A comprehensive IDA and SWATH-DIA Lipidomics and Metabolomics dataset

Autor(en)

Ammar Tahir, Agnes Draxler, Tamara Stelzer, Amelie Blaschke, Brenda Laky, Marton Széll, Jessica Binar, Viktoria Bartak, Laura Bragagna, Lina Maqboul, Theresa Herzog, Rainer Thell, Karl-Heinz Wagner

Abstrakt

A significant hurdle in untargeted lipid/metabolomics research lies in the absence of reliable, cross-validated spectral libraries, leading to a considerable portion of LC-MS features being labeled as unknowns. Despite continuous advancement in annotation tools and libraries, it is important to safeguard, publish and share acquired data through public repositories. Embracing this trend of data sharing not only promotes efficient resource utilization but also paves the way for future repurposing and in-depth analysis; ultimately advancing our comprehension of Covid-19 and other diseases. In this work, we generated an extensive MS-dataset of 39 Covid-19 infected patients versus age- and gender-matched 39 healthy controls. We implemented state of the art acquisition techniques including IDA and SWATH-DIA to ensure a thorough insight in the lipidome and metabolome, ensuring a repurposable dataset.

Organisation(en)

Department für Pharmazeutische Wissenschaften, Department für Ernährungswissenschaften, Forschungsplattform Active Ageing

Externe Organisation(en)

FH Campus Wien, Klinik Donaustadt, Medizinische Universität Wien, Austrian Society of Regenerative Medicine, Vienna, Austria., Sigmund Freud Privatuniversität

Journal

Scientific Data

Band

11

Anzahl der Seiten

12

ISSN

2052-4463

DOI

https://doi.org/10.1038/s41597-024-03822-y

Publikationsdatum

09-2024

Peer-reviewed

Ja

ÖFOS 2012

303009 Ernährungswissenschaften

Schlagwörter

ASJC Scopus Sachgebiete

Information systems, Education, Library and Information Sciences, Statistics and Probability, Computer Science Applications, Statistics, Probability and Uncertainty

Link zum Portal

https://ucrisportal.univie.ac.at/de/publications/a150a6f1-612e-4971-9da2-c46c649923e8