The area of research termed metabolomics encompasses the study of a wide range of biomolecules that are products and substrates of enzymatic reactions within cells. One of the major subclasses of cellular metabolites are lipids, which they themselves are a diverse class of molecules that range from fatty acids, steroids, glycerolipids, glycerophospholipids, sphingolipids, and prenols. The measurement of lipids has significantly improved over the past decade, largely due to advances in mass spectrometry and various ancillary techniques. Lipids constitute an important class of compounds within the metabolomic sphere of interest because of the central role these molecules play, not only in separating compartments within cells through formation of lipid bilayers, but also through specific roles these molecules can play as precursor of signally molecules, targets for peroxidation chemistry, regulators of DNA expression, and even entities that are recognized by proteins that drive critical processes in normal cell biology. Within each class of lipids, there ae closely related molecules termed molecular species which increase the complexity of the lipid mixture and challenging analysis. Based upon recent advances we have made in using MALDI imaging mass spectrometry we propose that it will be possible to significantly increase the throughput of lipid analysis so that it will be possible to obtain important metabolomic information from several hundreds of samples per day on a fairly routine basis. Furthermore, we propose that this platform can be tuned to increase sensitivity for specific classes of lipids and used for high throughput lipidomic analysis to address specific questions concerning enzymatic pathways involved in lipid synthesis and metabolism. In part this approach will take advantage of the advances that have been made in the area of shotgun lipidomics coupled to the high throughput capability of MALDI mass spectrometry to yield both qualitative and quantitative information. Preliminary data shows that even untreated serum and plasma can yield information about the complex mixture of lipids present in this fluid without any further sample treatment except dilution. This data can be obtained within less than a minute in a form that can readily integrate into tools to automatically identify lipids as well as quantitate the abundance o lipids present. In order to carry out these studies, advanced mass spectrometric techniques will be used, including ion mobility technology to separate lipid ions from other compounds and impurities generated during the MALDI ionization process. The advanced mass spectrometric techniques to be developed can be implemented in many laboratories even without the ion mobility;however, ion mobility, as it becomes more widely available, provides a unique level of capability not currently present with other mass spectrometric system.

Public Health Relevance

Development of high throughput methods to measure the complex mixture of lipids present in biological samples, including serum, plasma, urine, as well as cells and tissues is challenging from the stand point of the degree of complexity of lipid components, but also the need to understand the quantitative levels of lipids present in these samples. A novel method to generate quantitative information concerning lipids is proposed based upon a MALDI ionization mass spectrometry platform and the use of database searching to identify lipids and internal standard quantitation to automatically convert mass spectrometric signals into quantitative measures of individual molecular species of lipids. The improvement of analytical throughput could have a significant bearing upon the reduction of costs in measuring these specific metabolites so that a large number samples including those in the 1,000s that have been collected in studies of specific human disorders can be analyzed to reveal the involvement of lipid biochemistry in disease processes.

Agency
National Institute of Health (NIH)
Institute
National Institute of Environmental Health Sciences (NIEHS)
Type
Research Project (R01)
Project #
5R01ES022172-02
Application #
8545850
Study Section
Special Emphasis Panel (ZRG1-BST-P (50))
Program Officer
Balshaw, David M
Project Start
2012-09-15
Project End
2017-05-31
Budget Start
2013-07-01
Budget End
2014-05-31
Support Year
2
Fiscal Year
2013
Total Cost
$360,839
Indirect Cost
$94,096
Name
University of Colorado Denver
Department
Pharmacology
Type
Schools of Medicine
DUNS #
041096314
City
Aurora
State
CO
Country
United States
Zip Code
80045
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