Software and Computational Tools for LC-MS-Based Epilipidomics: Challenges and Solutions
January 2023.
Tito Damiani, Stefano Bonciarelli, Gerhard G Thallinger, Nikolai Koehler, Christoph A Krettler, Arif K Saliho
A platelet lipidomics signature in patients with COVID-19
A platelet lipidomics signature in patients with COVID-19
December 2023.
Laura Goracci, Eleonora Petito, Alessandra Di Veroli, Emanuela Falcinelli, Caterina Bencivenga, Elisa Giglio, Cecilia Becattini, Edoardo De Robertis, Gaetano Vaudo, Paolo Gresele
Abstract
Ischemic cardiovascular and venous thromboembolic events are a frequent cause of death in severe COVID-19 patients. Platelet activation plays a key role in these complications, however platelet lipidomics have not been studied yet. The aim of our pilot investigation was to perform a preliminary study of platelet lipidomics in COVID-19 patients compared to healthy subjects. Lipid extraction and identification of ultrapurified platelets from eight hospitalized COVID-19 patients and eight age- and sex-matched healthy controls showed a lipidomic pattern almost completely separating COVID-19 patients from healthy controls. In particular, a significant decrease of ether phospholipids and increased levels of ganglioside GM3 were observed in platelets from COVID-19 patients. In conclusion, our study shows for the first time that platelets from COVID-19 patients display a different lipidomics signature distinguishing them from healthy controls, and suggests that altered platelet lipid metabolism may play a role in viral spreading and in the thrombotic complications of COVID-19.
Keywords: COVID-19; Platelet lipidomics.
Analysis of Phosphatidylinositol Modifications by Reactive Nitrogen Species Using LC-MS: Coming to Grips with Their Nitroxidative Susceptibility
Analysis of Phosphatidylinositol Modifications by Reactive Nitrogen Species Using LC-MS: Coming to Grips with Their Nitroxidative Susceptibility
July 2023.
Stefano Bonciarelli, Bruna Neves, Pedro Domingues, Tânia Melo, Laura Goracci, Maria Rosário Domingues
Abstract
Phosphatidylinositols (PIs) are complex lipids that play a key role in cell signaling. Like other phospholipids, they are esterified with unsaturated fatty acyl residues (FAs), making them susceptible to modification by reactive oxygen and nitrogen species (RNS). Recent studies using mass spectrometry (MS)-based lipidomics approaches have revealed that lipid nitration results in a plethora of structurally and chemically modified lipids (epilipids), including nitrated and nitroxidized derivatives of phosphatidylcholines, phosphatidylethanolamines, phosphatidylserines, and cardiolipins. However, there is a notable lack of knowledge regarding the characterization of RNS-modified PI derivatives. In this study, we used C18 high-resolution liquid chromatography-tandem MS approaches to describe the fragmentation signature of nitrated and nitroxidized PIs, bearing different fatty acyl chains. Using this approach and accurate mass measurements, we were able to identify nitro- PI derivatives, dinitro- and nitrohydroxy- derivatives for a few PI species. The data showed the typical neutral loss of nitrous acid (HNO2) as well as the fragmentation patterns corresponding to modified fatty acyl chains (such as NOx-RCOO–, [M – NOx-RCOOH – H]– and [M – NOx-RCOOH – C6H10O5 – H]–), making it possible to identify these epilipids. The susceptibility of PIs to nitration was also investigated, revealing that it depends exclusively on the chains of unsaturated FAs esterified in PI, showing a higher conversion rate for those with C18:1. Overall, the knowledge gathered in this study will contribute to the precise characterization of these epilipids in complex biological samples, offering new opportunities to unveil the pathophysiological roles of nitrated and nitroxidized PI derivatives at the cellular and tissue levels.
Keywords: LC-MS; lipidomics; nitration; nitrative stress; nitroxidative stress.
User Meeting Agenda
Wednesday 12th October
15.00h General presentation about Mass Analytica.
Gabriele Cruciani & Ismael Zamora. Molecular Discovery & Lead Molecular Design.
15.30h ONIRO: an efficient tool for Biotransformation studies.
Christophe Bouillod. Servier
16.00h How we use MassMetaSite and ONIRO in metabolite identification work at AstraZeneca, Gothenburg
Anja Ekdahl – AstraZeneca
16.30h Use of ONIRO
Virginie Gosselin – Sanofi
17.00h Roche/Biotransformation group
Bernd Steinhuber. F.Hoffmann La-Roche
17.30h Strategy for elucidation of VHH constructs (NANOBODY®)
Sabrina Schmeier – Sanofi
18.00h Harmonizing Discovery Workflows between Waters and Molecular Discovery
Russell Mortishire-Smith and David Heywood – Waters
Thursday 13th October
09.00h HRMS based Quantitation enabled through Automated Data Processing
Kevin Bateman – Merck
09.30h Quantification studies in ADME
Ismael Zamora. Lead Molecular Design
10.30h Macromolecule degradation studies
Fabien Fontaine / Luca Morettoni. Lead Molecular Design / Molecular Discovery
11.30h EAD vs CID Fragmentation for Small Molecule and their Metabolites
Christopher Kochansky – Exelisis
12.00h Benefits & challenges of software aided MetID
Christine Maurer – Merck Group
14.30h Lipostar 2 (the present) & MARS (on the way)
Laura Goracci. Molecular Discovery
15.00h In-depth and high throughput lipidomics solutions with Lipostar
Michele Wölk. Technische Universität Dresden
15.30h Add spatial dimension to your omics and metID: LipostarMSI and Pyxis for mass spec imaging data analysis”
Sara Tortorella. Molecular Horizon
16.00h Towards multimodal mass spectrometry analysis for cancer pathology assessment: current progress and unmet need.
Arash Zarrine. University of Toronto
16.30h How we use LipostarMSI and Pyxis at M4i and where to go from here
Tim Hendriks – Maastricht MultiModal Molecular Imaging Institute (M4i), The Netherlands
Friday 14th October
09.00h Compound Library: Model building
Ismael Zamora
9:30h Fase 2: Metabolism prediction
Gabriele Cruciani
10,30h Roundtable discussion
Automated identification of potential pesticides residues in fruit samples using HRMS data
Automated identification of potential pesticides residues in fruit samples using HRMS data
70th ASMS Conference on Mass Spectrometry. June 2022
Elisabeth Ortega1; Ismael Zamora1; Pol Giménez1; Luca Morettoni1; Roberto Romero-gonzalez2; Rosalía Lopez-Ruiz2; Antonia Garrido Frenich2
1Lead Molecular Design, S.L., Sant Cugat del Valles, Spain; 2Research Group ‘Analytical Chemistry of Contaminants’, Department of Chemistry and Physics, Research Centre for Agricultural and Food Biotechnology (BITAL), Agrifood Campus of International Excellence, University of Almeria, Almeria, Spain
Abstract
Introduction
In food safety and related fields, High Resolution Mass Spectrometry techniques applied for multiresidue analysis had become an alternative to the historical routine procedures involving triple quadrupole instruments. This evolution was mainly driven by the possibility to interrogate hundreds or thousands of compounds without a prior individual study of all of them. However, due to the big amount of information that can be generated during the data acquisition, the later data processing and data analysis steps can be quite time demanding. In this presentation we will show how this late step could be automized using Chemical Monitoring workflow included in MassChemSite 3.1.
Methods
For chromatographic analysis, Thermo Fisher Scientific Vanquish Flex Quaternary LC (Thermo Scientific Transcend™, Thermo Fisher Scientific, San Jose, CA, USA) was used. The chromatographic system is coupled to a hybrid mass spectrometer Q-Exactive Orbitrap Thermo Fisher Scientific (ExactiveTM, Thermo Fisher Scientific, Bremen, Germany) using an electrospray interface (ESI) (HESI-II, Thermo Fisher Scientific, San Jose, CA, USA) in positive-negative mode. ESI parameters were as follows: spray voltage, 4 kV; sheath gas (N2, 95%), 35 (adimensional); auxiliary gas (N2, 95%), 10 (adimensional); S-lens RF level, 50 (adimensional); heater temperature, 305 °C; and capillary temperature, 300 °C.
Data processing has been done using MassChemSite 3.1 (Molecular Discovery, Ltd. Borehamwood, UK). Data analysis was performed in ONIRO server (Molecular Discovery, Ltd. Borehamwood, UK).
Preliminary data
Strawberry, white grape and orange samples providing from Almeria (Spain) greenhouses were acquired in the University of Almería and processed using the Chemical Monitoring data workflow included in MassChemSite 3.1. Data was interrogated against an in-house pesticide database generated by literature search including up to 1500 different pesticides. From the total, up to 10 different pesticides were detected in all the samples in less than five minutes of data processing.
The identification step was performed using the MS and MSMS information: MS was used to detect the pesticide in the sample, while fragmentation information was used to finally elucidate the structure of the detected pesticide, by means of a computational fragmentation of the detected pesticide and a later assignation to the MSMS data provided by the instrument. The fitting among computed and experimental fragments is reported as “score” which can be used to discriminate among other structural isobaric compounds associated to the same chromatographic peak.
Data analysis and reporting were done in ONIRO server after an automatic uploading of the raw data. Later filtering steps were applied and tracked by the application for further inspection. Additionally, a final report was generated automatically once the experiment was reviewed. Data generated during the acquisition remained on the server for later use or further re-analysis.
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