Coll De Peña A, Vaduva M, Li NS, Shah S, Ben Frej M, Tripathi A. Enzymatic isolation and microfluidic electrophoresis analysis of residual dsRNA impurities in mRNA vaccines and therapeutics.
Analyst 2024;
149:1509-1517. [PMID:
38265070 DOI:
10.1039/d3an02157b]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2024]
Abstract
The versatility, rapid development, and ease of production scalability of mRNA therapeutics have placed them at the forefront of biopharmaceutical research. However, despite their vast potential to treat diseases, their novelty comes with unsolved analytical challenges. A key challenge in ensuring sample purity has been monitoring residual, immunostimulatory dsRNA impurities generated during the in vitro transcription of mRNA. Here, we present a method that combines an enzyme, S1 nuclease, to identify and isolate dsRNA from an mRNA sample with a microfluidic electrophoresis analytical platform to characterize the impurity. After the method was developed and optimized, it was tested with clinically relevant, pseudouridine-modified 700 and 1800 bp dsRNA and 818-4451 nt mRNA samples. While the treatment impacted the magnitude of the fluorescent signal used to analyze the samples due to the interference of the buffer with the labeling of the sample, this signal loss was mitigated by 8.8× via treatment optimization. In addition, despite the mRNA concentration being up to 400× greater than that of the dsRNA, under every condition, there was a complete disappearance of the main mRNA peak. While the mRNA peak was digested, the dsRNA fragments remained physically unaffected by the treatment, with no change to their migration time. Using these samples, we detected 0.25% dsRNA impurities in mRNA samples using 15 μL with an analytical runtime of 1 min per sample after digestion and were able to predict their size within 8% of the expected length. The short runtime, sample consumption, and high throughput compatibility make it suitable to support the purity assessment of mRNA during purification and downstream.
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