Absolute Quantification of Molecular Representation and Interaction

分子表示和相互作用的绝对定量

• 批准号: 8946468
• 负责人: Aleksandra Nita-Lazar
• 金额: $ 38.36万
• 依托单位: NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8946468
• 关键词: ATP Synthesis Pathway; Affinity; Agreement; Amino Acids; Behavior; Binding; Biological; Biological Assay; Catabolism; Cell Culture Techniques; Cell Cycle Regulation; Cell Line; Cells; Chemotaxis; Collaborations; Computer Simulation; Coupled; Data; Development; Experimental Models; Exposure to; Freedom; Gene Expression; Geometry; Immune system; In Vitro; Integrins; Interleukin 2 Receptor Gamma; Interleukin Receptor; Interleukin-15; Interleukin-2; Interleukin-4; Interleukin-7; Interleukin-9; Interleukins; Label; Length; Liquid Chromatography; Literature; Mammalian Cell; Mass Spectrum Analysis; Measurement; Mediating; Messenger RNA; Methodology; Methods; Mitochondria; Mitochondrial Proteins; Modeling; Modification; Molecular; Monitor; Mouse Protein; Mus; Organelles; Osteoclasts; Osteoporosis; Pathway interactions; Peptides; Printing; Process; Production; Protein Analysis; Protein Biosynthesis; Proteins; Proteome; Proteomics; PubMed; RNA; Reaction; Relative (related person); Reporting; Rheumatoid Arthritis; Sampling; Set protein; Shotguns; Signal Pathway; Signal Transduction; Site; Sphingosine-1-Phosphate Receptor; Stable Isotope Labeling; System; T-Lymphocyte; TLR4 gene; TRANCE protein; Testing; Transcript; base; bone; cathepsin K; cell type; chemokine; deamidation; design; mRNA Expression; macrophage; mathematical model; monocyte; nano; oxidation; protein expression; receptor; research study; simulation; sphingosine 1-phosphate; success; synthetic peptide; text searching; transcriptome sequencing; transcriptomics; vacuolar H+-ATPase

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

我们采用了基于使用质谱法的肽标准单反应监测的绝对定量方法。 我们使用巨噬细胞的破骨细胞发育作为初始实验模型。了解破骨细胞的形成和作用机制对于类风湿关节炎和骨质疏松症研究的进展至关重要。我们使用特征明确的小鼠巨噬细胞 RAW 264.7 细胞系作为破骨细胞前体模型细胞系。当用核因子 kappa B 配体受体激活剂 (RANKL) 刺激时，细胞融合形成多核破骨细胞，但分化过程受到 1-磷酸鞘氨醇 (S1P) 的抑制。与巨噬细胞分化为破骨细胞相关的蛋白质表达发生变化。许多蛋白质的 mRNA 水平发生变化，我们想看看这些变化是否反映在细胞蛋白质组的变化中。我们优化了破骨细胞富集的细胞培养条件和方法。使用 SILAC（细胞培养物中氨基酸的稳定同位素标记），我们比较了未经处理的 RAW 264.7 巨噬细胞、中间破骨细胞和分化的多核破骨细胞的蛋白质组。分析揭示了一组差异表达的蛋白质，我们用它们设计了一组标准肽，用于通过质谱法进行绝对定量。我们还使用微阵列进行 mRNA 表达分析，并确定了所有三种细胞类型之间的主要差异。具体来说，我们发现与破骨细胞前体相比，多核破骨细胞通过下调涉及细胞周期控制、基因表达和蛋白质合成的途径来节省能量。与之前的报道一致，发现多核破骨细胞表达相对较高水平的 V-ATP 酶、TRAP、组织蛋白酶 K 和整合素。参与 ATP 合成和分解代谢的蛋白质主要位于线粒体中，在多核破骨细胞中也上调，表明与破骨细胞前体和中间破骨细胞相比，破骨细胞上调 ATP 产生。我们已经证实成熟破骨细胞中线粒体质量和电位均升高，并且线粒体蛋白表达中值显着高于其他细胞器中蛋白表达中值。 S1P 调节破骨细胞前体进出骨骼的化学吸引和化学排斥。此处用作模型的鼠巨噬细胞 RAW 264.7 细胞表达两种 S1P 受体：S1PR1 和 S1PR2。这些受体对 S1P 的亲和力明显不同，并且在暴露于低/高浓度的 S1P 时会产生相反的效果。为了更深入地了解哺乳动物细胞趋化性，我们使用转录组学、鸟枪蛋白质组学、靶向蛋白质组学和途径模拟来研究 S1P 介导的破骨细胞前体趋化性。使用 RNA-seq 的转录组学能够识别和定量 RNA 转录本，而鸟枪法蛋白质组学能够识别蛋白型肽。目标肽的选择使用了多种标准，包括肽的蛋白型质量、序列独特性和修饰的脆弱性（例如氧化和脱酰胺），消除了许多理论上可能的肽，这些肽可能与质谱分析不兼容。我们利用鸟枪式蛋白质组学从破骨细胞前体获得的定量数据来寻找适合在 Orbitrap Velos 中分析的肽。 SPOT 合成用于制备一组 409 个标准合成肽，我们用它们来评估巨噬细胞和破骨细胞中的蛋白质表达。对掺有标准肽的 RAW264.7 细胞裂解物进行单反应监测 (SRM)，可对趋化因子信号网络中蛋白质的 409 个肽靶点中的 208 个进行可靠的鉴定和半定量。对来自不同实验条件下差异表达的蛋白质的较小组 65 个重标记定量内肽标准品进行 SRM 分析，提供了分子的绝对数量。此外，还获得了一组补充的 145 个粗制、未标记的肽，以靶向先前分析中遗漏的蛋白质，并且用这些肽鉴定的蛋白质将使用下一组重肽来靶向。然后将这些数据用于设计小鼠趋化途径蛋白质的靶向蛋白质组学测定。 使用纳流液相色谱结合选择反应监测质谱 (LC-SRM) 进行靶向蛋白质组学测定，以产生 RAW 264.7 细胞内每种靶蛋白的蛋白质绝对丰度值（以拷贝/细胞为单位）。 RAW 细胞再次被用作模型破骨细胞前体，因为它们具有非常相似的 S1P 定向趋化行为。基于规则的通路建模能够基于三维计算机原始细胞几何结构内的双分子相互作用模拟小鼠趋化通路。目标蛋白质组学测定产生的蛋白质绝对丰度值被用作使用 Simmune 进行模拟的参数。然后对该模型进行了改进，计算机结果显示可以成功预测体外实验的趋化性数据。   在这项研究中，我们利用靶向蛋白质组学和转录组学来帮助构建小鼠单核巨噬细胞系中 LPS-TLR4 信号通路的计算模型。通过对当前文献和描述 LPS-TLR4 信号传导的 KEGG 通路的回顾，确定了一组蛋白质靶标。根据几个标准评分后选择相应的肽，这些标准包括长度、鸟枪法蛋白质组学鉴定以及通过基序预测（Pubmed）进行文献挖掘确定的潜在 PTM 位点。在鸟枪模式和 SRM 模式下对肽进行分析，以确定在生物样品中成功的潜力。分析用 LPS 刺激的原始细胞样品中选定的肽。我们进行了半定量分析，并根据结果，我们订购了针对相应蛋白质靶标的重标记内肽标准品，以进行绝对定量测量。我们获得的数据将与当前文献综述一起使用，使用 Simmune Modeler 进行 TLR4-LPS 通路模拟。我们与 Martin Meier-Schellersheim 博士合作，为基于 Simmune 的模型创建了必需蛋白质及其相互作用的网络。 我们正在与 Rajat Varma 博士合作使用 SRM 方法来探索白细胞介素受体使用伽玛链的共性。白细胞介素 IL-2、IL-4、IL-7、IL-9、IL-15 和 IL-21 的受体共享一条共同的 γ 链，目前尚不清楚所有白细胞介素受体如何使用该链进行信号传导。我们研究了当伽马链成为限制因素时这些白细胞介素的信号传导途径。我们设计并获得了一组 77 种 T 细胞信号传导特异性肽，我们正在测试它们在该项目中的使用。 参考： 1. An E、Narayanan M、Manes NP 和 Nita-Lazar A. (2014) 使用定量蛋白质组学和 mRNA 分析表征破骨细胞发育过程中的功能重编程。 分子细胞蛋白质组学。 pii：mcp.M113.034371。电子版先于印刷版