Constructing Strong Cell Type-Specific Promoters Through Informed Design

  • Adam J. BrownEmail author
  • David C. James
Part of the Methods in Molecular Biology book series (MIMB, volume 1651)


Promoter functionality is highly context dependent, as exemplified by gene-specific expression profiles across different tissues and cell types. Cell type-specific promoter regulation is a function of each cell’s unique complement of transcriptional machinery components. Accordingly, to achieve high levels of transcriptional activity within a particular cell type, synthetic promoters must be specifically designed to harness those cells discrete repertoire of available transcription factors. Here, we describe a method for constructing very strong cell type-specific synthetic promoters for use in any given mammalian host cell. Transcription factor regulatory elements (TFREs; or transcription factor binding sites) that can independently mediate activation of recombinant gene transcription in the chosen host cells by using available transcription factor activity are identified and utilized as building blocks to construct novel promoter sequences with varying activities. Bioinformatics analysis of synthetic promoter’s TFRE compositions is then performed to determine how differing relative TFRE abundances explain variations in relative promoter activities. This information is used to derive an optimal second-generation promoter library construction design space, such that promoters with maximal transcriptional activity in the host cell type can be created.

Key words

Synthetic promoters Cell type-specific Mammalian cells Transcriptional regulation Transcription factor binding sites 


  1. 1.
    Vaquerizas JM, Kummerfeld SK, Teichmann SA, Luscombe NM (2009) A census of human transcription factors: function, expression and evolution. Nat Rev Genet 10:252–263CrossRefGoogle Scholar
  2. 2.
    Schlabach MR, JK H, Li M, Elledge SJ (2010) Synthetic design of strong promoters. Proc Natl Acad Sci U S A 107:2538–2543CrossRefGoogle Scholar
  3. 3.
    Consortium TF (2014) A promoter-level mammalian expression atlas. Nature 507:462–470CrossRefGoogle Scholar
  4. 4.
    Brown AJ, James DC (2016) Precision control of recombinant gene transcription for CHO cell synthetic biology. Biotechnol Adv 34:492–503CrossRefGoogle Scholar
  5. 5.
    Liu R, Baillie J, Sissons JP, Sinclair JH (1994) The transcription factor YY1 binds to negative regulatory elements in the human cytomegalovirus major immediate early enhancer/promoter and mediates repression in nonpermissive cells. Nucleic Acids Res 22:2453–2459CrossRefGoogle Scholar
  6. 6.
    Chen WY, Townes TM (2000) Molecular mechanism for silencing virally transduced genes involves histone deacetylation and chromatin condensation. Proc Natl Acad Sci U S A 97:377–382CrossRefGoogle Scholar
  7. 7.
    Meier JL, Stinski MF (2013) Major immediate-early enhancer and its gene products. In: Reddehase M (ed) Cytomegaloviruses: from molecular pathogenesis to intervention Caister. Academic, Norfolk, pp 152–173Google Scholar
  8. 8.
    Kim M, O’Callaghan PM, Droms KA, James DC (2011) A mechanistic understanding of production instability in CHO cell lines expressing recombinant monoclonal antibodies. Biotechnol Bioeng 108:2434–2446CrossRefGoogle Scholar
  9. 9.
    Brown AJ, Sweeney B, Mainwaring DO, James DC (2015) NF-κB, CRE and YY1 elements are key functional regulators of CMV promoter-driven transient gene expression in CHO cells. Biotechnol J 10:1019–1028CrossRefGoogle Scholar
  10. 10.
    Han J, McLane B, Kim E-H, Yoon J-W, Jun H-S (2011) Remission of diabetes by insulin gene therapy using a hepatocyte-specific and glucose-responsive synthetic promoter. Mol Ther 19:470–478CrossRefGoogle Scholar
  11. 11.
    Jianwei D, Qianqian Z, Songcai L, Mingjun Z, Xiaohui R, Linlin H, Qingyan J, Yongliang Z (2012) The combination of a synthetic promoter and a CMV promoter improves foreign gene expression efficiency in myocytes. J Biotechnol 158:91–96CrossRefGoogle Scholar
  12. 12.
    Brown AJ, Sweeney B, Mainwaring DO, James DC (2014) Synthetic promoters for CHO cell engineering. Biotechnol Bioeng 111:1638–1647CrossRefGoogle Scholar
  13. 13.
    Manke T, Roider HG, Vingron M (2008) Statistical modeling of transcription factor binding affinities predicts regulatory interactions. PLoS Comput Biol 4:e1000039CrossRefGoogle Scholar
  14. 14.
    Turatsinze J-V, Thomas-Chollier M, Defrance M, van Helden J (2008) Using RSAT to scan genome sequences for transcription factor binding sites and cis-regulatory modules. Nat Protoc 3:1578–1588CrossRefGoogle Scholar
  15. 15.
    Mathelier A, Zhao X, Zhang AW, Parcy F, Worsley-Hunt R, Arenillas DJ, Buchman S, Chen C-y, Chou A, Ienasescu H (2013) JASPAR 2014: an extensively expanded and updated open-access database of transcription factor binding profiles. Nucleic Acids Res 42:D142–D147CrossRefGoogle Scholar
  16. 16.
    Schug J (2008) Using TESS to predict transcription factor binding sites in DNA sequence. Curr Protoc Bioinformatics 21:2.6.1–2.6.15Google Scholar
  17. 17.
    Weingarten-Gabbay S, Segal E (2014) The grammar of transcriptional regulation. Hum Genet 133:701–711CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media LLC 2017

Authors and Affiliations

  1. 1.Department of Chemical and Biological EngineeringUniversity of SheffieldSheffieldUK

Personalised recommendations