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Proteomics quantitative

The objective of quantitative proteomics is to identify differentially expressed proteins in a biological sample. Differential expression of proteins is caused by a disease state, stress due to external factors (drugs, toxins, etc.), or experimental manipulation. Quantitative proteomics can help identify biomarkers of a particular disease and aid in an early diagnostic intervention and prevention of a disease. Several strategies have been developed for quantitative proteomics some are exclusively gel-based approaches, and others require mass spectrometry measurements [66]. [Pg.310]

Quantification by Two-Dimensional Gel Electrophoresis 2-DE is still considered the gold standard for quantitative proteomics [57,67]. This procedure relies on differential expression of proteins in control and test samples. Proteins from the two samples are separated by the 2-DE protocol, followed by staining with a suitable dye (e.g., CCB or SYPRO Ruby). Next, images of the stained spots are acquired, and spot densities are measured and compared by image analysis software to provide differential expression of proteins. Gel-to-gel variations can affect the precision of quantification by this procedme. [Pg.310]

Quantification by Two-Dimensional Differential Imaging Gel Electrophoresis 2D-DIGE is a more precise version of the 2-DE approach. This method uses multicolored cyanine dyes to label proteins in the two experimental samples [Pg.310]

Another ICAT reagent, known as HisTag reagent, used to tag Cys residues, has been reported recently [70]. It is a 10-mer derivatized peptide H2N-(His)e-Ala-Arg-Ala-Cys(2-thiopyridyl disulfide)-CONH2 and has a trypsin cleavable site (-Arg-Ala-) that facilitates removal of the Hise-tag during the final digestion step. The thiopyridyl disulfide moiety acts as a thiol reactive group and d4 label is incorporated in Ala-9 residue. [Pg.312]

Quantification by the Proteolytic 0-Water Labeling Approach This method, also known as enzymatic labeling, relies on trypsin-catalyzed labeling [Pg.312]

Structures of sidechains X of the 20 common amino acids NH2-CHX-COOH (but note unusual case of proline). [Pg.664]

However, trypsin can not hydrolyze the lysine-proline bond (probably a result of steric hindrance), and if a protein sequence contains adjacent basic residues (KK, KR, RK or RR) the resulting digestion products include single amino acids (K or R) that are difficult to detect. As a check on this and other possibilities, other proteases are used in addition to trypsin, e.g., Lys-C, Arg-C and Glu-C are proteases that hydrolyze peptide bonds on the C-terminal side of only lysine, arginine and glutamic acid, respectively. Cyanogen bromide chemically hydrolyses peptide bonds on the C-terminal side of methionine to form peptides with a homoserine residue (X = -CH2-CH2-OH) at the C-terminus. [Pg.664]

The body tissue that is most often sampled for proteomics analyses is the blood, partly because of its relatively easy access and partly because, during its circulation through all other organs, it picks up leakage proteins and thus reflects to some extent all the physiological processes occurring within the body. Of course the downside of this aspect is the consequent complexity [Pg.664]

Unlike nucleic acids, proteins in an organism are present at very different concentration levels. Thus, it is not sufficient to demonstrate that a particular protein is present we also need to know its concentration. From the high-concentration globulins in blood to the low-copy-number proteins that are represented by only a few molecules per cell, there is an enormous dynamic range. This presents a challenge to the utilized analytical methods because of the potential interferences, especially when quantitating the proteins at low concentration. For example, the high-abundance proteins can compete in the ionization process and suppress the ion formation from the low-level species. This ion suppression effect is quite common in MALDI and ESI ion sources. [Pg.186]

Common approaches to minimize these problems include extensive separation before mass spectrometric analysis. Typical separation protocols consist of an orthogonal combination of affinity chromatography, 2-DE, lEX, HPLC, and ion mobility techniques. If these steps can reduce the sample complexity to a single component, the signal from the separation method (e.g., chromatographic peak area) can be used for quantitation. Frequently this is not achievable or verifiable. Relative quantitation in these instances can be performed by stable isotope labeling methods. [Pg.186]

A common example of relative quantitation is used in comparative proteomics. For example, to uncover the differences in protein makeup and concentration levels between the healthy state and a particular disease (e.g., protein expression in normal vs. HIV-infected cells [26]), stable isotope labeling can be applied to one or the other. A frequently used variant of this approach is the isotope-coded affinity tag (ICAT) method [27]. Fig. 7 shows how an ICAT reagent is used to tag the cysteine residues of a peptide, human insulin chain B in this example. First, the reactive end of the ICAT reagent covalently attaches to the [Pg.186]

The mass spectrum of the captured mixture exhibits the peptide peaks as doublets with a mass shift of 8 or, in case of multiple cysteine residues, its multiples between the normal and the diseased sample. The abundance ratios of these doublets characterize the relative quantity of a particular protein in the two samples. As both the dg- and the dg-tagged components are in the same matrix and differ only in isotope composition, the relative peak intensities are a true reflection of the protein level changes in disease. The ICAT method is limited to cysteine-containing proteins, but other tagging protocols (e.g., through proteolytic 0 labeling) are being developed to eliminate this restriction [28]. [Pg.187]


Tao WA, Aebersold R (2003) Advances in quantitative proteomics via stable isotope tagging and mass spectrometry. Curr Opin Biotechnol 14 110-118... [Pg.1031]

Griffin, T. J. Han, D. K. Gygi, S. R Rist, B. Lee, H. Aebersold, R. Parker, K. C. Toward a high-throughput approach to quantitative proteomic analysis Expression-dependent protein identification by mass spectrometry. J. Am. Soc. Mass. Spectrom. 2001,12,1238-1246. [Pg.225]

Gu, S Du, Y Chen, J., Liu, Z Bradbury, E.M., Hu, C.A., Chen, X. (2004). Large-scale quantitative proteomic study of PUMA-induced apoptosis using two-dimensional liquid chromatography—mass spectrometry coupled with amino acid-coded mass tagging. J. Proteome Res. 3, 1191 1200. [Pg.257]

MacKay, V. L., Li, X., Flory, M. R., Turcott, E., and Law, G. L. (2004). Gene expression analyzed by high-resolution state array analysis and quantitative proteomics Response of yeast to mating pheromone. Mol. Cell Proteomics 3, 478—489. [Pg.234]

Jain MR, Liu T, Hu J, et al. Quantitative proteomic analysis of formahn fixed paraffin embedded oral HPV lesions from HIV patients. Open Proteomics J. 2008 1 40-45. [Pg.345]

Balgley BM, Wang W, Song T, et al. Evaluation of confidence and reproducibility in quantitative proteomics performed by a capillary isoelectric focusing-based proteomic platform coupled with a spectral counting approach. Electrophoresis 2008 29 3047-3054. [Pg.365]

Aebersold, R. (2003) Quantitative proteome analysis Methods and applications. /. Infect. Dis. 187 (Suppl. 2), S315-S320. [Pg.1041]

Gartner, C.A., Elias, J.E., Bakalarski, C.E., and Gygi, S.P. (2007) Catch-and-release reagents for broads-cale quantitative proteomics analyses./. Broteome Res. 6(4), 1482-1491. [Pg.1065]

Warwood, S., Mohammed, S., Cristeal, I.M., Evans, C., Whetton, A.D., and Gaskell, S.J. (2006) Guanidination chemistry for qualitative and quantitative proteomics. Rapid Comm. Mass Spectrom. 20, 3245-3256. [Pg.1126]

Wei, Y., and Chen, S.S. (2005) Mass spectrometry-based quantitative proteomic profiling. Briefings in functional genomics and proteomics 4, 1-12. [Pg.1126]

Zappacosta, F., and Annan, R.S. (2004) N-terminal isotope tagging strategy for quantitative proteomics Results-driven analysis of protein abundance changes. Anal. Chem. 76, 6618-6627. [Pg.1131]

Zhou, H., Ranish, J.A., Watts, J.D., and Aebersold, R. (2002) Quantitative proteome analysis by solid-phase isotope tagging and mass spectrometry. Nat. Biotechnol. 20, 512-515. [Pg.1132]

Foster, L. J., de Hoog, C. L. and Mann, M. Unbiased quantitative proteomics of lipid rafts reveals high specificity for signaling factors. Proc. Natl. Acad. Sci. U.S.A. 100 5813— 5818,2003. [Pg.32]

Gygi, S. P., Rist, B., and Aebersold, R., Measuring gene expression by quantitative proteome analysis, Curr. Opin. Biotechnol., 11, 396, 2000. [Pg.94]

R. Aebersold. Quantitative Proteome Analysis Methods and Applications. J. Infect. Dis., 187, Suppl 2(2003) S315-20. [Pg.220]

Wolf-Yadlin, A., Hautaniemi, S., Lauffen-burger, D.A. and White, E.M. (2007) Multiple Reaction Monitoring for Robust Quantitative Proteomic Analysis of Cellular Signaling Networks. Proc Natl Acad Sci, 104, 5860-5865. [Pg.82]

Li C, Hong Y, Tan YX et al. Accurate qualitative and quantitative proteomic analysis of clinical hepatocellular carcinoma using laser capture microdissection coupled with isotope-coded affinity tag and two-dimensional liquid chromatography mass spectrometry. Mo/ Cell Proteomics 2004,3399-409. [Pg.44]

Nirmalan, N., Sims, P.F.C. and Hyde, J.E. (2004) Quantitative proteomics of the human malaria parasite Plasmodium falciparum and its application to studies of development and inhibition. Molecular Microbiology 52, 11 87-11 99. [Pg.346]

Smolka MB, Zhou H, Purkayastha S, Aebersold R. 2001. Optimization of the isotope-coded affinity tag-labeling procedure for quantitative proteome analysis. Anal Biochem 297 25-31. [Pg.450]

Murray, J., Gilkerson, R., and Capaldi, R. A. (2002) Quantitative proteomics the copy number of pyruvate dehydrogenase is more than 10(2)-fold lower than that of complex III in human mitochondria, FEBS Lett. 9, 173-178. [Pg.132]

Sechi S, Oda Y Quantitative proteomics using mass spectrometry. Curr. Opin. Chem. Biol. (2003) 7 70-77. [Pg.180]


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