We have adapted the methods for absolute quantification based on the Single Reaction Monitoring with peptide standards using mass spectrometry. We used osteoclast development from macrophages as the initial experimental model. Understanding the mechanisms of osteoclast formation and action is crucial for progress in studies of rheumatoid arthritis and osteoporosis. We used the well characterized murine macrophage RAW 264.7 cell line as the osteoclast precursor model 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 changes of the cell proteome. We have optimized cell culture conditions and methods for 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 also performed mRNA expression analysis using microarrays and identified major differences between all three cell types. Specifically, we found that compared to osteoclast precursors, multinucleated osteoclasts conserve energy by down-regulating pathways involved in cell cycle control, gene expression, and protein synthesis. In agreement with 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. S1P regulates the chemoattraction and chemorepulsion of osteoclast precursors to and from 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 upon exposure to low/high concentrations of S1P. To develop a deeper understanding of mammalian cell chemotaxis, we used transcriptomics, shotgun proteomics, targeted proteomics, and pathway simulation to investigate S1P-mediated chemotaxis of osteoclast precursors. Transcriptomics using RNA-seq enabled the identification and quantitation of RNA transcripts and shotgun proteomics enabled the identification of proteotypic peptides. 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 mass spectrometric analysis. We used the quantitative data obtained from osteoclast precursors by shotgun proteomics to find the peptides amenable to 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 smaller 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 proteins missed in the prior analysis and the proteins identified with these peptides will be targeted using the next set of heavy peptides. These data were then used to design targeted proteomics assays of the proteins of the mouse chemotaxis pathway. Targeted proteomics assays using nano-flow liquid chromatography coupled to selected reaction monitoring mass spectrometry (LC-SRM) were performed to produce protein absolute abundance values (in units of copies/cell) for each of the target proteins within RAW 264.7 cells. RAW cells were again used as model osteoclast precusors because they have very similar S1P-directed chemotaxis behavior. Rules-based pathway modeling enabled the simulation of the mouse chemotaxis pathway based on bi-molecular interactions within the geometry of a three-dimensional in silico RAW cell. The protein absolute abundance values resulting from the targeted proteomics assays were used as parameters for the simulations using Simmune. The model was then refined, and the in silico results were shown to successfully predict chemotaxis data from in vitro experiments. In this study, we utilize targeted proteomics with transcriptomics to aid in contructing a computational model of the LPS-TLR4 signaling pathway in a mouse monocyte-macrophage cell line. A set of protein targets was identified from a review of current literature and KEGG pathways describing LPS-TLR4 signaling. Corresponding peptides were selected after scoring based on several criteria including length, shotgun proteomics identification, and potential PTM sites as determined by literature mining by motif prediction (Pubmed). Peptides were analyzed in both shotgun-mode and SRM-mode to determine the potential for success in biological samples. RAW cell samples stimulated with LPS were analyzed for the selected peptides. We performed semi-quantitative analysis and based on the results, we have ordered heavy-labeled internal peptide standards against corresponding protein targets for absolute quantitation measurements. The data we obtain will be used together with the review of current literature to perform TLR4-LPS pathway simulation using the Simmune Modeler. In collaboration with Dr. Martin Meier-Schellersheim, we have created the network of essential proteins and their interactions for the Simmune-based model. We are using the SRM approach in collaboration with Dr. Rajat Varma for exploration of the commonality of gamma chain usage by 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 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. References: 1. An E, Narayanan M, Manes NP, and Nita-Lazar A. (2014) Characterization of functional reprogramming during osteoclast development using quantitative proteomics and mRNA profiling. Mol Cell Proteomics. pii: mcp.M113.034371. Epub ahead of print
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