Location: Plant Genetics ResearchTitle: Quantification of peptide m/z distributions from 13C-labeled cultures with high resolution mass spectrometry Author
|Allen, Douglas - Doug|
Submitted to: Analytical Chemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/3/2014
Publication Date: 1/3/2014
Publication URL: http://handle.nal.usda.gov/10113/58574
Citation: Allen, D.K., Goldford, J., Gierse, J.K., Mandy, D., Diepenbrock, C.H., Libourel, I. 2014. Quantification of peptide m/z distributions from 13C-labeled cultures with high resolution mass spectrometry. Analytical Chemistry. 86:1894-1901. Interpretive Summary: Soybean seed composition including protein and oil production in seeds occurs in specific subcellular locations, however there are few experimental techniques that describe these processes. Mass spectrometry can be developed to measure metabolites in specific locations. This work describes the use of an advanced mass spectrometer along with computational methods necessary to mine mass spectral data in a semi-high throughput way. Soybeans were isotopically labeled (e.g. 13-carbon in the form of 13C-glucose) through culturing techniques. This led to isotopic labeling of soybean proteins that were analyzed by mass spectrometry. Two major soybean storage proteins, glycinin and beta conglycinin were analyzed. The proteins were processed by first cutting them with several enzymes to create peptides. The peptides were then inspected by mass spectrometry. We also performed more traditional analyses of amino acids by chemically hydrolyzing peptides and measuring the resulting amino acid labeling directly with gas chromatography mass spectrometry. The labeling in amino acids can be mathematically calculated to describe the labeling in the peptides, however as shown in this work the traditional measurement of amino acids does not adequately describe subcellular and temporal processes. Measurements of peptide labeling described here provides a superior level of information and therefore represents an important development to better characterize plant metabolism. These methods are necessary to improve our understanding of soybean metabolism and can guide efforts in metabolic engineering that aim to favorably alter the composition of the soybean.
Technical Abstract: With the introduction of orbital trap mass spectrometers molecular masses can be determined with great precision and accuracy. In addition, orbital trap spectrometers (Orbitraps) are sensitive and possess a linear dynamic range of multiple orders of magnitude. These qualities make the Orbitrap well-suited for both identification and quantification of compounds, and Orbitraps have become an instrument of choice for many proteomics applications. Orbitrap methods frequently include isotope labeling; therefore these instruments are potentially amenable to 13C metabolic flux analysis (MFA). Peptides synthesized from isotopically-labeled amino acids in metabolism, contain spatial and temporal information associated with the origin of the peptide, consequently, proteins that are expressed in a distinct tissue or during a specific developmental stage enable targeted metabolic studies. We investigated the suitability of Orbitrap measurements for isotope labeling quantification. Orbitrap spectra were carefully quantified; missing values were gap-filled; and standard deviations were estimated experimentally and compared to the expected multinomial sampling variance. Observed m/z distributions of labeled soy and E. coli peptides indicated no significant differences compared to simulated distributions. Gas chromatography mass spectrometry methods to quantify isotopic labeling in amino acids were extended and used with hydrolyzed protein from the same labeling experiments. The amino acids measured from GC-MS were mathematically convolved and compared with those obtained directly from the Orbitrap resulting in differences due to temporal labeling of proteins in metabolism. We conclude that Orbitrap measurements faithfully represent mass distributions, are suitable for quantification of isotope labeling-based studies, and are capable of assessing temporal differences in metabolism whereas other approaches cannot.