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Brain on a Chip: A Method to Detect Novel Neuroprotective Candidate Targets

  • Yang Tang
  • Myriam Bernaudin
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 399)

Abstract

The search of potential novel therapeutical targets for neuroprotection has been widely intensified since the usefulness of microarray techniques. Indeed, this recent technology (also called Gene chip) provides a powerful tool to examine gene expression changes of thousands of genes at the same time, on a single chip in the brain. Arrays can paint a picture or “profile” (gene profiling, gene expression patterns) of which genes in the genome are active in a particular cell type and under a particular condition. In this chapter, we will describe the methods to perform microarrays and analyze the following data using GeneChip® technology (Affymetrix, Inc., Santa Clara, CA, USA), to identify, for example, potential brain neuroprotective targets. Moreover, step-by-step explanations of software operation will be provided. Finally, methods are presented to validate the gene expression changes revealed from the microarray analyses.

Key Words

Chip microarray brain neuroprotection genomic 

References

  1. 1.
    Tang, Y., Lu, A., Aronow, B. J., Wagner, K. R., and Sharp, F. R. (2002) Genomic responses of the brain to ischemic stroke, intracerebral haemorrhage, kainate seizures, hypoglycemia, and hypoxia. Eur J Neurosci 15, 1937–1952.CrossRefPubMedGoogle Scholar
  2. 2.
    Bernaudin, M., Tang, Y., Reilly, M., Petit, E., and Sharp, F. R. (2002) Brain genomic response following hypoxia and re-oxygenation in the neonatal rat. Identification of genes that might contribute to hypoxia-induced ischemic tolerance. J Biol Chem 277, 39728–39738.Google Scholar
  3. 3.
    Tang, Y., Pacary, E., Freret, T., Divoux, D., Petit, E., Schumann-Bard, P., and Bernaudin, M. (2005) Effect of hypoxic preconditioning on brain genomic response before and following ischemia in the adult mouse: Identification of potential neuroprotective candidates for stroke. Neurobiol Dis 21, 18–28.CrossRefPubMedGoogle Scholar
  4. 4.
    Jin, K., Mao, X. O., Eshoo, M. W., Nagayama, T., Minami, M., Simon, R. P., and Greenberg, D. A. (2001) Microarray analysis of hippocampal gene expression in global cerebral ischemia. Ann Neurol 50, 93–103.CrossRefPubMedGoogle Scholar
  5. 5.
    Stenzel-Poore, M. P., Stevens, S. L., Xiong, Z., Lessov, N. S., Harrington, C. A., Mori, M., Meller, R., Rosenzweig, H. L., Tobar, E., Shaw, T. E., Chu, X., and Simon, R. P. (2003) Effect of ischaemic preconditioning on genomic response to cerebral ischaemia: similarity to neuroprotective strategies in hibernation and hypoxia-tolerant states. Lancet 362, 1028–1037.CrossRefPubMedGoogle Scholar
  6. 6.
    Kawahara, N., Wang, Y., Mukasa, A., Furuya, K., Shimizu, T., Hamakubo, T., Aburatani, H., Kodama, T., and Kirino, T. (2004) Genome-wide gene expression analysis for induced ischemic tolerance and delayed neuronal death following transient global ischemia in rats. J Cereb Blood Flow Metab 24, 212–223.CrossRefPubMedGoogle Scholar
  7. 7.
    Lu, X. C., Williams, A. J., Yao, C., Berti, R., Hartings, J. A., Whipple, R., Vahey, M. T., Polavarapu, R. G., Woller, K. L., Tortella, F. C., and Dave, J. R. (2004) Microarray analysis of acute and delayed gene expression profile in rats after focal ischemic brain injury and reperfusion. J Neurosci Res 77, 843–857.CrossRefPubMedGoogle Scholar
  8. 8.
    Dhodda, V. K., Sailor, K. A., Bowen, K. K., and Vemuganti, R. (2004) Putative endogenous mediators of preconditioning-induced ischemic tolerance in rat brain identified by genomic and proteomic analysis. J Neurochem 89, 73–89.CrossRefPubMedGoogle Scholar
  9. 9.
    Mirnics, K., Middleton, F. A., Marquez, A., Lewis, D. A., and Levitt, P. (2000) Molecular characterization of schizophrenia viewed by microarray analysis of gene expression in prefrontal cortex. Neuron 28, 53–67.CrossRefPubMedGoogle Scholar
  10. 10.
    Sandberg, R., Yasuda, R., Pankratz, D. G., Carter, T. A., Del Rio, J. A., Wodicka, L., Mayford, M., Lockhart, D. J., and Barlow, C. (2000) Regional and strain-specific gene expression mapping in the adult mouse brain. Proc Natl Acad Sci USA 97, 11038–11043.CrossRefPubMedGoogle Scholar
  11. 11.
    Eisen, M. B., Spellman, P. T., Brown, P. O., and Botstein, D. (1998) Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci USA 95, 14863–14868.CrossRefPubMedGoogle Scholar
  12. 12.
    Tavazoie, S., Hughes, J. D., Campbell, M. J., Cho, R. J., and Church, G. M. (1999) Systematic determination of genetic network architecture. Nat Genet 22, 281–285.CrossRefPubMedGoogle Scholar
  13. 13.
    Tamayo, P., Slonim, D., Mesirov, J., Zhu, Q., Kitareewan, S., Dmitrovsky, E., Lander, E. S., and Golub, T. R. (1999) Systematic determination of genetic network architecture. Proc Natl Acad Sci USA 96, 2907–2912.CrossRefPubMedGoogle Scholar
  14. 14.
    Brazma, A. and Vilo, J. (2000) Gene expression data analysis. FEBS Lett 480, 17–24.CrossRefPubMedGoogle Scholar
  15. 15.
    Sherlock, G. (2000) Analysis of large-scale gene expression data. Curr Opin Immunol 12, 201–205.CrossRefPubMedGoogle Scholar
  16. 16.
    Anderson, L. and Seilhamer, J. (1997) A comparison of selected mRNA and protein abundances in human liver. Electrophoresis 18, 533–537.CrossRefPubMedGoogle Scholar
  17. 17.
    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.PubMedGoogle Scholar
  18. 18.
    Bernaudin, M. and Sharp, F. R. (2004) Methods to detect hypoxia-induced ischemic tolerance in the brain. Methods Enzymol 381, 399–416.CrossRefPubMedGoogle Scholar
  19. 19.
    Claverie, J. M. (1999) Computational methods for the identification of differential and coordinated gene expression. Hum Mol Genet 8, 1821–1832.CrossRefPubMedGoogle Scholar

Copyright information

© Humana Press Inc. 2007

Authors and Affiliations

  • Yang Tang
    • 1
  • Myriam Bernaudin
    • 2
  1. 1.Department of NeurologyUniversity of Minnesota Medical SchoolMinneapolis
  2. 2.UMR-CNRS 6185, Centre Cyceron, Neurodégénérescence: Modèles et Stratégies ThérapeutiquesUniversité de CaenCaenFrance

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