How Advances in LC/LC–MS Enable Better Characterization of mRNA Therapeutics

Characterizing mRNA therapeutics presents myriad challenges in
early discovery and research, because their large size and complexity requires that they be analyzed piece-by-piece. Emerging liquid chromatography (LC) or liquid chromatography–mass spectrometry (LC–MS) methods for oligonucleotide mapping, enabled by advances in nucleases and columns, promise to improve the characterization of mRNA product candidates.

The success of two mRNA vaccines to fight Covid-19 fueled an explosion in mRNA research. More than 300 mRNA vaccines and therapeutics are currently under development to treat a wide range of infectious diseases, cancers and metabolic disorders (1). But this rapid advance in mRNA science has brought to light one major challenge: mRNA therapeutics are challenging to characterize, slowing down early discovery and the identification of the most promising candidates to move into clinical development.

mRNA Technology - Messenger RNA - Two Strands of mRNA on Abstract Technology Background | Image Credit: © ArtemisDiana - stock.adobe.com

Three qualities of mRNA therapeutics are critically important to characterize. They are the full sequence, which is often thousands of nucleotides in length, as well as the guanosine-5’-triphosphate (GTP) cap and 3’ poly-A tail. The 3-prime poly-A tail is essential to maintaining the stability of the mRNA molecule, and the 5-prime cap helps it to enter cells, avoid degradation by enzymes, and start the translation process by which cells make therapeutic proteins.

Recent advances in liquid chromatography (LC) and liquid
chromatography–mass spectrometry (LC–MS) are helping mRNA researchers characterize mRNA therapeutics more quickly and accurately. In particular, new choices in nucleases, columns, and improved chromatography methodologies are enabling new efficiencies in the characterization process.

Divide and Conquer

Characterizing mRNA sequences that are 1000-plus nucleotides in length is impossible using intact LC–MS analysis. So mRNA researchers have no choice but to divide and conquer using nuclease mapping, a technique similar to peptide mapping that researchers use to characterize large proteins. Researchers use LC or LC–MS to study protein therapeutics peptide by peptide, analyzing each piece and then stitching everything back together to complete their characterization of the full sequence. A similar strategy is used for mRNA characterization: A specific nuclease is used to fragment the mRNA into many pieces small enough to be fully characterized by liquid chromatography–tandem mass spectrometry (LC–MS/MS) analysis.

Even when mRNA is cut into pieces, however, it’s considerably more complicated to characterize. With proteins, there are 20 amino acids, among which there are likely to be unique sequence identities that are easy to spot. Because mRNA has just four distinct nucleotides—A, C, U, and G— the sequence is likely to include overlaps and repeats. When you are dealing with a four-letter alphabet across a very large sequence, characterizing the identity of everything that’s there becomes quite complex.

Oligonucleotide mapping has emerged in recent years as a method for characterizing the structure of mRNA using enzymatic digestion. Among the new advances making this task easier is an expanding selection of ribonuclease (RNase) enzymes that are used to cleave nucleotides into small pieces. Researchers have long used the enzyme RNase T1 to divide long nucleases, but it is not ideal because its lack of specificity generates small fragments that are difficult to map on an mRNA sequence. Recently new RNAses have emerged with increased cleavage site specificity, resulting in a less complex mixture of fragments that are easier to assign to a specific sequence of a complex mRNA.

Choosing the right column is also important. To properly characterize mRNA, researchers need to isolate a high number of separated peaks so they can efficiently identify all the pieces of the sequence. Traditional stainless-steel columns are problematic because oligonucleotides often bind to the stainless steel hardware used in high performance liquid chromatography (HPLC) columns. HPLC columns using inert hardware can greatly increase sensitivity and recovery, improving the ability to characterize mRNA by studying small segments.

Characterizing the Poly-A Tail and Cap

Advances in LC and LC–MS are helping mRNA researchers better characterize the 3-prime poly-A tail. Tools designed for characterizing small pieces of long nucleotide sequences aren’t always well-suited to analyzing the poly-A tail because of its large size, which increases the demand for enzymes and chromatography or other separation methods that are tailored specifically to this large and critical piece of mRNA therapeutics.

Detecting the degradation of the poly-A tail is vital in determining the viability of an mRNA candidate. In one recent study, researchers combined LC with high-resolution MS (HRMS) to detect a naturally degraded poly-A tail with single-nucleotide resolution (2). They used RNase 4 to enzymatically digest mRNA oligonucleotide strands of 1250 nucleotides, then injected them into an organo-silica, core-shell column. This method was particularly well-suited to the mobile-phase conditions that are ideal for separating minor differences in characteristics among oligonucleotides.

Characterizing the 5-prime cap is equally challenging. It is an inverted 7-methyldeazaguanosine 5’-triphosphate (GTP) cap that’s attached to the mRNA. As a result, there’s likely to be some heterogeneity among caps in any given sample, requiring particularly strong chromatographic resolution to distinguish and quantitate them. Researchers often struggle with chromatography methods and columns that are ill-suited to separating and characterizing 5-prime caps.

In a 2022 study using the same LC–HRMS method that detected degradation of the poly-A tail in mRNA oligonucleotides, researchers were able to characterize the integrity and diversity of 5-prime caps. They detected three different types of caps, as well as sequences with no caps (3).

In addition to choosing the right enzymes, columns, and chromatography methods for characterizing mRNA therapeutics, it is essential that researchers use clean and very precise laboratory practices. One challenge of working with these molecules is that RNases saturate our environment, so samples can easily get contaminated with random nucleases that can negatively impact the reproducibility of experiments. Scientists must take care to use RNase-free water, add the proper amount of enzymes, and control digestion times to maximize reproducibility.

The potential to address many diseases with mRNA therapeutics and vaccines is huge. But those opportunities bring with them daunting analytical challenges. By embracing new developments in LC/LC–MS tools and methods, mRNA researchers will improve the efficiency, accuracy, and reproducibility of their discovery work, ensuring faster breakthroughs for patients in need.

References

(1) Wang, Y.; Kumari, M.; Chen, G.; Hong, M.; Yuan, J.P.; Tsai, J.; Wu, H. mRNA-Based Vaccines and Therapeutics: An In-Depth Survey of Current and Upcoming Clinical Applications. J. Biomed Sci. 2023, 30, 84. DOI: 10.1186/s12929-023-00977-5

(2) Eggleston-Rangel, R.; Lebedev, I.; Tackett, B. mRNA Poly-A Tail Degradation Detection on a Biozen Oligo Column. Phenomenex, Inc. 2023. https://www.phenomenex.com/documents/2022/11/01/00/21/mrna-poly-a-tail-degradation-detection-on-a-biozen-oligo-column (accessed 2023-12-11)

(3) Eggleston-Rangel, R.; Lebedev, I.; Tackett, B. mRNA Cap Purity Analysis on a Biozen Oligo Column. Phenomenex, Inc. 2023. https://phenomenex.blob.core.windows.net/documents/1ff330fa-7c6f-4c83-bc59-4d1163cecf08.pdf (accessed 2023-12-11)

About the Author

Michael McGinley is Director of Applications at Phenomenex. In his more than 20 years at the company, he has managed the commercialization of HPLC and SPE products and the global technical services group. In his current role, he manages the planning and developing of the application portfolio supporting Phenomenex’s products globally. Direct correspondence to: MichaelM@phenomenex.com