs against multiple targets remains an attractive approach to interrogating highly regulated pathways. Currently, questions remain regarding how broadly such an approach can be applied, since siRNAs have been shown to compete with one another for binding to Argonaute2 (Ago2), the protein responsible for initiating siRNA-mediated mRNA degradation. Mathematical modeling, coupled with in vitro and in vivo experiments, led us to conclude that endosomal escape kinetics had the highest impact on Ago2 depletion by competing lipid-nanoparticle (LNP)-formulated siRNAs. This, in turn, affected the level of competition observed between them. A future application of this model would be to optimize delivery of desired siRNA combinations in vitro to attenuate competition and maximize the combined therapeutic effect.