Phosphorothioate RNA Analysis by NETD Tandem Mass Spectrometry.

Therapeutic RNAs are routinely modified during their synthesis to ensure proper drug uptake, stability, and efficacy. Phosphorothioate (PS) RNA, molecules in which one or more backbone phosphates are modified with a sulfur atom in place of standard nonbridging oxygen, is one of the most common modifications because of ease of synthesis and pharmacokinetic benefits. Quality assessment of RNA synthesis, including modification incorporation, is essential for drug selectivity and performance, and the synthetic nature of the PS linkage incorporation often reveals impurities. Here, we present a comprehensive analysis of PS RNA via tandem mass spectrometry (MS). We show that activated ion-negative electron transfer dissociation MS/MS is especially useful in diagnosing PS incorporation, producing diagnostic a- and z-type ions at PS linkage sites, beyond the standard d- and w-type ions. Analysis using resonant and beam-type collision-based activation reveals that, overall, more intense sequence ions and base-loss ions result when a PS modification is present. Furthermore, we report increased detection of b- and x-type product ions at sites of PS incorporation, in addition to the standard c- and y-type ions. This work reveals that the gas-phase chemical stability afforded by sulfur alters RNA dissociation and necessitates inclusion of additional product ions for MS/MS of PS RNA.

Large-Scale Multi-omic Analysis of COVID-19 Severity.

We performed RNA-seq and high-resolution mass spectrometry on 128 blood samples from COVID-19-positive and COVID-19-negative patients with diverse disease severities and outcomes. Quantified transcripts, proteins, metabolites, and lipids were associated with clinical outcomes in a curated relational database, uniquely enabling systems analysis and cross-ome correlations to molecules and patient prognoses. We mapped 219 molecular features with high significance to COVID-19 status and severity, many of which were involved in complement activation, dysregulated lipid transport, and neutrophil activation. We identified sets of covarying molecules, e.g., protein gelsolin and metabolite citrate or plasmalogens and apolipoproteins, offering pathophysiological insights and therapeutic suggestions. The observed dysregulation of platelet function, blood coagulation, acute phase response, and endotheliopathy further illuminated the unique COVID-19 phenotype. We present a web-based tool (covid-omics.app) enabling interactive exploration of our compendium and illustrate its utility through a machine learning approach for prediction of COVID-19 severity.

Large-scale Multi-omic Analysis of COVID-19 Severity.

We performed RNA-Seq and high-resolution mass spectrometry on 128 blood samples from COVID-19 positive and negative patients with diverse disease severities. Over 17,000 transcripts, proteins, metabolites, and lipids were quantified and associated with clinical outcomes in a curated relational database, uniquely enabling systems analysis and cross-ome correlations to molecules and patient prognoses. We mapped 219 molecular features with high significance to COVID-19 status and severity, many involved in complement activation, dysregulated lipid transport, and neutrophil activation. We identified sets of covarying molecules, e.g., protein gelsolin and metabolite citrate or plasmalogens and apolipoproteins, offering pathophysiological insights and therapeutic suggestions. The observed dysregulation of platelet function, blood coagulation, acute phase response, and endotheliopathy further illuminated the unique COVID-19 phenotype. We present a web-based tool (covid-omics.app) enabling interactive exploration of our compendium and illustrate its utility through a comparative analysis with published data and a machine learning approach for prediction of COVID-19 severity.

Ribonucleic Acid Sequence Characterization by Negative Electron Transfer Dissociation Mass Spectrometry.

Modified oligonucleotides represent a promising avenue for drug development, with small interfering RNAs (siRNA) and microRNAs gaining traction in the therapeutic market. Mass spectrometry (MS)-based analysis offers many benefits for characterizing modified nucleic acids. Negative electron transfer dissociation (NETD) has proven valuable in sequencing oligonucleotide anions, particularly because it can retain modifications while generating sequence-informative fragments. We show that NETD can be successfully implemented on a widely available quadrupole-Orbitrap-linear ion trap mass spectrometer that uses a front-end glow discharge source to generate radical fluoranthene reagent cations. We characterize both unmodified and modified ribonucleic acids and present the first application of activated-ion negative electron transfer dissociation (AI-NETD) to nucleic acids. AI-NETD achieved 100% sequence coverage for both a 6-mer (5'-rGmUrArCmUrG-3') with 2'-O-methyl modifications and a 21-mer (5'-rCrArUrCrCrUrCrUrArGrArGrGrArUrArGrArArUrG-3'), the luciferase antisense siRNA. Both NETD and AI-NETD afforded complete sequence coverage of these molecules while maintaining a relatively low degree of undesired base-loss products and internal products relative to collision-based methods.