iGEM 2023 — Team kuleuven

{% extends "layout.html" %}
{% block title %}Notebooks{% endblock %}
{% block lead %}Get a detailed account of the work done each day for our project.{% endblock %}
{% block page\_content %}

[![](https://static.igem.wiki/teams/4661/wiki/home/droplet-light-blue.svg) Introduction](#introduction)
[![](https://static.igem.wiki/teams/4661/wiki/home/droplet-light-blue.svg) Dry Lab](#drylab)
[![](https://static.igem.wiki/teams/4661/wiki/home/droplet-light-blue.svg) Wet Lab](#wetlab)

## Introduction

---

Good laboratory practice of course involves sufficient training, good preparation, and sufficient knowledge of what you’re doing, but proper notetaking is just as important! Our team realized this from the start and thus was very careful in taking excellent notes, both for dry lab and wet lab. Knowing how exactly we ran a simulation is just as important as being able to find what concentration of a certain reagent we used for example. All of our lab notes can be find in the PDFs below.

## Dry Lab

---

### Enzyme Screening

Below we provide the notebook for the enzyme screening performed as part of our dry lab work (if the PDF doesn't appear below, you can download it [here](https://static.igem.wiki/teams/4661/wiki/notebook/dry-lab-notebook-enzyme-screening.pdf)):

### Genetic Switch

Below we provide the notebook for the enzyme screening performed as part of our dry lab work (if the PDF doesn't appear below, you can download it [here](https://static.igem.wiki/teams/4661/wiki/notebook/dry-lab-notebook-genetic-switch.pdf)):

### Growth Model

Below we provide the notebook for the enzyme screening performed as part of our dry lab work (if the PDF doesn't appear below, you can download it [here](https://static.igem.wiki/teams/4661/wiki/notebook/dry-lab-notebook-growth-model-final.pdf)):

### Hydrophobin Design

Below we provide the notebook for the enzyme screening performed as part of our dry lab work (if the PDF doesn't appear below, you can download it [here](https://static.igem.wiki/teams/4661/wiki/notebook/dry-lab-notebook-hydrophobin-design.pdf)):

## Wet Lab

---

### Pinheiro Lab

Below we provide the notebook for part our wet lab activities conducted at our primary PI Vitor Pinheiro's lab (if the PDF doesn't appear below, you can download it [here](https://static.igem.wiki/teams/4661/wiki/notebook/notebook-pinheiro-lab.pdf)):

### Van Dijck Lab

Below we provide the notebook for part our wet lab activities conducted at our secondary PI Patrick Van Dijck's lab (if the PDF doesn't appear below, you can download it [here](https://static.igem.wiki/teams/4661/wiki/notebook/notebook-van-dijck-lab.pdf)):

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{% extends "layout.html" %}
{% block title %}Engineering Success{% endblock %}
{% block lead %}On this page, you can read how our team implemented iterations of the engineering cycle to complete a successful project.{% endblock %}
{% block page\_content %}

[![Blue droplet](https://static.igem.wiki/teams/4661/wiki/home/droplet-light-blue.svg) Introduction](#introduction)
[![Blue droplet](https://static.igem.wiki/teams/4661/wiki/home/droplet-light-blue.svg) *E. coli*](#ecoli)
[![Blue droplet](https://static.igem.wiki/teams/4661/wiki/home/droplet-light-blue.svg) *S. cerevisiae* & *Y. lipolytica*](#scere)
[![Blue droplet](https://static.igem.wiki/teams/4661/wiki/home/droplet-light-blue.svg) Genetic switch](#switch)
[![Blue droplet](https://static.igem.wiki/teams/4661/wiki/home/droplet-light-blue.svg) Future Concerns](#future)
[![Blue droplet](https://static.igem.wiki/teams/4661/wiki/home/droplet-light-blue.svg) References](#references)

## Introduction

---

### Purpose of Our Project

The main objective of this project is campesterol production by using waste cooking oil (WCO) as a carbon-source. This is accomplished by engineering the *Yarrowia lipolytica*, a type of oleaginous yeast. To do so, we aimed to metabolically engineer *Yarrowia lipolytica* and disrupt the ergosterol synthesis pathway to replace it with 7-dehydrocholesterol reductase (DHCR7), which leads to campesterol production (Figure 1)1,2.

Because metabolically engineering *Y. lipolytica* to produce campesterol is a project tackled in academic communities at large scale and would have not been feasible within the time frame of this project, we focused on the expression of biosurfactants. This increases the yeast’s access to WCO, which can increase campesterol yield 3. Biosurfactants have amphiphilic properties, meaning they mix well both with oil and water. This allows them to interact with the oil-water interface, reducing surface tension and stabilizing emulsions. By engineering *Y. lipolytica* to secrete biosurfactants into the cell culture media, WCO uptake can be improved. Our goals are as follows:

1. Expressing natural hydrophobins as well as mutated hydrophobins and characterizing this expression.
2. Future work would entail metabolic engineering and thus replacing the ERG-5 enzyme in the terpenoid production pathway with the DHCR7 enzyme to produce campesterol.
3. Future implementation of our work as a start-up would also lead us to looking into filtering protocols for waste cooking oil and potential technical issues with the surfactants such as foaming.

![](https://static.igem.wiki/teams/4661/wiki/description/figure-campesterol-pathway.jpg)
***Figure 1. The mevalonate pathway and examples of terpenoids, such as campesterol, produced by engineered *Yarrowia lipolytica*  strains**1. The mevalonate pathway occurs in the yeast cytosol. Many terpenoids accumulate either in lipid compartments or the extracellular matrix, although the terpenoid transport mechanisms in *Y. lipolytica* remain poorly understood. Reproduced from a paper with permission from the authors1.*

### Design Principles

With these goals in mind, we devised a modular approach for three different chassis to produce biosurfactants, that we would execute in the following order:

1. Optimization and expression in *E. coli*.
2. Transformation into and expression in *S. cerevisiae*.
3. Transformation into and expression in *Y. lipolytica*.

First, we optimized hydrophobin sequences in *E. coli* to create *E. coli* hydrophobin plasmid constructs. We then devised cloning strategies for the yeast species *S. cerevisiae* as well as *Y. lipolytica.*

Another important design aspect we explored were the different protein secretion signals in *S. cerevisiae* and *Y. lipolytica*. This was done to ensure an optimal production and transport of biosurfactant proteins in the engineered strains.

### The DBTL Cycle

![iGEM engineering cycle](https://static.igem.wiki/teams/4661/wiki/engineering/cycle.png)
***Figure 2. iGEM Engineering Cycle***

To successfully bring our design principle into reality, we’ve referred to the DBTL cycle from the iGEM engineering guideline: Design → Build → Test → Learn (Figure 2).

Our wet lab project presented some challenges that gave us the opportunity to make ample us of all components of the cycle. Hence, we have completed three full iterations of this cycle. We gave them the following names:

1. Sequence design and our first attempt at cloning.
2. The transition to a step-wise cloning strategy and a different plasmid system.
3. Final cloning and expression evaluation.

These iterations are subdivided into four sections:

1. **Design**: our fundamental design idea was already explained above, but these sections go into further detail regarding our logic on how we chose a certain backbone and parts to rationally sketch our plasmid constructs.
2. **Build**: the actual methods that we used to build our assembly.
3. **Test**: we explained which measurement we chose to test our build and showed corresponding results.
4. **Learn**: we discussed possible reasons why the first design went wrong, as well as which improvements should be taken for the next DBTL cycle.

The DBTL cycle was incredibly helpful when engineering our microorganism because it motivated us to learn from previous mistakes and accomplish several iterations to achieve true engineering success. However, we only got to implement full iterations for *E. coli*. We devised cloning strategies for *Y. lipolytica* and *S. cerevisiae* *in silico*, but we eventually didn’t get to build them.

## *Escherichia coli*

---

### Sequence Design and Our First Attempt at Cloning in pET28

- **First Design:**

  We decided to assemble parts into a pET28 backbone for transformation into *E. coli*. To find the best biosurfactant, we screened a diverse library of sequences from three classes of biosurfactants: HGFI (hydrophobin class I), HFBI and HFBII (hydrophobins class II)4,5 and the MBSP1 protein6. In addition, mutations at the cysteine residues were introduced into the hydrophobin sequences to promote higher protein expression and secretion7. Starting from fundamental parts for our vector, such as the terminator sequence, selection marker (KanR2), Ori (pBR322), repressor (lac I), and His-tag, we designed fusion AcGFP-linker-hydrophobin constructs. Each of the hydrophobin sequences was preceded by a GFP signal (AcGFP) linked with a flexible polypeptide sequence to track successful expression of hydrophobin by measuring fluorescence. As we screened four different biosurfactants (HGFI, HFBI, HFBII, and MBSP1) with different cysteine mutations (HGFI\_half\_mut, HGFI\_full\_mut, HFBI\_mut, HFBII\_mut), we created a total of eight AcGFP-hydrophobin assemblies using Benchling (Table 1).

  ![Figure of pET28](https://static.igem.wiki/teams/4661/wiki/engineering/1stdesign.png)

  ***Figure 3. pET28\_AcGFP\_MBSP1\_060723.***

  | Hydrophobins | Class | Length (bp) |
  | --- | --- | --- |
  | HFBI | Class II hydrophobin | 231 bp |
  | HFBI mutation \* | Class II hydrophobin | 231 bp |
  | HFBII | Class II hydrophobin | 294 bp |
  | HFBII mutation \* | Class II hydrophobin | 294 bp |
  | HGFI | Class I hydrophobin | 324 bp |
  | HGFI half mutation \*\* | Class I hydrophobin | 324 bp |
  | HGFI full mutation \*\* | Class I hydrophobin | 324 bp |
  | MBSPI | Biosurfactant | 897 bp |

  ***Table 1.** Hydrophobins used for pET28\_AcGFP\_linker\_hydrophobin constructs.*

  \* mutations = cysteine residues replaced with serine.
  \*\* HGFI half/full mutation = As HGFI hydrophobin contains 8 cysteine residues, we mutated first 4 cysteins to serine and named it as HGFI half mutation; in case of HGFI full mutation, all cysteines were replaced with serines
- **First Build:**

  By using the Assembly Wizard function in Benchling, we generated primer pairs to make the backbone, AcGFP, and hydrophobin sequences compatible with Golden Gate cloning. We calculated annealing temperatures for all the primer pairs using the NEB Tm Calculator tool. We then PCR amplified our pET28 backbone, AcGFP reporter and insert sequences.
- **First Test:**

  The PCR for AcGFP as well as for the mutated HGFI sequence worked, while that for the pET28 backbone did not, even with various changes such as the use of different polymerases or by gradient PCR. The PCR result was checked using 1% agarose gel electrophoresis. The result can be seen in Figure 4.

  ![](https://static.igem.wiki/teams/4661/wiki/engineering/1sttest.jpg)
  ***Figure 4. Agarose gel showing the result of our first iteration of the DBTL cycle.**
  Lane 1, 3: 1kb ladder
  Lane 2: pET28 plasmid: 5500 bp
  Lane 4: AcGFP fragment: 730 bp
  Lane 5: HGFI\_full\_mutated fragment: 324 bp
  Lane 7: Low MW DNA ladder*
- **First Learn:**

  After repeated failed trials of amplifying our initial desired pET28 backbone, we decided to shift our focus onto a slightly different plasmid backbone (pET29). This backbone already contained a His-tagged GFP sequence. We also dedicated special attention to designing primer pairs with a more appropriate annealing temperature. Another improvement we made was to generate a two-step cloning process, in which a short linker was initially introduced upstream of the sfGFP sequence on the plasmid backbone. Then, the coding sequences for biosurfactant proteins would be introduced in a second cloning step, allowing us to only work with one insert at a time.

### Transition to a Step-wise Cloning Strategy and a Different Plasmid System (pET29)

- **Second Design:**

  Based on the conclusion of the first engineering cycle, we decided to shift to a different backbone: pET29. The result of this can be seen in figures 5 and 6.

  Moreover, the “Learn” from our previous iteration also mentioned improving annealing temperatures. Thus, before building our constructs, we performed an *in silico* PCR through benchling to see if primers were functional to make amplicons for the backbone. By using a different backbone, we were able to obtain primers with lower melting temperatures to create inserts at the desired site within the vector.

  ![pET28_AcGFP_MBSP1_060723](https://static.igem.wiki/teams/4661/wiki/engineering/pet29.png)

  ***Figure 5. pET29\_link\_MBSP1\_200723.***

  ![](https://static.igem.wiki/teams/4661/wiki/engineering/29linker.png)

  ***Figure 6. pET29\_linker\_sfGFP\_200723\_5547bp.***
- **Second Build:**

  To create an intermediate pET29-linker-sfGFP plasmid, we first amplified the original backbone (pET29-sfGFP) using Q5 Polymerase. As correct PCR amplification was confirmed by gel electrophoresis, we moved onto the next step: the annealing of linker oligonucleotides. The amplified plasmid backbone digested with BsaI was ligated to the oligonuclotide duplex containing compatible overhangs using a T4 ligase. The purpose of this cloning step was to introduce a short flexible linker upstream of the GFP sequence, in frame with our expression cassette. After performing T4 ligation, we transformed the ligated intermediated plasmid backbone (pET29-linker-sfGFP) into NEB 10-β competent *E. coli* cells. We amplified our assembly through miniprep and sent samples for sequencing to check the integration of the short oligonucleotide linker. Figure 7 summarizes what we did for this iteration.

  ![](https://static.igem.wiki/teams/4661/wiki/engineering/assembly.png)

  ***Figure 7. Flowchart for intermediate plasmid assembly.***
- **Second Test:**

  The sequencing results did not confirm the insertion of the linker (Figure 8). However, we observed BsaI sites still present in the construct, which led us to believe the plasmid backbone digestion with BsaI was inefficient.

  ![](https://static.igem.wiki/teams/4661/wiki/engineering/seq.jpg)
  ***Figure 8. Sequencing result for linker plasmid.***
- **Second Learn:**

  Since we suspected incomplete BsaI digestion, we tested restriction activity of Bsal on a plasmid with Bsal sites. The results (not shown) demonstrated that the Bsal enzyme successfully cut the plasmid into two fragments (6kb +1kb fragment). Accordingly, we decided to repeat experiments and re-digest amplified pET29 vector with Bsal, while changing the incubation time (30 minutes to 1 hour).

### Final Cloning Strategy and Expression Evaluation

- **Final Design:**

  The design we used for this iteration is identical to the one from the previous cycle.
- **Final Build:**

  As our subsequent sequencing result showed that the linker was successfully inserted, we started PCR amplification of hydrophobin sequences (HGFI, HGFI\_mut\_half, HGFI\_mut\_full) for both Golden Gate and Gibson assemblies. After PCR purification, these hydrophobin amplicons went through a Gibson Assembly reaction to create a “pET29-sfGFP-hydrophobin” plasmid construct.
- **Final Test:**

  As part of our final test, the constructs were miniprepped and sequenced to check if the hydrophobin sequence was incorporated or not.

  Since we suspected incomplete BsaI digestion, we tested restriction activity of Bsal on a plasmid with Bsal sites. The results (not shown) demonstrated that the Bsal enzyme successfully cut the plasmid into two fragments (6kb +1kb fragment). Accordingly, we decided to repeat experiments and re-digest amplified pET29 vector with Bsal, while changing the incubation time (30 minutes to 1 hour).

  ![GFP expression in E. coli](https://static.igem.wiki/teams/4661/wiki/engineering/gfp.jpg)

  ***Figure 9. GFP expression in E. coli.***

  Unfortunately, we came to learn that our expression was leaky, even in the absence of the IPTG inducer. While this observation validated our approach of fusing the proteins of interest to a sfGFP sequence for an easy and visual readout of expression and leakiness, we would like to highlight the need for better transcriptional control in the future. To that end, our team proposes the usage of tight inducible promoters such as those derived in the *E. coli* “Marionette” strains8.

![GFP expression in E. coli](https://static.igem.wiki/teams/4661/wiki/engineering/fig10.png)

***Figure 10. Our idea for improving our promotor and ensuring inducible expression of our target protein.***

- **Final Learn:**

  Upon finalizing our documentation, we realized that the wrong inducer was used in the protein expression experiments in our *E. coli* system. Therefore, the induction with IPTG is most likely not responsible for the driving of protein expression. This realization also highlighted the leakiness of our system and the need for a more tightly controlled system.

  This being said, we still showed that our system leads to hydrophobin expression. This means that fixing the promoter will only result in expression that is actually inducible.

## *Saccharomyces cerevisiae* and *Yarrowia lipolytica*

---

![Plasmid](https://static.igem.wiki/teams/4661/wiki/engineering/scere.png)
***Figure 10. pBEVY-nat\_HFBI\_210823, the plasmid we would have used for cloning in S. cerevisiae.***

We successfully cloned MBSP1, HFBI, and mutant HFBI in *E. coli* and derived strategies to clone the others in *S. cerevisiae* and *Yarrowia lipolytica*. We have plasmid backbones for the two yeast species and designed theoretical plasmid maps using Benchling. However, we could not finish them in the lab, as there was a limited time before the deadline. See Figures 10 and 11 for our constructs for *S. cerevisiae* and *Y. lipolytica* respectively.

![Plasmid](https://static.igem.wiki/teams/4661/wiki/engineering/yw.png)
***Figure 11. NDV-URA3-P1TEF-Lip2\_secretion\_MBSP1\_Lip2\_terminator, the plasmid we would have used in Y. lipolytica.***

## Genetic switch

---

Two separate parts of our project can be distinguished: campesterol biosynthesis and bioemulsifier expression.
Performing both at the same time could be a heavy burden for the cell. Thus, we designed a genetic switch
*in silico* to help mediate this. With a use of such a switch, the cell could switch between producing
campesterol and biosurfactants without overworking itself.

The mechanism would be a simple toggle switch 7,8 that when triggered, changes from one state to the
other. Coming up with the idea for the trigger turned out to be more challenging than we expected.
The easy approach would be to create an oscillatory circuit​9​ that depends on the concentration of
campesterol and biosurfactants. Unfortunately, due to the properties of these molecules, detecting
their concentration would be hard or even impossible. After looking into other possibilities such as
a recombinase addressable data (RAD) module10​, we gathered a few ideas for our bio switch. One of them
consisted of a thermal switch which would be relatively easy to apply.

Normally, during steroid biosynthesis, temperature rises, which would require constant cooling.
We could easily control temperature in a bioreactor by stopping the cooling for a moment and letting
the temperature rise. This would then cause the switch to go from one state to the other.
An additional advantage of such an implementation is that the temporary stops in cooling would
decrease the energy consumption. We also talked about the possibility of exploring the morphological
transition from yeast-to-hyphal growth in *Y. lipolytica* as the trigger for the switch. This could act
as a “one time” switch where in the yeast growth phase, the cell would produce biosurfactant and in
the hyphae form, it would switch to campesterol production. Some other ideas consisted of using
metabolic load as the trigger, or utilizing a quorum sensing system, but these avenues would need
to be explored more thoroughly.

![Genetic switch](https://static.igem.wiki/teams/4661/wiki/engineering/switch.png)

## Future Engineering Concerns

---

As can be seen from the points above, our team did a lot of engineering work already. However, this process isn’t quite done, and we anticipate further engineering challenges down the line. Here, we go over them quickly.

We acknowledge that the use of potentially toxic waste may come with challenges, such as inconsistent chemical composition of the raw material. Another concern are impurities that could affect the proper growth of our yeast as well as patient safety if they are included in the final medicinal product. It is for this reason that we investigated strategies of purifying the WCO substrate for better experimental control. From the literature, we were able to find that using a polypropylene (PP) hollow fiber ultrafiltration (UF) membrane or a combination of esterification, adsorption, solvent extraction, and distillation have been successfully employed in research and industrial settings9.

Moreover, as foaming can become an issue when using surfactants, we acknowledge this limitation and plan to address it through tight transcriptional control of the bioemulsifier sequence eventually produced by our yeast. By separating the emulsifier production phase from the metabolization of waste cooking oil, *Y. lipolytica*  would only produce the proper amount of biosurfactant that it needs to efficiently grow on the oil substrate. To see how we are planning on doing this, check out the next chapter!

### References

1. Arnesen, J. A., Borodina, I. (2022) Engineering of *Yarrowia lipolytica* for terpenoid production. *Metab. Eng. Commun.* **15**: e00231, ISSN 2214-0301.
2. Du H-X, Xiao W-H, Wang Y, Zhou X, Zhang Y, Liu D, et al. (2016) Engineering *Yarrowia lipolytica* for Campesterol Overproduction. *PLoS ONE* **11**(1).
3. Meyer, A.J., Segall-Shapiro, T.H., Glassey, E. et al.*Escherichia coli* “Marionette” strains with 12 highly optimized small-molecule sensors. *Nat Chem Biol* **15**, 196–204 (2019).
4. Cheng, Y., Wang, B., Wang, Y., Zhang, H., Liu, C., Yang, L, et al. (2020) Soluble hydrophobin mutants produced in *Escherichia coli* can self-assemble at various interfaces. *J. Colloid Interface Sci* **574**, 384-395.
5. Aliwarga, L. et al. Impurity Removal of Waste Cooking Oil Using Hydrophobic Polypropylene Hollow Fiber Membrane. *J. Eng. Technol. Sci.* **51**, 216–230 (2019).
6. Cárdenas, J. et al. Pre-treatment of used cooking oils for the production of green chemicals: A review. *J. Clean. Prod.* **289**, 125129 (2021).
7. Gardner, T. S., Cantor, C. R. & Collins, J. J. Construction of a genetic toggle switch in Escherichia coli. *Nature* **403**, (2000).
8. Leon, M., Woods, M. L., Fedorec, A. J. H. & Barnes, C. P. A computational method for the investigation of multistable systems and its application to genetic switches. *BMC Syst Biol* **10**, (2016).
9. Niederholtmeyer, H. et al. Rapid cell-free forward engineering of novel genetic ring oscillators. *Elife* **4**, (2015).
10. Bonnet, J., Subsoontorn, P. & Endy, D. Rewritable digital data storage in live cells via engineered control of recombination directionality. *Proc Natl Acad Sci U S A* **109**, (2012).

{% endblock %}

{% extends "layout.html" %}
{% block title %}Experiments{% endblock %}
{% block lead %}Read about the research, experiments, and protocols we used in our project.{% endblock %}
{% block page\_content %}

[![](https://static.igem.wiki/teams/4661/wiki/home/droplet-light-blue.svg) Dry Lab](#drylab)
[![](https://static.igem.wiki/teams/4661/wiki/home/droplet-light-blue.svg) Wet Lab](#wetlab)

## Dry Lab

---

### Molecular Dynamics Simulations

You can find the protocol for the MD simulations we performed as part of our dry lab work below (if the PDF doesn't appear, you can download it [here](https://static.igem.wiki/teams/4661/wiki/experiments/md-protocol.pdf)):

## Wet Lab

---

### Protocol Summary

You can find summary of all the protocols we performed as part of our wet lab work below (if the PDF doesn't appear, you can download it [here](https://static.igem.wiki/teams/4661/wiki/experiments/experimental-design-2.pdf)):

{% endblock %}

{% extends "layout.html" %}
{% block title %}Results{% endblock %}
{% block lead %}Delve into the results of our wet- and dry lab work!{% endblock %}
{% block page\_content %}

[![](https://static.igem.wiki/teams/4661/wiki/home/droplet-light-blue.svg) Linker](#linker)
[![](https://static.igem.wiki/teams/4661/wiki/home/droplet-light-blue.svg) Cloning](#cloning)
[![](https://static.igem.wiki/teams/4661/wiki/home/droplet-light-blue.svg) Expression](#expression)
[![](https://static.igem.wiki/teams/4661/wiki/home/droplet-light-blue.svg) Time-lapse](#timelapse)
[![](https://static.igem.wiki/teams/4661/wiki/home/droplet-light-blue.svg) Growth](#growth)
[![](https://static.igem.wiki/teams/4661/wiki/home/droplet-light-blue.svg) Transformation](#trans)
[![](https://static.igem.wiki/teams/4661/wiki/home/droplet-light-blue.svg) Enzyme Screening](#enzyme)
[![](https://static.igem.wiki/teams/4661/wiki/home/droplet-light-blue.svg) Hydrophobin Design](#hydrophobin)
[![](https://static.igem.wiki/teams/4661/wiki/home/droplet-light-blue.svg) References](#references)

## Overview

---

This page only reports our results without delving into the design or background of our
thinking. More background information can be found on our [Engineering](%7B%7B%20url_for%28%27pages%27%2C%20page%3D%27engineering%27%29%20%7D%7D),
[Experiments](%7B%7B%20url_for%28%27pages%27%2C%20page%3D%27experiments%27%29%20%7D%7D),
and [Notebook](%7B%7B%20url_for%28%27pages%27%2C%20page%3D%27notebook%27%29%20%7D%7D) pages.
Additionally, the main results of our dry lab work are also described on this current page. For more details however, please refer to our [Model](%7B%7B%20url_for%28%27pages%27%2C%20page%3D%27model%27%29%20%7D%7D) page.

## pET29-linker-sfGFP Assembly

---

We received the pET29-sfGFP plasmid from our lab. We then proceeded to insert a 21 bp linker upstream of sfGFP sequence by Gibson assembly. The successful integration of the linker sequence is shown in Figure 6 [below](#seq).

## Cloning of Biosurfactant Sequences and transformation of *E. coli*

---

We selected several biosurfactants from the literature for expression in *E. coli*.
Specifically, we concentrated on creating expression vectors for MBSP1, HFBI, HFBII, and HGFI.
To enhance the expression levels of HFBI and HFBII, we performed *in silico* mutations on the cysteine
residues. For HFBI, we developed two constructs: one with half of the cysteine residues mutated and
another with all cysteine residues mutated. Additionally, we retained the natural sequence for
comparison in all cases. All of the PCR products showed the desired product length MBSP1 (897 bp),
HFBI sequences (231 bp), HFBII sequences (294 bp) and HGFI sequences (324 bp), (Figure 1).

![](https://static.igem.wiki/teams/4661/wiki/results/figure-1-2.jpg)
***Figure 1: Agarose gel of PCR amplified gBlocks.** LMW = low molecular weight DNA ladder (NEB).*

Following PCR, the PCR products were ligated into our pET29-linker-sfGFP plasmid through
Gibson assembly. The ligated plasmids were transformed in NEB 10-beta Competent *E. coli* cells.
After obtained colonies on selection plates, colony PCR was performed. Colony PCR
performed on MBSP1 showed positive results, as well as for our HFBI constructs
(natural and mutated sequence) and HFBII construct (mutated sequence).

![](https://static.igem.wiki/teams/4661/wiki/results/colony-pcr-for-gibson-assemblies-of-mbsp1.jpg)
***Figure 2. Colony PCR for Gibson assemblies of MBSP1.** LMW = Low Molecular Weight Ladder. Results for 8 different colonies.*

![](https://static.igem.wiki/teams/4661/wiki/results/figure-2.jpg)
***Figure 3. Colony PCR for Gibson assemblies of HFBI (natural sequence).** LMW = Low Molecular Weight Ladder. Results for 8 different colonies.*

![](https://static.igem.wiki/teams/4661/wiki/results/figure-3.jpg)
***Figure 4. Colony PCR for Gibson assemblies of HFBI (mutated sequence).** LMW = Low Molecular Weight Ladder. Results for 8 different colonies.*

![](https://static.igem.wiki/teams/4661/wiki/results/figure-4.jpg)
***Figure 5. Colony PCR for Gibson assemblies of HFBII (mutated sequence).** LMW = Low Molecular Weight Ladder. Results for 8 different colonies.*

For all our other Gibson assemblies we obtained colonies but could not obtain positive
colony PCR results. These were HFBII (natural sequence) and our three HFGI sequences
(natural sequence, half mutated sequence and fully mutated sequence).
After confirming the correct sizes of bands for MBSP1, HFBI (natural sequence),
HFBI (mutated sequence), and HFBII (mutated sequence), plasmids were extracted and
sent for sequencing to Macrogen.

The *in silico* sequences were aligned with the sequencing results, of which the results are shown below in Figure 6. Ligations for MBSP1, HFBI and mutated HFBI were successful. Sequencing also confirmed the insertion of the linker sequence. However, for the mutated HFBII we could not confirm the insertion of the hydrophobin sequence.

![](https://static.igem.wiki/teams/4661/wiki/results/figure-5.jpg)
***Figure 6. Sequencing results for MBSP1, HFBI (natural sequence) and the HFBI (mutated sequence).***

## Expression of MBSP1 and HFBI Sequences

---

We induced recombinant protein expression of MBSP1, HFBI (natural sequence) and our HFBI mutated sequence in
*E. coli* BL21 cells with IPTG. The proteins were extracted, purified and analyzed through
SDS-PAGE.

Our main observation here is that the HFBI mutated sequence shows more intense bands
than HFBI, which indicates that the mutations introduced in the HFBI sequence increased
protein expression. The weights of sfGFP, MBSP1, and HFBI are all about 26.8 kDa, 25 kDa, and
7 kDa, respectively. Therefore, we expected to see a band appearing at around 50 kDa for
MBSP1, but we only see one slightly higher than 25 kDa. We suspect MBSP1 was cleaved off
during protein purification. The results for HFBI are quite similar: for the natural HFBI
protein and mutated HFBI protein, faint bands at different heights can be observed. This
might indicate incomplete cleavage of the sfGFP and HFBI proteins.

![](https://static.igem.wiki/teams/4661/wiki/results/figure-6.jpg)
***Figure 7. SDS-PAGE for MBSP1, HFBI (natural sequence) and HFBI (mutated sequence).** BPSBR = Blue Protein Standard Broad Range P7706S ladder.*

## Live-cell Time-lapse Experiment

---

Time-lapse imaging (Figure 8) reflects the first 20 frames from the microscopy
experiment, where images were taken every 10 minutes for the first hour and every
25 minutes for the subsequence measurements. In accordance with hydrophobin physical
properties1, green fluorescent aggregates can be seen
forming at the poles of the cells. The aggregates are less apparent in the case of the mutated HFBI sequence, where disulfide bridges between cysteine residues were removed.

![Live microscopy](https://static.igem.wiki/teams/4661/wiki/results/hfbi-1-track8-1-20.gif)

**Figure 8a: HFBI natural sequence**

![Live microscopy](https://static.igem.wiki/teams/4661/wiki/results/hfbi-mut1-frame2-1-20.gif)

**Figure 8b: HFBI mutated sequence**

![Live microscopy](https://static.igem.wiki/teams/4661/wiki/results/mbsp1-1-track1-1-20.gif)

**Figure 8c: MBSP1**

## Analyzing the Growth of *Yarrowia lipolytica*

---

![Growth data](https://static.igem.wiki/teams/4661/wiki/results/scatter-plot-of-all-replicated-new.jpg)
 ***Figure 9: Optical density (OD) measurements of *Y. lipolytica* on
a logarithmic scale as a function of time.** Each row represents a different carbon
source used in the growth of the yeast (sunflower oil or glucose at concentrations
of 3.7% and 5%, respectively). The OD values were measured at two different dilution
factors (1:10 and 1:100), as highlighted by the 2 separate columns in the panel.*

Our project implies that *Y. lipolytica* would be grown on waste cooking oil (WCO)
at some point. Thus, we proceeded to evaluate the growth of *Y. lipolytica* on
sunflower seed oil, a commonly used oil for cooking purposes. We then compared
this to the growth on glucose. We know that sunflower oil is not the oil most commonly
used for cooking fries in Belgium, but it was available in the lab and still serves
as a good starting point.

Two replicates of glucose and four of oil culture were prepared for additional accuracy
and OD600 was measured from the cultures every 2 hours for 60 hours.

Based on previous research done on *Y. lipolytica*'s growth on oil
we were expecting a slower growth on oil compared to glucose2.
However, as seen on our growth curve, we observed a faster growth on oil.
This could perhaps be because of an initial glucose starvation as *Y. lipolytica*
was inoculated overnight in 3 ml YPD. This may have led to expression of enzymes to
harvest alternative carbon sources.

![Growth curve](https://static.igem.wiki/teams/4661/wiki/results/image-3.png)

***Figure 10. Growth on 2% glucose medium and 3.7% oil.***

![Growth curve](https://static.igem.wiki/teams/4661/wiki/results/image-2.png)

***Figure 11. Growth on 2% glucose medium and 3.7% oil.***

Alternatively, we hypothesized that 5% glucose could also cause osmotic stress to the cells. However, when comparing the growth to growth on 2% glucose (YPD), the cells reached the end OD of around 24 in both cases and the growth was faster in the case of 5% glucose. Therefore, this hypothesis was dismissed. Growth curves are shown in Figure 10 and Figure 11.

The potential effect of oil on the accuracy of the measurements was also a concern. However, when cells were spun down and the size of pellets were compared between the two cultures, we saw that there was in fact a significant difference between the number of cells present in each culture. This allowed us to also rule out this hypothesis.

In conclusion, since none of the previous research comparing these growth conditions was performed on our strain, we concluded that our strain grows faster and reaches a higher OD on oil compared to glucose. This further supports us choosing *Y. lipolytica* as the strain for our project.

![Growth curve](https://static.igem.wiki/teams/4661/wiki/results/figure-3-baranyi-model-for-the-oil-group.png)

***Figure 12. Growth on oil medium modelled by our growth model (Baranyi model).***

![Growth curve](https://static.igem.wiki/teams/4661/wiki/results/figure-4-baranyi-model-for-the-glucose-group.png)

***Figure 13. Growth on glucose medium modelled by our growth model (Baranyi model).***

Figures 12 and 13 show the growth curves fitted by the Baranyi model. When comparing the two carbon sources, it's notable that the maximum growth rate of oil is two times smaller than that of glucose (Table 1). Additionally, the maximum yield for oil is larger than that for glucose.

| Parameters | Glucose Medium | Oil Medium |
| --- | --- | --- |
| **Initial cell density** | 0.599 | 0.631 |
| **Maximum growth rate** | 0.169 | 0.081 |
| **Maximum yield** | 3.374 | 4.060 |

***Table 1. Maximum growth rates and maximum yields calculated with the Baranyi model for Y. lipolytica growth on glucose and oil medium.***

## Cloning of Plasmids for Transformation in *S. cerevisiae*

---

After successful transformation of *E. coli* and biosurfactant production, we proceeded to create constructs for transformation in *S. cerevisiae* as the next step preceding *Y. lipolytica*’s transformation.

For that purpose, we transformed *E. coli* with a pBEVY vector assembled with HFBI, HFBII or MBSP1 sequences coupled with the native Mating factor alpha-1 secretion signal as our signal for protein export.

### pBEVY, Biosurfactant and Secretion Factor Amplification

Biosurfactants and the secretion factor were successfully amplified using the Q5® High-Fidelity DNA Polymerase (Figure 14). However, the pBEVY amplification was not successful using this enzyme. Therefore, TaKaRa Ex Taq DNA Polymerase was used instead for the plasmid and amplification was carried out successfully (Figure 15). Used primers are shown in Table 2.

|  |  |
| --- | --- |
| **pBEVY Fwd** | CACCATCACCATTAATACCGAGCTCGAATTCGACAC |
| **pBEVY Rev** | GCAGTAAAAATTGAAGGAAATCTCATCCCGGGGAGTTGATTGTATGC |
| **MF Fwd** | GCATACAATCAACTCCCCGGGATGAGATTTCCTTCAATTTTTACTGCAG |
| **MF Rev** | TGAACCTCCAGAACCGCCACTTCTTTTATCCAAAGATACCCCTTCTTC |
| **HFBI Fwd** | AGTGGCGGTTCTGGAGGTTCATCTAACGGCAATGGTAACGTTTGTCC |
| **HFBI Rev** | CGAGCTCGGTATTAATGGTGATGGTGATGGTGCGCCCCAACCGCTGTTTG |
| **HFBII Fwd** | AGTGGCGGTTCTGGAGGTTCAAAGTTCTTCACTGCAGCAGCCC |
| **HFBII Rev** | CGAGCTCGGTATTAATGGTGATGGTGATGGTGAGCAGCACCAACAGCAGC |
| **MBSP1 Fwd** | AGTGGCGGTTCTGGAGGTTCATCGGACCAATACCTTGACTTTG |
| **MBSP1 Rev** | CGAGCTCGGTATTAATGGTGATGGTGATGGTGCGTGGAATCCTGGCCC |

***Table 2: Primers used in the amplification of vector, biosurfactants, and secretion signal.***

![Gel results](https://static.igem.wiki/teams/4661/wiki/results/gel-q5-amplification.jpeg)

***Figure 14. Q5 PCR result: 1= ladder, 2=HFBI, 3= HFBII, 4= MBSP1, 5=pBEVY, 6= MF.***

![Ex taq results](https://static.igem.wiki/teams/4661/wiki/results/extaq-pbevy-amplification.jpeg)

***Figure 15. Ex Taq PCR result: 1 & 3= DNA ladder (1kb), 2= pBEVY.***

### Colony PCR

Colony PCR was performed on eight colonies from the plate with the lesser number of colonies using TaKaRa Ex Taq DNA Polymerase.

However, the result of the colony PCR showed an unsuccessful cloning (Figures 16, 17, and 18)
for the most part. Further analysis did still show possible successful
transformation on colony 7 of HFBII and colony 2 of MBSP1. However, as we were approaching
the deadline, the *S. cerevisiae* transformation was cut short. Table 3 shows the primers
that were used in the colony PCR.

|  |  |
| --- | --- |
| **Forward primer** | 5' GTTGTTGTCTCACCATATCC 3' |
| **Reverse primer** | 5' CTGTTTGTTGGAGGATGCCGTA 3' |

***Table 3: Primers used in the colony PCR.***

![PCR result](https://static.igem.wiki/teams/4661/wiki/results/hfbi.jpeg)

***Figure 16. HFBII colony PCR result.***

![PCR result](https://static.igem.wiki/teams/4661/wiki/results/hfbii.jpeg)

***Figure 17. HFBI colony PCR result.***

![PCR result](https://static.igem.wiki/teams/4661/wiki/results/mbsp1.jpeg)

***Figure 18. MBSP1 colony PCR result.***

## Enzyme Screening

---

The results obtained from molecular docking and MD simulations deviated from our initial expectations. In many of the analyzed organisms, the atoms that were anticipated to form hydrogen bonds did not come into close proximity after simulation, even when they appeared to establish hydrogen bonds during the initial docking phase. Of particular surprise is the case of *Danio rerio*, as the DHCR7 enzyme from this organism had previously demonstrated the highest campesterol yield in the literature3. The docking results indicated strong ligand binding and hydrogen bond formation, yet after conducting MD simulations, the hydroxyl group of ergosta-5.7-dienol and the binding site residues moved apart. This trend was observed in several organisms. We have an idea what could have caused the results to be suboptimal and we elaborate on that on our [Model](%7B%7B%20url_for%28%27pages%27%2C%20page%3D%27model%27%29%20%7D%7D) page.

After analyzing the results from all stages of our enzyme screening, we have identified few promising DHCR7 enzymes that we can introduce to *Yarrowia lipolytica* to facilitate the transformation of ergosta-5.7-dienol into campesterol. In our study, DHCR7 enzymes from *Xenopus laevis* and *Waddlia chondrophila* displayed the most promising behavior with our substrate. However, to validate their efficacy, experimental testing is still required. Additionally, we recommend testing DHCR7 from *Danio rerio* alongside the previously mentioned enzymes, as prior literature4 has indicated its potential for achieving the best campesterol yield.

## Hydrophobin Design

---

We obtained a mutated sequence of HFBI that exhibits a lower isoelectric point than the unmodified HFBI. The isoelectric point decreased from 5.74 to 3.17 due to the mutations K32D, R35D, and K50D. We attempted to employ AlphaFold to investigate the impact of these mutations on the protein structure; however, we encountered a limitation with the tool. The algorithm heavily relies on sequence similarity and cannot effectively detect the influence of point mutations on protein stability.

Furthermore, we employed another tool, PredictSNP, which did not indicate that the introduced mutations would disrupt the stability of the hydrophobin. Nevertheless, this study represents a preliminary assessment, and a more comprehensive analysis, along with wet lab experiments, will be necessary to determine the true success of our design.

### References

1. Torkkeli, M., Serimaa, R., Ikkala, O. & Linder, M. Aggregation and self-assembly of hydrophobins from trichoderma reesei: Low-resolution structural models. *Biophysical Journal* **83**, 2240–2247 (2002).
2. Du HX, Xiao WH, Wang Y, Zhou X, Zhang Y, Liu D, Yuan YJ. Engineering Yarrowia lipolytica for Campesterol Overproduction. *PLoS One*. 2016 Jan 11;11(1):e0146773.
3. Zhang, Y. et al. Improved campesterol production in engineered Yarrowia lipolytica strains. *Biotechnol Lett* **39**, (2017).
4. Ryan Sestric, Garret Munch, Nazim Cicek, Richard Sparling, David B. Levin, Growth and neutral lipid synthesis by Yarrowia lipolytica on various carbon substrates under nutrient-sufficient and nutrient-limited conditions, *Bioresource Technology*, **164**, 2014, 41-46, ISSN 0960-8524.

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