Application of a Novel Mass Spectral Data Acquisition Approach to Lipidomic Analysis of Liver Extracts from Sitaxentan-Treated Liver-Humanized PXB Mice.
Adam M KingMatthew BaginskiYoshio MorikawaPaul D RainvilleLee A GethingsIan D WilsonRobert S PlumbPublished in: Journal of proteome research (2019)
The application of a data-independent acquisition (DIA) method ("SONAR") that employs a rapidly scanning quadrupole is described for the lipidomic analysis of complex biological extracts. Using this approach, the MS acquisition window can be varied between 1 and 25 Da, enabling the isolation of ions prior to their entering the collision cell. By rapidly scanning the resolving quadrupole window over a specified mass range, co-eluting precursor ions are transmitted sequentially into the collision cell, where collision energies are cycled between low and elevated levels to induce fragmentation. This method of data generation provides both precursor and fragment ion information at high specificity, allowing for greater accuracy of compound identification, whether using a database, spectral libraries, or comparison to authentic standards. The value of the approach in simplifying and "de-cluttering" the spectra of co-eluting lipids is shown with examples from lipidomic profiles obtained in investigations of the composition of organic extracts of livers obtained from SCID and chimeric liver-humanized mice administered under various experimental conditions.
Keyphrases
- mass spectrometry
- cell therapy
- electronic health record
- single cell
- big data
- optical coherence tomography
- high resolution
- quantum dots
- high performance liquid chromatography
- tandem mass spectrometry
- high fat diet induced
- gas chromatography
- simultaneous determination
- stem cells
- electron microscopy
- density functional theory
- magnetic resonance imaging
- ms ms
- mesenchymal stem cells
- monoclonal antibody
- emergency department
- fatty acid
- machine learning
- bone marrow
- skeletal muscle
- newly diagnosed
- adverse drug
- artificial intelligence
- insulin resistance
- structural basis
- clinical evaluation