Difference between revisions of "Part:BBa K2918050"

(References)
(References)
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Lou, C., Stanton, B., Chen, Y.-J., Munsky, B., & Voigt, C. A. (2012). Ribozyme-based insulator parts buffer synthetic circuits from genetic context. <i>Nature Biotechnology</i>, 30(11), 1137–1142.</a>
 
Lou, C., Stanton, B., Chen, Y.-J., Munsky, B., & Voigt, C. A. (2012). Ribozyme-based insulator parts buffer synthetic circuits from genetic context. <i>Nature Biotechnology</i>, 30(11), 1137–1142.</a>
 
</li>
 
</li>
<li> <a href="https://www.ncbi.nlm.nih.gov/pubmed/27665861"> Adams, B. (2016). The Next Generation of Synthetic Biology Chassis: Moving Synthetic Biology from the Laboratory to the Field. ACS Synthetic Biology, 5(12), 1328-1330.</a></li>
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<li> <a id="Adams2016" href="https://www.ncbi.nlm.nih.gov/pubmed/27665861"> Adams, B. (2016). The Next Generation of Synthetic Biology Chassis: Moving Synthetic Biology from the Laboratory to the Field. ACS Synthetic Biology, 5(12), 1328-1330.</a></li>
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<li><a id="Gelder2007"  href="https://www.ncbi.nlm.nih.gov/pubmed/17259616">  De Gelder, L., Ponciano, J., Joyce, P., & Top, E. (2007, 2). Stability of a promiscuous plasmid in different hosts: No guarantee for a long-term relationship. Microbiology, 153(2), 452-463. </a></li>
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<li> <a id="Meysman2014" href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0088717"> Meysman, P., Collado-Vides, J., Morett, E., Viola, R., Engelen, K., & Laukens, K. (2014, 2 7). Structural properties of prokaryotic promoter regions correlate with functional features. PLoS ONE, 9(2). </a></li>
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            <li> <a id="Omotajo2015" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4535381/"> Omotajo, D., Tate, T., Cho, H., & Choudhary, M. (2015, 8 14). Distribution and diversity of ribosome binding sites in prokaryotic genomes. BMC Genomics, 16(1). </a></li>
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  <li> <a id= "Sharp2005" href="https://www.ncbi.nlm.nih.gov/pubmed/15728743"> Sharp, P., Bailes, E., Grocock, R., Peden, J., & Sockett, R. (2005). Variation in the strength of selected codon usage bias among bacteria. Nucleic Acids Research, 33(4), 1141-1153. </a></li>
 
</ul>
 
</ul>
<li><a href="https://www.ncbi.nlm.nih.gov/pubmed/17259616">  De Gelder, L., Ponciano, J., Joyce, P., & Top, E. (2007, 2). Stability of a promiscuous plasmid in different hosts: No guarantee for a long-term relationship. Microbiology, 153(2), 452-463. </a></li>
 
<li> <a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0088717"> Meysman, P., Collado-Vides, J., Morett, E., Viola, R., Engelen, K., & Laukens, K. (2014, 2 7). Structural properties of prokaryotic promoter regions correlate with functional features. PLoS ONE, 9(2). </a></li>
 
            <li> <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4535381/"> Omotajo, D., Tate, T., Cho, H., & Choudhary, M. (2015, 8 14). Distribution and diversity of ribosome binding sites in prokaryotic genomes. BMC Genomics, 16(1). </a></li>
 
  <li> <a href="https://www.ncbi.nlm.nih.gov/pubmed/15728743"> Sharp, P., Bailes, E., Grocock, R., Peden, J., & Sockett, R. (2005). Variation in the strength of selected codon usage bias among bacteria. Nucleic Acids Research, 33(4), 1141-1153. </a></li>
 
 
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Revision as of 19:17, 21 October 2019

Cross-species based iFFL

Genetic implementation of an incoherent feed forward loop (iFFL) in which a stabilized broad host range (PBHR) promoter is controlling GFP expression.

Sequence and Features


Assembly Compatibility:
  • 10
    INCOMPATIBLE WITH RFC[10]
    Illegal PstI site found at 283
    Illegal PstI site found at 2538
  • 12
    INCOMPATIBLE WITH RFC[12]
    Illegal PstI site found at 283
    Illegal PstI site found at 2538
  • 21
    INCOMPATIBLE WITH RFC[21]
    Illegal XhoI site found at 250
    Illegal XhoI site found at 3383
  • 23
    INCOMPATIBLE WITH RFC[23]
    Illegal PstI site found at 283
    Illegal PstI site found at 2538
  • 25
    INCOMPATIBLE WITH RFC[25]
    Illegal PstI site found at 283
    Illegal PstI site found at 2538
    Illegal AgeI site found at 1277
  • 1000
    COMPATIBLE WITH RFC[1000]

The two transcriptional units in this composite part are oriented outwards.

Usage and Biology

A incoherent feed-forward loop (iFFL) is a unique control systems motif where the output signal is robust to changes in the input signal. This is achieved by the introduction of a repressor.

  • Figure 1: Overview of incoherent feed-forward loop

iFFL can be applied to genetic circuits to achieve expression independent from copy number, transcriptional and translational rates. To implement the iFFL in a genetic circuit, TALE proteins can be used. These proteins consist of repeats where 12th and 13th amino acids can vary, these are called the repeat variable diresidue (RVD). RVDs have been shown to bind to DNA in a simple one-to-one binding code (Doyle, Stoddard et al., 2013). The direct correspondence between amino acids allows scientists to engineer these repeat regions to target any sequence they want. In our system, we used the TALE protein as a repressor by engineering promoters to contain the binding site of this specific TALE protein (0.1 T7sp1 promoter, 0.5 T7sp1 promoter and PBHRsp1 promoter).
In our genetic circuit, a unrepressed promoter controls the expression of TALE protein while the promoters with the TALE binding sites drive expression of GFP.

  • Figure 2: Overview of how TALE protein represses GFP

When transcriptional units are placed in series, due to low effieciency of terminators, leaky expression of the gene in the neighbouring transcriptonal unit can occur. This significantly influences the behavior of the iFFL genetic circuit (Segall-Shapiro et al., 2018). Hence, the transcriptional units in the circuit are oriented outward to achieve insulation from influence of the neighboring transcriptional unit.

An interesting application of the iFFL is to achieve controllable gene expression across different bacterial species. Gene expression in different bacterial contexts is influenced by changes in copy number, transcriptional and translational rates. iFFL based on broad host range promoters (PBHR promoter and PBHRsp1 promoter) has been demonstrated below to achieve controllable expression between E. coli and P. putida .

Strain Construction

The construct was assembled by golden gate assembly based modular cloning system. First, the individual transcriptional units were cloned into level 1 destination vectors pICH47761 and pICH47822 by BpiI based golden gate assembly. The multi-transcriptional unit construct was assembled by a BsaI based golden gate. The assembly was a one-pot restriction-ligation reaction where the individual level 1 constructs were added along with the destination vector pICH48055. The correct clone was distinguished by blue-white screening and the construct was confirmed by sequencing. The cloning protocol can be found in the MoClo section below.

Modular Cloning

Modular Cloning (MoClo) is a system which allows for efficient one pot assembly of multiple DNA fragments. The MoClo system consists of Type IIS restriction enzymes that cleave DNA 4 to 8 base pairs away from the recognition sites. Cleavage outside of the recognition site allows for customization of the overhangs generated. The MoClo system is hierarchical. First, basic parts (promoters, UTRs, CDS and terminators) are assembled in level 0 plasmids in the kit. In a single reaction, the individual parts can be assembled into vectors containing transcriptional units (level 1). Furthermore, MoClo allows for directional assembly of multiple transcriptional units. Successful assembly of constructs using MoClo can be confirmed by visual readouts (blue/white or red/white screening). For the protocol, you can find it here.


Note: The basic parts sequences of the Sci-Phi 29 collection in the registry contain only the part sequence and therefore contain no overhangs or restriction sites. For synthesizing MoClo compatible parts, refer to table 2. The complete sequence of our parts including backbone can be found here.


Table 1: Overview of different level in MoClo

Level Basic/Composite Type Enzyme
Level 0 Basic Promoters, 5’ UTR, CDS and terminators BpiI
Level 1 Composite Transcriptional units BsaI
Level 2/M/P Composite Multiple transcriptional units BpiI

For synthesizing basic parts, the part of interest should be flanked by a BpiI site and its specific type overhang. These parts can then be cloned into the respective level 0 MoClo parts. For level 1, where individual transcriptional units are cloned, the overhangs come from the backbone you choose. The restriction sites for level 1 are BsaI. However, any type IIS restriction enzyme could be used.


Table 2: Type specific overhangs and backbones for MoClo. Green indicates the restriction enzyme recognition site. Blue indicates the specific overhangs for the basic parts

Basic Part Sequence 5' End Sequence 3' End Level 0 backbone
Promoter NNNN GAAGAC NN GGAG TACT NN GTCTTC NNNN pICH41233
5’ UTR NNNN GAAGAC NN TACT AATG NN GTCTTC NNNN pICH41246
CDS NNNN GAAGAC NN AATG GCTT NN GTCTTC NNNN pICH41308
Terminator NNNN GAAGAC NN GCTT CGCT NN GTCTTC NNNN pICH41276

Characterization

The aim of our project is to achieve stable expression across species. When transferring a genetic circuit between organisms, interspecies variations (Adams, 2016), such as copy number of plasmids (De Gelder, Ponciano, Joyce, & Top, 2007), transcription rates of promoters (Meysman, et al., 2014), translation initiation rates of ribosome binding sites (RBS) (Omotajo, Tate, Cho, & Choudhary, 2015) and the codon usage of coding sequences (Sharp, Bailes, Grocock, Peden, & Sockett, 2005) influence the expression of genetic parts and makes the behavior unpredictable.

We first characterized the functioning of this system through modeling to understand how our system would function when plasmids copy number, transcriptional and translational rates change the expression of a gene of interest. According to our modeling this system always yields the same gene of interest (GOI) expression levels when the copy number of the plasmid changes, and when the transcriptional and translational rates of both genes (TALE and GOI) are changed in the same ratio. When transferring a genetic circuit between organisms all of these variables change. In order to demonstrate this system's ability to have stable expression across species, we cloned this BioBrick into E. coli and P. putida.


Using the PBHR and PBHRsp1, we constructed an iFFL genetic circuit driving GFP expression. The circuit was transformed in E. coli and P. putida and, output fluorescence was measured by flow cytometry during the logarithmic growth phase. To correct for background fluorescence, E. coli and P. putida without plasmids were used as blanks. GFP under the control of PBHRsp1 was used as a negative (unrepressed) control. As the cell morphologies of E. coli and P. putida are different they cannot be compared directly, gating was based on the most dense regions in the scatter plot for each organism (figures 5 and 7). In order to compare the GFP expression levels between each organism, the background fluorescence for each organism was subtracted by its respective blank (figures 4 and 6) .

The protocol for preparation of samples for the flow cytometry assay is as follows:

  1. Samples were grown overnight
  2. Overnight cultures were diluted to OD = 0.01 into 1 mL, and grow for 2 hours on 30 degrees 250 rpm shaking in 2 mL Eppendorf tubes.
  3. Overnight cultures were diluted 1:100 into 5 mL, and grow for 4 hours on 30 degrees 250 rpm shaking in 50 mL falcon tubes.

In figure 3, the median fluorescence of the gated populations is plotted. A significantly large difference in expression levels is observed between the unrepressed controls and the broad host range promoter based iFFL systems in E. coli and </i>P. putida</i>. However, similar levels of expression were observed from iFFL systems in E. coli and P. putida. The difference in expression levels between the unrepressed circuit is significantly higher than the difference in expression levels between the iFFL system (578530 and 2351.2 respectively).

  • Figure 3: Median fluorescence values of gated populations with respective blanks substracted.

Conclusion

Although many variables play a role in the level of gene expression, we managed to reduce the difference in expression levels by 2 orders of magnitude through the implementation of this iFFL. We therefore set the basis for transferring genetic circuits across bacterial species.

Raw data

Our flow cytometry raw data can be found below. Figures 5 and 7 were used for gating on size and complexity. FIgures 4 and 6 were used to determine between cells that were on and off.

  • Figure 4: Fluorescence histogram of P. putida obtained by flow cytometry. Black is P. putida without plasmid, blue is stabilized system and red is negative control
  • Figure 5: Scatter plot of P. putida with region selected for gating.
  • Figure 6:Fluorescence histogram of E. coli obtained by flow cytometry. Black is E. coli without plasmid, blue is stabilized system and red is negative control.
  • Figure 7: Scatter plot of E. coli with region selected for gating.

References