RNA changes quickly detected with mass spectrometry software

RNA analysis is not limited to the determination of nucleotide sequences. There is also the detection of post-transcriptional modifications (PTxM). More than 170 PTxMs are known, and they seem to affect various biological processes – translation and decoding, control of gene expression, bacterial resistance to antibiotics, immunomodulation, development and human diseases. Unfortunately, PTxMs have not been easily identified or quantified.

To facilitate the study of PTxMs, scientists at Scripps Research have developed an open-source software tool called Pytheas. It automates the analysis of RNA data from tandem mass spectrometry experiments. According to the Scripps team, Pytheas is a reliable tool for analyzing the most abundant PTxMs present in any cell.

Details about Pytheas appeared in Nature Communicationin an article titled “Pytheas: a software package for the automated analysis of RNA sequences and modifications by tandem mass spectrometry.”

“Key features of Pytheas are flexible handling of RNA isotope tagging and modifications, with statistical validation of false discovery rate based on sequence decoys,” the paper’s authors wrote. “We demonstrate bottom-up mass spectrometric characterization of diverse RNA sequences, with broad applications in stable RNA biology and quality control of RNA therapies and mRNA vaccines.”

In this paper, 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,” said the study’s lead author, James Williamson. , PhD, Professor in the Department of Integrative Structural and Computational Biology, and Vice President of Research and Academic Affairs at Scripps Research.

Pytheas should be useful with both natural and synthetic RNAs. Natural RNAs often have modifications that affect their functions, while synthetic 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, and therefore 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 spectrometry 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.

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