We have adapted the methods for absolute quantification and designed peptides for the modified AQUA method of MS-based quantification. We are developing and testing standards of tagged proteins (in collaboration with Dr. Iain Fraser). We used the osteoclast development from macrophages as the initial experimental model. Understanding the mechanisms of osteoclast formation and action is crucial for the progress in the studies of rheumatoid arthritis and osteoporosis. We studied the well characterized murine macrophage RAW 264.7 cell line. The cells fuse to form multinucleated osteoclasts when stimulated with receptor activator of nuclear factor kappa B ligand (RANKL), but the differentiation process is inhibited by sphingosine-1 -phosphate (S1P). There are changes in protein expression connected with macrophage differentiation into osteoclasts. The mRNA levels of many proteins change and we wanted to see if these changes are reflected in the changes of the cell proteome. We have optimized the cell culture conditions and osteoclast enrichment. Using SILAC (stable isotope labeling with amino acids in cell culture) we compared the proteomes of untreated RAW 264.7 macrophages, intermediate osteoclasts and differentiated, multinucleated osteoclasts. The analysis revealed a set of differentially expressed proteins, which we used to design a set of standard peptides for absolute quantification by mass spectrometry. We have performed also mRNA expression analysis using microarrays and identified major differences between all three cell types. Specifically, we found evidence that compared to osteoclast precursors, multinucleated osteoclasts conserve energy by down-regulating pathways involved in cell cycle control, gene expression, and protein synthesis. Similarly to previous reports, multinucleated osteoclasts were found to express relatively high levels of V-ATPase, TRAP, cathepsin K, and integrins. Proteins involved in ATP synthesis and catabolism, localized primarily in the mitochondria, were also upregulated in multinucleated osteoclasts, suggesting that osteoclasts up-regulate ATP production compared with osteoclast precursors and intermediate osteoclasts. We have confirmed that both mitochondrial mass and potential are elevated in mature osteoclasts, and median mitochondrial protein expression was significantly higher than the median protein expression in other organelles. The manuscript describing these findings has been submitted. S1P regulates the chemoattraction and chemorepulsion of osteoclast precursors to and from the bones. The murine macrophage RAW 264.7 cells, used here as a model, express two receptors for S1P: S1PR1 and S1PR2. These receptors have markedly different affinity to S1P and cause the opposite effects of the exposure to the low/high concentrations of S1P. In order to obtain data necessary for the modeling of the S1P mediated chemotaxis, a set of mouse chemotaxis pathway target proteins was constructed from a literature and pathway database search. Selection of the target peptides used a wide variety of criteria including peptide proteotypic qualities, sequence uniqueness, and vulnerability to modification (e.g., oxidation and deamidation), eliminating many theoretically possible peptides, which could be non-compatible with the mass spectrometric analysis. We used the quantitative data obtained from osteoclast precursors by shotgun proteomics to find the peptides amenable to the analysis in our Orbitrap Velos. SPOT synthesis was used to prepare a set of 409 standard, synthetic peptides, which we used to assess the protein expressions in macrophages and osteoclasts. Single Reaction Monitoring (SRM) of RAW264.7 cell lysates spiked with the standard peptides resulted in the confident identification and semi-quantitation of 208 of the 409 peptide targets from proteins in the chemokine signaling network. The SRM analysis of a narrower set of 65 heavy-labeled, quantitated internal peptide standards from proteins differentially expressed under different experimental conditions provided absolute numbers of molecules. Additionally, a supplementary set of 145 crude, unlabeled peptides was obtained to target the missed proteins and the proteins identified with these peptides will be targeted using the next set of heavy peptides. Quantitative pathway simulation is being performed using Simmune Modeler (in collaboration with Dr. Martin Meier-Schellersheim). We have obtained a robust pipeline to use for absolute quantification of proteins in other projects and we are currently writing the manuscript describing this work. We are using the SRM approach in the collaboration with Dr. Rajat Varma on the exploration of the commonality of gamma chain in interleukin receptors. The receptors for interleukins IL-2, IL-4, IL-7, IL-9, IL-15 and IL-21 share a common gamma chain, and it is not known how all the interleukin receptors use this chain for signaling. We study the signaling pathways of these interleukins under the conditions when the gamma chain becomes the limiting factor. We have designed and obtained a set of 77 T-cell signaling-specific peptides and we are testing them for use in this project.

Project Start
Project End
Budget Start
Budget End
Support Year
5
Fiscal Year
2013
Total Cost
$356,545
Indirect Cost
City
State
Country
Zip Code
Manes, Nathan P; Nita-Lazar, Aleksandra (2018) Application of targeted mass spectrometry in bottom-up proteomics for systems biology research. J Proteomics 189:75-90
Manes, Nathan P; Nita-Lazar, Aleksandra (2017) The development of SRM assays is transforming proteomics research. Proteomics 17:
Manes, Nathan P; Angermann, Bastian R; Koppenol-Raab, Marijke et al. (2015) Targeted Proteomics-Driven Computational Modeling of Macrophage S1P Chemosensing. Mol Cell Proteomics :
Manes, Nathan P; Mann, Jessica M; Nita-Lazar, Aleksandra (2015) Selected Reaction Monitoring Mass Spectrometry for Absolute Protein Quantification. J Vis Exp :e52959
An, Eunkyung; Narayanan, Manikandan; Manes, Nathan P et al. (2014) Characterization of functional reprogramming during osteoclast development using quantitative proteomics and mRNA profiling. Mol Cell Proteomics 13:2687-704
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