Skip to main content

Advertisement

SpringerLink
Log in

Genes that code for T cell signaling proteins establish transcriptional regulatory networks during thymus ontogeny

  • Published:
Molecular and Cellular Biochemistry Aims and scope Submit manuscript

Abstract

Gene expression profiling by cDNA microarrays during murine thymus ontogeny has contributed to dissecting the large-scale molecular genetics of T cell maturation. Gene profiling, although useful for characterizing the thymus developmental phases and identifying the differentially expressed genes, does not permit the determination of possible interactions between genes. In order to reconstruct genetic interactions, on RNA level, within thymocyte differentiation, a pair of microarrays containing a total of 1,576 cDNA sequences derived from the IMAGE MTB library was applied on samples of developing thymuses (14–17 days of gestation). The data were analyzed using the GeneNetwork program. Genes that were previously identified as differentially expressed during thymus ontogeny showed their relationships with several other genes. The present method provided the detection of gene nodes coding for proteins implicated in the calcium signaling pathway, such as Prrg2 and Stxbp3, and in protein transport toward the cell membrane, such as Gosr2. The results demonstrate the feasibility of reconstructing networks based on cDNA microarray gene expression determinations, contributing to a clearer understanding of the complex interactions between genes involved in thymus/thymocyte development.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  1. Anderson G, Moore NC, Owen JJT, Jenkinson EJ (1996) Cellular interactions in thymocyte development. Annu Rev Immunol 14:73–99. doi:10.1146/annurev.immunol.14.1.73

    Article  PubMed  CAS  Google Scholar 

  2. Anderson G, Jenkinson EJ (2001) Lymphostromal interactions in thymic development and function. Nat Rev Immunol 1:31–40. doi:10.1038/35095500

    Article  PubMed  CAS  Google Scholar 

  3. Kishimoto H, Sprent J (1999) Several different cell surface molecules control negative selection of medullary thymocytes. J Exp Med 190:65–73. doi:10.1084/jem.190.1.65

    Article  PubMed  CAS  Google Scholar 

  4. Klein L, Kyewski B (2000) Self-antigen presentation by thymic stromal cells: a subtle division of labor. Curr Opin Immunol 12:179–186. doi:10.1016/S0952-7915(99)00069-2

    Article  PubMed  CAS  Google Scholar 

  5. Kyewski B, Derbinski J (2004) Self-representation in the thymus: an extended view. Nat Rev Immunol 4:688–698. doi:10.1038/nri1436

    Article  PubMed  CAS  Google Scholar 

  6. Puthier D, Joly F, Irla M, Saade M, Victorero G, Loriod B et al (2004) A general survey of thymocyte differentiation by transcriptional analysis of knockout mouse models. J Immunol 173:6109–6118

    PubMed  CAS  Google Scholar 

  7. Magalhães DA, Macedo C, Junta CM, Mello SS, Marques MM, Cardoso RS et al (2005) Hybridization signatures during thymus ontogeny reveals modulation of genes coding for T-cell signaling proteins. Mol Immunol 42:1043–1048. doi:10.1016/j.molimm.2004.09.031

    Article  PubMed  CAS  Google Scholar 

  8. Cardoso RS, Junta CM, Macedo C, Magalhães DA, Silveira EL, Paula MO, Marques MM, Mello SS, Zarate-Blades CR, Nguyen C, Houlgatte R, Donadi EA, Sakamoto-Hojo ET, Passos GA (2006) Hybridization signatures of gamma-irradiated murine fetal thymus organ culture (FTOC) reveal modulation of genes associated with T-cell receptor V(D)J recombination and DNA repair. Mol Immunol 43:464–472. doi:10.1016/j.molimm.2005.03.010

    Article  PubMed  CAS  Google Scholar 

  9. Eisen MB, Spellmam PT, Brown PO, Botstein D (1998) Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci USA 95:14863–14868. doi:10.1073/pnas.95.25.14863

    Article  PubMed  CAS  Google Scholar 

  10. Tusher VG, Tibshirani R, Chu G (2001) Significance analysis of microarrays applied to ionizing radiation response. Proc Natl Acad Sci USA 98:5126–5121. doi:10.1073/pnas.091062498

    Article  Google Scholar 

  11. Sousa-Cardoso R, Magalhães DA, Baião AM, Junta CM, Macedo C, Marques MM et al (2006) Onset of promiscuous gene expression in fetal thymus organ culture. Immunology 119:369–375. doi:10.1111/j.1365-2567.2006.02441.x

    Article  PubMed  CAS  Google Scholar 

  12. Wu CC, Huang HC, Juan HF, Chen ST (2004) GeneNetwork: an interactive tool for reconstruction of genetic network using microarray data. Bioinformatics 20:3691–3693. doi:10.1093/bioinformatics/bth428

    Article  PubMed  CAS  Google Scholar 

  13. Schatz DG (2004) V(D)J recombination. Immunol Rev 200:5–11. doi:10.1111/j.0105-2896.2004.00173.x

    Article  PubMed  CAS  Google Scholar 

  14. Kishimoto H, Sprent J (2000) The thymus and negative selection. Immunol Res 21:315–323. doi:10.1385/IR:21:2-3:315

    Article  PubMed  CAS  Google Scholar 

  15. Ghendler Y, Hussey RE, Witte T, Mizoguchi E, Clayton LK, Bhan AK et al (1997) Double-positive T cell receptor (high) thymocytes are resistant to peptide/major histocompatibility complex ligand induced negative selection. Eur J Immunol 27:2279–2289. doi:10.1002/eji.1830270923

    Article  PubMed  CAS  Google Scholar 

  16. Shortman K, Wu L (1996) Early T lymphocytes progenitors. Annu Rev Immunol 14:29–47. doi:10.1146/annurev.immunol.14.1.29

    Article  PubMed  CAS  Google Scholar 

  17. Junta CM, Passos GAS (1998) Emergence of TCR alpha/beta V(D)J recombination and transcription during ontogeny of inbred mouse strains. Mol Cell Biochem 187:67–72. doi:10.1023/A:1006807021251

    Article  PubMed  CAS  Google Scholar 

  18. Macedo C, Junta CM, Passos GAS (1999) Onset of T-cell receptor VBeta8.1 and DBeta2.1 V(D)J recombination and transcription during ontogeny of inbred mouse strains. Immunol Lett 69:371–373. doi:10.1016/S0165-2478(99)00110-8

    Article  PubMed  CAS  Google Scholar 

  19. Espanhol AR, Macedo C, Junta CM, Cardoso RS, Victorero G, Loriod B et al (2003) Gene expression profiling during thymus ontogeny and its association with TCRVbeta8.1-Dbeta2.1 rearrangements of inbred mouse strains. Mol Cell Biochem 252:223–228. doi:10.1023/A:1025556510001

    Article  PubMed  CAS  Google Scholar 

  20. DeRyckere D, Mann DL, DeGregori J (2003) Characterization of transcriptional regulation during negative selection in vivo. J Immunol 171:802–811

    PubMed  CAS  Google Scholar 

  21. Hoffmann R, Bruno L, Seidl T, Rolink A, Melchers F (2003) Rules for gene usage inferred from a comparison of large-scale gene expression profiles of T and B lymphocytes development. J Immunol 170:1339–1353

    PubMed  CAS  Google Scholar 

  22. Schmitz I, Clayton LK, Reinherz EL (2003) Gene expression analysis of thymocyte selection in vivo. Int Immunol 15:1237–1248. doi:10.1093/intimm/dxg125

    Article  PubMed  CAS  Google Scholar 

  23. Rugh R (1968) The mouse. Its reproduction and development, 1st edn. Burgess Publishing Company, Edina

    Google Scholar 

  24. Nguyen C, Rocha D, Granjeaud S, Baldit M, Bernard K, Naquet P et al (1995) Differential gene expression in murine thymus assayed by quantitative hybridization of arrayed cDNA clones. Genomics 29:207–215. doi:10.1006/geno.1995.1233

    Article  PubMed  CAS  Google Scholar 

  25. Bertucci F, Houlgatte R, Granjeaud S, Nasser V, Loriod B, Beaudoing E et al (2002) Prognosis of breast cancer and gene expression profiling using DNA arrays. Ann N Y Acad Sci 975:217–231

    PubMed  CAS  Google Scholar 

  26. Verdeil G, Puthier D, Nguyen C, Schmitt-Verhulst AM, Auphan-Anezin N (2002) Gene profiling approach to establish the molecular bases for partial versus full activation of naïve CD8 T lymphocytes. Ann NY Acad Sci 975:68–76

    Article  PubMed  CAS  Google Scholar 

  27. Honore P, Granjeaud S, Tagett R, Deraco S, Beaudoing E, Rougemont J et al (2006) MicroArray facility: a laboratory information management system with extended support for nylon based technologies. BMC Genomics 7:240. doi:10.1186/1471-2164-7-240

    Article  PubMed  CAS  Google Scholar 

  28. Quackenbush J (2002) Microarray data normalization and transformation. Nat Genet 32:496–501. doi:10.1038/ng1032

    Article  PubMed  CAS  Google Scholar 

  29. Basso K, Margolin AA, Stolovitzky G, Klein U, Dalla-Favera R, Califano A (2005) Reverse engineering of regulatory networks in human B cells. Nat Genet 37:382–390. doi:10.1038/ng1532

    Article  PubMed  CAS  Google Scholar 

  30. Margolin A, Nemenman I, Basso K, Wiggins C, Stolovitzky G, Dalla Favera R et al (2006) Aracne: an algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context. BMC Bioinformatics Suppl 1: S7

  31. Gardner T, di Bernardo D, Lorenz D, Collins J (2003) Infering genetic networks and identifying compound mode of action via expression profiling. Science 301:102–105. doi:10.1126/science.1081900

    Article  PubMed  CAS  Google Scholar 

  32. Di Bernardo D, Thomson M, Gardner T, Chobot S, Eastwood E, Wojtovich A et al (2005) Chemogenomic profiling on a genome-wide scale using reverse-engineered gene networks. Nat Biotechnol 23:377–383. doi:10.1038/nbt1075

    Article  PubMed  CAS  Google Scholar 

  33. Bansal M, Della Gatta G, di Bernardo D (2006) Inference of gene regulatory networks and compound mode of action from time course gene expression profiles. Bioinformatics 22:815–822. doi:10.1093/bioinformatics/btl003

    Article  PubMed  CAS  Google Scholar 

  34. Yu J, Smith VA, Wang PP, Hartemink AJ, Jarvis ED (2004) Advances to Bayesian network inference for generating causal networks from observational biological data. Bioinformatics 20:3594–3603. doi:10.1093/bioinformatics/bth448

    Article  PubMed  CAS  Google Scholar 

  35. Soinov LA, Krestyaninova MA, Brazma A (2003) Towards reconstruction of gene networks from expression data by supervised learning. Genome Biol 4(1):R6.1–R6.10

    Article  Google Scholar 

  36. Faith JJ, Hayete B, Thaden JT et al (2007) Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles. PLoS Biol 5:54–66. doi:10.1371/journal.pbio.0050008

    Article  CAS  Google Scholar 

  37. Sandmann T, Girardot C, Brehme M et al (2007) A core transcriptional network for early mesoderm development in Drosophila melanogaster. Genes Dev 21:436–449. doi:10.1101/gad.1509007

    Article  PubMed  CAS  Google Scholar 

  38. Takaku T, Ohyashiki JH, Zhang Y, Ohyashikik K (2005) Estimating immunoregulatory gene networks in human herpesvirus type 6-infected T cells. Biochem Biophys Res Commun 336:469–477. doi:10.1016/j.bbrc.2005.08.104

    Article  PubMed  CAS  Google Scholar 

  39. Takasaki I, Takarada S, Fukuchi M, Yasuda M, Tsuda M, Tabuchi Y (2007) Identification of genetic networks involved in the cell growth arrest and proliferation of a rat astrocyte cell line RCG-12. J Cell Biochem 102:1472–1485. doi:10.1002/jcb.21369

    Article  PubMed  CAS  Google Scholar 

  40. de La Fuente A, Brazhnik P, Mendes P (2002) Linking the genes: inferring quantitative gene networks from microarray data. Trends Genet 18:395–398. doi:10.1016/S0168-9525(02)02692-6

    Article  PubMed  Google Scholar 

  41. Feske S, Giltnane J, Dolmetsch R, Staudt LM, Rao A (2001) Gene regulation mediated by calcium signals in T lymphocytes. Nat Immunol 2:316–324. doi:10.1038/86318

    Article  PubMed  CAS  Google Scholar 

  42. Feske S, Okamura H, Hogan PG, Rao A (2003) Ca+/calcineurin signalling in cells of the immune system. Biochem Biophys Res Commun 311:1117–1122. doi:10.1016/j.bbrc.2003.09.174

    Article  PubMed  CAS  Google Scholar 

  43. Heissmeyer V, Macian F, Im SH, Varma R, Feske S, Venuprasad K et al (2004) Calcineurin imposes T cell unresponsiveness through targeted proteolysis of signaling proteins. Nat Immunol 5:255–265. doi:10.1038/ni1047

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgments

This study was funded by the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) and the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq). The cDNA clones used for preparing the microarrays were kindly ceded by Dr. Catherine Nguyen (INSERM, URM 206, Marseille, France). We thank Guilherme Liberato Silva for help with the GeneNetwork program and discussions.

Author information

Authors and Affiliations

  1. Molecular Immunogenetics Group, Department of Genetics, Faculty of Medicine of Ribeirão Preto, University of São Paulo (USP), 14040-900, Ribeirão Preto, SP, Brazil

    Cláudia Macedo, Danielle A. Magalhães, Monique Tonani, Márcia C. Marques, Cristina M. Junta & Geraldo A. S. Passos

  2. Discipline of Genetics, Department of Morphology (DMEF), Faculty of Dentistry, University of São Paulo (USP), 14040-904, Ribeirão Preto, SP, Brazil

    Geraldo A. S. Passos

Authors
  1. Cláudia Macedo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Danielle A. Magalhães
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Monique Tonani
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Márcia C. Marques
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Cristina M. Junta
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Geraldo A. S. Passos
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Geraldo A. S. Passos.

Additional information

Cláudia Macedo and Danielle A. Magalhães contributed equally to this study.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Macedo, C., Magalhães, D.A., Tonani, M. et al. Genes that code for T cell signaling proteins establish transcriptional regulatory networks during thymus ontogeny. Mol Cell Biochem 318, 63–71 (2008). https://doi.org/10.1007/s11010-008-9857-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11010-008-9857-7

Keywords

Search

Navigation