Systems and Synthetic Biology

, Volume 8, Issue 1, pp 3–20 | Cite as

Analysis of DevR regulated genes in Mycobacterium tuberculosis

  • Arnab Bandyopadhyay
  • Soumi Biswas
  • Alok Kumar Maity
  • Suman K. Banik
Research Article
First Online:
Received:
Revised:
Accepted:
  • 234 Downloads

Abstract

The DevRS two component system of Mycobacterium tuberculosis is responsible for its dormancy in host and becomes operative under hypoxic condition. It is experimentally known that phosphorylated DevR controls the expression of several downstream genes in a complex manner. In the present work we propose a theoretical model to show role of binding sites in DevR mediated gene expression. Individual and collective role of binding sites in regulating DevR mediated gene expression has been shown via modeling. Objective of the present work is twofold. First, to describe qualitatively the temporal dynamics of wild type genes and their known mutants. Based on these results we propose that DevR controlled gene expression follows a specific pattern which is efficient in describing other DevR mediated gene expression. Second, to analyze behavior of the system from information theoretical point of view. Using the tools of information theory we have calculated molecular efficiency of the system and have shown that it is close to the maximum limit of isothermal efficiency.

Keywords

Mycobacterium tuberculosis Dormancy Two component system Information theory 
This is a preview of subscription content, log in to check access.

Notes

Acknowledgements

We express our sincerest gratitude to Jaya S Tyagi and Thomas D Schneider for stimulating discussions and suggestions. AB acknowledges CSIR, Government of India, for a research fellowship (09/015(0375)/2009-EMR-I). SB acknowledges support from Centre of Excellence (CoE) at Bose Institute, Kolkata, supported by DBT, Government of India. AKM acknowledges UGC, Government of India, for a research fellowship [UGC/776/JRF(Sc)]. SKB acknowledges support from Bose Institute through Institutional Programme VI—Development of Systems Biology.

References

  1. Appleby JL, Parkinson JS, Bourret RB (1996) Signal transduction via the multi-step phosphorelay: not necessarily a road less traveled. Cell (Cambridge, MA, US) 86:845–848PubMedCrossRefGoogle Scholar
  2. Barkai N, Leibler S (1997) Robustness in simple biochemical networks. Nat Biotechnol 387(6636):913–917PubMedCrossRefGoogle Scholar
  3. Barrick D, Villanueba K, Childs J, Kalil R, Schneider TD, Lawrence CE, Gold L, Stormo GD (1994) Quantitative analysis of ribosome binding sites in E. coli. Nucleic Acids Res Suppl 22:1287–1295PubMedCentralPubMedCrossRefGoogle Scholar
  4. Berg OG, von Hippel PH (1987) Selection of DNA binding sites by regulatory proteins. statistical-mechanical theory and application to operators and promoters. J Mol Biol 193:723–750PubMedCrossRefGoogle Scholar
  5. Berg OG, von Hippel PH (1988) Selection of dna binding sites by regulatory proteins. Trends Biochem Sci 13:207–211PubMedCrossRefGoogle Scholar
  6. Betts JC, Lukey PT, Robb LC, McAdam RA, Duncan K (2002) Evaluation of a nutrient starvation model of Mycobacterium tuberculosis persistence by gene and protein expression profiling. Mol Microbiol 43:717–731PubMedCrossRefGoogle Scholar
  7. Bijlsma JJ, Groisman EA (2003) Making informed decisions: regulatory interactions between two-component systems. Trends Microbiol 11:359–366PubMedCrossRefGoogle Scholar
  8. Borst A, Theunissen FE (1999) Information theory and neural coding. Nat Neurosci 2:947–957PubMedCrossRefGoogle Scholar
  9. Bretl DJ, Demetriadou C, Zahrt TC (2011) Adaptation to environmental stimuli within the host: two-component signal transduction systems of Mycobacterium tuberculosis. Microbiol Mol Biol Rev 75:566–582PubMedCentralPubMedCrossRefGoogle Scholar
  10. Callen HB (1985) Thermodynamics and an introduction to thermostatistics. Wiley, New YorkGoogle Scholar
  11. Chauhan S, Tyagi JS (2008a) Cooperative binding of phosphorylated DevR to upstream sites is necessary and sufficient for activation of the Rv3134c-DevRs operon in Mycobacterium tuberculosis: implication in the induction of DevR target genes. J Bacteriol 190:4301–4312PubMedCentralPubMedCrossRefGoogle Scholar
  12. Chauhan S, Tyagi JS (2008b) Interaction of DevR with multiple binding sites synergistically activates divergent transcription of nark2-Rv1738 genes in Mycobacterium tuberculosis. J Bacteriol 190:5394–5403PubMedCentralPubMedCrossRefGoogle Scholar
  13. Chauhan S, Sharma D, Singh A, Surolia A, Tyagi JS (2011) Comprehensive insights into mycobacterium tuberculosis DevR (DosR) regulon activation switch. Nucleic Acids Res Suppl 39:7400–7414PubMedCentralPubMedCrossRefGoogle Scholar
  14. Cotter PA, Jones AM (2003) Phosphorelay control of virulence gene expression in bordetella. Trends Microbiol 11:367–373PubMedCrossRefGoogle Scholar
  15. Cover T, Thomas J (1991) Elements of information theory. Wiley-Interscience, New YorkCrossRefGoogle Scholar
  16. Das N, Valjavec-Gratian M, Basuray AN, Fekete RA, Papp PP, Paulsson J, Chattoraj DK (2005) Multiple homeostatic mechanisms in the control of P1 plasmid replication. Proc Natl Acad Sci U S A 102:2856–2861PubMedCentralPubMedCrossRefGoogle Scholar
  17. Güémez J, Fiolhais C, Fiolhais M (2002) Sadi Carnot on Carnot’s theorem. Am J Phys 70:42–47CrossRefGoogle Scholar
  18. Hengen PN, Bartram SL, Stewart LE, Schneider TD (1997) Information analysis of fis binding sites. Nucleic Acids Res Suppl 25:4994–5002PubMedCentralPubMedCrossRefGoogle Scholar
  19. Hoch JA (2000) Two-component and phosphorelay signal transduction. Curr Opin Microbiol 3:165–170PubMedCrossRefGoogle Scholar
  20. Jaynes ET (1988) The evolution of Carnot’s principle. In: Erickson GJ, Smith CR (eds) Maximum-entropy and Bayesian methods in science and engineering, vol 1., Kluwer Acdemic Publishers, Dordrecht, pp 267–281CrossRefGoogle Scholar
  21. Jaynes ET (2003) Note on thermal heating efficiency. Am J Phys 71:180–182CrossRefGoogle Scholar
  22. Kim JG, Takeda Y, Matthews BW, Anderson WF (1987) Kinetic studies on Cro repressor-operator DNA interaction. J Mol Biol 196:149–158PubMedCrossRefGoogle Scholar
  23. Kumar A, Deshane JS, Crossman DK, Bolisetty S, Yan BS, Kramnik I, Agarwal A, Steyn AJ (2008) Heme oxygenase-1-derived carbon monoxide induces the Mycobacterium tuberculosis dormancy regulon. J Biol Chem 283:18032–18039PubMedCrossRefGoogle Scholar
  24. Laub MT, Goulian M (2007) Specificity in two-component signal transduction pathways. Annu Rev Genet 41:121–145PubMedCrossRefGoogle Scholar
  25. Linnell J, Mott R, Field S, Kwiatkowski DP, Ragoussis J, Udalova IA (2004) Quantitative high-throughput analysis of transcription factor binding specificities. Nucleic Acids Res Suppl 32:e44PubMedCentralPubMedCrossRefGoogle Scholar
  26. Park HD, Guinn KM, Harrell MI, Liao R, Voskuil MI, Tompa M, Schoolnik GK, Sherman DR (2003) Rv3133c/DosR is a transcription factor that mediates the hypoxic response of Mycobacterium tuberculosis. Mol Microbiol 48:833–843PubMedCentralPubMedCrossRefGoogle Scholar
  27. Pierce J, Cutler C (1959) Interplanetary communications. In: Ordway III FI (eds) Advances in space science, Vol. 1., Academic Press, Inc, NY, pp 55–109CrossRefGoogle Scholar
  28. Raisbeck G (1963) Information theory: an introduction for scientists and engineers. MIT Press, CambridgeGoogle Scholar
  29. Rhee A, Cheong R, Levchenko A (2012) The application of information theory to biochemical signaling systems. Phys Biol 9:045011PubMedCrossRefGoogle Scholar
  30. Schaufler LE, Klevit RE (2003) Mechanism of DNA binding by the ADR1 zinc finger transcription factor as determined by SPR. J Mol Biol 329:931–939PubMedCrossRefGoogle Scholar
  31. Schneider TD (1991a) Theory of molecular machines. I. Channel capacity of molecular machines. J Theor Biol 148:83–123PubMedCrossRefGoogle Scholar
  32. Schneider TD (1991b) Theory of molecular machines. II. Energy dissipation from molecular machines. J Theor Biol 148:125–137PubMedCrossRefGoogle Scholar
  33. Schneider TD (1994) Sequence logos, machine/channel capacity, Maxwell’s demon, and molecular computers: a review of the theory of molecular machines. Nanotechnology 5:1–18CrossRefGoogle Scholar
  34. Schneider TD (1997a) Information content of individual genetic sequences. J Theor Biol 189:427–441PubMedCrossRefGoogle Scholar
  35. Schneider TD (1997b) Sequence walkers: a graphical method to display how binding proteins interact with DNA or RNA sequences. Nucleic Acids Res Suppl 25:4408–4415PubMedCentralPubMedCrossRefGoogle Scholar
  36. Schneider TD (1999) Measuring molecular information. J Theor Biol 201:87–92PubMedCrossRefGoogle Scholar
  37. Schneider TD (2000) Evolution of biological information. Nucleic Acids Res Suppl 28:2794–2799PubMedCentralPubMedCrossRefGoogle Scholar
  38. Schneider TD (2001) Strong minor groove base conservation in sequence logos implies DNA distortion or base flipping during replication and transcription initiation. Nucleic Acids Res Suppl 29:4881–4891PubMedCentralPubMedCrossRefGoogle Scholar
  39. Schneider TD (2010) 70 % efficiency of bistate molecular machines explained by information theory, high dimensional geometry and evolutionary convergence. Nucleic Acids Res Suppl 38:5995–6006PubMedCentralPubMedCrossRefGoogle Scholar
  40. Schneider TD, Stephens RM (1990) Sequence logos: a new way to display consensus sequences. Nucleic Acids Res Suppl 18:6097–6100PubMedCentralPubMedCrossRefGoogle Scholar
  41. Schneider TD, Stormo GD, Gold L, Ehrenfeucht A (1986) Information content of binding sites on nucleotide sequences. J Mol Biol 188:415–431PubMedCrossRefGoogle Scholar
  42. Shannon CE (1948) The mathematical theory of communication. Bell Syst Tech J 27:379–423CrossRefGoogle Scholar
  43. Shearwin KE, Callen BP, Egan JB (2005) Transcriptional interference—a crash course. Trends Genet 21:339–345PubMedCentralPubMedCrossRefGoogle Scholar
  44. Shiloh MU, Manzanillo P, Cox JS (2008) Mycobacterium tuberculosis senses host-derived carbon monoxide during macrophage infection. Cell Host Microbe 3:323–330PubMedCentralPubMedCrossRefGoogle Scholar
  45. Shultzaberger RK, Roberts LR, Lyakhov IG, Sidorov IA, Stephen AG, Fisher RJ, Schneider TD (2007) Correlation between binding rate constants and individual information of E. coli Fis binding sites. Nucleic Acids Res Suppl 35:5275–5283PubMedCentralPubMedCrossRefGoogle Scholar
  46. Taneja NK, Dhingra S, Mittal A, Naresh M, Tyagi JS (2010) Mycobacterium tuberculosis transcriptional adaptation, growth arrest and dormancy phenotype development is triggered by vitamin C. PLoS One 5:e10860PubMedCentralPubMedCrossRefGoogle Scholar
  47. Voskuil MI, Schnappinger D, Visconti KC, Harrell MI, Dolganov GM, Sherman DR, Schoolnik GK (2003) Inhibition of respiration by nitric oxide induces a Mycobacterium tuberculosis dormancy program. J Exp Med 198:705–713PubMedCentralPubMedCrossRefGoogle Scholar
  48. Wayne LG, Sohaskey CD (2001) Nonreplicating persistence of Mycobacterium tuberculosis. Annu Rev Microbiol 55:139–163PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Arnab Bandyopadhyay
    • 1
  • Soumi Biswas
    • 1
  • Alok Kumar Maity
    • 2
  • Suman K. Banik
    • 1
  1. 1.Department of ChemistryBose InstituteKolkataIndia
  2. 2.Department of ChemistryUniversity of CalcuttaKolkataIndia

Personalised recommendations