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Biology subjects

Wein, S.

Publications and source records attributed to Wein, S..

4 recordsLinked to original sources

Harmonized nucleoside mass spectrometry enables reproducible cross-platform RNA modification quantification

RNA modification analysis by LC-MS/MS is central to epitranscriptomics, yet quantitative comparison across laboratories and instrument platforms remains poorly standardized. Here, we performed a community-driven benchmarking study during the first Human RNome Project workshop to systematically evaluate cross-platform reproducibility of ribonucleoside mass spectrometry workflows. Using the same analytical column and gradient, standardized RNA samples, and shared reagents, we compared nucleoside quantification across quadrupole, time-of-flight, and orbitrap-based LC-MS platforms employing distinct acquisition strategies. While chromatographic separation was highly reproducible across systems, nucleoside-specific MS response behavior differed substantially between platforms and limited direct comparability of relative signal intensities. These response differences varied across analytes and concentration ranges, demonstrating that harmonized chromatography alone is insufficient for transferable quantitative analysis. Stable isotope-labeled internal standard (SILIS) normalization substantially reduced platform-and method-dependent response and improved agreement for most evaluated modifications. External calibration improved agreement between qTOF and Orbitrap workflows for a subset of modifications but did not fully resolve residual intersystem differences. Based on these findings, we establish benchmark-derived recommendations for harmonized relative and absolute RNA modification quantification, including guidance for calibration design, quality control, and data reporting. Together, this work provides a methodological framework for reproducible nucleoside LC-MS/MS workflows and establishes a foundation for large-scale comparative epitranscriptomic studies. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/739095v1_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@6e4e98org.highwire.dtl.DTLVardef@1ea13beorg.highwire.dtl.DTLVardef@b65858org.highwire.dtl.DTLVardef@1623337_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

Human 28S rRNA analysed by state-of-the-art oligonucleotide mass spectrometry: benchmarking current capabilities and a call to action for MS-Seq

Oligonucleotide mass spectrometry (MS-Seq) is emerging as a powerful approach for sequence-resolved RNA modification analysis, yet the field lacks standards for experimental workflows, data analysis and reporting. To assess current capabilities, the Human RNome Project Consortium conducted a cross-platform benchmarking study using a common RNA sample. A partial RNase T1 digest of human 28S rRNA was distributed to participating laboratories and analysed using existing LC-MS/MS workflows spanning different chromatographic strategies and mass spectrometers. To enable direct comparison, datasets were analysed using a harmonized NucleicAcidSearchEngine (NASE) workflow. Despite substantial methodological differences, laboratories recovered highly overlapping oligonucleotide sets and generated similar sequence coverage maps with a global coverage of 54.16%, demonstrating reproducible sequence information across platforms under standardized sample and analysis conditions. The benchmark further revealed incomplete sequence coverage, platform-specific differences in data architecture and increased assignment ambiguity during dynamic modification searches. Together with the community consensus developed during the HRPC workshop, these findings define priorities for the field, including improved sensitivity, standardized data analysis and reporting, community repositories, and robust bioinformatic workflows for confident de novo RNA modification discovery. This study provides an experimental benchmark and roadmap toward routine MS-based mapping of the human RNome. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=120 SRC="FIGDIR/small/739151v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@1fb1b9borg.highwire.dtl.DTLVardef@d172a5org.highwire.dtl.DTLVardef@bdc185org.highwire.dtl.DTLVardef@1ec1cc9_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

An acyclic nucleoside phosphonate effectively blocks the egress of the malaria parasite by inhibiting the synthesis of cyclic GMP.

The urgent need for new antimalarial therapies arises from the alarming spread of malaria parasite resistance to existing drugs. A promising candidate, UA2239, an acyclic nucleoside phosphonate with a guanine as nucleobase, demonstrates rapid and irreversible cytotoxic effects on Plasmodium parasites, both in vitro and in an animal model. It blocks the active exit process, named egress, of merozoites and gametes from infected erythrocytes. UA2239 disrupts the essential cGMP-dependent egress pathway by decreasing cGMP levels in the parasite, making guanylate cyclase (PfGC) the most likely target. We also uncovered the remarkable molecular mechanism of resistance developed by parasites after prolonged exposure to the drug, which involves mutating not the target itself, but a downstream effector. The unique mechanism action of UA2239 makes it a valuable first-in-class candidate for further development and its ability to inhibit both parasite growth and transmission highlights its therapeutic potential as a dual-stage antimalarial agent.

microbiology↗

A computational platform for high-throughput analysis of RNA sequences and modifications by mass spectrometry

The field of epitranscriptomics is growing in importance, with chemical modification of RNA being associated with a wide variety of biological phenomena. A pivotal challenge in this area is the identification of modified RNA residues within their sequence contexts. Next-generation sequencing approaches are generally unable to capture modifications, although workarounds for some epigenetic marks exist. Mass spectrometry (MS) offers a comprehensive solution by using analogous approaches to shotgun proteomics. However, software support for the analysis of RNA MS data is inadequate at present and does not allow high-throughput processing. In particular, existing software solutions lack the raw performance and statistical grounding to efficiently handle the large variety of modifications present on RNA. We present a free and open-source database search engine for RNA MS data, called NucleicAcidSearchEngine (NASE), that addresses these shortcomings. We demonstrate the capability of NASE to reliably identify a wide range of modified RNA sequences in three original datasets of varying complexity. In a human tRNA sample, we characterize over 20 different modification types simultaneously and find many cases of incomplete modification.

bioinformatics↗