Relevant bibliographies by topics / Quantitative proteomic analysis

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Quantitative proteomic analysis'

Author: Grafiati
Published: 4 June 2021
Last updated: 2 February 2022

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Journal articles on the topic "Quantitative proteomic analysis"

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Kamal, Abu Hena Mostafa, Jong-Soon Choi, Yong-Gu Cho, Hong-Sig Kim, Beom-Heon Song, Chul-Won Lee, and Sun-Hee Woo. "Comprehensive proteome analysis using quantitative proteomic technologies." Journal of Plant Biotechnology 37, no. 2 (June 30, 2010): 196–204. http://dx.doi.org/10.5010/jpb.2010.37.2.196.

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Yaacob, Mohamad Fakhri, Nur Anisah Johari, Alya Nur Athirah Kamaruzzaman, and Mohd Fakharul Zaman Raja Yahya. "Mass Spectrometry-Based Proteomic Investigation of Heterogeneous Biofilms: A Review." Scientific Research Journal 18, no. 2 (September 1, 2021): 67–87. http://dx.doi.org/10.24191/srj.v18i2.11718.

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Biofilm represents a major public health concern. It is a highly structured and heterogeneous microbial population that is well protected by a hydrated extracellular matrix. In most cases, the difficulties in combating a wide spectrum of biofilm-associated diseases are due to the presence of dormant cells and differential molecular expression. Proteomics is the large-scale and systematic study of cellular proteome expression at any given time by mass spectrometry. It allows high-sensitivity and high-specificity identification of differentially expressed proteins in the biofilms. Over the past few decades, multiple lines of proteomic works have successfully elucidated various aspects of the biofilm including developmental stages, antimicrobial resistance, and survival mechanisms. However, the heterogeneity of biofilms may contribute to inconsistent proteome expression throughout a proteomic experiment. This is due to the fact that the mature biofilm is often associated with the mixture between monolayer and multilayer biofilms, thick microbial population, and chemical gradient of nutrients. This review highlights the biofilm heterogeneities, the principle of mass spectrometry in proteomics, and the possible strategies for quantitative proteomic analysis of heterogeneous biofilms. It is suggested that isolation of monolayer biofilm, laser capture microdissection, flow cytometry, and subtractive proteome profiling may be considered for an accurate and reliable quantitative proteomics experiment.
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Chignell, Jeremy F., Christin Schlegel, Roland Ulber, and Kenneth F. Reardon. "Quantitative proteomic analysis ofLactobacillus delbrueckiissp.lactisbiofilms." AIChE Journal 64, no. 12 (October 31, 2018): 4341–50. http://dx.doi.org/10.1002/aic.16449.

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Eckersall, David. "321 ASAS-EAAP Talk: Quantitative proteomics in animal and veterinary science: a pipeline for exploiting advanced analytical technology." Journal of Animal Science 98, Supplement_4 (November 3, 2020): 55–56. http://dx.doi.org/10.1093/jas/skaa278.100.

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Abstract Application of proteomic investigation to veterinary and animal sciences has grown over the last decade, but has still not reached its full potential of application in animal health and production research [1]. Nevertheless, establishing a versatile methodology has allowed the application of quantitative proteomics for increased understanding of physiological and pathophysiological challenges, and especially to identify potential biomarkers of disease in a range of animal species. A pipeline of sample preparation and mass spectrometry followed by statistical, bioinformatic and biochemical analyses has been established to deal with biofluids and tissue samples from cattle, sheep, pigs, chickens, dogs and cats as well as wild animals. Quantitative proteomic investigation of milk in an experimental model of Streptococcus uberis mastitis of dairy cows has identified potential novel biomarkers with implications for diagnosis and treatment of this major disease. Proteins in milk which have potential as disease biomarkers, such as cathelicidin, haptoglobin and mammary associated serum amyloid A3, are significantly increased in abundance during bovine mastitis. Proteomic investigation has confirmed that these biomarkers are also increased in milk during subclinical and clinical mastitis. Proteomic analysis of plasma from chicken following stimulation of the inflammatory response to Escherichia coli lipopolysaccharide endotoxin has characterised major changes in the chicken plasma proteome. Novel biomarker candidates of hemopexin and fatty acid binding protein have been identified. This proteomic pipeline can be incorporated into many areas of research, providing novel findings at the forefront of animal and veterinary science. Such proteomic investigation requires close interdisciplinary collaboration between experts in mass spectrometry, bioinformatics, statistics and animal production in order to fully exploit recent technological advances in the omic sciences.[1] P. Bilic, et al, Proteomics in Veterinary Medicine and Animal Science: Neglected Scientific Opportunities with Immediate Impact, Proteomics. 47 (2018) 1–7. doi:10.1002/pmic.201800047.
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Tsai, Chia-Feng, Rui Zhao, Sarah M. Williams, Ronald J. Moore, Kendall Schultz, William B. Chrisler, Ljiljana Pasa-Tolic, et al. "An Improved Boosting to Amplify Signal with Isobaric Labeling (iBASIL) Strategy for Precise Quantitative Single-cell Proteomics." Molecular & Cellular Proteomics 19, no. 5 (March 3, 2020): 828–38. http://dx.doi.org/10.1074/mcp.ra119.001857.

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Mass spectrometry (MS)-based proteomics has great potential for overcoming the limitations of antibody-based immunoassays for antibody-independent, comprehensive, and quantitative proteomic analysis of single cells. Indeed, recent advances in nanoscale sample preparation have enabled effective processing of single cells. In particular, the concept of using boosting/carrier channels in isobaric labeling to increase the sensitivity in MS detection has also been increasingly used for quantitative proteomic analysis of small-sized samples including single cells. However, the full potential of such boosting/carrier approaches has not been significantly explored, nor has the resulting quantitation quality been carefully evaluated. Herein, we have further evaluated and optimized our recent boosting to amplify signal with isobaric labeling (BASIL) approach, originally developed for quantifying phosphorylation in small number of cells, for highly effective analysis of proteins in single cells. This improved BASIL (iBASIL) approach enables reliable quantitative single-cell proteomics analysis with greater proteome coverage by carefully controlling the boosting-to-sample ratio (e.g. in general <100×) and optimizing MS automatic gain control (AGC) and ion injection time settings in MS/MS analysis (e.g. 5E5 and 300 ms, respectively, which is significantly higher than that used in typical bulk analysis). By coupling with a nanodroplet-based single cell preparation (nanoPOTS) platform, iBASIL enabled identification of ∼2500 proteins and precise quantification of ∼1500 proteins in the analysis of 104 FACS-isolated single cells, with the resulting protein profiles robustly clustering the cells from three different acute myeloid leukemia cell lines. This study highlights the importance of carefully evaluating and optimizing the boosting ratios and MS data acquisition conditions for achieving robust, comprehensive proteomic analysis of single cells.
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Arnold, Georg J., and T. Frohlich. "Dynamic proteome signatures in gametes, embryos and their maternal environment." Reproduction, Fertility and Development 23, no. 1 (2011): 81. http://dx.doi.org/10.1071/rd10223.

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Comprehensive molecular analysis at the level of proteins represents a technically demanding, but indispensable, task since several post-transcriptional regulation mechanisms disable a valid prediction of quantitative protein expression profiles from transcriptome analysis. In crucial steps of gamete and early embryo development, de novo transcription is silenced, meaning that almost all macromolecular events take place at the level of proteins. In this review, we describe selected examples of dynamic proteome signatures addressing capacitation of spermatozoa, in vitro maturation of oocytes, effect of oestrous cycle on oviduct epithelial cells and embryo-induced alterations to the maternal environment. We also present details of the experimental strategies applied and the experiments performed to verify quantitative proteomic data. Far from being comprehensive, examples were selected to cover several mammalian species as well as the most powerful proteomic techniques currently applied. To enable non-experts in the field of proteomics to appraise published proteomic data, our examples are preceded by a customised description of quantitative proteomic methods, covering 2D difference gel electrophoresis (2D-DIGE), nano-liquid chromatography combined with tandem mass spectrometry, and label-free as well as stable-isotope labelling strategies for mass spectrometry-based quantifications.
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KANAZAWA, Mitsuhiro, Hisae ANYOJI, Hsiao-kun TU, Umpei NAGASHIMI, and Atsushi OGIWARA. "Quantitative Proteomic Analysis System: i-OPAL." Journal of Computer Chemistry, Japan 9, no. 4 (2010): 197–204. http://dx.doi.org/10.2477/jccj.h2117.

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Huang, He, Shu Lin, Benjamin A. Garcia, and Yingming Zhao. "Quantitative Proteomic Analysis of Histone Modifications." Chemical Reviews 115, no. 6 (February 17, 2015): 2376–418. http://dx.doi.org/10.1021/cr500491u.

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Pflieger, Delphine, Martin A. Jünger, Markus Müller, Oliver Rinner, Hookeun Lee, Peter M. Gehrig, Matthias Gstaiger, and Ruedi Aebersold. "Quantitative Proteomic Analysis of Protein Complexes." Molecular & Cellular Proteomics 7, no. 2 (October 23, 2007): 326–46. http://dx.doi.org/10.1074/mcp.m700282-mcp200.

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Pham, Trong Khoa, Pawel Sierocinski, John van der Oost, and Phillip C. Wright. "Quantitative Proteomic Analysis ofSulfolobus solfataricusMembrane Proteins." Journal of Proteome Research 9, no. 2 (February 5, 2010): 1165–72. http://dx.doi.org/10.1021/pr9007688.

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Dissertations / Theses on the topic "Quantitative proteomic analysis"

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Eberl, Hans Christian. "Quantitative proteomic analysis of chromatin associated protein complexes." Diss., lmu, 2012. http://nbn-resolving.de/urn:nbn:de:bvb:19-153101.

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Chiu, Han-Chen. "High-throughput quantitative proteomic analysis of dengue virus infected cells." Thesis, University of Bristol, 2015. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.687071.

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The four serotypes of dengue virus (DENV 1-4) cause the most important arthropod-borne viral disease of humans. Dengue is a global health concern with up to 390 million human infections estimated to occur annually. Despite intensive research, the pathogenesis of dengue is not well understood. The use of high-throughput transcriptomic and small interfering RNA approaches has led to the identification of cellular proteins and pathways that are required for, and modulated by, the DENV lifecycle. In comparison to other high-throughput approaches, high-throughput proteomic analysis has not been applied to the investigation of the DENV -host protein interaction. In this study, for the first time, ~table isotope labelling by ~mino acids in fell culture (SILAC) combined with high throughput mass spectrometry (MS) has been used to examine the host cell response to DENV infection. Initially, SILAC-MS analysis was used to investigate the changes that occurred in the proteome of human alveolar epithelial A549 cells in response to DENV infection. Nuclear and cytoplasmic fractions prepared from mock and DENV -2 infected A549 cells were analysed. 2115 and 3098 proteins in nuclear and cytoplasmic fractions respectively were identified and quantified in both the mock and DENV -2 infected A549 cells. The SILAC-MS results were subjected to bioinformatics analysis and validated for eight selected proteins by Western blot and immunofluorescence analysis. Two of the selected proteins, ELKS/Rab6-interactinglCAST family member 1 (ERC 1) and PRA 1 family protein 2 (PRAF2), significantly decreased during infection and were investigated in more detail to determine their relevance to the DENV lifecycle. Knockdown of ERCI but not PRAF2 inhibited DENV -2 replication whereas overexpression of PRAF2 but not ERCI inhibited DENV-2 infection. Co-immunoprecipitation analysis combined with SILAC-MS revealed that ERCI and PRAF2 interacted with the DENV NS5 and NS 1 respectively and cellular proteins involved in trafficking, suggesting that DENV may modulate intracellular transport processes during its release. Comparative analysis of DENV -2 and DENV -4 infected human hepatocyte Huh-7 cells was then done by SILAC-MS. The SILAC-MS results identified common and cell specific pathways that were modulated by DENV infection and identified cellular proteins that were differentially effected by DENV -2 and DENV -4 infection. Furthermore, the analysis of cell specific pathways that were modulated by DENV infection was done by comparison ofDENV-2 infected A549 and DENV-2 infected Huh- 7 cells. Overall the work described in this thesis demonstrated that SILAC-MS is a powerful approach for the analysis of changes in the host proteome upon DENV infection. A number of novel protein changes were identified that can now be furher examined to increase our understanding of DENV replication and identify targets against which antiviral strategies can be developed.
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Kaneva, Iliyana. "Quantitative proteomic analysis of kinase and phosphatase substrates in Candida albicans." Thesis, University of Sheffield, 2017. http://etheses.whiterose.ac.uk/17558/.

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The ability of the fungus Candida albicans to switch interchangeably between yeast and hyphal forms of growth contributes significantly to its pathogenesis. This morphogenetic shift occurs in response to environmental changes and it is accomplished by a complex network of signal transduction pathways. Protein kinases and phosphatases are important messengers in these pathways and several of them have been directly implicated in controlling C. albicans morphogenesis. Kinases and phosphatases (KP) are enzymes that modulate the function of their substrates via reversible phosphorylation and dephosphorylation, respectively. While the specificity of KP is tightly controlled, some enzymes can target a huge number of proteins and have a master regulatory role over various cell processes. The function of KP in C. albicans is poorly understood and methods for global analysis of KP interactions have not been adapted to this organism. This study developed a protocol for large scale analysis of protein interactions in C. albicans using immunoprecipitation and SILAC in conjunction with quantitative mass spectrometry analysis. The protocol was successfully applied for identification of Cdc14 interactors using the substrate-trapping mutant Cdc14C275S. Cdc14 is a phosphatase required for proper hyphal formation, cytoskeletal organisation and cell separation at the end of mitosis. This study reveals over 100 potential substrates of Cdc14 and new roles of the phosphatase in DNA damage repair, DNA replication, chromosome segregation and transcription regulation. In addition, experiments were performed separately with both yeast and hyphae allowing for direct comparison of Cdc14 interactome between both forms. Many of the identified proteins have unknown function and the significance of these putative interactions remains to be found.
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McQueen, Peter. "Alternative strategies for proteomic analysis and relative protein quantitation." Wiley-VCH, 2015. http://hdl.handle.net/1993/30850.

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The main approach to studying the proteome is a technique called data dependent acquisition (DDA). In DDA, peptides are analyzed by mass spectrometry to determine the protein composition of a biological isolate. However, DDA is limited in its ability to analyze the proteome, in that it only selects the most abundant ions for analysis, and different protein identifications can result even if the same sample is analyzed multiple times in succession. Data independent acquisition (DIA) is a newly developed method that should be able to solve these limitations and improve our ability to analyze the proteome. We used an implementation of DIA (SWATH) to perform relative protein quantitation in the model bacterial system, Clostridium stercorarium, using two different carbohydrate sources, and found that it was able to provide precise quantitation of proteins and was overall more consistent in its ability to identify components of the proteome than DDA. Relative quantitation of proteins is an important method that can determine which proteins are important to a biochemical process of interest. How we determine which proteins are differentially regulated between different conditions is an important question in proteomic analysis. We developed a new approach to analyzing differential protein expression using variation between biological replicates to determine which proteins are being differentially regulated between two conditions. This analysis showed that a large proportion of proteins identified by quantitative proteomic analysis can be differentially regulated and that these proteins are in fact related to biological processes. Analyzing changes in protein expression is a useful tool that can pinpoint many key processes in biological systems. However, these techniques fail to take into account that enzyme activity is regulated by other factors than controlling their level of expression. Activity based protein profiling (ABPP) is a method that can determine the activity state of an enzyme in whole cell proteomes. We found that enzyme activity can change in response to a number of different conditions and that these changes do not always correspond with compositional changes. Mass spectrometry techniques were also used to identify serine hydrolases and characterize their expression in this organism.
February 2016
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Eberl, Hans Christian [Verfasser], and Matthias [Akademischer Betreuer] Mann. "Quantitative proteomic analysis of chromatin associated protein complexes / Hans Christian Eberl. Betreuer: Matthias Mann." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2012. http://d-nb.info/1031380728/34.

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Yousuf, Amjad. "High-throughput quantitative proteomic analysis of host proteins interacting with dengue virus replication complex." Thesis, University of Bristol, 2016. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.702423.

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Dengue virus (DENV) is a global health problem with approximately 390 million infections annually. Currently, no completely effective vaccines or medications are available to prevent DENV infection. This study used high-throughput quantitative proteomic analysis to identify cellular proteins that modulate DENV replication and are potential targets for the development of antiviral strategies. DENV is known to replicate and package its genome in association with perinuclear ER membranes. Initially, experimental conditions were optimised to infect human Huh-7 liver cells at high efficiency, with DENV serotypes -2 and -4 and to isolate a subcellular heavy membrane fraction (16K) enriched in the DENV replication complex. Then, stable isotope labelling by amino acids in cell culture (SILAC) coupled with high-throughput mass spectrometry (MS) was used to identify changes in the Huh-7 cell proteome and the subcellular 16K fraction in response to DENV-2 and DENV-4 infection. The analysis led to the identification and quantification of 3650 and 4026 and 3461 and 3668 proteins in the 16K and total cell proteomes from DENV-2 and DENV-4 infected cells respectively. For comparison, the total cell proteomes were also analysed by tandem mass tagging combined with MS. Proteomic bioinformatics was done on the datasets which showed that DENV modulated various cellular pathways including; protein biosynthesis, the secretory pathway, lipid metabolism and the cell cycle. A comparison of changes in the total and 16K proteomes from DENV infected cells identified a number of cellular proteins that selectively increased in the replicase containing fraction. which was validated by Western blotting and immunofluorescence analysis. Seven proteins (APOB, ARFRP1, BAG2, GOLGA1, GOLGB1, GOSRI and TMED9) were further investigated for their role in DENV -2 replication by examining either viral or replicon replication in cells depleted of the proteins by siRNA knockdown which revealed proteins that both positively and negatively modulated DENV replication.
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Griaud, François. "Proteomic analysis of leukaemogenic protein tyrosine kinase action." Thesis, University of Manchester, 2012. https://www.research.manchester.ac.uk/portal/en/theses/proteomic-analysis-of-leukaemogenic-protein-tyrosine-kinase-action(ff9d490b-5a94-45fc-a857-4f0826e4a11a).html.

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Introduction: Chronic myeloid leukaemia is a blood cancer which progresses from a chronic phase to an acute blast crisis if untreated. Disease progression and treatment resistance may be precipitated by the mutator action of BCR/ABL protein tyrosine kinase (PTK), but only few protein phosphosites involved in the DNA damage response have been investigated with respect to BCR/ABL action. Aim: The aim of this PhD project was to demonstrate that BCR/ABL PTK expression can affect the response to genotoxic stress signalling at the protein phosphorylation level. Methodology: Etoposide-induced DNA damage response has been studied in control and BCR/ABL PTK-expressing Ba/F3 cells using apoptosis and γH2AX assays. Quantitative phosphoproteomics was performed with iTRAQ peptide labelling to discover putative modulated phosphorylation sites. Absolute quantification (AQUA ) performed with selected reaction monitoring was used to validate discovery phosphoproteomics. The effect of genotoxic stress on the THO complex protein Thoc5/Fmip was studied using western blots. Results: The expression of BCR/ABL PTK induced γH2AX phosphorylation after etoposide exposure. This was associated with the modulation of H2AX tyrosine 142 phosphorylation, MDC1 (serines 595 and 1053) and Hemogen serine 380 phosphorylation among proteins regulated by both BCR/ABL PTK and etoposide. We identified that leukaemogenic PTKs mediate Thoc5/Fmip phosphorylation on tyrosine 225 via Src proto-oncogene and oxidative stress, while ATM and MEK1/2 may control its phosphorylation. Human CD34+ CD38- leukaemic stem cells showed pronounced level of THOC5/FMIP tyrosine phosphorylation. Expression of phosphomutant Thoc5/Fmip Y225F might reduce apoptosis mediated by etoposide and H2O2. Conclusion: BCR/ABL PTK can sustain, create, block and change the intensity of protein phosphorylation related to genotoxic stress. Modulation of H2AX, MDC1, Hemogen and Thoc5/Fmip post-translational modifications by BCR/ABL PTK might promote unfaithful DNA repair, genomic instability, anti-apoptotic signalling or abnormal cell differentiation, resulting in leukaemia progression.
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Gilmore, Ian Richard. "Quantitative proteomic analysis of the effect of 24(S),25-epoxycholesterol on SN4741 neuron cells." Thesis, Swansea University, 2013. https://cronfa.swan.ac.uk/Record/cronfa42712.

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Oxysterols are oxygenated derivatives of cholesterol or its precursors. One oxysterol, 24(S),25-epoxycholesterol (24(S),25-EC), which results from a shunt in the cholesterol synthesis pathway has been found at higher than expected levels in embryonic murine brain. Interestingly, the receptor that 24(5),25-EC is a ligand for, Liver X Receptor (LXR), has been implicated in neurogenesis in the ventral mid brain region of embryonic brain; an area with a high density of dopaminergic neurons. The mechanism by which LXR induces this effect is unclear. Therefore, proteomic and phosphoproteomic studies were performed using a stable isotope labelled in amino acid in cell culture (SILAC) approach in order to quantify changes in the proteome between different treatment groups in a mouse substantia nigra dopaminergic cell line (SN4741) SN4741 cells were cultured in SILAC media containing differentially isotope labelled arginine and lysine. For protein expression studies SN4741 cells were treated in serum free media with vehicle, 10muM 24(S),25-EC, or 1muM GW3965, a synthetic ligand of LXR, for 24 hours. For analysis of changes in the phosphoproteome SN4741 cells were treated in serum free media with vehicle, 10muM 24(5),25-EC, or 30muM 25- hydroxycholesterol for 6 hours. Cells were lysed and protein combined in a 1:1 ratio before trypsin digestion and peptide separation via strong cation exchange chromatography. Phosphopeptides were enriched using immobilised metal affinity chromatography (IMAC). Resulting fractions were analysed, using a data dependent LC-MS/MS method. Data was quantified using MaxQuant software in conjunction with Mascot using an IPl mouse database. In protein expression analysis known oxysterol regulated genes, via SREBP or LXR, were differentially expressed. Oxysterol treatment induced global changes in proteins involved in lipid (cholesterol, fatty acid, phospholipid, triglyceride) synthesis. LXR? protein expression increased after GW3965 and 24(5),25-EC treatment, though no change was seen on LXRp mRNA, implying that ligand binding protects LXR? from degradation. 24(S),25-EC induced changes in expression and localisation of the membrane protein caveolin-1. Also, phosphoethanolamine cytidylyltransferase and collagen type IV alpha-3-binding protein, 2 proteins involved in phospholipid synthesis, had an altered expression after 24(S),25-EC treatment suggesting a role for oxysterols in membrane homeostasis. A cytokine, macrophage colony stimulating factor, which is required for normal neuronal development and macrophage differentiation had an LXR independent increased expression after 24(S),25-EC treatment. Quantitative RT-PCR data demonstrated that proteomic changes were due to both transcriptional and post-transcriptional effects of oxysterol. In addition, studies examining changes in the mouse phosphoproteome identified a number of novel phosphorylation sites.
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Puchalska, Monika [Verfasser], and Gerhard [Akademischer Betreuer] Mittler. "Quantitative proteomic analysis of the interactome of mammalian S/MAR (scaffold/matrix attachment region) elements​." Freiburg : Universität, 2018. http://d-nb.info/1216826447/34.

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Saito-Benz, Hideshiro. "Identification of therapeutic targets to revert tamoxifen resistance by quantitative proteomic analysis of signaling networks." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/61231.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biological Engineering, June 2009.
"April 2009." Cataloged from PDF version of thesis.
Includes bibliographical references.
Tamoxifen resistance is the biggest problem in endocrine treatment against hormone receptor positive breast cancer patients. HER2 is a membrane receptor tyrosine kinase that is known to correlate with poor disease outcome and unresponsiveness to endocrine treatment. Although much work has been done over the past decades to elucidate pathways involved in HER2 receptor signaling, the map of network-wide signaling events that contributes to the resistance to Tamoxifen treatment has not been characterized, making it difficult to pin-point the downstream drug target to revert the Tamoxifen resistance. To gain a molecular understanding of the mechanisms by which cells gain drug resistance, we have employed a proteomic analysis by mass spectrometry to quantitatively analyze cellular tyrosine phosphorylation signaling events in breast cancer model systems and human tumor samples. As a result of research, we have identified the major differences in downstream signaling pathways between Tamoxifen sensitive and Tamoxifen resistant breast cancer cell line models. These findings were further analyzed in Tamoxifen sensitive, and Tamoxifen treated/recurred patient samples to study clinical relevance. Specifically, we determined that P13K/Akt, MEK/ERK, and Src/FAK/Abl pathways are major components of the Tamoxifen resistance. We further showed that they signaling components are possible drug targets to revert Tamoxifen resistance. This study revealed cell-context specific network-wide changes in signaling events in response to use of therapeutic drugs. This is, to our first knowledge, the first phosphoproteomic analysis of the signaling network in breast cancer to address Tamoxifen resistance. We believe that same approach is applicable to other drug resistance problems in various disease settings.
by Hideshiro Saito-Benz.
Ph.D.
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Books on the topic "Quantitative proteomic analysis"

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Quantitative Proteomics: Rsc. Royal Society of Chemistry, The, 2014.

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1960-, Sechi Salvatore, ed. Quantitative proteomics by mass spectrometry. Totowa, N.J: Humana Press, 2007.

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Sechi, Salvatore. Quantitative Proteomics by Mass Spectrometry. Humana Press, 2007.

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Kinter, Michael, and Caroline S. Kinter. Application of Selected Reaction Monitoring to Highly Multiplexed Targeted Quantitative Proteomics: A Replacement for Western Blot Analysis. Springer, 2013.

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Kinter, Michael, and Caroline S. Kinter. Application of Selected Reaction Monitoring to Highly Multiplexed Targeted Quantitative Proteomics: A Replacement for Western Blot Analysis. Springer, 2013.

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Rapley, Ralph, and Stuart Harbron. Molecular Analysis and Genome Discovery. Wiley & Sons, Incorporated, John, 2005.

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Rapley, Ralph, and Stuart Harbron. Molecular Analysis and Genome Discovery. Wiley & Sons, Incorporated, John, 2011.

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Ralph, Rapley, and Harbron Stuart, eds. Molecular analysis and genome discovery. Chichester, West Sussex, England: J. Wiley, 2004.

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Rapley, Ralph, and Stuart Harbron. Molecular Analysis and Genome Discovery. Wiley & Sons, Incorporated, John, 2011.

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Ralph, Rapley, and Harbron Stuart, eds. Molecular analysis and genome discovery. Chichester, West Sussex, England: J. Wiley, 2004.

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Book chapters on the topic "Quantitative proteomic analysis"

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Schork, Karin, Katharina Podwojski, Michael Turewicz, Christian Stephan, and Martin Eisenacher. "Important Issues in : Statistical Considerations of Quantitative Proteomic Data." In Methods in Molecular Biology, 1–20. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1024-4_1.

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AbstractMass spectrometry is frequently used in quantitative proteomics to detect differentially regulated proteins. A very important but unfortunately oftentimes neglected part in detecting differential proteins is the statistical analysis. Data from proteomics experiments are usually high-dimensional and hence require profound statistical methods. It is especially important to already correctly design a proteomic experiment before it is conducted in the laboratory. Only this can ensure that the statistical analysis is capable of detecting truly differential proteins afterward. This chapter thus covers aspects of both statistical planning as well as the actual analysis of quantitative proteomic experiments.
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Shiraya, Takeshi, Kentaro Kaneko, and Toshiaki Mitsui. "Quantitative Proteomic Analysis of Intact Plastids." In Methods in Molecular Biology, 469–80. Totowa, NJ: Humana Press, 2013. http://dx.doi.org/10.1007/978-1-62703-631-3_32.

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Yu, Li-Rong, Van M. Hoang, and Timothy D. Veenstra. "New Tools for Quantitative Phosphoproteome Analysis." In Handbook of Proteomic Methods, 241–57. Totowa, NJ: Humana Press, 2003. http://dx.doi.org/10.1007/978-1-59259-414-6_16.

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Bensaddek, Dalila, Armel Nicolas, and Angus I. Lamond. "Quantitative Proteomic Analysis of the Human Nucleolus." In The Nucleolus, 249–62. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-3792-9_20.

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Dannenmaier, Stefan, Silke Oeljeklaus, and Bettina Warscheid. "2nSILAC for Quantitative of Prototrophic Baker’s Yeast." In Methods in Molecular Biology, 253–70. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1024-4_18.

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AbstractStable isotope labeling by amino acids in cell culture (SILAC) combined with high-resolution mass spectrometry is a quantitative strategy for the comparative analysis of (sub)proteomes. It is based on the metabolicincorporation of stable isotope-coded amino acids during growth of cells or organisms. Here, complete labeling of proteins with the amino acid(s) selected for incorporation needs to be guaranteed to enable accurate quantification on a proteomic scale. Wild-type strains of baker’s yeast (Saccharomyces cerevisiae), which is a widely accepted and well-studied eukaryotic model organism, are generally able to synthesize all amino acids on their own (i.e., prototrophic). To render them amenable to SILAC, auxotrophies are introduced by genetic manipulations. We addressed this limitation by developing a generic strategy for complete “native” labeling of prototrophic S. cerevisiae with isotope-coded arginine and lysine, referred to as “2nSILAC”. It allows for directly using and screening several genome-wide yeast mutant collections that are easily accessible to the scientific community for functional proteomic studies but are based on prototrophic variants of S. cerevisiae.
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Zhang, Yi, Alejandro Wolf-Yadlin, and Forest M. White. "Quantitative Proteomic Analysis of Phosphotyrosine-Mediated Cellular Signaling Networks." In Methods in Molecular Biology, 203–12. Totowa, NJ: Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-255-7_14.

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Wu, Christine C., and Michael J. MacCoss. "Quantitative Proteomic Analysis of Mammalian Organisms Using Metabolically Labeled Tissues." In Methods in Molecular Biology, 191–201. Totowa, NJ: Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-255-7_13.

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Trzeciecka, Anna, Padmanabhan Pattabiraman, Maria Carmen Piqueras, Carol Toris, and Sanjoy K. Bhattacharya. "Quantitative Proteomic Analysis of Human Aqueous Humor Using iTRAQ 4plex Labeling." In Glaucoma, 89–95. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-7407-8_9.

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Zhou, Lei, and Roger W. Beuerman. "Quantitative Proteomic Analysis of N-linked Glycoproteins in Human Tear Fluid." In Methods in Molecular Biology, 297–306. Totowa, NJ: Humana Press, 2012. http://dx.doi.org/10.1007/978-1-62703-146-2_20.

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Azimzadeh, Omid, Michael J. Atkinson, and Soile Tapio. "Qualitative and Quantitative Proteomic Analysis of Formalin-Fixed Paraffin-Embedded (FFPE) Tissue." In Methods in Molecular Biology, 109–15. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4939-2550-6_10.

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Conference papers on the topic "Quantitative proteomic analysis"

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Smith, L., D. Potts, O. Qutob, MB Watson, AW Beavis, V. Garimella, MJ Lind, PJ Drew, and L. Cawkwell. "Quantitative proteomic analysis of radioresistant breast cancer cell lines." In CTRC-AACR San Antonio Breast Cancer Symposium: 2008 Abstracts. American Association for Cancer Research, 2009. http://dx.doi.org/10.1158/0008-5472.sabcs-5074.

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Jiang, Biaobin, David F. Gleich, and Michael Gribskov. "Differential flux balance analysis of quantitative proteomic data on protein interaction networks." In 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP). IEEE, 2015. http://dx.doi.org/10.1109/globalsip.2015.7418343.

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Sandri, Brian, Andrew Limper, Pratik Jagtap, Svetlana Avdulov, Mark Peterson, Ping Yang, Ola Larsson, et al. "Large-scale quantitative proteomic analysis identifies pathways in COPD-associated lung cancer." In Annual Congress 2015. European Respiratory Society, 2015. http://dx.doi.org/10.1183/13993003.congress-2015.pa4270.

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Serada, Satoshi, Yorihisa Kotobuki, Atsushi Tanemura, Ichiro Katayama, and Tetsuji Naka. "Abstract 1275: Quantitative proteomic analysis of tumor growth associated proteins in cutaneous malignant melanoma." In Proceedings: AACR 103rd Annual Meeting 2012‐‐ Mar 31‐Apr 4, 2012; Chicago, IL. American Association for Cancer Research, 2012. http://dx.doi.org/10.1158/1538-7445.am2012-1275.

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Yokoyama, Takuhei, Takayuki Enomoto, Satoshi Serada, Shinya Matsuzaki, Toshihiro Kimura, Yutaka Ueda, Masami Fujita, et al. "Abstract 5108: Quantitative proteomic analysis of cell-surface membrane proteins: Biomarker discovery in endometrial cancer." In Proceedings: AACR 102nd Annual Meeting 2011‐‐ Apr 2‐6, 2011; Orlando, FL. American Association for Cancer Research, 2011. http://dx.doi.org/10.1158/1538-7445.am2011-5108.

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Taguchi, Ayumu, Avnish Kapoor, Amin Momin, Hiroyuki Katayama, Wantong Yao, Hong Wang, Haoqiang Ying, Ronald DePinho, and Samir Hanash. "Abstract PR03: Global quantitative proteomic and phosphoproteomic analysis of oncogenic Kras-driven mouse pancreatic cancer." In Abstracts: AACR Special Conference on RAS Oncogenes: From Biology to Therapy; February 24-27, 2014; Lake Buena Vista, FL. American Association for Cancer Research, 2014. http://dx.doi.org/10.1158/1557-3125.rasonc14-pr03.

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Harada, Emi, Satoshi Serada, Tsuyoshi Takahashi, Minoru Fujimoto, and Tetsuji Naka. "Abstract 5312: Quantitative proteomic analysis of cell-surface membrane proteins: Biomarker discovery in esophageal squamous cancer." In Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA. American Association for Cancer Research, 2014. http://dx.doi.org/10.1158/1538-7445.am2014-5312.

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Chiang, Chang Hsu, Chih-Ching Wu, and Ann-Joy Cheng. "Abstract 5157: Quantitative proteomic analysis identifying Krt17 plays a critical role in areca nut inducing oral carcinogenesis." In Proceedings: AACR 107th Annual Meeting 2016; April 16-20, 2016; New Orleans, LA. American Association for Cancer Research, 2016. http://dx.doi.org/10.1158/1538-7445.am2016-5157.

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Schwartz, S., Y. Tian, R. Fasani, M. Diaz Delgado, C. Hierro, J. Rodon, S. Sellappan, F. Cecchi, T. Hembrough, and P. Nuciforo. "Abstract P6-07-16: Quantitative proteomic analysis of FGFR by mass spectrometry may improve identification of FGFR amplified tumors sensitive to inhibitor therapy." In Abstracts: 2016 San Antonio Breast Cancer Symposium; December 6-10, 2016; San Antonio, Texas. American Association for Cancer Research, 2017. http://dx.doi.org/10.1158/1538-7445.sabcs16-p6-07-16.

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Salka, K., A. Panigrahi, K. Brown, M. A. Arroyo Morr, G. R. Nino, M. Rose, and G. F. Perez. "Use of Quantitative Proteomic Analysis of CF and Non-CF Human Bronchial Epithelial (HBE) Cell Apical Secretome (AS) to Identify Changes in Innate Immunity of Lungs." In American Thoracic Society 2019 International Conference, May 17-22, 2019 - Dallas, TX. American Thoracic Society, 2019. http://dx.doi.org/10.1164/ajrccm-conference.2019.199.1_meetingabstracts.a6191.

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Reports on the topic "Quantitative proteomic analysis"

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Rabinowitz, Joshua D. Final Technical Report--Quantitative analysis of metabolic regulation by integration of metabolomics, proteomics, and fluxomics. Office of Scientific and Technical Information (OSTI), December 2018. http://dx.doi.org/10.2172/1487155.

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