Difference between revisions of "Team:TUDelft/Results"

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                 <h1>Controllability</h1>
 
                 <h1>Controllability</h1>
 
                 <h2>Overview</h2>
 
                 <h2>Overview</h2>
                 <p>The behavior of genetic parts and circuits in different bacterial species is unpredictable as it is influenced by host-dependent variations (Liu et al., 2018) . 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 levels of genetic parts. We engineered a unique implementation of the IFFL incoherent feed forward loop  motif to achieve gene expression independent of these variables. Furthermore, the iFFL loop was shown to reduce relative level expression differences between <i>E. coli</i> and <i>P. putida</i>.</p>   
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                 <p>The behavior of genetic parts and circuits in different bacterial species is unpredictable as it is influenced by host-dependent variations (Liu et al., 2018) . 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 levels of genetic parts. We engineered a unique implementation of the IFFL incoherent feed forward loop  motif to achieve gene expression independent of these variables. Furthermore, the IFFL loop was shown to reduce relative level expression differences between <i>E. coli</i> and <i>P. putida</i>.</p>   
  
 
                 <div id="CopyNumber">
 
                 <div id="CopyNumber">
                    <h2>Copy number</h2>
 
                    <p>Copy number of plasmids vary when used in different bacterial hosts and this significantly alters behaviour of parts (Segall-Shapiro et al., 2018). We used a modeling approach to study the behavior of a genetic implementation of an iFFL. Our model shows complete independence to copy number of the steady-state gene expression.</p>
 
  
 
                     <ul class="accordion">
 
                     <ul class="accordion">

Revision as of 15:18, 21 October 2019

Sci-Phi 29

Overview


The aim of this project is to develop Sci-Phi 29: a versatile platform to expand the repertoire of bacterial species currently used in synthetic biology. Sci-Phi 29 enables host independent replication of genetic vectors thanks to the concept of orthogonality and ensures controllable expression of your gene of interest across different bacterial species. To achieve this goal, we investigated the Φ29 replication system (orthogonality module) and engineered an incoherent feed-forward loop (controllability module). (Link both the bold text to the design page).

Parts Construction

Within this project we constructed successfully several parts (Link to all the parts you have), all of which have been confirmed by sequencing. In detail, we generated 20 basic parts that allowed us to then create 16 composite constructs for the orthogonality module, and 30 composite constructs for the controllability module. All these parts have been employed in our assays which included: confirmation in vitro of each single orthogonal constructs as well as the in vitro demonstration of the replication of our linear construct, toxicity assays to ensure tightly controlled expression of the orthogonal system, testing of copy number independency across different species and demonstration of transcriptional variation, modelling of translational variation independence and quantitative analysis on codon harmonization.


Part Characterization

In vitro characterization of the orthogonal replication parts

First, we characterized in vitro the four proteins needed for orthogonal replication, DNAP, TP, p5 and p6. For expressing these constructs we used PUREfrex® (GeneFrontier Corporation, Japan). The PURE (Protein Synthesis Using Recombinant Elements) system contains all the purified components found to be sufficient to sustain the reactions involved in protein synthesis. Specifically, we employed PUREfrex®2.0 for its high protein yield and its prolonged expression lifetime in bulk. After cell-free gene expression of each construct (3 hours, 37C) we verified for the presence of our protein of interest by SDS-PAGEl and/or mass spectrometry. Since the multiple proteins present in the PUREfrex® system for some constructs ( DNAP and TP) it was difficult to properly identify the presence of our expressed protein via SDS-PAGE and mass spectrometry helped us. To perform mass spectrometry analysis, pre-ran PURE system samples were trypsin-digested and analyzed by liquid chromatography-coupled mass spectrometry (LC-MS). All mass spectrometry data were normalized to the presence of EF-TU, an elongation factor that can be found in the same concentration in all PURE system reactions. The mass spectrometer looks for the mass of unique peptide sequences, and their elution time. The optimized parameters and raw data for the mass spectrometry method can be found here and here.

  • DNAP

    The successful expression of DNAP from our construct was confirmed by mass spectrometry as reported by figure . For DNAP the mass spectrometer screened for the following peptide sequences: ENGALGFR and LVEGSPDDYTDIK.

    Figure 1: Identification by mass spectrometry of ENGALGFR peptide (A) and of LVEGSPDDYTDIK peptide (B) in the DNAP expressed sample.
  • TP
    The successful expression of TP from our construct was confirmed by mass spectrometry as reported by figure . For TP the mass spectrometer screened for the following peptide sequences TP: IAEIER, LVDEK, ILSYLEQYR.
    Figure 2: Identification by mass spectrometry of IAEIER peptide (A), of LVDEK peptide (B) and of ILSYLEQYR peptide (C) in the TP expressed sample.
  • p5
    The expression of p5 was successfully identified by an 18% SDS-PAGE gel. From the 10-μL of expression reaction, 8 μL was loaded on the SDS-PAGE while the other 2 μL was analyzed by the mass spectrometer for further confirmation. Click here (link) for the protocols. A SDS-PAGE was carried out for the p5 protein with 3 different promoter strengths (Wild-Type, medium and weak). To have a negative control one expression reaction was run in the absence of DNA. In figure XXX the three samples and the control can be seen on the runned gel. The presence of a band (depicted with a red star) at the expected molecular weight (13,3kDa) confirmed the presence of the expressed p5. In the control line with no gene added, a smear background of GreenLys is visible that is distinct from gene-specific bands. The other upper band l could be due to contamination in the expression reaction as it is also present in the negative control. The correct p5 expression starting from our three DNA constructs was further confirmed by mass spectrometry as reported by figure . For p5 the mass spectrometer screened for the following peptide sequences: IFNAQTGGGQSFK and TVAEAASDLIDLVTR. The difference in height can be attributed to the strength of the promoters, less peptides were measured with decreasing strength.
    Figure 3: Left and middle: Identification by mass spectrometry of FNAQTGGGQSFK peptide (A) and of TVAEAASDLIDLVTR peptide (B) in the p5 expressed sample. Right: SDS-PAGE gels of DSB after cell-free expression. Translation products were analysed by fluorescence imaging of an 18% gel. The bands depicted with an upper red asterisk correspond to the protein of interest with expected molecular weight. In the control line (most right) no specific band can be observed.
  • p6

    As for p5, the expression of p6 was successfully confirmed by an 18% SDS-PAGE gel and mass spectrometry. Click here (link) for the protocols. An SDS-PAGE was carried out for the three p6 encoding construct with the three different promoter strengths (Wild-Type, medium and weak). To have a negative control one expression reaction was run in the absence of DNA. In figure XXX the three samples and the control can be seen on the runned gel. The presence of a band (depicted with a red star) at the expected molecular weight (13kDa) confirmed the presence of the expressed p5. In the control line with no gene added, a smear background of GreenLys is visible that is distinct from gene-specific bands. The other upper band l could be due to contamination in the expression reaction as it is also present in the negative control. The correct p6 expression starting from our three DNA constructs was further confirmed by mass spectrometry as reported by figure. For p6 the mass spectrometer screened for the following peptide sequences GEPVQVVSVEPNTEVYELPVEK and FLEVATVR.The difference in height can be attributed to the strength of the promoters, less peptides were measured with decreasing strength.

    Figure 4: Left and middle: Identification by mass spectrometry of FLEVATVR peptide (A) and of GEPVQVVSVEPNTEVYELPVEK peptide (B) in the p6 expressed sample. Right: Figure ..: SDS-PAGE gels of p6 after cell-free expression. Translation products were analysed by fluorescence imaging of an 18% gel. The bands depicted with an upper red asterisk correspond to the protein of interest with expected molecular weight. In the control line (most right) no specific band can be observed.

Conclusion

We were able to successfully identify DNAP, TP, p5 and P6 after in vitro expression of our construct. The results indicate that our construct are correct and can lead to the expression of the protein of interest. Furthermore, we were able to observe a difference in expression level when using different promoter, for example a lower amount of protein was produced and observed when using the weak promoter.


Orthogonality

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Orthogonal Replication

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Toxicity Assay

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Controllability

Overview

The behavior of genetic parts and circuits in different bacterial species is unpredictable as it is influenced by host-dependent variations (Liu et al., 2018) . 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 levels of genetic parts. We engineered a unique implementation of the IFFL incoherent feed forward loop motif to achieve gene expression independent of these variables. Furthermore, the IFFL loop was shown to reduce relative level expression differences between E. coli and P. putida.

  • Results -- Copy number independence

      The expression levels in a genetic circuit are strongly correlated to the plasmid copy number of the DNA template Segall-Shapiro et al., (2018) The amount of gene plasmid copy number can change when the plasmid is transferred between organisms. Therefore there is a need for expression levels independent of plasmid copy number if the same genetic circuit is used in different organisms. The steady-state solution of our model tells us that when our repressor binding is fully non-cooperative, we have complete independence of plasmid copy number.


      TALE system
      Figure 1: Steady-state GOI production for gene plasmid copy number 1 to 600 (genome integration to high plasmid copy number plasmid).

      The model without assumptions has the same expression level independent of plasmid copy number (figure ). We therefore can transfer our circuit between organisms and expect the expression of the gene of interest to be independent of the changes in plasmid copy number of our orthogonal plasmid.

Portable T7 expression system

To facilitate the development of portable gene expression systems and reduce host dependency we demonstrated the iFFL system was successfully expressed along with the Universal Bacterial Expression Resource (UBER) system (Kushwaha & Salis, 2015).
  • Experimental design

      We cloned our T7 promoter based optimized iFFL and a control into low and medium copy number backbones ( pICH82113 , and pICH82094 respectively) from the MoClo toolkit.



      To reduce dependency on host transcriptional machinery, we co-transformed these constructs with the UBER portable T7 expression system. The UBER system expresses T7 RNAP at a stable level as described on our design page .

      Results

      TALE system
      Figure 1: Fluorescence histogram of cotransformations of obtained by flow cytometry. Black is regular E. coli TOP10 cells, green is cotransformation of our T7 promoter based optimized iFFL , pink is cotransformation of an iFFL without repression.

      Figure 1 shows the fluorescence hisogram obtained by flow cytometry. Clearly a shift in fluorescence is observed when our plasmid is cotransformed with the UBER plasmids.

Conclusion

Our unique iFFL genetic circuits are compatible with the portable T7 expression system.

Transcriptional variation

Behavior of promoters (transcriptional rates) significantly changes across different bacterial hosts (Yang S et al., 2017) . Hence, promoters either need to be re-characterized for each bacterial hosts or promoters specific to the host need to be identified. Using iFFL, we demonstrated gene expression independent of transcriptional rates when the transcription rate of both genes (TALE and GOI) maintain the same ratio, as predicted by modeling .

  • Results -- Independence to promoter strengths

      To validate our model prediction, we designed T7 promoters based iFFL systems with varying promoter strengths. We compared our wild-type T7 promoter based iFFL system (figure 1) to a iFFL system based on a T7 promoter variant with 50% strength compared to the wild-type (figure 2) (Ryo Komura et al., 2018) (medium T7 based iFFL system). As a control we express GFP without any TALE (figure 3).

      TALE system
      Figure 1: T7 based iFFL. Both genes are controlled by a T7 promoter.

      TALE system
      Figure 2: Medium T7 based iFFL. Both genes are controlled by a medium strength version of a T7 promoter.

      TALE system
      Figure 3: Negative control, T7 promoter controlling GFP.


      The output GFP fluorescence was measured using flow cytometry during logarithmic growth phase after induction with 1mM IPTG. As a reference for background fluorescence we use E. coli BL21DE(3) cells without any plasmid. The most dense region (determined by eye) in the scatter plot (forward and side-scatter) is selected for gating in order to only compare cells of similar morphology. Furthermore, the fluorescence histogram is gated to discern between cells that are "off" or "on" (expressing GFP or not), by gating the E. coli BL21DE(3) cells without any plasmid.


      The median of the background is subtracted from the median of the samples and the resulting values are plotted (figure 4).

      Results

      TALE system

      Figure 4: Steady-state GFP fluorescence measurement of promoter variation using flow cytometry. The graph depicts T7 and medium T7 iFFL systems, expected to give the same fluorescence according to the model. As a control, GFP under control of an unrepressed T7 promoter was used.

      In figure 4, similar GFP fluorescence can be observed for the iFFL systems while the unrepressed control system shows high fluorescence. This suggests successful insulation of gene expression from change in promoter strengths.

  • Results -- Independence to IPTG concentration

      Aside from testing gene expression independent of transcriptional variation by using promoters of different strengths, the effect of different concentrations of IPTG on the iFFL loop was tested. Change in IPTG concentrations, changes in-vivo concentrations of T7 RNAP and this contributes to variations in transcriptional rates. In unrepressed systems, the expression of the GOI is a function of IPTG concentrations. However, in iFFL systems, since the transcriptional rates of TALE and GFP are under control of T7 promoters, similar GOI expression is expected (figure 1). As a control we expressed GFP under the control of T7sp1 promoter was used (figure 2). TALE system

      Figure 1: Optimized T7 based iFFL. TALE is under cotntrol of weak T7 promtoer. GFP is controlled by a T7 promoter.

      TALE system
      Figure 2: Negative control, T7 promoter controlling GFP.

      The output GFP fluorescence was measured using flow cytometry during logarithmic growth phase after induction with 1mM IPTG. As a reference for background fluorescence we use E. coli BL21DE(3) cells without any plasmid. The most dense region (determined by eye) in the scatter plot (forward and side-scatter) is selected for gating in order to only compare cells of similar morphology. Furthermore, the fluorescence histogram is gated to discern between cells that are "off" or "on" (expressing GFP or not), by gating the E. coli BL21DE(3) cells without any plasmid.


      The median of the background is subtracted from the samples and are compared.

      Results

      Figure 3 the GFP fluorescence of the unrepressed control changes with changing concentrations of IPTG while the iFFL system shows the same GFP expression across different IPTG concentrations. Thus, the iFFL system has been shown to insulate gene expression against changes in transcription rates (achieved by varying IPTG concentrations). .

      TALE system
      Figure 3: Steady-state GFP fluorescence measurement of IPTG titration using FACS. The graph depicts a T7 iFFL system induced using different levels of IPTG, which according to the model should give the same result. As a control GFP under control of an unrepressed T7 promoter was used.

  • Results -- Tunability

      The predictions made by modeling not only tell us that we can maintain the same level of gene expression but also that we can easily tune the expression levels by changing one of the promoters. By changing one of the promoters to another variant of T7 we can expect a different level of expression, while at the same time expect it to behave similarly when transferred between organisms. Through the use of T7 variants we could achieve wide ranges of expression levels, which can be used to establish complex genetic circuits, while also expecting it to work similarly in different biological contexts.

      We tested the prediction by changing the promoter controlling the TALE protein to a variant of T7 which has been shown to be about 10% in strength compared to the wild-type (Ryo Komura et al., 2018). According to the model the expression should increase.

      We measure GFP fluorescence using flow cytometry. As a reference for background fluorescence we use E. coli BL21DE(3) cells without any plasmid. The most dense region (determined by eye) in the scatter plot (forward and side-scatter) is selected for gating in order to only compare cells of similar morphology. Furthermore, the fluorescence histogram is gated to discern between cells that are "off" or "on" (expressing GFP or not), by gating the E. coli BL21DE(3) cells without any plasmid.


      The median of the background is subtracted from the samples and are compared.

      Results

      Figure 1 suggests there is a higher fluorescence when a lower T7 promoter version is used to express the TALE protein in comparison to our systems with the same ratio in promoter strengths for both genes.

      TALE system
      Figure 1: Steady-state GFP fluorescence measurement of E. coli BL21DE(3) cells expressing our iFFL systems. The graph depicts a different T7 iFFL systems, one with both promoters T7, one with both medium strength and one where the promoter controlling of the TALE is weak. As a control GFP under control of an unrepressed T7 promoter was used.

Conclusion

Results above indicate successful implementation of the iFFL system to insulate from transcriptional variations. Transcriptional variations were achieved by using T7 promoters of different strengths and by induction at different IPTG concentrations. Furthermore, we demonstrated the tunability of the iFFL system to achieve different levels of gene expression. As predicted by our model, we achieved gene expression independent of changes in transcriptional rates by maintaining constant ratios of transcriptional rates of TALE and GFP genes.

Translational variation

In order to see the effect of translational variation on the expression levels of the gene of interest (GOI) we modeled our system for a range of translational rates for both genes (TALE and GOI).
  • Results

      As can be seen in figure … the steady-state expression levels of GFP remain the same when the translation rates are kept constant.

Conclusion

According to our model solution we can maintain the same level of GOI expression when both translation rates remain constant. We therefore designed our system to contain the same RBS in front of both TALE and the GOI.

Expression across different organisms

To achieve similar gene expression across different organisms the iFFL system needs to be robust to changes in copy number, transcriptional and translational rates. We experimentally demonstrated gene expression independent of transcriptional variations and through modelling showed adaptation variations in copy number and translational variation of our iFFL system. Through the implementation of the iFFL loop using engineered broad host range promoters, we successfully demonstrated similar GFP expression across E. coli and P. putida. Thereby demonstrating gene expression insulated from variations associated to microbial hosts.

  • Results -- Expression across organisms

      Broad host range promoter (PBHR) was designed by combining the conserved -10 and -35 regions from E.coli and B.subtilis (Yang S et al., 2018) and the promoter was engineered to contain a binding site for TALE repressor (PBHRsp1). 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 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 positive (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. In order to compare the GFP expression levels between each organism, the background fluorescence for each organism was subtracted by its respective blank .

      Results

      Figure 1 clearly shows higher fluorescence when a lower T7 promoter version is used to express the TALE protein in comparison to our systems with the same ratio in promoter strengths for both genes.

      TALE system
      Figure 1: : Steady-state GOI production while translation rates of both TALE and GOI are changed. The lines indicate the constant rate of the translation rates.

      In figure 1, the median fluorescence of the gated populations is plotted. 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 P.putida. 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).

Conclusion

The implementation of the iFFL significantly decreased the differences in expression levels between organisms. Our system sets the basis for controllability across organisms.

Cross species codon harmonization


When heterologous proteins were expressed in new bacterial host cells, altered protein expression levels were observed due to the variance in codon usage between the original organism and the new host cell (Angov et al, 2008). To increase the expression level of the heterologous protein in the host cell, new codon optimization tools are developed. The current limitation of codon adaptation tools is that the adaptation of the DNA coding sequence can be performed for one single organism at the time. Therefore we created the first cross-species codon harmonization tool. The tool provides the user with a single DNA coding sequence that will yield the same protein expression level in different bacterial host cells. We demonstrated functional protein expression using our own harmonized coding sequence for E. coli , B. Subtilus, and V. Natrigen.

  • Results -- functional protein production
    • To validate whether the cross-species codon harmonization results in a functional protein, we designed a cross-species codon harmonized GFP coding sequence. The sequence was harmonized using E. coli BL21(DE3) as reference organism, and V. natriegens NBRC 15636 = ATCC 14048 = DSM 759) and B. Subtilis subsp. subtilis str. 16
      The harmonized GFP was constructed through MoClo assembling with the WT t7 promoter , universal RBS, universal RBS harmonized GFP, harmonized GFP and WT terminator The assembled plasmid is transformed into E. coli BL21(DE3).
      We measure the GFP fluorescence using the Gel doc. As reference for background fluorescence we use untransformed E. coli BL21(DE3) pLysS). As reference for fluorescence we use E. coli BL21(DE3) pLysS with BBa_K2918030 plasmid.

      Furthermore, to validate the harmonized GFP even more, a flow cytometer experiment was performed putting the harmonized GFP under two different promoter strength. The two promoter strength of the med T7sp1 promoter. and T7sp1 promoter were cloned in the same backbone ( pICH47761) and were paired with the same RBS (universal RBS). The fluorescence is measured with fluorescence readout from harmonized GFP by flow cytometry and E.coli BL21 DE(3) cells were used as blank. Click here for the protocol. FCSalyzer v.0.9.18-alpha was used to analyze data from the flow cytometry experiment.

      Results

      Both the positive control and the harmonized GFP showed some level of fluorescence expression. The harmonized GFP showed fluorescing cells but the positive control was almost not visual. For better validation a flow cytometer measurement was performed.

      GFP Harmonized
      Figure ...: qualitative data of a fluorescence measurement of pelleted cells in eppendorf tubes after IPTG induction. From left to right E. coli BL21(DE3) pLysS with no plasmid (negative control), E. coli BL21(DE3) pLysS with JuniperGFP (positive control), and E. coli BL21(DE3) pLysS with harmonized GFP. A) The fluorescing image was taken using the gel doc. As seen the cell pellets are all fluorescing. B) After removing the autofluorescence by subtracting the negative control from the image, the green fluorescence cells has been visualized . The still fluorescing cell pellets are marked with a green circle. C) A 3D plot of the fluorescing cells. The height of the graph corresponds with the intensity of the measured GFP.


      The raw data of the cytoflow meter is shown in figure…. The curves represent fluorescence values of E.coli BL21 DE (3) cells (black), clones with GFP expressed from T7sp1 (red) and clones with GFP expressed from T7sp1 (blue). cytoflowharmonizedGFP
      Figure ...: Raw fluorescence data. The curves represent fluorscenece values of E.coli BL21 DE (3) cells (black), clones with GFP expressed from T7sp1 (red) and clones with GFP expressed from T7sp1 (blue).

Conclusion

The fluorescence measurement using the gel doc did not show a clear separation between the positive and negative control. the result was insufficient to see whether the harmonized GFP sequence resulted into functional protein production. .

The cytoflow meter did show a better qualitative data. The clear shift between the implicates active GFP protein production. So the harmonized GFP coding sequence encodes for functional GFP proteins.


Future Plan

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References