Difference between revisions of "Artificial transcriptional terminators"

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Line 100: Line 100:
 
*Terminator 6:
 
*Terminator 6:
  
delG=-16.2 d=54.38 %T>90
+
delG=-16.2 d=57.39 %T>90
  
 
delG reverse=-18.9 d=66.22 %T>90
 
delG reverse=-18.9 d=66.22 %T>90
Line 113: Line 113:
 
*Terminator 7:
 
*Terminator 7:
  
delG=-16.2 d=30.84 %T=80
+
delG=-16.2 d=33.32 %T=80
  
 
delG reverse=-18.9 d=42.69 %T>90
 
delG reverse=-18.9 d=42.69 %T>90
Line 126: Line 126:
 
*Terminator 8:
 
*Terminator 8:
  
delG=-16.2 d=21.19 %T=70
+
delG=-16.2 d=22.84 %T=70
  
 
delG reverse=-18.9 d=33.03 %T=80
 
delG reverse=-18.9 d=33.03 %T=80
Line 139: Line 139:
 
*Terminator 9:
 
*Terminator 9:
  
delG=-16.2 d=10.46 %T=40
+
delG=-16.2 d=11.56 %T=40
  
 
delG reverse=-18.9 d=22.31 %T=75
 
delG reverse=-18.9 d=22.31 %T=75
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*Terminator 10:
 
*Terminator 10:
  
delG=-16.2 d=-1.45 %T<10
+
delG=-16.2 d=-0.72 %T<10
  
 
delG reverse=-18.9 d=10.40 %T=40
 
delG reverse=-18.9 d=10.40 %T=40

Revision as of 13:25, 31 August 2006

The goal is to create a series of transcriptional terminators with varying efficiencies. The majority of transcriptional terminators have a G+C rich stem of 7(+/-1)bp and a loop of 4(+/-1) nucleodtides followed by a poly(U) tail. Two common loops are UUCG and GAAA, both of which are known to increase RNA hairpin stability. The sequence GCGGG(G) is a common sequence found on the 3' arm of the stem. [1]

Effects of stem loop sequence on terminator efficiency

Bulges and mismatches in the stem, as well low G+C content of the stem will lower TE more than reducing the length of or elimination of the poly(U) tail [2]. The sequences downstream of the poly(U) tail and between the stop codon and the start of the stem loop structure also affect the TE of a terminator, particularly T7Te or T3Te.

  • T7Te

Several sources [3] [Chamberlin 79] measured the termination efficiency(TE) of T7Te at around 90%. However, efficiency for the biobricks part BBa_B0012 [1], also T7Te, is around 30%. T7Te has a very short poly(U) tail and requires the further downstream sequence for efficiecent termination [3], and this further downstream sequence is lacking in BBa_B0012. If the sequence for BBa_B0012 is lengthened to include this downstream segment, then the TE of part should be improved.

Predicting terminator efficiency

It may be possible to predict terminator efficiency using methods from d'Aubenton, in particular, the score d assigned to a possible terminator sequence

d = nt*18.16+Y*96.59-116.87

where nt measures the statistical distribution of the T residues in the non transcribed DNA strand and Y is the free energy per nucleodtide of the stem loop structure.

The score d will give a rough estimate of how efficient a terminator is.

d<0: TE<20%

0<d<30: 20%<TE<70%

d>30: TE>70%

Ideal terminator

  • has 6 base stem with 3' sequence of GCGGGG
  • 4 base loop, either UUCG or GAAA
  • tail containing >8 uridines
  • for a biobrick part, flanking regions will be biobrick site

Designed terminators

The score d is calculated as mentioned above. The energy of hairpin formation, delG, is caluclated using UNAFold.

These terminators are designed to be bidirectional. delG reverse is the energy of hairpin formation on the opposite strand.

  • Terminator 1:

delG=-12.6 d=62.33 %T>90

delG reverse=-10.2 d=53.09 %T>90

stem loop: CCCCGCTTCGGCGGGG

primer 1: GTTTCTTCGAATTCGCGGCCGCTTCTAGAGAAAAAAAAACCCCGCTTCGGC

primer 2: GTTTCTTCCTGCAGCGGCCGCTACTAGTAAAAAAAAACCCCGCCGAAGC


  • Terminator 2:

delG=-12.6 d=38.25 %T>90

delG reverse=-10.2 d=23.02 %T=75

stem loop: CCCCGCTTCGGCGGGG

primer 1: GTTTCTTCGAATTCGCGGCCGCTTCTAGAGCGCAAAAAACCCCGCTTCGGC

primer 2: GTTTCTTCCTGCAGCGGCCGCTACTAGTAGCGAAAAAACCCCGCCGAAGC


  • Terminator 3:

delG=-12.6 d=27.78 %T=80

delG reverse=-10.2 d=11.64 %T=40

stem loop: CCCCGCTTCGGCGGGG

primer 1: GTTTCTTCGAATTCGCGGCCGCTTCTAGAGCGCCAAAAACCCCGCTTCGGC

primer 2: GTTTCTTCCTGCAGCGGCCGCTACTAGTAGCGGAAAAACCCCGCCGAAGC


  • Terminator 4:

delG=-12.6 d=16.05 %T=55

delG reverse=-10.2 d=0.91 %T=<20

stem loop: CCCCGCTTCGGCGGGG

primer 1: GTTTCTTCGAATTCGCGGCCGCTTCTAGAGGCCGAAAACCCCGCTTCGGC

primer 2: GTTTCTTCCTGCAGCGGCCGCTACTAGTACGGCAAAACCCCGCCGAAGC


  • Terminator 5:

delG=-12.6 d=4.22 %T=25

delG reverse=-10.2 d=-11 %T<10

stem loop: CCCCGCTTCGGCGGGG

primer 1: GTTTCTTCGAATTCGCGGCCGCTTCTAGAGCGCCGCAAACCCCGCTTCGGC

primer 2: GTTTCTTCCTGCAGCGGCCGCTACTAGTAGCGGCGAAACCCCGCCGAAGC


  • Terminator 6:

delG=-16.2 d=57.39 %T>90

delG reverse=-18.9 d=66.22 %T>90

stem loop: CCCCGCCCCUGACAGGGCGGGG

primer 1: GTTTCTTCGAATTCGCGGCCGCTTCTAGAGAAAAAAAAACCCCGCCCCTGACAGG

primer 2: GTTTCTTCCTGCAGCGGCCGCTACTAGTAAAAAAAAACCCCGCCCTGTCAGGG


  • Terminator 7:

delG=-16.2 d=33.32 %T=80

delG reverse=-18.9 d=42.69 %T>90

stem loop: CCCCGCCCCUGACAGGGCGGGG

primer 1: GTTTCTTCGAATTCGCGGCCGCTTCTAGAGCGCAAAAAACCCCGCCCCTGACAGG

primer 2: GTTTCTTCCTGCAGCGGCCGCTACTAGTAGCGAAAAAACCCCGCCCTGTCAGGG


  • Terminator 8:

delG=-16.2 d=22.84 %T=70

delG reverse=-18.9 d=33.03 %T=80

stem loop: CCCCGCCCCUGACAGGGCGGGG

primer 1: GTTTCTTCGAATTCGCGGCCGCTTCTAGAGCGCCAAAAACCCCGCCCCTGACAGG

primer 2: GTTTCTTCCTGCAGCGGCCGCTACTAGTAGCGGAAAAACCCCGCCCTGTCAGGG


  • Terminator 9:

delG=-16.2 d=11.56 %T=40

delG reverse=-18.9 d=22.31 %T=75

stem loop: CCCCGCCCCUGACAGGGCGGGG

primer 1: GTTTCTTCGAATTCGCGGCCGCTTCTAGAGCGCCGAAAACCCCGCCCCTGACAGG

primer 2: GTTTCTTCCTGCAGCGGCCGCTACTAGTAGCGGCAAAACCCCGCCCTGTCAGGG


  • Terminator 10:

delG=-16.2 d=-0.72 %T<10

delG reverse=-18.9 d=10.40 %T=40

stem loop: CCCCGCCCCUGACAGGGCGGGG

primer 1: GTTTCTTCGAATTCGCGGCCGCTTCTAGAGCGCCGCAAACCCCGCCCCTGACAGG

primer 2: GTTTCTTCCTGCAGCGGCCGCTACTAGTAGCGGCGAAACCCCGCCCTGTCAGGG


  • Terminator 11: this is not supposed to work. if it does, then something is wrong

delG=-3.3 d=-52.65 %T=0

delG reverse=-0.5 d=-69.56 %T=0

stem loop: TTTTATGAAAATAAAA

primer 1: GTTTCTTCGAATTCGCGGCCGCTTCTAGAGCGCCGCAAATTTTATGAAAAT

primer 2: GTTTCTTCCTGCAGCGGCCGCTACTAGTAGCGGCGAAATTTTATTTTCAT

References

  1. d'Aubenton Carafa Y, Brody E, and Thermes C. Prediction of rho-independent Escherichia coli transcription terminators. A statistical analysis of their RNA stem-loop structures. J Mol Biol. 1990 Dec 20;216(4):835-58. PubMed ID:1702475 | HubMed [Aubenton90]
  2. Abe H and Aiba H. Differential contributions of two elements of rho-independent terminator to transcription termination and mRNA stabilization. Biochimie. 1996;78(11-12):1035-42. PubMed ID:9150882 | HubMed [Abe96]
  3. Reynolds R and Chamberlin MJ. Parameters affecting transcription termination by Escherichia coli RNA. II. Construction and analysis of hybrid terminators. J Mol Biol. 1992 Mar 5;224(1):53-63. PubMed ID:1372366 | HubMed [Reynolds92II]
  4. Brendel V, Hamm GH, and Trifonov EN. Terminators of transcription with RNA polymerase from Escherichia coli: what they look like and how to find them. J Biomol Struct Dyn. 1986 Feb;3(4):705-23. DOI:10.1080/07391102.1986.10508457 | PubMed ID:3078109 | HubMed [Bredel86]
  5. Cheng SW, Lynch EC, Leason KR, Court DL, Shapiro BA, and Friedman DI. Functional importance of sequence in the stem-loop of a transcription terminator. Science. 1991 Nov 22;254(5035):1205-7. PubMed ID:1835546 | HubMed [Cheng91]
  6. Christie GE, Farnham PJ, and Platt T. Synthetic sites for transcription termination and a functional comparison with tryptophan operon termination sites in vitro. Proc Natl Acad Sci U S A. 1981 Jul;78(7):4180-4. PubMed ID:7027254 | HubMed [Christie81]
  7. Ermolaeva MD, Khalak HG, White O, Smith HO, and Salzberg SL. Prediction of transcription terminators in bacterial genomes. J Mol Biol. 2000 Aug 4;301(1):27-33. DOI:10.1006/jmbi.2000.3836 | PubMed ID:10926490 | HubMed [Ermolaeva00]
  8. Lesnik EA, Sampath R, Levene HB, Henderson TJ, McNeil JA, and Ecker DJ. Prediction of rho-independent transcriptional terminators in Escherichia coli. Nucleic Acids Res. 2001 Sep 1;29(17):3583-94. PubMed ID:11522828 | HubMed [Lesnik01]
  9. Lynn SP, Kasper LM, and Gardner JF. Contributions of RNA secondary structure and length of the thymidine tract to transcription termination at the thr operon attenuator. J Biol Chem. 1988 Jan 5;263(1):472-9. PubMed ID:2961747 | HubMed [Lynn88]
  10. Petrillo M, Silvestro G, Di Nocera PP, Boccia A, and Paolella G. Stem-loop structures in prokaryotic genomes. BMC Genomics. 2006 Jul 4;7:170. DOI:10.1186/1471-2164-7-170 | PubMed ID:16820051 | HubMed [Petrillo06]
  11. Reynolds R, Bermúdez-Cruz RM, and Chamberlin MJ. Parameters affecting transcription termination by Escherichia coli RNA polymerase. I. Analysis of 13 rho-independent terminators. J Mol Biol. 1992 Mar 5;224(1):31-51. PubMed ID:1372365 | HubMed [Reynolds92I]
  12. Unniraman S, Prakash R, and Nagaraja V. Conserved economics of transcription termination in eubacteria. Nucleic Acids Res. 2002 Feb 1;30(3):675-84. PubMed ID:11809879 | HubMed [Unniraman02]
  13. Uptain SM and Chamberlin MJ. Escherichia coli RNA polymerase terminates transcription efficiently at rho-independent terminators on single-stranded DNA templates. Proc Natl Acad Sci U S A. 1997 Dec 9;94(25):13548-53. PubMed ID:9391063 | HubMed [Uptain97]
  14. von Hippel PH and Yager TD. The elongation-termination decision in transcription. Science. 1992 Feb 14;255(5046):809-12. PubMed ID:1536005 | HubMed [VonHippel92]
  15. Wilson KS and von Hippel PH. Stability of Escherichia coli transcription complexes near an intrinsic terminator. J Mol Biol. 1994 Nov 18;244(1):36-51. DOI:10.1006/jmbi.1994.1702 | PubMed ID:7966320 | HubMed [Wilson94]
  16. Wilson KS and von Hippel PH. Transcription termination at intrinsic terminators: the role of the RNA hairpin. Proc Natl Acad Sci U S A. 1995 Sep 12;92(19):8793-7. PubMed ID:7568019 | HubMed [Wilson95]
  17. Yager TD and von Hippel PH. A thermodynamic analysis of RNA transcript elongation and termination in Escherichia coli. Biochemistry. 1991 Jan 29;30(4):1097-118. PubMed ID:1703438 | HubMed [Yager91]
  18. Gusarov I and Nudler E. The mechanism of intrinsic transcription termination. Mol Cell. 1999 Apr;3(4):495-504. PubMed ID:10230402 | HubMed [Gusarov99]
  19. de Hoon MJ, Makita Y, Nakai K, and Miyano S. Prediction of transcriptional terminators in Bacillus subtilis and related species. PLoS Comput Biol. 2005 Aug;1(3):e25. DOI:10.1371/journal.pcbi.0010025 | PubMed ID:16110342 | HubMed [deHoon05]
  20. Pfleger BF, Pitera DJ, Smolke CD, and Keasling JD. Combinatorial engineering of intergenic regions in operons tunes expression of multiple genes. Nat Biotechnol. 2006 Aug;24(8):1027-32. DOI:10.1038/nbt1226 | PubMed ID:16845378 | HubMed [Smolke06]
All Medline abstracts: PubMed | HubMed