Novel analytical platform quantitatively characterizes mRNA vaccines

Researchers from Tokyo Metropolitan University and RIKEN CSRS have developed a new analytical platform based on liquid chromatography, mass spectrometry and software analysis that quantifies the structure of messenger RNA (mRNA) based medicines.

They can elucidate mRNA sequences while quantifying "capping" at one end of the molecule and the integrity of the tail on the other, all vital in mRNA pharmaceuticals. The method is a crucial innovation for quality control in production lines.

Messenger RNA (mRNA) is a vital molecule responsible for transmitting the sequence information stored in our DNA to ribosomes, the protein-making machinery of our cells. However, the mRNA does not necessarily have to come from our DNA; by artificially designing mRNA molecules, we can use it as a drug which enables our cells to produce specific protein structures, like antigens which can trigger an immune response and act as a vaccine. mRNA medicines burst into the public consciousness as the primary component of the most effective COVID-19 vaccines. They have many advantages over competing technologies: they are considered much safer, as they do not integrate into the host cell genome; they are relatively easy to manufacture and scale up. Now, the technology is said to hold promise for treating a wide range of other illnesses, including cancer and metabolic diseases.

But with the wide deployment of this new technology, methods are now needed to perform quality control in a more effective, efficient way. mRNA medicines have three key components: the sequence, which determines what proteins are synthesized; the 5'-capping, which ensures that the mRNA is read efficiently during protein translation; the poly(A) tail, which dampens the immune response against the foreign mRNA itself. All three need to be in good working order for the treatment to be effective. However, there is currently no method that can quantify the state of all three in one go.

Now, a team led by Drs Masato Taoka of Tokyo Metropolitan University and Hiroshi Nakayama of RIKEN CSRS have developed an analytical platform combining liquid chromatography, mass spectrometry and automated software analysis to quantitatively monitor the properties of mRNA molecules. The team's platform combines two important innovations. Firstly, using liquid chromatography and mass spectrometry, they undertake a systematic comparison of different fragments of a mRNA molecule to be tested with a similarly fragmented reference mRNA labelled with a stable carbon isotope. Secondly, automated analysis using Ariadne software helps ascertain structures with the help of a sequence database. The team found that their analysis platform could successfully assign the primary structure of the reference, then rapidly identify even the most minute changes in the mRNA molecule being tested, all while yielding quantitative information on the capping and tail group.

The method is applicable to a wide range of mRNA lengths and sequences from completely different origins, allowing all three parts to be analyzed in one go. It promises unparalleled efficiency in checking for the quality of mRNA medicines, both those in action now and yet to be developed.

Source:
Journal reference:

Nakayama, H., et al. (2022) Liquid Chromatography–Mass Spectrometry-Based Qualitative Profiling of mRNA Therapeutic Reagents Using Stable Isotope-Labeled Standards Followed by the Automatic Quantitation Software Ariadne. Analytical Chemistry. doi.org/10.1021/acs.analchem.2c04323.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of AZoLifeSciences.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
Genomic Insights Into the Evolution of Gigantism in Cetaceans