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

我们已经根据质谱法对单个反应监测进行了基于单个反应监测的绝对定量方法进行了调整。 我们使用巨噬细胞的破骨细胞发育作为初始实验模型。了解破骨细胞形成和作用的机制对于类风湿关节炎和骨质疏松症的研究对于进展至关重要。我们将表征良好的鼠巨噬细胞RAW 264.7细胞系用作破骨细胞前体模型细胞系。当用核因子kappa b配体（RANKL）刺激刺激刺激的细胞以形成多核破骨细胞（RANKL），但是分化过程受到鞘氨氨酸-1-磷酸盐（S1P）的抑制。与巨噬细胞分化与破骨细胞相关的蛋白质表达发生了变化。许多蛋白质的mRNA水平发生了变化，我们想看看这些变化是否反映在细胞蛋白质组的变化中。我们已经优化了细胞培养条件和破骨细胞富集的方法。使用SILAC（在细胞培养中使用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织。该分析显示了一组差异表达的蛋白质，我们用于设计一组标准肽，以通过质谱法进行绝对定量。我们还使用微阵列进行了mRNA表达分析，并确定了所有三种细胞类型之间的主要差异。具体而言，我们发现，与破骨细胞前体相比，多核破骨细胞通过下调与细胞周期控制，基因表达和蛋白质合成有关的途径来保护能量。与先前的报告一致，发现多核破骨细胞表达了相对较高的V-ATPase，TRAP，组织蛋白酶K和整联蛋白。在多核破骨细胞中，主要位于线粒体中的ATP合成和分解代谢的蛋白质也被上调，这表明与骨细胞前体和中间层状球菌相比，破骨细胞会上调ATP的产生。我们已经证实，在成熟的破骨细胞中，线粒体质量和电势均升高，线粒体蛋白表达的中位数明显高于其他细胞器中的中位蛋白表达。 S1P调节骨骼前体和从骨骼的化学提取和化学粘液。在此用作模型的鼠巨噬细胞RAW 264.7细胞为S1P：S1PR1和S1PR2表达两个受体。这些受体与S1P的亲和力明显不同，并对暴露于低/高浓度S1P的影响会产生相反的影响。为了对哺乳动物细胞趋化性有更深入的了解，我们使用了转录组学，shot弹枪蛋白质组学，靶向蛋白质组学和途径模拟来研究骨细胞前体的S1P介导的趋化性。使用RNA-Seq的转录组学使RNA转录本和shot弹枪蛋白质组学的鉴定和定量得以识别蛋白质型肽。靶肽的选择使用了多种标准，包括肽蛋白型品质，序列唯一性和易受修饰的脆弱性（例如氧化和脱氨酸），消除了许多理论上可能的肽，这些肽可能与质谱分析无兼容。我们使用了通过shot弹枪蛋白质组学从破骨细胞前体获得的定量数据来找到在Orbitrap Velos中分析的肽。斑点合成用于制备一组409个标准的合成肽，我们用来评估巨噬细胞和破骨细胞中的蛋白质表达。 RAW264.7细胞裂解物的单个反应监测（SRM）用标准肽尖峰导致对趋化因子信号网络中蛋白质的409肽靶标的208个自信鉴定和半定量。对在不同实验条件下差异表达的蛋白质的65个重型标记的，定量的内部肽标准品的SRM分析提供了绝对数量的分子。此外，在先验分析中遗漏的靶蛋白中获得了一组145个原油，未标记的肽，使用这些肽鉴定的蛋白质将使用下一组重型肽来靶向。然后，这些数据被用于设计小鼠趋化途径蛋白质的靶向蛋白质组学测定。 使用纳米流液色谱法与选定的反应监测质谱法（LC-SRM）结合的靶向蛋白质组学测定，以生成原始264.7细胞中每个靶蛋白的蛋白质绝对丰度值（以副本/细胞的单位/细胞为单位）。由于它们具有非常相似的S1P定向趋化性行为，因此RAW细胞再次被用作模型破骨细胞预防酶。基于规则的途径建模能够基于在硅生生细胞中三维的几何形状中基于双分子相互作用的小鼠趋化途径的模拟。靶向蛋白质组学测定产生的蛋白质绝对丰度值被用作使用Simmune的模拟参数。然后对模型进行了完善，并显示出在体外实验中成功预测趋化性数据的结果。   在这项研究中，我们利用具有转录组学的靶向蛋白质组学来帮助在小鼠单核细胞 - 巨噬细胞系中的LPS-TLR4信号通路的计算模型。从描述LPS-TLR4信号传导的当前文献和KEGG途径的回顾中确定了一组蛋白质靶标。根据几个标准，包括长度，shot弹枪蛋白质组学识别和潜在的PTM位点在得分后选择相应的肽，这些肽由基序预测（PubMed）确定的潜在PTM位点。在shot弹枪模式和SRM模式中分析了肽，以确定生物样品成功的潜力。用LPS刺激的原细胞样品为选定的肽分析。我们进行了半定量分析，并基于结果，我们针对相应的蛋白质靶标进行了重标记的内部肽标准标准，以进行绝对定量测量。我们获得的数据将与当前文献的回顾一起使用，以使用Simmune Modeler进行TLR4-LPS途径模拟。与Martin Meier-Schellersheim博士合作，我们创建了基于Simmune模型的基本蛋白质网络及其相互作用。 我们正在与Rajat Varma博士合作使用SRM方法，以探索白介素受体的伽马链使用情况的通用性。白介素IL-2，IL-4，IL-7，IL-9，IL-15和IL-21的受体具有共同的γ链，尚不清楚所有白介素受体如何使用该链来进行信号传导。当伽马链成为限制因素时，我们研究了这些白介素的信号传导途径。我们已经设计并获得了一组77个T细胞信号特异性肽，我们正在测试它们在该项目中使用。 参考： 1。A，Narayanan M，Manes NP和Nita-Lazar A.（2014）使用定量蛋白质组学和mRNA分析在破骨细胞发育过程中功能重编程的表征。 摩尔细胞蛋白质组学。 PII：MCP.M113.034371。 epub在印刷前