Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Deciphering the transcriptional regulatory logic of amino acid metabolism


Although metabolic networks have been reconstructed on a genome scale, the corresponding reconstruction and integration of governing transcriptional regulatory networks has not been fully achieved. Here we reconstruct such an integrated network for amino acid metabolism in Escherichia coli. Analysis of ChIP-chip and gene expression data for the transcription factors ArgR, Lrp and TrpR showed that 19 out of 20 amino acid biosynthetic pathways are either directly or indirectly controlled by these regulators. Classifying the regulated genes into three functional categories of transport, biosynthesis and metabolism leads to the elucidation of regulatory motifs that constitute the integrated network's basic building blocks. The regulatory logic of these motifs was determined on the basis of relationships between transcription factor binding and changes in the amount of transcript in response to exogenous amino acids. Remarkably, the resulting logic shows how amino acids are differentiated as signaling and nutrient molecules, revealing the overarching regulatory principles of the amino acid stimulon.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Get just this article for as long as you need it


Prices may be subject to local taxes which are calculated during checkout

Figure 1: Genome-wide distribution of ArgR- and TrpR-binding regions (regulatory code analysis).
Figure 2: Functional classification of genes directly regulated by ArgR, Lrp and TrpR.
Figure 3: Delineation of amino acid biosynthetic pathways and transport systems in E. coli (topological analysis).
Figure 4: Causal relationships between direct associations of transcription factors and the changes in RNA transcript levels of genes (functional analysis).
Figure 5: Reconstruction of regulatory motif and the logical structures of connected-circuit motifs in response to the exogenous amino acids (network analysis).

Accession codes


Gene Expression Omnibus


  1. Joyce, A.R. & Palsson, B.Ø. The model organism as a system: integrating 'omics' data sets. Nat. Rev. Mol. Cell Biol. 7, 198–210 (2006).

    Article  CAS  Google Scholar 

  2. Covert, M.W., Knight, E.M., Reed, J.L., Herrgard, M.J. & Palsson, B.Ø. Integrating high-throughput and computational data elucidates bacterial networks. Nature 429, 92–96 (2004).

    Article  CAS  Google Scholar 

  3. Cho, B.K., Barrett, C.L., Knight, E.M., Park, Y.S. & Palsson, B.Ø. Genome-scale reconstruction of the Lrp regulatory network in Escherichia coli. Proc. Natl. Acad. Sci. USA 105, 19462–19467 (2008).

    Article  CAS  Google Scholar 

  4. Alon, U. Network motifs: theory and experimental approaches. Nat. Rev. Genet. 8, 450–461 (2007).

    Article  CAS  Google Scholar 

  5. Hershberg, R. & Margalit, H. Co-evolution of transcription factors and their targets depends on mode of regulation. Genome Biol. 7, R62 (2006).

    Article  Google Scholar 

  6. Charlier, D. et al. Arginine regulon of Escherichia coli K-12. A study of repressor-operator interactions and of in vitro binding affinities versus in vivo repression. J. Mol. Biol. 226, 367–386 (1992).

    Article  CAS  Google Scholar 

  7. Yang, J. et al. In vivo and in vitro studies of TrpR-DNA interactions. J. Mol. Biol. 258, 37–52 (1996).

    Article  CAS  Google Scholar 

  8. Pittard, J., Camakaris, H. & Yang, J. The TyrR regulon. Mol. Microbiol. 55, 16–26 (2005).

    Article  CAS  Google Scholar 

  9. Tani, T.H., Khodursky, A., Blumenthal, R.M., Brown, P.O. & Matthews, R.G. Adaptation to famine: a family of stationary-phase genes revealed by microarray analysis. Proc. Natl. Acad. Sci. USA 99, 13471–13476 (2002).

    Article  CAS  Google Scholar 

  10. Levin, J.Z. et al. Comprehensive comparative analysis of strand-specific RNA sequencing methods. Nat. Methods 7, 709–715 (2010).

    Article  CAS  Google Scholar 

  11. Faith, J.J. et al. Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles. PLoS Biol. 5, e8 (2007).

    Article  Google Scholar 

  12. Calvo, J.M. & Matthews, R.G. The leucine-responsive regulatory protein, a global regulator of metabolism in Escherichia coli. Microbiol. Rev. 58, 466–490 (1994).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Cho, B.K., Knight, E.M. & Palsson, B.Ø. PCR-based tandem epitope tagging system for Escherichia coli genome engineering. Biotechniques 40, 67–72 (2006).

    Article  CAS  Google Scholar 

  14. Cho, B.K. et al. The transcription unit architecture of the Escherichia coli genome. Nat. Biotechnol. 27, 1043–1049 (2009).

    Article  CAS  Google Scholar 

  15. Gama-Castro, S. et al. RegulonDB version 7.0: transcriptional regulation of Escherichia coli K-12 integrated within genetic sensory response units (Gensor Units). Nucleic Acids Res. 39, D98–D105 (2011).

    Article  CAS  Google Scholar 

  16. Keseler, I.M. et al. EcoCyc: a comprehensive view of Escherichia coli biology. Nucleic Acids Res. 37, D464–D470 (2009).

    Article  CAS  Google Scholar 

  17. Caldara, M., Charlier, D. & Cunin, R. The arginine regulon of Escherichia coli: whole-system transcriptome analysis discovers new genes and provides an integrated view of arginine regulation. Microbiology 152, 3343–3354 (2006).

    Article  CAS  Google Scholar 

  18. Caldara, M., Minh, P.N., Bostoen, S., Massant, J. & Charlier, D. ArgR-dependent repression of arginine and histidine transport genes in Escherichia coli K-12. J. Mol. Biol. 373, 251–267 (2007).

    Article  CAS  Google Scholar 

  19. Jeeves, M., Evans, P.D., Parslow, R.A., Jaseja, M. & Hyde, E.I. Studies of the Escherichia coli Trp repressor binding to its five operators and to variant operator sequences. Eur. J. Biochem. 265, 919–928 (1999).

    Article  CAS  Google Scholar 

  20. Van Duyne, G.D., Ghosh, G., Maas, W.K. & Sigler, P.B. Structure of the oligomerization and L-arginine binding domain of the arginine repressor of Escherichia coli. J. Mol. Biol. 256, 377–391 (1996).

    Article  CAS  Google Scholar 

  21. Zhang, R.G. et al. The crystal structure of trp aporepressor at 1.8 A shows how binding tryptophan enhances DNA affinity. Nature 327, 591–597 (1987).

    Article  CAS  Google Scholar 

  22. Maas, W.K. Studies on the mechanism of repression of arginine biosynthesis in Escherichia coli: I. dominance of repressibility in diploids. J. Mol. Biol. 8, 365–370 (1964).

    Article  CAS  Google Scholar 

  23. Kiupakis, A.K. & Reitzer, L. ArgR-independent induction and ArgR-dependent superinduction of the astCADBE operon in Escherichia coli. J. Bacteriol. 184, 2940–2950 (2002).

    Article  CAS  Google Scholar 

  24. Khodursky, A.B. et al. DNA microarray analysis of gene expression in response to physiological and genetic changes that affect tryptophan metabolism in Escherichia coli. Proc. Natl. Acad. Sci. USA 97, 12170–12175 (2000).

    Article  CAS  Google Scholar 

  25. Bennett, B.D. et al. Absolute metabolite concentrations and implied enzyme active site occupancy in Escherichia coli. Nat. Chem. Biol. 5, 593–599 (2009).

    Article  CAS  Google Scholar 

  26. Cho, B.K. et al. The PurR regulon in Escherichia coli K-12 MG1655. Nucleic Acids Res. 39, 6456–6464 (2011).

    Article  CAS  Google Scholar 

  27. Krishna, S., Semsey, S. & Sneppen, K. Combinatorics of feedback in cellular uptake and metabolism of small molecules. Proc. Natl. Acad. Sci. USA 104, 20815–20819 (2007).

    Article  CAS  Google Scholar 

  28. Semsey, S. et al. Genetic regulation of fluxes: iron homeostasis of Escherichia coli. Nucleic Acids Res. 34, 4960–4967 (2006).

    Article  CAS  Google Scholar 

  29. Semsey, S., Krishna, S., Sneppen, K. & Adhya, S. Signal integration in the galactose network of Escherichia coli. Mol. Microbiol. 65, 465–476 (2007).

    Article  CAS  Google Scholar 

  30. Powell, B.S. et al. Novel proteins of the phosphotransferase system encoded within the rpoN operon of Escherichia coli. Enzyme IIANtr affects growth on organic nitrogen and the conditional lethality of an erats mutant. J. Biol. Chem. 270, 4822–4839 (1995).

    Article  CAS  Google Scholar 

  31. Klig, L.S., Oxender, D.L. & Yanofsky, C. Second-site revertants of Escherichia coli trp repressor mutants. Genetics 120, 651–655 (1988).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Cho, B.K., Knight, E.M., Barrett, C.L. & Palsson, B.Ø. Genome-wide analysis of Fis binding in Escherichia coli indicates a causative role for A-/AT-tracts. Genome Res. 18, 900–910 (2008).

    Article  CAS  Google Scholar 

  33. Cho, B.K., Knight, E.M. & Palsson, B.Ø. Genomewide identification of protein binding locations using chromatin immunoprecipitation coupled with microarray. Methods Mol. Biol. 439, 131–145 (2008).

    Article  CAS  Google Scholar 

  34. Mosteller, F. & Tukey, J.W. Data Analysis and Regression: A Second Course in Statistics (Addison-Wesley Pub. Co., 1977).

  35. Wu, Z. et al. A model-based background adjustment for oligonucleotide expression arrays. J. Am. Stat. Assoc. 99, 909–917 (2004).

    Article  Google Scholar 

  36. Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B Methodol. 57, 289–300 (1995).

    Google Scholar 

  37. Bailey, T.L. et al. MEME SUITE: tools for motif discovery and searching. Nucleic Acids Res. 37, W202–W208 (2009).

    Article  CAS  Google Scholar 

  38. Bailey, T.L., Williams, N., Misleh, C. & Li, W.W. MEME: discovering and analyzing DNA and protein sequence motifs. Nucleic Acids Res. 34, W369–W373 (2006).

    Article  CAS  Google Scholar 

  39. Makarova, K.S., Mironov, A.A. & Gelfand, M.S. Conservation of the binding site for the arginine repressor in all bacterial lineages. Genome Biol. 2, RESEARCH0013 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

Download references


The authors thank M. Abrams and J. Lerman for critical reading of the manuscript. The US National Institutes of Health (through grant GM062791) and the Office of Science–Biological and Environmental Research, US Department of Energy (through grant DE-FOA-0000143) supported this work.

Author information

Authors and Affiliations



B.-K.C. and B.Ø.P. conceived the study. B.-K.C. and Y.-S.P. designed and performed ChIP-chip and gene expression experiments. B.-K.C. and S.F. analyzed data with contributions from K.Z. The manuscript was written by B.-K.C., S.F., K.Z. and B.Ø.P.

Corresponding authors

Correspondence to Byung-Kwan Cho or Bernhard Ø Palsson.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Results (PDF 1346 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Cho, BK., Federowicz, S., Park, YS. et al. Deciphering the transcriptional regulatory logic of amino acid metabolism. Nat Chem Biol 8, 65–71 (2012).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:

This article is cited by


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing