Multi-dimensional characterization and identification of sterols in untargeted LC-MS analysis using all ion fragmentation technology
- 1. University of Chinese Academy of Sciences, Beijing, 100049 (China)
- 2. Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai, 200032 (China)
Description
Highlights: • A LC-MS based all ion fragmentation (AIF) technology was developed for untargeted analysis of sterols in biological samples. • The integration of multi-dimensional properties supported unambiguous identification of sterols, including distinguishing sterol isomers. • AIF based multi-dimensional analysis provided a possibility to identify sterols without chemical standards and facilitated to discover novel compounds with sterol-like structures. Sterols are an important type of lipids, and play many important roles in physiological and pathological processes. However, comprehensive analysis of sterols especially identification of unknown sterols is challenging. In this work, LC-MS with all ion fragmentation (AIF) technology was developed for untargeted analysis of sterols in biological samples. AIF technology provided holistic and multi-dimensional characterization for both knowns and unknowns sterols, including accurate m/z, isotope pattern, retention time (RT), and co-eluted peak profiles between MS1 and MS2 ions in one analysis. We further developed an analysis strategy by integrating the multi-dimensional properties to support unambiguous identification of sterols, including distinguishing sterol isomers. The developed strategy enabled to identify a total of 23 sterols in mouse samples, and quantified 19 sterols in mouse liver tissues. More importantly, we demonstrated that AIF based multi-dimensional analysis provided a possibility to identify sterols without chemical standards and facilitated to discover novel compounds with sterol-like structures in biological samples. In summary, we employed the LC-MS based AIF technology to develop multi-dimensional characterization and identification of both known and unknown sterols in complex biological samples. The comprehensive analysis of sterols facilitates to provide molecular insights to many physiological and pathological activities in biology.
Availability note (English)
Available from http://dx.doi.org/10.1016/j.aca.2020.10.058Additional details
Identifiers
- DOI
- 10.1016/j.aca.2020.10.058;
- PII
- S0003267020310904;
Publishing Information
- Journal Title
- Analytica Chimica Acta
- Journal Volume
- 1142
- Journal Page Range
- p. 108-117
- ISSN
- 0003-2670
- CODEN
- ACACAM
INIS
- Country of Publication
- Netherlands
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 53101258
- Subject category
- S60: APPLIED LIFE SCIENCES; S37: INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL CHEMISTRY;
- Descriptors DEI
- ANIMAL TISSUES; BIOLOGICAL MATERIALS; ISOMERS; ISOTOPES; LIPIDS; LIVER; MANY-DIMENSIONAL CALCULATIONS; MICE; STEROLS
- Descriptors DEC
- ANIMALS; BODY; DIGESTIVE SYSTEM; GLANDS; HYDROXY COMPOUNDS; MAMMALS; MATERIALS; ORGANIC COMPOUNDS; ORGANS; RODENTS; STEROIDS; VERTEBRATES
Optional Information
- Copyright
- Copyright (c) 2020 Elsevier B.V. All rights reserved.