Genetically Encoding Ultrastable Virus-like Particles Encapsulating Functional DNA Nanostructures in Living Bacteria

Investigating and Modeling the Factors That Affect Genetic Circuit Performance

Over the past 2 decades, synthetic biology has yielded ever more complex genetic circuits that are able to perform sophisticated functions in response to specific signals. Yet, genetic circuits are not immediately transferable to an outside-the-lab setting where their performance is highly compromised. We propose introducing a broader test step to the design-build-test-learn workflow to include factors that might contribute to unexpected genetic circuit performance. As a proof of concept, we have designed and evaluated a genetic circuit in various temperatures, inducer concentrations, nonsterilized soil exposure, and bacterial growth stages. We determined that the circuit's performance is dramatically altered when these factors differ from the optimal lab conditions. We observed significant changes in the time for signal detection as well as signal intensity when the genetic circuit was tested under nonoptimal lab conditions. As a learning effort, we then proceeded to generate model predictions in untested conditions, which is currently lacking in synthetic biology application design. Furthermore, broader test and learn steps uncovered a negative correlation between the time it takes for a gate to turn ON and the bacterial growth phases. As the synthetic biology discipline transitions from proof-of-concept genetic programs to appropriate and safe application implementations, more emphasis on test and learn steps (i.e., characterizing parts and circuits for a broad range of conditions) will provide missing insights on genetic circuit behavior outside the lab.

Virus-like particles for drug delivery: a review of methods and applications

Virus-like particles (VLPs) are self-assembling protein nanoparticles that have great promise as vectors for drug delivery. VLPs are derived from viruses but retain none of their infection or replication capabilities. These protein particles have defined surface chemistries, uniform sizes, and stability properties that make them attractive starting points for drug-delivery scaffolds. Here, we review recent advances in tailoring VLPs for drug-delivery applications, including VLP platform engineering approaches as well as methods for cargo loading, activation, and release. Finally, we highlight several successes using VLPs for drug delivery in model systems.

Engineered Riboswitch Nanocarriers as a Possible Disease-Modifying Treatment for Metabolic Disorders

Both DNA- and RNA-based nanotechnologies are remarkably useful for the engineering of molecular devices in vitro and are applied in a vast collection of applications. Yet, the ability to integrate functional nucleic acid nanostructures in applications outside of the lab requires overcoming their inherent degradation sensitivity and subsequent loss of function. Viruses are minimalistic yet sophisticated supramolecular assemblies, capable of shielding their nucleic acid content in nuclease-rich environments. Inspired by this natural ability, we engineered RNA-virus-like particles (VLPs) nanocarriers (NCs). We showed that the VLPs can function as an exceptional protective shell against nuclease-mediated degradation. We then harnessed biological recognition elements and demonstrated how engineered riboswitch NCs can act as a possible disease-modifying treatment for genetic metabolic disorders. The functional riboswitch is capable of selectively and specifically binding metabolites and preventing their self-assembly process and its downstream effects. When applying the riboswitch nanocarriers to an in vivo yeast model of adenine accumulation and self-assembly, significant inhibition of the sensitivity to adenine feeding was observed. In addition, using an amyloid-specific dye, we proved the riboswitch nanocarriers' ability to reduce the level of intracellular amyloid-like metabolite cytotoxic structures. The potential of this RNA therapeutic technology does not apply only to metabolic disorders, as it can be easily fine-tuned to be applied to other conditions and diseases.