The “Pytheas” application allows scientists to identify and quantify modified RNA molecules more easily than ever

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Scripps Research scientists have unveiled a new software tool to study RNA (ribonucleic acid) molecules, which have a host of critical roles in organisms. The open source application, “Pytheas”, described on May 3, 2022, in Nature Communication, accelerates the process of RNA characterization and quantification in basic research and drug development environments.

The app is designed specifically to analyze RNA data generated by a method called mass spectrometry. The “mass specification” is commonly used to evaluate RNA molecules that are not simple strings of standard RNA nucleotides, but rather are modified in some way. Among their demonstrations, the researchers showed that Pytheas can be used to quickly identify and quantify modified RNA molecules like those in the current Pfizer and Moderna COVID-19 mRNA vaccines.

“The analysis of RNA data from mass spectrometry has been a relatively laborious process, lacking the tools found in other areas of biological research, and so our goal with Pytheas is to bring the field into the 21st century,” says lead study author James Williamson, PhD, a professor in the Department of Integrative Structural and Computational Biology and vice president of research and academic affairs at Scripps Research.

The study’s first authors were Luigi D’Ascenzo, PhD, and Anna Popova, PhD, postdoctoral research associate and staff scientist, respectively, in the Williamson lab during the study.

RNA is chemically very similar to DNA, and RNA molecules in cells are heavily involved in the process of translating genes into proteins, as well as fine-tuning gene activity. Additionally, RNA-based therapies – which include the Pfizer and Moderna vaccines – are seen as a very promising new class of drugs, able in principle to hit their biological targets more potently and selectively than traditional small molecule drugs. .

A common tool to detect RNA molecules that exhibit chemical modifications is mass spectrometry, which can be used basically to recognize RNAs and their modifications based on their masses. Natural RNAs often have modifications that affect their functions, while RNAs used for vaccines and RNA-based drugs are almost always artificially modified to optimize their activity and reduce side effects. Until now, methods for processing raw mass spectrometry data on modified RNAs have been relatively slow and manual – thus very laborious – in contrast to corresponding methods in the field of protein analysis, for example.

Williamson and his team developed Pytheas, which is based on the Python programming language, to greatly improve the automation of this processing. The application takes as input mass specification data on an RNA sample and outputs the RNA sequences and predicted chemical modifications, in a way that also facilitates the quantification of distinct RNAs in a sample.

The team demonstrated the speed, accuracy and versatility of Pytheas using mass specification data for important bacterial and yeast RNAs, and for SARS-CoV-2 spike protein messenger RNAs like those used in Pfizer and Moderna COVID-19 vaccines.

“We hope that companies involved in the manufacture of RNA vaccines and other RNA-based therapies will find Pytheas useful, for example for monitoring the quality of their products,” Williamson said.

The researchers now use Pytheas in their studies of natural RNAs and continue to optimize the software.

Pytheas is available for free on the Github software repository.

“Pytheas: A software package for automated analysis of RNA sequences and modifications via tandem mass spectrometry” was co-authored by Luigi D’Ascenzo, Anna Popova, Scott Abernathy, Kai Sheng, Patrick Limbach and James Williamson, all of Scripps Research.

Research support was provided by the National Institutes of Health (GM136412, GM053757, GM058843).

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