Can Next-generation Sequencing accelerate mRNA vaccine development?

Currently, many new mRNA-based therapies have been vigorously developed for a wide variety of diseases, including other infectious pathogens, cancer and auto-immune diseases. In the meanwhile, the concerns about its safety and potential side-effects have been undoubtfully arisen as happened to other new treatments. Though diverse techniques, such as RT-qPCR, capillary gel electrophoresis, IP-RP-HPLC and immunoblotting have been implemented in the quality analysis of mRNA vaccines, those methods are tedious, expensive and lack of sensitivity in detection essential mRNA features. Consequently, a demand on a robust and combinatory analytical method is urgently needed to evaluate mRNA vaccines integrity, efficiency, and more importantly to monitor contaminants and off-target effect to address those safety and specificity concerns. In the last few years, Next-generation sequencing technology has been advanced with a rapid pace on multiple aspects, including improved sequencing throughput capacity, speed, accuracy, significant reduction of cost and long-read development, promoting its various applications in both research and clinical diagnosis. Can next-generation sequencing assist the development and validation of mRNA vaccines and therapies??


An RNA-sequencing study published recently in Nature communication combined and evaluated both short- and long-read sequencing for mRNA vaccine and therapies analysis. The study proposed a streamlined method, VAX-seq workflow (Gunter et al., 2023) followed by an integrated bioinformatic tool called Mana to gain a comprehensive assessment on those mRNA key attributes, including sequence integrity, 3’-end poly(A) tail length and DNA/RNA contaminants (Fig. 2). Moreover, VAX-seq also provides a solution in the detection of off-target RNAs, which are generated during in vitro transcription as truncated, readthrough or anti-sense form of RNAs triggering innate immune response. Both long- and short-read sequencing revealed the similar on- and off-target RNAs percentage.