iGEM 2024 — Team tuebingen

{% 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 %}
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## Week 1

22.02.24 Weekly team meeting, Research Project ideas

## Week 2

29.02.2024 Weekly team meeting, Research Project ideas

## Week 3

07.03.2024 weekly Team meeting, decided on project idea, division into subteams

## Week 4

14.03.2024 weekly Team meeting, started PI search, research sponsors and grants

## Week 5

21.03.2024 weekly Team meeting, Contacted potential PIs, Identified family of model regulators (LuxR), collected data/papers

## Week 6

28.03.2024 weekly Team meeting, Experimental Design Team starts, project name brainstorming

## Week 7

04.04.2024 weekly Team meeting, First Human Practices meetings, preliminary modelling work with alphafold multimer, identified proof of concept paper and review, identified challenges

## Week 8

11.04.2024 weekly Team meeting, finished NarL/YdfI and OmpR/CcaR Alphafold modelling, started research into DCA. Collected literature for experimental design

## Week 9

18.04.2024 weekly Team meeting, Wetlab meeting, meeting with experts from VectorBuilder

## Week 10

25.04.2024 weekly Team meeting, wetlab meeting, meeting with Professor Hartmann regarding structural modelling (24.04.2024), applied to grants and sponsorships, contacted Faktor 14 and Experimenta

## Week 11

02.05. weekly Team meeting, meeting with PI Professor Kronenberger, DCA reveals first promising results, crystal structure analysis, journal club

## Week 12

16.05.2024 weekly Team meeting, application to promega grant

## Week 13

23.05.2024 weekly Team meeting, further Alphafold modelling, initial trial MD simulations, research into mode of action of regulators, finalized design, iGEM meetup Bielefeld

## Week 14

31.05.2024 weekly Team meeting, Research into structural families of regulators, Inventory of our lab supplies, search for labspace

## Week 15

06.06.2024 weekly Team meeting, 05.06 Meeting with Professor Stegmann regarding applications of our technique, Wetlab meeting, ordered Lab supplies, contacting further sponsors, wrote Faktor 14 article

## Week 16

13.06.2024 weekly Team meeting, drylab meeting, development/exploration of Direct coupling based metrics, social media collaboration with iGEM team ULAVAL, member posts on instagram

## Week 17

20.06.2024 weekly Team meeting, first prototype of DDIZ metric, rework Faktor 14 draft, setup collaboration with Mindful Science, finalize logo

## Week 18

27.06.2024 weekly Team meeting, refined DDIZ metric, finalize portfolio

## Week 19

04.07.2024 weekly Team meeting, investigation into structural correlations of DDIZ metric, investigation of linker conservation, meeting with PI Professor Kronenberger

## Week 20

11.07.2024 weekly Team meeting, analysis of conservation of DDIZ pattern across regulators, structural analyses

## Week 21

18.07.2024 weekly Team meeting, started work on webservice to make DDIZ score usable for everyone, started further literature review, started work on modelling clashes in active state of regulator.

## Week 22

25.07.2024 weekly Team meeting

## Week 23

01.08.2024 weekly Team meeting, further structural analyses, experiment planning

## Week 24

08.08.2024 weekly Team meeting, finish first webservice prototype

## Week 25

15.08.2024 weekly Team meeting, Wetlab meeting

## Week 26

26.08 weekly Team meeting, meeting with Professor Hartmann regarding modelling, increased performance using ESM, exploratory analysis of 50% similarity clustered Dataset, meeting with Professor Stegmann

## Week 27

05.09.2024 weekly Team meeting, meeting with Professor Ziemert regarding feedback for the webtool, meeting with Professor Stegmann and Dr. Muth regarding experimental design, ordered Lab supplies and plasmids

## Week 28

12.09.2024 weekly Team meeting, Coordinate wetlab and wiki documentation tasks , wetlab meeting

## Week 29

26.09.2024 weekly Team meeting, Started Labwork, finished gibson assembly, transformation and screening for insert, tried induction

## Week 30

02.10.2024 finish iGEM wiki and upload finalized ClusterControl

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{% extends "layout.html" %}
{% block title %}Engineering Success{% endblock %}
{% block lead %}Demonstrate engineering success in a technical aspect of your project by going through at least one iteration of the engineering design cycle. This achievement should be distinct from your Contribution for Bronze.{% endblock %}
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## Engineering Success: ClusterControl

---

The idea for our project originated from the need to simplify the complex process of regulating biosynthetic gene clusters.
With over 100,000 biosynthetic gene clusters identified and only a fraction explored, it became clear that their full potential remained largely untapped.
To address this, we developed **ClusterControl**—an integrated, scalable web tool that empowers researchers to optimize the regulatory networks within these clusters.
By significantly reducing the time spent on trial-and-error testing of rewired regulator proteins, **ClusterControl** streamlines the discovery and manipulation of biosynthetic gene clusters.

## Design Phase

### Drylab Design

Our primary objective was to create a flexible platform capable of precisely controlling gene cluster expression.
Upon analyzing existing approaches, we found that the main obstacle was the unpredictability of native regulatory elements, which often respond to unknown signals.
To overcome this, we focused on developing a modular framework that leverages **rewired regulatory proteins** capable of responding to well-characterized and customizable signals.

We began by building a robust database of regulatory domains from the **Helix-Turn-Helix (HTH) family**, known for their modularity and flexibility.
Each domain was annotated with its **binding preferences** and **signal-sensing capabilities**.

A major challenge we faced in designing functional rewired bacterial regulators was identifying the optimal **rewiring points**.
This issue became the foundation for developing **ClusterControl** as the culmination of our prior research.

### Evolutionary and Structural Analysis

We explored various approaches to predict optimal rewiring points, including **Alphafold2** predictions of structural complexes between regulatory proteins and their associated promoters, as well as **evolutionary analyses**.

Using **NarL** from *E. coli* and **YdfI** from *B. subtilis* as a model, we tested different rewiring points.
A significant correlation was found between the **DDIZ scores** and the experimentally measured **regulatory activity** of multiple rewiring points in this chimeric regulator.
This validation demonstrated the predictive power of **ClusterControl’s** metrics, supporting its utility in designing functional chimeric regulators.

1. We conducted **BLAST searches** against a custom database of LuxR-family HTH regulators, clustered at 50% sequence similarity.
2. Using multiple sequence alignments for regulators with 20-80% sequence similarity, we constructed a **Direct Information (DI) matrix**, quantifying evolutionary couplings between amino acids.
3. To enhance the accuracy, we filtered the data using **Z-scores** within three standard deviations, highlighting **Disrupted Direct Information (DDI) points**—areas where potential rewiring would disrupt evolutionary couplings.

We developed a new metric called **DDIZ (Disrupted Direct Information Z-scored)**, where a lower score suggests minimal disruption, and thus, optimal rewiring points.
The correlation between DDIZ scores and experimental data provides strong validation for the tool.

**Figure 1:** ![Visual representation of DDI points](https://static.igem.wiki/teams/5486/narl-ydfi-ddiz.png)Visual representation of DDI points

**Figure 2:** ![Graph showing correlation between DDIZ scores and activity](https://static.igem.wiki/teams/5486/narl-ydfi-correlation.png)Graph showing correlation between DDIZ scores and activity

### Structural Validation

To further validate our predictions, we performed **structural analysis using PyMOL**, which showed that optimal rewiring points align with the start of stable beta-sheet or alpha helix regions in **Winged Helix-Turn-Helix and tetra helical bundle regulators respectively**.
This confirmed that modular swaps can be made without compromising protein integrity. Additionally, we incorporated **ESM-based contact maps** to speed up initial screenings, representing a performance improvement for initial assessments.

**Figure 3:** ![structural visualization of DDIZ score](https://static.igem.wiki/teams/5486/narl-ddiz-structure.jpeg)structural visualization of DDIZ score

## ClusterControl Development

---

**ClusterControl** is the result of these engineering insights and provides researchers with an intuitive, scalable platform.
It combines a **Wiki** and **Database**, where researchers can share and access information on regulators.
This community-driven aspect of **ClusterControl** will grow into a valuable resource on bacterial Helix-Turn-Helix regulators.
Additionally, users can upload their own protein sequences and use the tool to predict optimal rewiring points.

**ClusterControl** is built using **MongoDB**, **Flask**, and is deployable via **Docker** for seamless, scalable deployment.
By allowing researchers to design rewired regulators with customizable signals, it greatly accelerates the research process in synthetic biology.

**Figure 4:** ![ClusterControl workflow](https://static.igem.wiki/teams/5486/cluster-control-msa-workflow.jpeg)ClusterControl workflow

**Figure 5:** ![Web interface showing the process of visualizing DDIZ scores](https://static.igem.wiki/teams/5486/new-rewiring-interface.jpeg)Web interface showing the process of visualizing DDIZ scores

## Wet Lab Validation

### Build

The **ClusterControl** interface was designed to be clean and user-friendly, guiding researchers through the design process.
Users can upload sequences, select from a library of regulatory domains, and use our predictive models to simulate regulatory interactions.
During the build phase, users receive visual representations of **DDIZ scores**, aiding their decision-making process.

### Test

To validate **ClusterControl**, we tested it against experimental data from other researchers. Initial benchmarking results were encouraging, and we are currently conducting our own experimental validations to provide direct feedback.
These tests will offer deeper insights into how the tool performs with **novel constructs**.

The final stage was to validate these predictions experimentally. We are currently testing the predicted fusion points in the lab, focusing on whether the chimeric constructs retain their functionality. The experimental data will further confirm the modularity.

### Learn

As with any engineering project, we encountered setbacks. The most significant learning points included the need to integrate both **computational predictions** and **structural analysis** to define more accurate modular swaps.
The **DDIZ metric**, combined with **fluorescence data**, provided a clearer view of how rewired proteins perform in practice.

**Figure 6:** ![Structural modelling of OmpR in Complex with EnvZ](https://static.igem.wiki/teams/5486/structural-modelling-ompr.jpeg)Structural modelling of OmpR in Complex with EnvZ along with functional/nonfunctional points marked

One of the key takeaways was the necessity for a **user-friendly interface**.
Early users struggled with the complexity of the design options, prompting us to simplify and streamline the interface to accommodate researchers of varying experience levels.

## Future Directions

---

Moving forward, we will continue refining **ClusterControl** by addressing discrepancies between **DDIZ scores** and **functional outcomes**, expanding the tool’s capabilities, and incorporating user feedback from researchers across diverse fields.
Through these iterations, we aim to create a comprehensive tool that empowers scientists to unlock the full potential of biosynthetic gene clusters.

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

1. Thaw all reagents completely on ice.
2. Add 1 μl of ligation reaction to thawed competent cells (E. coli NEB5α) and gently mix by tapping tube.
3. Incubate on ice for 30 min.
4. Heatshock for 45s at 42°C in heat block.
5. Incubate for 2 min on ice.
6. Fill to 950 μl with LB medium.
7. Incubate at 37°C and shake at 250 rpm for 1 h.
8. EITHER transfer into more LB medium and let grow overnight at 37°C while shaking,
9. OR spread on selection plate and incubate overnight at 37°C.

## Plasmid Isolation with Plasmid Miniprep Kit (Monarch NEB)

1. Pellet 1–5 ml bacterial culture by centrifugation for 30 seconds. Discard supernatant.
2. Resuspend pellet in 200 μl Plasmid Resuspension Buffer (B1). Ensure cells are completely resuspended.
3. Add 200 μl Plasmid Lysis Buffer (B2), invert 5–6 times, incubate for 1 minute at room temperature.
4. Add 400 μl Plasmid Neutralization Buffer (B3), invert gently, incubate for 2 minutes.
5. Centrifuge lysate for 2–5 minutes. Transfer supernatant to spin column and centrifuge for 1 minute.
6. Add 200 μl of Plasmid Wash Buffer 1, centrifuge for 1 minute. Discard flow-through.
7. Add 400 μl of Plasmid Wash Buffer 2, centrifuge for 1 minute.
8. Transfer column to clean microfuge tube, add ≥30 μl DNA Elution Buffer, incubate 1 minute, centrifuge for 1 minute.

## Glycerol Stock Preparation

1. Prepare a liquid culture by incubating a bacterial sample in 5-10 ml LB medium overnight.
2. Dilute glycerol with distilled water to create a 50% glycerol solution.
3. Transfer 750 μl of the glycerol solution into a microfuge tube.
4. Add 750 μl of bacterial culture to the microfuge tube.
5. Close lid, mix gently, and freeze at –80°C.

## Cast & Run Electrophoresis Gel

1 L 50x TAE Buffer:

1. Tris base 2M (242 g)
2. Acetic acid 1M (57 ml)
3. EDTA 0.05 M (100 ml 0.5 M)
4. Fill up to 1 L with MilliQ H2O.

Dilute 50x TAE to 1x TAE for use.

1. Cast 50 ml 1% agarose gel (1g agarose, fill up to 100 ml with 1x TAE buffer).
2. Load gel, including at least one lane for a DNA ladder.
3. Run gel at 120V for 45 min.

## DNA Gel Extraction

Gel extraction using QIAgen DNA Gel extraction kit, [QIAGEN kit manual](https://www.qiagen.com/us/resources/resourcedetail?id=a72e2c07-7816-436f-b920-98a0ede5159a&lang=en).

## Q5 Polymerase DNA Amplification using PCR

PCR Mix:

| Component | Volume | Final Conc |
| --- | --- | --- |
| 5X Q5 Reaction Buffer (NEB) | 10 µl | 1X |
| dNTP Mix, 10 mM each | 1 µl | 0.2 mM each dNTP |
| Fwd primer | 2.5 µl | 0.5 µM |
| Rev primer | 2.5 µl | 0.5 µM |
| Q5® High-Fidelity DNA Polymerase | 0.5 µl | 0.02 u |
| DNA to be amplified | 1 µl | < 1,000 ng |
| ddH2O | 32.5 µl | – |
| Total | 50 µl | – |

PCR Program:

| Step | Temp/°C | Duration/sec | n repeats |
| --- | --- | --- | --- |
| Denaturation | 98 | 30 | 1 |
| Denaturation | 98 | 10 | 30 |
| Annealing | Depends on primers | 30 | 30 |
| Extension | 72 | 120 | 30 |
| Final Extension | 72 | 120 | 1 |
| Cooling | 7 | 120 | 1 |

## Colony PCR

Q5 reaction mix

| Component | Volume | Final Conc |
| --- | --- | --- |
| 5X Q5 Reaction Buffer (NEB) | 10 µl | 1X |
| dNTP Mix, 10 mM each | 1 µl | 0.2 mM each dNTP |
| Fwd primer | 2.5 µl | 0.5 µM |
| Rev primer | 2.5 µl | 0.5 µM |
| Q5® High-Fidelity DNA Polymerase | 0.5 µl | 0.02 u |
| ddH2O | 33.5 µl | – |
| Total | 50 µl | – |

1. Mix reaction mix for each colony to be analyzed.
2. Pick colony using disposable pipette tip.
3. Stab pipette tip onto replica plate and note number.
4. Mix pipette tip in PCR mix.
5. Run PCR (see program above).
6. Analyze PCR using agarose gel to check if the expected insert was amplified.
7. Incubate replica plate overnight.

## Tetracycline Induction and Reporter Gene Assay

1. Add 10ng/μl Tetracycline to LB medium.
2. Add signal molecule to medium at the appropriate concentration to induce regulator activation.
3. Incubate at 37°C for 2-6 hours.
4. Image reporter gene assay using a microplate reader at the appropriate wavelength to induce reporter gene fluorescence (e.g., for GFP: 480 nm).

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{% extends "layout.html" %}
{% block title %}Results{% endblock %}
{% block lead %}You can describe the results of your project and your future plans here.{% endblock %}
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## Construction of Plasmid Vectors for Protein Expression

---

Using the Plasmid pSR357.24 as a base, we constructed two expression vectors using a restriction digest followed by Gibson assembly. The digest was performed by a double digest with Bsu36I, as well as EcoRI or BseRI, respectively. In one of the plasmids, we cut out an insert consisting of the already present rewired regulator NarL-YdfI, and in the other, we cut out NarL-YdfI along with its associated promoter PydfJ115.

We designed inserts consisting of the rewired regulators EL222-YdfI and NarL-LuxR. EL222-YdfI was inserted into the plasmid with the YdfI promoter PydfJ115 intact, while for NarL-LuxR, the promoter was replaced by pLuxR.

The plasmid backbones without the insert were purified by gel electrophoresis and extracted using a QIAGEN gel extraction kit.

**Figure 1:** ![Gel electrophoresis of plasmid backbones](https://static.igem.wiki/teams/5486/gel.png)Gel electrophoresis of plasmid backbones.

The inserts were manufactured as gBlocks by Integrated DNA Technologies. Full plasmids were assembled using NEB HiFi Gibson assembly and transformed into NEB5α (New England Biolabs) chemically competent cells. Colonies were selected on LB plates containing chloramphenicol.

After one day, colonies were picked and streaked onto induction plates containing chloramphenicol and 10ng/μl tetracycline. EL222 plates were illuminated with 470nm LEDs, and for NarL, sodium nitrate was added for induction. Unfortunately, none of the streaked colonies showed fluorescence under a 470nm light source.

**Figure 2:** ![Plates showing colony plating](https://static.igem.wiki/teams/5486/plates.jpg)Plates showing colony plating

## Project Achievements

---

Throughout the summer, we worked on designing a system for chimeric regulator construction with the goal of inducing specific gene expression via reporter genes.
While we were able to successfully assemble the plasmid and transform it into E.coli, which was evident from the numerous colonies in our cloning strain NEB5alpha, we were not able to observe any reporter gene activity in our experiments, including in the controls that we did not assemble ourselves but had instead ordered from addgene.
While this outcome was not what we had hoped for, it provided valuable insights into our experimental setup, assembly methods, and troubleshooting approaches. Below is a summary of both our achievements and the challenges we faced.
Our hypothesis for why our induction has failed so far are multiple, and we are currently planning on checking each untill the Jamboree. First, potentially our Tetracycline induction concentation was too low at 10ng/ul.
We are planning to induce again at 25ng/ul. Second, we plan to re screen our inserts. Third, we plan to do another gibson assembly, incase something went wrong with the first.
And lastly, we are trying to transform the assembled plasmid into a different strain of E.coli to test for induction again. In theory the NarX-NarL system should be active in DH5alpha derived strains, but as cloning strains they are not ideal protein producers.

* **Achievements:**
* Developed a fully functional [ClusterControl web tool](https://gitlab.igem.org/2024/software-tools/tuebingen) for predicting regulatory rewiring points.
* Conducted comprehensive experimental plans, with protocols and workflows established for DNA transformation, plasmid isolation, glycerol stock preparation, induction, and more.
* Integrated evolutionary analysis, structural analyses and the DDIZ metric into our predictive models, successfully nominating these methods for broader use in regulatory protein studies.

* **Challenges:**
* Failed to induce reporter gene activity in any of our experiments, including control experiments.
* Learned the importance of testing all experimental components (including positive controls) under real conditions.
* Observed possible issues with experimental timing, assembly accuracy, and transformation efficiency that we plan to address in future iterations.
* Recognized that troubleshooting efforts should include a wider range of experimental variables, including cell growth conditions, plasmid stability, and protein expression timing.

## Future Plans

---

Based on the results and challenges faced during this iGEM cycle, we have several future plans to improve and continue our work:

* Redesigning and troubleshooting the assembly process to ensure greater control over each step, focusing on identifying any potential bottlenecks in the reporter gene expression system.
* Incorporating additional validation points, including performing quantitative fluorescence measurements over time to detect even minimal reporter gene activity.
* Further development and application of the ClusterControl tool to explore new regulatory rewiring opportunities and refine predictions based on real experimental results.

## Considerations for Replicating the Experiments

---

For anyone attempting to replicate our experiments, we recommend closely monitoring the following factors:

* Ensure that all reagents (e.g., competent cells, transformation buffers) are fresh and handled with care to avoid contamination or degradation, especially the tetracycline used for induction. At these concentations even minimal degradation could lead to a loss of induction
* Use alternative protocols for transformation and plasmid assembly, such as different strains of E. coli or varying inducer concentrations.
* Pay attention to experimental timing, as issues with incubation periods, heat shock, or growth conditions could impact the final results.
* Incorporate rigorous controls, both positive and negative, to ensure that the lack of gene expression is due to experimental variables rather than assembly or plasmid stability issues.

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