Electrophoresis-Mediated Characterization of Full and Empty Adeno-Associated Virus Capsids

Electrophoretic Microfluidic Characterization of mRNA- and pDNA-Loaded Lipid Nanoparticles

Lipid nanoparticles (LNPs) are clinically advanced nonviral gene delivery vehicles with a demonstrated ability to address viral, oncological, and genetic diseases. However, the further development of LNP therapies requires rapid analytical techniques to support their development and manufacturing. The method developed and described in this paper presents an approach to rapidly and accurately analyze LNPs for optimized therapeutic loading by utilizing an electrophoresis microfluidic platform to analyze the composition of LNPs with different clinical lipid compositions (Onpattro, Comirnaty, and Spikevax) and nucleic acid (plasmid DNA (pDNA) and messenger RNA (mRNA)) formulations. This method enables the high-throughput screening of LNPs using a 96- or 384-well plate with approximate times of 2-4 min per sample using a total volume of 11 μL. The lipid analysis requires concentrations approximately between 109 and 1010 particles/mL and has an average precision error of 10.4% and a prediction error of 19.1% when compared to using a NanoSight, while the nucleic acid analysis requires low concentrations of 1.17 ng/μL for pDNA and 0.17 ng/μL for mRNA and has an average precision error of 4.8% and a prediction error of 9.4% when compared to using a PicoGreen and RiboGreen assay. In addition, our method quantifies the relative concentration of nucleic acid per LNP. Utilizing this approach, we observed an average of 263 ± 62.2 mRNA per LNP and 126.3 ± 21.2 pDNA per LNP for the LNP formulations used in this study, where the accuracy of these estimations is dependent on reference standards. We foresee the utility of this technique in the high-throughput characterization of LNPs during manufacturing and formulation research and development.

Concise Analysis of Single-Stranded DNA of Recombinant Adeno-Associated Virus By Automated Electrophoresis System

Recombinant adeno-associated virus (rAAV) is a prominent viral vector currently available for human gene therapy. The diameter of the rAAV capsid is ∼25 nm, and a positive or negative single-stranded DNA is packaged within the vector capsid. In this report, we describe a concise method to examine the extracted rAAV genome using an automated electrophoresis system. The rAAV genome, prepared from vector particles through either heat treatment at 95°C for 10 min or the phenol-chloroform extraction method, was analyzed using an automated electrophoresis system under denaturation conditions. The heat treatment protocol demonstrated a comparable yield with the phenol-chloroform extraction protocol, and the quantified amounts of the rAAV genome obtained using the automated electrophoresis system were consistent with those quantitated by quantitative PCR. Additionally, crude rAAV extractions could also be analyzed by the automated electrophoresis system after DNase I treatment. These results indicated that this simple and quick analysis using automated electrophoresis is highly useful for confirming the purity and integrity of the rAAV genome.

Microfluidic AAV Purity Characterization: New Insights into Serotype and Sample Treatment Variability

Despite recent advances in nucleic acid delivery systems with the success of LNP vehicles, adeno-associated virus (AAV) remains the leading platform for targeted gene delivery due to its low immunogenicity to humans, high transduction efficiency, and range of serotypes with varying tropisms. Depending on the therapeutic goals and serotype used, different production conditions may be more amenable, generating an ever-growing need for rapid yet robust analytical techniques to support the high-quality manufacturing of AAV. A critical bottleneck exists for assessing full capsids where rapid, high-throughput techniques capable of analyzing a range of serotypes are needed. Here, we present a rapid, high-throughput analytical technique, microfluidic electrophoresis, for the assessment of full capsids compatible with AAV1, AAV2, AAV6, AAV8, and AAV9 without the need for assay modifications or optimizations, and AAV5 with some constraints. The method presented in this study uses a mathematical formulation we developed previously with a reference standard to combine the independently obtained capsid protein and single-stranded DNA (ssDNA) profiles to estimate the percentage of full capsids in a sample of unknown concentration. We assessed the ability to use a single serotype (AAV8) as the reference standard regardless of the serotype of the sample being analyzed so long as the melting temperature (Tm) of the capsids is within 12 °C from the Tm of AAV8. Using this method, we are able to characterize samples ±6.1% with an average analytical turnaround time of <5 min/sample, using only 10 μL/sample at a concentration of 2.5 × 1012 VG/mL.

A microfluidic electrophoretic dual dynamic staining method for the identification and relative quantitation of dsRNA contaminants in mRNA vaccines

mRNA vaccines (i.e., COVID-19 vaccine) offer various advantages over traditional vaccines in preventing and reducing disease and shortening the time between pathogen discovery and vaccine creation. Production of mRNA vaccines results in several nucleic acid and enzymatic by-products, most of which can be detected and removed; however, double-stranded RNA (dsRNA) contaminants pose a particular challenge. Current purification and detection platforms for dsRNA vary in effectiveness, with problems in scalability for mass mRNA vaccine production. Effectively detecting dsRNA is crucial in ensuring the safety and efficacy of the vaccines, as these strands can cause autoimmune reactions with length-symptom dependency and enhance mRNA degradation. We present a new microfluidics method to rapidly identify and quantify dsRNA fragments in mRNA samples. Our innovation exploits the differences in the dynamic staining behavior between mRNA and dsRNA molecules to detect dsRNA contaminants in a high throughput approach. The limit of detection of the system for dsRNA was estimated to be between 17.7-76.6 pg μL-1 with a maximum loading capacity of mRNA of 12.99 ng μL-1. Based on these estimated values, our method allows for the detection of dsRNA contaminants present in percentages as low as 0.14-0.59% compared to the total mRNA concentration. Here, we discuss the molecular mechanism of the dynamic staining behavior of dsRNA and mRNA for two different stains. We believe our method will accelerate the mRNA vaccine development from initial development to quality control workflows.