Gene expression noise in a complex artificial toxin expression system

English version

Autoři: Alexandra Goetz ^aff001; Andreas Mader ^aff001; Benedikt von Bronk ^aff001; Anna S. Weiss ^aff001; Madeleine Opitz ^aff001
Působiště autorů: Faculty of Physics and Center for NanoScience, Ludwig-Maximilians-Universität München, Geschwister-Scholl-Platz 1, Munich, Germany ^aff001
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0227249

Souhrn

Gene expression is an intrinsically stochastic process. Fluctuations in transcription and translation lead to cell-to-cell variations in mRNA and protein levels affecting cellular function and cell fate. Here, using fluorescence time-lapse microscopy, we quantify noise dynamics in an artificial operon in Escherichia coli, which is based on the native operon of ColicinE2, a toxin. In the natural system, toxin expression is controlled by a complex regulatory network; upon induction of the bacterial SOS response, ColicinE2 is produced (cea gene) and released (cel gene) by cell lysis. Using this ColicinE2-based operon, we demonstrate that upon induction of the SOS response noise of cells expressing the operon is significantly lower for the (mainly) transcriptionally regulated gene cea compared to the additionally post-transcriptionally regulated gene cel. Likewise, we find that mutations affecting the transcriptional regulation by the repressor LexA do not significantly alter the population noise, whereas specific mutations to post-transcriptionally regulating units, strongly influence noise levels of both genes. Furthermore, our data indicate that global factors, such as the plasmid copy number of the operon encoding plasmid, affect gene expression noise of the entire operon. Taken together, our results provide insights on how noise in a native toxin-producing operon is controlled and underline the importance of post-transcriptional regulation for noise control in this system.

Klíčová slova:

Gene expression – Messenger RNA – Mutant strains – Noise reduction – Operons – Plasmid construction – Toxins – Yellow fluorescent protein

Zdroje

1. Elowitz MB, Levine AJ, Siggia ED, Swain PS. Stochastic gene expression in a single cell. Science (80-). 2002;297: 1183–1187. doi: 10.1126/science.1070919 12183631

2. Kærn M, Elston TC, Blake WJ, Collins JJ. Stochasticity in gene expression: From theories to phenotypes. Nat Rev Genet. 2005;6: 451–464. doi: 10.1038/nrg1615 15883588

3. McAdams HH, Arkin A. Stochastic mechanisms in gene expression. Proc Natl Acad Sci. 1997;94: 814–819. doi: 10.1073/pnas.94.3.814 9023339

4. Losick R, Desplan C. Stochasticity and Cell Fate. Science (80-). 2008;320: 65–68. doi: 10.1126/science.1147888 18388284

5. Ferguson ML, Le Coq D, Jules M, Aymerich S, Radulescu O, Declerck N, et al. Reconciling molecular regulatory mechanisms with noise patterns of bacterial metabolic promoters in induced and repressed states. Proc Natl Acad Sci. 2012;109: 155–160. doi: 10.1073/pnas.1110541108 22190493

6. Sanchez A, Choubey S, Kondev J. Regulation of Noise in Gene Expression. Annu Rev Biophys. 2013;42: 469–491. doi: 10.1146/annurev-biophys-083012-130401 23527780

7. Ozbudak E, Thattai M, Kurtser I, Grossman A, van Oudenaarden A. Regulation of noise in the expression of a single gene. Nat Genet. 2002;

8. Murphy KF, Adams RM, Wang X, Balázsi G, Collins JJ. Tuning and controlling gene expression noise in synthetic gene networks. Nucleic Acids Res. 2010;38: 2712–2726. doi: 10.1093/nar/gkq091 20211838

9. Hansen MMK, Weinberger LS. Post-Transcriptional Noise Control. BioEssays. 2019;41: 1–10. doi: 10.1002/bies.201900130

10. Kleijn IT, Krah LHJ, Hermsen R. Noise propagation in an integrated model of bacterial gene expression and growth. PLoS Comput Biol. 2018;14: 1–18. doi: 10.1371/journal.pcbi.1006386 30289879

11. Pedraza JM, van Oudenaarden A. Noise propagation in gene networks. Science (80-). 2005;307: 1–12. doi: 10.1126/science.1109090 15790857

12. Newman JRS, Ghaemmaghami S, Ihmels J, Breslow DK, Noble M, DeRisi JL, et al. Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise. Nature. 2006;441: 840–846. doi: 10.1038/nature04785 16699522

13. Blake WJ, Kærn M, Cantor CR, Collins JJ. Noise in eukaryotic gene expression. 2003;249: 247–249.

14. Mundt M, Anders A, Murray SM, Sourjik V. A System for Gene Expression Noise Control in Yeast. ACS Synth Biol. 2018;7: 2618–2626. doi: 10.1021/acssynbio.8b00279 30354070

15. Silander OK, Nikolic N, Zaslaver A, Bren A, Kikoin I, Alon U, et al. A Genome-Wide Analysis of Promoter-Mediated Phenotypic Noise in Escherichia coli Olin. Plos Gene. 2012;8. doi: 10.1371/journal.pgen.1002443 22275871

16. Carey JN, Goulian M. A bacterial signaling system regulates noise to enable bet hedging. Curr Genet. 2018; 1–6. doi: 10.1007/s00294-018-0856-2 29947971

17. Ackermann M. A functional perspective on phenotypic heterogeneity in microorganisms. Nat Rev Microbiol. 2015;13: 497–508. doi: 10.1038/nrmicro3491 26145732

18. Colin R, Rosazza C, Vaknin A, Sourjik V. Multiple sources of slow activity fluctuations in a bacterial chemosensory network. Elife. 2017;6: 1–32. doi: 10.7554/eLife.26796 29231168

19. Engl C. Noise in bacterial gene expression. Biochem Soc Trans. 2018;47: 209–217. doi: 10.1042/BST20180500 30578346

20. Wang Z, Zhang J. Impact of gene expression noise on organismal fitness and the efficacy of natural selection. Proc Natl Acad Sci. 2011;108: E67–E76. doi: 10.1073/pnas.1100059108 21464323

21. Kussell E. Phenotypic Diversity, Population Growth, and Information in Fluctuating Environments. Science (80-). 2005;309: 2075–2078. doi: 10.1126/science.1114383 16123265

22. Raj A, van Oudenaarden A. Nature, Nurture, or Chance: Stochastic Gene Expression and Its Consequences. Cell. 2008;135: 216–226. doi: 10.1016/j.cell.2008.09.050 18957198

23. Raser JM, O’Shea EK. Noise in Gene Expression: Origins, Consequences, and Control. Science (80-). 2005;309: 2010 LP– 2013. Available: http://science.sciencemag.org/content/309/5743/2010.abstract

24. Li GW, Xie XS. Central dogma at the single-molecule level in living cells. Nature. 2011;475: 308–315. doi: 10.1038/nature10315 21776076

25. Balázsi G, Van Oudenaarden A, Collins JJ. Cellular decision making and biological noise: From microbes to mammals. Cell. 2011;144: 910–925. doi: 10.1016/j.cell.2011.01.030 21414483

26. Cascales E, Buchanan SK, Duche D, Kleanthous C, Lloubes R, Postle K, et al. Colicin Biology. Microbiol Mol Biol Rev. 2007;71: 158–229. doi: 10.1128/MMBR.00036-06 17347522

27. Wu PJ, Shannon K, Phillips I. Mechanisms of hyperproduction of TEM-1 β-lactamase by clinical isolates of escherichia coli. J Antimicrob Chemother. 1995;36: 927–939. doi: 10.1093/jac/36.6.927 8821592

28. Millan AS, Escudero JA, Gifford DR, Mazel D, Maclean RC. Multicopy plasmids potentiate the evolution of antibiotic resistance in bacteria. Nat Ecol Evol. 2016; doi: 10.1038/s41559-016-0010 28812563

29. Kerr B, Riley MA, Feldman MW, Bohannan BJM. Local dispersal promotes biodiversity in a real-life game of rock-paper-scissors. Nature. 2002;418: 171–174. doi: 10.1038/nature00823 12110887

30. Kelsic ED, Zhao J, Vetsigian K, Kishony R. Counteraction of antibiotic production and degradation stabilizes microbial communities. Nature. 2015;521: 516–519. doi: 10.1038/nature14485 25992546

31. Kirkup BC, Riley MA. Antibiotic-mediated antagonism leads to a bacterial game of rock–paper–scissors in vivo. Nature. 2004;428: 694–696.

32. Lechner M, Schwarz M, Opitz M, Frey E. Hierarchical Post-transcriptional Regulation of Colicin E2 Expression in Escherichia coli. PLoS Comput Biol. 2016;12: 1–20. doi: 10.1371/journal.pcbi.1005243 27977665

33. Reichenbach T, Mobilia M, Frey E. Mobility promotes and jeopardizes biodiversity in rock-paper-scissors games. Nature. 2007;448: 1046–1049. doi: 10.1038/nature06095 17728757

34. von Bronk B, Schaffer SA, Götz A, Opitz M. Effects of stochasticity and division of labor in toxin production on two-strain bacterial competition in Escherichia coli. PLoS Biol. 2017;15: 1–25. doi: 10.1371/journal.pbio.2001457 28459803

35. von Bronk B, Götz A, Opitz M. Locality of interactions in three-strain bacterial competition. Phyisical Biol. 2019;16.

36. Mader A, von Bronk B, Ewald B, Kesel S, Schnetz K, Frey E, et al. Amount of Colicin Release in Escherichia coli Is Regulated by Lysis Gene Expression of the Colicin E2 Operon. PLoS One. 2015;10: e0119124. doi: 10.1371/journal.pone.0119124 25751274

37. Mrak P, Podlesek Z, Van Putten JPM, Žgur-Bertok D. Heterogeneity in expression of the Escherichia coli colicin K activity gene cka is controlled by the SOS system and stochastic factors. Mol Genet Genomics. 2007;277: 391–401. doi: 10.1007/s00438-006-0185-x 17216493

38. Kamenšek S, Podlesek Z, Gillor O, Žgur-Bertok D. Genes regulated by the Escherichia coli SOS repressor LexA exhibit heterogenous expression. BMC Microbiol. 2010;10: 283. doi: 10.1186/1471-2180-10-283 21070632

39. Ozeki H, Stocker B, De Margerie H. Production of colicine by single bacteria. Nature. 1959;184.

40. Riley M a., Wertz JE. Bacteriocins: Evolution, Ecology, and Application. Annu Rev Microbiol. 2002;56: 117–137. doi: 10.1146/annurev.micro.56.012302.161024 12142491

41. Yang TY, Sung YM, Lei GS, Romeo T, Chak KF. Posttranscriptional repression of the cel gene of the ColE7 operon by the RNA-binding protein CsrA of Escherichia coli. Nucleic Acids Res. 2010;38: 3936–3951. doi: 10.1093/nar/gkq177 20378712

42. Weilbacher T, Suzuki K, Dubey AK, Wang X, Gudapaty S, Morozov I, et al. A novel sRNA component of the carbon storage regulatory system of Escherichia coli. Mol Microbiol. 2003;48: 657–670. doi: 10.1046/j.1365-2958.2003.03459.x 12694612

43. Suzuki K, Babitzke P, Kushner SR, Romeo T. Identification of a novel regulatory protein (CsrD) that targets the global regulatory RNAs CsrB and CsrC for degradation by RNase E. Genes Dev. 2006;20: 2605–2617. doi: 10.1101/gad.1461606 16980588

44. Gudapaty S, Suzuki K, Wang X, Romeo T, Wang XIN, Babitzke P. Regulatory Interactions of Csr Components: the RNA Binding Protein CsrA Activates csrB Transcription in Escherichia coli. J Bacteriol. 2001;183: 6017–6027. doi: 10.1128/JB.183.20.6017-6027.2001 11567002

45. Babitzke P, Romeo T. CsrB sRNA family: sequestration of RNA-binding regulatory proteins. Curr Opin Microbiol. 2007;10: 156–163. doi: 10.1016/j.mib.2007.03.007 17383221

46. Vakulskas CA, Leng Y, Abe H, Amaki T, Okayama A, Babitzke P, et al. Antagonistic control of the turnover pathway for the global regulatory sRNA CsrB by the CsrA and CsrD proteins. Nucleic Acids Res. 2016;44: 7896–7910. doi: 10.1093/nar/gkw484 27235416

47. Romeo T, Babitzke P. Global Regulation by CsrA and Its RNA Antagonists. Microbiol Spectr. 2018;6: 1–14. doi: 10.1128/microbiolspec.RWR-0009-2017.Correspondence

48. Götz A, Lechner M, Mader A, von Bronk B, Frey E, Opitz M. CsrA and its regulators control the time-point of ColicinE2 release in Escherichia coli. Sci Rep. 2018;8: 6537. doi: 10.1038/s41598-018-24699-z 29695793

49. Shimoni Y, Altuvia S, Margalit H, Biham O. Stochastic Analysis of the SOS Response in Escherichia coli. PLoS One. 2009;4: e5363. Available: doi: 10.1371/journal.pone.0005363 19424504

50. Vimberg V, Tats A, Remm M, Tenson T. Translation initiation region sequence preferences in Escherichia coli. BMC Mol Biol. 2007;8: 100. doi: 10.1186/1471-2199-8-100 17973990

51. Cole ST, Saint-Joanis B PA. Molecular characterisation of the colicin E2 operon and identification of its products. Mol Gen Genet. 1985;24: 198(3):465–72. doi: 10.1007/bf00332940 3892228

52. Silva JPN, Lopes SV, Grilo DJ, Hensel Z. Plasmids for Independently Tunable, Low-Noise Expression of Two Genes. mSphere. 2019; 1–9. https://doi.org/10.1128/mSphere.00340–19. Editor

53. Dacheux E, Malys N, Xiang M, Ramachandran V, Mendes P, McCarthy JEG. Translation initiation events on structured eukaryotic mRNAs generate gene expression noise. Nucleic Acids Res. 2017;45: 6981–6992. doi: 10.1093/nar/gkx430 28521011

54. Bar-Even A, Paulsson J, Maheshri N, Carmi M, O’Shea E, Pilpel Y, et al. Noise in protein expression scales with natural protein abundance. Nat Genet. 2006;38: 636–643. doi: 10.1038/ng1807 16715097

55. Romeo T. Global regulation by the small RNA-binding protein CsrA and the non- coding RNA molecule CsrB. Mol Microbiol. 1998;29: 1321–1330. doi: 10.1046/j.1365-2958.1998.01021.x 9781871

56. Taniguchi Y, Choi PJ, Li G, Chen H, Babu M, Hearn J, et al. Quantifying E. coli proteome and transcriptome with single-molecule sensitivity in single cells. Science (80-). 2010;329: 533–539. doi: 10.1126/science.1188308 20671182

57. Esquerré T, Bouvier M, Turlan C, Carpousis AJ, Girbal L, Cocaign-Bousquet M. The Csr system regulates genome-wide mRNA stability and transcription and thus gene expression in Escherichia coli. Sci Rep. 2016;6: 25057. doi: 10.1038/srep25057 27112822

58. Baker CS, Eöry L a., Yakhnin H, Mercante g, Romeo T, Babitzke P. CsrA inhibits translation initiation of Escherichia coli hfq by binding to a single site overlapping the Shine-Dalgarno sequence. J Bacteriol. 2007;189: 5472–5481. doi: 10.1128/JB.00529-07 17526692

59. Vassilieva IM, Garber MB. The regulatory role of the Hfq protein in bacterial cells. Mol Biol. 2002;36: 785–791. doi: 10.1023/A:1021621623503

60. Valentin-Hansen P. Structure, function and RNA binding mechanisms of the prokaryotic Sm-like protein hfq. Regulatory RNAs in Prokaryotes. Springer; 2012. pp. 147–162.

61. Edri S, Tuller T. Quantifying the effect of ribosomal density on mRNA stability. PLoS One. 2014;9. doi: 10.1371/journal.pone.0102308 25020060

62. Jones DL, Brewster RC, Phillips R. Promoter architecture dictates cell-to-cell variability in gene expression. Science (80-). 2014;346: 1533–1536. doi: 10.1126/science.1255301 25525251

63. Hol FJH, Voges MJ, Dekker C, Keymer JE. Nutrient-responsive regulation determines biodiversity in a colicin-mediated bacterial community. BMC Biol. 2014; 1–14. doi: 10.1186/1741-7007-12-1

64. Edelstein A, Amodaj N, Hoover K, Vale R, Stuurman N. Computer Control of Microscopes Using MicroManager. Curr Protoc Mol Biol. 2010; doi: 10.1002/0471142727.mb1420s92 20890901

65. Rasband WS (USNI of H. ImageJ [Internet]. Available: http://imagej.nih.gov/ij/

66. Youssef S, Gude S, Radler JO. Automated tracking in live-cell time-lapse movies. Integr Biol. 2011;3: 1095–1101. doi: 10.1039/C1IB00035G 21959912

67. Kremers G, Goedhart J, Munster EB Van, Gadella TWJ. Cyan and Yellow Super Fluorescent Proteins with Improved Brightness, Protein Folding, and FRET F ö rster Radius Cyan and Yellow Super Fluorescent Proteins with Improved Brightness, Protein Folding, and FRET Fo. Biochemistry. 2006; 6570–6580. doi: 10.1021/bi0516273 16716067

68. Kremers GJ, Goedhart J, Van Den Heuvel DJ, Gerritsen HC, Gadella TWJ. Improved green and blue fluorescent proteins for expression in bacteria and mammalian cells. Biochemistry. 2007;46: 3775–3783. doi: 10.1021/bi0622874 17323929

69. Markwardt ML, Kremers GJ, Kraft C a, Ray K, Cranfill PJC, Wilson K a., et al. An improved cerulean fluorescent protein with enhanced brightness and reduced reversible photoswitching. PLoS One. 2011;6. doi: 10.1371/journal.pone.0017896 21479270

Gene expression noise in a complex artificial toxin expression system

Souhrn

Klíčová slova:

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PLOS One

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