iGEM 2025 — Team concordia-shanghai

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# Notebook

Learn about our background research and the steps to achieve this project!

![](https://static.igem.wiki/teams/5594/icons/purple-arrows.webp)

### Table of Contents

 [Main Constructs](#sec1)
 [PET Isolation in Plastic](#sec1sub1)
[PET to PHB](#sec1sub2)
[PHB Production Optimization](#sec1sub3)
[PHB Depolymerization](#sec1sub4)
 [Modyfying Ecoli to Produce PHB from TPA](#sec2)
 [Experimental Design](#sec3)
[FBA Constraints](#sec4)
[Experiment Logs](#sec5)
[References](#sec6)

# Main Constructs

## PET to PHB

![Figure 1](https://static.igem.wiki/teams/5594/individualpages/wetlab/research/wetlab-research-fig1.webp)

Figure 1:

Research notes describing the paper on flotation technique to isolate PET.
 Based on this source: (Guo et al., 2016).

1. Problem with simple density separation

* Plastics lighter than water (e.g., PE, PP) can be separated through density separation because they float
* Other plastics (e.g., PET, PVC, PC, and PS) are all denser than water which means they will sink

+ Once sunk, they are indistinguishable from one another

2. Solution modified flotation technique
 The principle of this method is to add/modify wetting agents in water to change the flotation behavior of plastics, allowing them to be separated. This process may need to be repeated 2 or 3 times to achieve full separation of a mixed plastic stream.

* Chemical modification

+ Wetting agents can be used to treat plastic, making them more polar/hydrophilic to help with sinking

* Specific protocol from paper

+ Use 3mol/L of NaOH to modify the plastic
+ Use 8mmol/L of DBS added to the water as a wetting agent (its function is to reduce the surface tension of the water)

3. Outcome
Using the specified method (NaOH modification and DBS wetting agent), PVC, PVC, PC, and PS plastics float while the desired plastic (PET) sinks.

## PET to PHB

Reference Documents

* [Main Project Document](https://docs.google.com/document/d/1CPB2nEyg2-n-z_zEXX-6ejc5QDwtBi2tZywoBOvy2YU/edit?tab=t.0)
* [(Project Description | Queens Canada - IGEM 2023, 2023)](https://2023.igem.wiki/queens-canada/description)

1. One-Step PET Degradation and PHB Biosynthesis Strategy

* Rationale for co-cultivation

+ Using a yeast expression system alongside E. coli is advantageous because yeast does not require the addition of inducers, which reduces enzyme production costs (Liu et al., 2021).

2. Key Enzyme for PET Degradation

* The enzyme LCCICCG is highly effective for depolymerizing PET (Arnal et al., 2023).

+ Function - Converts PET into monomeric products Terephthalic Acid (TPA) and Ethylene Glycol (EG)
  - Our desired products are TPA and EG
+ Efficiency - Outperforms other enzymes
  - 98% conversion of PET into TPA and EG in 24 hours

3. Optimized Reaction Conditions for LCCICCG

* Optimization allows for a the required enzyme amount to be reduced by a third and a lower reaction temperature

+ Ideal reaction condition
  - 68°C, 0.1 M phosphate buffer at pH 8.0
+ Duration
  - At 68°, the reaction takes over 48 hours

4. Protein production

* Protocol for producing LCCICCG enzyme:

+ Host
  - E. coli BL21 (DE3) competent cells
+ Expression
  - Cultivation in ZYM auto-inducible medium for 23 hours at 21°C
+ Purification Process
  - Cell harvesting through centrifugation
  - Lysis in buffer (20 mM Tris−HCl, pH 8.0, 300 mM NaCl) through sonication
  - Clarification by centrifugation
  - Purification using TALON metal affinity resin
  - Washing with lysis buffer (+ 10 mM imidazole)
  - Elution with elution buffer (20 mM Tris−HCl, pH 8.0, 300 mM NaCl, 250 mM imidazole)
  - Buffer exchange to storage buffer (100 mM potassium phosphate, pH 8.0) using a desalting column
+ Analysis: Protein concentration determined by molar extinction coefficient; purity evaluated by SDS-PAGE.

![Table 1](https://static.igem.wiki/teams/5594/individualpages/wetlab/research/wetlab-research-table1.webp)

Table 1:

Critical parameters to consider for an upscaling of the enzyme-based PET depolymerization reaction from the perspective of an industrial deployment(Arnal et al., 2023a).

## PHB Production Optimization

1. Overexpression of the zwf gene strategy

* The zwf gene encodes for Glucose-6-phosphate Dehydrogenase (G6PDH)
* Overexpression of zwf leads to increased levels of NADPH, which increases PHB production
* This method provides a greater PHB production increase but also causes greater cell depression
* The process must be aerobic (condition?)
Based on (Lim et al., 2003).

2. Proposed systems for testing

Comparison of 2 systems:* System 1: constant overexpression
  + Overexpression of zwf to increase NADPH and PHB production
* System 2: switchable system
  + Overexpress zwf to boost PHB production
  + Includes the ability to switch off the overexpression to allow normal acetyl-CoA production to return to the regular TCA cycle
    to sustain energy by restoring normal metabolic flux when not producing PHB

Source: (Shi et al., 1999)

3. Metabolic engineering: Balancing NADPH and Acetyl-coa

* Increases in the availability of both Acetyl-CoA and NADPH are necessary to achieve the maximum yield of PHB
* Acetyl-CoA availability can be increased by…
  + Increasing fluxes from glucose to Acetyl-CoA
  + Inducing a blockage in the Acetyl-CoA-consuming pathway
* NADPH availability can be increased by rerouting carbon fluxes to the Pentose Phosphate (PP) pathway (where zwf operates)

![](https://static.igem.wiki/teams/5594/individualpages/wetlab/research/wetlab-research-fig2-cropped.webp)

Figure 2:

One of the major NADPH resources in E.coli is pentose phosphate pathway. Glucose-6-Phosphate-Dehydrogenase is the key enzyme to this pathway. Taken from: [iGEM parts](https://parts.igem.org/Part%3ABBa_K1674004)

* Recombinant E. coli grows faster on gluconate than on glucose, indicating a high conversion rate to acetyl-CoA
  + Does not directly correlate to an increased PHB synthesis rate without sufficient NADPH

4. Aerobic

![Figure 3](https://static.igem.wiki/teams/5594/individualpages/wetlab/research/wetlab-research-fig3.webp)

Figure 3:

E.coli genetic circuit with phbCAB and ZWF or GND

![Figure 4](https://static.igem.wiki/teams/5594/individualpages/wetlab/research/wetlab-research-fig4.webp)

Figure 4:

E.coli genetic circuit with PhnCAB Operon

![Figure 5](https://static.igem.wiki/teams/5594/individualpages/wetlab/research/wetlab-research-fig5.webp)

Figure 5:

Effect of zw and gnd gene amplifications on true cell mass (A) and PHB content (B) in the E. coli transformants. Cultivated in LB medium at the first stage for cell growth at 37°C for 24h, and then transferred to M9 medium containing 10 g/l of glucose and 5 g/l of NH,Cl for PHB accumulation at pH 7.0, 37°C, for 24 h at the second stage. Open circle, Transformant E. coli HB52 harboring the phbCAB operon only; closed triangle, transformant E. coli GHB; closed circle, transformant E. coli ZHB. Taken from: [DOI](https://doi.org/10.1016/s1389-1723%2899%2980132-7)

### PHB Depolymerization

1. Enhanced whole-cell biodegradation of PHB

* Method

+ Co-expression of ORFCma with PHB Depolymerase (PhaZCma) in E. coli

* Result

+ Co-expression induces efficient whole-cell biodegradation of polyesters
+ E. coli with only the depolymerase (pPHAZ) causes 80% weight loss in PHB films in 28 hours
+ E. coli with both the depolymerase and ORF (pORFPHAZ) achieves 80% weight loss in 21 hours

* Enzyme Specific condition: Optimum pH for depolymerase PHAZ\_TALFU is 6.0
  Based on: (Lee et al., 2018)

2. Enzyme Screening and Evolution

The objective was to screen and evolve PhaZ enzymes for higher activity and substrate specificity to degrade PHB into BHB.* Reference Papers

+ (Tan et al., 2012)
+ (Joho et al., 2024)

3. Candidate polar molecules for petase system

When selecting a polar protein candidate for a PETase system, factors considered included size, solubility, stability, and compatibility with the enzyme.* Human Serum Albumin
  + Most abundant protein in blood plasma- Globular protein
  + Weight is around 66.5 kDa
  + Water-soluble and biocompatible
  + Structure changes with pH
    - pH ~7.4: Maintains heart-like structure
    - pH ~3.5: Transitions into cigar-like shape
  + Its spherical structure may limit surface interactions
* Type I Collagen
  + Most abundant protein in humans and animals
  + Weight is around ~3-6 kDa

# Modifying E. coli to produce PHB from TPA

* First Iteration

![Figure 6](https://static.igem.wiki/teams/5594/individualpages/wetlab/research/wetlab-research-fig6.webp)

Figure 6:

Original construct of TPA to PHB in P.Stutz.
In this construct, the promoter being used is the T7 promoter, BBa\_B0034 as the RBS and BBa\_K2560091 as the terminator. After researching Pseudomonas cells, we realized that the T7 promoter, BBa\_B0034 and BBa\_ K2560091 are not compatible with Pseudomonas cell.

* Second Iteration

![Figure 7](https://static.igem.wiki/teams/5594/individualpages/wetlab/research/wetlab-research-7.webp)

Figure 7:

New construct with modified promoter
This discovery led us to find new promoters, terminators and RBS. We talked with Dr. deLorenzo where he recommended us to use xylS/Pm system where it offers tight regulation with minimal basal expression and high induction levels. After talking with Dr. deLorenzo, we also changed the organism we’re using from P.stuts to P.putida strain KT2440. P.stutz is harder to work with than P.putida since P.putida are more domesticated which is more optimal for genetic engineering than P.stutz where it has a more limited genetic tool box.

* Third Iteration

![Figure 7](https://static.igem.wiki/teams/5594/individualpages/wetlab/research/wetlab-research-8.webp)

Figure 8:

Final construct modified to work in Pseudomonas cells
After sending the construct to the company Genscript for plasmid synthesis, we were told the original Phasin-HlyA (BBa\_K2260002) would not work in Pseudomonas cells. The function of Phasin- HlyA is to tag and secrete PHB out of the cell. With this in mind, we found BBa\_K4728007 which is PhaF. This has the same function as Phasin-HlyA, but it can work in Pseudomonas cells.

The Processes

+ PET → TPA → PCA → PHB
+ TPA → PCA
+ PCA → PHB

Based On:

* (Li et al., 2024)
* (Wells & Ragauskas, 2012)

![Figure 9](https://static.igem.wiki/teams/5594/individualpages/wetlab/research/wetlab-research-fig9.webp)

Figure 9:

PCA to PHB reaction pathway

* Protocatechuate 3,4-dioxygenase (pcaGH):
  Sources:+ (Part:BBa K2091001 - Parts.igem.org, 2016)
  + (UniProt, 2025)
* 3-carboxy-cis,cis-muconate cycloisomerase (pcaB):
  Sources:+ (EMBL-EBI, 2025)
* 4-Carboxymuconolactone Decarboxylase (pcaC):
  Sources:+ (Part:BBa K2091002 - Parts.igem.org, 2016)
* ELH
  Sources:+ (Gene - GCF\_042159195.1, 2025)

FILLER/UNCOM. Change later
pcaD (P. putida), catD (A. calcoaceticus)

Beta-ketoadipate enol-lactone hydrolase

TH: pcaF

b-Ketoadipyl-CoA thiolase

![](https://static.igem.wiki/teams/5594/individualpages/wetlab/research/wetlab-research-table2.webp)

Table 2:

Table showing the enzymes involved in converting PCA into Acetyl- CoA

# Experimental Design

### PART 1: PET Linker

### PART 2: Verify LCCICCG: PET to PHB and EG construct

* PETase:
  + Optimization of reaction conditions for LCCICCG:
    Source: (Team:KEYSTONE/Engineering - 2020.Igem.org, 2020)- Combine 1 ml of a 0.69µM solution of purified LCCICCG protein (in 20 mM Tris-HCl, pH 8, 300 mM NaCl) with 100 mg PET powder and 49ml of 100 mM potassium phosphate buffer (pH 8) in a 100 ml flask
    - Incubate at 72˚C under 170 rpm agitation
* PHB production:
  + Media: glucose;1 g, peptone;0.25 g, yeast extract;0.25 g, NaCl;0.01 g, KH2PO4;0.05 g, MgSO4;0.02 g (Krishnan et al., 2017, Mostafa et al., 2020).
* PHB production (E COLI)
  + Optimum culture medium: 37.96 g deproteinated milk whey powder/l, 29.39 g corn steep liquor/l, and 23.76 g phosphates/l (r2 = 0.957)

### PART 3: PHB to BHB (no PET)

* Optimum reaction conditions:
  + pH = 6
* Proposed conditions for PHAZ\_TALFU optimization
  + Substrate: 0.1% PHB
  + Buffer: K₂HPO₄ (1.6 g/L)
  + Temperature: 27 ℃
  + Duration: Seven days

  - Based On: (Amir et al., 2022)

# FBA Constraints

* ZWF gene encodes for Glucose-6-Phosphate Dehydrogenase - overexpressing zwf produces increased levels of NADPH through the PP pathway, leading to increased PHB production
* Try co-overexpression of sdaA - increase L-serine dehydratase 1 (L-SD1) enzyme
* Try inactivating the phosphoglucose isomerase (encoded by pgi) gene

+ (Zhang et al., 2014)

![Figure 11](https://static.igem.wiki/teams/5594/individualpages/wetlab/research/wetlab-research-fig11.webp)

Figure 11:

Schematic representation of the SD and ED metabolic pathways in PHB accumulation recombinant E.coli. Dashed lines indicate multiple enzymatic steps.
The bold lines indicate the enzymes of the SD pathway including reactions catalyzed by SerACB and SdaA. The enzymes that had been overexpressed in this work were shown in boldface. G6P, glucose-6-phosphate; FBP, fructose-1,6-bisphosphate; G3P, glycerahyde-3-phosphate; DHAP, dihydroxyacetone phosphate; 6PG, 6-phosphate-gluconate. Enzymes are as follows: Zwf, glucose 6-phosphate-1-dehydrogenase; Edd, phosphogluconate dehydratase; Eda, 2-keto-3-deoxygluconate 6-phosphate aldolase; Pgk, phosphoglycerate kinase; SerA, D-3-phosphoglycerate dehydrogenase; SerB, phosphoserine phosphatase; SerC, 3-phosphoserine aminotransferase; SdaA, L-serine deaminase I; PoxB, pyruvate oxidase; Pta, phosphate acetyltransferase; Ack, acetate kinase; PhaA, B-ketothiolase; PhaB, NADPH-dependent acetoacetyl-CoA reductase; PhaC, PHB synthase.

### PET to TPA and EG (w/ LCCICCG/H218Y mutation)

![Figure 12](https://static.igem.wiki/teams/5594/individualpages/wetlab/research/wetlab-research-12.webp)

Figure 12:

This construct in E.coli converts PET to TPA and EG. Part BBa\_E0040 encodes for the GFP protein that allows for visual confirmation of circuit activity. Part B LCC-ICCG/H218Y is the LCC-ICCG gene with a H218Y mutation. The introduction of a histidine to tyrosine substitution at position 218 in Petase shows an increase in Petase activity (Orr et al., 2024). LCC- ICCG codes for the protein Petase that degrades PET into TPA and EG. EG will not go on to further processes and will be discarded. Taken from: [DOI](https://doi.org/10.1002/biot.202400021)

### PHB to BHB (E.coli)

![Figure 13](https://static.igem.wiki/teams/5594/individualpages/wetlab/research/wetlab-research-fig13.webp)

Figure 13:

This is the construct of PHB to BHB Pathway

The system uses pTet to express the PHB biosynthesis enzymes (3 genes phaA, B, and C), followed by Phasin (binds to intracellular PHB and marks it for secretion outside of the cell). Also downstream of this promoter is LuxI for the production of AHL, which can activate pLux when cell density is high. Under the control of pLux is PHB depolymerase enzyme and TetR (repressor of pTet). This system will break down PHB into BHB as well as providing negative feedback to the first promoter to prevent over exhaustion of the cell and stopping PHB production.

### PET to PHB (w/ zwf and LCCICCG/H218Y mutation)

![Figure 14](https://static.igem.wiki/teams/5594/individualpages/wetlab/research/wetlab-research-14.webp)

Figure 14:

This combines our constructs into one system for the breakdown of PET into PHB.

# Experiment Logs

# References

1
Amir, M., Bano, N., Baker, A., Zia, Q., Saeed Banawas, Mohd. Rehan Zaheer, Shariq, M., Md Sarfaraz Nawaz, Mohd. Farhan Khan, Azad, A., Gupta, A., Iqbal, D., & Roohi. (2022). Isolation and optimization of extracellular PHB depolymerase producer Aeromonas caviae Kuk1-(34) for sustainable solid waste management of biodegradable polymers. PLOS ONE, 17(4), e0264207–e0264207.

[DOI](https://doi.org/10.1371/journal.pone.0264207)

2
Arnal, G., Anglade, J., Gavalda, S., Tournier, V., Chabot, N., Bornscheuer, U. T., Weber, G., & Marty, A. (2023). Assessment of Four Engineered PET Degrading Enzymes Considering Large-Scale Industrial Applications. ACS Catalysis, 13(20), 13156–13166.

[DOI](https://doi.org/10.1021/acscatal.3c02922)

3
Baler, K., Martin, O. A., Carignano, M. A., Ameer, G. A., Vila, J. A., & Szleifer, I. (2014). Electrostatic Unfolding and Interactions of Albumin Driven by pH Changes: A Molecular Dynamics Study. The Journal of Physical Chemistry B, 118(4), 921–930.

[DOI](https://doi.org/10.1021/jp409936v)

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[EBI](https://www.ebi.ac.uk/ena/browser/view/L17082)

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Gene - GCF\_042159195.1. (2025). NCBI.

[NCBI](https://www.ncbi.nlm.nih.gov/datasets/gene/GCF_042159195.1/?search=pca)

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Guo, J., Li, X., Guo, Y., Ruan, J., Qiao, Q., Zhang, J., Bi, Y., & Li, F. (2016). Research on Flotation Technique of Separating PET from Plastic Packaging Wastes. Procedia Environmental Sciences, 31, 178–184.

[DOI](https://doi.org/10.1016/j.proenv.2016.02.024)

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[DOI](https://doi.org/10.1016/j.jsamd.2023.100549)

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[DOI](https://doi.org/10.1093/protein/gzae009)

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Lee, M., Liu, E., Yang, C., Hsiao, L., Wu, T., & Li, S. (2018). Co‐Expression of ORFCma with PHB Depolymerase (PhaZCma) in Escherichia coli Induces Efficient Whole‐Cell Biodegradation of Polyesters. Biotechnology Journal, 13(4).

[DOI](https://doi.org/10.1139/m95-190)

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[DOI](https://doi.org/10.3390/molecules24224031)

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[DOI](https://doi.org/10.1021/acssynbio.6b00083)

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[DOI](https://doi.org/10.1016/S1389-1723%2802%2980235-3)

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[Book](https://www.ncbi.nlm.nih.gov/books/NBK459198/)

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[Part BBa\_K2091001](https://parts.igem.org/Part%3ABBa_K2091001)

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[Part BBa\_K2091002](https://parts.igem.org/Part%3ABBa_K2091002)

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[iGEM Queens Canada](https://2023.igem.wiki/queens-canada/description)

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[DOI](https://doi.org/10.3389/fbioe.2023.1297431)

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# Engineering

Learn how our team incorporated the design engineering cycle!

![](https://static.igem.wiki/teams/5594/icons/purple-arrows.webp)

### Table of Contents

[Introduction](#sec1)
[Iteration 1](#sec2)
[Design](#sec2sub1)
[Build](#sec2sub2)
[Test](#sec2sub3)
[Learn](#sec2sub4)
[Iteration 2](#sec3)
[Design](#sec3sub1)
[Build](#sec3sub2)
[Test](#sec3sub3)
[Learn](#sec3sub4)
[Final Product](#sec4)
[References](#sec5)

# Introduction

Our team demonstrated engineering success through an iterative approach to metabolic engineering, resulting in the design of composite
synthetic biology devices essential for achieving our goal of upcycling PET plastic. This undertaking was informed by our Integrated Human
Practices work, where we consulted with Dr. Chitong Rao, Chief Scientist at Bluepha Co., Ltd.—a global leader in using synthetic biology
for degradable bio-polymer production—and Dr. Joanne Sadler from the University of Edinburgh, whose work on producing vanillin from the
microbial breakdown of PET served as initial inspiration for our project.

From these meetings, we learned that metabolic engineering to increase yields of useful products would be essential for making our concepts
both economically viable and environmentally sustainable. This insight was further confirmed through our team's Life Cycle Analysis of our
desired products and during the development of our business plan.

Our goal was to increase the production of poly(3-hydroxybutyrate) (PHB), a type of polyhydroxyalkanoate (PHA) that can be downstream depolymerized
into beta-hydroxybutyrate (BHB). We chose this target for several reasons:

1. It is a type of PHA where Dr. Rao's expertise and the information he provided during our collaboration could be leveraged.
2. PHB can be depolymerized by an enzyme known to the team, as described by the 2024 Concordia iGEM team, thus enabling for the production of BHB as a high-value product from increased PHB levels.
3. We had already designed genetic circuits in both E. coli and P. putida to produce PHB, allowing our research to focus on enhancing this biosynthesis pathway familiar to the team.

Through literature research, we discovered that increasing the production of NADPH and Acetyl-CoA would result in increased PHB production via
the PHB biosynthesis pathway (Shi et al., 1999). We utilized Flux Balance Analysis (FBA), a constraint-based metabolic modeling method, using
several target genes, enzymes, and reactions identified from the literature (Lim et a., 2002; Zhang et al., 2020, Zhang et al., 2014).

The first iteration of the Design-Build-Test-Learn (DBTL) cycle tested whether incorporating certain genetic targets (identified from literature)
would have the desired effect of increasing NADPH production by increasing metabolic flux. After verifying plausible targets, the second iteration
determined whether our designed devices would elicit an increase in NADPH when modeled with expected enzyme concentrations and reaction fluxes.

Our engineering design cycle addressed the following questions:

1. Which potential gene/protein could be engineered into our devices that will increase the amount of NADPH available to the PHB biosynthesis pathway?
2. Will the engineering of new genes/proteins into these devices increase the amount of NADPH available to the PHB biosynthesis pathway when the solved enzyme concentrations and reaction rates are incorporated?

# Iteration 1

![](https://static.igem.wiki/teams/5594/individualpages/drylab/dbtl-iteration1-correct.webp)

Figure 1:

DBTL cycle for Iteration 1.

### Design

Suggested by the literature on engineering E.coli to improve poly(3-hydroxybutyrate) production, the team identified genes,
enzymes, and reaction targets of which we hypothesized would be effective in increasing the production of Acetyl-CoA and NADPH.
Subsequently, we hypothesized an increase in the production of PHB, a high-value product. (Zhang et al., 2014) In the metabolic
engineering upregulation process, the reaction targets were G6PD and PDH, as they were proven to be responsible for the production
of Acetyl-CoA and NADPH. (Lim et a., 2002; Zhang et al., 2020) The identified gene and enzyme targets included increasing zwf,
increasing serA, and more.

### Build

The team identified two models: iJN1463 for Pseudomonas putida KT2440 and iEC1356\_Bl21DE3 for E. coli BL21(DE3). Using the model
of Pseudomonas putida KT2440, we utilized Flux Balance Analysis, a constraints-based modeling, to test the effect of targets. To
increase a certain gene or enzyme, the upper and lower bounds of the associated reaction need to be increased. Therefore, we identified
the reactions that the selected target genes code for. The upper and lower bounds during the first iteration were theoretical values,
as it was impossible to know the exact possible increase in the selected targets.

### Test

We implemented a Python package, COBRApy, to conduct a flux balance analysis with the gene, enzyme, and reaction targets.

## Data (First Trial)

All influx and outflux values are expressed in mmol/gDW/h.

### 1. Increase serA, serB, and serC

serA BIGG ID: PP\_5155

Associated reaction: Phosphoglycerate dehydrogenase (PGCD)

serB BIGG ID: PP\_4909

Associated reaction: Phosphoserine phosphatase (L-serine) (PSP\_L) Associated reaction: Phosphoglycerate dehydrogenase (PGCD)

serC BIGG ID: PP\_1768

Associated reactions: O-Phospho-4-hydroxy-L-threonine (OHPBAT)

| Weight 0.5 (G6PD) : 0.5 (PDH) | Before ser increase | After ser increase |
| --- | --- | --- |
| NADPH influx | 209.080 | 183.387 |
| NADPH outflux | 197.080 | 524.320 |
| Acetyl-CoA influx | 3.898e-14 | 5.826e-14 |
| Acetyl-CoA outflux | 298.160 | 144 |

Table 1:

Increase serA, serB, and serC (0.5:0.5 weighing)

| Weight 0.7 (G6PD) : 0.3 (PDH) | Before ser increase | After ser increase |
| --- | --- | --- |
| NADPH influx | 75.387 | 75.387 |
| NADPH outflux | 596.320 | 596.320 |
| Acetyl-CoA influx | 0 | 0 |
| Acetyl-CoA outflux | 1.312e-14 | 0 |

Table 2:

Increase serA, serB, and serC (0:7:0.3 weighing)

| Weight 0.3 (G6PD) : 0.7 (PDH) | Before ser increase | After ser increase |
| --- | --- | --- |
| NADPH influx | 197.080 | 197.080 |
| NADPH outflux | 233.080 | 66.920 |
| Acetyl-CoA influx | 3.111e-14 | 6.539e-16 |
| Acetyl-CoA outflux | 310.160 | 310.160 |

Table 3:

Increase serA, serB, and serC (0.3:0.7 weighing)

---

### 2. Increase serA

serA BIGG ID: PP\_5155

Associated reaction: Phosphoglycerate dehydrogenase (PGCD)

| Weight 0.5 (G6PD) : 0.5 (PDH) | Before ser increase | After ser increase |
| --- | --- | --- |
| NADPH influx | 209.080 | 183.387 |
| NADPH outflux | 197.080 | 524.320 |
| Acetyl-CoA influx | 3.898e-14 | 5.826e-14 |
| Acetyl-CoA outflux | 298.160 | 144 |

Table 4:

Increase serA (0.5:0.5 weighing)

| Weight 0.7 (G6PD) : 0.3 (PDH) | Before ser increase | After ser increase |
| --- | --- | --- |
| NADPH influx | 75.387 | 75.387 |
| NADPH outflux | 596.320 | 596.320 |
| Acetyl-CoA influx | 0 | 0 |
| Acetyl-CoA outflux | 1.312e-14 | 2.010e-14 |

Table 5:

Increase serA (0.7:0.3 weighing)

| Weight 0.3 (G6PD) : 0.7 (PDH) | Before ser increase | After ser increase |
| --- | --- | --- |
| NADPH influx | 197.080 | 197.080 |
| NADPH outflux | 233.080 | 66.920 |
| Acetyl-CoA influx | 3.111e-14 | 0 |
| Acetyl-CoA outflux | 310.160 | 310.160 |

Table 6:

Increase serA (0.3:0.7 weighing)

---

### 3. Increase zwf

zwf BIGG ID: PP\_5351

Associated reaction: Beta-D-Glucose-6-phosphate NADP+ 1-oxoreductase (G6PBDH)

| Weight 0.5 (G6PD) : 0.5 (PDH) | Before zwf increase (G6PBDH) | After zwf increase |
| --- | --- | --- |
| NADPH influx | 209.080 | 10209.080 |
| NADPH outflux | 197.080 | 10197.080 |
| Acetyl-CoA influx | 3.898e-14 | 3.898e-14 |
| Acetyl-CoA outflux | 298.160 | 298.160 |

Table 7:

Increase zwf (0.5:0.5 weighing)

| Weight 0.7 (G6PD) : 0.3 (PDH) | Before zwf increase (G6PBDH) | After zwf increase |
| --- | --- | --- |
| NADPH influx | 75.387 | 10075.387 |
| NADPH outflux | 596.320 | 10596.320 |
| Acetyl-CoA influx | 0 | 0 |
| Acetyl-CoA outflux | 1.312e-14 | 0 |

Table 8:

Increase zwf (0.7:0.3 weighing)

| Weight 0.3 (G6PD) : 0.7 (PDH) | Before zwf increase (G6PBDH) | After zwf increase |
| --- | --- | --- |
| NADPH influx | 197.080 | 10197.080 |
| NADPH outflux | 233.080 | 10233.080 |
| Acetyl-CoA influx | 3.111e-14 | 3.181e-12 |
| Acetyl-CoA outflux | 310.160 | 310.160 |

Table 9:

Increase zwf (0.3:0.7 weighing)

---

### 4. Increase zwf and serA

| Weight 0.5 (G6PD) : 0.5 (PDH) | Before zwf and serA increase | After zwf and serA increase |
| --- | --- | --- |
| NADPH influx | 209.080 | 10183.387 |
| NADPH outflux | 197.080 | 10524.32 |
| Acetyl-CoA influx | 3.898e-14 | 9.702e-14 |
| Acetyl-CoA outflux | 298.160 | 144 |

Table 10:

Increase zwf and serA (0.5:0.5 weighing)

| Weight 0.7 (G6PD) : 0.3 (PDH) | Before zwf and serA increase | After zwf and serA increase |
| --- | --- | --- |
| NADPH influx | 75.387 | 10075.387 |
| NADPH outflux | 596.320 | 10596.320 |
| Acetyl-CoA influx | 0 | 0 |
| Acetyl-CoA outflux | 1.312e-14 | 0 |

Table 11:

Increase zwf and serA (0.7:0.3 weighing)

| Weight 0.3 (G6PD) : 0.7 (PDH) | Before zwf and serA increase | After zwf and serA increase |
| --- | --- | --- |
| NADPH influx | 197.080 | 10197.080 |
| NADPH outflux | 233.080 | 10066.920 |
| Acetyl-CoA influx | 3.111e-14 | 0 |
| Acetyl-CoA outflux | 310.160 | 310.160 |

Table 12:

Increase zwf and serA (0.3:0.7 weighing)

---

### 5. Increase sdaA

Genes: tdcG-I, tdcG-II, tdcG-III

BIGG ID: PP\_0297, PP\_0987, PP\_3144

Associated reaction: L-serine deaminase (SERD\_L)

| Weight 0.5 (G6PD) : 0.5 (PDH) | Before sdaA increase | After sdaA increase |
| --- | --- | --- |
| NADPH influx | 209.080 | 183.387 |
| NADPH outflux | 197.080 | 524.320 |
| Acetyl-CoA influx | 3.898e-14 | 0 |
| Acetyl-CoA outflux | 298.160 | 144 |

Table 13:

Increase sdaA (0.5:0.5 weighing)

| Weight 0.7 (G6PD) : 0.3 (PDH) | Before sdaA increase | After sdaA increase |
| --- | --- | --- |
| NADPH influx | 75.387 | 75.387 |
| NADPH outflux | 596.320 | 596.320 |
| Acetyl-CoA influx | 0 | 4.704e-15 |
| Acetyl-CoA outflux | 1.312e-14 | 7.116e-13 |

Table 14:

Increase sdaA (0.7:0.3 weighing)

| Weight 0.3 (G6PD) : 0.7 (PDH) | Before sdaA increase | After sdaA increase |
| --- | --- | --- |
| NADPH influx | 197.080 | 131.080 |
| NADPH outflux | 233.080 | 167.080 |
| Acetyl-CoA influx | 3.111e-14 | 7.474e-15 |
| Acetyl-CoA outflux | 310.160 | 310.160 |

Table 15:

Increase sdaA (0.3:0.7 weighing)

---

### 6. Increase fbaA

fbaA BIGG ID: PP\_4960

Associated reaction: Fructose-bisphosphate aldolase (FBA)

| Weight 0.5 (G6PD) : 0.5 (PDH) | Before fbaA increase | After fbaA increase |
| --- | --- | --- |
| NADPH influx | 209.080 | 209.080 |
| NADPH outflux | 197.080 | 197.080 |
| Acetyl-CoA influx | 3.898e-14 | 3.898e-14 |
| Acetyl-CoA outflux | 298.160 | 298.160 |

Table 16:

Increase fbaA (0.5:0.5 weighing)

| Weight 0.7 (G6PD) : 0.3 (PDH) | Before fbaA increase | After fbaA increase |
| --- | --- | --- |
| NADPH influx | 75.387 | 75.387 |
| NADPH outflux | 596.320 | 596.320 |
| Acetyl-CoA influx | 0 | 0 |
| Acetyl-CoA outflux | 1.312e-14 | 1.312e-14 |

Table 17:

Increase fbaA (0.7:0.3 weighing)

| Weight 0.3 (G6PD) : 0.7 (PDH) | Before fbaA increase | After fbaA increase |
| --- | --- | --- |
| NADPH influx | 197.080 | 197.080 |
| NADPH outflux | 233.080 | 233.080 |
| Acetyl-CoA influx | 3.111e-14 | 3.111e-14 |
| Acetyl-CoA outflux | 310.160 | 310.160 |

Table 18:

Increase fbaA (0.3:0.7 weighing)

---

### 7. Knock out pgi

Pgi BIGG IDs: PP\_4701, PP\_1808

| Weight 0.5 (G6PD) : 0.5 (PDH) | Before knockout | After knockout |
| --- | --- | --- |
| NADPH influx | 209.080 | 197.080 |
| NADPH outflux | 197.080 | 185.080 |
| Acetyl-CoA influx | 3.898e-14 | 0 |
| Acetyl-CoA outflux | 298.160 | 310.160 |

Table 19:

Knock out pgi (0.5:0.5 weighing)

| Weight 0.7 (G6PD) : 0.3 (PDH) | Before knockout | After knockout |
| --- | --- | --- |
| NADPH influx | 75.387 | 197.080 |
| NADPH outflux | 596.320 | 185.080 |
| Acetyl-CoA influx | 0 | 5.227e-47 |
| Acetyl-CoA outflux | 1.312e-14 | 310.160 |

Table 20:

Knock out pgi (0.7:0.3 weighing)

| Weight 0.3 (G6PD) : 0.7 (PDH) | Before knockout | After knockout |
| --- | --- | --- |
| NADPH influx | 197.080 | 197.080 |
| NADPH outflux | 233.080 | 185.080 |
| Acetyl-CoA influx | 3.111e-14 | 0 |
| Acetyl-CoA outflux | 310.160 | 310.160 |

Table 21:

Knock out pgi (0.3:0.7 weighing)

---

### 8. Coexpression of sdaA, serA, and pgk

Pgk BIGG ID: PP\_4963

Associated reaction: Phosphoglycerate kinase (PP\_4963)

| Weight 0.5 (G6PD) : 0.5 (PDH) | Before coexpression | After coexpression |
| --- | --- | --- |
| NADPH influx | 209.080 | 183.387 |
| NADPH outflux | 197.080 | 524.320 |
| Acetyl-CoA influx | 3.898e-14 | 0 |
| Acetyl-CoA outflux | 298.160 | 144 |

Table 22:

Coexpression of sdaA, serA, and pgk (0.5:0.5 weighing)

| Weight 0.7 (G6PD) : 0.3 (PDH) | Before coexpression | After coexpression |
| --- | --- | --- |
| NADPH influx | 75.387 | 75.387 |
| NADPH outflux | 596.320 | 596.320 |
| Acetyl-CoA influx | 0 | 4.704e-15 |
| Acetyl-CoA outflux | 1.312e-14 | 7.116e-13 |

Table 23:

Coexpression of sdaA, serA, and pgk (0.7:0.3 weighing)

| Weight 0.3 (G6PD) : 0.7 (PDH) | Before coexpression | After coexpression |
| --- | --- | --- |
| NADPH influx | 197.080 | 131.080 |
| NADPH outflux | 233.080 | 167.080 |
| Acetyl-CoA influx | 3.111e-14 | 7.474e-15 |
| Acetyl-CoA outflux | 310.160 | 310.160 |

Table 24:

Coexpression of sdaA, serA, and pgk (0.3:0.7 weighing)

---

### Learn

serA and zwf were shown to be successful in increasing the NADPH yield, though they had minimal effect on Acetyl-CoA yield. However,
increasing NADPH yield can have the desired effect of downstream upregulation of key metabolites in PHB synthesis. Other targets showed
insignificant changes in yields. Hence, serA and zwf were chosen as effective targets, specifically zwf being the most successful one.

# Iteration 2

![](https://static.igem.wiki/teams/5594/individualpages/drylab/dbtl-iteraction2.webp)

Figure 2:

DBTL cycle for Iteration 2.

### Design

From Iteration 1, the team designed genetic circuits using targets and standard parts, including inducible promoter systems T7 (E.coli) and Xysl (P.putida).
The genetic circuits included serA and zwf as they were shown to be effective.

### Build

To find yields of key enzymes, we aimed to find exact upper reaction bounds for our Constraint-Based Modeling. This was done through ODEs and enzyme
kinetics for our designed circuits. We modelled PHGDH production by serA to obtain the maximum enzyme concentration. A similar work was done with the
second target, zwf. Then, utilizing enzyme kinetics for our designed circuits, that value was converted to an upper bound that could be used in the FBA.
Full working can be found here: [Model](%7B%7B%20url_for%28%27pages%27%2C%20page%3D%27model%27%29%20%7D%7D)

### Test

To test how our system will behave after modifying the model, we used the upper bounds for our model from previous steps in the engineering cycle and
conducted a second flux balance analysis for zwf.

## Data (Second Trial - zwf)

| Weight 0.5 (G6PD) : 0.5 (PDH) | Before zwf increase (G6PBDH) | After zwf increase |
| --- | --- | --- |
| NADPH influx | 209.080 | 955.940 |
| NADPH outflux | 197.080 | 983.949 |
| Acetyl-CoA influx | 3.898e-14 | 3.287e-15 |
| Acetyl-CoA outflux | 298.160 | 298.160 |

Table 25:

Increase zwf (0.5:0.5 weighing)

| Weight 0.7 (G6PD) : 0.3 (PDH) | Before zwf increase (G6PBDH) | After zwf increase |
| --- | --- | --- |
| NADPH influx | 75.387 | 862.247 |
| NADPH outflux | 596.320 | 1383.180 |
| Acetyl-CoA influx | 0 | 0 |
| Acetyl-CoA outflux | 1.312e-14 | 9.714e-14 |

Table 26:

Increase zwf (0.7:0.3 weighing)

| Weight 0.3 (G6PD) : 0.7 (PDH) | Before zwf increase (G6PBDH) | After zwf increase |
| --- | --- | --- |
| NADPH influx | 197.080 | 983.940 |
| NADPH outflux | 233.080 | 1019.940 |
| Acetyl-CoA influx | 3.111e-14 | 3.111e-14 |
| Acetyl-CoA outflux | 310.160 | 310.160 |

Table 27:

Increase zwf (0.3:0.7 weighing)

### Learn

The team learned that zwf increase is effective in increasing NADPH yield in our designed inducible systems. We confirmed our decision to utilize zwf in
the experimentations, since it was also most effective in increasing NADPH and following PHB yield,
a high-value product produced from PET plastic. We then proceeded to the final design based on data from FBA models.

# Final Product (Designed Composite Parts)

![](https://static.igem.wiki/teams/5594/individualpages/drylab/engineering1.webp)

Figure 3:

ZWF gene (pink) which codes for Glucose-6-Phosphate-Dehydrogenase under the influence of T7 promoter. PhaC/A/B code for the biosynthesis of PHB. Bba\_K2260002 is Phasin.

![](https://static.igem.wiki/teams/5594/individualpages/drylab/engineering2.webp)

Figure 4:

Zwf in P. putida under the Xysl/Pm expression system. SerA gene (pink) which codes for D-3-phosphoglycerate dehydrogenase. PhaC/A/B code for the biosyntehsis of PHB.

Through constraint-based metabolic modeling, our team demonstrated engineering success by showing that the increase in zwf and serA increased the amount of NADPH available to the PHB biosynthesis pathway. Moreover, our designed devices elicited an increase in NADPH when modeled with expected enzyme concentrations and reaction fluxes, thus confirming that, theoretically, our gene engineering result in increased PHB production.

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{% endblock %}


{% extends "layout.html" %}
{% block page\_content %}

# Results

Learn about our results!

![](https://static.igem.wiki/teams/5594/icons/purple-arrows.webp)

## Table of Contents

[1. Testing for the construct of PET to TPA and EG (Synthesis of Petase)](#sec1)
[Experimental Design](#sec1sub1)
[Procedure](#sec1sub2)
[Results](#sec1sub3)
[2. TPA transporter](#sec2)
[Procedure](#sec2sub1)
[Results](#sec2sub2)
[3. PHB to BHB Pathway (Expression of PHAZ\_TALFU)](#sec3)
[Procedure](#sec3sub1)
[Results](#sec3sub2)
[4. Transformation of chromoprotein parts](#sec4)
[References](#sec5)

![](https://static.igem.wiki/teams/5594/individualpages/wetlab/results/experiments-results-fig-8.avif)

Figure 1:

PET to TPA pathway in E.coli

We constructed a PET degradation system that enables E. coli to convert polyethylene terephthalate (PET) into terephthalic acid (TPA) and ethylene glycol (EG). Part BBa\_E0040 is the GFP protein that allows for visual confirmation of circuit activity. Part BBa\_K3478888 is the LCC-ICCG gene with a H218Y mutation. The introduction of a histidine to tyrosine substitution at position 218 in PETase shows an increase in PETase activity (Orr et al., 2024). LCC- ICCG codes for the protein PETase that degrades PET into TPA and EG. EG will not go on to further processes and will be discarded. We confirmed the expression of this construct by measuring OD600 absorbance and calculated a maximum protein concentration of 3.79 ug/ml using a Bradford Assay.

![](https://static.igem.wiki/teams/5594/individualpages/wetlab/results/results-fig-2.avif)

Figure 2:

TPA to PCA pathway in E.coli

This construct in E.coli encodes a transporter system allowing TPA to enter E.coli and enzymes allowing for the breakdown of TPA into PCA. To ensure that the TPA transporter is on the cell before the production of TPA, two promoters were engineered into the construct: the T7 promoter (BBa\_I719005) and a constitutive promoter (BBa\_J23100). The T7 promoter is induced after the TPA transporters are synthesized. BBa\_K808011 (tphA1) is the gene that codes for the enzyme terephthalate dioxygenase reductase. In this construct, BBa\_K808012 (tphA2) and BBa\_K808013 (tphA3) work together, along with tphA1, to form the complex terephthalic acid 1,2-dioxygenase system (TERDOS). TERDOS catalyzes the reaction that degrades TPA. BBa\_K2013010 codes for the enzyme 1,2-dihydroxy-3,5-cyclohexadiene-1,4-dicarboxylate dehydrogenase (DCDDH) which decarboxylates the product of TERDOS to form PCA. This pathway of tphA1, tphA2, tphA3 and DCDDH are used due to its high efficiency in BL21 DE3 E.coli cell. The enzymes TPADO (tphA1, tphA2, tphB2) and DCDDH form a natural, sequential metabolic pathway in native TPA-degrading bacteria Comamonas sp. This feature allows those genes to have optimal heterologous expression, high catalytic efficiency, and proper protein assembly in E. Coli. Compared with other constructs also derived from native TPA- degrading bacteria (such as Ideonella sakaiensis and Rhodococcus jostii RHA1), the TPA degrading genes derived from Comamonas sp showed the highest efficiency (Li et al., 2024). By comparing the area under the peak from HPLC for cells transformed with this construct with WT E.coli cells, we showed that the TPA transporter successfully took in TPA into the cell.

![](https://static.igem.wiki/teams/5594/individualpages/wetlab/results/results-fig-3.avif)

Figure 3:

Theoretical pathway of PCA to Acetyl-Coa in E.coli

![](https://static.igem.wiki/teams/5594/individualpages/wetlab/results/results-fig-4.avif)

Figure 4:

Diagram showing the process of each PCA genes for degradation of PCA

This theoretical pathway in E.coli converts PCA into Acetyl-CoA and succinyl-CoA. The gene PCAK codes for the PCA transporter on E.coli that allows PCA to enter the E.coli cell. Figure 4 shows the function of each PCA gene. The gene PCAGH codes for the enzyme protocatechuate 3,4-dioxygenase, which is responsible for the ring-cleavage of PCA, forming Beta- carboxyl-cis-cis-muconate. PCAB codes for the enzyme 3-carboxy-cis,cis-muconate cycloisomerase which catalyzes anti cycloisomerization, leading to the formation of γ-carboxymuconolactone. BBa\_K2091002 (PCAC) codes for the enzyme γ-carboxymuconolactone decarboxylase which then, through decarboxylation, converts γ-carboxymuconolactone into Beta- ketoadipate enol-lactone. PCAD codes for the enzyme β-ketoadipate enol-lactone hydrolase which would catalyze a hydrolysis reaction that adds a water molecule on β-ketoadipate enol-lactone's lactone ring, forming β-ketoadipate. PCAIJ codes for the enzyme β-ketoadipate:succinyl-CoAtransferase, which forms Beta- ketoadipyl- CoA by adding a coenzyme A group on Beta- ketoadipate. PCAF codes for the enzyme β-ketoadipyl-CoA thiolase, which breaks the carbon-carbon bond in the middle of the β-ketoadipyl-CoA molecule to form succinyl- CoA and acetyl CoA. Acetyl-Coa would then go on to the next construct for further reactions. This pathway is efficient for acetyl-CoA production because they form a specialized, coordinated, and energetically favorable catabolic system for breaking down aromatic compounds directly into central metabolites. The enzymes in this pathway have high specificity for their substrates, minimizing side reactions and ensuring a smooth, efficient flow of carbon through the pathway (Buchan et al., 2000).

![](https://static.igem.wiki/teams/5594/individualpages/wetlab/results/results-fig-5.avif)

Figure 5:

Acetyl-Coa to PHB pathway

This construct in E.coli converts Acetyl-CoA into PHB then uses natural E.coli metabolic pathways to secrete the product out of the cell. phaC, phaA, and phaB come together to form the phaCAB operon. The phaCAB operon codes for an enzyme that converts acetyl-coa to PHB. Specifically, phaA codes for the enzyme Acetyl-CoA acetyltransferase that converts Acetyl-Coa into Acetoacetyl-Coa. phaB codes for the enzyme Acetoacetyl-Coa reductase which consumes NADPH as an energy source to convert Acetoacetyl-Coa into (R)-3-hydroxybutyryl-CoA. This is the reason why BBa\_K1674004 is added. BBa\_K1674004 is zwf gene which codes for the enzyme NADPH reductase that reduces NADP+ into NADPH. By adding the zwf gene into the construct, there will be a higher yield of NADPH which would result in a more efficient process of synthesizing PHB from Acetyl-Coa. phaC codes for the enzyme PHA synthase, which converts (R)-3-hydroxybutyryl-CoA into PHB. BBa\_K2560091 codes for Phasin-HIyA, a protein combining phasin—which binds electrostatically to intracellular PHB—with the C-terminal secretion signal from the HlyA toxin. The HlyA tag hijacks E. coli's type one secretion system, causing the bound phasin-PHB complex to be transported out of the cell, allowing PHB to be excreted out of the E.coli cell which removes the need for cell lysis.

![](https://static.igem.wiki/teams/5594/individualpages/wetlab/results/results-fig-6.avif)

Figure 6:

TPA to PHB synthesis pathway in P.putida cells

In P.putida KT2440 cells, we selected the Pm promoter which is coded by BBa\_K4757009 (Kernel does not show the proper symbol for this promoter). phaC, phaA and phaB form the same phaCAB operon used in E.coli cells, which converts Acetyl-Coa to PHB. Since P.putida can naturally metabolize TPA and break down TPA into Acetyl-Coa naturally, only the PhaCAB operon is needed for the final conversion to PHB from acetyl-CoA.BBa\_K1674004 encodes for NADPH reductase, which reduces NADP+ to NADPH, allowing for a higher concentration of NADPH in the system. This increased concentration of NADPH makes PHB synthesis more efficient, since phaB encodes Acetoacetyl-Coa reductase, which uses NADPH as an energy source. BBa\_K4728007 codes for phaF and has the same function as the Phasin- HIyA protein in the Acetyl-CoA to PHB pathway in E.coli, which is to secrete PHB out of the cell. Phasin-HIyA is not used in this construct because the gene would not be translated into the final protein in Pseudomonas cells.

![](https://static.igem.wiki/teams/5594/individualpages/wetlab/results/results-fig-7.avif)

Figure 7:

PHB to BHB pathway in E.coli cells

This construct in E.coli depolymerizes PHB into BHB. The system Includes an inducible promoter, RBS, coding sequence for PHAZ\_TALFU, linker, coding sequence for GFP, and a terminator. Once we add IPTG, the system produces PHAZ\_TALFU, which is a PHB depolymerase that catalyzes the hydrolysis of PHB into monomers of BHB, as well as GFP, which acts as a reporter. The linker will link the GFP molecule and BHB together, which can allow us to determine the levels of PHAZ\_TALFU, and relatively the concentrations of BHB, by detecting GFP. By measuring fluorescence using FLUOstar Omega microplate reader we confirmed that this construct successfully expresses PHAZ\_TALFU and synthesizes Polyhydroxybutyrate depolymerase. Using a fluorescein standard curve, it was also calculated that the highest concentration of Polyhydroxybutyrate depolymerase is shown to be 0.31 uM when 0.5 mM IPTG is induced for 16 hours.

# 1. Testing for the construct of PET to TPA and EG (Synthesis of Petase)

## Experimental Design

#### Construct Used:

![](https://static.igem.wiki/teams/5594/individualpages/wetlab/results/results-fig-real-8.avif)

Figure 8:

Construct of synthesis of PETase

#### Purpose

BBa\_K3478888 is the LCC- ICCG gene, which codes for the enzyme PETase that can degrade PET into TPA and EG. To test this construct, the TPA concentration will be tested after the cell is lysed.

## Procedure

The procedures for transforming plasmids that either encode the TPA transporter, TPA to PCA construct, PET to TPA, and EG construct are all identical. Our plasmids were all synthesized by GenScript. To transform the cell, we first prepared 250 µL of transformation solution. We then used a loop to transfer colonies of bacteria into the transformation solution. Then, we used another loop to transfer plasmid into the same solution and gently flick it to mix. The solution is then incubated on ice for 10 minutes, and after that transferred to a 42 degrees Celsius water bath for 50 seconds. After that, the tube is put back on ice for 2 minutes. Then, 250 µL of LB Broth was added into the tube, and 100 microliters of the solution was taken out from the tube and plated with a loop. The plate was incubated at 37 degrees Celsius overnight. 30 mL of LB + ampicillin and a colony of bacteria (from the plate using a loop) was then added into the falcon tube. The falcon tube is then incubated in a shaking incubator. The OD 600s are tested every 2 hours and when it reaches a maximum OD600, experiment Group Samples were induced with IPTG (0.1mM and 0.5mM) and a Control group of uninduced cells was also used for comparison. A Blank group containing Untransformed BL21 DE3 cells was also measured. After inducement, the samples are all centrifuged with 5000 rpm for 5 minutes. The supernatant is then taken out for Bradford Assay. The Bradford Assay Standard curve is generated under the Sangon Biotech’s Bradford Assay standard curve protocolhttps://store.sangon.com/productImage/DOC/C100530/C100530\_EN\_P.pdf.

## Results

|  | Absorbance (595 nm) |  |  |
| --- | --- | --- | --- |
| Group | 120 min | 180 min | 240 min |
| Blank 1 | 0 | 0 | N/A |
| Blank 2 | 0 | 0 | N/A |
| Blank 3 | 0 | 0 | N/A |
| 0.5 mM IPTG | 0.01 | 0.08 | 0.21 |
| 0.5 mM IPTG | 0 | 0.08 | 0.16 |
| 0.5 mM IPTG | 0.02 | 0.07 | 0.19 |
| 0.1 mM IPTG | 0 | 0.07 | 0.09 |
| 0.1 mM IPTG | 0 | 0.08 | 0.08 |
| 0.1 mM IPTG | 0 | 0.06 | 0.08 |
| 0.0 mM IPTG | 0 | 0.04 | 0.04 |
| 0.0 mM IPTG | 0 | 0.03 | 0.05 |
| 0.0 mM IPTG | 0 | 0.03 | 0.03 |

Table 1:

This table shows the absorbance of the samples over time under different IPTG concentrations and a wild type BL21DE3 E.coli cell as a negative. Each sample is repeated three times.

|  | Absorbance (595 nm) |  |  |
| --- | --- | --- | --- |
| Group | 120 min | 180 min | 240 min |
| Blank | 0 | 0 | N/A |
| 0.5 mM IPTG | 0.01 | 0.08 | 0.19 |
||  |  |  |  |
| --- | --- | --- | --- |
| 0.1 mM IPTG | 0 | 0.07 | 0.08 |
| 0.0 mM IPTG | 0 | 0.03 | 0.04 |

Table 2:

The standard curve for HPLC generated to determine the concentration of TPA in extracellular space with different area under the peak
This table shows the average absorption of each sample over different time and different IPTG concentration with a wild type BL21 DE3 E.coli cell.

![](https://static.igem.wiki/teams/5594/individualpages/wetlab/results/results-fig-real-9.avif)

Figure 9:

Line graph showing the Petase concentration (ug/ml) at different IPTG concentration over time

![](https://static.igem.wiki/teams/5594/individualpages/wetlab/results/results-fig-real-10.avif)

Figure 10:

This graph is the standard curve of Bradford Assay with an equation of y= 0.0501x

#### Calculations of Petase concentration under different time and IPTG concentration:

#### 120 min: Blank

0=0.0501x

x=0 ug/ml

0.5 mM IPTG-

=0.0501x

x=0.20 ug/ml

0.1 mM IPTG-

=0.0501x

x=0 ug/ml

0.0 mM IPTG-

=0.0501x

x=0 ug/ml

#### 180 min: Blank

0=0.0501x

x=0 ug/ml

0.5 mM IPTG-

0.08=0.0501x

x=1.60 ug/ml

0.1 mM IPTG-

0.07=0.0501x

x= 1.40 ug/ml

0.0 mM IPTG-

0.03=0.0501x

x= 0.60 ug/ml

#### 240 min: Blank

N/A

0.5 mM IPTG-

0.19= 0.0501x

x= 3.79 ug/ml

0.1 mM IPTG-

0.08=0.0501x

x= 1.60 ug/ml

0.0 mM IPTG-

0.04= 0.0501x

x= 0.80 ug/ml

|  | Petase concentration (ug/ml) |  |  |
| --- | --- | --- | --- |
| Group | 120 min | 180 min | 240 min |
| Blank | 0 | 0 | N/A |
| 0.5 mM IPTG | 0.2 | 1.6 | 3.79 |
||  |  |  |  |
| --- | --- | --- | --- |
| 0.1 mM IPTG | 0 | 1.4 | 1.6 |
| 0.0 mM IPTG | 0 | 0.6 | 0.8 |

Table 3:

This table shows the PETase concentration in ug/ml for each sample at each time

The PETase synthesized from our engineered E.coli cell has shown to be successfully synthesized and secreted out of the cell. The maximum OD600 level of 0.6 was reached after 240 minutes. From table 2 and figure 10, when the maximum OD600 of 0.6 is reached, the sample with 0.5 mM of IPTG induced has the highest absorbance of 0.19. This means the PETase concentration secreted out of the cell is highest when 0.5 mM of IPTG is induced. Bradford Assay was conducted according to the kit protocol described by Sangon Biotech. The standard curve generated and protein amount in ug/ml was determined as shown in figure 9. Using the standard curve generated from figure 10, the PETase concentration can be calculated in ug/ml. The highest PETase concentration is 3.79 ug/ml when 0.5 mM of IPTG is induced at maximum OD600 (0.6 at 240 minutes) shown in figure 9. There is also absorbance shown when the IPTG concentration is at 0.0 mM because T7 promoter is a fairly leaky promoter which means even without the use of an inducer, the T7 promoter still expresses the construct to a certain extent (Namdev et al., 2019).

### SDS Page:

The measured protein concentration can be further verified as Petase using SDS- Page. The SDS Page is conducted with two samples Control (Not transformed) versus Transformed. The samples are centrifuged, and its supernatant is extracted out. TCA precipitation protocol for concentrating extracellular proteins is used on the supernatants. TCA precipation is required to concentrate the secreted proteins to a detectable level as these proteins are typically very diluted. TCA is used to get 10-50x more concentrated protein.

### TCA Protocol:

1. Prepare TCA Solution:

* Add TCA to your culture supernatant to a final concentration of 10-20% (w/v)
* For example: Add 100 μL of 100% TCA to 900 μL supernatant for ~10% final concentration

2. Precipitate Proteins:

* Mix well and incubate on ice for 30 minutes to 2 hours
* Proteins will precipitate out of solution

3. Collect Precipitate:

* Centrifuge at 12,000-15,000 × g for 15 minutes at 4°C
* You should see a protein pellet at the bottom

4. Wash the Pellet:

* Remove supernatant carefully
* Add ice-cold acetone to wash the pellet (removes TCA and salts)
* Centrifuge again at 12,000 × g for 5 minutes at 4°C
* Repeat acetone wash 1-2 more times

5. Dry and Resuspend:

* Air dry the pellet for 5-10 minutes (until acetone evaporates)
* Resuspend in SDS-PAGE loading buffer (much smaller volume than original)

##### Destaining:

* Transfer the gel into a destaining solution. A common solution is 10% methanol and 10% acetic acid in water.
* Allow the gel to destain for 30 minutes to several hours with gentle rocking. You may need to change the destain solution a couple of times until the background is sufficiently reduced and the protein bands stand out clearly.

##### Rinsing:

* Once the background has been removed, rinse the gel with distilled water to remove any residual acids and methanol.

# 2. TPA transporter

![](https://static.igem.wiki/teams/5594/individualpages/wetlab/results/results-fig-real-11.avif)

Figure 11:

Construct synthesizing TPA transporter

### Purpose:

This is the construct of TPA transporter in E.coli. BBa\_K4728011 is the tpaK gene that codes for the TPA transporter. The TPA transporter allows TPA to enter the E.coli cell for further processes.

## Procedure

The transformation procedures for the cells are the same as the PET to TPA and EG construct, but the plasmid used is the plasmid that codes for TPA transporter. The experimental group is the cells with engineered plasmid of TPA transporter, while the control group is the untransformed cell (wild type BL21 DE3 E.coli cells). The cell is first grown to an OD600 reading of 0.6. Cells are then centrifuged with supernatant removed. Cells were resuspended in M9 minimal media. Experimental Group cells added to M9 media containing TPA (10mM) as the sole carbon source. Control Group Cells added to M9 media containing Glucose plus TPA (10mM) as carbon sources. Afterwards, 0.5 mM of IPTG is used to induce the experimental group only. HPLC is then used to test for the concentration of TPA in the media every 90 minutes.

## Results

|  | Area under the peak |  |  |
| --- | --- | --- | --- |
|  | 0 sec | 90 sec | 180 sec | 270 sec |
| Wild Type | 211.582 | 212.968 | 205.546 | 203.046 |
| Transformed Cells | 208.247 | 189.816 | 154.935 | 133.299 |

Table 4:

This table is the area under the peak from HPLC for both samples (wild type BL21 DE3 E.coli cell and transformed cell) at different time

![](https://static.igem.wiki/teams/5594/individualpages/wetlab/results/results-fig-real-12.avif)

Figure 12:

The standard curve for HPLC generated to determine the concentration of TPA in extracellular space with different area under the peak

![](https://static.igem.wiki/teams/5594/individualpages/wetlab/results/results-fig-real-13.avif)

Figure 13:

Line graph of the TPA concentration from HPLC for WT vs transformed samples.

### Calculations

#### Wild Type

0 sec:

Y=26.546x-58.272

211.582=26.546x-58.272

X=10.17mM of TPA

90 sec:

Y=26.546x-58.272

212.968=26.546x-58.272

X=10.22mM of TPA

180 sec:

Y=26.546x-58.272

205.546=26.546x-58.272

X=9.94 mM of TPA

270 sec:

Y=26.546x-58.272

203.046=26.546x-58.272

X=9.84 mM of TPA

#### Experimental Group

0 sec:

Y=26.546x-58.272

208.247=26.546x-58.272

X=10.04 mM of TPA

90 sec:

Y=26.546x-58.272

189.816=26.546x-58.272

X=9.35 mM of TPA

180 sec:

Y=26.546x-58.272

154.935=26.546x-58.272

X=8.03 mM of TPA

270 sec:

Y=26.546x-58.272

133.299=26.546x-58.272

X=7.22 mM of TPA

|  | TPA concentration (mM) |  |  |  |
| --- | --- | --- | --- | --- |
|  | 0 min | 90 min | 180 min | 270 min |
| Wild Type | 10.17 | 10.22 | 9.94 | 9.84 |
| Transformed Cells | 9.0 | 9.35 | 8.03 | 7.22 |

Table 5:

A table showing the concentration of TPA at each time for each sample

The TPA transporter from our experiment result has been shown to successfully take in TPA into the cell. As shown in Figure 13 and Table 3, there is a decrease in the area under the peak as the time increases for the transformed sample. The area under the peak of HPLC is a measure of the TPA concentration in the extracellular space of each sample. A decrease in the area under the peak means a decrease in the TPA concentration in the extracellular space. This means the TPA entered the cell via the TPA transporter which resulted in a decrease in TPA concentration in extracellular space. As shown in Figure 13, the area under the peak for the control group (untransformed cell) is approximately constant over time which means the TPA concentration in the extracellular space is constant. This means the TPA did not enter the wild type BL21 DE3 E.coli cell. By using the standard curve shown in figure 12, the actual concentration of TPA in the extracellular space at each time can be calculated as shown in the calculation section. Furthermore, at the fifth time stamp (360 sec), the amount of TPA concentration of the experiment group increased significantly – it was decided to end the experiment and attribute the increase to cell lysis and toxicity of TPA: these cells did not have metabolic pathways to use TPA.

# 3. PHB to BHB Pathway (Expression of PHAZ\_TALFU)

![](https://static.igem.wiki/teams/5594/individualpages/wetlab/results/results-fig-real-14.avif)

Figure 14:

Construct converts PHB into BHB

### Purpose

This construct contains PHAZ\_TALFU which codes for PHB depolymerase that can break down PHB into BHB which then links with GFP (BBa\_K2459011) by a linker (BBa\_K3286268) which allows us to use the measure of fluorescein to find the concentration of BHB synthesized by this construct. This can test the T7 expression system and confirm expression of recombinant proteins.

## Procedure

Transformation of BL21 DE3 E.coli cells with the PHB to BHB construct plasmid was done using the same cell transformation procedures that have been used for previous experiments. Four groups were prepared and tested: Wild Type (untransformed BL21 DE3 cells), uninduced transformed BL21 DE3 cells, induced with 0.5mM, induced with 0.1mM. Measurement of GFP expression was used to verify the expression of genes within the system. Under the T7 promoter. IPTG concentrations were used to induce and investigate expression levels. Absolute Fluorescence was measured and graphed. Additionally, MEF (molecules of equivalent fluorescein) was determined for each group using a standard curve. We carried out a calibration with fluorescein (from the distribution kit). We followed the standard protocol as described by the iGEM measurement committee: https://www.protocols.io/view/calibration-protocol-plate-reader-fluorescence-cal-x54v986dpl3e/v3. Fluorescence was measured using FLUOstar Omega microplate reader.

## Results

| 12 hours |  |  |  |  |
| --- | --- | --- | --- | --- |
|  | Fluorescence |  |  |  |
|  | Sample 1 | Sample 2 | Sample 3 | Average |
| Wild Type (untransformed BL21 DE3 E.coli cells) | 186 | 201 | 203 | 197 |
||  |  |  |  |  |
| --- | --- | --- | --- | --- |
| Uninduced (transformed BL21 DE3 cell) | 302 | 426 | 412 | 380 |
| 0.5 mM IPTG | 702 | 683 | 747 | 711 |
| 0.1 mM IPTG | 661 | 641 | 678 | 660 |

| 13 hours |  |  |  |  |
| --- | --- | --- | --- | --- |
|  | Fluorescence |  |  |  |
|  | Sample 1 | Sample 2 | Sample 3 | Average |
| Wild Type (untransformed BL21 DE3 E.coli cells) | N/A | N/A | N/A | N/A |
||  |  |  |  |  |
| --- | --- | --- | --- | --- |
| Uninduced (transformed BL21 DE3 cell) | 438 | 441 | 424 | 434 |
| Induced 0.5 mM | 742 | 798 | 807 | 782 |
| Induced 0.1 mM | 716 | 709 | 724 | 716 |

| 14 hours |  |  |  |  |
| --- | --- | --- | --- | --- |
|  | Fluorescence |  |  |  |
|  | Sample 1 | Sample 2 | Sample 3 | Average |
| Wild Type (untransformed BL21 DE3 E.coli cells) | 218 | 221 | 222 | 220 |
||  |  |  |  |  |
| --- | --- | --- | --- | --- |
| Uninduced (transformed BL21 DE3 cell) | 477 | 484 | 432 | 464 |
| Induced 0.5 mM | 898 | 892 | 899 | 896 |
| Induced 0.1 mM | 774 | 771 | 836 | 794 |

| 15 hours |  |  |  |  |
| --- | --- | --- | --- | --- |
|  | Fluorescence |  |  |  |
|  | Sample 1 | Sample 2 | Sample 3 | Average |
| Wild Type (untransformed BL21 DE3 E.coli cells) | N/A | N/A | N/A | N/A |
||  |  |  |  |  |
| --- | --- | --- | --- | --- |
| Uninduced (transformed BL21 DE3 cell) | 514 | 520 | 521 | 518 |
| Induced 0.5 mM | 944 | 932 | 978 | 951 |
| Induced 0.1 mM | 891 | 852 | 911 | 885 |

| 16 hours |  |  |  |  |
| --- | --- | --- | --- | --- |
|  | Fluorescence |  |  |  |
|  | Sample 1 | Sample 2 | Sample 3 | Average |
| Wild Type (untransformed BL21 DE3 E.coli cells) | 228 | 220 | 219 | 334 |
||  |  |  |  |  |
| --- | --- | --- | --- | --- |
| Uninduced (transformed BL21 DE3 cell) | 679 | 673 | 667 | 673 |
| Induced 0.5 mM | 1015 | 988 | 979 | 994 |
| Induced 0.1 mM | 920 | 917 | 912 | 916 |

Table 6:

Fluorescence reading of each group (wild type, uninduced, 0.5 mM IPTG, 0.1mM IPTG) over time with three samples tested for each group at each time period

|  | Fluorescence |  |  |  |  |
| --- | --- | --- | --- | --- | --- |
|  | 12 hours | 13 hours | 14 hours | 15 hours | 16 hours |
| Wild Type (untransformed BL21 DE3 E.coli cells) | 197 | N/A | 220 | N/A | 334 |
||  |  |  |  |  |  |
| --- | --- | --- | --- | --- | --- |
| Uninduced (transformed BL21 DE3 cell) | 380 | 434 | 464 | 518 | 673 |
| Induced 0.5 mM | 711 | 782 | 896 | 951 | 994 |
| Induced 0.1 mM | 660 | 716 | 794 | 885 | 916 |

Table 7:

This table shows the average fluorescence at each time and each group for all three samples.

![](https://static.igem.wiki/teams/5594/individualpages/wetlab/results/results-fig-real-15.avif)

Figure 15:

Fluorescein Standard Curve generated using data from Figure 17

![](https://static.igem.wiki/teams/5594/individualpages/wetlab/results/results-fig-real-16.avif)

Figure 16:

Graph showing the PHB depolymerase concentration (uM) over time for each group (wild type, uninduced, induced 0.5 mM IPTG, induced 0.1 mM IPTG)

![](https://static.igem.wiki/teams/5594/individualpages/wetlab/results/results-fig-real-17.avif)

Figure 17:

Table showing the data used to generate the Fluorescein Standard Curve

### Calculations

#### 12 hours

Wild Type:

197=3156.2x+14.7

X=0.06 uM

Uninduced:

380=3156.2x+14.7

X=0.12 uM

Induced 0.5 mM IPTG:

711= 3156.2x+14.7

X=0.22 uM

Induced 0.1 mM IPTG:

660=3156.2x+ 14.7

X=0.20 uM

#### 13 hours

Wild Type:

N/A

Uninduced:

434=3156.2x+14.7

X=0.13 uM

Induced 0.5 mM IPTG:

782= 3156.2x+14.7

X=0.24 uM

Induced 0.1 mM IPTG:

716= 3156.2x+14.7

X=0.22 uM

#### 14 hours

Wild Type:

220= 3156.2x+14.7

X=0.07 uM

Uninduced:

464= 3156.2x+14.7

X=0.14 uM

Induced 0.5 mM IPTG:

896= 3156.2x+14.7

X=0.28 uM

Induced 0.1 mM IPTG:

794= 3156.2x+14.7

X=0.25 uM

#### 15 hours

Wild Type:

N/A

Uninduced:

518=3156.2x+14.7

X=0.16 uM

Induced 0.5 mM IPTG:

951= 3156.2x+14.7

X=0.30 uM

Induced 0.1 mM IPTG:

881= 3156.2x+14.7

X=0.27 uM

#### 16 hours

Wild Type:

334= 3156.2x+14.7

X=0.10 uM

Uninduced:

673= 3156.2x+14.7

X=0.21 uM

Induced 0.5 mM IPTG:

994= 3156.2x+14.7

X=0.31 uM

Induced 0.1 mM IPTG:

916= 3156.2x+14.7

X=0.29 uM

|  | PHB Depolymerase Concentration (uM) |  |  |  |
| --- | --- | --- | --- | --- |
|  | 12 hours | 13 hours | 14 hours | 15 hours | 16 hours |
| Wild Type (untransformed BL21 DE3 E.coli cells) | 0.06 | N/A | 0.07 | N/A | 0.10 |
| Uninduced (transformed BL21 DE3 cell) | 0.12 | 0.13 | 0.14 | 0.16 | 0.21 |
||  |  |  |  |  |  |
| --- | --- | --- | --- | --- | --- |
| UInduced 0.5 mM | 0.22 | 0.24 | 0.28 | 0.30 | 0.31 |
| UInduced 0.1 mM | 0.20 | 0.22 | 0.25 | 0.27 | 0.29 |

Table 7:

This table shows the PHB Depolymerase Concentration in (uM) for each sample at each time.

From the experiments, this construct has been proven to successfully express PHAZ\_TALFU and synthesize Polyhydroxybutyrate depolymerase. The addition of GFP allows us to measure fluorescence as an indicator for the concentration of Polyhydroxybutyrate depolymerase. As shown in figure 16, the highest concentration of Polyhydroxybutyrate depolymerase is shown to be 0.31 uM when 0.5 mM IPTG is induced for 16 hours and with an induction of 0.5 mM IPTG shows the highest concentration of fluorescence out of all other experimental groups. This means induction with 0.5 mM IPTG yields the highest concentration of Polyhydroxybutyrate depolymerase.

# 4. Transformation of Chromoprotein Parts

We first designed parts that included each of the chromoprotein components as described by the 2011 Uppsala iGEM team's collection:[http://2011.igem.org/Team:Uppsala-Sweden/2011](%E2%80%AFhttp%3A//2011.igem.org/Team%3AUppsala-Sweden/2011)

Six different colors were chosen to form the palette for our agar art. These chromoproteins are expressed as proteins inside cells, typically used as reporters in synthetic biology, and are coded for by the following parts:

| Name | Part |
| --- | --- |
| Eforred | [https://parts.igem.org/Part:BBa\_K1073022](https://parts.igem.org/Part%3ABBa_K1073022) |
| AmilGFP | [https://parts.igem.org/wiki/index.php/Part:BBa\_K1073024](https://parts.igem.org/wiki/index.php/Part%3ABBa_K1073024%20) |
| Aeblue | [https://parts.igem.org/wiki/index.php/Part:BBa\_K1073020](https://parts.igem.org/wiki/index.php/Part%3ABBa_K1073020) |
||  |  |
| --- | --- |
| TsPurple | [https://parts.igem.org/Part:BBa\_K1033906](https://parts.igem.org/Part%3ABBa_K1033906%20) |
| AmilCP | [https://parts.igem.org/Part:BBa\_K592009](https://parts.igem.org/Part%3ABBa_K592009%20) |
| Cjblue | [https://parts.igem.org/Part:BBa\_K592011](https://parts.igem.org/Part%3ABBa_K592011%20) |

We placed the coding sequences for the chromoproteins under the control of the pBAD promoter and cloned them into a plasmid containing ampicillin resistance. We selected the pET3a plasmid to achieve strong expression of the chromoproteins, ensuring rich colors for our agar art.

 Transformation was carried out using the heat shock method as described at:[https://www.addgene.org/protocols/bacterial-transformation/](%E2%80%AFhttps%3A//www.addgene.org/protocols/bacterial-transformation/) Cells were grown overnight on selection plates containing ampicillin.

![](https://static.igem.wiki/teams/5594/individualpages/wetlab/results/results-agar1.avif)

Colonies that grew on the selection plates were inoculated into liquid LB broth containing ampicillin and grown for 12 hours before being transferred onto plates containing LB agar, ampicillin, and arabinose. Results are shown below:

![](https://static.igem.wiki/teams/5594/individualpages/wetlab/results/results-agar2.avif)

![](https://static.igem.wiki/teams/5594/individualpages/wetlab/results/results-agar3.avif)

Agar art could now be conducted using our transformed cells engineered to express chromoproteins in the presence of arabinose. Large square plates (9 cm × 9 cm) were prepared with LB agar containing arabinose and ampicillin to ensure chromoprotein expression. Some results are shown below:

![](https://static.igem.wiki/teams/5594/individualpages/wetlab/results/results-agar4.avif)

![](https://static.igem.wiki/teams/5594/individualpages/wetlab/results/results-agar5.avif)

![](https://static.igem.wiki/teams/5594/individualpages/wetlab/results/results-agar-6.avif)

---

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