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Gene Arrays and Proteomics

A Primer

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Opioid Research

Part of the book series: Methods in Molecular Biology™ ((MIMM,volume 84))

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Abstract

In recent years, molecular biology has increasingly focused on how cellular effectors are modulated by the environment and, in turn, modulate each other to control cellular functions. In the opioid field, we concern ourselves both with signaling mechanisms within cells and the functions of neural circuitry in mediating the behavioral effects of opioids. All of these mechanisms identified to date have proven to be extremely complex, suggesting that behavioral outcomes mediated by opioids are dependent on the interactions of multiple gene products. Opioid-mediated behavioral outcomes such as tolerance, dependence, and addiction may reflect problems in the regulation of complex biological and emotional functions. From this, it follows that slight alterations in the expression or function of individual genes that still fall within the “normal” range could lead to pathological effects or behaviors. Genetic polymorphisms cause changes in the coding and regulatory regions of genes. Thus, in addition to changes in levels of protein expression, encoded proteins may have slightly different functions or undergo differential regulation in cells.

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References

  1. Ramsay, G. (1998) DNA chips: State-of-the-art. Nature Biotechnol. 16, 40–44.

    Article  CAS  Google Scholar 

  2. Watson, S. J. and Akil, H. (1999) Gene chips and arrays revealed: a primer on their power and their uses. Biol. Psych. 45, 533–543.

    Article  CAS  Google Scholar 

  3. Marshall, A. and Hodgson, J. (1998) DNA chips: An array of possibilities. Nature Biotechnol. 16, 27–31.

    Article  CAS  Google Scholar 

  4. Graves, D. J. (1999) Powerful tools for genetic analysis come of age. Tibtech 17, 127–134.

    CAS  Google Scholar 

  5. Zirlinger, M., Kreiman, G., and Anderson, D. J. (2001) Amygdala-enriched genes identified by microarray technology are restricted to specific amygdaloid subnuclei. Proc. Natl. Acad. Sci. USA 98, 5270–5275.

    Article  PubMed  CAS  Google Scholar 

  6. Sandberg, R., Yasuda, R., Pankratz, D., Carter, T., Del Rio, J., Wodicka, L., et al. (2000) Regional and stran-specific gene expression mapping in the adult mouse brain. Proc. Natl. Acad. Sci. USA 97, 11,038–11,043.

    Article  PubMed  CAS  Google Scholar 

  7. Hess, K. R., Zhang, W., Baggerly, K. A., Stivers, D. N., and Coombes, K. R. (2001) Microarrays: handling the deluge of data and extracting reliable information. Trends Biotechnol. 19, 463–468.

    Article  PubMed  CAS  Google Scholar 

  8. Wu, T. (2001) Analysing gene expression data from DNA microarrays to identify candidate genes. J. Pathol. 195, 53–65.

    Article  PubMed  CAS  Google Scholar 

  9. Brazma, A. and Vilo, J. (2000) Gene expression data analysis. FEBS Lett. 480, 17–24.

    Article  PubMed  CAS  Google Scholar 

  10. Lee, M., Kuo, F., Whitmore, G., and Sklar, J. (200) Importance of replication in microarray gene expression studies: Statistical methods and evidence from repetitive cDNA hybridizations. Proc. Natl. Acad. Sci. USA 97, 9834–9839.

    Google Scholar 

  11. Livesey, F. and Hunt, S. (1996) Identifying changes in gene expression in the nervous system: mRNA differential display. Trends Neurosci. 19, 84–88.

    Article  PubMed  CAS  Google Scholar 

  12. Velculescu, V. E., Zhang, L., Vogelstein, B., and Kinzler, K. W. (1995) Serial analysis of gene expression. Science 270, 484–487.

    Article  PubMed  CAS  Google Scholar 

  13. Velculescu, V. E. (1999) Essay: Amersham Pharmacia Biotech & Science prize. Tantalizing transcriptomes—SAGE and its use in global gene expression analysis. Science 286, 1491–1492.

    Article  PubMed  CAS  Google Scholar 

  14. Sagerstrom, C. G., Sun, B. I., and Sive, H. L. (1997). Subtractive cloning: past, present, and future. Ann. Rev. Biochem. 66, 751–783.

    Article  PubMed  CAS  Google Scholar 

  15. Williams, K. L. and Hochstrasser, D. F. (1997) Introduction to the proteome. In Proteome Research: New Frontiers in Functional Genomics (Wilkins, M. R., Williams, K. L., Appel, R. D. and Hochstrasser, D. F., eds.), Springer, Berlin pp. 1–12.

    Google Scholar 

  16. Gygi, S. P., Rochon, Y., Franza, B. R., and Aebersold, R. (1999) Correlation between protein and mRNA abundance in yeast. Mol. Cell Biol. 19, 1720–1730.

    PubMed  CAS  Google Scholar 

  17. Anderson, L. and Seilhamer, J. (1997) A comparison of selected mRNA and protein abundances in human liver. Electrophoresis 18, 533–537.

    Article  PubMed  CAS  Google Scholar 

  18. Chambers, G., Lawrie, L., Cash, P., and Murray, G. I. (2000) Proteomics: a new approach to the study of disease. J. Pathol. 192, 280–288.

    Article  PubMed  CAS  Google Scholar 

  19. Godovac-Zimmermann, J. and Brown, L. R. (2001) Perspectives for mass spectrometry and functional proteomics. Mass Spectrom. Rev. 20, 1–57.

    Article  PubMed  CAS  Google Scholar 

  20. Naaby-Hansen, S., Waterfield, M. D., and Cramer, R. (2001) Proteomics—post-genomic cartography to understand gene function. Trends Pharmacol. Sci. 22, 376–384.

    Article  PubMed  CAS  Google Scholar 

  21. Herbert, B. (1999) Advances in protein solubilisation for two-dimensional electrophoresis. Electrophoresis 20, 660–663.

    Article  PubMed  CAS  Google Scholar 

  22. Gorg, A., Obermaier, C., Boguth, G., Harder, A., Scheibe, B., Wildgruber, R., et al. (2000) The current state of two-dimensional electrophoresis with immobilized pH gradients. Electrophoresis 21, 1037–1053.

    Article  PubMed  CAS  Google Scholar 

  23. Molloy, M. P., Herbert, B. R., Williams, K. L., and Gooley, A. A. (1999) Extraction of Escherichia coli proteins with organic solvents prior to two-dimensional electrophoresis. Electrophoresis 20, 701–704.

    Article  PubMed  CAS  Google Scholar 

  24. Hastie, N. D. and Bishop, J. O. (1976) The expression of three abundance classes of messenger RNA in mouse tissues. Cell 9, 761–774.

    Article  PubMed  CAS  Google Scholar 

  25. Herbert, B. R., Harry, J. L., Packer, N. H., Gooley, A. A., Pedersen, S. K., and Williams, K. L. (2001) What place for polyacrylamide in proteomics? Trends Biotechnol. 19, S3–9.

    Article  PubMed  CAS  Google Scholar 

  26. Corthals, G. L., Wasinger, V. C., Hochstrasser, D. F., and Sanchez, J. C. (2000) The dynamic range of protein expression: a challenge for proteomic research. Electrophoresis 21, 1104–1115.

    Article  PubMed  CAS  Google Scholar 

  27. Pasquali, C., Fialka, I. and Huber, L. A. (1999) Subcellular fractionation, electromigration analysis and mapping of organelles. J. Chromatogr. B. Biomed. Sci. Appl. 722, 89–102.

    Article  PubMed  CAS  Google Scholar 

  28. Molloy, M. P., Herbert, B. R., Walsh, B. J., Tyler, M. I., Traini, M., Sanchez, J. C., et al. (1998) Extraction of membrane proteins by differential solubilization for separation using two-dimensional gel electrophoresis. Electrophoresis 19, 837–844.

    Article  PubMed  CAS  Google Scholar 

  29. Klose, J. and Kobalz, U. (1995) Two-dimensional electrophoresis of proteins: an updated protocol and implications for a functional analysis of the genome. Electrophoresis 16, 1034–1059.

    Article  PubMed  CAS  Google Scholar 

  30. Herbert, B. and Righetti, P. G. (2000) A turning point in proteome analysis: sample prefractionation via multicompartment electrolyzers with isoelectric membranes. Electrophoresis 21, 3639–3648.

    Article  PubMed  CAS  Google Scholar 

  31. Husi, H., Ward, M. A., Choudhary, J. S., Blackstock, W. P., and Grant, S. G. (2000) Proteomic analysis of NMDA receptor-adhesion protein signaling complexes. Natl. Neurosci. 3, 661–669.

    Article  CAS  Google Scholar 

  32. Issaq, H. J. (2001) The role of separation science in proteomics research. Electrophoresis 22, 3629–3638.

    Article  PubMed  CAS  Google Scholar 

  33. Washburn, M. P., Wolters, D., and Yates, J. R., 3rd. (2001) Large-scale analysis of the yeast proteome by multidimensional protein identification technology. Nat. Biotechnol. 19, 242–247.

    Article  PubMed  CAS  Google Scholar 

  34. Moseley, M. A. (2001) Current trends in differential expression proteomics: isotopically coded tags. Trends Biotechnol. 19, S10–16.

    Article  PubMed  CAS  Google Scholar 

  35. Lauber, W. M., Carroll, J. A., Dufield, D. R., Radabaugh, M. R., and Malone, J. P. (2001) Mass spectrometry compatibility of two-dimensional gel protein stains. Electrophoresis 22, 906–918.

    Article  PubMed  CAS  Google Scholar 

  36. Yan, J. X., Harry, R. A., Spibey, C., and Dunn, M. J. (2000) Postelectrophoretic staining of proteins separated by two-dimensional gel electrophoresis using SYPRO dyes. Electrophoresis 21, 3657–3665.

    Article  PubMed  CAS  Google Scholar 

  37. Miller, M. D., Jr., Acey, R. A., Lee, L. Y., and Edwards, A. J. (2001) Digital imaging considerations for gel electrophoresis analysis systems. Electrophoresis 22, 791–800.

    Article  PubMed  CAS  Google Scholar 

  38. Chalmers, M. J. and Gaskell, S. J. (2000) Advances in mass spectrometry for proteome analysis. Curr. Opin. Biotechnol. 11, 384–390.

    Article  PubMed  CAS  Google Scholar 

  39. Yates, J. R., 3rd. (1998) Mass spectrometry and the age of the proteome. J. Mass. Spectrom. 33, 1–19.

    Article  PubMed  CAS  Google Scholar 

  40. Fenyo, D. (2000) Identifying the proteome: software tools. Curr. Opin. Biotechnol. 11, 391–395.

    Article  PubMed  CAS  Google Scholar 

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© 2003 Humana Press Inc.

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Moulédous, L., Gutstein, H.B. (2003). Gene Arrays and Proteomics. In: Pan, Z.Z. (eds) Opioid Research. Methods in Molecular Biology™, vol 84. Humana Press. https://doi.org/10.1385/1-59259-379-8:141

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  • DOI: https://doi.org/10.1385/1-59259-379-8:141

  • Publisher Name: Humana Press

  • Print ISBN: 978-1-58829-059-5

  • Online ISBN: 978-1-59259-379-8

  • eBook Packages: Springer Protocols

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