iGEM 2023 — Team bitspilani-goa-india

{% extends "layout.html" %}
{% block title %}Notebook{% endblock %}
{% block lead %}Document the dates you worked on your project. This should be a detailed account of the work done each day for your project.{% endblock %}
{% block page\_content %}

# Notebook

Week 1

![](https://static.igem.wiki/teams/4963/wiki/week1-page-0001.jpg)

Week 2

![](https://static.igem.wiki/teams/4963/wiki/week2-page-0001.jpg)

Week 2

![](https://static.igem.wiki/teams/4963/wiki/week2-page-0002.jpg)

Week 3

![](https://static.igem.wiki/teams/4963/wiki/week3-page-0001.jpg)

Week 3

![](https://static.igem.wiki/teams/4963/wiki/week3-page-0002.jpg)

Week 4

![](https://static.igem.wiki/teams/4963/wiki/week4-page-0001.jpg)

Week 4

![](https://static.igem.wiki/teams/4963/wiki/week4-page-0002.jpg)

Week 5

![](https://static.igem.wiki/teams/4963/wiki/week5-page-0001.jpg)

Week 5

![](https://static.igem.wiki/teams/4963/wiki/week5-page-0002.jpg)

Week 6

![](https://static.igem.wiki/teams/4963/wiki/week6-page-0001.jpg)

Week 6

![](https://static.igem.wiki/teams/4963/wiki/week6-page-0002.jpg)

Week 6

![](https://static.igem.wiki/teams/4963/wiki/week6-page-0003.jpg)

Week 7

![](https://static.igem.wiki/teams/4963/wiki/week7-page-0001.jpg)

Week 7

![](https://static.igem.wiki/teams/4963/wiki/week7-page-0002.jpg)

Week 7

![](https://static.igem.wiki/teams/4963/wiki/week7-page-0003.jpg)

Week 8

![](https://static.igem.wiki/teams/4963/wiki/week8-page-0001.jpg)

Week 8

![](https://static.igem.wiki/teams/4963/wiki/week8-page-0002.jpg)

Week 9

![](https://static.igem.wiki/teams/4963/wiki/week9-page-0001.jpg)

Week 9

![](https://static.igem.wiki/teams/4963/wiki/week9-page-0002.jpg)

Week 9

![](https://static.igem.wiki/teams/4963/wiki/week9-page-0003.jpg)

Week 10

![](https://static.igem.wiki/teams/4963/wiki/week10-page-0001.jpg)

Week 10

![](https://static.igem.wiki/teams/4963/wiki/week10-page-0002.jpg)

Week 10

![](https://static.igem.wiki/teams/4963/wiki/week10-page-0003.jpg)

Week 10

![](https://static.igem.wiki/teams/4963/wiki/week10-page-0004.jpg)

Week 11

![](https://static.igem.wiki/teams/4963/wiki/week11-page-0001.jpg)

Week 11

![](https://static.igem.wiki/teams/4963/wiki/week11-page-0002.jpg)

Week 11

![](https://static.igem.wiki/teams/4963/wiki/week11-page-0003.jpg)

❮
❯

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{% extends "layout.html" %}
{% block title %}Engineering Success{% endblock %}
{% block lead %}Demonstrate engineering success in a part of your project by going through at least one iteration of the engineering design cycle.{% endblock %}
{% block page\_content %}

# Engineering

### Engineering Objectives

Antigen heterogeneity in solid tumors describes the presence of multiple antigens at the tumor site with variable levels of expression. CAR T - cell therapy, reliant on antigen specific action, is therefore rendered largely ineffective when it encounters multiple antigens[1](#references). The properties of a solid tumor are maintained by the tumor microenvironment (TME), which comprises a colony of cancer cells. At this site, the cancer cells adhere to the vascular endothelial cells to form a sustainable base for the tumor, enabling metastasis. This adhesion is physically manifested in selectin proteins: E and P - selectin in particular[2](#references). The dismantling of this adhesive network can therefore facilitate enhanced T-cell action by negating solid tumor properties.

Figure 1 displays the engineering design flow, starting from the primary objective here described

![](https://static.igem.wiki/teams/4963/wiki/eng-flow9-drawio.png)

*Figure 1: A representation of the project engineering flow. Legend provided on the top left corner. Created using draw.io*

### Primary Target

**- Specifications we looked at:**

Genetic upregulation (enhancement) of adhesive elements (E and P - Selectin)
**- Candidates:**

* STAT3
* NF-κB
* TNF-α

**Why STAT3 over other candidates?**

* **ICAM** and **VCAM**
  Apart from the selectin proteins, STAT3 also regulates the intercellular adhesion molecule (ICAM) - 1 and vascular adhesion molecule (VCAM) - 1 proteins, both crucial to the cell adhesive mechanism in solid tumors[3](#references).
* **Epithelial** to **Mesenchymal Transition (EMT)**:
  The EMT process allows a tumor to metastasize. The primary markers of EMT are **N-cadherin** and **vimentin**, whereas **E-cadherin**, an epithelial marker, is downregulated during the same[4](#references).
STAT3 is found to be a crucial gene in the regulation of EMT, as it increases the expression of EMT markers while down regulating E-cadherin and enhances the subsequent tumor metastasis[5](#references).
Therefore, STAT3 inhibition, apart from diluting onsite defenses, also neutralizes the spread of cancer to some extent.

![](https://static.igem.wiki/teams/4963/wiki/copy-of-emt-pathway-project-engg-fig1-2023-10-08-figure2.png)

*Figure 2: Genetic makeup of protein pathways for initiation of Epithelial-Mesenchymal Transition*[6](#references).
 Created with BioRender

* **Cell apoptosis:**
  STAT3 enhances the apoptosis inhibitors Bcl - x, Mcl - 1 and survivin, thereby supporting cancer survival. STAT3 inhibition therefore assists cancer apoptosis and not simply a reversion to the initial state[7](#references).

This unique positioning of STAT3 in the genetic pathways for tumor sustenance thus qualifies it as an excellent target for cancer therapy.

### Targeting Agent

**- Specifications we looked at:**

In our research, we focused on evaluating the STAT3 inhibitory activity of specific compounds. We aimed to achieve effective dispersion of these compounds, either through their concentrated self-directed action or by using a carrier to guide them. Tumor penetration was a critical consideration, and we prioritized small molecules for this purpose. It's worth noting that STAT1, another important signaling protein, shares similarities with STAT3 but plays a role in supporting tumor cell apoptosis[8](#references)
. Consequently, any targeting agent we developed needed to be selective and not interfere with STAT1. To minimize interference from normal cell activity, we opted for compounds that are not natural derivatives. These considerations guided our scientific approach to developing effective and precise therapies. Early on in our project, we spoke to people from the pharmaceutical industry, who also talked about how targeting the STAT3 receptor is being looked at with great interest by companies developing CAR T-cell therapy.

**- Candidates:**

One prominent candidate is identified:

**Honokiol[9](#references)**

**- Engineering Advantages: Honokiol**

As described later, honokiol provides a viable option of delivery by virtue of its binding activity with CB2 and CB1[10](#references).
 Owing to the advantages associated with the use of Cannabinoid receptors (as described ahead), honokiol is found to be the ideal targeting agent.

**- Testing and Verification**

Honokiol treatment (with CAR T - cells): introduction of CAR T - cells alongside honokiol to a tumor patient was studied and modeled mathematically to obtain the requisite data for the following parameters:

* Tumor cell mass
* Time taken for action

To effectively interpret the data, the following conditions were studied:

* Natural tumor growth
* Tumor growth after introduction of CAR T - Cells
* Tumor growth after introduction of drug
* Tumor growth after introduction of CAR T - cells and drug.

Kindly refer to the [Model](%7B%7Burl_for%28%27pages%27%2C%20page%3D%27model%27%29%7D%7D) page for detailed modeling process and results.

**- Optimization**

To determine the adequate dosage of honokiol, based on the mathematical model, various parameters of the study were varied to obtain optimal results. Upon varying the initial concentration of honokiol, the best results are obtained for 25 µM concentration, with a 70% tumor dispersion observed (upon further increase, the numbers do not change significantly). For detailed results, please refer to the [Model](%7B%7Burl_for%28%27pages%27%2C%20page%3D%27model%27%29%7D%7D) page.

Overall Treatment Design Requirements-

To achieve targeted tumor action in cancer therapy, it is of utmost importance to carefully design the delivery system for the treatment agent. Our approach is using receptor carriers, which can efficiently transport small molecules to tumor cells via specific molecular interactions. By employing receptor carriers, our small molecule drug can be effectively masked from normal cells, thereby minimizing off-target effects and reducing undesirable side effects associated with conventional cancer treatments.

### Delivery Mechanism

In order to deliver a small molecule, a carrier must be developed.

**DESIGN COMPONENTS:**

* **Receptor:** to bind to the small molecule
* **Vector:**for transport to the tumor site
* **Anchorage:**to link receptor to vector

![](https://static.igem.wiki/teams/4963/wiki/copy-of-recombinant-part-2023-10-08-figure-3.png)

*Figure 3: The receptor based carrier system for our drug. Created using BioRender.*

### Receptor

*** Specifications we looked at:**

Receptors serve as critical components, as choosing a receptor which has specific binding sites which facilitate the binding of small molecules like honokiol is important. While honokiol is not naturally synthesized within the human body, it originates from external sources (plants). Achieving controlled release of these compounds often relies on the availability and strategic use of suitable receptor antagonists, which must have a higher binding affinity to the receptor in the case of a competitive inhibitor, or must be binding to allosteric site such that the conformation of the receptor changes such that the drug gets released at the target site.

*** Candidates:**

Cannabinoid receptors 1 and 2 (**CB1** and CB2) are determined to be ideal candidates through extensive literature review. .

*** Engineering Advantages:CB1**

CB1 serves as the perfect receptor for our drug, as we had performed a virtual screen of sorts of potential receptors for our candidate drug. The binding scores are illustrated in the Docking Simulations section on our [Model](%7B%7Burl_for%28%27pages%27%2C%20page%3D%27model%27%29%7D%7D) page and are also illustrated below.

*** Testing and Verification**

+ Binding - CB1 binding with honokiol is studied in AutoDock, a software tool for binding studies. Figure 4 illustrates the binding simulation in PyMOL, a protein editing and visualization tool.

*** Optimization**

Parameters:

*** Binding Strength**

The free energy of binding describes the energy lost in the process of binding between a receptor and ligand. The greater the amount of energy lost, the more stable the binding. Highest binding strength was found to be **-8.72 kcal/mol**, followed by **-8.54 kcal/mol**.

*** Binding Site**

The region of binding for the ligand is another crucial parameter for the binding. Honokiol was found to bind in an opening in CB1, thus forming a secure binding. The region of binding is highlighted in **Figure 6**.

![](https://static.igem.wiki/teams/4963/wiki/screenshot-2023-10-09-160019-figure4.png)

*Figure 4: 3D-model of honokiol (magenta) binding to truncated CB1 protein. Created on PyMOL.*

*** Engineering Advantages: CB1 - modified**

1. Removal of **redundant** domains allows for more directed binding.
2. Reduction of **alternative binding sites**  for other biological agents, which may interfere with the system.
3. Increase in the probability of **competitive inhibition/release** of honokiol by AM - 6538, due to restriction to a smaller space.

*** Modification**

The excess domain in the CB1 sequence was removed using the delete feature on PyMOL. The domain was identified as the separate floating lobe opposite the free end (as against the binding end) of the primary group. The resultant is a coherent cylindrical structure functioning as the receptor, which is easier to engineer and fuse with other components.

*** Testing and Verification**

Extraction (in vivo):

The modified CB1 construct was obtained from  **GenScript** in cloning plasmid  **pUC57** with the restriction site specified against the type II restriction enzyme **EcoRV**. The plasmid  **pET28a**  is determined to be suitable for transfer and expression of CB1. Both plasmids are digested with EcoRV. For both plasmids, 1µl of sample was digested against 1µl

EcoRV in a 30µl reaction set for 4 hours. However, no bands were obtained for pET28a, while pUC57 was undigested.
The amount of plasmid was then increased 8µl to increase the probability of digestion. This time, pET28a was digested and a proper band obtained, however, pUC57 was still undigested.

The procedure was then repeated, with the reaction set for 8 hours. Negative results were obtained. The reaction was again repeated, now set for 12 hours, but to no avail.
In consultation with the company, the restriction targets were modified to **EcoR1** and **HindIII**. 1 µl each of both enzymes was used to digest 8 µl pET28a and 1ul pUC57. Both constructs were successfully digested.
For detailed procedure, kindly refer to the [Experiments](%7B%7Burl_for%28%27pages%27%2C%20page%3D%27experiments%27%29%7D%7D) page.
![](https://static.igem.wiki/teams/4963/wiki/screenshot-2023-10-10-010101-figure5.png)

*Figure 5: Restriction Digestion with EcoR1 and HindIII; gel electrophoresis results shown. pUC57 (digested) shown in lane1. Lane 5 shows positive control. Upper band in lane1 (red) is empty pUC57, at 2710bp. Lower band in lane1 is CB1, at 1083bp.*

### Release Mechanism

To release the small molecule at the tumor site for effective penetration, a release trigger is required.

**- Specifications we looked at:**

Once the drug is localized at the tumor site by the receptor system, it must be released in order to effectively penetrate the tumor microenvironment and inhibit STAT3. The key features of such a release mechanism are defined by the receptor and the primary drug. Furthermore, a release agent non-native to the human body is crucial so as to avoid accidental or uncontrolled release of the drug. We also talked to multiple experts about one of the major problems with chemotherapy - which is **unwarranted side effects**. To combat this, we thought of the following components:

1. Antagonist: an antagonistic small molecule to competitively bind to the receptor and release the drug.
2. Antagonist delivery:
   1. **Time displaced action:** the antagonist may be freely injected a specified time period after the introduction of the main vector, allowing the T-cell vectors to be localized at the tumor site.
   2. **Nano-particle: A guided small molecule carrier with release at the tumor site** A guided small molecule carrier with release at the tumor site

**- Candidates:**

1. Antagonist: enzymatic
2. Antagonist: **AM - 6538 (small molecule)**
3. Antagonist Delivery:
   1. Timing mode of introduction
   2. Nano-particle

**- Engineering Advantages**

1. AM - 6538

AM - 6538 is a known cannabinoid antagonist with high affinity for CB1 receptors[11](#references).
 A structural analog of rimonabant, the small molecule is an ideal model for a competitive release agent against honokiol.

2. Timing mode of delivery

In order to ensure effective delivery and release of the drug, a time gap must be put between the administration of the primary drug and the release agent. This period allows the primary drug carrying vectors to accumulate at the tumor site and localize. When the release agent is introduced, it now only releases the primary drug at the tumor site, thus preventing out of site release. Furthermore, the drug release is almost simultaneous due to the prior accumulation, allowing for better concentration of the dosage.

**- Testing and Verification**

Binding studies between CB1 and AM - 6538 were performed on Autodock and  **Molecular Dynamic Simulations** to determine efficiency of binding. Kindly refer to the Docking section of our [Model](%7B%7Burl_for%28%27pages%27%2C%20page%3D%27model%27%29%7D%7D) page for detailed results.

Parameters:

1. Binding efficiency
2. Binding sites

**Results:**

* **Binding energy of the antagonist must be higher than honokiol to CB1.** Best scores for binding energy obtained from Autodock are **-14.6 kcal/mol** and **-14.27 kcal/mol** , found to be much better than honokiol at **-8.72 kcal/mol** and **-8.54 kcal/mol.**
* **Binding sites for high scores are found to be coincidental for honokiol and AM - 6538.** Figure 6 demonstrates the binding regions for honokiol and AM - 6538.
* **Binding energy of the antagonist with a receptor-drug complex must be significantly high.** Binding energy scores of **-11.36 kcal/mol**and **-10.35 kcal/mol** are obtained on Autodock, indicating highly favorable competitive binding.

![](https://static.igem.wiki/teams/4963/wiki/screenshot-2023-10-09-162747-figure6-1.png)
![](https://static.igem.wiki/teams/4963/wiki/screenshot-2023-10-09-163043-figure6-2.png)

*Figure 6: Comparative images of CB1 binding with 1. Honokiol and 2. AM - 6538. Only Specific binding regions are shown. Created on PyMOL.*

### Vector

*** Specifications we looked at:**

A specific vector is required to deliver the drug precisely to the tumor site, while carrying an extracellular element (honokiol) on it. It should also express and sustain the receptor associated with the drug. Furthermore, the vector should localize at the tumor site to allow effective drug release.

*** Candidates:**

T - cells from the patient.

*** Egineering Advantages: T - cells**

T - cells provide natural specificity to the delivery mechanism as to the location of the tumor. This helps avoid out of site release while also reducing the time required for drug delivery. Furthermore, T - cells naturally localize at the tumor site, thus functioning as an anchor for drug release. T - cell accompaniment also ensures that immunological action initiates parallel to tumor dispersion, thereby increasing the potency of the treatment.

### Anchorage

**- Specifications we looked at:**

With the drug, receptor and vector determined, a final component is required to adhere them all together. As the small molecule is not naturally occurring and cannot be expressed by a cell, it must be carried by the cell externally. Therefore, the receptor must be expressed on the cell surface. Moreover, the receptor must be anchored to the cell surface. To this end, a fusion protein with cell surface expression is required.

**- Candidates:**

Two prominent surface expression vehicles are identified: [Ice Nucleation Protein N (INP - N)](http://parts.igem.org/Part%3ABBa_K3279006)and Lipoprotein Outer membrane protein A (Lpp - OmpA)[12](#references).

**- Engineering Advantages: INP - N**

The INP protein is a bacterial surface protein generally expressed in Gram negative bacteria. The general InaK protein comprises three major components: a hydrophobic N - domain, the Central repeated Domain (CRD) template and the hydrophilic C - domain. This functions as a well-defined surface expression vehicle[13](#references).

**- Optimization**

The load of the carrier is further optimized to a truncated sequence [INPN](http://parts.igem.org/Part%3ABBa_K3279006), developed by [iGEM19\_CAU\_China team.](https://2019.igem.org/Team%3ACAU_China/Parts)
It comprises an inbuilt anchoring domain (N - domain) to allow for surface expression, while an attached linker sequence allows it to fuse to the receptor (CB1). Furthermore, the sequence is very short, making it easy to obtain and engineer.

[* Engineering Objectives](#top-eng)
[* Primary Target](#primary)
[* Targeting Agent](#agent)
[* Delivery Mechanism](#delivery)
[* Receptor](#receptor)
[* Release Mechanism](#release-mech)
[* Vector](#vector-eng)
[* Anchorage](#anchorage)

## References

---

1. Chen N, Li X, Chintala NK, Tano ZE, Adusumilli PS. Driving CARs on the uneven road of antigen heterogeneity in solid tumors. Curr Opin Immunol. 2018 Apr;51:103-110. doi: 10.1016/j.coi.2018.03.002. Epub 2018 Mar 16. PMID: 29554494; PMCID: PMC5943172.  [(Link)](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5943172/)
2. Ferreira IG, Carrascal M, Mineiro AG, Bugalho A, Borralho P, Silva Z, Dall'olio F, Videira PA. Carcinoembryonic antigen is a sialyl Lewis x/a carrier and an E‑selectin ligand in non‑small cell lung cancer. Int J Oncol. 2019 Nov;55(5):1033-1048. doi: 10.3892/ijo.2019.4886. Epub 2019 Sep 26. PMID: 31793656; PMCID: PMC6776192.  [(Link)](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6776192/)
3. Cho YS, Kim CH, Ha TS, Ahn HY. Inhibition of STAT3 phosphorylation by sulforaphane reduces adhesion molecule expression in vascular endothelial cell. Can J Physiol Pharmacol. 2016 Nov;94(11):1220-1226. doi: 10.1139/cjpp-2015-0150. Epub 2015 Nov 18. PMID: 27681094.  [(Link)](https://pubmed.ncbi.nlm.nih.gov/27681094/)
4. Serrano-Gomez, S.J., Maziveyi, M. & Alahari, S.K. Regulation of epithelial-mesenchymal transition through epigenetic and post-translational modifications. Mol Cancer 15, 18 (2016).  [(Link)](https://doi.org/10.1186/s12943-016-0502-x)
5. Liu Z, Ma L, Sun Y, Yu W, Wang X. Targeting STAT3 signaling overcomes gefitinib resistance in non-small cell lung cancer. Cell Death Dis. 2021 May 31;12(6):561. doi: 10.1038/s41419-021-03844-z. PMID: 34059647; PMCID: PMC8166856.  [(Link)](https://pubmed.ncbi.nlm.nih.gov/34059647/)
6. Lamouille, Samy, et al. “Molecular Mechanisms of Epithelial–Mesenchymal Transition.” Nature Reviews Molecular Cell Biology, vol. 15, no. 3, Mar. 2014, pp. 178–96.  [(Link)](https://pubmed.ncbi.nlm.nih.gov/24556840/)
7. Mulu Geletu, Stephanie Guy, Rozanne Arulanandam, Hélène Feracci & Leda Raptis (2013) Engaged for survival, JAK-STAT, 2:4, DOI:  [(Link)](https://doi.org/10.4161/jkst.27363)
8. Meissl, K., Macho-Maschler, S., Müller, M. and Strobl, B., 2017. The good and the bad faces of STAT1 in solid tumours. Cytokine, 89, pp.12-20.  [(Link)](https://www.sciencedirect.com/science/article/pii/S1043466615300995)
9. Pan J, Lee Y, Zhang Q, Xiong D, Wan TC, Wang Y, You M. Honokiol Decreases Lung Cancer Metastasis through Inhibition of the STAT3 Signaling Pathway. Cancer Prev Res (Phila). 2017 Feb;10(2):133-141. doi: 10.1158/1940-6207.CAPR-16-0129. Epub 2016 Nov 14. PMID: 27849557; PMCID: PMC6005650.  [(Link)](https://pubmed.ncbi.nlm.nih.gov/27849557/)
10. Lin Y, Li Y, Zeng Y, Tian B, Qu X, Yuan Q and Song Y (2021) Pharmacology, Toxicity, Bioavailability, and Formulation of Magnolol: An Update. Front. Pharmacol. 12:632767. doi: 10.3389/fphar.2021.632767  [(Link)](https://www.frontiersin.org/articles/10.3389/fphar.2021.632767/full)
11. Paronis CA, Chopda GR, Vemuri K, Zakarian AS, Makriyannis A, Bergman J. Long-Lasting In Vivo Effects of the Cannabinoid CB1 Antagonist AM6538. J Pharmacol Exp Ther. 2018 Mar;364(3):485-493. doi: 10.1124/jpet.117.245647. Epub 2018 Jan 8. PMID: 29311110; PMCID: PMC5803641.  [(Link)](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5803641/)
12. Earhart CF. Use of an Lpp-OmpA fusion vehicle for bacterial surface display. Methods Enzymol. 2000;326:506-16. doi: 10.1016/s0076-6879(00)26072-2. PMID: 11036660.  [(Link)](https://pubmed.ncbi.nlm.nih.gov/11036660/)
13. Li Q, Yan Q, Chen J, He Y, Wang J, Zhang H, Yu Z, Li L. Molecular Characterization of an Ice Nucleation Protein Variant (InaQ) from Pseudomonas syringae and the Analysis of Its Transmembrane Transport Activity in Escherichia coli. Int J Biol Sci 2012; 8(8):1097-1108. doi:10.7150/ijbs.4524.  [(Link)](https://www.ijbs.com/v08p1097.htm)

{% endblock %}

{% extends "layout.html" %}
{% block title %}Experiments{% endblock %}
{% block lead %}Describe the research, experiments, and protocols you used in your iGEM project.{% endblock %}
{% block page\_content %}

# EXPERIMENTS

![](https://static.igem.wiki/teams/4963/wiki/images/campus.jpg)

---

## Competent Cell Preparation:

* Grow E. coli DH5ɑ/BL21 culture in 5 mL of LB broth from a single colony from a plate for 12 hours at 37℃ and 120 rpm.
* Inoculate 1% inoculum from the overnight culture into 20 mL of LB broth and grow till the OD600 is 0.4-0.5.
* Harvest the cells by centrifuging the culture at 5,000 rpm for 10 mins at 4℃.
* Wash the cell pellet with 5 mL of ice cold freshly prepared 75 mM CaCl2 solution.
* Harvest the cells by centrifuging the culture at 5,000 rpm for 10 mins at 4℃.
* Resuspend the pellet in 5 mL of ice cold CaCl2 solution and keep on ice for 30 mins.
* Harvest the cells by centrifuging the culture at 5,000 rpm for 10 mins at 4℃.
* Resuspend the pellet in 500 𝜇L of ice cold CaCl2 solution. Store on ice.
* Cells will become competent after 16-19 hrs.

---

## Restriction Digestion:

* Combine the following in a PCR or Eppendorf tube:
  + DNA (ideally around 0.4 - 0.6 𝜇g)
  + 3 𝜇L Enzyme-specific 10x buffer
  + 1 𝜇L Restriction Enzyme
  + H2O to make up volume till 30 𝜇L
* Incubate at 37℃ overnight

---

## Gel Extraction:

* Done using Qiagen’s QIAquick® Gel Extraction Kit. Alternate protocols may be there based on the kit used

---

## Ligation:

* Combine the following in a PCR or Eppendorf tube:
  + Vector DNA
  + Insert DNA
  + 3 𝜇L 10x Ligase Buffer
  + 0.5-1 𝜇L T4 DNA Ligase (depending on DNA concentration)
  + H2O to make up volume till 30 𝜇L
* Incubate at room temperature at 16 - 18°C overnight

---

## Transformation:

* Add 3-5 𝜇L of the insert DNA to 50 𝜇L of competent cells. Keep on ice for 30 mins.
* Give it a heat shock for 30 secs at 42℃.
* Keep it on ice for 15 mins.
* Add 1 mL of LB broth and incubate at 37℃ for 1 hr.
* Harvest the cells at 2,500 rpm for 1-2 mins and resuspend the pellet 1/5th of the supernatant.
* Spread on a LA antibiotic plate and incubate at 37℃.
* Observe colonies after 12 hrs.

---

## Plasmid Isolation:

* Centrifuge 2 mL of overnight culture at 2000g for 10 mins at 4℃.
* Discard the supernatant and resuspend the pellet in 100 𝜇L of ice cold Alkali Lysis Solution-I. Mix by vigorous vortexing.
* Add 200 𝜇L of freshly prepared ice cold Alkali Lysis Solution-II. Mix by inverting the tube 5-6 times.
* Immediately add 150 𝜇L of Alkali Lysis Solution-III. Disperse by rapidly inverting the tube several times. Incubate on ice for 5 mins.
* Centrifuge at 1200 rpm for 6 mins at 4℃.
* Transfer ~400 𝜇L of the supernatant to a fresh 1.5 ml eppendorf tube.
* Add 1.5 𝜇L of RNase A. Incubate at 37℃ for 1 hr.
* Add an equal volume of Phenol:Chloroform:Isoamyl alcohol (25:24:1). Mix by vigorous vortexing.
* Centrifuge at 12,000 rpm for 3 mins at 4℃.
* Transfer the aqueous layer to a fresh 1.5 mL eppendorf tube and add an equal volume of isopropanol at room temperature. Mix and allow to stand.
* Centrifuge at 12,000 rpm for 6 mins at room temperature.
* Discard the supernatant and add 250 𝜇L of 70% ethanol.
* Centrifuge at 7,500 rpm for 5 mins at room temperature.
* Air dry, then dissolve in 30 𝜇L nuclease-free water.

{% endblock %}

{% extends "layout.html" %}
{% block title %}Results{% endblock %}
{% block lead %}You can describe the results of your project and your future plans here.{% endblock %}
{% block page\_content %}

## What should this page contain?

---

* Clearly and objectively describe the results of your work.
* Future plans for the project.
* Considerations for replicating the experiments.

## Describe what your results mean

---

* Interpretation of the results obtained during your project. Don't just show a plot/figure/graph/other, tell us what you think the data means. This is an important part of your project that the judges will look for.
* Show data, but remember **all measurement and characterization data must also be on the Part's Main Page on the [Registry](http://parts.igem.org/Main_Page).** Otherwise these data will not be in consideration for any medals or part awards!
* Consider including an analysis summary section to discuss what your results mean. Judges like to read what you think your data means, beyond all the data you have acquired during your project.

## Project Achievements

---

You can also include a list of bullet points (and links) of the successes and failures you have had over your summer. It is a quick reference page for the judges to see what you achieved during your summer.

* A list of linked bullet points of the successful results during your project
* A list of linked bullet points of the unsuccessful results during your project. This is about being scientifically honest. If you worked on an area for a long time with no success, tell us so we know where you put your effort.

## Inspirations

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* [2019 Newcastle](https://2019.igem.org/Team%3ANewcastle/Results)
* [2019 Munich](https://2019.igem.org/Team%3AMunich/Results)
* [2019 Tec Chihuahua](https://2019.igem.org/Team%3ATec-Chihuahua/Results)
* [2020 Aalto Helsinki](https://2020.igem.org/Team%3AAalto-Helsinki/Results)
* [2020 GreatBay SCIE](https://2020.igem.org/Team%3AGreatBay_SCIE/Results)
* [2020 Queens Canada](https://2020.igem.org/Team%3AQueens_Canada/Results)

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