iGEM 2021 — Team UGM_Indonesia

[![](https://static.igem.org/mediawiki/2021/8/8b/HQ_page_logo.jpg)](https://2021.igem.org)

# Team:UGM Indonesia/Notebook

<!DOCTYPE html>

Notebook

![](https://static.igem.org/mediawiki/2021/f/f2/T--UGM_Indonesia--img--project-logo.png)

* [Home](https://2021.igem.org/Team%3AUGM_Indonesia)
* Project
  + [Description](https://2021.igem.org/Team%3AUGM_Indonesia/Description)
  + [Design](https://2021.igem.org/Team%3AUGM_Indonesia/Design)
  + [Engineering](https://2021.igem.org/Team%3AUGM_Indonesia/Engineering)
  + [Safety](https://2021.igem.org/Team%3AUGM_Indonesia/Safety)
  + [Contribution](https://2021.igem.org/Team%3AUGM_Indonesia/Contribution)
* Wet Lab
  + [Parts](https://2021.igem.org/Team%3AUGM_Indonesia/Parts)
  + [Experiments](https://2021.igem.org/Team%3AUGM_Indonesia/Experiments)
  + [Results](https://2021.igem.org/Team%3AUGM_Indonesia/Results)
  + [Notebook](https://2021.igem.org/Team%3AUGM_Indonesia/Notebook)
* Dry Lab
  + [Model](https://2021.igem.org/Team%3AUGM_Indonesia/Model)
  + [Bioreactor](https://2021.igem.org/Team%3AUGM_Indonesia/Bioreactor)
* Human Practices
  + [Human Practices](https://2021.igem.org/Team%3AUGM_Indonesia/Human_Practices)
  + [Integrated Human Practices](https://2021.igem.org/Team%3AUGM_Indonesia/IHP)
  + [Proposed Implementation](https://2021.igem.org/Team%3AUGM_Indonesia/Implementation)
  + [Education and Communication](https://2021.igem.org/Team%3AUGM_Indonesia/Communication)
  + [Education and Public Engagement](https://2021.igem.org/Team%3AUGM_Indonesia/Education)
  + [Entrepreneurship](https://2021.igem.org/Team%3AUGM_Indonesia/Entrepreneurship)
  + [Sustainable Development Impact](https://2021.igem.org/Team%3AUGM_Indonesia/Sustainable)
* Team
  + [Members](https://2021.igem.org/Team%3AUGM_Indonesia/Team)
  + [Attributions](https://2021.igem.org/Team%3AUGM_Indonesia/Attributions)
  + [Collaborations](https://2021.igem.org/Team%3AUGM_Indonesia/Collaborations)
  + [Partnership](https://2021.igem.org/Team%3AUGM_Indonesia/Partnership)
* Medals
  + [Medals](https://2021.igem.org/Team%3AUGM_Indonesia/Medals)

# Notebook

# Notebook

# Notebook

[Learn More](#main-content)

* [Notebook](#notebook)

Synthetic biology cannot be performed without the role of wet lab experiments as the proof of our proposed engineering design. Here, we provide the Benchling notebook that contains all of our wet lab experiments and results. Click
[here](https://static.igem.org/mediawiki/2021/8/89/T--UGM_Indonesia--others--notebook-lab-work.pdf)
!

![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/1/13/T--UGM_Indonesia--img--sponsor-ugm.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/0/03/T--UGM_Indonesia--img--sponsor-genscript.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/1/10/T--UGM_Indonesia--img--sponsor-rentokill.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/4/44/T--UGM_Indonesia--img--sponsor-geneious.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/2/28/T--UGM_Indonesia--img--sponsor-its.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/d/df/T--UGM_Indonesia--img--sponsor-twistbio.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/7/7a/T--UGM_Indonesia--img--sponsor-idt.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/6/67/T--UGM_Indonesia--img--sponsor-biotek.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/6/65/T--UGM_Indonesia--img--sponsor-biology.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/3/3c/T--UGM_Indonesia--img--sponsor-agriculture.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/1/1f/T--UGM_Indonesia--img--sponsor-pharmacy.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/2/2c/T--UGM_Indonesia--img--sponsor-engineering.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/f/f3/T--UGM_Indonesia--img--sponsor-kkmk.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/9/9e/T--UGM_Indonesia--img--sponsor-feb.png)

![Universitas Gadjah Mada Logo](https://static.igem.org/mediawiki/2021/f/f1/T--UGM_Indonesia--img--logo-ugm-white.png)
![iGEM UGM 2021 Logo](https://static.igem.org/mediawiki/2021/0/0b/T--UGM_Indonesia--img--logo-igem-ugm-white.png)

##### iGEM UGM

Bulaksumur F11, Caturtunggal, Kecamatan Depok, Kabupaten Sleman, Daerah Istimewa Yogyakarta, Indonesia 55281

igemugm@gmail.com

#### Get in Touch!

All content on this wiki is available under the [Creative Commons Attribution 4.0 license](https://creativecommons.org/licenses/by/4.0/) (or any later version).

[![](https://static.igem.org/mediawiki/2021/8/8b/HQ_page_logo.jpg)](https://2021.igem.org)

# Team:UGM Indonesia/Engineering

<!DOCTYPE html>

Engineering

![](https://static.igem.org/mediawiki/2021/f/f2/T--UGM_Indonesia--img--project-logo.png)

* [Home](https://2021.igem.org/Team%3AUGM_Indonesia)
* Project
  + [Description](https://2021.igem.org/Team%3AUGM_Indonesia/Description)
  + [Design](https://2021.igem.org/Team%3AUGM_Indonesia/Design)
  + [Engineering](https://2021.igem.org/Team%3AUGM_Indonesia/Engineering)
  + [Safety](https://2021.igem.org/Team%3AUGM_Indonesia/Safety)
  + [Contribution](https://2021.igem.org/Team%3AUGM_Indonesia/Contribution)
* Wet Lab
  + [Parts](https://2021.igem.org/Team%3AUGM_Indonesia/Parts)
  + [Experiments](https://2021.igem.org/Team%3AUGM_Indonesia/Experiments)
  + [Results](https://2021.igem.org/Team%3AUGM_Indonesia/Results)
  + [Notebook](https://2021.igem.org/Team%3AUGM_Indonesia/Notebook)
* Dry Lab
  + [Model](https://2021.igem.org/Team%3AUGM_Indonesia/Model)
  + [Bioreactor](https://2021.igem.org/Team%3AUGM_Indonesia/Bioreactor)
* Human Practices
  + [Human Practices](https://2021.igem.org/Team%3AUGM_Indonesia/Human_Practices)
  + [Integrated Human Practices](https://2021.igem.org/Team%3AUGM_Indonesia/IHP)
  + [Proposed Implementation](https://2021.igem.org/Team%3AUGM_Indonesia/Implementation)
  + [Education and Communication](https://2021.igem.org/Team%3AUGM_Indonesia/Communication)
  + [Education and Public Engagement](https://2021.igem.org/Team%3AUGM_Indonesia/Education)
  + [Entrepreneurship](https://2021.igem.org/Team%3AUGM_Indonesia/Entrepreneurship)
  + [Sustainable Development Impact](https://2021.igem.org/Team%3AUGM_Indonesia/Sustainable)
* Team
  + [Members](https://2021.igem.org/Team%3AUGM_Indonesia/Team)
  + [Attributions](https://2021.igem.org/Team%3AUGM_Indonesia/Attributions)
  + [Collaborations](https://2021.igem.org/Team%3AUGM_Indonesia/Collaborations)
  + [Partnership](https://2021.igem.org/Team%3AUGM_Indonesia/Partnership)
* Medals
  + [Medals](https://2021.igem.org/Team%3AUGM_Indonesia/Medals)

# Engineering

# Engineering

# Engineering

[Learn More](#main-content)

* [HCN-regulating System](#hcn-production)
* [Gene knockout for enhancing cyanide production flux](#genome-scale)
* [Pyrite Dissolution Bioreactor](#pyrite)
* [References](#references)

Our main goal is to create a feasible on-off system of the cyanide production and degradation according to either the presence or absence of arabinose. This page displays three engineering cycles; i.e., cyanide production, cyanide degradation, and arabinose conversion. Afterwards, an engineering cycle about the Auviola on-off system is performed to associate the aforementioned three cycles. An engineering cycle about the bioreactor is also demonstrated as the implementation of our Auviola system.

#### HCN-regulating System

![engineering-hcn](https://static.igem.org/mediawiki/2021/b/be/T--UGM_Indonesia--img--engineering-hcn.png)

##### Research & Imagine

###### What are the properties of HCN production in C. violaceum?

The HCN synthase, or also known as glycine dehydrogenase, is an enzyme that facilitates the conversion of an amino acid glycine into cyanide.1 This enzyme is a heterotrimeric protein as encoded by a cluster of three genes called hcnABC operon. This enzyme belongs to the oxidoreductase class as it oxidizes the amine (CH-NH2) functional group into imine (C=NH) and consecutively cleaves the molecule into HCN and carbon dioxide (CO2).2

###### What are some concerns to be considered?

The resulted cyanide species were designed to dissolve the gold into the soluble coordination compound of (NaAu(CN)2) through the reaction below:

4Au + 8NaCN + O2 + 2H2O 4(NaAu(CN)2) + 4NaOH1

According to previous study, the gold leaching process requires HCN compounds with concentration of 600 mg/L.2 On the other hand, a wild-type of C. violaceum was previously studied to produce 0.71 - 16 micromoles/mL which nearly equals to 19 - 432 of HCN in 8 hours.3 Therefore, an optimization of produced HCN concentration should be conducted to achieve an effective gold leaching process.

###### What are the types of regulators tested in C. violaceum?

Two of several regulator genes have tested in C. violaceum are araC and tetR.4 The araC works dependably to arabinose level which acts as both an activator in the presence of arabinose and a repressor in the absence of arabinose.5 A PBAD is one of the inducible promoters presented in C. violaceum and regulated by the araC.6 On the other hand, tetR acts as a repressor and normally play a role in tetracycline resistance with PTET promoter.7

,8

##### Design

###### Wetlab work: HCN Production

Our strategies for improving cyanide metabolism in the cells are to increase the accumulation of HCN, hydrolysis of HCN, and L-arabinose converter. In this study, the proposed design for increasing HCN production has been achieved. The principle behind this system is overexpression of hcnABC gene encoding cyanide synthase, an enzyme that is responsible for HCN synthesis, by addition of L-arabinose-induced pBAD-AraC regulon. The genetic circuit for this study is written in the
[Design](https://2021.igem.org/Team%3AUGM_Indonesia/Design)
page. At first, we were focusing on the first plasmid construction for the HCN production. To achieve this goal, several standard Biobrick parts as well as the hcnABC operon was required. Some standard parts that we use are listed below:

1. BBa\_K808000 (AraC-pBAD)
2. BBa\_B0015 (double terminator)
3. BBa\_B0034m (strong RBS)

The hcnABC operon as the main insert, were obtained through gene synthesis from Twist Bioscience. Subsequently, the plasmid map was created to determine the overall gene construction into the pSB1C3 vector. Benchling application system was used to design the circuit, particularly the HCN production plasmid (Kindly visit our
[Results](https://2021.igem.org/Team%3AUGM_Indonesia/Results)
page for our plasmid construct!).

We used AraC-pBAD derived from BBa\_K1602055 to regulate the hcnABC operon. We modified the hcnABC operon by adding RBS before each gene (hcnA, hcnB, hcnC) and also double terminator B0015. The hcnB and hcnC genes have a high percentage of GC content so we faced some problems to synthesize it. Thus, we altered the hcnB gene sequence to reduce the GC content and to remove some illegal sites. We also altered some bases in hcnC gene to remove the illegal site. For a detailed description of the construction, please visit our
[Design](https://2021.igem.org/Team%3AUGM_Indonesia/Design)
page. The recombinant plasmid transformed was verified through colony PCR and the inserted parts were confirmed by sequencing analysis.

A Kinetic modelling for demonstrating an overexpression of cyanide was performed in Tellurium. This modelling used several parameters obtained from literature. In addition, genome-scale modelling was performed to optimize the metabolic flux of *C. violaceum* to achieve optimal cyanide.

###### Drylab work: Kinetic Modelling

Beside the wet lab, we also perform dry lab analysis to model the HCN production, HCN degradation, and L-Arabinose isomerase in engineered *C. violaceum*. We use kinetic modelling approach to perform this analysis.

Kinetic modelling of metabolic pathways is important for predicting the output of a metabolic process, and to understand what type of modification should be carried out if the output is not desirable. For our model, the complete equations are explained in the
[Model](https://2021.igem.org/Team%3AUGM_Indonesia/Model)
page. We collected most of our parameters from research papers and past iGEM team modelling.

##### Build

###### Wetlab work: HCN Production

After we went through the design phase, we started to conduct our project at the Biotechnology Laboratory of Inter-University Center in Universitas Gadjah Mada. We ordered hcnA, hcnB, and hcnC sequences from Twist Bioscience. The sequences were referred to the genome of *Chromobacterium violaceum* ATCC 12472 (NCBI: GenBank: AE016825.1).

To meet the BioBrick standard, we altered some of the sequences i.e., hcnB and hcnC, to reduce the GC content and remove the illegal sites. However, Twist Bioscience reported a problem in synthesizing the hcnC gene, thus the hcnC synthesize failed. Thus, we isolated the hcnC gene using PCR from the genome of C. violaceum ATCC 12472 and removed an illegal site inside the sequence using overlap PCR (Phusion polymerase) (see
[Results](https://2021.igem.org/Team%3AUGM_Indonesia/Results)
page table 1, no. 7,8, and 9). The assembly of plasmid backbone (pSB1C3), AraC-pBAD (BBa\_ K1602055), RBS (BBa\_B0034m), hcnABC operon, and double terminator (BBa\_B0015) were done using Gibson Assembly. The assembled constructs were then transformed into two strains of E. coli, BL21(DE3) and DH5α using standard heat shock protocol. The screening of transformats were selected on LB agar supplemented with Chloramphenicol for both strains.

###### Drylab work: Kinetic Modelling

The equations needed for modelling gold cyanidation are explained in our
[Model](https://2021.igem.org/Team%3AUGM_Indonesia/Model)
page. We were utilizing python in Jupyter with the Tellurium package for most of our model, except for Au and CN interaction.

| Parameter | Description | Value | Units | Source |
| --- | --- | --- | --- | --- |
| A0 | Product concentration (grams/liter) | 1 x 10-5 | M | [[9]](#reference-9) |
| A1 | Substrate concentration (grams/liter) | 1 x 10-5 | M | [[10]](#reference-10) |
| kdiff | Feed substrate concentration (grams/liter) | 7 x 10-18 | Mole/cell/30 mins | [[10]](#reference-10) |
| k1 | Rate of cell or biomass growth (grams/liter/hr) | 1.2 x 10-4 | s-1 | [[11]](#reference-11) |
| k2 | Rate of product formation (grams/liter/hr) | 1.2 x 10-4 | s-1 | [[11]](#reference-11) |
| \gamma\_1 | Product yield coefficient | 1.49 x 10-3 | min-1 | [[12]](#reference-12) |
| \gamma\_m | Rate of mRNA degradation (in general) | 1.7 x 10-3 | s-1 | [[13]](#reference-13) |
| \gamma\_p , \gamma\_E | Rate of large organic molecule degradation (assumed to have the same value) | 5.6 x 10-5 | s-1 | [[13]](#reference-13) |
| , \gamma\_A1 |  |  |  |  |
| kA1 | forward reaction rate | 1.2 x 10-4 | s-1 |  |
| kA2 | reverse reaction rate | 1.2 x 10-4 | s-1 |  |
| kcat1 | Rate of Rhodanese-S2O3 complex synthesis | 48 | s-1 | [[14]](#reference-14) |
| kcat2 | Rate of thiocyanate (SCN) biosynthesis | 55 | s-1 | [[14]](#reference-14) |
| kf1 | Rate of Li-A1 – Arabinose complex formation | 1.2 x 10-4 | s-1 | [[15]](#reference-15) |
| kr1 | Rate of Li-A1 – Arabinose complex degradation | 1.2 x 10-4 | s-1 | [[15]](#reference-15) |
| kcatR | Rate of L-ribulose catalytic formation | 8.167 | s-1 | [[15]](#reference-15) |

Some of the kinetic constant cannot be found on any research paper or open source database that is available on the internet. Thus, we used the value of similar parameter(s).

##### Test

###### Wetlab work: HCN Production

The resulting gene constructs were transformed into two chassisses and verified by colony PCR using VF2 VR primers. After the colony PCR and electrophoresis, the expected bands were incorrect in size and unobtainable. Our amplified insert using VF2 VR primers should be around 4600 bp, yet we merely obtain approximately 3000 bp band. On the upper side of some bands, ColA. There were thin bands of which the sizes are over 3000 bp, which indicated that the desirable construct was inserted to the chassis. Therefore, we subcultured the ColA colony to LB broth media supplemented with Chloramphenicol overnight for plasmid isolation (check the
[Results](https://2021.igem.org/Team%3AUGM_Indonesia/Results)
page for plasmid isolation result). For further confirmation, we send our isolated plasmid for sequencing. Now we are still waiting for the result of sequencing and we will update and report the result by the time we receive it.

###### Drylab work: Kinetic Modelling

The graph below shows concentration (M) vs time (second).

![engineering-hcn-regulating-1](https://static.igem.org/mediawiki/2021/8/8e/T--UGM_Indonesia--img--engineering-hcn-regulating-1.jpg)

##### Learn

###### Wetlab work: HCN Production

It was such a challenge for us to construct the whole operon with the size over 4000 bp with high GC content. A more robust PCR method such as an adjustable KOD with high-fidelity PCR master mix kit is necessary to increase the PCR product and avoid point mutation that might happen in the amplified product.

###### Drylab work: Kinetic Modelling

We can learn that rhodanese was produced instantly, then the concentration of HCN decreased rapidly. The maximum speed of gold cyanidation only lasts briefly, less than 5 minutes.
Biohydrometallurgy method is favored in mineral processing field due to their ability to extract low-concentrated ore. With this kind of trend, it is almost impossible to gain a feasible gold extraction yield. In lab experiments, most bioleaching processes managed to attain large mineral yield in laboratory experiments. This modelling might be not reflecting the real conditions of the bioleaching process.

##### Design

###### Drylab work: Kinetic Modelling

We need to reconsider some of the parameters, especially those based on assumption. Rate of large organic molecule degradation is one of the main examples. There are 2 large organic molecules that are involved in this modelling, protein (enzyme) and monosaccharide. We need to separate the decay rate of protein and monosaccharide.
SCN formation constant also needs to be changed. Due to larger scale use and relatively dynamic environment, we assumed that the collision rate would be significantly slower. Therefore, the constant also becomes lower.
Rhodanese activates almost simultaneously after HCN hits its highest concentration, hence we need to set a starting point to delay rhodanese synthesis. The starting point will be based on L-arabinose concentration.

##### Build

###### Drylab work: Kinetic Modelling

The parameter that we consider to be revised are:

| Parameter | Description | Value | Units | Source |
| --- | --- | --- | --- | --- |
| \gamma\_A1 | Rate of L-arabinose degradation | 3.46e x 10-5 | s-1 | [[16]](#reference-16) |
| p | Rhodanese synthesis starting point | 50% of initial L-arabinose concentration | M |  |
| kcat2 | Rate of thiocyanate (SCN) biosynthesis | 5.5 | s-1 |  |

##### Test

###### Drylab work: Kinetic Modelling

The results of modelling using those parameters are:

![engineering-hcn-regulating-2](https://static.igem.org/mediawiki/2021/b/b9/T--UGM_Indonesia--img--engineering-hcn-regulating-2.jpg)

##### Learn

###### Drylab work: Kinetic Modelling

The HCN concentration reduction becomes less steep, thus gold cyanidation could be more efficient. It will prolong the almost optimum gold leaching period and surely increase the potential gold yield. Although we achieved desirable results through modelling, further laboratory experiments also needed to verify our model and obtain more realistic results. Large scale and pilot testing are also required for industrial application.

#### Genome Scale Metabolic Model: Gene knockout for enhancing the flux of cyanide production pathway

![engineering-genome-scale](https://static.igem.org/mediawiki/2021/1/11/T--UGM_Indonesia--img--engineering-genome-scale.png)

##### Design

###### How to enhance cyanide production?

Our idea was to perform the Genome Scale Model (GEMs) for a knockout prediction and flux analysis to optimize the cyanide production. The output for this model were production envelope which compares the metabolic map between the knockout mutant and wild type as well as to illustrate the flux uplift to the cyanide production pathway. We use BiGG Model database (<http://bigg.ucsd.edu>),17KEGG metabolic pathway (<https://www.genome.jp/kegg/pathway/>),18and Escher (<https://escher.github.io/#/>),19to confirm and simulate the pathway.

To perform the knockout prediction model, we use stochastic and deterministic approaches. Data resource that we used was the SBML model with XML language and Escher map which used JSON language. We carried out the engineering, simulation, and model alteration process using Jupyter Notebook and Jupyter widget which were provided in the Escher module. In general, the GEMs implementation used a particular module in Python which related to its task such as Escher, Cameo, and Cobra. These modules have a good documentation which enables us to understand its usage in either class or the methods.

Tay et al., (2013) once performed a comparative proteome analysis through cyanogenesis in C. violaceum and established the overview of cyanogenesis pathway.20On the other hand, Benarjee et al. (2019) also did the GEMs to C. violaceum, yet merely to describe and identify NAD+ recycling.21In our project, we updated the model and metabolic map from Benarjee et al. (2018) with the adaptation of cyanogenesis pathway that have been published by Tay et al. (2013).20

,21

After updating the model and metabolic map, we try to knockout the prediction gene using OptGene and OPTKnock.22

,23

These approaches were recommended to us by our instructor, Mr. Matin Nuhamunada. The results of this model were expected to illustrate the metabolic flux shiftment to cyanide production through gene knockout process.

##### Build

We used a model and map file from Banerjee et al. (2019) with some modification. Curation is still needed to match the reactions and metabolites IDs between the map and the model. We found that there are 32 reactions with some IDs mismatch between the Escher map and the model, three ‘double’ reactions, and two metabolites which should be curated. After that, we started to fix the IDs in the model. Following that, we had our discussion with our instructor, Mr. Matin Nuhamunada who helped us to evaluate and fix the model. In addition to the model, we also modified the metabolic map. We manually added some reactions in the cyanide production pathway to the metabolic map using the Escher module, because at the beginning it still lacks the cyanide production pathway. For further detail, please visit
[Model: Genome Scale Metabolic Model](https://2021.igem.org/Team%3AUGM_Indonesia/Model)
.

##### Test

We performed a phenotypic phase plane to show us a trade-off between our target (in this case cyanide production) and the biomass of C. violaceum. We also implemented the OptGene and OptKnock approaches from Cameo to predict the gene knockouts for enhancing the cyanide production. Based on the OptGene and OptKnock gene knockout result, we then analysed the reaction flux of the metabolic maps (Escher map) between the wild type and knockout mutant of C. violaceum, especially in cyanide production pathway. For further detail of our test result, please visit
[Model: Genome Scale Metabolic Model](https://2021.igem.org/Team%3AUGM_Indonesia/Model)
.

##### Learn

We found some difficulties due to the limited solution from OptGene and OptKnock. Some examples from the knockout prediction, especially which mentioned in <https://cameo.bio/05-predict-gene-knockout-strategies.html>were merely discussed and model the exchange reaction as the target,22

,23

in fact we did not use exchange reaction in our model. Thus, we did the consultation with our instructor and they suggested us to use the exchange reaction because it can represent the knockout prediction for the accumulation of targeted extracellular metabolic. However, in our knockout model we solely try the cyanide production reaction (glycine:acceptor oxidoreductase) as the main target. Therefore, it is necessary to improve and add the cyanide exchange reaction to our model and transform the target in the knockout prediction into the cyanide exchange reaction.

#### Pyrite Dissolution Bioreactor

![engineering-pyrite-0](https://static.igem.org/mediawiki/2021/6/6f/T--UGM_Indonesia--img--engineering-pyrite-0.png)

##### Design

There are many possibilities of pyrite dissolution enzyme inhibition mechanism. The bioreactor main variables, such as µmax, KS, and KP are determined by fitting the experimental data with semi-batch bioreactor equation and model. This variable will also vary depending on: bioreactor operating condition, such as pH and temperature; substrate, such as different type of gold ore; and computational method, such as Lineweaver-Burk or linear regression.

Determining the inhibition mechanism of pyrite dissolution bioreactor will be useful for scale-up, developing process control (like PID), and further research for bioleaching of another metals using archaebacterial.

In this case, we modelled and calculated the results using python via jupyter notebook.

##### Build

For bioreactor modelling, we wrote ODE based on the relation of X (cell count), P (product concentration), and S (substrate concentration) with V (total volume) by applying Monod model and dilution rate:

\begin{align\*} \frac{d(XV)}{dt} = V\frac{dX}{dt} + X\frac{dV}{dt} = V\frac{dX}{dt} + F(t)X \\ \frac{dX}{dt} = - \frac{F(t)}{V}X + r\_c(X,S) \\ \end{align\*} \begin{align} \frac{d(PV)}{dt} = V\frac{dP}{dt} + P\frac{dV}{dt} = V\frac{dP}{dt} + F(t)P \\ \frac{dP}{dt} = - \frac{F(t)}{V}P + r\_P(X,S) \\ \end{align} \begin{align\*} \frac{d(SV)}{dt} = V\frac{dS}{dt} + S\frac{dV}{dt} = V\frac{dS}{dt} + F(t)S \\ \frac{dS}{dt} = \frac{F(t)}{V}(S\_f - S) - \frac{1}{Y\_{X/S}}r\_g(X,S) \\ \end{align\*}

The formula derivation from basic ODE correlation of X, P, and S with V is described in
[Bioreactor](https://2021.igem.org/Team%3AUGM_Indonesia/Bioreactor)
page.

The specific cell growth rate expressed as follows:

\[\mu\_{S} = \mu\_{max}\frac{S}{K\_S + S}\]

However, that equation doesn’t include the inhibitor variable. Based on ferrous iron oxidation in *T. Ferrooxidans periplasm*, we hypothesized that the cell regulates itself to inhibit the oxidation process with competitive inhibition. Thus, the µs equation with competitive inhibition would be:

\[\mu\_{S} = \mu\_{max}\frac{S}{K\_S(1+ \frac{S\_0-S}{K\_P})+S}\\\]

| X | Cell concentration (grams/liter) |
| --- | --- |
| P | Product concentration (grams/liter) |
| S | Substrate concentration (grams/liter) |
| \(S\_0\) | Feed substrate concentration (grams/liter) |
| \(r\_c\) | Rate of cell or biomass growth (grams/liter/hr) |
| \(r\_p\) | Rate of product formation (grams/liter/hr) |
| \(Y\_{P/X}\) | Product yield coefficient |
| \(Y\_{S/X}\) | Cell growth coefficient |
| F(t) | Flowrate (liter/hr) |
| \(\mu\_{S}\) | Cell specific growth rate |
| \(\mu\_{max}\) | Maximum cell specific growth rate |
| \(K\_S\) | Half saturation constant |
| \(K\_P\) | Inhibition constant |

The regulation of *T. Ferrooxidans cell* as competitive inhibitor assumption gives the following value for bioreactor-related variables:

| Kinetic Variable | FIELD2 |
| --- | --- |
| \(\mu\_{max}\) | 1.25 hr^{-1} |
| \(K\_S\) | 0.125 gram/liter |
| \(K\_P\) | 0.02 gram/liter |
| \(Y\_{S/X}\) | 0.324 gram/gram |
| \(Y\_{P/X}\) | 0.4348 gram/gram |
| \(S\_0\) | 606.6225 gram/liter |
| Bioreactor Operating Condition |  |
| pH | 2.3 |
| Temperature | 25oC |

Suzuki et al, 1989

##### Test

###### Cell-Regulated Competitive Inhibition

In this model, it is assumed that the operating conditions are maintained from the beginning until the end of the process batch. Then, the reaction was modelled via Jupyter Notebook.

![engineering-pyrite-1](https://static.igem.org/mediawiki/2021/f/fe/T--UGM_Indonesia--img--engineering-pyrite-1.png)

These are the results of cell concentration (X), product concentration (P), substrate concentration (S), and total volume (V) in 40 hours batch time:

| Variable | Initial (time = 0 hr) | End of Batch (time = 40 hr) | Unit |
| --- | --- | --- | --- |
| X | 0.05 | 1,95E+10 | Gram/liter |
| P | 0 | 8.463.576.051 | Gram/liter |
| S | 6.066.225 | 583.712.039 | Gram/liter |
| V | 25 | 27 | Liter |

##### Learn

To further extract the product, the residence time could be extended to be more than 40 hours. However, it is not efficient. The 40 hours residence time is considered to be moderate time for the gold bioleaching step, but it is still time consuming.

##### Design

There is another component that potentially be the most potent inhibitor agent: Fe3+, the product itself. The product being the inhibitor itself is present in a lot of other enzymatic reactions. This hypothesis could also be true for pyrite dissolutions.

##### Build

The second theory is by assuming Fe3+, the product itself to be the one who inhibits the iron oxidation process with a competitive inhibition mechanism. This theory gives the following value for bioreactor-related variables:

| Kinetic Variable | FIELD2 |
| --- | --- |
| \(\mu\_{max}\) | 1.25 hr^{-1} |
| \(K\_S\) | 0.048 gram/liter |
| \(K\_P\) | 0.06 gram/liter |
| \(Y\_{S/X}\) | 0.324 gram/gram |
| \(Y\_{P/X}\) | 0.4348 gram/gram |
| \(S\_0\) | 606.6225 gram/liter |
| Bioreactor Operating Condition |  |
| pH | 1.6 |
| Temperature | 30oC |

Jones et al, 1983

##### Test

In this model, it is assumed that the operating conditions are maintained from the beginning until the end of the process batch. Then, the reaction was modelled via Jupyter Notebook.

![engineering-pyrite-2](https://static.igem.org/mediawiki/2021/e/e3/T--UGM_Indonesia--img--engineering-pyrite-2.png)

These are the results of cell concentration (X), product concentration (P), substrate concentration (S), and total volume (V) in just 4 hours batch time, 36 hours shorter than the previous mechanism:

| Variable | Initial (time = 0 hr) | End of Batch (time = 4 hr) | Unit |
| --- | --- | --- | --- |
| X | 0.05 | 1,96E+10 | Gram/liter |
| P | 0 | 8.508.121.549 | Gram/liter |
| S | 6.066.225 | 267.506.643 | Gram/liter |
| V | 25 | 25.2 | Liter |

We managed to achieve 4 hours of pyrite dissolution process with this mechanism. Still, there are another inhibition mechanism by Fe3+ that is worth modeling.

##### Design

There are 3 types of enzyme inhibition: competitive, non-competitive, and uncompetitive. According to one research, Fe3+ also has potential to inhibit the iron oxidation in *T. Ferrooxidans* by non-competitive inhibition.

##### Build

The third theory is by assuming Fe3+ to inhibit the reaction by non-competitive inhibition mechanism. For non-competitive inhibition, the value of cell specific growth rate would be described as:

\[\mu\_{S} = \mu\_{max}\frac{S}{K\_S+S(1+ \frac{S\_0-S}{K\_P})}\\\]

This theory gives the following value for bioreactor-related variables:

| Kinetic Variable | FIELD2 |
| --- | --- |
| \(\mu\_{max}\)   µmax | 1.33 hr^{-1} |
| \(K\_S\)   KS | 0.04 gram/liter |
| \(K\_P\)   KP | 0.06 gram/liter |
| \(Y\_{S/X}\)   YS/X | 0.324 gram/gram |
| \(Y\_{P/X}\)   YP/X | 0.4348 gram/gram |
| \(S\_0\)   S0 | 606.6225 gram/liter |
| Bioreactor Operating Condition |  |
| pH | 1.6 |
| Temperature | 30 oC |

Jones et al, 1983

##### Test

###### Fe3+ Non-Competitive Inhibition

In this model, it is assumed that the operating conditions are maintained from the beginning until the end of the process batch. Then, the reaction was modelled via Jupyter Notebook.

![engineering-pyrite-3](https://static.igem.org/mediawiki/2021/1/15/T--UGM_Indonesia--img--engineering-pyrite-3.png)

These are the results of cell concentration (X), product concentration (P), substrate concentration (S), and total volume (V) in 17000 hours:

| Variable | Initial (time = 0 hr) | End of Batch (time = 17000 hr) | Unit |
| --- | --- | --- | --- |
| X | 0.05 | 1,97E+10 | Gram/liter |
| P | 0 | 8.545.373.735 | Gram/liter |
| S | 6.066.225 | 0.0307269178 | Gram/liter |
| V | 25 | 875 | Liter |

##### Learn

From the non-competitive hypothesis, the residence time increased to 1700 hours. The volume also expanded 35 times.

##### Final Conclusion

Thus, the best inhibition mechanism to determine bioreactor for artisanal & small scale gold mining (ASGM) is competitive inhibition by Fe3+.

#### References

1. KEGG, ENZYME: 1.4.99.5
   [Online]
   <https://www.genome.jp/dbget-bin/www_bget?ec:1.4.99.5>
   [accessed on July 28, 2021 at 09:06 WIT]
2. Kianinia, Y., Khalesi, M.R., Abdollahy, M., Hefter, G., Senanayake, G., Hnedkovsky L., Darban, A.K., Shahbazi, M., 2018, Predicting Cyanide Consumption in Gold Leaching: A Kinetic and Thermodynamic Modeling Approach, Minerals, vol. 8, no. 3, pp. 110. doi:10.3390/min8030110
3. Michaels, R. and Corpe, W.A., 1965, Cyanide Formation by Chromobacterium violaceum, Journal of Bacteriology, vol. 89, no. 1, pp. 106-112.
4. Brazilian National Genome Project Consortium, 2003, The complete genome sequence of Chromobacterium violaceum reveals remarkable and exploitable bacterial adaptability, Proceedings of the National Academy of Sciences of the United States of America, vol. 100, no. 20, pp. 11660-11665.
5. Lobell, R.B., Schleif, R.F., 1990, DNA looping and unlooping by AraC protein, Science, vol. 250, no. 4980, pp. 528-532.
6. Schleif, R., 2003, AraC protein: a love-hate relationship, Bioessays, vol. 25, pp. 274-282.
7. Brazilian National Genome Project Consortium, 2003, The complete genome sequence of Chromobacterium violaceum reveals remarkable and exploitable bacterial adaptability, Proceedings of the National Academy of Sciences of the United States of America, vol. 100, no. 20, pp. 11660–11665. doi:10.1073/pnas.1832124100
8. Cuthbertson, L., Nodwell, J.R., 2013, The TetR family of regulators, Microbiology and molecular biology reviews: MMBR, vol. 77, no. 3, pp. 440–475. doi:10.1128/MMBR.00018-13
9. Anonymous, 2011, Registry of Standard Biological Parts - pBAD Strong Characterization, Last Updated 22 Oct 2009)
   [Online]
   [http://partsregistry.org/Part:BBa\_K206000:Characterization](http://partsregistry.org/Part%3ABBa_K206000%3ACharacterization)
   [accessed on August 21, 2021 at 08:34 WIT]
10. Schleif, R 1969, Induction of the L-arabinose operon, Journal of Molecular Biology, Vol 46, pp. 197-199. doi: 10.1016/0022-2836(69)90066-7
11. Hendrickson, W.., Schleif, R., 1984, Regulation of the Escherichia coli L-Arabinose Operon Studied by Gel Electrophoresis DNA Binding Assay, Journal of Molecular Biology, Vol 174, no. 3, pp. 611-628.
12. Koostra, A.M.J., Mosier, N.S., Scott E.L., Beeftink, H.H., Sanders, J.P.M., 2009 , Differential effects of mineral and organic acids on the kinetics of arabinose degradation under lignocellulose pretreatment conditions, Biochemical Engineering Journal, Vol 43, pp. 92-97.
13. Bionumbers Logo, Key Numbers for Cell Biologists
    [Online]
    <http://bionumbers.hms.harvard.edu/KeyNumbers.aspx>
    [accessed on October 22, 2021]
14. Mintel, R. and Westley, J., 1966, The Rhodanese Reaction : Mechanism of Thiosulfate Binding, The Journal of Biological Chemistry, vol. 241, no. 14, pp. 3386 – 3389.
15. Seo, J.M., 2013, Characterization of an L-Arabinose Isomerase from Bacillus Thermoglucosidasius for D-Tagatose Production, Bioscience, Biotechnology, and Biochemistry, vol. 77, no. 2, pp. 385-388.
16. Megerle, J.A., Fritz, G., Gerland, U., Jung, K., Radler, J.O., 2008, Timing and Dynamics of Single Cell Gene Expression in the Arabinose Utilization System, Biophysics Journal, vol. 95, no. 4, pp. 2013-2115. doi: 10.1529/biophysj.107.127191
17. King, Z.A., Lu, J.S., Dräger, A., Miller, P.C., Federowicz, S., Lerman, J.A., Ebrahim, A., Palsson, B.O., and Lewis, N.E., 2016, BiGG Models: A platform for integrating, standardizing, and sharing genome-scale models, Nucleic Acids Research, vol. 44, no. D1, pp. D515-D522. doi:10.1093/nar/gkv1049
18. KEGG, Metabolic pathways - Reference pathway
    [Online]
    <https://www.genome.jp/kegg/pathway/>
    [accessed on October 22, 2021]
19. The Regents of the University of California, 2019, ESCHER: Build, share, and embed visualizations of metabolic pathways
    [Online]
    <https://escher.github.io/#/>
    [accessed on October 22, 2021]
20. Tay, S., Natarajan, G., Rahim, M., Tan, H., Chung, M., Ting, Y. et al., 2013, Enhancing gold recovery from electronic waste via lixiviant metabolic engineering in Chromobacterium violaceum, Scientific Reports, vol. 3, no. 1.
21. Banerjee, D., Raghunathan, A., 2019, Constraints-based analysis identifies NAD+ recycling through metabolic reprogramming in antibiotic resistant Chromobacterium violaceum, PLOS ONE, vol. 14, no. 1, pp. e0210008.
22. Patil, K. R., Rocha, I., Förster, J., Nielsen, J., 2005, Evolutionary programming as a platform for in silico metabolic engineering, BMC Bioinformatics, vol. 6, no. 308. doi:10.1186/1471-2105-6-308
23. Burgard, A.P., Pharkya, P., Maranas, C.D., 2003, OptKnock: A Bilevel Programming Framework for Identifying Gene Knockout Strategies for Microbial Strain Optimization, Biotechnology and Bioengineering, vol. 84, no. 6, pp. 647-657.

![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/1/13/T--UGM_Indonesia--img--sponsor-ugm.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/0/03/T--UGM_Indonesia--img--sponsor-genscript.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/1/10/T--UGM_Indonesia--img--sponsor-rentokill.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/4/44/T--UGM_Indonesia--img--sponsor-geneious.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/2/28/T--UGM_Indonesia--img--sponsor-its.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/d/df/T--UGM_Indonesia--img--sponsor-twistbio.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/7/7a/T--UGM_Indonesia--img--sponsor-idt.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/6/67/T--UGM_Indonesia--img--sponsor-biotek.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/6/65/T--UGM_Indonesia--img--sponsor-biology.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/3/3c/T--UGM_Indonesia--img--sponsor-agriculture.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/1/1f/T--UGM_Indonesia--img--sponsor-pharmacy.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/2/2c/T--UGM_Indonesia--img--sponsor-engineering.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/f/f3/T--UGM_Indonesia--img--sponsor-kkmk.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/9/9e/T--UGM_Indonesia--img--sponsor-feb.png)

![Universitas Gadjah Mada Logo](https://static.igem.org/mediawiki/2021/f/f1/T--UGM_Indonesia--img--logo-ugm-white.png)
![iGEM UGM 2021 Logo](https://static.igem.org/mediawiki/2021/0/0b/T--UGM_Indonesia--img--logo-igem-ugm-white.png)

##### iGEM UGM

Bulaksumur F11, Caturtunggal, Kecamatan Depok, Kabupaten Sleman, Daerah Istimewa Yogyakarta, Indonesia 55281

igemugm@gmail.com

#### Get in Touch!

All content on this wiki is available under the [Creative Commons Attribution 4.0 license](https://creativecommons.org/licenses/by/4.0/) (or any later version).

[![](https://static.igem.org/mediawiki/2021/8/8b/HQ_page_logo.jpg)](https://2021.igem.org)

# Team:UGM Indonesia/Experiments

<!DOCTYPE html>

Experiments

![](https://static.igem.org/mediawiki/2021/f/f2/T--UGM_Indonesia--img--project-logo.png)

* [Home](https://2021.igem.org/Team%3AUGM_Indonesia)
* Project
  + [Description](https://2021.igem.org/Team%3AUGM_Indonesia/Description)
  + [Design](https://2021.igem.org/Team%3AUGM_Indonesia/Design)
  + [Engineering](https://2021.igem.org/Team%3AUGM_Indonesia/Engineering)
  + [Safety](https://2021.igem.org/Team%3AUGM_Indonesia/Safety)
  + [Contribution](https://2021.igem.org/Team%3AUGM_Indonesia/Contribution)
* Wet Lab
  + [Parts](https://2021.igem.org/Team%3AUGM_Indonesia/Parts)
  + [Experiments](https://2021.igem.org/Team%3AUGM_Indonesia/Experiments)
  + [Results](https://2021.igem.org/Team%3AUGM_Indonesia/Results)
  + [Notebook](https://2021.igem.org/Team%3AUGM_Indonesia/Notebook)
* Dry Lab
  + [Model](https://2021.igem.org/Team%3AUGM_Indonesia/Model)
  + [Bioreactor](https://2021.igem.org/Team%3AUGM_Indonesia/Bioreactor)
* Human Practices
  + [Human Practices](https://2021.igem.org/Team%3AUGM_Indonesia/Human_Practices)
  + [Integrated Human Practices](https://2021.igem.org/Team%3AUGM_Indonesia/IHP)
  + [Proposed Implementation](https://2021.igem.org/Team%3AUGM_Indonesia/Implementation)
  + [Education and Communication](https://2021.igem.org/Team%3AUGM_Indonesia/Communication)
  + [Education and Public Engagement](https://2021.igem.org/Team%3AUGM_Indonesia/Education)
  + [Entrepreneurship](https://2021.igem.org/Team%3AUGM_Indonesia/Entrepreneurship)
  + [Sustainable Development Impact](https://2021.igem.org/Team%3AUGM_Indonesia/Sustainable)
* Team
  + [Members](https://2021.igem.org/Team%3AUGM_Indonesia/Team)
  + [Attributions](https://2021.igem.org/Team%3AUGM_Indonesia/Attributions)
  + [Collaborations](https://2021.igem.org/Team%3AUGM_Indonesia/Collaborations)
  + [Partnership](https://2021.igem.org/Team%3AUGM_Indonesia/Partnership)
* Medals
  + [Medals](https://2021.igem.org/Team%3AUGM_Indonesia/Medals)

# Experiments

# Experiments

# Experiments

[Learn More](#main-content)

* [Competent Cell Preparation](#competent)
* [Heat Shock Transformation Protocol for  *E. coli*]](#heat-shock)
* [Genome Isolation](#genome)
* [Gel extraction protocol (Geneaid)](#gel)
* [PCR Cleanup Protocol Procedure](#pcr)
* [Gibson Assembly Protocol](#gibson)
* [Fluorometry for Green Fluorescent Protein (GFP) Measurement](#fluorometry)
* [Spectrophotometry for Cell Growth Measurement](#spectrophotometer)

Our project was designed to engineer bacteria into a cyanide-regulating system then analyze its protein expression profiles. These protocols below are our ways to obtain results from our lab works.

#### Competent Cell Preparation

We made 2 competent cells at once: *E. coli* \(BL21\) and *E. coli* \(DH5α\) with the Sambrook protocol:

1. prepare overnight pre culture taken from the streak plate of each strain.
2. inoculate 1% of overnight pre-culture to 50mL LB medium.
3. incubate in room temperature ~2.5h up to the OD600 reaches 0.5 - 0.6.
4. divide the broth culture into 2 falcon tubes.
5. centrifuge in 4oC, 7000rpm in 5 mins.
6. discard the supernatant and keep the pellet in an ice box.
7. add 25mL of pre-chilled 0.1M CaCl2 solution and resuspend the cell.
8. incubate for 15 mins in the ice box.
9. centrifuge 4oC, 7000rpm in 5 mins. discard the supernatant and keep the pellet on ice.
10. add 15mL pre-chilled CaCl2 solution and resuspend the pellet.
11. incubate on ice for 15 mins.
12. centrifuge in 4oC, 7000rpm in 5 min, discard the supernatant and keep the pellet on ice.
13. add 1mL CaCl2 + glycerol solution. Resuspend the pellet. Better work in LAF/ BSC.
14. divide the culture into 1.5mL microtube, 60uL each.
15. freeze all tubes using liquid nitrogen.
16. keep in -80oC.

#### Heat Shock Transformation Protocol for *E. coli*

1. Thaw competent cells on ice.
2. Add 2 μL of the chilled assembly product to the competent cells. Mix gently by pipetting up and down or by flicking the tube 4–5 times. Do not vortex.
3. Place the mixture on ice for 30 minutes. Do not mix.
4. Heat shock at 42°C for 45 seconds. Do not mix.
5. Transfer tubes to ice for 5 minutes.
6. Add 950 μL of room-temperature SOC media to the tube.
7. Incubate the tube at 37°C for 60 minutes. Shake vigorously (250 rpm) or rotate.
8. Warm selection plates to 37°C.
9. Spread 100 μl of the cells onto the selection plates.
10. Centrifuge the remaining 800 μL of the cells at 6800 xg for 3 minutes.
11. Remove 700 μL of supernatant, and mix the remaining 100 μl supernatant with the pellet.
12. Spread 100 μL of the "9x concentration" cells onto the selection plates
13. Incubate overnight at 37°C.

#### Genome Isolation

Kit used: Presto mini gDNA bacteria kit

Protocol for gram negative

1. ##### Sample preparation

   Transfer bacterial cells (up to 1 x 109) to a 1.5 mL microcentrifuge tube. Centrifuge for 1 minute at 14,000-16,000 x g then discard the supernatant. Add 180 µl of GT Buffer then re-suspend the cell pellet by vortex or pipette. Add 20 µL of Proteinase K (make sure ddH2O was added). Incubate at 60ºC for at least 10 minutes. During incubation, invert the tube every 3 minutes. Proceed with step 2 (Lysis).
2. ##### Lysis

   Add 200 µl of GB Buffer to the sample and mix by vortex for 10 seconds. Incubate at 70ºC for at least 10 minutes to ensure the sample lysate is clear. During incubation, invert the tube every 3 minutes. At this time, pre-heat the required Elution Buffer (200 μL per sample) to 70ºC (for step 5 DNA Elution).
3. ##### DNA binding

   Add 200 µL of absolute ethanol to the sample lysate and mix IMMEDIATELY by shaking vigorously. If precipitate appears, break it up as much as possible with a pipette. Place a GD Column in a 2 ml Collection Tube. Transfer mixture (including any insoluble precipitate) to the GD Column then centrifuge at 14,000-16,000 x g for 2 minutes. Discard the 2 ml Collection Tube containing the flow-through then place the GD Column in a new 2 ml Collection Tube.
4. ##### Wash

   Add 400 µL of W1 Buffer to the GD Column. Centrifuge at 14,000-16,000 x g for 30 seconds then discard the flow-through. Place the GD Column back in the 2 ml Collection Tube. Add 600 µL of Wash Buffer (make sure ethanol was added) to the GD Column. Centrifuge at 14,000-16,000 x g for 30 seconds then discard the flow-through. Place the GD Column back in the 2 mL Collection Tube. Centrifuge again for 3 minutes at 14,000-16,000 x g to dry the column matrix.
5. ##### Elution

   Transfer the dried GD Column to a clean 1.5 mL microcentrifuge tube. Add 100 μL of pre-heated Elution Buffer1, TE Buffer or water into the CENTER of the column matrix. Let stand for at least 3 minutes to allow the Elution Buffer, TE Buffer or water to be completely absorbed. Centrifuge at 14,000-16,000 x g for 30 seconds to elute the purified DNA.

#### Gel extraction protocol (Geneaid)

This protocol refers to the Instructor Manual for GenepHlow™ Gel/PCR Kit created by Geneaid Biotech Ltd (link:<https://www.geneaid.com/data/files/1605861013102532959.pdf>).

1. ##### Gell dissociation

   Cut the agarose gel slice containing relevant DNA fragments and remove any extra agarose to minimize the size of the gel slice. Transfer up to 300 mg of the gel slice to a 1.5 mL microcentrifuge tube. Add 500 µL of Gel/PCR Buffer to the sample then mix by vortex. Incubate at 55-60ºC for 10-15 minutes or until the gel slice is completely dissolved. During incubation, invert the tube every 2-3 minutes. If the color of the mixture has turned from yellow to purple, add 10 µL of 3M Sodium Acetate (pH5.0) and mix thoroughly. This will adjust pH and the color will return to yellow. Cool the dissolved sample mixture to room temperature.
2. ##### DNA Binding

   Place a DFH Column in a 2 mL Collection Tube. Transfer 800 µl of the sample mixture to the DFH Column. Centrifuge at 14,000-16,000 x g for 30 seconds. Discard the flow-through then place the DFH Column back in the 2 mL Collection Tube.
3. ##### Wash

   Add 400 µL of W1 Buffer into the DFH Column. Centrifuge at 14,000-16,000 x g for 30 seconds then discard the flow-through. Place the DFH Column back in the 2 mL Collection Tube. Add 600 µL of Wash Buffer (make sure absolute ethanol was added) into the DFH Column and let it stand for 1 minute. Centrifuge at 14,000-16,000 x g for 30 seconds then discard the flow-through. Place the DFH Column back in the 2 mL Collection Tube. Centrifuge at 14,000-16,000 x g for 3 minutes to dry the column matrix.
4. ##### Elution

   Transfer the dried DFH Column to a new 1.5 ml microcentrifuge tube. Add 20-50 µL of Elution Buffer1, TE2 or water3 into the CENTER of the column matrix. Let stand for at least 2 minutes to allow the Elution Buffer, TE or water to be completely absorbed. Centrifuge at 14,000-16,000 x g for 2 minutes at room temperature to elute the purified DNA.

#### PCR Cleanup Protocol Procedure

This protocol refers to the Instructor Manual for GenepHlow™ Gel/PCR Kit created by Geneaid Biotech Ltd (link: <https://www.geneaid.com/data/files/1605861013102532959.pdf>).

1. ##### Sample preparation

   Cut the agarose gel slice containing relevant DNA fragments and remove any extra agarose to minimize the size of the gel slice. Transfer up to 300 mg of the gel slice to a 1.5 mL microcentrifuge tube. Add 500 µL of Gel/PCR Buffer to the sample then mix by vortex. Incubate at 55-60ºC for 10-15 minutes or until the gel slice is completely dissolved. During incubation, invert the tube every 2-3 minutes. If the color of the mixture has turned from yellow to purple, add 10 µL of 3M Sodium Acetate (pH5.0) and mix thoroughly. This will adjust pH and the color will return to yellow. Cool the dissolved sample mixture to room temperature.
2. ##### DNA Binding

   Place a DFH Column in a 2 mL Collection Tube. Transfer the sample mixture to the DFH Column. Centrifuge at 14,000-16,000 x g for 30 seconds. Discard the flow-through and place the DFH Column back in the 2 ml Collection Tube.
3. ##### Wash

   Add 600 µL of Wash Buffer (make sure absolute ethanol was added) into the DFH Column and let it stand for 1 minute. Centrifuge at 14,000-16,000 x g for 30 seconds then discard the flow-through. Place the DFH Column back in the 2 ml Collection Tube. Centrifuge at 14,000-16,000 x g for 3 minutes to dry the column matrix.
4. ##### Elution

   Transfer the dried DFH Column to a new 1.5 mL microcentrifuge tube. Add 20-50 µL of Elution Buffer1, TE2 or water3 into the CENTER of the column matrix. Let stand for at least 2 minutes to allow the Elution Buffer, TE or water to be completely absorbed. Centrifuge at 14,000-16,000 x g for 2 minutes at room temperature to elute the purified DNA.

#### Gibson Assembly Protocol

1. ##### Design the Plasmid

   For the plasmid design, users should consider the adjacent segments which have identical sequences with the inserts on the end. The identical sequence can be obtained with PCR using a specific primer. The adjacent/overhang sequence should be at least 12 - 30bp.
2. ##### Generate DNA Segments by PCR

   DNA segments with identical adjacent sequences on the end of the sequences are amplified with PCR and run it to agarose electrophoresis gel to check the size and yield. If more than one band is found, it is necessary to cut and purify the sequences from the electrophoresis gel. Otherwise, PCR product purification can proceed if a single clear band is obtained from the electrophoresis.
3. ##### Gibson Assembly Reaction

   Mix the DNA segments and the backbone in one tube. Yield will be the best if each DNA fragment has equimolar concentration. Mix the DNA fragment and add the Gibson Cloning Master Mix. Incubate for 1 hour in 50ºC.

#### Fluorometry for Green Fluorescent Protein (GFP) Measurement

1. 3mL of cells are collected in every 15 minutes interval within 6 hours of incubation.
2. The samples are transferred into the fluorometer cuvette.
3. The fluorescence intensity of samples are measured by fluorometry in excitation and emission wavelengths of 504 and 515 nm, respectively. Luria Bertani Broth (LB) medium was used as the blank solution. The resulting intensity values indicate the fluorescence occurrences by the expressed GFPs.

#### Spectrophotometry for Cell Growth Measurement

1. 3mL of cells are collected in every 15 minutes interval within 6 hours of incubation.
2. The samples are transferred into the spectrophotometer cuvette.
3. The cell growth is measured by the optical density (OD600).

![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/1/13/T--UGM_Indonesia--img--sponsor-ugm.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/0/03/T--UGM_Indonesia--img--sponsor-genscript.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/1/10/T--UGM_Indonesia--img--sponsor-rentokill.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/4/44/T--UGM_Indonesia--img--sponsor-geneious.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/2/28/T--UGM_Indonesia--img--sponsor-its.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/d/df/T--UGM_Indonesia--img--sponsor-twistbio.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/7/7a/T--UGM_Indonesia--img--sponsor-idt.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/6/67/T--UGM_Indonesia--img--sponsor-biotek.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/6/65/T--UGM_Indonesia--img--sponsor-biology.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/3/3c/T--UGM_Indonesia--img--sponsor-agriculture.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/1/1f/T--UGM_Indonesia--img--sponsor-pharmacy.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/2/2c/T--UGM_Indonesia--img--sponsor-engineering.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/f/f3/T--UGM_Indonesia--img--sponsor-kkmk.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/9/9e/T--UGM_Indonesia--img--sponsor-feb.png)

![Universitas Gadjah Mada Logo](https://static.igem.org/mediawiki/2021/f/f1/T--UGM_Indonesia--img--logo-ugm-white.png)
![iGEM UGM 2021 Logo](https://static.igem.org/mediawiki/2021/0/0b/T--UGM_Indonesia--img--logo-igem-ugm-white.png)

##### iGEM UGM

Bulaksumur F11, Caturtunggal, Kecamatan Depok, Kabupaten Sleman, Daerah Istimewa Yogyakarta, Indonesia 55281

igemugm@gmail.com

#### Get in Touch!

All content on this wiki is available under the [Creative Commons Attribution 4.0 license](https://creativecommons.org/licenses/by/4.0/) (or any later version).

[![](https://static.igem.org/mediawiki/2021/8/8b/HQ_page_logo.jpg)](https://2021.igem.org)

# Team:UGM Indonesia/Results

<!DOCTYPE html>

Results

![](https://static.igem.org/mediawiki/2021/f/f2/T--UGM_Indonesia--img--project-logo.png)

* [Home](https://2021.igem.org/Team%3AUGM_Indonesia)
* Project
  + [Description](https://2021.igem.org/Team%3AUGM_Indonesia/Description)
  + [Design](https://2021.igem.org/Team%3AUGM_Indonesia/Design)
  + [Engineering](https://2021.igem.org/Team%3AUGM_Indonesia/Engineering)
  + [Safety](https://2021.igem.org/Team%3AUGM_Indonesia/Safety)
  + [Contribution](https://2021.igem.org/Team%3AUGM_Indonesia/Contribution)
* Wet Lab
  + [Parts](https://2021.igem.org/Team%3AUGM_Indonesia/Parts)
  + [Experiments](https://2021.igem.org/Team%3AUGM_Indonesia/Experiments)
  + [Results](https://2021.igem.org/Team%3AUGM_Indonesia/Results)
  + [Notebook](https://2021.igem.org/Team%3AUGM_Indonesia/Notebook)
* Dry Lab
  + [Model](https://2021.igem.org/Team%3AUGM_Indonesia/Model)
  + [Bioreactor](https://2021.igem.org/Team%3AUGM_Indonesia/Bioreactor)
* Human Practices
  + [Human Practices](https://2021.igem.org/Team%3AUGM_Indonesia/Human_Practices)
  + [Integrated Human Practices](https://2021.igem.org/Team%3AUGM_Indonesia/IHP)
  + [Proposed Implementation](https://2021.igem.org/Team%3AUGM_Indonesia/Implementation)
  + [Education and Communication](https://2021.igem.org/Team%3AUGM_Indonesia/Communication)
  + [Education and Public Engagement](https://2021.igem.org/Team%3AUGM_Indonesia/Education)
  + [Entrepreneurship](https://2021.igem.org/Team%3AUGM_Indonesia/Entrepreneurship)
  + [Sustainable Development Impact](https://2021.igem.org/Team%3AUGM_Indonesia/Sustainable)
* Team
  + [Members](https://2021.igem.org/Team%3AUGM_Indonesia/Team)
  + [Attributions](https://2021.igem.org/Team%3AUGM_Indonesia/Attributions)
  + [Collaborations](https://2021.igem.org/Team%3AUGM_Indonesia/Collaborations)
  + [Partnership](https://2021.igem.org/Team%3AUGM_Indonesia/Partnership)
* Medals
  + [Medals](https://2021.igem.org/Team%3AUGM_Indonesia/Medals)

# Results

# Results

# Results

[Learn More](#main-content)

* [Gene construction of for HCN production](#geneconstruct)
* [Assembly](#assembly)
* [Genetic Transformation](#transformation)
* [Future Work](#future)

We tried to create an on-off system for HCN production and HCN degradation for *C. violaceum*. We engineered 3 plasmids which consist of the hcnABC operon (the HCN production plasmid combined with AraC-pBAD promoter), the rhodanese gene (HCN degradation gene with AraC repressible promoter), and L-arabinose isomerase (responsible to transform the Arabinose to shut down the HCN production). The overview of our gene construct depicted in **Figure 1**. Due to the complexity of the project and the construct itself, we divided our project into 3 sub-projects and for this time we are focusing to create the first construct, which is the HCN production circuit.

![](https://static.igem.org/mediawiki/2021/1/17/T--UGM_Indonesia--img--results-figure-1.jpg)

**Figure 1.** Circuitry design of *Auviola*.

#### Gene construction of for HCN production

To construct the HCN production gene, we needed several biobrick parts. Gene construction for HCN production consists of several parts:

1. AraC-pBAD promoter (**BBa\_K1602055**)
2. RBS (**BBa\_B0034**)
3. hcnABC operon (synthesized by Twist Bioscience)
4. hcnC from extracted genome *C. violaceum*
5. Double terminator (**BBa\_B0015**)
6. BBa\_B0034 (strong RBS)
7. Origin of replication from pBBR1-MCS2 (obtained from colleague)

The total legth of the overal construct with the backbone is around 7000s bp (**Figure 2**). During the first step of the assembly, we used the native origin of replication from pSB1C3.

![](https://static.igem.org/mediawiki/2021/6/61/T--UGM_Indonesia--img--results-figure-2.jpg)

**Figure 2.** Plasmid Design of the Circuit.

Each of the required part was amplified by Phusion High-Fidelity PCR Kit with the specific primers as shown in **Table 1**. The gene amplification was visualized by gel electrophoresis under UV-light (**Figure 3**) and purified by gel purification system in order to obtain the desirable gene sequence. The DNA concentration of each product were quantified using Nanodrop (**Table 2**).

Gel purification was performed for sample 1, 2, 5, 6, 8, 9, 10, and 11. The rest samples were purified using PCR clean-up purification protocol.

**Table 2.** DNA Concentration Result after PCR product and Gel Purification.

| Tube | DNA Concentration (ng/uL) |
| --- | --- |
| 1 | 13.154 |
| 2 | 16.277 |
| 3 | 12.196 |
| 4 | 40.619 |
| 5 | 33.277 |
| 6 | 89.711 |
| 7 | 35.234 |
| 8 | 37.004 |
| 9 | 26.598 |
| 10 | 19.461 |
| 11 | 28.206 |
| 12 | 18.477 |

#### Assembly

After all of the constructs with the overhang sites (elongated through PCR system) were obtained, then we continued the process for the assembly. Some constructs that we assembled consist of:

1. P1: BBa\_ K1602055 (Biobrick Parts)
2. P2: hcnAB (Twist Bioscience)
3. P3: hcnC-1st fragment (isolated from *C. violaceum* WT genome; before the illegal site)
4. P4: hcnC-2nd fragment (isolated from *C. violaceum* WT genome; after the illegal site)
5. P5: BBa\_B0015 double terminator, together with the backbone

These parts were all assembled using the Gibson assembly method. The reaction mix are incubated in 50oC for 1 hour in a thermal cycler.

#### Genetic Transformation

We transformed the construct to *E. coli* \(BL21(DE3)\) and \(DH5α\) using a strandard heat shock transformation protocol. LB agar plate supplemented with chloramphenicole was used to select the transformants. After an overnight incubation, we did the colony PCR, using VF2 VR primers (**Table 3**), to the randomly picked the colonies and directly subcultured the colonies and subcultured them in the LB broth with antibiotic. The following figure (**Figure 3**) depicts the results.

**Table 3.** The Sequence of VF2 and VR Primer.

| Primer | Sequence |
| --- | --- |
| VF2 | TGCCACCTGACGTCTAAGAA |
| VR | GCTCACTCAAAGGCGGTAAT |

![](https://static.igem.org/mediawiki/2021/6/63/T--UGM_Indonesia--img--results-figure-4.jpg)

**Figure 3.** Colony PCR Result of the Random-picked Transformants.

The elctropherogram showed that the DNA size were merely under 1500 bp, however, there were some bands appears with the size of arround 4600 bp. We suspected that the PCR mix was not robust to amplify our construct. Therefore, we directly subcultured the first colony (ColA) for plasmid extraction, obtaining the concentration of **ColA: 146.20 ng/uL**.

Another PCR cycle was conducted using hcnABC primers to confirm whether the construct is fully inserted to the vector (**Figure 4**).

![](https://static.igem.org/mediawiki/2021/d/d5/T--UGM_Indonesia--img--results-figure-6.jpg)

**Figure 4.** Electrophoresis Result for ColA.

Additional bands were shown on the gel electrophoresis result with the size of around 5000 bp and 1500 bp. Although the desired band (~4600s bp) have been obtained, further investigation is necessary in order to confirm that the construct is correct. Therefore, we send the extracted plasmid and some primers for Sanger sequencing analysis.

This time we still waiting for the sequenced plasmid. The sequencing result will be reported soon.

#### Future Work

By the time we receive the sequencing result, we will directly assess the construct and measure the accumulation of cyanide production in *E. coli* \(BL21(DE3)\) expression system. In contrast, the assembly and reconstruction will be conducted when the result were not as we expected. Besides, we also plan to change the ORI from pBBR1-MCS2 plasmid because this ORI is compatible for both *E. coli* and *C. violaceum*.[1](#reference-1) Next, we will transform the plasmid to competent cell *C. violaceum* using some methods such as heat shock, optimized electroporation,[2](#reference-2)and freeze thawing method. Transformation optimization is necessary for this step because *C. violaceum* \(ATCC 12472\) is a non-model chassis, which makes it more challenging engineer.

Following that, we plan to measure the cyaide production of the engineered *C. violaceum* \(ATCC 14272\) using picric acid method,[3](#reference-3) confirm and re-assess our Genome Scale Model and kinetic models, and compare the cyanide production with the Wild Type. If the result found out that the average cyanide production is higher, it will be the first step for further improvement, i.e., pH optimization, given that the bioleaching process by cyanide is a pH-dependent process.

#### References

1. Liow, L.T., Go, M.K., Chang, M.W., Yew, W.S., 2020, Toolkit development for cyanogenic and gold biorecovery chassis *Chromobacterium violaceum*, *ACS Synth. Biol*, vol. 9, pp. 953 – 961.
2. Loke, W.K. and Saud, H.M., 2020. Electrotransformation on selected plant growth-promoting Rhizobacteria (PGPR) and *Chromobacterium violaceum*. *Journal of Agrotechnology*, vol. 11, no. 1, pp. 63 – 69.
3. Drochiou, G., Pui, A., Danac, R., Basu, C., Murariu, M., 2003, Improved spectrophotometric assay of cyanide with picric acid, *Revue Roumaine de Chimie*, vol. 48, no. 8, pp. 601 – 606.

![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/1/13/T--UGM_Indonesia--img--sponsor-ugm.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/0/03/T--UGM_Indonesia--img--sponsor-genscript.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/1/10/T--UGM_Indonesia--img--sponsor-rentokill.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/4/44/T--UGM_Indonesia--img--sponsor-geneious.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/2/28/T--UGM_Indonesia--img--sponsor-its.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/d/df/T--UGM_Indonesia--img--sponsor-twistbio.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/7/7a/T--UGM_Indonesia--img--sponsor-idt.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/6/67/T--UGM_Indonesia--img--sponsor-biotek.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/6/65/T--UGM_Indonesia--img--sponsor-biology.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/3/3c/T--UGM_Indonesia--img--sponsor-agriculture.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/1/1f/T--UGM_Indonesia--img--sponsor-pharmacy.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/2/2c/T--UGM_Indonesia--img--sponsor-engineering.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/f/f3/T--UGM_Indonesia--img--sponsor-kkmk.png)
![Universitas Gadjah Mada](https://static.igem.org/mediawiki/2021/9/9e/T--UGM_Indonesia--img--sponsor-feb.png)

![Universitas Gadjah Mada Logo](https://static.igem.org/mediawiki/2021/f/f1/T--UGM_Indonesia--img--logo-ugm-white.png)
![iGEM UGM 2021 Logo](https://static.igem.org/mediawiki/2021/0/0b/T--UGM_Indonesia--img--logo-igem-ugm-white.png)

##### iGEM UGM

Bulaksumur F11, Caturtunggal, Kecamatan Depok, Kabupaten Sleman, Daerah Istimewa Yogyakarta, Indonesia 55281

igemugm@gmail.com

#### Get in Touch!

All content on this wiki is available under the [Creative Commons Attribution 4.0 license](https://creativecommons.org/licenses/by/4.0/) (or any later version).