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<b>Figure 7. Represser constructs with pSB1C3 backbone; promoter driving GFP constructs with pSB3K3 backbone; in DS941 cells. Cells were grown overnight in 100μM, 30 μM, 10 μM, 3 μM, and 0 μM IPTG, to induce expression of the repressor proteins. Replicates of constructs and controls of three dilutions from one colony, under the same conditions. Mean and standard deviation of replicates were calculated to give value and error bars.<div class="scrollConclusion"></div></p>
 
          
 
          
  

Revision as of 16:25, 16 September 2015

Summary

Aim: To characterise PhlF and SrpR repressors and their respective repressible promoters for submission to the iGEM registry.


Results Overview:
• K1725000 and K1725020 successfully drive expression of GFP in E. coli.
• K1725042 represses K1725001 GFP expression 83-fold.
• K1725083 represses K1725082 GFP expression 33-fold.
• K1725042 and K1725083 are orthongonal.


Basic Parts submitted:
BBa_K1725000 – PhlF repressible promoter
BBa_K1725020 – SrpR repressible promoter
BBa_K1725040phlF encoding PhlF repressor
BBa_K1725060srpR encoding SrpR repressor
BBa_K1725080 – Promoter (lacI regulated, lambda pL hybrid) with extra NheI site

Introduction

Our genetic circuit needed an inverter, as our UVA sensor turns on transcription, but our circuit needed to turn off transcription when UVA was present. There are several repressor protein/repressible promoter pairs in the iGEM registry suitable for with function such as TetR or LacI, however, it was decided to characterise and submit two new repressors to the registry. Stanton et al., (2014) have recently identified sixteen prokaryotic TetR-like repressors by genomic mining and designed synthetic repressible promoters, as shown in Figure 1A. To understand how they were able to design synthetic repressible promoters, it is important to understand how promoters and repressors work.


Transcription is the process where RNA polymerase binds to DNA to make mRNA; a promoter tells RNA polymerase where to bind to the DNA, so a promoter is found upstream of a gene. Promoters have -10 and -35 sites that the sigma transcription facter binding to and attract RNA polymerase, as shown in Figure1B, and transcription starts at +1. If one or both of these sites are bound by another protein, sigma factor cannot recognise the promoter, and transcription does not take place. Transcriptional repressors are proteins that bind to DNA at a specific sequence; this is called the operator sequence. Stanton et al., (2014) overlapped the operator sequence for each repressor over the -10 and/or -35 sites of BBa_J23119, a strong, constitutive Anderson family promoter, meaning when the repressor binds to its operator sequence sigma factor cannot recognise the promoter and transcription cannot start, as shown in Figure 1B. This is how the synthetic repressible promoters work.



Figure 1 Synthetic Repressible Promoter Design. A – Synthetic repressible promoters with PhlF and SrpR operator sequences, with -35 and -10 sites shown relative to BBa_J23119, and operator sequence in red capital letters. BioBricks of these promoters include sequence from 5’ end to 3’ end of operator sequence. Image reproduced from (Stanton et al., 2014) B – sigma factor binding to -35 and -10 sites to attract RNA polymerase; repressor protein binding to operator sequence preventing sigma factor binding. Altered from (Alberts et al, 2008)


For a repressor to be useful in a genetic circuit, is must be specific so as not to interfere with another part of the circuit or have unwanted interactions within the cell. Repressors that do this are called orthogonal. Repressor A binds to promoter A; repressor B binds to promoter B; but repressor A cannot bind to promoter B, and vice versa. The sixteen prokaryotic TetR-like repressors Stanton et al., (2014) identified are orthogonal, as shown in Figure 2. In particular, TetR, PhlF, and SrpR do not show significant repression of the other’s repressible promoters.



Figure 2 Orthogonal Repressors. Most orthogonal starting top left corner, decreasing towards bottom right corner. TetR, SrpR, and PhlF indicated by arrows. Image reproduced from (Stanton et al., 2014)


It was decided to make BioBricks of two of the sixteen repressors and characterise them for the iGEM registry. The first repressor we decided to submit as a BioBrick was the PhlF repressor from Pseudomonas protegens Pf-5. In P. protegens PhlF is involved in regulation of the phlACBD operon which synthesises an antifungal metabolite 2,4-diacetylphloroglucinol (PHL). (Sheehan et al., 2000, Abbas et al., 2002) The second repressor was the SrpR repressor from Pseudomonas putida S12. In P. putida SrpR is involved in regulation of the srpABC operon which is involved in organic solvent tolerance. (Wery et al., 2001, Sun et al., 2011) The aim was to submit and characterise both phlF and srpR and their respective repressible promoters.

Methods

E. coli strains used: TOP10, DH5α, and DS941. Plasmids in Table 1 constructed by BioBrick Standard Assembly, and checked by digest before confirming by sequencing.


Table 1 Composite Parts Assembled. K1725041, K1725061, and R0011.B0032 (for assembly into K1725083) construct synthesised by IDT. K1725062 sequencing showed a deletion in K1725080.


Protocols for CaCl2 competent cells, transformation, miniprep, restriction digest, gel electrophoresis, ethidium bromide staining, Azure A staining, gel extraction, oligo annealing, and ligation available on our Protocols page. Fluorescence measurements taken as documented on our Interlab Study page.

Results

GFP fluorescence of K1725001, K1725002, K1725021, K1725022, K1725082, and E5504 with plasmid backbone pSB3K3 was measured to compare the relative strengths of promoters K1725000 and K1725020 to a promoter already well documented in the registry, R0040. Figure 3 shows the fluorescence scan image and a graph of approximate molecules of GFP per cell. These results indicated that K1725000 is a significantly stronger promoter than R0040 or K1725020. It also further confirms that B0034 is a stronger ribosome binding site that B0032. Due to this, promoters driving expression of GFP with B0034 ribosome binding site were used for characterisation of the repressors.



Figure 3 Characterising Promoters. All constructs with pSB3K3 plasmid backbone, in DH5α cells. Replicates of constructs and controls from three colonies, under the same conditions. Mean and standard deviation of replicates were calculated to give value and error bars.


To test if our repressers were orthogonal, a smaller version of the cross-talk table Stanton et al., (2014) created was emulated, and our expected results are shown in Figure 4. For example, K1725042 is expected to repress GFP expression from K1725001 so these cells should not fluoresce, however, it is not expected to repress GFP expression from K1725021 so these cells should fluoresce green. In order to transform two different plasmids into the same cell, they must have different origins of replication, and different antibiotic resistance so both plasmids could be selected for. It was decided to keep the K1725042, K1725062, and K1725083 with the pSB1C3 backbone with a high copy number origin of replication, and give K1725001, K1725021, and K1725082 the pSB3K3 backbone with a lower copy number.



Figure 4 Expected GFP fluorescence of cells containing plasmids of repressor BioBricks with pSB1C3 backbone, and promoter BioBricks with pSB3K3 backbone. Cells with bold border shown in detail below: K1725042 represses K1725001; K1725042 does not repress K1725021


As shown in Figure 5, K1725083 represses GFP expression from K1725082, but not from K1725001 or K1725021. Similarly, K1725042 represses GFP expression from K1725001, but not from K1725082 or K1725021, as expected. K1725062, however, was not observed repessing either of the three promoter constructs. Sequencing of K1725062 showed a deletion in the promoter, K1725080, suggesting K1725060 was not being expressed. Furthermore, K1725063 (K1725061 driven by promoter K1725000) has been observed to repress expression driven by the K1725020 promoter (more detail on our Bistable Switch page). This supports that K1725062 should be capable of repressing GFP expression from K1725021. Unfortunately, there was not enough time for reconstruction of K1725062 with the correct sequence, and repetition of this experiment.



Figure 5 Characterising Repressors. Represser constructs with pSB1C3 backbone; promoter driving GFP constructs with pSB3K3 backbone; in DS941 cells. DS941 genotype given on our Protocols page. Cells were grown overnight in 100μM IPTG, to induce expression of the repressor proteins. Replicates of constructs and controls of three dilutions from one colony, under the same conditions. Mean and standard deviation of replicates were calculated to give value and error bars.


In addition to showing K1725042 and K1725083 were capable of repressing K1725001 and K1725082, repectively, quantification of how many fold GFP expression was repressed was calculated. Figure 6 shows K1725082 represses K1725083 GFP expresion by 33-fold, whereas K1725042 represses K1725001 GFP expression by 83-fold.



Figure 6 Fold Repression. Repressor protein expression induced with 100μM IPTG. Values and error bars from experiments described above.


To further characterise K1725042 and K1725083, the concentration of IPTG used to induce repressor expression was reduced to investigate the range of regulation of GFP expression. Figure 7 shows that K1725083 has a wider range of regulation, whereas K1725042 shows no significant difference between 100μM and 10μM IPTG.



Figure 7. Represser constructs with pSB1C3 backbone; promoter driving GFP constructs with pSB3K3 backbone; in DS941 cells. Cells were grown overnight in 100μM, 30 μM, 10 μM, 3 μM, and 0 μM IPTG, to induce expression of the repressor proteins. Replicates of constructs and controls of three dilutions from one colony, under the same conditions. Mean and standard deviation of replicates were calculated to give value and error bars.

Conclusion

text

References

Abbas, A., Morrissey, J.P., Marquez, P.C., Sheehan, M.M., Delany, I.R., and O’Gara, F. (2002). Characterization of Interactions between the Transcriptional Repressor PhlF and Its Binding Site at the phlA Promoter in Pseudomonas fluorescens F113. J. Bacteriol. 184, 3008–3016.

Alberts et al (2008). Molecular Biology of the Cell (Garland Science, Taylor and Francis Group). Chapter 7, p337-434

Sheehan, M.M., Delany, I., Fenton, A., Bardin, S., O’Gara, F., and Aarons, S. (2000). Regulation of production of the antifungal metabolite 2,4-diacetylphloroglucinol in Pseudomonas fluorescens F113: genetic analysis of phlF as a transcriptional repressor. Microbiology 146, 537–546.

Stanton, B.C., Nielsen, A.A.K., Tamsir, A., Clancy, K., Peterson, T., and Voigt, C.A. (2014). Genomic mining of prokaryotic repressors for orthogonal logic gates. Nat. Chem. Biol. 10, 99–105.

Sun, X., Zahir, Z., Lynch, K.H., and Dennis, J.J. (2011). An Antirepressor, SrpR, Is Involved in Transcriptional Regulation of the SrpABC Solvent Tolerance Efflux Pump of Pseudomonas putida S12. J. Bacteriol. 193, 2717–2725.

Wery, J., Hidayat, B., Kieboom, J., and Bont, J.A.M. de (2001). An Insertion Sequence Prepares Pseudomonas putida S12 for Severe Solvent Stress. J. Biol. Chem. 276, 5700–5706.

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