iGEM 2025 — Team uni-padua-it

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# Notebook

The notebook is organized into clear sections that chronicle our journey through laboratory experiments. It includes experimental procedures to support and guide other teams in our research.

* [Computational Biology](#1st-pillar)
* [Yeast Model Testing](#2nd-pillar)
* [Mammalian Cells Validation](#3rd-pillar)

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## September '25

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If the PDF does not load, [open it in a new tab](https://static.igem.wiki/teams/5700/pdf/notebook-cell-free-benchling.pdf).

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## May - June '25

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If the PDF does not load, [open it in a new tab](https://static.igem.wiki/teams/5700/pdf/may-june-notebook-yeast.pdf).

## July '25

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If the PDF does not load, [open it in a new tab](https://static.igem.wiki/teams/5700/pdf/july-notebook-yeast.pdf).

## August '25

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If the PDF does not load, [open it in a new tab](https://static.igem.wiki/teams/5700/pdf/august-notebook-yeast.pdf).

## September - October '25

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If the PDF does not load, [open it in a new tab](https://static.igem.wiki/teams/5700/pdf/september-october-notebook-yeast-new.pdf).

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## April '25

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If the PDF does not load, [open it in a new tab](https://static.igem.wiki/teams/5700/pdf/april-notebook-mammalian-benchling.pdf).

## May '25

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If the PDF does not load, [open it in a new tab](https://static.igem.wiki/teams/5700/pdf/may-notebook-mammalian-benchling.pdf).

## June - July '25

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If the PDF does not load, [open it in a new tab](https://static.igem.wiki/teams/5700/pdf/june-july-notebook-mammalian-benchling.pdf).

## August '25

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If the PDF does not load, [open it in a new tab](https://static.igem.wiki/teams/5700/pdf/august-pt1-notebook-mammalian-benchling.pdf).

If the PDF does not load, [open it in a new tab](https://static.igem.wiki/teams/5700/pdf/august-pt2-notebook-mammalian-benchling.pdf).

If the PDF does not load, [open it in a new tab](https://static.igem.wiki/teams/5700/pdf/august-pt-3notebook-mammalian-benchling.pdf).

## September - October '25

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If the PDF does not load, [open it in a new tab](https://static.igem.wiki/teams/5700/pdf/september-october-notebook-mammalian-benchling.pdf).

[← Prev](%7B%7B%20url_for%28%27pages%27%2C%20page%3D%27contribution%27%29%20%7D%7D#3rd-pillar "Go to Contribution – Mammalian Cells Validation")

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# Engineering

This page documents our DBTL journey across computational biology, yeast testing, and mammalian validation. We modeled progerin (including farnesyl constraints), designed and docked selective interactors, refined structures via relaxation pipelines and benchmarked selectivity versus lamin A; in parallel, we built Y2H constructs, optimized cloning and CFPS and adapted cell models to achieve robust expression and transfection converging on targeted progerin degradation.

* [Computational Biology](#1st-pillar)
* [Yeast Model Testing](#2nd-pillar)
* [Mammalian Cells Validation](#3rd-pillar)

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## Cycle 1.1: Progerin fragmentation

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### Design

At the outset of our project, we faced a major challenge: **the absence of experimental structural data for the C-terminus of progerin**. This region is **intrinsically disordered**, making it inaccessible to crystallography and only marginally informative through cryo-EM. To overcome this limitation, we employed **AlphaFold3** to predict the structure of progerin, using these models as an initial indication of the possible conformations of the C-terminal region and as a starting point for our computational strategy.

### Build

To address this challenge, we established a **computational pipeline** that integrates different levels of modeling and analysis. Our approach combines **AI-based structure prediction and design with molecular docking and affinity estimation** to enhance the design process. Specifically, AlphaFold3, RFdiffusion, and ProteinMPNN were used in succession for structural modeling, binder backbone generation, and sequence design, while HADDOCK and ClusPro were applied for docking simulations, followed by PRODIGY for the estimation of binding affinities. The pipeline was conceived to move from **structural modeling and refinement** of the target, through the **design of potential binders**, and finally to the **evaluation of their interactions**, providing an integrated framework for iterative improvement.

### Test

We applied this pipeline by generating **full-length structural predictions of progerin** using AlphaFold3 and analyzing the outputs with Predicted Alignment Error (PAE) plots. Most of the protein was modeled with high confidence, with well-defined regions showing strong cross-correlation. In contrast, the **C-terminal region displayed very low confidence**, consistent with its intrinsically disordered nature. This confirmed that AlphaFold was **unable to assign a stable fold to this segment**, leaving a crucial gap in the model and highlighting the need for a refined approach.

### Learn

At this point, we sought expert advice to interpret our results and improve our strategy. Professor Roberto Steiner guided us through the analysis of the PAE plots, consulting with a researcher from DeepMind. Based on their input, **we shifted our focus to the isolated C-terminal region**, generating AlphaFold3 predictions of the **fragment at different lengths**. This modification improved the confidence values, which, although still moderate, produced more coherent conformations. However, because AlphaFold is context-dependent, these structures should not be viewed as definitive but rather as **snapshots of possible folding states**. Interpreting them as a library of candidate conformations enabled us to refine our computational pipeline and expand the set of potential interactors to be designed against progerin.

## Cycle 1.2 – Progerin Fragmentation

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### Design

Building upon the limitations discovered in the first cycle, we refined our design approach.
In this cycle, we decided to focus on a series of **C-terminal fragments**. By narrowing the scope of the target region, we aimed to improve the reliability of the predicted structures.

### Build

We updated our pipeline to focus on the **C-terminal fragments** of progerin, as well as exploring **AlphaFold3’s capability to predict shorter fragments**. For the structural modeling, we still employed **AlphaFold3** predictions at varying fragment lengths. This fragment-focused design approach enabled us to improve the precision of predicted structures.

### Test

Structural outputs from **AlphaFold3** showed improved **PAE plots** with greater coherence in the folded conformations. While the confidence in the C-terminal region was still moderate, we observed clearer patterns and more stable structures compared to the first cycle.

### Learn

Narrowing our focus to the C-terminal fragment allowed us to obtain more reliable structural predictions and enabled us to design **better-targeted interactors**.
Additionally, the iterative process of generating multiple AlphaFold3 predictions for fragments of different lengths provided us with a **library of candidate conformations**. This not only improved our understanding of the C-terminal flexibility but also highlighted the need for **contextual interpretation** of the predicted models, treating them as **snapshots** rather than definitive structures.

## Cycle 2.1: Usage of Alphafold or SWISS-MODEL

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### Design

In the first stage of our structural prediction workflow for Progerin, we considered two different tools: **AlphaFold** and **SWISS-MODEL**. Our goal was to compare the structural outputs obtained from both approaches. These platforms rely on fundamentally different strategies: while SWISS-MODEL generates structures based on available templates in protein databases (homology modeling), AlphaFold predicts protein conformations *de novo* using deep learning and evolutionary information.

### Build

We performed structural predictions for both **Progerin** and **Lamin A** using SWISS-MODEL and AlphaFold.

### Test

Model validation was performed through **MolProbity** and by examining internal quality parameters (e.g., pLDDT and pTM for AlphaFold, GMQE and QMEAN for SWISS-MODEL).
SWISS-MODEL predictions exhibited **low confidence scores** and poor model coverage, likely due to the absence of suitable structural templates for Progerin in existing databases.
Conversely, **AlphaFold** produced **high-confidence structures**, capturing the overall domain organization and maintaining consistent secondary structure elements, making them more reliable for further applications such as docking and interactor design.

### Learn

Given the higher reliability of AlphaFold predictions, we selected **AlphaFold as our primary tool for structural prediction**.

## Cycle 2.2: Validation of AlphaFold Predictions

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### Design

Having selected AlphaFold as our primary tool for structural prediction due to its higher reliability, we adjusted the pipeline accordingly.

### Build

We performed structural prediction of full-length progerin and its C-terminal fragments with AlphaFold.

### Test

Model validation was carried out using MolProbity to check for structural quality, including the verification of stereochemistry, Ramachandran plot analysis, and potential clashes.

### Learn

Our analysis confirmed that the AlphaFold-predicted structures were better in terms of structural quality, and that we could proceed with further experimental work.

## Cycle 3.1 – Farnesylation Challenge

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### Design

One of our first challenges was to capture the three-dimensional structure of progerin, the mutant protein responsible for Hutchinson–Gilford Progeria Syndrome. A **key difference from lamin A is that progerin permanently retains its farnesyl group**, a small but crucial post-translational modification that anchors the protein to the nuclear membrane.
We realized that any attempt to design a specific interactor would be incomplete without accounting for this feature. For this reason, our design strategy started by **incorporating the farnesyl group into the predicted structures** of progerin, making the model as close as possible to its biological form.

### Build

After generating the initial structural model, we moved into “molecular carpentry.” Using **ChimeraX**, we carefully **attached the farnesyl group**—sourced from PubChem (entry 444108)—to the protein. This manual step was more than cosmetic: it was the moment where our predicted model began to resemble the biologically relevant form of progerin.

### Test

We then **processed our model** using the bioinformatic tools integrated into our pipeline for protein relaxation. To our surprise, **the system stalled**: post-translational modifications (PTMs) were a blind spot for these otherwise powerful algorithms. The **output was unusable**, highlighting an important limitation of current computational pipelines. In other words: we had built something too realistic for the software to handle.

### Learn

This obstacle became an opportunity. Instead of abandoning the PTM, we stepped back and asked ourselves: **what is the real effect of the farnesyl group on progerin?**
The answer: it acts as a **molecular anchor**, tethering the farnesyl–cysteine to the inner nuclear membrane and **reducing the local flexibility of the protein**. With this insight, we adapted our approach. By simulating the association between the farnesyl group and the nuclear membrane through **semi-flexible docking with restraints**, we struck a balance: the C-terminus remained fully flexible, except for the rigidly attached farnesyl–cysteine. Moreover, we excluded the farnesyl–cysteine from the **RFdiffusion hotspot definition** used for designing the interactors. This prevented the algorithm from incorrectly interpreting the chemical environment around the absent farnesyl group, thereby avoiding computational artifacts in the design of the interactors.
This adjustment transformed a computational limitation into a refined, biologically grounded model, paving the way for more reliable interactor design.

## Cycle 3.2 – Farnesyl-Constrained Modeling and Interactor Redesign

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### Design

Building on the insights from the first cycle, we redefined our structural approach. Instead of explicitly modeling the farnesyl group, we decided to represent its effect on local rigidity through **spatial restraints and reduced conformational freedom** at the C-terminal cysteine. Our goal was to create a model that realistically mimics the farnesyl-anchored configuration of progerin, while remaining compatible with computational tools such as AlphaFold3, RFdiffusion, and HADDOCK. We also revised the interactor design pipeline to ensure that generated peptides targeted **the accessible portion of the C-terminal region**, rather than the membrane-facing farnesylated site.

### Build

We implemented this design by introducing **positional restraints in the molecular docking stage to mimic membrane tethering**. The C-terminal cysteine was treated as a pseudo-anchored residue, while the remaining amino acids were free to relax naturally. At the same time, we updated the RFdiffusion and ProteinMPNN pipelines by explicitly excluding the terminal residues involved in membrane association from the diffusion hotspot definition. This modification guided the AI models to focus binding toward the biologically accessible surfaces of progerin.

### Test

We re-ran docking under these revised conditions. The resulting structures displayed **consistent folding** of the C-terminal tail, while maintaining compatibility with all downstream validation steps.

### Learn

Through this second cycle, we learned how to **translate biological realism into computationally tractable constraints**. By abstracting the physical effect of the farnesyl anchor instead of directly modeling it, we overcame a key bottleneck in AI-driven protein design workflows. This approach allowed us to preserve the biological relevance of progerin’s membrane association while unlocking full compatibility with modern prediction and docking platforms.

## Cycle 4.1: relax pipeline design

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### Design

In defining our pipeline, we anticipated the **need to relax the structure after prediction**, but we were uncertain about how to outline this necessary step. During the design phase, we decided to employ the two methods most accessible to us: **Amber** from the NeuroSnap package and **Rosetta Relax** from ROSIE. However, we were unsure how to use them and in which order.

### Build

We **performed structural relaxations** on the entire progerin structure and some fragments using Amber and RosettaRelax.

### Test

We validated the predicted structures using **MolProbity**, a widely adopted tool for structural quality assessment. We summarized some of our analyses and compared different relaxation methods ([Comparison of different relaxation methods](https://static.igem.wiki/teams/5700/pdf/comparison-of-different-relaxation-methods.pdf)). To evaluate the effect of relaxation, we first applied each tool independently and then tested combinations of both methods in sequence. This approach allowed us to identify not only the **improvements introduced by each tool** but also the optimal **order of application** for achieving the most reliable structural refinement.

### Learn

At the end of our analyses, we identified the most effective relaxation strategy to achieve both optimal energy minimization and a stereochemically sound structure. The best approach consisted of three consecutive steps: **Amber** → **RosettaRelax** → **Amber**. We compared the resulting models by evaluating their **MolProbity scores** and **energy values**.

## Cycle 4.2: Advanced Structural Refinement and Validation

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### Design

In the previous cycle, we established a relaxation pipeline to obtain an optimized structure for our goal. We decided to continue using the relaxation sequence **Amber → RosettaRelax → Amber**.

### Build

We applied the relaxation procedure to all the structures of Progerin and its fragments.

### Test

We performed a **new cycle of validation** for the relaxed structures, again using MolProbity to check the quality of the predicted structures. During this phase, we focused on **analyzing the improvements** introduced by each relaxation step and the combination of methods to ensure there were no artifacts or distortions. In this phase, we also analyzed the **energy progress in relation to structural stability**.

### Learn

We found that the relaxation sequence chosen in the previous cycle continues to **work effectively**. Our analysis confirmed that our **Amber → RosettaRelax → Amber** approach produces the best structures, which have been selected for subsequent docking studies and interactor design. Despite the good performance, we are considering the implementation of additional relaxation cycles, such as multiple iterations with Amber, to explore potential further improvements.

## Cycle 5: Identification of folding issues of the interactor in the presence of RING

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### Design

In this stage, we aimed to assess how the fusion of our interactors with the **RING domain** affected their structure and binding performance.
To ensure consistency with previous analyses, we applied the same **computational pipeline** and **docking methodology** established in earlier cycles, this time integrating the RING domain into the constructs.
This step was essential to understand whether the addition of RING influenced the folding stability and binding specificity of the interactors toward **progerin** and **lamin A**.

### Build

All selected interactors were re-processed through our structural workflow, now including **structure prediction with the RING domain**, **relaxation**, **validation**, and **docking simulations** against both target proteins.
Each model was evaluated through standardized quality parameters to ensure cross-dataset comparability and to detect any RING-related conformational effects.

### Test

Docking outputs were analyzed using **binding affinity (Kd)** as the primary quantitative descriptor.
For each fusion construct, we calculated **the Kdratio = Kd(progerin) / Kd(lamin a)** to determine binding preference. A Kd ratio < 1 indicates a stronger affinity for progerin, while a Kd ratio > 1 indicates a stronger affinity for lamin A.
The full dataset and comparative analysis are reported in the [Model](%7B%7B%20url_for%28%27pages%27%2C%20page%3D%27model%27%29%20%7D%7D) section of our wiki.

### Learn

From this analysis, we observed that some promising interactors, **lost their proper folding when fused to the RING domain**, leading to a **modification in binding affinity for progerin**, in some cases leading to a loss of specificity. This suggests that **steric interference or linker rigidity** may modify structural integrity. We therefore learned that further optimization — for example, **evaluating different linker lengths or flexible sequences** — will be necessary to preserve the correct folding while maintaining RING functionality. In the **next cycle**, we plan to build on the insights gained from this "learn" phase by further optimizing the linker length and assessing the impact of the RING domain. Specifically, we aim to experiment with varying linker lengths and flexible sequences to ensure proper folding while maintaining the functionality of the RING domain.

## Cycle 6.1 – CFPS at 30 °C

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![CFPS DBTL Cycle: Optimization at 30 °C to Mimic Human Physiological Conditions](https://static.igem.wiki/teams/5700/images/engineering/dbtl1-cellfree.webp)

**Figure 1.** CFPS DBTL cycle. Optimization, performed at 30 °C to better approximate human physiological conditions. Made with Biorender.com

### Design

To validate the Syn-Xpress™ SILVER cell-free protein synthesis (CFPS) system, we aimed to establish conditions for efficient expression of our constructs. The first objective was to test protein synthesis at 30 °C, a temperature that more closely resembles human physiological conditions. Although we were aware that the enzymatic machinery of the kit is derived from *E. coli*, we wanted to assess whether the system would still function efficiently under these conditions.

### Build

Reagents (Syn-Xpress™ SILVER mix and plasmid DNA) were thawed on ice and handled carefully, avoiding vortex agitation. Reactions were prepared in 50 µL final volume, containing 40 µL of Syn-Xpress™ SILVER mix (final 1×), 15 ng/µL of plasmid DNA, and nuclease-free water. Tubes were sealed with sufficient headspace for oxygenation and incubated with shaking at 150 rpm.

### Test

The reaction was incubated for 6 h at 30 °C. mEGFP expression was measured using a Thermo Scientific™ Varioskan™ LUX reader. Fluorescence values confirmed protein synthesis, with the positive control yielding 260 RFU.

### Learn

Although protein was expressed at 30 °C, the fluorescence signal was lower than expected. This suggested that optimal expression of our constructs might occur at a different temperature, prompting a second cycle of optimization.

## Cycle 6.2 – CFPS at 20 °C

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![CFPS DBTL Cycle: Optimization at 20 °C to Enhance Expression Efficiency in the Cell-Free System](https://static.igem.wiki/teams/5700/images/engineering/dbtl2-cellfree.webp)

**Figure 2.** CFPS DBTL cycle. Optimization at 20 °C to enhance expression efficiency in the cell-free system. Made with Biorender.com

### Design

Based on the reduced expression observed at 30 °C, we decided to lower the incubation temperature to 20 °C. This was expected to favor proper folding and stability of proteins synthesized in vitro, especially small peptides like SpyTag and SpyCatcher.

### Build

The same CFPS workflow was followed: 50 µL reactions with 40 µL Syn-Xpress™ SILVER mix (final 1×), 15 ng/µL plasmid DNA, and nuclease-free water. Reactions were incubated with shaking at 150 rpm.

### Test

The reaction was incubated for 6 h at 20 °C. mEGFP expression was quantified with the same fluorescence assay. The positive control yielded 859 RFU, a much stronger signal compared to 30 °C.

### Learn

Lowering the incubation temperature significantly improved protein yield. For this reason, subsequent CFPS experiments with SpyTag and SpyCatcher were conducted at 20 °C, providing both higher expression and better reproducibility of results.

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## Progerin expression

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![Expression of the C-terminal fragment of progerin in yeast for the   Yeast Two-Hybrid DBTL cycle](https://static.igem.wiki/teams/5700/images/engineering/dbtl-cycle-yeast.webp)

**Figure 3.** Yeast lab DBTL cycle We worked in order to be able to express progerin sequence in yeast two hybrid (Y2H) plasmids pGAD and pGBK. Since the whole sequence was responsible for a cytotoxic effect, we chose to express only its C-terminal. Made with Biorender.com

### Design

One of the central objectives of our project was to establish a yeast-based model for **Hutchinson–Gilford Progeria Syndrome (HGPS)**. Since our work focuses on studying protein–protein interactions, we identified the **Yeast Two-Hybrid (Y2H) system** as a suitable platform to search for and test potential interactors of progerin. By implementing this assay, we aimed to investigate both progerin’s interaction partners and its potential for self-association, a phenomenon already observed *in vivo*.

### Build

Our initial design strategy was to express progerin in both Y2H plasmids, **pGAD (bait)** and **pGBK (prey)**, fused with either the activation domain (AD) or the DNA binding domain (BD), respectively. This setup would allow us not only to test possible heterologous interactions, but also to directly test whether progerin could self-interact in the yeast model.

### Test

We transformed *Saccharomyces cerevisiae* Y190 with the two Y2H plasmids **pGBK** and **pGAD**, carrying the full-length sequence of progerin (this initial version was not RFC10 optimised), in frame with BD and AD, respectively. Although our plan was to engineer the yeasts to express both plasmids simultaneously, this was not achieved due to two main issues:

1. We did not observe consistent growth of the transformed yeast cultures;
2. In the colonies that were able to grow on selective media, **progerin expression was suppressed**, as confirmed by *Western* blot analysis

These results indicate that constitutive expression of full-length progerin in both pGAD and pGBK exerts a **cytotoxic effect**, preventing yeast growth unless protein expression is repressed.

### Learn

The cytotoxicity observed with full-length progerin prompted us to revise our strategy and to restrict expression to its **C-terminal portion** (residues 430–614 and 545–614). This region is particularly relevant, as it contains the sequence differences that distinguish progerin from its *wild type* counterpart, lamin A. Specifically, we selected:

* **Residues 430–614** [BBa\_25HM35ST](https://registry.igem.org/parts/bba-25hm35st), a longer sequence including the immunoglobulin-like domain;
* **Residues 545–614** [BBa\_25IF4C4Z](https://registry.igem.org/parts/bba-25if4c4z), a shorter sequence corresponding to the unique C-terminal tail

These fragments were chosen based on prior studies [[1]](https://doi.org/10.1038/s43587-023-00361-w). In addition, we decided to clone progerin exclusively in the **pGBK (prey) plasmid**. This adjustment was made to limit the ability of progerin to distribute abnormally within the yeast cell, thereby reducing potential cytotoxicity and improving the reliability of interaction assays.

This allowed us to successfully express at least the C-term of progerin in the pGBK vector and proceed with further experiments.

## References

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* [1] Zhang, N., Hu, Q., Sui, T., Fu, L., Zhang, X., Wang, Y., Zhu, X., Huang, B., Lu, J., Li, Z., & Zhang, Y. (2023). Unique progerin C-terminal peptide ameliorates Hutchinson-Gilford progeria syndrome phenotype by rescuing BUBR1. Nature aging, 3(2), 185–201. <https://doi.org/10.1038/s43587-023-00361-w>

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## Cycle 1.1: Ligation of DNA fragments into NanoBiT vectors

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![NanoBiT Cloning Strategy DBTL First Cycle: Unsuccessful Ligation Due to Plasmid Self-Resealing](https://static.igem.wiki/teams/5700/images/engineering/dbtl1-mam.webp)

**Figure 4.** NanoBiT cloning strategy DBTL first cycle. In the first cycle, we designed the ligation strategy using EcoRI and XhoI restriction sites to open the Multiple Cloning Site. However, it did not work because the plasmid resealed itself.

### Design

Our goal was to insert our DNA fragments into the NanoBiT (for more information, check our [experiments page](%7B%7B%20url_for%28%27pages%27%2C%20page%3D%27experiments%27%29%20%7D%7D#3rd-pillar)) vectors to generate functional fusion constructs. We designed the ligation strategy using EcoRI and XhoI restriction sites to open the Multiple Cloning Site (MCS) and enable the directional insertion of our target sequences.

### Build

We transformed *E. coli* DH5α with the ligation mixture and selected positive colonies for further analysis. Plasmids were extracted through mini-prep and purified according to standard protocols.

### Test

Electrophoresis analysis of the purified plasmids revealed that most samples contained the recircularized vector rather than the desired ligation product. This indicated that the ligation had not occurred efficiently, likely due to the persistence of linearized backbone DNA in the mixture.

### Learn

From this outcome, we understood the necessity of an additional purification step to remove unligated vector backbones. To improve ligation efficiency, we planned a gel purification to separate the opened plasmid backbone from the MCS fragment before repeating the cloning procedure.

## Cycle 1.2 – Re-ligation after gel purification

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![NanoBiT Cloning Strategy – DBTL Second Cycle: Improved Ligation with Gel Extraction and Purification](https://static.igem.wiki/teams/5700/images/engineering/dbtl2-mam.webp)

**Figure 5.** NanoBiT Cloning Strategy - DBTL Second Cycle. We designed the ligation strategy using EcoRI and XhoI restriction sites to open the Multiple Cloning Site. This time, we proceeded with the steps of gel band cutting and purification.

### Design

To overcome the recircularization problem, we aimed to increase ligation specificity by removing any residual backbone contaminants. A 1% agarose gel purification step was added to isolate the linearized NanoBiT vector digested with EcoRI and XhoI.

### Build

Following gel extraction, purified backbones and inserts were quantified and used for a new ligation reaction under optimized molar ratios. The ligation products were then transformed into *E. coli* DH5α competent cells.

### Test

Colonies were screened and analyzed by mini-prep and gel electrophoresis. The resulting plasmids showed bands corresponding to the expected size of the recombinant constructs, confirming successful ligation.

### Learn

Introducing the gel purification step successfully eliminated the background of recircularized vector and improved cloning efficiency. This optimized workflow was subsequently adopted for all following NanoBiT construct assemblies.

## Cycle 2.1 – Seeding of HGPS-derived fibroblasts

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![Seeding of HGPS-Derived Fibroblasts – DBTL First Cycle: Transition to Control Fibroblasts Transfected with Progerin to Model the Pathological Phenotype](https://static.igem.wiki/teams/5700/images/engineering/agg-dbtl1.webp)

**Figure 6.** Seeding of HGPS-derived fibroblasts - DBTL First Cycle. HGPS-derived fibroblasts were initially used but showed limited proliferation, leading to the use of control fibroblasts transfected with progerin to reproduce the pathological phenotype *in vitro*.

### Design

We planned to design and conduct our experiments using fibroblast cell lines derived from HGPS patients, kindly provided by Prof. Lattanzi. These cells represent a valuable model that naturally expresses progerin. Using patient-derived fibroblasts allows us to directly evaluate the physiological relevance of our degradation system and to assess its ability to specifically target and reduce progerin levels in a disease-relevant context.

### Build

We cultured the cells in T25 flasks to monitor their growth dynamics, morphology, and overall health over time. This setup allowed us to carefully observe their adherence, proliferation, and characteristic morphological features under standard culture conditions.

### Test

We allowed the cells to grow until they reached full confluence, ensuring that a uniform and continuous monolayer was formed across the entire flask surface. This step was essential to guarantee consistent cell density and physiological conditions for all subsequent experiments.

### Learn

The cells did not proliferate as expected and failed to reach confluence in the T25 flasks, likely due to their reduced replicative capacity and altered metabolic state typical of HGPS-derived fibroblasts. As a result, we decided to adapt our experimental strategy by switching to healthy control fibroblasts provided by Prof. Lattanzi. These cells allow us to artificially express progerin and reproduce the pathological phenotype in a controlled manner.

## Cycle 2.2 – Seeding of control fibroblasts

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![Seeding of Control Fibroblasts – DBTL Second Cycle: Transition to MRC-5 Cell Line for Improved Growth and Transfection Reproducibility](https://static.igem.wiki/teams/5700/images/engineering/agg-dbtl2.webp)

**Figure 7.** Seeding of control fibroblasts - DBTL Second Cycle. The study initially used primary control fibroblasts, but due to their limited proliferation, the approach was refined by switching to the MRC-5 fibroblast cell line, which offers higher growth rates and reproducibility for transfection with progerin.

### Design

We planned to design our experiments using healthy fibroblast control cell lines provided by Prof. Lattanzi, which served as essential negative controls throughout the study. These cells, derived from unaffected donors, display normal nuclear architecture and lamin A expression, making them an ideal baseline for comparison with HGPS-derived or progerin-expressing fibroblasts. Furthermore, we intended to transfect these control fibroblasts with a progerin-expressing construct to induce the pathological phenotype, thereby enabling a controlled and reproducible model for our experiments.

### Build

We cultured the cells in T25 flasks to monitor their growth dynamics, morphology, and overall health over time. This setup allowed us to carefully observe their adherence, proliferation, and characteristic morphological features under standard culture conditions.

### Test

We allowed the cells to grow until they reached full confluence, ensuring that a uniform and continuous monolayer was formed across the entire flask surface. This step was essential to guarantee consistent cell density and physiological conditions for all subsequent experiments.

### Learn

The control fibroblasts did not proliferate properly and were unable to reach confluence in the culture flasks, likely due to their nature as a primary cell line.. To ensure reproducibility and maintain optimal culture conditions, we therefore decided to switch to a commercially available human fibroblast cell line (MRC-5). These cells, derived from normal lung tissue, offer a robust and well-characterized model for transfection experiments. By introducing a progerin-expressing construct into MRC-5 cells, we aimed to recreate the progeria-like phenotype in a controlled and viable system, suitable for evaluating the efficiency of our designed degradation approach.

## Cycle 2.3 – Seeding of MRC5 cells

▲

![Seeding of MRC-5 Cells – DBTL Third Cycle: Transition to 293T Cell Line for Enhanced Growth and Transfection Efficiency](https://static.igem.wiki/teams/5700/images/engineering/agg-dbtl3.webp)

**Figure 8.** Seeding of MRC5 cells - DBTL third Cycle. After observing low transfection efficiency of MRC5, the strategy was adapted by switching to the 293T epithelial cell line, which ensures higher growth rates and transfection efficiency for progerin expression studies.

### Design

We planned to design our experiments using the MRC-5 cell line, which we selected because it consists of human fibroblasts, making it suitable for modeling cellular processes related to progerin expression. By transfecting MRC-5 cells with progerin-expressing constructs, we aimed to reproduce the molecular and morphological features of HGPS in a controlled experimental context, providing a reliable model to evaluate the efficiency and specificity of our degradation system.

### Build

We cultured the cells in T25 flasks to monitor their growth dynamics, morphology, and overall health over time. This setup allowed us to carefully observe their adherence, proliferation, and characteristic morphological features under standard culture conditions.

### Test

We allowed the cells to grow until they reached full confluence, ensuring that a uniform and continuous monolayer was formed across the entire flask surface. This step was essential to guarantee consistent cell density and physiological conditions for all subsequent experiments.

### Learn

The MRC5 cells were able to reach confluence in the flasks; but they exhibited very low transfection efficiency, making them unsuitable for reproducible expression studies. To overcome these limitations, we decided to use a commercially available human epithelial cell line (HEK 293T). These cells are widely used due to their high proliferative rate and exceptional transfection efficiency. By transfecting 293T cells with a progerin-expressing construct, we aimed to establish a reliable and scalable cellular model that would allow us to efficiently test our system’s ability to induce the degradation of progerin while maintaining optimal experimental reproducibility.

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# Experiments

This page summarizes experiments supporting our progerin‑targeting strategy: cell‑free expression with Microscale Thermophoresis to quantify binding of *in silico*–designed peptide interactors to progerin; assays in *S. cerevisiae* (inducible expression, *Western* blotting, growth/spot tests, yeast two‑hybrid with lamin A controls) to assess toxicity and interaction specificity; analyses in human fibroblasts (MRC‑5 and HGPS patient‑derived) covering ROS and viability assays, flow cytometry, Western blotting, and fluorescence microscopy; and benchmarking of the RING–SpyCatcher degradation system.

* [Computational Biology](#1st-pillar)
* [Yeast Model Testing](#2nd-pillar)
* [Mammalian Cells Validation](#3rd-pillar)

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## Measuring the binding affinity to progerin with MST

▲

To evaluate the binding affinity of our interactors to progerin, we use Microscale Thermophoresis (MST) on the Monolith X system. MST allows sensitive detection of molecular interactions in solution and provides dissociation constants (Kd) that reflect affinities under near-physiological conditions. From the resulting dose–response curves, Kd values are extracted, offering quantitative insight into the strength and specificity of each interaction.

![Picture rapresenting how Monolith works](https://static.igem.wiki/teams/5700/images/experiments/monolith.webp)

**Figure 1.** Monolith X. Binding affinity measurements of *in silico*–designed interactors with progerin using the Monolith instrument

## How can we produce our interactors? Cell-Free Transcription-Translation (TXTL)

▲

Cell-free transcription-translation (TXTL) is a powerful system that enables protein and peptide expression directly from DNA, without the need for living cells. It relies on bacterial extracts containing ribosomes, tRNAs, polymerases, nucleotides, amino acids, and an energy-regeneration mix. Once a DNA template is added, the extract transcribes it into mRNA and immediately translates it into the corresponding protein.

In our project, TXTL is used to produce the synthetic peptides designed as potential interactors of progerin. Instead of cloning each sequence into cells and waiting for bacterial cultures, we can express them directly *in vitro*. This approach saves time and allows rapid testing of multiple peptide candidates.

Concretely, we ordered plasmids carrying the peptide DNA sequences from IDT. Shipped in lyophilized form, they are resuspended in nuclease-free water and directly added to the TXTL reaction. After a few hours of incubation, the system produces the desired peptides.
These peptides are then purified and tested with the Monolith X instrument, which quantifies their binding affinity to progerin. This workflow not only accelerates the design–build–test–learn cycle of our project but also provides preliminary experimental validation of our interactors before moving to mammalian cell models.

![Cell-Free Transcription-Translation: Schematic of Plasmid-to-Protein Expression](https://static.igem.wiki/teams/5700/images/experiments/txtl.webp)

**Figure 2.** Cell-Free Transcription-Translation. Schematic representation of cell-free protein synthesis: the plasmid is transcribed into mRNA, which is subsequently translated into the peptide.

## CFPS Control Reaction Setup

▲

Reagents (Syn-Xpress™ SILVER mix and DNA) were thawed on ice and handled carefully, avoiding vortexing. A 50 µL reaction was prepared with 40 µL of Syn-Xpress™ SILVER mix (final 1×) and a volume of synmEGFP plasmid DNA sufficient to achieve a final reaction concentration of 15 ng/µL, or nuclease-free water for the negative control. The volume was adjusted to 50 µL with nuclease-free water and mixed gently to prevent bubble formation.

Reactions were sealed in tubes with sufficient headspace for oxygenation and incubated at 150 rpm for 6 h with shaking. Positive and negative controls were incubated at 20 °C, while an additional positive control was incubated at 30 °C. At the end of incubation, samples were placed on ice.

mEGFP expression was measured with a Thermo Scientific™ Varioskan™ LUX Multimode Microplate Reader. Fluorescence values (RFU, Relative Fluorescence Units) were:

* Positive control at 30 °C: 260 RFU
* Positive control at 20 °C: 859 RFU

## CFPS SpyTag SpyCatcher

▲

Since the recombinant progerin ordered from Diatheva has not yet arrived, we began by expressing and testing SpyTag and SpyCatcher. These well-characterized proteins form a stable covalent interaction, making them an ideal model system. Working with them allowed us to familiarize ourselves with the Monolith X instrument and validate the workflow before moving to experiments with our designed interactors and progerin.

Based on the yields obtained from control reactions, we expressed the peptides at 20 °C. Each CFPS reaction contained 40 µL of Syn-Xpress™ SILVER mix (final 1×), 15 ng/µL of plasmid DNA, and nuclease-free water to a final volume of 50 µL, mixed gently to prevent bubble formation.

## Purification of SpyTag and SpyCatcher

▲

The resin (HisPur™ Ni-NTA, 50 µL effective volume) was washed with Milli-Q water and then with PBS (centrifugation 5 min, 3000 rpm each). The 50 µL TXTL reaction was loaded onto the resin and incubated for 30 min at room temperature with shaking to promote binding.

The resin with bound proteins was transferred into a spin column and processed sequentially:

* **Flow-through (FT):** collected after washing with PBS 1× (300 µL);
* **Wash (W1):** obtained after an additional wash with PBS 1× (200 µL);
* **Elution:** proteins were eluted twice with PBS 1×, pH 7.7 containing 500 mM imidazole (200 µL each), yielding fractions E1 and E2;

All fractions (FT, W1, E1, E2) were retained for SDS-PAGE analysis, and the resin was recovered for reuse.

## SDS-PAGE

▲

To assess the presence of the recombinant proteins SpyTag and SpyCatcher, we performed SDS-PAGE on samples collected during purification. The results, however, were unsatisfactory: the expected His-tagged bands were faint or obscured, and the gel displayed multiple background bands. These likely originated from endogenous proteins in the cell-free synthesis system that were retained during early purification steps.

This nonspecific binding was probably due to an excessively high resin-to-protein ratio, which promoted interaction of non-target proteins with the affinity matrix. As a result, the purity of the eluted fractions was compromised, making it difficult to identify the target proteins with confidence.

To address these issues, we plan to optimize the purification protocol by adjusting the resin volume relative to the protein concentration in future experiments. This should help reduce nonspecific binding and improve the clarity of SDS-PAGE results, allowing us to better evaluate the expression and purity of our target proteins.

To improve retention and resolution of these proteins, we are repeating the experiment with a more suitable gel matrix. Two controls will also be included: one with the reaction mixture lacking expressed protein and another with resin alone. Detection will be refined by anti-His Western blotting, as both SpyTag and SpyCatcher are His-tagged.

Here is the image of the gel:

![SDS-PAGE Analysis of SpyCatcher and SpyTag Purification: Flow-Through, Wash, and Elution Profiles](https://static.igem.wiki/teams/5700/images/experiments/sdspage-cellfree.webp)

**Figure 3.** SDS-PAGE analysis of SpyCatcher and SpyTag purification Lanes 1marker, 2–5: SpyCatcher (flow-through, PBS wash, elution 1, elution 2). Lane 6: empty. Lanes 7–10: SpyTag (eluate, flow-through, PBS wash, elution 1, elution 2)

| Interactor | Code |
| --- | --- |
| Interactor 1: 62aa11\_1 | [BBa\_254PC42U](https://registry.igem.org/parts/bba-254pc42u) |
| Interactor 2: LOGO | [BBa\_252ADNO1](https://registry.igem.org/parts/bba-252adno1) |
| Interactor 3: n80\_02 | [BBa\_25KT4K90](https://registry.igem.org/parts/bba-25kt4k90) |
| Interactor 4: Rank\_15 | [BBa\_25E35V1M](https://registry.igem.org/parts/bba-25e35v1m) |
| Interactor 5: Rank\_21 | [BBa\_253S6Z46](https://registry.igem.org/parts/bba-253s6z46) |
| Linker-SpyTag | [BBa\_25BEEQ7F](https://registry.igem.org/parts/bba-25beeq7f) |
| SpyCatcher | [BBa\_259R437F](https://registry.igem.org/parts/bba-259r437f) |
**Table 1.** List of constructs for Monolith assay.

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## Phenotype

▲

We used *Saccharomyces cerevisiae* as a cellular model to study the toxicity of progerin underlying the Hutchinson–Gilford Progeria Syndrome. To assess the impact of this protein on yeast cells, several experiments were performed.

In the experimental process we used pYES2 expressing progerin sequence optimization ([BBa\_25NDL8N0](https://registry.igem.org/parts/bba-25ndl8n0)) for the expression in yeast cells by selecting proper codon usage. This plasmid expresses progerin under the galactose-inducible promoter GAL1 which allows controlled expression of the progerin sequence. It carries a selectable marker (uracil synthesis pathway) which enables growth selection in transformed *S. cerevisiae* strains with auxotrophy for uracil.

### Bacterial transformation and plasmid extraction

The progerin-expressing plasmid was initially **transformed into competent bacterial cells** in order to amplify its quantity. We followed the standard manufacturer’s protocol and worked with 5 μL of plasmid and 25 μL of competent cells *E. coli* TOP10.
Transformed cells were incubated overnight at 37oC on solid LB medium supplemented with ampicillin (final concentration = 0.1 mg/ml). The following day colonies were isolated for plasmid extraction and further analysis.

Plasmid DNA was extracted with a miniprep Kit based on alkaline lysis and silica column purification, and quantified using a NanoDrop spectrophotometer. Additionally, the extracted plasmid DNA was checked by gel electrophoresis.

### Chemical transformation

Once confirmed that the plasmid was correctly expressed in bacterial cells, confirmed by both agarose gel electrophoresis and Sanger sequencing, we proceeded with the **Chemical transformation of yeast cells** in order to obtain our transformed yeast culture. The efficiency of this method relies on ensuring a sufficient number of competent cells, thus increasing the probability of successful plasmid uptake. We used the CEN.PK strain, which was inoculated and grown overnight in rich YPG medium at 28°C with agitation. Each transformation required 2 mL of overnight culture. Pelleted cells were resuspended with all the necessary reagents, along with 1000 ng of plasmid DNA. After transformation, cells were plated on minimal solid SD Glu - URA medium. Following 2 days of incubation at 28oC we were able to select only the cells that had successfully taken up and expressed the plasmid.

### Protein extraction, quantification, SDS-PAGE and *Western* blot

To verify protein expression in the transformed yeast cells, we incubated them in liquid SD Gal -URA medium overnight at 28oC, allowing galactose to induce progerin expression and provide sufficient protein for analysis. The following day, we measured the OD of each inoculum to calculate the volume required to achieve a final OD of 5. For protein extraction we applied the **Trichloroacetic acid (TCA) method** combined with glass beads for cell lysis. The extracted proteins were solubilized in Laemmli Sample Buffer 1X (LSB), the pH was adjusted with Tris-HCl (pH 8.8), and the samples were denatured at 95°C for 5 minutes. Proteins in the supernatant could then be stored at -20oC or used immediately.

Protein quantification is a crucial step in protein analysis. The **Bradford assay** is a colorimetric method for protein quantification based on the binding of Coomassie Brilliant Blue G-250 dye to proteins. We applied this method to quantify our samples, ensuring that the equal amounts of protein were loaded from each sample in order to obtain comparable results within each well.

After extraction and quantification, we proceeded with **SDS-PAGE** (Sodium Dodecyl Sulfate–Polyacrylamide Gel Electrophoresis). In this method, Sodium Dodecyl Sulfate (SDS) denatures proteins and imparts a uniform negative charge, enabling their separation according to molecular weight during electrophoresis. At the end of this process, the gel was ready for protein transfer.

Protein transfer was performed onto a PVDF membrane (previously activated in ethanol) using a semi-dry transfer system: 20 minutes at 16 mA (through the stacking gel) and 1h at 24 mA (through the running gel). Successful protein transfer was confirmed by Ponceau staining, which revealed visible bands.
The membrane was then blocked with 5% milk in TBS-T for 1h at room temperature under gentle stirring. After blocking, the membrane was washed with TBS-T to remove residual milk and subsequently incubated with the primary antibody.

Our part [BBa\_25NDL8N0](https://registry.igem.org/parts/bba-25ndl8n0) contains a myc epitope tag, designed for Western blot detection. Therefore, the membrane was incubated with a mouse anti-myc primary antibody diluted 1:1000 in 1% BSA in TBS-T for 1h and 30 min at room temperature, followed by three washes with TBS-T (5 minutes each, under gentle stirring).
A freshly prepared secondary antibody, diluted 1:3000 in 1% BSA in TBS-T, was then applied for 1h at room temperature under stirring. After incubation, the membrane was washed three times in TBS-T (5 minutes each) and once in TBS for 5 minutes.

Detection was performed using luminol solution to activate the peroxydase activity of the secondary antibody, and the signal was visualized using a Uvitec imaging system.
The results confirmed protein expression, indicating that our yeast culture successfully expressed progerin.

### Vitality tests

Once we obtained significant results for the expression of progerin in CEN.PK we tested some independent colonies to gain a better understanding of how the mutant protein can affect the phenotype of *S. cerevisiae*.
We aimed to monitor the growth of yeast cultures in liquid and solid glucose and galactose medium to study the effect of progerin on the cell growth.

Since the three pYES\_empty colonies and the five pYES\_progerin colonies used for the Western Blot had been restreaked and stored at 4°C for preservation, we inoculated them into 10 mL of SD-GLU –URA medium.

When the yeast cells had reached the stationary phase in a selective minimal medium we started to set our growth curve analyses.

To standardize the initial cell density and ensure comparable growth curves across various conditions, the optical density (OD) of each overnight culture was measured at 600 nm. The volume needed to achieve an initial OD600 of 0.15 in 15 mL of fresh medium was calculated using the following formula: **ODculture × Vinitial = ODfinal × Vfinal**

Each 15 mL culture was transferred into a 50 mL flask to ensure proper aeration and robust growth.

We worked in duplicate with two strains in two different media (SD Glucose 2% -URA and SD Galactose 2% -URA) both for the control and the samples to test. After inoculation, cultures were incubated at 28 °C with shaking and monitored over time.

A volume of 800 µL was taken without dilution to measure the initial OD of the cell culture. This was used to verify that all cultures started at a standardized OD600 of 0.15. For the first measurements in the afternoon, after approximately 6 hours of incubation, samples were diluted in a 1:2 ratio for both galactose and glucose cultures. The same dilution (1:2) was applied for the following measurements (after another 6 hours) for galactose cultures, while glucose cultures were diluted 1:10. For the subsequent measurement periods (the following afternoon and morning), all cultures were diluted 1:10 before OD readings.

Although the overall growth trends were not sharply distinct, a clear difference became evident after 24 hours between the progerin-expressing cultures and their respective controls.

![Effect of Progerin Expression on <i>S. cerevisiae</i> CEN.PK Growth in Glucose and Galactose Media](https://static.igem.wiki/teams/5700/images/experiments/growth-curve-pyes2-progerin-eng-2.webp)

**Figure 1.** Effect of progerin expression on *S. cerevisiae* CEN.PK growth. pYES\_∅ GLU and pYES2\_progerin GLU cultures were growing in SD Glucose 2% -URA, while pYES\_∅ GAL and pYES2\_progerin GAL cultures were growing in SD Galactose 2% -URA. Galactose is the inductor of the GAL1 promoter in the pYES2 plasmid; for this reason, pYES2\_progerin GAL is the only culture where progerin is expressed, and, as it is possible to see, the only one showing markedly limited growth. The limited growth of pYES\_∅ GAL is probably due to the use of a less-preferred sugar.

Simultaneously we worked on the spot test. The spot test allows us to compare the growth of the same cultures under different conditions. Up to eight cultures can be tested at the same time, with each culture plated in four serial dilutions (1, 10-1, 10-2 , and 10-3) to better assess differences in growth. Each dilution is prepared from a culture standardized to an OD of 1, meaning that the first dilution corresponds to an OD 1 cell concentration.
Plating was performed by depositing a drop of each culture onto the pre-designed array on the plate. Plates are then incubated at 28°C for three days, and photographs are taken daily to capture the full progression of growth.

All of the five colonies containing pYES\_progerin were tested and we used pYES\_empty as control. We measured the optical density (OD) of each culture to calculate the appropriate dilutions, standardizing the **starting concentration to OD = 1 for the first spot**.
We then calculated the ml needed to achieve this OD in 1ml of water. Then a series of four 1:10 serials dilutions were prepared and we pipetted 4 µl of volume from each dilution to compare the growth of the same cultures on different mediums.

In order to evaluate the impact of the protein expression on cells, growth differences across dilutions and different media conditions are analyzed. Every 24 hours, pictures of the plates were taken to visually track growth and confirm the trends observed in OD measurements. At 24 and 48 hours, all strains grew similarly on glucose medium, showing colony formation regardless of the presence of the plasmid. This indicates that under repressive conditions, the presence of the plasmid does not affect the viability of the yeast cells.
In contrast, on galactose plates, a clear difference between two strains could be seen over time. Colonies carrying the empty pYES2 maintained consistent growth, indicating that galactose itself does not inhibit growth. In contrast, yeast carrying the pYES\_Progerin plasmid showed progressively reduced growth on galactose plates compared to those growing in glucose and to the empty vector controls. This growth reduction was more noticeable at 72 hours, where the density and size of the colonies expressing progerin decreased significantly. These results confirm that the expression of progerin under galactose-inducing conditions exerts a toxic effect on yeast cells.

![Spot Test on <i>S. cerevisiae</i> CEN.PK: Galactose-Inducible Progerin Expression Limits Growth on SD Glucose -URA](https://static.igem.wiki/teams/5700/images/experiments/spot-test-pyes2-progerin-19-09.webp)

**Figure 2.** Spot test results on *S. cerevisiae* CEN.PK. progerin expression (galactose-inducible) is responsible for limiting yeast growth on SD Glucose -URA medium.

## Yeast Two-Hybrid (Y2H)

▲

*S. cerevisiae* provides a convenient and cost-effective system to study protein-protein interactions using the **Yeast Two-Hybrid** (Y2H) assay. This approach allows us to test the interaction between two proteins via the use of two plasmids: one encoding the “prey” protein and the other encoding for the “bait” protein. In our experiments, we used the commercially available plasmids pGADT7 and pGBKT7. The pGAD plasmid expresses the activation domain (AD) and serves as the prey vector, whereas pGBK expresses the DNA-binding domain (BD) and serves as the bait vector.
The genes encoding the proteins of interest can be cloned into these plasmids in frame with the AD or BD domains, enabling the system to assess potential protein-protein interactions.
When both plasmids are co-transformed into the same *S. cerevisiae* cell, an interaction between the two proteins brings the BD and AD domains into proximity, reconstituting a functional transcription factor that activates a reporter gene, allowing yeast growth on selective medium.

![Yeast Two-Hybrid (Y2H) Mechanism: Protein–Protein Interaction Detection via Reporter Activation](https://static.igem.wiki/teams/5700/images/experiments/y2h-explanation.webp)

**Figure 3.** Yeast two hybrid (Y2H) molecular mechanisms. The two plasmids coding for the prey and bait domain are cloned in frame with the two proteins to be assessed for interaction and co-transformed into the same *S. cerevisiae* cell. If the two proteins of interest interact, the reporter pathway is activated. Made with Biorender.com

The experimental procedure for performing Y2H consists of two main steps:

* **Co-transformation** of the bait and prey plasmids into the same yeast cell;
* **Spot test assay** on selective medium to assess activation of the Y2H reporter pathway

### Plasmids for Y2H

The plasmids employed in Y2H are:

* **pGBKT7**: expresses the DNA-binding domain (BD) fused to a myc epitope and serves as the bait plasmid. Its nutritional selection relies on tryptophan auxotrophy. In bacteria, this plasmid can be selected by its Kanamycin resistance;
* **pGADT7**: expresses the activation domain (AD), fused to a HA epitope and a Nuclear Localization Signal (NLS), serving as the prey plasmid. Its nutritional selection relies on leucine auxotrophy. In bacteria, this plasmid can be selected by its ampicillin resistance

In our experiment, the report pathway used is the **HIS3 pathway**. Accordingly, the selective medium is SD Glucose -Leu -Trp -His +3-AT. The addition of 3-AT (3-aminotriazole), an inhibitor of histidine synthesis, is necessary because activation of HIS3 is leaky, and it strengthens selection for true positive interactions.

### Cloning progerin for Y2H

At the start of our Y2H experiments, we first cloned the full-length sequence of progerin (in this case, a non-RFC10-standardized sequence) into both the Y2H plasmids, pGADT7 and pGBKT7.

Our aim was to assess whether Y2H could be applied to progerin and, if so, whether progerin’s ability to bind with other progerin molecules could be assessed via this system.

To achieve this, we started by cloning the progerin sequence into our plasmids via **Infusion cloning**, which in this case required a 2:1 ratio of insert to plasmid (100 ng of insert, 50 ng of plasmid), 2 µL of Infusion solution, and water to bring the final volume to 10 µL. The Infusion reaction was carried out at 55°C for 15 min.
Afterwards, *E. coli* Top10 cells were transformed with the cloning products and plated on LB Agar + ampicillin/kanamicine plates, which were incubated overnight at 37°C.

The next day, plasmid DNA was extracted via extraction procedure. Before proceeding with yeast transformation, the plasmids were digested with restriction enzymes and analyzed by gel electrophoresis to verify fragments lengths. Specifically, EcoRV and BamHI were used on pGBK, and EcoRV on pGAD, yielding bands of the expected sizes.

### *S. cerevisiae* Y190 transformed for Y2H

Afterwards, we proceeded with yeast transformation. For our work concerning Y2H, we used the ***S. cerevisiae* Y190** strain (different from the CEN.PK strain used for phenotype characterisation). This strain is commonly used in Y2H experiments because it carries specific reporter constructs and genetic features that minimize auto-activation of the reporter genes, allowing more reliable detection of true protein-protein interactions.
Transformation was performed using the **one-step protocol**, as we expected a high transformation efficiency.

At this stage, we encountered an unexpected problem: transformation was successful on only a few plates, and those that showed growth had limited, small colonies.
Due to this result, we tested the obtained colonies for progerin expression via Western blot.

***Western* blot** was performed on a liquid culture of the selected clones. Proteins were extracted from 5 OD of culture using the **trichloroacetic acid (TCA) protocol**. After protein extraction, samples were loaded onto **5% acrylamide SDS-PAGE gel**, which was then transferred on PVDF membrane. Ponceau staining confirmed correct protein transfer and migration on the membrane.

Then we started the blotting procedures, which were performed using two different primary antibodies: anti-myc for pGBKT7, and anti-HA for pGADT7, reflecting the epitopes present on the two plasmids.
The secondary antibody was the same for both: anti-mouse peroxydase antibody.
Finally, membranes were developed using Luminol solution and analysed with a Uvitech system.

As we expected from the unusual transformation results we saw on plates, none of the yeast cultures expressed progerin.
We attributed the inability of the cells to grow in the context of progerin expression to the **cytotoxic effect of progerin** when constitutively expressed. Indeed, the **ADH1 promoter** which drives protein expression in both pGBKT7 and pGADT7, is a constitutive promoter (unlike the GAL1 promoter of pYES2).

Following this result, we changed our initial strategy regarding progerin expression:

* We decided to express only the **C-terminal portion of progerin**;
* We chose to express progerin only in pGBKT7

The main reason behind these choices was to limit progerin cytotoxicity. Consequently, we were unable to test whether progerin could interact with other progerin molecules and instead focused on assessing progerin binding to a known interactor. Based on previous studies[1], this interactor was selected as the **N-terminal region of BUBR1**.

### Progerin C-term fragments cloning

The fragments selected for expression, instead of the full-length progerin, were the same as those described in the studies that recognised BUBR1 as a progerin interactor[1].
The regions we chose to express are the following:

* From amino acids 430 to 614 ([BBa\_25HM35ST](https://registry.igem.org/parts/bba-25hm35st)): includes the Ig-like domain of the protein;
* From amino acids 545 to 614 ([BBa\_25IF4C4Z](https://registry.igem.org/parts/bba-25if4c4z)): does not include the Ig-like domain

We chose to continue our experiments using only the pGBKT7 plasmid, as we believed that expression through the BD would limit progerin cytotoxicity, since the BD localizes primarily to its DNA targets and is less likely to diffuse freely within the cell.

Instead of ordering new fragments, we derived our sequence of interest from the pGBK\_progerin plasmid already available in the lab and [BBa\_25NDL8N0](https://registry.igem.org/parts/bba-25ndl8n0), using specifically designed primers:

* In the first procedure, the primer design allowed us to remove the N-terminal region of progerin that we did not want to express (aa 1-430 and 1-545), leaving the C-terminal fragments intact;
* In the second procedure, primers were designed to amplify the fragments of interest by PCR

Both procedures required In-Fusion to complete the cloning procedure and obtain a circular plasmid. In the end, we obtained pGBK\_progerin 430 using the first procedure and pGBK\_progerin 545 using the second.

The cloning results were verified by restriction enzyme digestion and gel electrophoresis, confirming the correct length of our fragments. The enzymes used were **EcoRI** and **BamHI**. Finally, we also verified the sequences by **Sanger sequencing**.

### Progerin C-term fragment transformation in *S. cerevisiae* Y190

Using the C-terminal fragments of progerin, we were able to achieve consistent yeast growth. On top of that, progerin expression was confirmed by Western blot, performed using the same procedure as before.
Based on these results, we concluded that we were now able to use these cultures for the Y2H assay.

### BUBR1 N-terminal cloning

When establishing the Y2H system for a new protein such as progerin, it is important to first characterize the protein’s known interactions.
For this reason, before testing our bioinformatically predicted interactors (check out our modelling [here](%7B%7B%20url_for%28%27pages%27%2C%20page%3D%27model%27%29%20%7D%7D)) and after our negative result testing progerin with itself, we decided to assess progerin’s C-terminal ability to bind a known interactor: **BUBR1**.

Since we selected pGBKT7 for progerin expression, BUBR1 N-terminal was consequently cloned into pGADT7. Only the N-terminal region of BUBR1 was selected based on previous studies showing its ability to bind the progerin C-terminal region[1 ]. This sequence was ordered from TWIST, and designed with appropriate extremities for Infusion cloning. Since we cloned it in frame after the Y2H activation domain, we weren’t able to add the RFC10 extremities.

The cloning workflow was as follows:

* **PCR amplification** of the BUBR1 N-terminal fragments received from TWIST in order to increase its concentration;
* **Infusion cloning** into pGADT7;
* **Transformation** into E.coli Top10 and plating on LB Agar + ampicillin at 37°C overnight;
* **Plasmid extraction** from obtained colonies;
* Verification of correct cloning via **restriction digestion**, **gel electrophoresis**, and **Sanger sequencing**

At this point, to confirm BUBR1 expression, proteins were extracted from 5 OD of liquid culture, followed by SDS-PAGE and transferred onto a PVDF membrane. Ponceau staining confirmed protein transfer, and then subjected to Western blot analysis with an anti-HA primary antibody.
The secondary antibody was, again, anti-mouse peroxydase, that allowed the membrane to be developed on a Uvitech system using Luminol solution.

After assessing BUBR1 expression, we proceeded with co-transformation with pGBK\_progerin C-terminal fragments to perform the Y2H assays.

### Yeast two hybrid: co-transformation

We performed single and co-transformation to obtain the following cultures for Y2H experiments (including negative controls):

* pGAD\_∅
* pGBK\_∅
* pGBK\_progerin 430
* pGBK\_progerin 545;
* pGAD\_BUBR1;
* pGAD\_∅ + pGBK\_∅
* pGAD\_∅ + pGBK\_progerin 430;
* pGAD\_∅ + pGBK\_progerin 545;
* pGAD\_BUBR1 + pGBK\_∅
* pGAD\_BUBR1 + pGBK\_progerin 430;

These cultures were tested on Y2H selective medium (SD Glucose -Leu - Trp -His +3-AT) and compared with growth on non-selective medium (SD Glucose -Leu -Trp). We first checked growth by just streaking, and then performed a spot test assay.

### Y2H - progerin interaction confirmation by spot test assay

The final step to assess progerin interaction between progerin and BUBR1 was the **spot test** on selective medium (SD Glucose -Leu -Trp -His +3-AT), compared with growth of the same cultures on non-selective medium (SD Glucose -Leu -Trp). If the proteins interact, growth on the selective medium should be similar to, or at least approach, the growth observed on the non-selective medium.

These are the results we obtained from the spot test designed to assess the interaction between BUBR1 and the C-terminal fragments of progerin.

![Spot Test in Y2H Selective Medium: No Interaction Detected Between Progerin C-Term (aa 430–614) and BUBR1 N-Terminal](https://static.igem.wiki/teams/5700/images/experiments/spot-test-conferma-y2h-bubr172h.webp)

**Figure 4.** Spot test results in Y2H selective medium. We can conclude that no specific interaction occurs between progerin C-term (aa 430-614) and BUBR1 N-terminal, as no specific growth was observed where co-transformed culture spots were made.

| Posizione | Plate 1 | Plate 2 |
| --- | --- | --- |
| 1 | CTR (+) | CTR (+) |
| 2 | CTR (-) | CTR (-) |
| 3 | pGBK\_∅ + pGAD\_BUBR1 #1 | pGBK\_∅ + pGAD\_BUBR1 #1 |
| 4 | pGBK\_∅ + pGAD\_BUBR1 #2 | pGBK\_progerin 430 + pGAD\_∅ #1 |
| 5 | pGBK\_progerin 430 + pGAD\_∅ #1 | pGBK\_progerin 430 + pGAD\_BUBR1 #1 |
| 6 | pGBK\_progerin 430 + pGAD\_∅ #2 | pGBK\_progerin 430 + pGAD\_BUBR1 #3 |
| 7 | pGBK\_progerin 430 + pGAD\_BUBR1 #1 | pGBK\_progerin 430 + pGAD\_BUBR1 #4 |
| 8 | pGBK\_progerin 430 + pGAD\_BUBR1 #2 | pGBK\_progerin 430 + pGAD\_BUBR1 #5 |

The results show that **no interaction occurs**, at least **in this system**.

## ⁠Interactors

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To analyse our bioinformatically predicted interactions using the Yeast Two Hybrid system and confirm their functionality, we selected a small subset from the total pool of our predicted interactors.

### Infusion cloning

For this reason, we ordered yeast codon-optimised sequences for the chosen interactors:

* <BBa_25R6U8N1>: LOGO, optimised for *S. cerevisiae*;
* [BBa\_25RLZ3X4](https://registry.igem.org/parts/bba-25rlz3x4): n80\_02, optimised for *S. cerevisiae*;
* [BBa\_25G9QB6S](https://registry.igem.org/parts/bba-25g9qb6s): Rank\_15, optimised for *S. cerevisiae*;
* [BBa\_25UZI9YM](https://registry.igem.org/parts/bba-25uzi9ym): Rank\_21, optimised for *S. cerevisiae*;
* [BBa\_256U2NU6](https://registry.igem.org/parts/bba-256u2nu6): 62aa11\_1, optimised for *S. cerevisiae*

The sequences were designed with **infusion cloning extremities**, but not RFC10 extremities, as they needed to be cloned directly after the AD domain.

Once the sequences from IDT arrived, they were cloned into the pGADT7 plasmid (“prey” plasmid, expressing the activation domain “AD”) using Infusion cloning for 15 minutes at 55°C. The reaction was performed at a molar ratio of 1:2 (vector:insert), taking into account the lengths and concentration of the linear plasmid and the interactor insert. Since the interactors are ~50 bp inserts and the plasmid <10 kb, a vector-to-insert ratio of 2:1 was used, as recommended by the In-Fusion protocol.

### Bacterial transformation and plasmid extraction

5µl of the plasmid (pGAD + interactor X, where X = 1-5) were transformed into Top10 Competent *E. coli* cells to obtain colonies for plasmid extraction. The constructs carry ampicillin resistance, so the transformation mix was plated on LB agar + ampicillin and incubated overnight at 37°C.

From successfully grown colonies, five of them per construct were isolated and grown in 5 mL of LB medium with ampicillin at 37°C in agitation overnight. Plasmid extraction was then performed using a miniprep protocol (without a kit) the following day..

The extracted plasmid DNA was quantified using Nanodrop, and 1000 ng of each sample were analyzed by 1% agarose gel electrophoresis. Two controls were included: pGAD\_empty and pGAD\_BUBR1.
Prior to gel analysis, plasmids were digested for 2 hours with HindIII and SmaI, enzymes that each cut the plasmid at a single site:
**HindIII** recognizes **AAGCTT** and generates 5′ overhangs (sticky ends);
**SmaI** recognizes **CCCGGG** and produces blunt ends

Expected fragment sizes were:

* pGAD\_empty: 520bp and 280bp;
* pGAD\_interactor: 950bp;
* pGAD\_BUBR1: 1350bp and 700bp

Once the expected bands were verified on the gel, plasmid DNA from one colony per construct was sent for Sanger sequencing at “BMR Genomics”, confirming the presence of the insert.

Additional plasmid DNA was obtained by re-inoculating the bacteria in LB + Amp and incubating overnight at 37°C, followed by mini-prep extraction using a kit. This material served both as a working plasmid for experiments and as a stock for the first three interactors in pGADT7, after Sanger sequencing confirmed their sequences.

### Transformation in Y190 for Y2H

As we obtained the results from all of the verification analyses, we proceeded to the chemical transformation in *S. cerevisiae* Y190 to generate the strains required for the Y2H assay.

All sequenced interactors were transformed into Y190 using our “**One-step protocol**:

* interactors 1,2, and 3: 20 µL and 80 µL of transformation mix plated;
* interactors 4 and 5: 50 µL of transformation mix plated

Plating was done on a permissive medium (SD Glucose -Leu), and cells were incubated at 28°C to grow.

Three days later, five colonies per interactor were re-streaked and incubated at 28°C for an additional three days. Once sufficient material was obtained, the yeast cultures were co-transformed via chemical method with:

* pGBK\_empty and pGBK\_progerin545 for all the five interactors;
* pGBK\_progerin430 just for the first three interactors

The transformation mix was plated on SD Glu -LEU -TRP agar, as successful internalization of the plasmids allows growth in this selective medium.

### Performing the Y2H assay

At this stage, all constructs were ready for testing, and positive and negative controls were preserved at 4°C. Cultures were inoculated in SD Glu -LEU -TRP medium overnight.
The following day, we performed the spot test according to our protocol on both the permissive medium (SD Glu Agar -TRP -LEU) and the selective medium (SD Glu Agar -TRP -LEU -HIS + 3-AT 30 mM), which allows growth only of yeast cells in which an interaction between progerin and the tested interactors occurs.

No growth was observed on the selective medium, indicating that the C-terminal fragments of progerin tested do not interact with the selected partners under these conditions.

![Spot Test Assay: Evaluation of Progerin_430 Interaction with Interactors 1–3 in Yeast Two-Hybrid System](https://static.igem.wiki/teams/5700/images/contribution/interactorsa-b-c-430.webp)

**Figure 5.** (A) Spot test assay to evaluate the interaction between progerin\_430 and Interactor 1 (colonies #1–#5), (B) Interactor 2 (colonies #1–#5) and (C) Interactor 3 (colonies #1–#5) SD\_GLU <LEU> <TRP> represents our positive control, because this medium selects transformed yeasts. On the other hand, SD\_GLU <LEU> <TRP> <HIS> +3-AT 30mM medium should select those yeast cells where interaction between progerin and interactors occurs. We can conclude that we’re unable to determine progerin 430 interaction with our three interactors, at least in the yeast two hybrid systems.

| No. | PLATE A | PLATE B | PLATE C |
| --- | --- | --- | --- |
| 1 | pGBK\_progerin 430 + pGAD\_∅ | pGBK\_progerin 430 + pGAD\_∅ | pGBK\_progerin 430 + pGAD\_∅ |
| 2 | pGBK\_progerin 430 + pool pGAD\_interactor 1 #1 | pGBK\_progerin 430 + pool pGAD\_interactor 2 #1 | pGBK\_∅ + pool pGAD\_interactor 3 |
| 3 | pGBK\_progerin 430 + pool pGAD\_interactor 1 #2&3 | pGBK\_progerin 430 + pool pGAD\_interactor 2 #2&3 | pGBK\_progerin 430 + pool pGAD\_interactor 3 #1 |
| 4 | pGBK\_progerin 430 + pool pGAD\_interactor 1 #4&5 | pGBK\_progerin 430 + pool pGAD\_interactor 2 #4&5 | pGBK\_progerin 430 + pool pGAD\_interactor 3 #2&3 |
| 5 | pGBK\_∅ + pool pGAD\_interactor 1 | pGBK\_∅ + pool pGAD\_interactor 2 | pGBK\_progerin 430 + pool pGAD\_interactor 3 #4&5 |

![Spot Test Assay: Evaluation of Progerin_545 Interaction with Interactors 1–3 in Yeast Two-Hybrid System](https://static.igem.wiki/teams/5700/images/contribution/interactorsd-e-f-545.webp)

**Figure 6.** (D) Spot test assay to evaluate the interaction between progerin\_545 and Interactor 1 (colonies #1–#5), (E) Interactor 2 (colonies #1–#5) and (F) Interactor 3 (colonies #1–#5) SD\_GLU <LEU> <TRP> represents our positive control, because this medium selects transformed yeasts. On the other hand, SD\_GLU <LEU> <TRP> <HIS> +3-AT 30mM medium should select those yeast cells where interaction between progerin and interactors occurs. We can conclude that we’re unable to determine progerin 545 interaction with our three interactors, at least in the yeast two hybrid system.

| No. | PLATE D | PLATE E | PLATE F |
| --- | --- | --- | --- |
| 1 | pGBK\_progerin 545 + pGAD\_∅ | pGBK\_progerin 545 + pGAD\_∅ | pGBK\_progerin 545 + pGAD\_∅ |
| 2 | pGBK\_progerin 545 + pool pGAD\_interactor 1 #1 | pGBK\_∅ + pool pGAD\_interactor 2 | pGBK\_∅ + pool pGAD\_interactor 3 |
| 3 | pGBK\_progerin 545 + pool pGAD\_interactor 1 #2&3 | pGBK\_progerin 545 + pool pGAD\_interactor 2 #1 | pGBK\_progerin 545 + pool pGAD\_interactor 3 #1 |
| 4 | pGBK\_progerin 545 + pool pGAD\_interactor 1 #4&5 | pGBK\_progerin 545 + pool pGAD\_interactor 2 #2&3 | pGBK\_progerin 545 + pool pGAD\_interactor 3 #2&3 |
| 5 | pGBK\_∅ + pool pGAD\_interactor 1 | pGBK\_progerin 545 + pool pGAD\_interactor 2 #4&5 | pGBK\_progerin 545 + pool pGAD\_interactor 3 #4&5 |

![Spot Test Assay: Evaluation of Progerin_545 Interaction with Interactors 4 and 5 in Yeast Two-Hybrid System](https://static.igem.wiki/teams/5700/images/contribution/interactors-g-h-545.webp)

**Figure 7.** (G) Spot test assay to evaluate the interaction between progerin\_545 and Interactor 4 (colonies #1–#5) and (H) Interactor 5 (colonies #1–#5) SD\_GLU   represents our positive control, because this medium selects transformed yeasts. On the other hand, SD\_GLU <LEU> <TRP> <HIS> +3-AT 30mM medium should select those yeast cells where interaction between progerin and interactors occurs.

| No. | PLATE G | PLATE H |
| --- | --- | --- |
| 1 | pGBK\_∅ + pGAD\_interactor 4 | pGBK\_∅ + pGAD\_interactor 5 |
| 2 | pGBK\_progerin 545 + pGAD\_∅ | pGBK\_progerin 545 + pGAD\_∅ |
| 3 | pGBK\_progerin 545 + pGAD\_interactor 4 #1&2 | pGBK\_progerin 545 + pGAD\_interactor 4 #1&2 |
| 4 | pGBK\_progerin 545 + pGAD\_interactor 4 #3&4&5 | pGBK\_progerin 545 + pGAD\_interactor 4 #3&4&5 |

### Validation of the interactors against lamin A

To further investigate the specificity of our selected interactors against progerin, the five chosen interactors were tested against its wild-type counterpart, lamin A.

We started by cloning the C-terminal sequence of lamin A (aa 430-646) into pGBKT7 (“bait” plasmid, expressing the binding domain “BD”) using Infusion cloning for 15 minutes at 55°C. The reaction was carried out at a molar ratio of 1:1, taking into account the concentration and length of both the plasmid and insert (pGBK vector: 7200 bp, 70 ng/µl; lamin A [BBa\_25K3P964](https://registry.igem.org/parts/bba-25k3p964): 686bp, 25 ng/µl).

The resulting construct was then transformed in *E. coli* Top10, and the transformation mix was plated on LB Agar + kanamycin (the vector carries kanamycin resistance) and incubated overnight at 37°C.

The following day, six colonies were selected and inoculated in LB + Kan to perform the mini-prep without kit the next day. The extracted plasmid DNA was quantified using the Nanodrop, and 1000 ng were digested to verify the insertion of lamin A in pGBK.

Plasmids were digested for 2 hours with **PstI** and **EcoRV**, enzymes that each cut the plasmid at a single site:

* **PstI** recognizes **CTGCAG** and generates 3′ overhangs (sticky ends);
* **EcoRV** recognizes **GATATC** and produces blunt ends

Digestion was verified by 1% agarose gel electrophoresis, using pGBK\_empty as a control. Once correct insertion was confirmed, the pGBK\_laminA plasmid was transformed into *S. cerevisiae* Y190 and co-transformed with the following pGADT7 plasmids:

* pGBK\_LaminA + pGAD\_∅
* pGBK\_LaminA + pGAD\_interactor1;
* pGBK\_LaminA + pGAD\_interactor4;
* pGBK\_LaminA + pGAD\_interactor5

Transformation and co-transformation mixes were plated on permissive medium (SD glucose -LEU) and incubated at 28°C for growth.

Three days later, five colonies for each interactor were picked and inoculated overnight at 28°C. Positive and negative controls, stored at 4°C, were also inoculated in SD Glu -LEU -TRP overnight.

Once we obtained sufficient material, we performed the spot test, according to our protocol, on both the permissive medium (SD Glu Agar -TRP -LEU) and the selective medium (SD Glu Agar -TRP -LEU -HIS + 3-AT 30 mM), which allows growth only of yeast cells in which an interaction between progerin and the tested interactors occurs.

No growth was observed on the selective medium, suggesting that the C-terminal fragment of lamin A does not interact with the tested partners. This result confirms that our selected interactors do not target lamin A, validating their specificity for progerin.

![Spot Test Assay: Validation of Interactors 1, 4, and 5 for Absence of Off-Target Binding to Lamin A](https://static.igem.wiki/teams/5700/images/contribution/lamina-interactors-i-l-m.webp)

**Figure 8.** Spot test assay to validate that interactor 1 (I), interactor 4 (L) and interactor 5 (M) do not show off-target binding to lamin A SD\_GLU <LEU> <TRP> represents our positive control, because this medium selects transformed yeasts. On the other hand, SD\_GLU <LEU> <TRP> <HIS> +3-AT 30mM medium should select those yeast cells where interaction between lamin A and interactors may occur.

| No. | PLATE I | PLATE L | PLATE M |
| --- | --- | --- | --- |
| 1 | pGBK\_∅ + pGAD\_interactor 1 | pGBK\_∅ + pGAD\_interactor 4 | pGBK\_∅ + pGAD\_interactor 5 |
| 2 | pGBK\_laminA + pGAD\_∅ | pGBK\_laminA + pGAD\_∅ | pGBK\_laminA + pGAD\_∅ |
| 3 | pGBK\_laminA + pGAD\_interactor 1 #1&2 | pGBK\_laminA + pGAD\_interactor 4 #1&2 | pGBK\_laminA + pGAD\_interactor 5 #1&2 |
| 4 | pGBK\_laminA + pGAD\_interactor 1 #3&4&5 | pGBK\_laminA + pGAD\_interactor 4 #3&4&5 | pGBK\_laminA + pGAD\_interactor 5 #3&4&5 |

## Protocols

▲

If the PDF does not load, [open it in a new tab](https://static.igem.wiki/teams/5700/pdf/yeast-laboratory-protocols.pdf).

## References

▲

* [1] Zhang, N., Hu, Q., Sui, T., Fu, L., Zhang, X., Wang, Y., Zhu, X., Huang, B., Lu, J., Li, Z., & Zhang, Y. (2023). Unique progerin C-terminal peptide ameliorates Hutchinson-Gilford progeria syndrome phenotype by rescuing BUBR1. Nature Aging, 3(2), 185–201. <https://doi.org/10.1038/s43587-023-00361-w>

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## Cell Lines and Experimental Setup

▲

To validate our constructs and investigate progerin degradation in a relevant biological context, we performed all our cell-based experiments using **MRC-5 human fibroblasts**.
MRC-5 cells are a diploid, non-tumorigenic cell line derived from normal human lung fibroblasts, commonly used as a model for physiological cellular processes such as growth, senescence, and oxidative stress. Their fibroblastic origin makes them a suitable system for studying progerin-associated phenotypes, which primarily affect connective tissue.

All experiments were conducted at the **Department of Molecular Medicine (DMM)**, **University of Padua**, inside **biosafety level-2 (BSL-2) cabinets**, ensuring proper containment and sterile handling.
Cell Housekeeping methods and protocols are linked:

* Freezing cell cultures: [Freezing\_Cells\_Benchling.pdf](https://static.igem.wiki/teams/5700/pdf/freezing-cells-benchling.pdf)
* Handling cell cultures: [Handling\_Human\_Cell\_Lines\_Benchling.pdf](https://static.igem.wiki/teams/5700/pdf/handling-human-cell-lines-benchling.pdf)
* Thawing cell cultures: [Thawing\_Cells\_Benchling.pdf](https://static.igem.wiki/teams/5700/pdf/thawing-cells-benchling.pdf)

Each transfection was performed using **Lipofectamine™ 3000** ([lipofectamine3000\_protocol.pdf](https://static.igem.wiki/teams/5700/pdf/lipofectamine3000-protocol.pdf) Thermo Fisher Scientific), following the manufacturer’s protocol, to achieve efficient delivery of plasmid constructs into mammalian cells.
Because MRC-5 cells are not included in the iGEM’s White List, we submitted a Check-In form (ID: oE95JbCxfaXB7whj844xfP).

To perform experiments in a disease-relevant model, we used primary fibroblast lines derived from Hutchinson–Gilford Progeria Syndrome (HGPS) patients, obtained through a scientific collaboration with Dr. Giovanna Lattanzi, a leading expert in laminopathies and Head of the Laminopathies and Muscle Biobank at the CNR Institute of Molecular Genetics in Bologna, Italy. These patient-derived fibroblasts faithfully reproduce the molecular and morphological hallmarks of Progeria, including aberrant nuclear morphology, increased oxidative stress, and reduced proliferative capacity, providing an ideal model to test the degradation system under pathological conditions.
Since these cell lines are not included in iGEM’s White List, we submitted a Check-In form (ID: f8GE5FZ1Qtx1A9267ZKPS8) to ensure compliance with iGEM safety standards.

As specified in the forms, our cell lines were tested to confirm the absence of mycoplasma and viral contaminants.
Official documentation certifying these results, signed by Prof. Claudia Del Vecchio (Microbiology, University of Padua) and Prof. Livio Trainotti (Project PI), is available at the following ([Declaration\_virus-free\_Padua.pdf](https://static.igem.wiki/teams/5700/pdf/declaration-virus-free-padua.pdf) )

## Total Reactive Oxygen Species (ROS) Assay Kit 520 nm Invitrogen

▲

Progeria is often associated with increased oxidative stress and elevated ROS production, contributing to the disease phenotype. To establish this phenotype and test for a potential reversal toward a healthy phenotype, we developed a ROS production assay to assess ROS levels in different transfected conditions.

**Experimental Setup:**
The experiment was performed in a 24-well plate, 5 × 104 MRC-5 fibroblasts were seeded on Day 0 and transfected using Lipofectamine™ 3000 on Day 1. The ROS Assay Reagent was added on Day 4, and the results were analyzed using the Varioskan™ plate reader on Day 6. The assay was performed in biological triplicates to ensure reproducibility. The assay was performed using **Total Reactive Oxygen Species (ROS) Assay Kit 520 nm (Thermo Fisher Scientific)** ([Total\_ROS\_Protocol.pdf](https://static.igem.wiki/teams/5700/pdf/total-ros-protocol.pdf)), following the manufacturer's protocol.

The following constructs were transfected into the wells:

* **HA-progerin:** To evaluate ROS production due to the presence of progerin;
* **SpyTag-progerin:** To determine the effect of progerin tagged with SpyTag on ROS levels;
* **mEGFP-progerin:** A fusion construct of progerin with mEGFP, used to investigate whether the addition of a fluorescent tag alters ROS production;
* **RING-mEGFP:** To assess the effect of the RING domain (fused to mEGFP) on ROS production, testing whether the RING domain influences oxidative stress;
* **RING-SpyCatcher:** To analyze whether the combination of the RING domain with SpyCatcher modifies ROS production, potentially due to the structural impact of SpyCatcher;
* **mEGFP-NLS:** Used as a control to evaluate whether the mEGFP tag alone contributes to ROS production;
* **mEGFP-SpyCatcher:** A control to test the effect of the SpyCatcher tag in the context of mEGFP-tagged constructs;
* **LMNA-SpyTag:** A lamin A control construct to compare progerin-induced ROS with a non-pathological lamin protein;
* **Negative control:** Untransfected cells used to establish baseline ROS production, representing normal ROS levels in cells not subjected to transfection or overexpression.

**Reasoning Behind Controls:**
The **negative control** (untransfected cells) was used to establish baseline ROS production, representing normal cellular ROS levels in the absence of transfected constructs.

The **HA-progerin** construct was used to assess the ROS production induced by progerin, which is known to contribute to oxidative stress. **SpyTag-progerin** was included to isolate the effect of the SpyTag itself on ROS production, helping us understand whether the tag exacerbates oxidative stress independently of progerin. The **mEGFP-progerin** fusion construct was employed to examine whether the addition of the fluorescent tag alters ROS levels, as mEGFP tags can sometimes cause misfolding or mislocalization of the protein, potentially influencing ROS production.

The **RING-mEGFP** construct was used to assess the effect of the RING domain (without the SpyCatcher system) on ROS production. This allows us to determine whether the RING domain alone influences oxidative stress. In contrast, the **RING-SpyCatcher** construct was used to explore whether the addition of SpyCatcher influences ROS production when combined with RING. This test is essential to evaluate whether **SpyCatcher’s structural role** modifies ROS production, potentially enhancing or mitigating oxidative stress compared to RING alone. The **mEGFP-NLS** and **mEGFP-SpyCatcher** constructs serve as controls to determine whether the mEGFP tag or the SpyCatcher system alone influences ROS production, ensuring that observed changes are due to the specific interactions of progerin and the RING-SpyCatcher system.

Finally, the **LMNA-SpyTag** control serves as a comparison to progerin-induced ROS production, providing a baseline of ROS levels associated with lamin A (a non-pathological form) and allowing us to distinguish between ROS production due to progerin expression and ROS generated by other factors.

**Readout:**
By comparing ROS levels across these constructs, we aimed to confirm whether the expression of progerin and its degradation system affected oxidative stress and to assess the potential therapeutic effects of the RING-SpyCatcher system in reducing ROS production.

## Cell Viability Assay in 96-Well Plates (alamarBlue™ Assay)

▲

Cellular viability is a critical factor in understanding the effects of progerin expression and the potential therapeutic effects of the RING-SpyCatcher system. In this experiment, we measured cell viability using the alamarBlue® assay, which provides a reliable readout of metabolic activity and cell proliferation.

**Experimental Setup:**
The experiment was performed in two identical 96-well plates, 1 × 104 MRC-5 fibroblasts were seeded on Day 0 and transfected using Lipofectamine™ 3000 on Day 1. A **second transfection** was performed on **Day 2**, and cell viability was assessed on **Day 5** and on **Day 7**. Fluorescence was measured using the Varioskan™ plate reader. The assay was performed in **octuplicate** to ensure robust results and statistical reliability. The assay was performed using **alamarBlue® Cell Viability Reagent (Invitrogen™)** ([AlamarBlue\_protocol.pdf](https://static.igem.wiki/teams/5700/pdf/alamarblue-protocol.pdf) ), following the manufacturer’s protocol.

The following constructs were transfected into the wells:

* **Control:** Untransfected cells, serving as a baseline for cell viability;
* **Progerin-SpyTag:** To assess the impact of progerin expression tagged with SpyTag on cell viability;
* **SpyTag-mEGFP-SpyTag + RING-SpyCatcher:** To evaluate whether the degradative activity of RING towards mEGFP affects cell viability;
* **Progerin-SpyTag + RING-SpyCatcher:** To investigate whether **Progerin degradation via the RING-SpyCatcher system** restores cell viability to normal levels or improves it;
* **LMNA-SpyTag:** A lamin A control construct to compare the effects of progerin-induced viability defects with a non-pathological lamin protein.

**Reasoning Behind Controls:**The **Control** group (untransfected cells) served as the baseline for cell viability, allowing us to evaluate the normal metabolic activity and proliferation of untreated cells. The **progerin-SpyTag** construct was included to determine whether progerin expression tagged with SpyTag alone has any effect on cell viability, as progerin is known to induce cellular defects in Progeria.

The **SpyTag-mEGFP-SpyTag + RING-SpyCatcher** construct was included to specifically test whether the **degradative activity of RING towards mEGFP** influences cell viability. Since the RING domain has been shown to promote protein degradation, we aimed to determine if this activity, when directed at mEGFP, could affect cell survival or metabolic activity.

The **progerin-SpyTag + RING-SpyCatcher** construct was included to evaluate whether **progerin degradation via the RING-SpyCatcher system** restores cell viability to normal levels or improves it. This was key to testing whether the degradation of progerin could reverse or mitigate the cellular defects caused by its accumulation, leading to improved cell survival and proliferation.

The **LMNA-SpyTag** control was used as a non-pathological comparison to progerin, allowing us to distinguish the specific impact of progerin on cell viability from that of the non-pathological lamin A.

**Readout:**
By comparing cell viability across these different constructs, we aimed to confirm whether progerin expression and its degradation system affected cell survival and to assess whether the RING-SpyCatcher system could restore or improve viability defects caused by progerin.

## Flow Cytometry (FACS) in 12-Well Plates

▲

Flow cytometry is a powerful technique for analyzing protein expression and degradation at the single-cell level. In this experiment, we used FACS to test whether **RING-SpyCatcher** could **degrade mEGFP** in the presence of **SpyTag**, by evaluating changes in mEGFP expression levels.

**Experimental Setup:**
The experiment was performed in a 12-well plate. 2.5 × 105 MRC-5 fibroblasts was seeded on Day 0 and transfected using Lipofectamine™ 3000 on Day 1, ensuring uniform cell density. A **second transfection** was performed on **Day 2** with the relevant constructs, and cell analysis was performed on **Day 4**. The assay was conducted in **duplicate** for each sample, with a **negative control** group used to establish the baseline fluorescence for untransfected cells.

On **Day 4**, we harvested the cells for **flow cytometry analysis**. Each well was washed twice with **PBS** to remove residual medium, and cells were detached by adding **trypsin** and incubating for **5 minutes at 37 °C**. Trypsinization was stopped by adding **DMEM supplemented with FBS**, and the resulting cell suspensions were transferred into **FACS tubes**. The duplicate wells were transferred into the same tubes. Samples were centrifuged for **8 minutes at 1500 rpm**, the supernatant was discarded, and the pellets were resuspended in **PBS**. This washing step was repeated **twice** under the same conditions. After the final centrifugation, the supernatant was removed and the cells were **resuspended in 250 µL of PBS** for immediate **FACS acquisition**.

The following constructs were transfected into the wells:

* **Control:** Untransfected cells, used to establish the baseline fluorescence (without mEGFP expression).
* **SpyTag-GFP-SpyTag:** To evaluate the expression of mEGFP in cells with SpyTag tags, without any degradation system.
* **RING-SpyCatcher + SpyTag-mEGFP-SpyTag:** To assess the effect of **RING-SpyCatcher** on mEGFP expression and test whether RING degrades mEGFP in the presence of the SpyTag/SpyCatcher system.

**Reasoning Behind Controls:**
The **Control** group (untransfected cells) served as the baseline for fluorescence, allowing us to measure any background signal from cells that do not express mEGFP.

The **SpyTag-mEGFP-SpyTag** construct was used to measure baseline mEGFP expression levels in cells transfected with the mEGFP construct tagged with SpyTag, but without the RING-SpyCatcher system, to establish normal mEGFP expression.

The **RING-SpyCatcher + SpyTag-mEGFP-SpyTag** construct was included to evaluate whether the **RING domain in combination with SpyCatcher** induces mEGFP degradation. A reduction in mEGFP fluorescence would indicate that the **RING-SpyCatcher system** is effectively promoting mEGFP degradation, confirming the system's functionality.

The **negative control** (untransfected cells) was included to measure the background fluorescence (or absence of mEGFP) and ensure that observed changes in fluorescence were due to the transfected constructs and not due to non-specific fluorescence.

**Readout:**
By analyzing the mEGFP signal through FACS, we aimed to assess whether **RING-SpyCatcher** can degrade mEGFP and to evaluate the effectiveness of the **SpyTag/SpyCatcher system** in inducing protein degradation.

## Western Blotting in 24-Well Plates

▲

Western blotting was performed to confirm the expression of progerin and to assess the degradation of **progerin-Tag** when co-transfected with **RING-Catcher**. For **HA-progerin**, we used an **anti-HA** antibody, while for all other constructs, we used **anti-progerin** antibody to detect progerin expression, kindly provided by **Diatheva** as part of our collaboration.

**Experimental Setup:**
The experiment was conducted in a 24-well plate, 1 × 105 MRC-5 fibroblasts were seeded on Day 0 and transfected using Lipofectamine™ 3000 on Day 1 and Day 2, only for certain wells. Cells were harvested on **Day 3** for **single transfections**, and on **Day 4** for **double transfections**, and protein was extracted for Western blot analysis.

The following constructs were transfected into the wells:

Single Transfection (Day 1, Analyzed on Day 3):

* **Control:** Untransfected cells, used to assess non-specific binding and background signals;
* **HA-progerin:** To confirm the expression of progerin tagged with the HA epitope using anti-HA antibody;
* **Progerin-SpyTag:** To assess the expression of progerin tagged with SpyTag using anti-progerin antibody;
* **Progerin-mEGFP:** To evaluate the expression change of progerin fused with mEGFP using **anti-progerin** antibody;
* **RING-Catcher:** This control helps ensure the antibody's specificity in detecting only progerin in the double transfection with RING-SpyCatcher construct;
* **mEGFP-NLS**: This control helps ensure the antibody's specificity in detecting only progerin in the double transfection with mEGFP-NLS construct.

Double Transfection (Day 1 + Day 2, Analyzed on Day 4):

* **Progerin-Tag + mEGFP:** To serve as a **baseline for progerin expression**, allowing us to compare the effects of **RING-Catcher** on progerin levels and degradation and it also ensures the same transfection conditions for both samples, without affecting **progerin expression**;
* **Progerin-Tag + RING-Catcher:** To evaluate **progerin degradation** when progerin-Tag is co-transfected with **RING-Catcher** using **anti-progerin** antibody. This condition tests whether the RING-SpyCatcher system induces progerin degradation, with **progerin-Tag + mEGFP** serving as the baseline control for the double transfection setup.

**Readout:**
By performing Western blot analysis on both **single transfection** (on Day 1, analyzed on Day 3) and **double transfection** (on Day 1 + Day 2, analyzed on Day 4) setups, we aimed to:

* **Confirm the expression of progerin** in the various tagged constructs (**HA-progerin, progerin-SpyTag, progerin-mEGFP**, etc.);
* Evaluate whether the **RING-SpyCatcher system** effectively induces progerin degradation, which is expected to reduce the progerin signal in the **progerin-Tag + RING-Catcher** condition compared to **progerin-Tag + GFP**

## Fluorescence Microscopy Analysis

▲

Fluorescence microscopy was used to assess the localization of the **RING-mEGFP, progerin-mEGFP**, **progerin-SpyTag + mEGFP-SpyCatcher**, **mEGFP-NLS**, and **SpyTag-mEGFP-SpyTag** constructs within the transfected cells. The analysis aimed to visualize the expression and subcellular localization of these constructs, which is crucial for understanding the behavior of the tagged proteins in relation to progerin and RING domains. Fluorescence was analyzed using an excitation wavelength of **488 nm** and an emission wavelength of **525 nm**, detected in the **FITC channel**.

**Experimental Setup:**
The cells were transfected with the following constructs:

* **RING-mEGFP:** This construct was used to assess the localization of the **RING domain** tagged with mEGFP. It was important to confirm that the RING domain was properly expressed and localized in the cells, particularly in the **nucleus**, where it might interact with progerin or other substrates for degradation;
* **Progerin-mEGFP:** The **progerin-mEGFP** fusion was used to visualize the localization of progerin in cells. Since progerin has been associated with mislocalization and aggregation, this construct was essential to confirm whether the mEGFP tag interferes with progerin’s natural localization pattern and whether the fusion alters its cellular behavior;
* **Progerin-SpyTag + mEGFP-SpyCatcher:** This construct was used to assess whether the **SpyTag-SpyCatcher interaction** affects the localization of progerin. It allowed us to test if the **SpyCatcher system** alters the distribution of progerin in cells, particularly in the context of protein aggregation or mislocalization, which could be a relevant factor in Progeria;
* **mEGFP-NLS:** This construct serves as a **nuclear localization control**, ensuring that mEGFP can be directed to the nucleus when tagged with an NLS. This control helped to confirm that the mEGFP tag itself does not cause mislocalization, providing a baseline for comparison with the other constructs;
* **SpyTag-mEGFP-SpyTag:** This construct serves to confirm the **nuclear localization of mEGFP** even if tagged with the double SpyTag. This control helped to confirm that the SpyTag does not cause mislocalization, providing a baseline for comparison with the other constructs.

**Methodology:**
The cells for these constructs were **not re-transfected** specifically for this experiment but instead, images were acquired from transfections performed as part of other experiments. On **Day 3** (for single transfections) and **Day 4** (for double transfections), fluorescence microscopy was used to capture the images of these constructs under appropriate excitation settings for mEGFP.

**Purpose:**
The purpose of this fluorescence microscopy analysis was to:

* **Visualize the subcellular localization** of the **RING-mEGFP**, **Progerin-mEGFP**, and **progerin-SpyTag + mEGFP-SpyCatcher** constructs;
* **Determine the impact of mEGFP fusion and SpyCatcher** on **progerin localization**, especially in terms of whether it causes aggregation or mislocalization;
* **Verify the proper nuclear localization** of the mEGFP-tagged proteins, especially in the **mEGFP-NLS** construct, to ensure that any mislocalization observed in **progerin-mEGFP** or **progerin-SpyTag + mEGFP-SpyCatcher** was not due to mEGFP itself but rather the nature of the fusion.

**Conclusion:**
This microscopy analysis provided important visual data on the localization of progerin and RING constructs within cells, shedding light on the potential effects of the fusion tags and **SpyCatcher interaction** on protein behavior and subcellular distribution.

## Constructs

▲

In the following paragraphs, we provide a detailed description of the pipeline we followed to generate the constructs required for future transfections.

| Constructs | Registry ID | Reference |
| --- | --- | --- |
| HA-progerin | [BBa 25B01XHB](https://registry.igem.org/parts/bba-25b01xhb) | A |
| SpyTag-progerin | [BBa\_25IIEVZB](https://registry.igem.org/parts/bba-25iievzb) | B |
| mEGFP-progerin | [BBa\_25Y190DU](https://registry.igem.org/parts/bba-25y190du) | C |
| RING-mEGFP | [BBa\_256804GM](https://www.addgene.org/BBa_256804GM) | D |
| RING-SpyCatcher | [BBa\_255KDS7V](https://registry.igem.org/parts/bba-255kds7v) | E |
| mEGFP-NLS | [BBa\_252QSG7W](https://registry.igem.org/parts/bba-252qsg7w) | F |
| mEGFP-SpyCatcher | [BBa\_257EBH49](https://registry.igem.org/parts/bba-257ebh49) | I |
| LMNA-SpyTag | [BBa\_2505I756](https://registry.igem.org/parts/bba-25o5i756) | K |
| SpyTag-mEGFP-SpyTag | [BBa\_2507I0A8](https://registry.igem.org/parts/bba-25o71oa8) | M |
**Table 1.**  List of cloned constructs for experimentation activities in MRC5 cells.

**Preliminary experiments**
Enzyme Functionality Check
First of all, it was necessary to verify the activity of BamHI-HF and XhoI.
Three digestion reactions and one negative control were prepared, for a total of four tubes containing, respectively:

1. 150 ng of pcDNA3.1 plasmid + 0.5 µL BamHI HF + 2 µL restriction buffer + H2O up to a final volume of 20 µL;
2. 150 ng of pcDNA3.1 plasmid + 0.5 µL XhoI + 2 µL restriction buffer + H2O up to a final volume of 20 µL;
3. 150 ng of pcDNA3.1 plasmid + 0.5 µL BamHI HF + 0.5 µL XhoI + 2 µL restriction buffer + H2O up to a final volume of 20 µL;
4. 150 ng of pcDNA3.1 plasmid + H2O up to a final volume of 20 µL

The reactions were incubated at 37°C for 40 minutes in a water bath. At the end, an electrophoresis was performed. The expected bands were observed: a single band for the first three samples, since the enzymes have a single cutting site within the pcDNA3.1 plasmid, and a smear in the fourth lane, corresponding to the uncut plasmid. The latter appears in multiple isoforms, differing in the degree of supercoiling, and therefore does not show a single defined band. The functionality of the enzymes was thus confirmed.

When the plasmid was digested, either with BamHI HF or with XhoI, a single band was observed even though the two sites were not overlapping; therefore, a second band at a lower molecular weight corresponding to the DNA fragment between the two sites should also be visible. This does not occur because the sites are only 60 bp, so the fragment migrates too fast and runs off the gel before detection.

**Linearization of pcDNA3.1**
Before proceeding with cloning, it was necessary to linearize the pcDNA3.1 plasmid by restriction digestion with BamHI HF and XhoI. The pcDNA3.1 plasmid had previously been amplified through transformation in *E. coli* DH5α cells and then extracted using the PureLink™ HQ Mini Plasmid Purification Kit (Invitrogen).

From the extracted plasmid DNA, three vials were prepared, each containing:

* 5 µg of plasmid DNA (concentration 230 ng/µL, added volume = 21.7 µL);* 2 µL BamHI HF;
  * 2 µL XhoI;
  * 3 µL Buffer (10X)
  * H₂O up to a final volume of 30 µL.

The reaction was incubated for 40 minutes in a water bath at 37°C. After 40 minutes, 1 µL of BamHI HF and 1 µL of XhoI were added, and the vials are left for another 40 minutes in the water bath at 37°C. An electrophoresis was performed to check the linearization: one sample from each vial and one uncut plasmid sample are loaded as a control.

The bands correspond to expectations: each digested plasmid showed a single well-defined band, and a smear for the uncut plasmid because it exists in multiple isoforms that migrate differently depending on the degree of supercoiling. The plasmids were then purified using the QIAquick Gel Extraction Kit (QIAGEN) and quantified with NanoDrop.

| Sample | DNA (ng/µL) | A260/A280 | A260/A230 |
| --- | --- | --- | --- |
| pcDNA3.1 1 | 73.8 | 1.85 | 0.18 |
| pcDNA3.1 2 | 69.3 | 1.86 | 0.30 |
| pcDNA3.1 3 | 71.8 | 1.85 | 0.22 |
**Table 2.**  pcDNA3.1 Quantification. For each sample, two reliable measurements were performed, and the table reports the average value. The A260/230 ratio was very low, most likely due to incomplete removal of carbohydrates by the purification kit.

**pJET1.2 cloning**All constructs arrived lyophilized, were rehydrated, and then used for ligation into pJET1.2.
The reactions were set up in the following way:

| Components | Volume (µL) | Note/Concentration |
| --- | --- | --- |
| pJET1.2 | 1 | 50 ng/µL |
| Insert DNA | See Note | Ratio 1:3 (Vector:Insert) |
| Buffer (10x) | 10 | 10x |
| T4-DNA ligase | 1 |  |
| nuclease free H2O | 8 | Calculated Volume |
| Final Volume | 20 |  |
**Table 3.**  Ligation reaction in pJET1.2.

The ligation product was then used to transform *E. coli* DH5α competent cells, which were plated on LB agar plates containing ampicillin (100 µg/mL) and incubated overnight.

**Procedure:**

1. Thaw competent *E. coli* DH5α cells on ice;
2. Add plasmid DNA to the cells and gently tap the tube to mix;
3. Incubate on ice for **30 min**;
4. Heat shock at **37°C for 3–4 min**;
5. Immediately return the cells to ice;
6. Add **200 µL LB medium (no antibiotic)** and incubate at **37°C for 45 min**;
7. Plate **100 µL** of the culture onto LB agar + ampicillin (100 µg/mL). Spread evenly until dry;
8. Incubate plates **overnight at 37°C**;
9. The following day, pick isolated colonies and inoculate into tubes containing **3 mL LB + ampicillin (100 µg/mL)**.

The first constructs subjected to this process were A, B, and C. To verify the transformation efficiency of the pJET1.2 plasmid, six colonies per plate were selected the following day. Once the high efficiency of transformation into pJET1.2 was confirmed, three colonies were selected for each of the remaining constructs (D, E, F, I, K, M).

From each selected colony, corresponding inocula were prepared and numbered for identification. These were incubated overnight at 37°C with shaking at 150 rpm. The following day, plasmid DNA was extracted using the PureLink™ HQ Mini Plasmid Purification Kit (Invitrogen) and quantified with NanoDrop.

| Sample | DNA (ng/µL) | A260/A280 | A260/A230 |
| --- | --- | --- | --- |
| A1 | 24.2 | 2.10 | 2.10 |
| A2 | 31.7 | 1.56 | 1.81 |
| A3 | 53.1 | 1.79 | 1.87 |
| A4 | 85.8 | 1.50 | 1.26 |
| A5 | 50.4 | 1.75 | 1.64 |
| A6 | 45.4 | 1.78 | 1.82 |
| B1 | 114.6 | 1.85 | 2.11 |
| B2 | 23.5 | 1.94 | 2.08 |
| B3 | 56.7 | 1.82 | 1.88 |
| B4 | 85.9 | 1.87 | 2.27 |
| B5 | 88.9 | 1.73 | 1.95 |
| B6 | 58.4 | 1.87 | 2.37 |
| C1 | 51.9 | 1.90 | 2.37 |
| C2 | 75.3 | 1.81 | 1.89 |
| C3 | 104.5 | 1.45 | 1.13 |
| C4 | 61.2 | 1.89 | 2.12 |
| C5 | 74.2 | 1.88 | 2.19 |
| C6 | 55.0 | 1.88 | 2.25 |
| D1 | 64.4 | 1.84 | 1.87 |
| D2 | 46.8 | 1.91 | 2.04 |
| D3 | 207.5 | 1.89 | 2.23 |
| E1 | 60.9 | 1.88 | 2.10 |
| E2 | 49.1 | 1.91 | 2.23 |
| E3 | 44.2 | 1.90 | 2.16 |
| F1 | 67.1 | 1.87 | 2.08 |
| F2 | 4.5 | 1.84 | 2.16 |
| F3 | 62.5 | 1.87 | 2.05 |
| I1 | 54.0 | 1.86 | 2.03 |
| I2 | 91.1 | 1.72 | 1.52 |
| I3 | 24.6 | 1.80 | 2.01 |
| K1 | 73.0 | 1.85 | 2.05 |
| K2 | 86.6 | 1.85 | 2.20 |
| K3 | 70.9 | 1.81 | 2.01 |
| M1 | 121.1 | 1.89 | 2.21 |
| M2 | 100.0 | 1.88 | 2.22 |
| M3 | 107.8 | 1.90 | 2.15 |
**Table 4.**  Quantification of pJET1.2 containing inserts A, B, C, D, E, F, K, I, M. For each sample, two reliable measurements were performed, and the table reports the average value

Following quantification, a portion of the extracted plasmid DNA was used to perform a restriction digestion with the enzymes BamHI HF and XhoI.

The reactions were set up in the following way:

| Component | Volume (µL) | Note |
| --- | --- | --- |
| DNA | 1.5 |  |
| Buffer CutSmarter (10x) | 2 | 10x |
| BamHI HF | 0.5 | Restriction Enzyme |
| XhoI | 0.5 | Restriction Enzyme |
| nuclease free H2O | 15.5 | Calculated Volume |
| Final Volume | 20 |  |
**Table 5.**  Restriction digestion with BamHI HF and XhoI

The restriction product was then analyzed by electrophoresis to assess whether the plasmid contained the desired insert. Positive samples displayed two distinct bands at different molecular weights: one corresponding to the plasmid backbone, and the other, lighter, corresponding to the insert. If the insert band aligned with the expected molecular weight, the sample was considered positive.

The positive samples were: A3, A4, A5, B3, B4, B5, B6, C1, C2, C4, C6, D1, D3, E1, E2, F1, F2, F3, I1, I2, K1, K3, M1, M2, M3.
We chose to proceed with A3, B5, C2, D3, E1, F3, I2, K1, and M1 because these samples displayed higher DNA concentrations as measured by NanoDrop.

**pcDNA3.1 cloning**
Restriction digestion was performed on all plasmid DNA from positive samples. Since NanoDrop measurements indicated low concentrations, the entire 42 µL of DNA was used instead of the 5 µg specified by the protocol.

The reactions were set up in the following way:

| Component | Volume (µL) | Note |
| --- | --- | --- |
| DNA | 41 | Fixed for enriching 50 µL final volume |
| Buffer CutSmarter (10x) | 5 | 10x |
| BamHI HF | 2 | Restriction Enzyme |
| XhoI | 2 | Restriction Enzyme |
| nuclease free H2O | 0 | Calculated Volume (the sum of the components is 50 µL) |
| Final Volume | 50 | Target Volume |
**Table 6.**  Restriction digestion for positive control.

Digestion products were run on a 1% agarose gel with wide wells, clearly separating the plasmid backbone (higher molecular weight) from the insert (lower molecular weight). Insert bands were excised and purified using the QIAquick Gel Extraction Kit (QIAGEN).

The first three samples were quantified by NanoDrop to determine the volume required for ligation at a 3:1 insert-to-plasmid ratio. Purified inserts were ligated into the previously digested pcDNA3.1 plasmid, and the ligation reaction was incubated overnight.

The reactions were set up in the following way:

| Component | Volume (µL) | Note/Concentration |
| --- | --- | --- |
| pcDNA3.1 | 2 | 70 ng/µL |
| Insert DNA | See Note | Ratio 1:3 (Vector:Insert) |
| Buffer (10x) | 2.5 | 10x |
| T4-DNA ligase | 1 |  |
| nuclease free H2O | 19.5 | Calculated Volume |
| Final Volume | 25 |  |
**Table 7.**  Ligation into previously digested pcDNA3.1

Two control ligation reactions were prepared:

1. **Plasmid with restriction enzymes:** This control was included to confirm complete digestion of the plasmid DNA by both restriction enzymes. In cases of incomplete digestion, the plasmid may remain intact or be cleaved at a single site, thereby generating compatible ends that could be re-circularized by the ligase. Transformation with uncut or re-circularized plasmid DNA results in colony formation;
2. **Plasmid only:** This control was performed to exclude the occurrence of colonies arising from spontaneous plasmid re-circularization or external contamination, thus ensuring that colony growth in experimental reactions reflected specific ligation events.

The following day, chemically competent *E. coli* DH5α cells were transformed with the ligation products and plated on LB agar with ampicillin. Two vials of competent cells were also transformed with the control ligation reactions. After overnight incubation, all plates showed growth except for the control plate transformed with linearized plasmid without ligase. In contrast, ≈180 colonies appeared on the plate from the first control, due to T4 ligase re-ligating a 69 bp fragment left between the restriction sites, allowing colony growth.

This unintended re-ligation may also have occurred in experimental ligations. To verify, six colonies from each plate were selected, grown overnight at 37 °C with shaking (150 rpm), and plasmid DNA was extracted using the PureLink™ HQ Mini Plasmid Purification Kit (Invitrogen). Restriction digestion with BamHI-HF and XhoI followed by agarose gel electrophoresis confirmed positive clones.

Positive samples displayed two distinct bands: one corresponding to the plasmid backbone and the other at the molecular weight consistent with the expected insert length. The first gel did not allow us to determine which samples were positive, as the molecular weight marker was lost during electrophoresis.

It was necessary to repeat the restriction reaction and load a new gel, from which the following samples were identified as positive: A3.3, B5.1, C2.3, D3.1, D3.4, E1.1, E1.5, F3.1, F3.2, F3.3, F3.4, I2.2, I2.3, K1.1, K1.2, K1.3, K1.5, K1.6, M1.2.

We selected samples A3.3, B5.1, C2.3, D3.1, E1.1, F3.3, I2.2, K1.3, and M1.2 for sequencing based on band quality and intensity.

Quantification of the positive samples selected for sequencing was then performed.

| Sample | DNA (ng/µL) | A260/A280 | A260/A230 |
| --- | --- | --- | --- |
| A3.3 | 237.3 | 1.77 | 2.01 |
| B5.1 | 148.2 | 1.75 | 2.01 |
| C2.3 | 373.5 | 1.93 | 2.31 |
| D3.1 | 123.0 | 1.91 | 2.16 |
| E1.1 | 420.0 | 1.90 | 2.21 |
| F3.3 | 610.0 | 1.94 | 2.32 |
| I2.2 | 421.3 | 1.93 | 2.20 |
| K1.3 | 218.0 | 1.93 | 2.36 |
| M1.2 | 539.2 | 1.83 | 2.25 |
**Table 8.**  Quantification of pcDNA3.1 containing inserts A3.3, B5.1, C2.3, D3.1, E1.1, F3.3, I2.2, K1.3, M1.2. For each sample, two reliable measurements were performed, and the table reports the average value.

**Sequencing**
 In addition to the positive samples, we also decided to send E1.4 and M1.3 for sequencing. Both displayed two bands that, based on their molecular weight, could correspond to two different constructs. This likely indicates contamination, where two different colonies were inoculated into the same tube: half of the bacteria transformed with one construct and half with another.

Before sequencing, the previously extracted DNA was amplified using the Applied Biosystems™ BigDye™ Terminator v3.1 Cycle Sequencing Kit (Fisher Scientific).

We set up 22 PCR reactions, 2 for each sample: one with the CMV forward primer and one with the BGH reverse primer.

The thermocycler was programmed according to the following protocol:

| Step | Temperatura (°C) | Tempo (minuti:secondi) | Cicli (N°) |
| --- | --- | --- | --- |
| Initial denaturation | 96.0 | 2:52 | 1 |
| Denaturation | 96.0 | 0:10 |  |
| Annealing | 50.0 | 0:05 | 45 |
| Extention | 60.0 | 4:00 |  |
| Final step | 4.0 | Hold | 1 |
**Table 9.**  PCR reaction.

Before proceeding with automatic Sanger sequencing, the samples were purified from PCR reagents using the OPTIMA DTR™ 96-Well Plate kit (EdgeBio).
The obtained sequences were then compared with the expected ones through BLAStn alignments, where our ordered sequence was set as Subject and the sequencing results as Query.

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{% endblock %}

{% extends "layout.html" %}
{% block toc\_enabled %}true{% endblock %}
{% block title %}Results{% endblock %}
{% block lead %}Page Lead{% endblock %}
{% block intro\_block %}

# Results

Our results demonstrate a targeted approach for progerin degradation, built upon three core pillars: bioinformatics, yeast and mammalian cells. Using computational tools, we designed peptide binders targeting the C-terminal tail of progerin, which were validated through *in silico* predictions and in vitro assays. In yeast, we tested their efficacy, while bioinformatics provided insights into binding specificity. Finally, mammalian cell assays evaluated our system’s potential as a therapeutic strategy for Progeria.

▲

❮

![Overview of the Computational Strategy for Designing Selective progerin Binders](https://static.igem.wiki/teams/5700/images/results/graphical-abstract-bioinfo.webp)

Computational Strategy for Designing Selective Progerin Binders
Created with Biorender.com

![Yeast Laboratory Project Scheme](https://static.igem.wiki/teams/5700/images/results/project-yeast-new.avif)

Yeast Laboratory Project Scheme for Progeria Phenotype Investigation
Created with Biorender.com

![ProgERASE Strategy Graphical Abstract](https://static.igem.wiki/teams/5700/images/results/project-description-mam.webp)

ProgERASE: Stepwise Strategy for Targeted Progerin Degradation
Created with Biorender.com

❯

* [Computational Biology](#1st-pillar)
* [Yeast Model Testing](#2nd-pillar)
* [Mammalian Cells Validation](#3rd-pillar)

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{% block page\_content %}

## Introduction

▲

Our project leverages a sophisticated bioinformatics pipeline to design and evaluate synthetic peptides aimed at selectively binding the intrinsically disordered C-terminal region of progerin, a truncated form of lamin A implicated in Hutchinson-Gilford Progeria Syndrome (HGPS). Artificial Intelligence (AI)-based platforms like AlphaFold combined with generative models such as RFdiffusion and ProteinMPNN, have paved the way for new approaches in protein design, particularly in targeting intrinsically disordered regions (IDRs). In our work, we integrated these AI-based models with molecular docking platforms such as HADDOCK and ClusPro, which enable us to simulate and assess potential interactions between designed peptides and progerin.

The pipeline begins with structural modeling of progerin, followed by the design of peptide binders using RFdiffusion and ProteinMPNN, which generate sequences expected to fold into specific structural motifs. These peptides are then subjected to docking simulations, where their interaction with progerin is evaluated. The integration of advanced tools like AlphaFold3 allows us to model even disordered regions, which are notoriously difficult to study experimentally. The results of docking simulations are further refined through affinity estimation using PRODIGY, providing us with valuable insights into the binding strength of each candidate. This multi-step, AI-driven pipeline provides a powerful framework for designing selective peptide binders for progerin, a critical step in developing therapeutic strategies for HGPS.

Our computational pipeline enabled the exploration of a broad library of designed peptides to assess their potential binding to the flexible C-terminal tail of progerin. We identified candidates displaying consistent and promising binding behavior. Our workflow illustrates how rational design, sequence analysis, and energy-based evaluation can effectively guide the selection of peptide binders with high confidence for subsequent experimental validation.
More information about our pipeline design in our wiki [Model page](%7B%7B%20url_for%28%27pages%27%2C%20page%3D%27model%27%29%20%7D%7D).

## Phase 1: Computational Predictions and Binders Design

▲

Our docking analysis revealed that our binders exhibited heterogeneous binding patterns. Some peptides designed with RFdiffusion on the full-length structure of progerin only weakly interacted with the C-terminal region or did so in clusters of limited size, suggesting that these interactions were not significant. In contrast, other binders consistently engaged the C-terminal tail and produced several clusters of considerable size, indicating reproducible and reliable interactions. This agreement with hotspot-driven docking adds confidence to the overall analysis.

For the binders modelled on individual C-terminal fragments, the picture is more complex. Since IDRs can adopt multiple conformations, the AlphaFold3 model of full-length progerin represents only one possible conformation. This means that the lack of interaction in docking simulations does not necessarily indicate a binder would fail, but rather that the interaction may require or induce alternative conformations of the protein to engage properly.

Based on these observations, we selected for affinity prediction only the binders that displayed interactions in proximity to the last 15 residues of their fragment, corresponding to the hotspot region defined during design with RFdiffusion. In addition, binders that also docked at the C-terminal tail of full-length progerin were considered as particularly promising candidates, as they suggested a stronger and more consistent affinity for that region. In total, we analyzed approximately 350 interactors; the sequences are provided in the supplemental materials.

### Application of other techniques for binding design

Furthermore, for the binders designed against full-length progerin, the fifteen sequences retained from ProteinMPNN were subjected to multiple sequence alignment (MSA), revealing which positions were conserved and which varied across different designs.
Stability analyses were then performed using the Stabilize Protein protocol in ROSIE, which suggested specific substitutions to increase the thermodynamic stability of the candidates. From this process, a consensus sequence was derived and designated as LOGO, in which certain residues were substituted to enhance stability, while others were replaced according to the consensus from the alignment. LOGO represents our rational design approach, using a consensus sequence optimized based on previous observations (Figure 2).

![Insights into LOGO: Rational Design and Interaction Analysis with progerin](https://static.igem.wiki/teams/5700/images/results/logo-lagorai.webp)

**Figure 2.** Insights into LOGO, the interactor obtained through rational design. A: Schematic illustrating how the LOGO sequence was generated for rational design, by analyzing the most frequent amino acids and their properties. B and C: Analysis of the interaction between progerin and the LOGO interactor.

In addition to the main computational pipeline, we employed NeuroBind, which was not part of our main workflow, but was used to explore additional candidates outside the RFdiffusion–ProteinMPNN design process. NeuroBind generated 25 candidate binders in a single run, which were subsequently inspected in ChimeraX. Candidates that produced unrealistic conformations of progerin were discarded. The remaining models were retained for downstream analysis.

After refinement of the docking complex, the binding affinities of the complexes were estimated with PRODIGY at 36 °C. For the HADDOCK results, the first model from the top three clusters ranked by HADDOCK score was analyzed for each binder. For the ClusPro docking against full-length progerin, all clusters in which the interaction involved the C-terminal region were evaluated, while for the fragment-based docking, only the first two clusters by size were considered. For each case, the predicted Kd values were averaged by calculating a weighted mean, in which the weight was given by the cluster size. This procedure yielded one mean Kd per binder from HADDOCK and one from ClusPro.

### Insights from the selected models

Table 1 summarizes key properties of the five interactors selected for laboratory validation. The conformations of these interactors vary to explore which structural features correlate with optimal binding to the progerin C-terminus. **62aa11\_1** adopts an α-helical structure and stands out for its strong binding affinity to the 62-residue C-terminal fragment, with a Kd of 4.90 × 10⁻⁹ M. **LOGO** and **n80\_02** are both globular interactors. LOGO was designed rationally and demonstrates a satisfactory binding affinity to the progerin C-terminus (7.50 × 10⁻⁸ M), while n80\_02 was generated through our computational pipeline.

**Rank 15** and **Rank 21** were produced using NeuroBind, which predicts very high binding affinities. We included these to assess the potential of this bioinformatic tool. Their structures are less well defined and more disordered than the other interactors, reflected in relatively low pTM scores of 0.20 for Rank 15 and 0.32 for Rank 21.

| Interactor | pTM | HADDOCK Kd Progerin | Sequence | Structure |
| --- | --- | --- | --- | --- |
| 62aa11\_1 | 0.76 | 9.32E-07 | GLEEAQRRAEEARRQIALANRAGRDQEEAARLQRELEALEAEIEEAKTG | ![62aa11_1 structure](https://static.igem.wiki/teams/5700/images/model/62aa11.webp) |
| LOGO | 0.44 | 7.50E-08 | APGRGRCRGNPPVCCCPNCPRCDADCTQGGGSGCPACPCP | ![LOGO structure](https://static.igem.wiki/teams/5700/images/model/logo.webp) |
| n80\_02 | 0.33 | 6.92E-08 | AAGCGRCIGNPPVCCCCNCPECGQDCTQCGGSGCPNCPCP | ![n80_02 structure](https://static.igem.wiki/teams/5700/images/model/n80-02.webp) |
| Rank 15 | 0.2 | 1.08E-17 | GLPLPELDLPEAMFRGKCAQANGAGASGTTHTAPPPEPREPLSGE | ![Rank 15 structure](https://static.igem.wiki/teams/5700/images/model/rank15.webp) |
| Rank 21 | 0.32 | 5.15E-15 | ACAGSPRNCPAPCTGTDCPPCPGPAFEGDTEKPGPGEPPRGGAGG | ![Rank 21 structure](https://static.igem.wiki/teams/5700/images/model/rank21.webp) |
**Table 1.**  Key information about the interactors tested in the laboratory, including their pTM (prediction confidence), the predicted Kd from HADDOCK for the interaction with the full-length progerin C-terminus, as well as the peptide sequence and structural features. Other interactors were interesting for further analysis, but we only had the possibility to test 6 of them. The sequences of all the other interactors are present in the supplemental materials section.

### Conclusion

We developed a computational pipeline for the de novo design of peptide binders selectively targeting the C-terminal tail of progerin, combining structural modeling, sequence design, docking, and PRODIGY-based affinity prediction. From an initial library of 96 candidates, nine binders were selected with consistent engagement of the C-terminal region and estimated dissociation constants in the nanomolar range or lower.

While limited by single AlphaFold3 conformations and rigid docking, the approach demonstrates the feasibility of designing selective binders for intrinsically disordered regions. Future experimental validation in yeast and human cells will test these predictions and guide iterative optimization, supporting the design of effective interactors for the ProgERASE therapeutic strategy.

These results must be interpreted in light of recent advances in the field. In particular, two studies recently published on Nature and Science by the Baker Lab have introduced pipelines for designing binders against intrinsically disordered regions, which have long been regarded as inaccessible to rational design [[1]](https://doi.org/10.1038/s41586-025-09248-9), [[2]](https://doi.org/10.1126/science.adr8063) . While our strategy shares some core elements with these pipelines, such as the integration of deep generative models and docking simulations, their approaches explicitly account for the conformational ensemble of the disordered region, either by co-folding the target and binder during diffusion or by guiding design with multiple conformations and secondary structure propensities. In contrast, our method relies on AlphaFold3 snapshots of individual conformations combined with rigid docking, which inevitably restricts the exploration of the full structural heterogeneity of the IDR. These differences underline both the strengths and the limitations of our method. While it demonstrates the feasibility of designing selective binders for disordered regions, it also highlights the need for broader conformational sampling. In particular, AlphaFold3 predictions could have been expanded by using multiple random seeds, thereby capturing a larger ensemble of conformations of the disordered C-terminal tail, and secondary structure predictions could have been integrated to better approximate its conformational landscape. Moreover, more extensive sampling during binder design would likely have increased the diversity of viable candidates. Such refinements would bring our pipeline closer to the state of the art in IDR-targeted binder design and represent clear directions for methodological improvement in future work.

#### Laboratory Experimentation

These computational predictions will require rigorous experimental validation. First, the interaction between the designed peptides and progerin has been assessed using a yeast two-hybrid assay to detect direct interactions in a cellular context (visit our yeast [wiki page](%7B%7B%20url_for%28%27pages%27%2C%20page%3D%27description%27%29%20%7D%7D)). In parallel, the NanoLuc® Binary Technology (NanoBiT) complementation assay will be applied in human MRC-5 fibroblasts to confirm binding under physiologically relevant conditions. Finally, quantitative affinity measurements will be carried out by Microscale Thermophoresis (MST) and Spectral Shift on a Monolith X instrument (NanoTemper Technologies), enabling the precise determination of dissociation constants for the peptide–progerin complexes (visit our [Mammalian Cell Validation](%7B%7B%20url_for%28%27pages%27%2C%20page%3D%27experiments%27%29%20%7D%7D) wiki page. Together, these experiments will provide critical validation of our computational predictions and allow us to refine the design pipeline through an iterative cycle of in silico modeling and *in vitro* testing.

## Phase 2: Binding Affinity Analysis of the Interactor with progerin and lamin A

▲

The entire phase 2 was carried out in parallel with, and subsequently to, the experimental testing of the interactors, due to the time constraints of the iGEM competition. The results presented from this point onward did not have a direct impact on the project, but they will become relevant if the study is continued.

### Step 1 - Without RING domain

After predicting the interactors using AI-driven tools and trying to target specifically progerin, further analyses involve the measurement of the binding affinity with lamin A to inspect if our peptides can discriminate between the two proteins. To do that, we continued our analyses focusing on the first 9 interactors that showed the strongest binding affinity with progerin. First, we predicted the interactors using Alphafold3 a second time, in order to be sure to continue the analyses with the best structures possible as we wanted to refine and test effectively the binding capability of both lamin A and progerin. After obtaining the AlphaFold structures, we ran the relax cycle and we checked the structure integrity using MolProbity as we previously described. For each interactor, we maintained the structure that showed the best features and compromise between a low energy level and a good MolProbity score. The same was performed for lamin A.

| Interactor | Energy | | | | MolProbity score | | |
| --- | --- | --- | --- | --- | --- | --- | --- |
| Pre-Relax | Post-AMBER | Post-Rosie | Post-AMBER 2.0 | Post-AMBER | Post-Rosie | Post-AMBER 2.0 |
| lamin A | 33.167,06 | -86.321,45 | **-65.282,53** | -88.179,65 | 1,90 | **0,90** | 1,84 |
| LOGO | -716,32 | -3.606,94 | **-3.001,67** | -3.914,43 | 1,93 | **0,86** | 2,70 |
| n80\_02 | 12.057,20 | -2.528,40 | -1.272,80 | **-2.425,82** | 2,02 | 1,68 | **1,56** |
| Rank 15 | 316,67 | -2.755,90 | -1.375,60 | **-2.868,68** | 1,46 | 1,88 | **1,99** |
| Rank 21 | 7.667,93 | -1.766,30 | -329,59 | **-1.912,69** | 2,02 | 1,88 | **1,19** |
| 62aa11\_1 | -6.279,97 | -9.645,16 | **-7.290,12** | -9.855,37 | 1,94 | **0,53** | 2,81 |
| 52aa2\_1 | -2.907,52 | -6.645,47 | **-5.453,73** | -6.911,33 | 3,01 | **1,01** | 2,35 |
| 42-2L03 | 2.855,60 | -1.668,46 | **-844,73** | -1.712,35 | 1,73 | **0,50** | 2,22 |
| n51\_02 | -618,09 | -2.918,23 | **-1.947,73** | -3.036,73 | 2,43 | **1,65** | 1,54 |
| Rank 7 | 1.030,02 | 101,65 | 1.247,85 | **-43.38** | 1,46 | 1,19 | **1,83** |
**Table 2.**  Relaxation results for the predicted most promising interactors. The table shows the energy levels and MolProbity scores of the structures after each relaxation step.

In the docking step of our pipeline, ClusPro results for lamin A docking showed no binding between the interactors and the region of interest in the C-terminus. HADDOCK results were useful for assessing the binding capability between the interactor and lamin A. After defining the interacting region, we focused on clusters with low HADDOCK scores and large cluster sizes, as these indicate significant and reliable interactions. We focused on clusters with a HADDOCK score lower than -35, and we measured the weighted average Kd, with the cluster size as weighting factor.

| Lamin A | Cluster information | | | Prodigy | |
| --- | --- | --- | --- | --- | --- |
| Cluster | Haddock score | Cluster size | Kd [M] | Weighted average |
| LOGO | 2 | -41.8 ± 3.1 | 22 | 8.60E-08 | 1.28E-07 |
| 3 | -41.5 ± 4.6 | 16 | 3.80E-08 |
| 1 | -36.9 ± 3.3 | 29 | 2.10E-07 |
| n80\_02 | 2 | -38.2 ± 2.7 | 21 | 9.40E-09 | 3.49E-08 |
| 3 | -31.2 ± 2.1 | 17 | 4.70E-08 |
| 1 | -29.2 ± 3.7 | 80 | 3.90E-08 |
| Rank 15 | 3 | -22.3 ± 6.9 | 15 | 1.90E-06 | 9.10E-07 |
| 10 | -20.3 ± 6.3 | 5 | 1.00E-06 |
| Rank 21 | 2 | -25.8 ± 2.2 | 17 | 9.70E-09 | 2.18E-07 |
| 5 | -42.4 ± 2.1 | 9 | 3.50E-07 |
| 4 | -35.1 ± 7.4 | 11 | 1.10E-07 |
| 62aa11\_1 | 4 | -40.6 ± 3.4 | 15 | 2.40E-08 | 1.73E-07 |
| 1 | -40.6 ± 5.2 | 60 | 2.10E-07 |
| 52aa2\_1 | 3 | -34.0 ± 3.9 | 14 | 1.80E-06 | 1.80E-06 |
| 5 | -40.9 ± 1.6 | 13 | 1.60E-07 |
| 42-2L03 | 2 | -39.9 ± 2.6 | 39 | 6.40E-07 | 4.42E-07 |
| 4 | -38.7 ± 0.5 | 20 | 2.40E-07 |
| n51\_02 | 6 | -35.8 ± 1.3 | 6 | 1.30E-07 | 1.30E-07 |
| Rank 7 | 8 | -23.7 ± 3.6 | 6 | 1.30E-06 | 1.30E-06 |
**Table 3.**  HADDOCK docking results between the interactors and lamin A. The final Kd was calculated as a weighted average of the Kd values from individual clusters, using cluster size as the weighting factor. For models with insufficient significant clusters, the first reliable cluster was retained.

We repeated the same procedure with progerin to improve our Kd predictions using these refined progerin structures. Table 7 shows the HADDOCK results for progerin. We notice that the best Kd value is now 5.70 × 10⁻⁹M, corresponding to Rank 21, which likely retains part of the optimistic Kd predicted by NeuroBind.

| Progerin | Cluster information | | | Prodigy | |
| --- | --- | --- | --- | --- | --- |
| Cluster | Haddock score | Cluster size | Kd [M] | Weighted average |
| LOGO | 3 | -35.7 ± 4.0 | 10 | 1.30E-08 | 1.30E-08 |
| 7 | -50.3 ± 5.7 | 8 | 3.60E-08 |
| n80\_02 | 3 | -42.4 ± 3.7 | 11 | 1.60E-07 | 7.81E-08 |
| 5 | -41.9 ± 3.6 | 10 | 1.90E-09 |
| 4 | -40.8 ± 1.7 | 10 | 2.30E-07 |
| 2 | -38.4 ± 4.2 | 11 | 2.00E-09 |
| 1 | -38.0 ± 2.7 | 48 | 6.80E-08 |
| Rank 15 | 7 | -39.9 ± 9.6 | 8 | 1.30E-07 | 1.30E-07 |
| Rank 21 | 1 | -43.4 ± 1.8 | 28 | 5.70E-09 | 5.70E-09 |
| 62aa11\_1 | 1 | -32.2 ± 2.0 | 29 | 1.40E-06 | 1.40E-06 |
| 52aa2\_1 | 1 | -56.0 ± 0.8 | 32 | 9.50E-08 | 4.17E-07 |
| 3 | -53.7 ± 7.0 | 53 | 5.00E-07 |
| 2 | -51.2 ± 2.1 | 29 | 6.20E-07 |
| n51\_02 | 7 | -46.2 ± 2.8 | 8 | 3.00E-08 | 6.30E-08 |
| 15 | -43.8 ± 7.2 | 5 | 4.20E-08 |
| Rank 7 | 3 | -37.5 ± 2.8 | 10 | 1.00E-07 | 1.60E-07 |
| 42-2L03 | 2 | -29.9 ± 2.3 | 17 | 1.60E-07 | 4.53E-07 |
| 9 | -39.8 ± 2.4 | 8 | 1.00E-06 |
| 10 | -36.5 ± 3.4 | 7 | 4.00E-08 |
**Table 4.**  HADDOCK results for the interaction between progerin and the binding peptides. The final Kd was calculated as a weighted average of the Kd values from individual clusters, using cluster size as the weighting factor. For models with insufficient significant clusters, the first reliable cluster was retained.

To assess the selectivity of each designed interactor, we compared the dissociation constants (Kd) obtained from docking simulations with progerin and lamin A. To enable direct comparison, we calculated the ratio Kd(progerin)/Kd(lamin A), where values below 1 indicate stronger affinity for progerin, while ratios above 1 suggest preferential binding to lamin A. The results are summarized in Table 5.

This analysis revealed that several candidates displayed marked selectivity toward progerin, with ratios as low as 0.03–0.23, corresponding to up to an order of magnitude stronger binding compared to lamin A. These include the models **LOGO**, **Ranks 15 and 21, 7**, and **52aa\_1**, which represent the most promising interactors for specific recognition of the pathogenic isoform. **Rank 21 is the most promising interactor**. Conversely, a few candidates (n80-02, 62aa11\_1, and 42-2L03) showed ratios exceeding 1, suggesting potential cross-reactivity with lamin A due to the high structural similarity between the two C-terminal regions. In particular, 62aa11\_1 exhibited a significantly higher affinity for lamin A. One possible reason is that since the two binding sites of lamin A and progerin differ by only a few amino acids and also correspond to an intrinsically disordered region, the peptide designed to bind progerin efficiently may also have the potential to bind lamin A equally well or even better.

Overall, these results confirm that our computational pipeline can generate interactors with differential binding profiles and demonstrate that both de novo (NeuroBind) and rational design approaches are valid and complementary strategies.

| Interactor | Haddock Kd [M]  progerin - second analysis | Haddock Kd [M]  lamin A | Kd (progerin) / Kd (lamin A) |
| --- | --- | --- | --- |
| LOGO | 1.30E-08 | 1.28E-07 | 0.10 |
| n80\_02 | 7.81E-08 | 3.49E-08 | 2.24 |
| Rank 15 | 1.30E-07 | 9.10E-07 | 0.14 |
| Rank 21 | 5.70E-09 | 2.18E-07 | 0.03 |
| 62aa11\_1 | 1.40E-06 | 1.73E-07 | 8.10 |
| 52aa2\_1 | 4.17E-07 | 1.80E-06 | 0.23 |
| 42-2L03 | 4.53E-07 | 4.42E-07 | 1.02 |
| n51\_02 | 6.30E-08 | 1.30E-07 | 0.48 |
| Rank 7 | 1.60E-07 | 1.30E-06 | 0.12 |
**Table 5.**  Comparison of the Kd values for the interaction between the designed interactors and progerin versus lamin A. The third column reports the Kd ratio to facilitate the comparison of binding affinities. Values below 1 indicate stronger binding to progerin than to lamin A, while values above 1 correspond to higher affinity for lamin A. These results refer to the interactors without the RING domain.

### Step 2 - With the RING domain

To analyse the behaviour of the interactors when attached to the TRIM21-RING domain, it is first necessary to predict and relax the structures of the interactors-RING chimeric protein. The interactors were combined with the RING domain in the N-terminus tail using a flexible linker composed of glycine and serine (GGGGSGGGGSGGGGS). Table 10 presents the energy level of the structure after each relaxation step, run using Amber, RosettaRelax and Amber; along with the MolProbity score for structure validation. Additionally, the pTM score obtained by Alphafold is provided, which estimates the global confidence of the protein folding, serving as an indicator of the reliability of the global topology of the structure. In the table, we highlighted the structures that were retained based on their balance between MolProbity score and energy.

| Interactor | pTM | Energy | | | | MolProbity score | | |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Pre-Relax | Post-AMBER | Post-RosettaRelax | Post-AMBER 2.0 | Post-AMBER | Post-RosettaRelax | Post-AMBER 2.0 |
| LOGO | 0.41 | -1.570,60 | -5.551,27 | **-3.702,61** | -6.333,65 | 2.55 | **1.46** | 2.39 |
| n80\_02 | 0.4 | -588,60 | -4.514,32 | -2.275,82 | **-4.553,58** | 2.37 | 1.51 | **2.12** |
| Rank 15 | 0.39 | 365,13 | -3.555,26 | **-850,96** | -3.647,22 | 2.30 | **2.02** | 2.38 |
| Rank 21 | 0.39 | 302,12 | -2.899,76 | **-549,98** | -3.690,36 | 2.27 | **1.03** | 2.42 |
| 62aa11\_1 | 0.47 | -7.308,03 | -11.329,11 | -8.128,80 | **-11.533,71** | 2.12 | 1.40 | **2.17** |
| 52aa2\_1 | 0.41 | -5.565,58 | -8.299,75 | -5.352,63 | **-8.400,86** | 2.18 | 1.41 | **2.02** |
| 42-2L03 | 0.43 | -447,58 | -2.869,33 | **-853,65** | -3.031,81 | 2.18 | **1.55** | 2.46 |
| n51\_02 | 0.41 | -241,29 | -4.606,89 | -1.848,39 | **-4.534,06** | 2.32 | 1.51 | **2.18** |
| Rank 7 | 0.41 | 1.741,06 | -2.435,16 | 124,32 | **-2.813,69** | 2.15 | 1.45 | **2.01** |
**Table 6.**  Relaxation results for the predicted interactors attached to the RING domain. The table shows the energy levels and MolProbity scores of the structures after each relaxation step.

This phase has brought to light important insights about our interactors. We discovered that, when attached to the RING, not all structures are capable of maintaining the correct folding necessary for protein binding. This implies that, for some of the interactors and especially for the globular ones, more damaged by the presence of RING, the linker length needs to be optimized to achieve a functional and properly folded protein. Increasing the linker length can improve the folding of the interactor, but it should not compromise the activity of the RING domain by placing it too far from the target progerin. (We also discuss it in our [Engineering page](%7B%7B%20url_for%28%27pages%27%2C%20page%3D%27engineering%27%29%20%7D%7D), cycle 5). The most affected structure was LOGO, but we continued the downstream analysis to investigate whether it could retain some binding activity. The following images show comparisons between the properly folded structure and the one whose folding was disrupted by the presence of the RING domain.

![Folding Disruption of LOGO Interactor: Effects of the RING Domain on Globular Conformations](https://static.igem.wiki/teams/5700/images/model/forza-manuel.webp)

**Figure 3.** folding disruption of interactor LOGO. Globular conformations are the most affected by the presence of the RING domain.

![Folding Disruption of Interactor n80_02: RING Domain Impact with Overall Structural Maintenance](https://static.igem.wiki/teams/5700/images/model/alleluia.webp)

**Figure 4.** folding disruption of interactor n80\_02. Globular conformations are the most affected by the presence of the RING domain. Nevertheless, a global maintenance of the interactor’s folding is observed.

We then calculated HADDOCK binding Kd values for lamin A and progerin to investigate whether our interactors could discriminate between the progerin target and lamin A. The most promising interactor appears to be Rank 15, with a Kd of 1.20 × 10⁻⁸ M (Table 7). For other interactors, such as n80\_02, the presence of the RING domain enhanced their ability to bind progerin, decreasing the Kd from 7.81 × 10⁻⁸ M to 5.55 × 10⁻⁸ M (Table 7), likely due to conformational rearrangements (Figure 4). Nevertheless, a Kd of 5.55 × 10⁻⁸M can still be considered acceptable.

| progerin | Cluster information | | | Prodigy | |
| --- | --- | --- | --- | --- | --- |
| Cluster | Haddock score | Cluster size | Kd [M] | Weighted average |
| LOGO | 6 | -40.4 ± 1.3 | 14 | 6,20E-07 | 1,38E-07 |
| 1 | -38.3 ± 2.8 | 47 | 3,90E-09 |
| 8 | -38.0 ± 3.2 | 6 | 3,80E-07 |
| 5 | -36.1 ± 3.6 | 15 | 1,40E-08 |
| n80\_02 | 1 | -48.5 ± 1.8 | 98 | 7,10E-09 | 5,55E-08 |
| 2 | -48.3 ± 2.3 | 19 | 3,30E-07 |
| 3 | -40.8 ± 8.8 | 17 | 4,40E-08 |
| 4 | -35.5 ± 1.0 | 6 | 1,00E-08 |
| Rank 15 | 1 | -41.0 ± 3.1 | 49 | 1,20E-08 | 1,20E-08 |
| Rank 21 | 2 | -31.7 ± 2.5 | 26 | 7,80E-08 | 7,80E-08 |
| 62aa11\_1 | 1 | -23.4 ± 8.4 | 39 | 1,70E-07 | 1,70E-07 |
| 52aa2\_1 | 1 | -45.9 ± 1.3 | 49 | 3,80E-07 | 3,80E-07 |
| 42-2L03 | 2 | -52.9 ± 1.7 | 24 | 1,60E-07 | 1,19E-07 |
| 4 | -45.3 ± 3.3 | 9 | 8,50E-09 |
| n51\_02 | 1 | -48.3 ± 3.6 | 74 | 2,00E-08 | 1,89E-07 |
| 10 | -41.7 ± 4.9 | 5 | 7,00E-07 |
| 2 | -41.7 ± 2.3 | 34 | 4,80E-07 |
| 3 | -41.0 ± 1.4 | 10 | 1,90E-07 |
| Rank 7 | 1 | -31.1 ± 2.2 | 116 | 2,20E-08 | 2,20E-08 |
**Table 7.**  HADDOCK docking results for the analysis between the interactors attached to the RING domain and progerin.

| Lamin A | Cluster information | | | Prodigy | |
| --- | --- | --- | --- | --- | --- |
| Cluster | Haddock score | Cluster size | Kd [M] | Weighted average |
| LOGO | 1 | -31.7 ± 1.8 | 19 | 1,30E-07 | 1,30E-07 |
| n80\_02 | 2 | -32.5 ± 2.8 | 50 | 4,90E-08 | 4,90E-08 |
| Rank 15 | 2 | -28.6 ± 13.4 | 19 | 4,50E-07 | 4,50E-07 |
| Rank 21 | 11 | -38.9 ± 9.0 | 4 | 1,80E-07 | 1,80E-07 |
| 62aa11\_1 | 1 | -43.1 ± 1.6 | 71 | 3,00E-09 | 3,00E-09 |
| 52aa2\_1 | 1 | -36.3 ± 2.6 | 73 | 7,30E-06 | 7,30E-06 |
| 42-2L03 | 5 | -52.7 ± 4.1 | 10 | 1,70E-07 | 1,19E-07 |
| 1 | -50.2 ± 2.1 | 42 | 1,60E-07 |
| 6 | -48.0 ± 0.7 | 9 | 3,50E-08 |
| 11 | -42.7 ± 2.9 | 4 | 7,70E-08 |
| 4 | -41.6 ± 3.8 | 13 | 2,40E-07 |
| n51\_02 | 1 | -48.0 ± 4.2 | 74 | 2,00E-08 | 1,97E-07 |
| 2 | -41.7 ± 2.3 | 36 | 4,80E-07 |
| 9 | -41.7 ± 4.9 | 6 | 7,00E-07 |
| 3 | -41.1 ± 1.3 | 10 | 1,90E-07 |
| Rank 7 | 3 | -44.6 ± 5.6 | 25 | 2,20E-07 | 2,20E-07 |
**Table 8.**  shows HADDOCK docking results for the interaction between the interactors with the RING domain and lamin A.

Table 9 compares the Kd values for the interaction between the RING-fused interactors and progerin or lamin A. The analysis revealed that, overall, the presence of the RING domain did not compromise the binding ability of most interactors. Several candidates maintained or even improved their selectivity toward progerin, as indicated by ratios below 1.

In particular, Rank 15 and 52aa2\_1 showed the strongest preference for progerin, with Kd ratios of 0.03 and 0.05, respectively, confirming that RING fusion can preserve and even enhance target discrimination. Rank 21 also retained moderate selectivity (ratio = 0.43). In contrast, the LOGO model exhibited a reduction in affinity, with a ratio approaching 1, likely due to conformational disruption observed in Figure 10. It would be interesting to test whether modifying the linker length or the position of the RING domain could restore its optimal configuration.

Notably, **42-2L03 maintained the same Kd for both progerin and lamin A** (ratio = 1.00), confirming its neutral binding behavior. **n80\_02 showed a slight improvement** compared to the isolated form, but still displayed a ratio above 1, indicating a stronger affinity for lamin A. **62aa11\_1 exhibited a pronounced shift in specificity (ratio = 56.67)**, suggesting that RING fusion induced unfavorable conformational rearrangements that impaired binding to progerin and favored lamin A instead. Both 62aa11\_1 and n80\_02 demonstrated low affinity for progerin and higher affinity for lamin A, and would likely be excluded from future optimization rounds.

Taken together, these data indicate that the inclusion of the RING domain generally preserves the designed binders’ selectivity for progerin, while also highlighting how structural compatibility between the effector domain and the interactor scaffold is crucial for maintaining target specificity.

| Interactors | HADDOCK Kd [M] Progerin | HADDOCK Kd [M] Lamin] | Kd(progerin) / Kd(lamin a) |
| --- | --- | --- | --- |
| LOGO | 1,38E-07 | 1,30E-07 | 1.07 |
| n80\_02 | 5,55E-08 | 4,90E-08 | 1.13 |
| Rank 15 | 1,20E-08 | 4,50E-07 | 0.03 |
| Rank 21 | 7,80E-08 | 1,80E-07 | 0.43 |
| 62aa11\_1 | 1,70E-07 | 3,00E-09 | 56.67 |
| 52aa2\_1 | 3,80E-07 | 7,30E-06 | 0.05 |
| 42-2L03 | 1,19E-07 | 1,19E-07 | 1.00 |
| n51\_02 | 1,89E-07 | 1,97E-07 | 0.96 |
| Rank 7 | 2,20E-08 | 2,20E-07 | 0.10 |
**Table 9.**  Comparison of the Kd values for the interaction between the interactors and progerin versus lamin A. The third column reports the Kd ratio to facilitate the comparison of binding affinities. Values below 1 indicate stronger binding to progerin than to lamin A, while values above 1 correspond to higher affinity for lamin A. These results refer to the interactors without the RING domain.

### Conclusion

In conclusion, as part of our project, we have developed a sophisticated bioinformatics pipeline for the design of peptide interactors specifically targeting an intrinsically disordered region—specifically, the C-terminal tail of progerin. This is a crucial aspect of our approach to tackling Hutchinson-Gilford Progeria Syndrome (HGPS). Our pipeline has undergone multiple iterations of trial and error, incorporating pages of engineering adjustments to refine the results, and we have validated the structures obtained using a variety of bioinformatics tools.

After generating these interactors, we proceeded to analyze their binding affinities. From the hundreds of initial interactors, we selected the top 9 candidates that demonstrated the most promising binding characteristics. These were then subjected to more in-depth analysis, both in laboratory experiments and further computational studies using software tools. As part of our investigation, we included both versions of the interactors: with and without the RING domain from the TRIM21 ubiquitin ligase, which is central to our project’s goal of targeted progerin degradation.

Our findings revealed that, from the many initial candidates, the 9 interactors we analyzed showed varying degrees of specificity. Some interactors performed better against progerin, while others were more effective against lamin A, which underscores the complexity of targeting intrinsically disordered regions with precision. All the interactors developed during this process are now available in the Registry, and their respective sequences are provided in the supplemental materials section for further reference. This resource will be crucial for future studies and experimental validation as we move forward with optimizing these interactors for therapeutic use in the ProgERASE approach.

## Supplemental materials

▲

* [Interaction analysis template](https://static.igem.wiki/teams/5700/pdf/interaction-analysis-template.pdf) Template to compute our data analysis
* [Tools' parameters](https://static.igem.wiki/teams/5700/pdf/tools-parameters.pdf) Depiction of all the settings we used to obtain our results
* [MULTI-FASTA](https://static.igem.wiki/teams/5700/pdf/multi-fasta.pdf) Sequences of all the interactors and fragments we analyzed

## References

▲

* [1] C. Liu et al. “Diffusing protein binders to intrinsically disordered proteins”. In: Nature 644 (2025). <https://doi.org/10.1038/s41586-025-09248-9>
* [2] Wu Kejia et al. “Design of intrinsically disordered region binding proteins”. In: Science 389 (2025). <https://doi.org/10.1126/science.adr8063>

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## Structure of the Yeast Results Section

▲

In this section we’ll provide our experimental design, highlighting the rationale behind each methodological choice concerning our work on *S. cerevisiae*.

After this introductory framework, the experimental results are presented in four parts:

* **Progeria phenotyping on *Saccharomyces cerevisiae***;
* **Yeast two-hybrid (Y2H): the limitation we found and the change we decided to apply**;
* **Translating of the known interactor BUBR1 into the Y2H**;
* **Usage of the system to translate the modelled interaction of our bioinformatics predicted peptides**

This structure allows the reader to follow a clear progression: from the strategy underlying our work, to the stepwise presentation, the analysis of experimental outcomes and the methodology choices we decided to apply along the way.

## Progeria (HGPS) model in *S. cerevisiae*

▲

Yeast, including our chassis *Saccharomyces cerevisiae*, has already been used in the past to study the effects of aberrant protein accumulation, such as in Alzheimer’s disease research. Despite this, our literature research revealed no peer-reviewed papers concerning the expression and **modeling** of progeria in yeast. That is why we decided to implement this model.

To do so, we expressed progerin sequence [BBa\_25NDL8N0](https://registry.igem.org/parts/bba-25ndl8n0) using pYES2 ([BBa\_K555009](https://parts.igem.org/Part%3ABBa_K555009)) in *S. cerevisiae* CEN.PK. In this way, we were able to create a chassis capable of expressing progerin in a galactose-dependent manner by cloning our progerin sequence under the control of the GAL1 promoter.
All the yeast strains used in our experiments (CEN.PK and Y190) are auxotrophic for certain amino acids and nucleotides: histidine, leucine, tryptophan, uracil, and adenine.
This allows us to select correctly transformed yeast without the need for antibiotics; however, it also requires the preparation of a specific medium with the appropriate compounds to support the growth of the desired yeast.

![pYES2 Plasmid (BBa_K555009): Galactose-Inducible progerin Expression in <i>S. cerevisiae</i>](https://static.igem.wiki/teams/5700/images/results/pyes2-plasmid.webp)

**Figure 2.**pYES2 plasmid (BBa\_K555009). This plasmid was cloned into *S. cerevisiae* CEN.PK in order to express progerin in a galactose-dependent manner under the GAL1 promoter. It carries the pathway for uracil synthesis (URA3), which complements the uracil auxotrophy of the laboratory yeast strain. When cloned in bacteria it replicates via the ColE1 origin and the transformed colonies can be selected by making use of the ampicillin resistance. Made with Benchling.

We employed this chassis in order to study the progerin phenotype through various assays: spot test and growth curves.

The spot test allows us to compare the growth of the same cultures on different mediums. Up to 8 cultures at the same time can be tested, and each culture is plated in four dilutions (1, 10-1, 10-2 , 10-3) in order to better understand the difference in growth between the different cultures. Each dilution is made from a culture standardized to OD 1; for this reason, the dilution 1 is equivalent to 1 OD concentration of cells.
Plating was performed by depositing a drop of culture onto the array created on the plate. After this, plates are incubated at 28°C for three days; with photos taken every 24 hours to allow results comparison.

The spot test offers the best results in terms of progerin phenotype; in the picture, it is possible to see the growth difference between the same cultures on SD Glucose -URA plate and SD Galactose -URA plate. These results confirm that the expression of progerin under galactose-inducing conditions exerts a toxic effect on yeast cells. Meanwhile, the presence of progerin had no impact under glucose repression, where the GAL1 promoter is inactive. Induction of progerin expression in a galactose-rich medium led to clear growth inhibition.

![Spot Test on <i>S. cerevisiae</i> CEN.PK: Galactose-Inducible Progerin Expression Restricts Growth on SD Glucose -URA Medium](https://static.igem.wiki/teams/5700/images/results/spot-test-pyes2-progerin-19-09.webp)

**Figure 3.** Spot test results on S. *cerevisiae* CEN.PK. progerin expression (galactose-inducible) is responsible for limiting yeast growth on SD Glucose -URA medium.

Find out more about the spot test assay [here](%7B%7B%20url_for%28%27pages%27%2C%20page%3D%27experiments%27%29%20%7D%7D#2nd-pillar).
As shown in the picture, progerin expression (induced by the presence of galactose in the sample) is responsible for the growth limitation observed in *S. cerevisiae* CEN.PK.

### Growth curve:

Despite performing the growth curve for pYES2+progerin multiple times, ([BBa\_25NDL8N0](https://registry.igem.org/parts/bba-25ndl8n0)+[BBa\_K555009](https://parts.igem.org/Part%3ABBa_K555009)) we were unable to obtain consistent results comparable to those from the spot tests.

After many tries, the curve in the picture is the one that represents most closely what we had expected. All experimental measurements were normalized to the first data point of each series to correct for initial differences between samples and allow direct comparison of relative changes over time. This approach ensures that observed trends reflect the actual biological response rather than variability in the starting values.

![Effect of progerin Expression on <i>S. cerevisiae</i> CEN.PK Growth: GAL1-Induced Cytotoxicity in Galactose Media](https://static.igem.wiki/teams/5700/images/results/growth-curve-pyes2-progerin.webp)

**Figure 4.**Effect of progerin expression on *S. cerevisiae* CEN.PK growth. pYES\_∅ GLU and pYES2\_progerin GLU cultures were growing in SD Glucose 2% -URA, while pYES\_∅ GAL and pYES2\_progerin GAL cultures were growing in SD Galactose 2% -URA. Galactose is the inductor of the GAL1 promoter in the pYES2 plasmid; for this reason, pYES2\_progerin GAL is the only culture where progerin is expressed, and, as it is possible to see, the only one with a strong limitation in growth. The limited growth of pYES\_∅ GAL is probably due to the usage of a less preferred sugar.

## Yeast Two-Hybrid - yeast as a chassis to find progerin interactors

▲

*S. cerevisiae* provides a convenient system to study protein interaction using the **Yeast Two-Hybrid** (Y2H) system. This approach allows us to test the interaction between two proteins via the use of two plasmids: one coding for a “prey” protein and another coding for a “bait” protein.

![Yeast Two-Hybrid (Y2H) Mechanism: Protein–Protein Interaction Detection via Reporter Activation](https://static.igem.wiki/teams/5700/images/experiments/y2h-explanation.webp)

**Figure 3.** Yeast two hybrid (Y2H) molecular mechanisms. The two plasmids coding for the prey and bait domain are cloned in frame with the two proteins to be assessed for interaction and co-transformed into the same *S. cerevisiae* cell. If the two proteins of interest interact, the reporter pathway is activated. Made with Biorender.com

The plasmids we used are commercially available, pGADT7 and pGBKT7:

* pGAD serves as the prey plasmid, expressing the activation domain (AD)
* pGBK serves as the bait plasmid, expressing the DNA-binding domain (BD)

Proteins of interest can be cloned into these plasmids in frame with the AD or BD domains, enabling the system to test their interaction.

When both plasmids are co-transformed into the same *S. cerevisiae* Y190 cells, interaction between the proteins of interest brings the BD and AD domains closer together; this way, the protein complex activates the HIS3 reporter gene, allowing yeast growth on a histidine-deficient medium. Because the HIS3 pathway is leaky, 3AT (a competitive inhibitor of the histidine pathway) is added to strengthen the selection when testing interactions.

### First attempt: cloning of the whole progerin sequence

We initially attempted to clone the entire progerin sequence (an initial version non complied with RFC10 standard), into both our yeast two-hybrid plasmids, pGADT7 and pGBKT7, in order to determine whether we would be able to observe the expected self-interaction of progerin molecules via Y2H.

Unfortunately, we found that cloning the whole progerin sequence into either pGAD or pGBK plasmids was not feasible, as it rendered *S. cerevisiae* unable to grow, most likely due to the cytotoxic effect related to progerin.

This conclusion was supported by:

* Abnormal colony morphology on selective plates (SD Glu -Trp or -Leu, when trying single transformation or -Trp -Leu, when trying co-transformation);
* Absence of detectable protein expression, as confirmed by Western blot (WB).

![S. cerevisiae Y190 Plates Transformed with pGBK_Progerin: Growth Impairment and Repression of Cytotoxic Progerin Expression](https://static.igem.wiki/teams/5700/images/results/pgbk-progerin-not-working-new.webp)

**Figure 6.** Plates of *S. cerevisiae* Y190 transformed with pGBK\_progerin after 72h. Progerin expressed by the constitutive promoter ADH1 impairs colony growth. Western blot analysis confirmed the absence of progerin expression. The colonies we see likely repressed protein expression as a response to progerin cytotoxicity.

This is likely due to a key difference between pGAD/pGBK and pYES2 plasmid: in pGAD and pGBK progerin synthesis is constitutively expressed by ADH1 promoter, whereas in pYES2 it is controlled by inducible promoter GAL1.

### Second attempt: cloning of progerin C-term

Since we were unable to obtain any growth by cloning the whole progerin sequence, we chose to repeat the cloning using only the C-terminal of the protein. Specifically, we decided to design two C-term proteins:

* From amino acid 430 to 614 ([BBa\_25HM35ST](https://registry.igem.org/parts/bba-25hm35st)); this sequence includes the Ig-like part of the protein;
* From amino acids 545 to 614 ([BBa\_25IF4C4Z](https://registry.igem.org/parts/bba-25if4c4z)); this sequence does not include the Ig-like part of the protein

![AlphaFold3-Predicted 3D Structure of Progerin: Visualization of the Ig-Like Domain and Farnesylated C-Terminal Tail](https://static.igem.wiki/teams/5700/images/results/3d-progerin-with-caption.webp)

**Figure 8.** Progerin predicted 3D structure. AlphaFold3-predicted model of progerin visualized through Chimera X. The Ig-like domain is followed by an intrinsically disordered C-terminal tail which contains the CaaX motif recognized by farnesyltransferase (FTase). From Chimera X.

We based our choice on a previous study  [[1]](https://doi.org/10.1038/s43587-023-00361-w) where they were able to prove progerin interaction with another protein: **BUBR1**, particularly its N-term.

Given the cytotoxic effect of progerin on cells described above, we decided to proceed with cloning progerin only into the pGBK plasmid. Since pGBK encodes the binding domain (BD), limiting progerin cloning to this plasmid should help prevent its cytotoxic effect on the cell.

![Constitutive Expression of Progerin C-Terminal Sections with Gal4 DNA-Binding Domain: Selection via Tryptophan Auxotrophy](https://static.igem.wiki/teams/5700/images/results/pgbk-progerin-430-545.webp)

**Figure 9.** Progerin C-term (430 and 545) cloned in pGBK. The selected progerin C-term sections are constitutively expressed along with the Gal4 DNA-binding domain. Since this plasmid encodes the tryptophan synthesis pathway, correctly transformed cells can be selected by not adding tryptophan in the medium. Made with Benchling.

This time, we were able to obtain growth on our plates and we confirmed protein expression through *Western* Blot (only for aa 430 to 416 fragment).

![S. cerevisiae Y190 Plates Transformed with pGBK_Progerin C-Term (430): Stable Growth and Confirmed Protein Expression](https://static.igem.wiki/teams/5700/images/results/pgbkgrowth-wb-progerin-430.webp)

**Figure 10.** Plates of *S. cerevisiae* Y190 transformed with pGBK\_progerin C-term (430). Growth is consistent and we were able to confirm protein expression through WB. This means that C-terminus of progerin does not appear to be cytotoxic for the cell when expressed in pGBK plasmid.

We used the colonies obtained from transformation to continue our studies. The cells were co-transformed with the other plasmid and tested for interaction on Y2H selective medium (SD Glu -Leu -Trp -His +3AT 30 mM).

### Let's start with something we already know: BUBR1 N-term

Before testing our bioinformatically predicted interactors, we wanted to validate the Y2H assay using a known progerin interactor, but we were not able to find any progerin known interactor tested through Y2H.
For this reason, we decided to test whether a known interactor would work in our system. To do so, we chose the N-terminal region of BUBR1.

The interaction between progerin (progerin C-term, as stated above) and BUBR1 N-term had been previously reported in mammalian cells via co-immunoprecipitation and pull-down assay [[1]](https://doi.org/10.1038/s43587-023-00361-w), but we had no information on whether this interaction could be reproduced in yeast.

We tested the interaction between progerin C-term (430 and 545) and BUBR1 N-term by cloning:

* Progerin C-term (430 and 545) into pGBK, for the reasons stated above;
* BUBR1 N-term in pGAD.

Our experimental results indicated that the previously reported interaction between progerin C-term and BUBR1 N-term (seen in previous studies) does not occur in the Y2H system. In fact, we were not able to obtain a positive result in our selective plates for Y2H (SD Glucose -Leu -Trp -His +3AT 30 mM).

![Spot Test in Y2H Selective Medium: No Interaction Detected Between Progerin C-Term (aa 430–614) and BUBR1 N-Term](https://static.igem.wiki/teams/5700/images/results/spot-test-conferma-y2h-bubr172h.webp)

**Figure 11.** Spot test results in Y2H selective medium. We can conclude that no specific interaction occurs between progerin C-term (aa 430-614) and BUBR1 N-term, as no specific growth was observed where co-transformed culture spots were made.

| Position | Plate 1 | Plate 2 |
| --- | --- | --- |
| 1 | CTR (+) | CTR (+) |
| 2 | CTR (-) | CTR (-) |
| 3 | pGBK\_∅ + pGAD\_BUBR1 #1 | pGBK\_∅ + pGAD\_BUBR1 #1 |
| 4 | pGBK\_∅ + pGAD\_BUBR1 #2 | pGBK\_progerin 430 + pGAD\_∅ #1 |
| 5 | pGBK\_progerin 430 + pGAD\_∅ #1 | pGBK\_progerin 430 + pGAD\_BUBR1 #1 |
| 6 | pGBK\_progerin 430 + pGAD\_∅ #2 | pGBK\_progerin 430 + pGAD\_BUBR1 #3 |
| 7 | pGBK\_progerin 430 + pGAD\_BUBR1 #1 | pGBK\_progerin 430 + pGAD\_BUBR1 #4 |
| 8 | pGBK\_progerin 430 + pGAD\_BUBR1 #2 | pGBK\_progerin 430 + pGAD\_BUBR1 #5 |

We concluded that these negative results are likely due to the following factors:

1. We used a different chassis and a different method to test protein interactions;
2. We were unable to test the full-length protein, as it is toxic for the cell

### Now it’s our turn: testing of the bioinformatically predicted interactors

Despite the negative results obtained when testing progerin C-term and BUBR1 N-term, we proceeded to test our predicted interactors.
We tested five colonies (#1,#2,#3,#4,#5) for each of the following interactors:

* <BBa_25R6U8N1>: LOGO - bioinformatically predicted progerin interactor 1;
* [BBa\_25RLZ3X4](https://registry.igem.org/parts/bba-25rlz3x4): n80\_02 - bioinformatically predicted progerin interactor 2;
* [BBa\_25G9QB6S](https://registry.igem.org/parts/bba-25g9qb6s): Rank\_15 - bioinformatically predicted progerin interactor 3

The interactors were tested both against progerin 430 and progerin 545 by co-transformation of the plasmids pGBK\_progerin430/545 + pGAD+interactor in *S. cerevisiae* Y190.
To test whether the interaction occurred, we carried out a spot test assay on Y2H selective medium SD GLU -Leu -Trp -His +3AT 30 mM.
When interaction occurs, yeast cells are able to grow in this medium; if the interaction does not occur, no growth should be observed.

Unfortunately, the lack of growth observed in the spot test suggests that interactions with progerin C-term (both 430 and 545 fragments) do not take place in the Y2H system for the first three interactors.

![Spot Test Assay: Assessment of Progerin_430 Interaction with Interactors 1–3 in Yeast Two-Hybrid System](https://static.igem.wiki/teams/5700/images/contribution/interactorsa-b-c-430.webp)

**Figure 12.** (A) Spot test assay to evaluate the interaction between progerin\_430 and Interactor 1 (colonies #1–#5), (B) Interactor 2 (colonies #1–#5) and (C) Interactor 3 (colonies #1–#5) SD\_GLU   represents our positive control, because this medium selects transformed yeasts. On the other hand, SD\_GLU    +3AT 30mM medium should select those yeast cells where interaction between progerin and interactors occurs. We can conclude that we are unable to determine progerin interaction with our interactors, at least in the yeast two-hybrid system.

| No. | PLATE A | PLATE B | PLATE C |
| --- | --- | --- | --- |
| 1 | pGBK\_progerin 430 + pGAD\_∅ | pGBK\_progerin 430 + pGAD\_∅ | pGBK\_progerin 430 + pGAD\_∅ |
| 2 | pGBK\_progerin 430 + pool pGAD\_interactor 1 #1 | pGBK\_progerin 430 + pool pGAD\_interactor 2 #1 | pGBK\_∅ + pool pGAD\_interactor 3 |
| 3 | pGBK\_progerin 430 + pool pGAD\_interactor 1 #2&3 | pGBK\_progerin 430 + pool pGAD\_interactor 2 #2&3 | pGBK\_progerin 430 + pool pGAD\_interactor 3 #1 |
| 4 | pGBK\_progerin 430 + pool pGAD\_interactor 1 #4&5 | pGBK\_progerin 430 + pool pGAD\_interactor 2 #4&5 | pGBK\_progerin 430 + pool pGAD\_interactor 3 #2&3 |
| 5 | pGBK\_∅ + pool pGAD\_interactor 1 | pGBK\_∅ + pool pGAD\_interactor 2 | pGBK\_progerin 430 + pool pGAD\_interactor 3 #4&5 |

![Spot Test Assay: Assessment of Progerin_545 Interaction with Interactors 1–3 in Yeast Two-Hybrid System](https://static.igem.wiki/teams/5700/images/contribution/interactorsd-e-f-545.webp)

**Figure 13.** (D) Spot test assay to evaluate the interaction between progerin\_545 and Interactor 1 (colonies #1–#5), (E) Interactor 2 (colonies #1–#5) and (F) Interactor 3 (colonies #1–#5) SD\_GLU   represents our positive control, because this medium selects transformed yeasts. On the other hand, SD\_GLU    +3AT 30mM medium should select those yeast cells where interaction between progerin and interactors occurs. We can conclude that we are unable to determine progerin interaction with our interactors, at least in the yeast two-hybrid system.

| No. | PLATE D | PLATE E | PLATE F |
| --- | --- | --- | --- |
| 1 | pGBK\_progerin 545 + pGAD\_∅ | pGBK\_progerin 545 + pGAD\_∅ | pGBK\_progerin 545 + pGAD\_∅ |
| 2 | pGBK\_progerin 545 + pool pGAD\_interactor 1 #1 | pGBK\_∅ + pool pGAD\_interactor 2 | pGBK\_∅ + pool pGAD\_interactor 3 |
| 3 | pGBK\_progerin 545 + pool pGAD\_interactor 1 #2&3 | pGBK\_progerin 545 + pool pGAD\_interactor 2 #1 | pGBK\_progerin 545 + pool pGAD\_interactor 3 #1 |
| 4 | pGBK\_progerin 545 + pool pGAD\_interactor 1 #4&5 | pGBK\_progerin 545 + pool pGAD\_interactor 2 #2&3 | pGBK\_progerin 545 + pool pGAD\_interactor 3 #2&3 |
| 5 | pGBK\_∅ + pool pGAD\_interactor 1 | pGBK\_progerin 545 + pool pGAD\_interactor 2 #4&5 | pGBK\_progerin 545 + pool pGAD\_interactor 3 #4&5 |

Despite the negative results the remaining two predicted interactors (Interactor 4 and Interactor 5) have yet to be tested, and interactions with the *wild type* protein must also be verified to fully assess the reliability of our predictions.

To address this, five colonies (#1,#2,#3,#4,#5) of the following two additional interactors were analyzed:

* [BBa\_25UZI9YM](https://registry.igem.org/parts/bba-25uzi9ym) (Rank\_21) – bioinformatically predicted interactor 4;
* [BBa\_256U2NU6](https://registry.igem.org/parts/bba-256u2nu6) (62aa11\_1) – bioinformatically predicted interactor 5

Following successful single transformations in *S. cerevisiae* Y190, co-transformations were carried out. Both interactors will be assayed against progerin 545.
Unfortunately we still did not obtain positive results, confirming that our five predicted interactors cannot be used to determinate progerin interaction in yeast.

![Spot Test Assay: Assessment of Progerin_545 Interaction with Interactors 4 and 5 in Yeast Two-Hybrid System](https://static.igem.wiki/teams/5700/images/contribution/interactors-g-h-545.webp)

**Figure 14.**  (G) Spot test assay to evaluate the interaction between progerin\_545 and Interactor 4 (colonies #1–#5) and (H) Interactor 5 (colonies #1–#5) SD\_GLU   represents our positive control, because this medium selects transformed yeasts. On the other hand, SD\_GLU    +3AT 30mM medium should select those yeast cells where interaction between progerin and interactors occurs.

| No. | PLATE G | PLATE H |
| --- | --- | --- |
| 1 | pGBK\_∅ + pGAD\_interactor 4 | pGBK\_∅ + pGAD\_interactor 5 |
| 2 | pGBK\_progerin 545 + pGAD\_∅ | pGBK\_progerin 545 + pGAD\_∅ |
| 3 | pGBK\_progerin 545 + pGAD\_interactor 4 #1&2 | pGBK\_progerin 545 + pGAD\_interactor 4 #1&2 |
| 4 | pGBK\_progerin 545 + pGAD\_interactor 4 #3&4&5 | pGBK\_progerin 545 + pGAD\_interactor 4 #3&4&5 |

To further investigate the specificity of these interactors, interactors 1, 4 and 5 were tested against lamin A, the *wild type* protein. For this purpose, lamin A was co-transformed into Y190 with different pGAD plasmids:

* pGBK\_LaminA + pGAD\_∅
* pGBK\_LaminA + pGAD\_interactor1;
* pGBK\_LaminA + pGAD\_interactor4
* pGBK\_LaminA + pGAD\_interactor5

The results demonstrated that lamin A is not affected by any of our tested interactors, ruling out off-target effects.

![Spot Test Assay: Validation of Interactors 1, 4, and 5 for Absence of Off-Target Binding to Lamin A](https://static.igem.wiki/teams/5700/images/contribution/lamina-interactors-i-l-m.webp)

**Figure 15.** Spot test assay to validate that interactor 1 (I), interactor 4 (L) and interactor 5 (M) do not show off-target binding to lamin A SD\_GLU   represents our positive control, because this medium selects transformed yeasts. On the other hand, SD\_GLU    +3AT 30mM medium should select those yeast cells where interaction between lamin A and interactors may occur.

| No. | PLATE I | PLATE L | PLATE M |
| --- | --- | --- | --- |
| 1 | pGBK\_∅ + pGAD\_interactor 1 | pGBK\_∅ + pGAD\_interactor 4 | pGBK\_∅ + pGAD\_interactor 5 |
| 2 | pGBK\_laminA + pGAD\_∅ | pGBK\_laminA + pGAD\_∅ | pGBK\_laminA + pGAD\_∅ |
| 3 | pGBK\_laminA + pGAD\_interactor 1 #1&2 | pGBK\_laminA + pGAD\_interactor 4 #1&2 | pGBK\_laminA + pGAD\_interactor 5 #1&2 |
| 4 | pGBK\_laminA + pGAD\_interactor 1 #3&4&5 | pGBK\_laminA + pGAD\_interactor 4 #3&4&5 | pGBK\_laminA + pGAD\_interactor 5 #3&4&5 |

### Conclusions

Although we expected to observe an interaction between the five interactors and the tested portions of progerin, no interaction was detected, indicating that (at least in the yeast two-hybrid system) these interactions do not occur.

On the other hand, for lamin A the results were consistent with our expectations, confirming that the interactors do not display off-target effects toward lamin A.

### Future perspectives

Unfortunately, due to time constraints, we were unable to explore the following topics, despite the potential relevance of the results they could have produced:

* **Post-translational modifications (PTMs)**: We would like to further investigate how progerin is processed in yeast and whether it undergoes the same post-translational modifications as in human cells, with farnesylation being the most critical. At present, we cannot determine whether progerin produced in yeast is fully comparable to the human form. However, it is likely that many of the processing steps occur, given the similarities in protein synthesis pathways between yeast and humans. For example, *S. cerevisiae* expresses Ste24, homologous to the human protease ZMPSTE24[2], which mediates the final cleavage of prelamin A. This step is absent in progerin due to the mis-splicing event that generates it. Mass spectrometry analysis of purified protein would help clarify the extent of these modifications in yeast-expressed progerin;
* **Subcellular localization**: Another key open question is whether progerin expressed in yeast correctly localizes to the nucleus. So far, we lack direct evidence of its localization. This could be addressed using immunofluorescence or immunohistochemistry with specific anti-progerin antibodies, which we were able to obtain thanks to our sponsor, Diatheva.

In terms of scientific impact, although our results represent just the beginning for modeling progeria (HGPS) in yeast, we believe that our work can serve as a valuable starting point for further studies. In fact, we anticipate that the phenotype observed in *S. cerevisiae* CEN.PK could be further standardized and subsequently used as a tool to study phenotype rescue in the context of **chemical screening**.
This is the reason why even though this tool represents foundational research, it has the potential to contribute to the development of new drugs aimed at mitigating the effects of progeria in patients.

## References

▲

* [1] Zhang, N., Hu, Q., Sui, T., Fu, L., Zhang, X., Wang, Y., Zhu, X., Huang, B., Lu, J., Li, Z., & Zhang, Y. (2023). Unique progerin C-terminal peptide ameliorates Hutchinson-Gilford progeria syndrome phenotype by rescuing BUBR1. Nature aging, 3(2), 185–201. <https://doi.org/10.1038/s43587-023-00361-w>
* [2] Spear, E. D., Alford, R. F., Babatz, T. D., Wood, K. M., Mossberg, O. W., Odinammadu, K., Shilagardi, K., Gray, J. J., & Michaelis, S. (2019). A humanized yeast system to analyze cleavage of prelamin A by ZMPSTE24. Methods (San Diego, Calif.), 157, 47–55. <https://doi.org/10.1016/j.ymeth.2019.01.001>

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## Introduction

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#### Structure of the Mammalian Results Section

In this experimental phase, we successfully expressed and confirmed the production of **progerin** in mammalian cells, establishing a working model for testing degradation and rescue strategies. Expression was verified through Western blot analysis of **HA-progerin**, confirming correct translation of the construct, and through fluorescence microscopy, which allowed direct visualization of the mEGFP-tagged proteins. In particular, fluorescence imaging confirmed the expression and localization of **progerin-mEGFP**, **SpyTag-mEGFP-NLS-SpyTag**, and **RING-NLS-mEGFP**, with all constructs showing the expected nuclear or perinuclear distribution patterns, albeit in a limited number of transfected cells due to the low transfection efficiency of MRC-5 fibroblasts.

Functional assays showed that progerin expression significantly reduced cell viability at four days post-transfection, as measured by the alamarBlue TM assay, indicating its characteristic cytotoxic effect on fibroblasts. A ROS production assay was also performed to evaluate oxidative stress, but the analysis was carried out at a later time point (six days), when most cells had already lost viability, resulting in uniform and non-informative oxidative profiles.

We also tested the **RING-SpyCatcher** system for its ability to degrade both **mEGFP** and **progerin**, using **flow cytometry** and **Western blot** analysis, respectively. However, the low transfection efficiency in MRC-5 cells prevented reliable detection of double-transfected populations and clear evaluation of degradation effects. Despite these limitations, the experiments provided valuable insights for future optimization, including adjustments to transfection strategies, timing of assays, and choice of cell lines, which will guide the next phase of testing and validation of the **ProgERASE degradation system**.

## Mammalian cell lines - Our experimental strategy

▲

### Overcoming Low DNA Quantity:

The DNA fragments from A to M, ordered from TWIST, were delivered with blunt ends and in a limited amount of **1000 ng**, which was insufficient for direct restriction. To overcome this, the fragments were first ligated into the **pJET1.2/blunt** plasmid to allow for amplification. The resulting plasmid was then digested with NEB restriction enzymes **BamHI HF and XhoI** and analyzed on a 1% agarose gel. Two distinct bands were observed: one corresponding to the plasmid backbone and the other to the insert, at the expected size. The insert band was excised and purified from the gel. Finally, the purified insert was ligated into the **pcDNA3.1** plasmid, pre-digested with the same restriction enzymes, to achieve directional cloning compatible with the RFC 10 standard.

![pcDNA3.1 plasmid map](https://static.igem.wiki/teams/5700/images/results/pcdna3-1.webp)

**Figure 1.**The pcDNA3.1 vector (5,428 bp) contains a strong CMV promoter for expression in mammalian cells and a high-copy pUC origin for propagation in *E. coli*. Cloning is carried out via restriction enzymes. Selection markers include Ampicillin resistance for bacteria and Neomycin resistance for eukaryotic cells.

![pJET1.2 plasmid map](https://static.igem.wiki/teams/5700/images/results/pjet1-2.webp)

**Figure 2.**pJET1.2 plasmid (2947 bp, Thermo Fisher Scientific). The vector features a positive selection system that enables efficient identification of recombinant colonies. Insertion of a DNA fragment disrupts a lethal restriction enzyme gene, allowing only cells carrying recombinant plasmids to survive, while self-ligated vectors lead to host cell death. The plasmid is supplied in a linearized blunt-end form, optimized for blunt-end cloning reactions.

#### Further analyis of our methods

##### Extra information

▲

##### pJET1.2 cloning

All constructs listed in the preview table were received in lyophilized form, rehydrated, and preliminarily ligated into pJET1.2. The ligation products were used to transform competent *Escherichia coli* DH5α, plated on LB agar with Ampicillin, and incubated overnight. The first constructs processed were A, B, and C. To assess pJET1.2 transformation efficiency, six colonies per plate were screened; once confirmed, three colonies were selected for each of the remaining constructs (D, E, F, I, K, M). Individual inocula were prepared, labeled, and grown overnight at 37°C with shaking (150 rpm). The following day, plasmid DNA was extracted with the PureLink™ HQ Mini Plasmid Purification Kit (Invitrogen) and quantified via NanoDrop.

Extracted plasmids were digested with BamHI HF and XhoI, and fragments analyzed by electrophoresis. Positive samples showed two bands (backbone and insert), with those matching the expected insert size considered correct.

##### pcDNA3.1 cloning

Restriction digestion was performed on all plasmid DNA from positive samples. Since NanoDrop measurements indicated low concentrations, the entire 42 µL of DNA was used instead of the 5 µg specified by the protocol. Digestion products were run on a 1% agarose gel with wide wells, clearly separating the plasmid backbone (higher molecular weight) from the insert (lower molecular weight). Insert bands were excised and purified using the QIAquick Gel Extraction Kit (QIAGEN).

The first three samples were quantified by NanoDrop to determine the volume required for ligation at a 3:1 insert-to-plasmid ratio. Purified inserts were ligated into the previously digested pcDNA3.1 plasmid, and the ligation reaction was incubated overnight.

Two control ligation reactions were prepared:

* **Plasmid with restriction enzymes**: This control was included to confirm complete digestion of the plasmid DNA by both restriction enzymes. In cases of incomplete digestion, the plasmid may remain intact or be cleaved at a single site, thereby generating compatible ends that could be re-circularized by the ligase. Transformation with uncut or re-circularized plasmid DNA results in colony formation;
* **Plasmid only**: This control was performed to exclude the occurrence of colonies arising from spontaneous plasmid re-circularization or external contamination, thus ensuring that colony growth in experimental reactions reflected specific ligation events

The following day, chemically competent *E. coli* DH5α cells were transformed with the ligation products and plated on LB agar with ampicillin. Two vials of competent cells were also transformed with the control ligation reactions. After overnight incubation, all plates showed growth except for the control plate transformed with linearized plasmid only. In contrast, ~180 colonies appeared on the plate from control “With T4 Ligase”, due to T4 ligase re-ligating a 69 bp fragment left between the restriction sites, allowing colony growth.

This unintended re-ligation may also have occurred in experimental ligations. To verify, six colonies from each plate were selected, grown overnight at 37 °C with shaking (150 rpm), and plasmid DNA was extracted using the PureLink TM HQ Mini Plasmid Purification Kit (Invitrogen). Restriction digestion with BamHI-HF and XhoI followed by agarose gel electrophoresis confirmed positive clones as those showing two bands: the plasmid backbone and the expected insert.

#### Sequencing

Sequencing was performed for positive samples. Extracted DNA was amplified using the Applied BiosystemsTM BigDyeTM Terminator v3.1 Cycle Sequencing Kit (Fisher Scientific). A total of 20 PCR reactions were set up, two per sample, using the CMV forward and BGH reverse primers.

PCR products were purified using OPTIMA DTRTM 96-Well Plates (EdgeBio) prior to automated Sanger sequencing. Obtained sequences were aligned with the expected sequences using Blast. **Sequence identity** ranged from **92% to 100%** for all constructs.

All plasmids that showed the correct sequence were amplified through transformation of *E. coli* DH5α cells followed by plasmid purification.

| Insert Name | Forward Sequence Identity | Reverse Sequence Identity |
| --- | --- | --- |
| HA-progerin | 98.35% | 99.12% |
| SpyTag-progerin | 100.00% | 99.66% |
| SpyTag-laminA | 99.12% | 98.90% |
| mEGFP-progerin | 98.18% | 100.00% |
| mEGFP-NLS | 92.47% | 93.82% |
| mEGFP-NLS-SpyCatcher | 97.60% | 99.01% |
| RING-NLS-HA | 100.00% | 99.74% |
| RING-NLS-mEGFP | 98.38% | 98.57% |
| RING-NLS-SpyCatcher | 99.35% | 100.00% |
**Table 1.** Identity % for both forward and reverse sequences obtained through pcDNA3.1-insert sequencing by PCR.

A deeper analysis of the alignment readings can be found in the following file:
[pCDNA3.1\_sequencing\_results.pdf](https://static.igem.wiki/teams/5700/pdf/pcdna3-1-sequencing-results.pdf)

### The Spy System

To assess the efficacy of our **RING-bait strategy** in human fibroblasts, we initially considered using HGPS-affected cells transfected with our RING-progerin interaction-fusion protein. However, to gain more reliable insights into the degradation dynamics of progerin, we opted for the **Spy System**, which facilitates protein-protein interactions between molecules fused with **SpyTag and SpyCatcher**. This two-part system allowed the expression of SpyTagged progerin in MRC-5 fibroblasts, enabling the formation of SpyTag-SpyCatcher specific **progerin-RING complexes**.

![Structure of Spt System, both attached and detached](https://static.igem.wiki/teams/5700/images/results/spycatcher-tag.avif)

**Figure 3.** Spy System structure prediction. SpyTag (yellow) and SpyCatcher (blu) are depicted both detached (left) and attached (right). When they interact, they form a covalent isopeptide bond that stabilizes the complex.

The SpyTag/SpyCatcher system originates from the *Streptococcus pyogenes* **FbaB protein**, a fibronectin-binding protein and virulence factor. The **CnaB2 domain** of FbaB forms a stable **isopeptide bond** between lysine K31 and aspartic acid D117, catalyzed by glutamate E77. By splitting the domain into SpyTag (13 amino acids, containing Asp) and SpyCatcher (138 amino acids, containing Lys and Glu), a covalent bond is reconstituted when the two fragments are combined. This system is **highly specific**, demonstrating **high affinity** (≈0.2 µM) and **low intrinsic reactivity** unless the residues are aligned appropriately. The SpyTag can be incorporated at any position on a protein, including the N- or C-terminus or internally, provided the position is surface-exposed. We selected this system for its precision and **one-to-one binding stoichiometry**, which mirrors the architecture of our designed chimeric protein. [1]

### A comparison between HGPS and healthy fibroblasts cell lines

#### Cell Lines Used

After defining the experimental strategy, the next step was to identify suitable cell models for testing the constructs. To this end, we established a collaboration with **Prof.ssa Giovanna Lattanzi** of the **National Research Council (CNR)** in Bologna, a leading expert in laminopathies. Through her laboratory, we obtained two human fibroblast lines, **cc00366s** and **cc00500s**.

The **cc00366s** line derives from a patient affected by Hutchinson–Gilford Progeria Syndrome (HGPS), while **cc00500s** corresponds to a healthy control. From their arrival in the laboratory, both lines were amplified to obtain a sufficient number of cells for subsequent experimental applications.

To assess morphological differences between healthy and progeria-affected cells, two T75 flasks were observed under bright-field microscopy: one containing fibroblasts derived from a healthy donor, and the other from a Hutchinson–Gilford Progeria Syndrome (HGPS) patient.

![On the left side Control fibroblasts exhibit the typical elongated, spindle-shaped morphology and form dense, well-organized monolayers. On the right side, HGPS fibroblasts display irregular and elongated shapes, with thinner cytoplasmic extensions and a disrupted growth pattern](https://static.igem.wiki/teams/5700/images/results/dalattanzi-new.webp)

**Figure 4.**Bright-field microscopy comparison between healthy control fibroblasts (left) and HGPS patient-derived fibroblasts (right); image acquired with Zeiss Primo Vert inverted microscope with 20x magnification. Control fibroblasts exhibit the typical elongated, spindle-shaped morphology and form dense, well-organized monolayers. In contrast, HGPS fibroblasts display irregular and elongated shapes, with thinner cytoplasmic extensions and a disrupted growth pattern. The cells appear less aligned and often form sparse, unevenly distributed clusters.

These **morphological alterations** reflect the **nuclear deformation** and **cytoskeletal instability** characteristic of progeria-affected cells. Even under standard culture conditions, the **phenotypic differences** between the two fibroblast lines **are evident**, visually confirming the impact of progerin accumulation on cellular structure and organization.

Although both lines were successfully expanded, they exhibited slow proliferation rates, with extended doubling times that made them less suitable for repeated transfection assays or large-scale functional studies. To perform the first experimental phase, we therefore adopted an alternative fibroblast line already available in the laboratory: **MRC-5 human lung fibroblasts**.

The **MRC-5** line consists of diploid, non-transformed fibroblasts derived from human fetal lung tissue. These adherent cells display the typical spindle-shaped morphology and form organized monolayers under standard culture conditions. Their doubling time ranges from **40 to 48 hours** in serum-supplemented medium, and they can undergo approximately **42–48 population doublings** before entering senescence.

Thanks to their moderate transfection efficiency, MRC-5 fibroblasts allow only a fraction of cells to express the introduced constructs. This condition prevents excessive accumulation of reactive metabolites and stress factors that would otherwise occur in highly transfected cultures, potentially affecting neighboring cells and leading to widespread toxicity. Maintaining a partially transfected population therefore enables a more physiological response and makes it easier to observe potential recovery effects or compensatory mechanisms within the culture.

**MRC-5** fibroblasts are particularly suited for short-term assays, such as the evaluation of morphological alterations, oxidative stress, and viability changes associated with progerin expression, while their limited lifespan and sensitivity to nutrient depletion and culture stress make them less suitable for long-term experiments.

The choice to use fibroblast lines rather than immortalized cell models was guided by both **biological and translational considerations**. Since the HGPS-derived cells obtained from Prof.ssa Lattanzi are fibroblasts, maintaining the same cell type ensures experimental continuity and phenotypic comparability. Moreover, fibroblasts are among the **most affected tissues in Progeria**, where **nuclear envelope defects** and **cytoskeletal disorganization** are most evident, making them a biologically relevant and disease-representative model.

![Bright-field images of MRC-5 fibroblasts at 90% confluence (left panel) and 40% confluence (right panel)](https://static.igem.wiki/teams/5700/images/results/mrc5-new.webp)

**Figure 5.**Bright-field images of MRC-5 fibroblasts acquired using LEICA: DMi1 inverted microscope. The left (10x magnification) panel shows cells at approximately 90% confluence, forming a dense and uniform monolayer with elongated spindle-like morphology. The right panel (20x magnification) shows the same cell line at around 50% confluence, where individual fibroblasts are more dispersed and clearly distinguishable, maintaining their characteristic elongated shape.

Overall, **MRC-5** fibroblasts provided a reliable and physiologically relevant system for studying the cellular effects of progerin accumulation, validating construct expression, and laying the groundwork for future optimization in more easily transfectable cell models such as **HEK293T**.

#### Unexpected Culture Loss and Impact on Experimental Timeline

During the second half of August, a **technical failure in the CO2 delivery system** of the cell culture incubators led to a complete loss of all our fibroblast cultures. As a result, we were left **without viable cells from mid-August until the second week of September**.
During this period, the team focused exclusively on cloning procedures and plasmid amplification, which had already been initiated in the preceding weeks. Although this allowed us to advance the molecular part of the project, the incident significantly delayed the experimental phase.
Because of the time constraints imposed by the **Wiki Freeze deadline**, we were only able to **perform each cellular assay once**, without the opportunity to repeat or optimize the experiments. This limitation prevented us from obtaining more robust and statistically consolidated data, even though the results provided valuable qualitative insights for future repetitions.

Details on the experimental rationale and control design are provided in the following section ([Experiments](%7B%7B%20url_for%28%27pages%27%2C%20page%3D%27experiments%27%29%20%7D%7D#3rd-pillar)).

### Fluorescence Microscopy

To visualize the **expression and localization** of the fluorescently tagged constructs, **MRC-5** fibroblasts were analyzed by **fluorescence microscopy** on **Day 3** (single transfections) and **Day 4** (double transfections).
Fluorescence was acquired at an excitation wavelength of **488 nm** and emission at **525 nm** in the **FITC channel**. Images were taken from cultures transfected as part of other experiments, and not from newly transfected samples. All the constructs are cloned into the same pcDNA3.1 backbone.

The following constructs were evaluated:

* **SpyTag-mEGFP-NLS-SpyTag**: visualization of mEGFP expression;
* **RING-NLS-mEGFP**: visualization of RING expression through mEGFP fusion;
* **progerin-mEGFP**: visualization of progerin expression through mEGFP fusion;
* **SpyTag-progerin + mEGFP-SpyCatcher**: visualization of progerin localization through forced interaction (SpyTag/Catcher system) with mEGFP

Fluorescence microscopy allowed the visualization of mEGFP expression, acting as a first visual control.

#### SpyTag-mEGFP-NLS-SpyTag visualization

![visualization of SpyTag-mEGFP-NLS-SpyTag in MRC-5 fibroblasts. Phase contrast (top-left), merged fluorescence (low-center), and GFP channel (top-right.](https://static.igem.wiki/teams/5700/images/results/gfp2st-new.webp)

**Figure 6.**Fluorescence induced visualization of SpyTag-mEGFP-NLS-SpyTag in MRC-5 fibroblasts. Phase contrast (top-left), merged fluorescence (low-center), and GFP channel (top-right). A few fluorescent cells can be observed, confirming the expression of the construct. Low cell confluence can be observed, providing insight on low transfection rates. Image acquired utilizing Olympus APX100 with 20x magnification.

#### RING-NLS-mEGFP visualization

![Fluorescence-based visualization of RING-NLS-mEGFP expression in MRC-5 fibroblasts. Phase contrast (top-left), merged fluorescence (low-center), and GFP channel top-right.](https://static.igem.wiki/teams/5700/images/results/ringfp-new.webp)

**Figure 7.** Fluorescence induced visualization of RING-NLS-mEGFP in MRC-5 fibroblasts. Phase contrast (top-left), merged fluorescence (low-center), and GFP channel (top-right). Cells expressing RING-NLS-mEGFP display a diffuse fluorescence, and for this reason subcellular localization was not possible. Only a limited number of fluorescent cells were detected, consistent with the low efficiency of transfection in this cell line. Image acquired utilizing Olympus APX100 with 20x magnification.

#### mEGFP-progerin visualization

![Fluorescence-based visualization of RING-NLS-mEGFP expression in MRC-5 fibroblasts. Phase contrast (left) and merged fluorescence (right).](https://static.igem.wiki/teams/5700/images/results/gfpprog-new.webp)

**Figure 8.**Fluorescence induced visualization of mEGFP-progerin in MRC-5 fibroblasts; phase contrast (left) and merged fluorescence (right. Cells expressing mEGFP-progerin show a faint but detectable GFP signal, confirming construct expression. As for the previous construct, only a limited number of fluorescent cells were observed, reflecting the low transfection efficiency of MRC-5 fibroblasts and the moderate expression levels achieved under these conditions. Image acquired utilizing Olympus APX100 at 20x magnification.

#### Progerin-Spytag + mEGFP-SpyCatcher visualization

![Fluorescence induced visualization of progerin-SpyTag + mEGFP-SpyCatcher in MRC-5 fibroblasts; phase contrast (left) and merged fluorescence (right.](https://static.igem.wiki/teams/5700/images/results/dopptrasfallita-new.webp)

**Figure 9.** Fluorescence induced visualization of progerin-SpyTag + mEGFP-SpyCatcher in MRC-5 fibroblasts; phase contrast (left) and merged fluorescence (right). The image shows no detectable fluorescence providing no information on mEGFP–SpyCatcher expression. suggesting difficulties during the second transfection. Image acquired utilizing Olympus APX100 at 20x magnification.

**Fluorescence microscopy** confirmed that all tested constructs were correctly expressed in MRC-5 fibroblasts, though with **very low transfection efficiency**.
This limitation was particularly **evident in double transfection experiments**, where the probability of cells simultaneously expressing both constructs was extremely low. As a result, fluorescence patterns and subsequent readouts, such as those for degradation or interaction assays, are likely affected by the low transfection efficiency, reducing the statistical robustness of the observations.
Future experiments will focus on **optimizing transfection conditions** or **employing alternative cell lines with higher transfectability** to ensure more reliable expression and localization analyses.

### Western Blot Analysis – Progerin Expression

To confirm the successful expression of **progerin**, we performed a Western blot analysis on lysates obtained from **MRC-5** fibroblasts transfected with the **HA-progerin** construct. Cells were collected on **Day 3**, corresponding to 48 hours after transfection. All the constructs are cloned into the same pcDNA3.1 backbone.

The following conditions were analyzed:

* **Control (untransfected cells):** used to assess background signal and confirm antibody specificity;
* **HA-progerin:** to verify the expression of the HA-tagged progerin construct using an **anti-HA antibody**

![](https://static.igem.wiki/teams/5700/images/results/actin-ha-new.webp)

**Figure 10.** The left panel shows the Western blot probed with an anti-HA antibody. The Thermo Scientific™ Spectra™ Multicolor Protein Ladder is visible on the left. A distinct HA–progerin–specific band is detected at approximately 74 kDa, while the untransfected control lane (to the right of the HA–progerin lane) shows no detectable signal. The right panel displays the Western blot for the housekeeping protein β-actin, developed using the Thermo Scientific™ PageRuler™ Plus Prestained Protein Ladder.

Western blot results confirmed the expression of **HA-progerin**, with a distinct band detected at approximately **74 kDa**, corresponding to the expected molecular weight of the protein. No signal was observed in the **untransfected control**, confirming the specificity of the anti-HA antibody and the absence of non-specific background bands.

These results demonstrate that the **HA-progerin** construct was **correctly expressed** in MRC-5 fibroblasts and can serve as a reliable reference for subsequent analyses of progerin variants and degradation assays.

### alamarBlueTM Cell Viability assay

To evaluate the **effect of progerin expression** and its **targeted degradation** through the RING-SpyCatcher system, cell viability was measured in MRC-5 fibroblasts four days and six days after transfection using the **alamarBlueTM assay**. The assay provided a quantitative readout of metabolic activity, reflecting the overall viability of cells transfected with different construct combinations. Each condition was analyzed in **eight replicates** to ensure statistical robustness, and fluorescence values were normalized as Relative Fluorescence Units (RFU).

Unlike the experimental samples, the control conditions were performed with a different number of replicates.The negative control was measured in duplicate, while the laminA-SpyTag condition was tested in six independent replicates. This difference in replication number should be taken into account when comparing standard errors between conditions, as lower replication increases variability and reduces statistical confidence in the mean values obtained. This difference derives from the limited amount of cells we had in culture. All the constructs are cloned into the same pcDNA3.1 backbone.

The following transfection conditions were tested:

* **Control:** Untransfected cells, serving as a baseline for cell viability;
* **Progerin-SpyTag:** To assess the impact of progerin expression tagged with SpyTag on cell viability;
* **SpyTag-mEGFP-SpyTag + RING-SpyCatcher:** To evaluate whether the degradative activity of RING towards mEGFP affects cell viability;
* **Progerin-SpyTag + RING-SpyCatcher:** To investigate whether **Progerin degradation via the RING-SpyCatcher system** restores cell viability to normal levels or improves it;
* **LaminA-SpyTag:** A lamin A control construct to compare the effects of progerin-induced viability defects with a non-pathological lamin protein

![Chart plotting the mean Relative Fluorescence Intensity against the different transfected wells.](https://static.igem.wiki/teams/5700/images/results/vitalit-def4-2.webp)

**Chart 1.** The bar chart plots the mean Relative Fluorescence Intensity against different transfected wells. Mean RFI and Standard Error are noted on the bottom of the chart.

#### Technical note on the four-day assay.

During the four-day alamarBlueTM assay, the first row of the 96-well plate was affected by a handling issue that compromised fluorescence readings. Consequently, all experimental conditions except laminA-SpyTag were analyzed using seven wells instead of eight, while the negative control was measured in a single well. The laminA-SpyTag condition, which was plated starting from the third row, was unaffected by this problem and was consistently measured in six replicates.

The results at four days revealed a **marked decrease in viability** in cells expressing **Progerin-SpyTag**, confirming the cytotoxic effect of progerin accumulation. Mean fluorescence intensity was approximately 250 RFU for progerin-expressing cells, significantly lower than that observed in both the **laminA-SpyTag** (≈ 550 RFU) and **Control** (≈ 570 RFU) groups, which displayed comparable viability levels.

Co-expression of **progerin-SpyTag** and **RING-SpyCatcher** did not fully restore viability, with **fluorescence values remaining close to those of progerin alone**, indicating that progerin degradation via the RING-SpyCatcher system was only partially effective or not sufficient to counteract the toxic effects of progerin accumulation at this time point. However, fluorescence microscopy and FACS analysis revealed a **low transfection efficiency in MRC-5 fibroblasts**, suggesting that the second transfection (**Day 2**) may not have been fully effective. This limitation could explain the **absence of a clear recovery in cell viability**, as a significant proportion of cells might not have received both constructs required for efficient progerin degradation.

In contrast, the **mEGFP + RING** condition, used as a functional control for RING activity, showed **no evident reduction in cell viability** compared to the control group; however, this observation should be interpreted cautiously, as the **low efficiency** of the second transfection might also have affected this condition, potentially **masking subtle effects of RING expression** on cell metabolism.

Overall, these findings demonstrate that **progerin expression significantly reduces cell viability at four days**, whereas **lamin A** and **mEGFP + RING** maintain metabolic activity comparable to untransfected controls. The partial or absent recovery observed in the **progerin + RING** condition may be linked to the limited transfection efficiency rather than to a complete lack of effect of the RING-SpyCatcher system. These data are consistent with fluorescence microscopy observations showing limited co-expression of the two constructs, and future experiments with optimized transfection conditions will be required to confirm the functional activity of the degradative system.

Cell viability was evaluated again at **six days post-transfection** using the alamarBlueTM assay to assess the **proliferation progression dependent from progerin expression and the RING-SpyCatcher system**.
![Chart plotting the mean RFI against the different transfected wells.](https://static.igem.wiki/teams/5700/images/results/vitalit-def6-2.webp)

**Chart 2.** The bar chart plots the mean Relative Fluorescence Intensity against the different transfected wells. Mean RFI and Standard Error are noted on the bottom of the chart.

At this time point, all transfected conditions showed a **strong decrease in metabolic activity** compared to the negative control, indicating a **general reduction in cell viability**. Mean fluorescence values ranged between 52–84 RFU for all transfected samples, while the negative control displayed a markedly higher mean value (≈ 320 RFU).

Notably, cells were not provided with a medium change after transfection, which likely contributed to the overall decline in viability observed across all conditions. This lack of medium renewal, combined with prolonged culture stress, may have led to nutrient depletion and waste accumulation, resulting in a widespread loss of metabolic activity independent of transfection type.

These results are consistent with the Total ROS Production Assay, where increased oxidative stress was detected in parallel cultures at the same time point, confirming that cellular stress and decreased metabolic function contributed to the loss of viability at six days.

Overall, the six-day data indicate that while progerin expression exerts cytotoxic effects, the **generalized cell death** observed here is largely **attributable to culture conditions** rather than to specific construct effects, emphasizing the need for medium renewal in extended assays to accurately evaluate viability differences over time.

### Total ROS Production Assay

To assess potential oxidative stress associated with progerin expression and its possible modulation by the **RING-SpyCatcher** system, we performed a **Total ROS Production Assay** in **MRC-5** fibroblasts. The assay was conducted six days after seeding, at the same timepoint as the alamarBlueTM viability assay. Fluorescence intensity was measured as Relative Fluorescence Units (RFU), providing a quantitative indicator of intracellular ROS accumulation. All the constructs are cloned into the same pcDNA3.1 backbone.

The following transfection conditions were tested:

* **HA-progerin:** To evaluate ROS production due to the presence of progerinl;
* **SpyTag-progerin:** To determine the effect of progerin tagged with SpyTag on ROS levels;
* **mEGFP-progerin:** A fusion construct of progerin with mEGFP, used to investigate whether the addition of a fluorescent tag alters ROS production;
* **RING-mEGFP:** To assess the effect of the RING domain (fused to mEGFP) on ROS production, testing whether the RING domain influences oxidative stress;
* **RING-SpyCatcher:** To analyze whether the combination of the RING domain with SpyCatcher modifies ROS production, potentially due to the structural impact of SpyCatcher;
* **mEGFP-NLS:** Used as a control to evaluate whether the mEGFP tag alone contributes to ROS production;
* **mEGFP-SpyCatcher:** A control to test the effect of the SpyCatcher tag in the context of mEGFP-tagged constructs;
* **laminA-SpyTag:** A lamin A control construct to compare progerin-induced ROS with a non-pathological lamin protein;
* **Negative control:** Untransfected cells used to establish baseline ROS production, representing normal ROS levels in cells not subjected to transfection or overexpression

Each condition was analyzed in multiple replicates, and mean RFU values with their respective standard deviations are reported below the chart.
![chart plots the mean RFI against the different transfected wells.](https://static.igem.wiki/teams/5700/images/results/roschart-2.webp)

**Chart 3.** Total Ros assay readout. The bar chart plots the mean Relative Fluorescence Intensity against the different transfected wells. Mean RFI and Standard Error are noted on the bottom of the chart.

As shown in **Chart 3**, all transfected conditions exhibited relatively similar fluorescence levels, with progerin-expressing constructs (**HA-progerin, progerin-SpyTag, progerin-mEGFP**) showing mean RFU values around 0.5, comparable to those of **RING** and **SpyCatcher** constructs. The negative control displayed a slightly higher fluorescence value (≈ 0.84 RFU).

At this stage of the experiment, cell viability was markedly reduced across all conditions, indicating that most cells were undergoing late-stage stress or death. Under these conditions, any **potential differences in ROS production** between constructs were likely masked by the **generalized loss of viable cells**. The residual fluorescence detected primarily reflects the number of surviving cells, rather than genuine differences in oxidative stress levels. The **higher RFU observed in the control** wells is therefore consistent with a **greater number of viable cells**, which naturally produce more ROS as a consequence of normal metabolic activity.

Overall, these results indicate that by **six days post-seeding**, **cell death had leveled out differences in ROS production**, resulting in comparable oxidative readouts across all transfected conditions. Future repetitions of this assay should be performed at four days post-transfection, when the alamarBlueTM viability assay revealed the greatest difference in cell survival between conditions. Performing the ROS test at that timepoint will allow a more accurate assessment of the relationship between progerin expression, oxidative stress, and cell viability.

### RING-SpyCatcher Functionality

To evaluate whether **RING-SpyCatcher** could induce **mEGFP** degradation in the presence of **SpyTag**, we performed a flow cytometry (FACS) assay on **MRC-5** fibroblasts transfected with different construct combinations. The analysis was conducted on **Day 4**, following two sequential transfections. Fluorescence was detected using an excitation wavelength of 488 nm and an emission wavelength of 525 nm, collected in the FITC channel. All the constructs are cloned into the same pcDNA3.1 backbone.

The following conditions were tested:

* **Negative Control:** untransfected cells, used to determine baseline fluorescence and gating parameters;
* **SpyTag-mEGFP-SpyTag**: single transfection to measure mEGFP expression levels in the absence of RING-SpyCatcher;
* **RING-SpyCatcher + SpyTag-GFP-SpyTag:** co-transfection to test whether the RING-SpyCatcher system induces mEGFP degradation

Each condition was analyzed in duplicate, and data were acquired from gated populations excluding debris and artifacts.

![FACS analysis of untransfected cells. Left: FSC-A vs SSC-A. Center: Fluorescence (B525-A) vs SSC-A plot of P1. Right: Histogram of fluorescence intensity](https://static.igem.wiki/teams/5700/images/results/ctrlfacs.webp)

**Figure 11.** Negative control (untransfected MRC-5 fibroblasts). FACS analysis of untransfected cells. Left: FSC-A vs SSC-A plot showing the gated cell population (P1). Center: Fluorescence (B525-A) vs SSC-A plot of P1, indicating absence of mEGFP-positive cells (0.19%). Right: Histogram of fluorescence intensity showing only background autofluorescence

![FACS analysis of MRC-5 fibroblasts expressing mEGFP tagged with SpyTag. Left: Gated population (P1) of single-transfected cells. Center: Fluorescent population (P2, 1.79%. Right: Histogram showing low fluorescence intensity.](https://static.igem.wiki/teams/5700/images/results/gfpfacs.webp)

**Figure 12.** SpyTag-mEGFP-SpyTag single transfection. FACS analysis of MRC-5 fibroblasts expressing mEGFP tagged with SpyTag. Left: Gated population (P1) of single-transfected cells. Center: Fluorescent population (P2, 1.79%) indicating limited mEGFP expression. Right: Histogram showing low fluorescence intensity (~10⁵ RFU), consistent with low transfection efficiency.

![FACS analysis of MRC-5 fibroblasts co-transfected with RING-SpyCatcher and SpyTag-GFP-SpyTag. Left: Gated population (P1) of co-transfected cells. Center: Fluorescent population (P2, 2.10%. Right: Histogram showing similar fluorescence intensity](https://static.igem.wiki/teams/5700/images/results/gfpringfacs.webp)

**Figure 13.** RING-SpyCatcher + SpyTag-mEGFP-SpyTag co-transfection. FACS analysis of MRC-5 fibroblasts co-transfected with RING-SpyCatcher and SpyTag-mEGFP-SpyTag. Left: Gated population (P1) of co-transfected cells. Center: Fluorescent population (P2, 2.10%) comparable to single mEGFP transfection, suggesting no evident degradation. Right: Histogram showing similar fluorescence intensity (~105 RFU) to mEGFP-only cells, indicating no measurable reduction in mEGFP signal.

#### Data visualization and gating strategy

Data visualization and gating strategy

Each set of plots is composed of three panels:

* **Left panel (FSC-A vs SSC-A):** represents forward scattering (FSC) versus side scattering (SSC), used to evaluate cell size and internal complexity. A gating region (P1) was defined to select the main cell population and exclude debris, aggregates, or air bubbles;
* **Middle panel (B525-A vs SSC-A):** displays fluorescence intensity versus side scatter, filtered according to the P1 gate. The fluorescent population (P2) is highlighted in the upper region of the plot, representing cells expressing mEGFP. The corresponding percentage of fluorescent cells within the total population is indicated;
* **Right panel (Fluorescence histogram):** shows fluorescence intensity distribution (x-axis) against cell count (y-axis) for the gated population. The histogram allows direct comparison of fluorescence magnitude between samples

#### Results

The negative control (untransfected cells) exhibited only background autofluorescence, confirming the validity of the gating strategy. In the **SpyTag-mEGFP-SpyTag** condition, a small fluorescent population was detected (~1.8% of total), indicating a low transfection efficiency in MRC-5 fibroblasts. In the **RING-SpyCatcher + SpyTag-mEGFP-SpyTag** co-transfection, the fluorescent population (~2.1%) and overall fluorescence intensity were comparable to the single mEGFP transfection, with no measurable reduction in mEGFP-positive cells or fluorescence magnitude.

These results suggest that **no significant mEGFP degradation was detectable** under the present conditions. The very low transfection efficiency likely limited the number of double-transfected cells, preventing clear observation of RING-mediated degradation. Moreover, the fluorescence intensity of mEGFP-positive populations was in the range of 10⁵ RFI, whereas in efficiently transfected cell lines, signals typically reach 106–107RFI, producing a distinct separation between fluorescent and non-fluorescent populations—an effect not observed here.

Overall, these data indicate that the RING-SpyCatcher system could not be effectively evaluated in this experiment due to low transfection rates in MRC-5 cells. The experiment will be **repeated using cell lines (HEK293T)** with higher transfection efficiency to confirm the degradative function of RING under optimized conditions.

### Western Blot Analysis – progerin Degradation

To evaluate whether the **RING-SpyCatcher system** could promote progerin degradation, we performed a Western blot on **MRC-5** fibroblast lysates collected from cells transfected with various constructs. All samples were detected using the **anti-progerin antibody** (Diatheva Srl, ANT0046; Rabbit Anti-Human Cleaved-Farnesylated Prelamin A).
Cells were transfected on **Day 1** and **Day 2** (for double transfections) and harvested on **Day 4** for protein extraction.

The following conditions were analyzed:

* **Control (untransfected cells):** used to verify the absence of background signal;
* **Progerin-SpyTag:** single transfection to confirm the expression of SpyTag-tagged Progerin;
* **Progerin-mEGFP:** to evaluate the expression of the mEGFP-fused progerin variant;
* **RING-Catcher:** used to confirm antibody specificity and ensure no cross-reactivity with RING-containing proteins;
* **mEGFP-NLS:** used as a negative control for the anti-progerin antibody;
* **Progerin-SpyTag + mEGFP:** baseline control for progerin expression in a double-transfection setup;
* **Progerin-SpyTag + RING-SpyCatcher:** experimental condition to test potential Progerin degradation induced by RING-SpyCatcher co-expression.

![](https://static.igem.wiki/teams/5700/images/results/westernno-new.webp)

**Figure 14.** Western blot readout (low) after incubation with primary antibody (Rabbit Anti-Human Cleaved-Farnesylated Prelamin A antibody; ANT0046; Diatheva Srl). No distinct bands could be detected under the concentrations and incubation time used. Longer exposure did not make any specific bands visible. Marker visualization is represented on top.

The resulting Western blot **did not show any progerin-specific bands** in any of the analyzed conditions. The Thermo ScientificTM SpectraTM Multicolor Protein Ladder bands were visible on the right side of the membrane, confirming proper electrophoretic migration and transfer. However, no distinct signal at the expected ~70 kDa band corresponding to progerin was detected in any sample.

This result rendered the assay inconclusive, as it was **not possible** to evaluate whether **RING-SpyCatcher induced progerin degradation**. The most plausible explanation is the suboptimal performance of the primary anti-progerin antibody, which had not been validated for Western blot detection.

The antibody was provided by **Diatheva Srl** within an active collaboration and had been previously validated only for immunofluorescence. As agreed with the company, the **present results**, whether positive or negative, **will be shared to support further antibody validation**.

In this assay, the antibody was used at a 1:2000 dilution with a 1-hour incubation, conditions that may have been insufficient for effective detection. **Future optimization** will include longer incubation times and alternative antibody dilutions, with the goal of establishing a reliable protocol for progerin detection by Western blot and enabling robust evaluation of RING-SpyCatcher–mediated degradation in subsequent experiments.

### NanoLuc Binary Technology (NanoBiT Assay)

![Starting from the in-silico designed library of interactors, the NanoBiT complementation assay.](https://static.igem.wiki/teams/5700/images/results/esperimento3-mam.webp)

**Figure 15.** NanoBiT pipeline: image created with BioRender. Starting from the in-silico designed library of interactors, the NanoBiT complementation assay will provide quantitative information on the actual interaction the peptides have onto progerin in a physiological environment.

To extend the validation of our system beyond degradation-focused assays and to directly assess protein–protein interactions between progerin and its designed interactors, we implemented the **NanoLuc Binary Technology (NanoBiT)** system [[2]](https://doi.org/10.1021/acschembio.5b00753).
This method is based on the **reversible reconstitution of NanoLuc luciferase** through the association of its two fragments, Small BiT (SmBiT) and Large BiT (LgBiT), each fused to a protein of interest. When the two fusion partners interact, the SmBiT and LgBiT fragments are brought into close proximity, allowing the luciferase enzyme to **refold into its active conformation**. This conformational change restores the **catalytic activity of NanoLuc**, producing a strong luminescent signal that can be quantitatively measured in living cells.

Although interaction between progerin and its binders was previously verified through yeast two-hybrid screening and will be further evaluated by **Microscale Thermophoresis** (Monolith X), the NanoBiT assay provides a crucial complementary validation. Unlike those systems, which operate in *in vitro* or yeast contexts, NanoBiT enables the detection of **protein–protein interactions within mammalian cells**, reproducing the physiological environment in which the designed degradation system must ultimately function. This ensures that binding events observed in earlier assays are not artifacts of heterologous systems but are maintained in the cellular context relevant for therapeutic applications.
![](https://static.igem.wiki/teams/5700/images/results/nanobit.webp)

**Figure 16.**  Schematic representation of the NanoBiT system showing Small BiT (yellow) and Large BiT (light green) in both a detached, inactive conformation (left) and a complexed, active conformation. When the fusion partners interact, the proximity of Small BiT and Large BiT induces a conformational rearrangement that restores NanoLuc catalytic activity, resulting in luminescence.

Although experimental validation could not yet be completed due to the limited number of MRC-5 fibroblasts available, the entire **preparatory phase of the assay was successfully accomplished**. This included DNA sequence optimization for NanoBiT cloning, vector assembly, and bacterial transformation. The constructs are currently awaiting sequence verification by Sanger sequencing using NanoBiT-specific primers, which will confirm successful cloning before proceeding with in-cell luminescence assays.

## Conclusions and Future Perspectives

▲

Through this experimental phase, we successfully established the complete workflow required to evaluate our degradation system in mammalian cells, from DNA amplification and cloning into the mammalian expression vector pcDNA3.1, to construct validation, transfection, and subsequent functional assays. The results confirmed the **correct expression of the designed constructs**, including HA-progerin, progerin-SpyTag, RING-SpyCatcher, progerin-mEGFP, and SpyTag-mEGFP-SpyTag.

Despite the low transfection efficiency observed in MRC-5 fibroblasts, **fluorescence microscopy** and **Western blot analyses** confirmed that the constructs were properly expressed. Cell viability tests provided preliminary but consistent indications that progerin accumulation negatively impacts cell metabolism and proliferation, while co-expression with the **RING-SpyCatcher system may partially modulate these effects**.

These results mark an important step toward the experimental validation of the ProgERASE strategy, in order to confirm the feasibility of using the RING-SpyCatcher platform as a programmable degradation system. Although several optimizations are still required, particularly regarding transfection efficiency, antibody validation, and assay sensitivity, the foundation for further development in mammalian models has been successfully established.

### Experiment Improvements

#### Cell Line Optimization: HEK293T as a High-Transfection Model

To **improve the consistency and interpretability of future experiments**, we plan to complement the current fibroblast-based assays with **HEK293T cells**, which exhibit one of the highest transfection efficiencies among mammalian cell lines (often exceeding 70–90% with standard lipid-based reagents such as Lipofectamine 2000 or PEI). We chose to perform our experiments using MRC-5 fibroblasts, as their lower transfection efficiency results in progerin expression at sub-saturating levels. This condition helps **preserve phenotypic variability** and prevents the extensive cell loss observed under high-expression scenarios.

However, to confirm the functionality of the **RING-SpyCatcher system**, we plan to continue our studies using **HEK293T cells**. These cells are immortalized, robust, and fast-growing, providing a more homogeneous model for testing genetic constructs and fluorescent reporters. Their high metabolic activity and resilience to transfection-induced stress make them particularly suitable for optimizing plasmid ratios and analyzing the kinetics of the degradation system.
Using **HEK293T cells** will allow us to:

* **Optimize time windows for assays** (24–72 h post-transfection) to capture degradation dynamics before secondary cytotoxic effects dominate;
* Achieve **clearer and more statistically reliable fluorescence and FACS readouts** due to a higher number of successfully transfected cells;
* Perform various Western blot assays on progerin-transfected cell’s lysates, optimizing **Diatheva ANT0046 antibody concentrations and exposure times** in cells with high transfection efficiency

#### Refinement of the mEGFP Degradation Assay

To enhance the evaluation of mEGFP degradation mediated by the **RING–SpyCatcher system**, future experiments will employ a **bicistronic plasmid designed to co-express RING–SpyCatcher and RFP from a single transcriptional unit**.
In the initial setup, MRC-5 fibroblasts were co-transfected with **SpyTag–mEGFP–SpyTag** and **RING–SpyCatcher** constructs; however, low transfection efficiency hindered the reliable detection of double-positive cells.
The inclusion of an RFP reporter will make it possible to **identify and gate RFP and mEGFP-positive cells**, those effectively expressing both **mEGFP-SpyTag** and **RING–SpyCatcher**, and quantitatively **compare mEGFP intensity between RFP-positive and RFP-negative populations**. This approach will:

* Provide an internally **normalized measurement** of degradation efficiency;
* **Reduce noise** caused by uneven transfection or expression variability;
* Allow **FACS-based sorting and downstream validation** (e.g. Western blot or microscopy) of the **RING–SpyCatcher** expressing population

#### Optimization of the ROS Assay

To improve data reliability in oxidative stress assays, future replicates of the **Total ROS assay** will be performed either on **Day 4** after seeding, or after a medium change at **Day 3** to maintain cell viability.
Previous tests showed that by **Day 6**, a significant proportion of cells had detached or died, leading to inconsistent fluorescence values. Adjusting timing and refreshing the medium will help ensure that **fluorescence reflects true intracellular ROS accumulation**, rather than artifacts from population loss.
Normalization to cell viability (e.g., via alamarBlue, DNA content, or confluence measurements) will be integrated into future runs to provide a quantitative correction factor linking ROS signal intensity to living cell number.

#### Optimization of the alamarBlueTM Viability Assay

To refine the assessment of cellular viability and better capture the dynamic effects of progerin expression and **RING–SpyCatcher** co-transfection, we plan to **optimize the alamarBlueTM Cell Viability assay protocol**. In the initial experiments, viability was measured at **Day 4** and **Day 6** post-transfection. While the **Day 4** assay revealed **clear and significant differences** in metabolic activity between the experimental conditions, by **Day 6** most cells had already lost viability, preventing further quantitative interpretation.

Future experiments will therefore include **daily viability monitoring over an extended time course to generate a detailed growth profile**. Specifically, fluorescence will be first recorded at **Day 0** (immediately after seeding) to establish a common baseline for all wells, and then measured daily for approximately ten days, with medium replacement performed as needed to maintain optimal culture conditions.

This approach will enable us to:

* Monitor the **progressive effects of progerin expression** and RING–SpyCatcher co-expression on cell proliferation and metabolic recovery;
* Identify the **exact time window** in which viability differences are most pronounced;
* Distinguish between **acute cytotoxicity** and **long-term adaptive responses**;
* Ensure that the assay reflects true metabolic variations rather than cumulative cell death due to culture stress

Tracking viability across multiple timepoints will thus provide a more accurate and continuous representation of cell health and growth dynamics in response to progerin expression and its targeted degradation.

### Future Perspectives

#### NanoBiT Assay

After confirming successful cloning through vector sequencing, we will proceed with testing the NanoBiT control vectors (N203, N204) to verify:

* The functionality of the assay reagents;
* The compatibility of MRC-5 fibroblasts with the NanoBiT detection system

Following control validation, we will assess the interaction between **LgBiT–laminA** and **SmBiT–progerin**, as well as between **SmBiT–progerin** and **LgBiT–progerin**. Detection of a luminescent signal in these conditions will confirm that **progerin is correctly folded and functionally expressed within the NanoBiT assay environment**. Moreover, the observation of **progerin–progerin** interaction would provide further insight into its **ability to self-associate**, supporting the possibility of RING dimerization within the degradation system.
Once these preliminary validations are completed, we will perform assays between **SmBiT–Progerin** and **LgBiT–Interactor** constructs to evaluate specific binding, while **SmBiT–lamin A** will be used in parallel as a **specificity control**. This comparison is essential to ensure that the designed interactors **selectively recognize progerin** without binding to wild-type lamin A.

If the NanoBiT system performs as expected, we will **extend the screening to a broader panel of interactors**, enabling a systematic evaluation of binding strength and specificity directly within mammalian cells.

#### Toward Viral-Mediate Delivery

In the next stages of development, we aim to translate our approach into a **disease-relevant context** by testing the system in **HGPS primary fibroblasts**. This step will be undertaken only after completing the characterization of our degradation mechanism in laboratory-engineered fibroblasts, ensuring **full validation under controlled conditions**.

To enable targeted delivery in patient-derived cells, we plan to use viral delivery systems, such as Adeno-Associated Virus (AAV) or Lentiviral Vectors, to deliver our therapeutic construct.

**AAVs** represent a well-established platform for gene delivery, offering stable, long-term expression without genomic integration, and the possibility of tailoring tissue tropism and minimizing immunogenicity through serotype and capsid selection. On the other hand, **Lentiviral Vectors** are effective gene delivery tools that enable stable, long-term expression by integrating into the host genome. They can transduce both dividing and non-dividing cells, making them versatile for therapeutic and research applications. By modifying their envelope proteins, lentiviruses can be tailored for specific tissue targeting and minimized immune responses, making them ideal for gene therapy and functional gene studies.

This preclinical phase will **bridge our current in vitro validation to future translational applications**, providing a robust framework for assessing safety, efficiency, and specificity in a physiopathological model of HGPS.

#### AAV-Immune Considerations and Pediatric Window

Although AAV can elicit innate and adaptive immune responses to both capsid and transgene, studies indicate that anti-AAV antibody seroprevalence is significantly lower in children (often <15% in ages 3–12, increasing to >50% in adults). [[3]](https://doi.org/10.1016/j.omtm.2024.101273)
This suggests a **therapeutic window in pediatric populations**, including HGPS patients, in which viral transduction could be achieved with **minimal immune interference**. Nonetheless, standard NAb screening will remain essential prior to any application.
Given that HGPS cells exhibit a pro-inflammatory phenotype—characterized by elevated NF-κB activity and cytokine secretion—careful immunological monitoring (IL-6, TNF-α, interferon-stimulated genes) will be implemented in translational stages.

## From Troubleshooting to Proof-of-Concept

▲

Following the conclusion of the initial experimental phase, where we identified low transfection efficiency in MRC-5 fibroblasts as a limiting factor, our team continued the validation process post-Wiki Freeze. Guided by the "Test" and "Learn" phases of our engineering cycle, we strategically transitioned to HEK293T cells to overcome expression hurdles and rigorously evaluate the functionality of the ProgERASE system.

This section presents the decisive data obtained during this optimization phase, providing the final experimental confirmation of our system's capabilities. The results are structured into three key validation steps:

* **Nuclear Activity Validation** (FACS Assay): Quantitative assessment of fluorescence reduction in HEK293T cells, demonstrating the system's ability to degrade a nuclear target (SpyTag-mEGFP-NLS-SpyTag) with statistical significance;
* **Subcellular Localization** (Confocal Microscopy): High-resolution imaging confirming the co-localization of our constructs with nuclear markers (DRAQ5), proving that the degradation occurs specifically within the nuclear compartment;
* **Target Degradation** (Western Blot): The definitive biochemical proof of Progerin clearance. Through optimized immunodetection protocols, we demonstrate robust degradation of the pathological protein Progerin in the presence of the RING-SpyCatcher system

These findings collectively resolve the limitations encountered in the preliminary phase and validate ProgERASE as a functional, nucleus-specific targeted degradation platform.

## References

▲

* [1] Long Li, Jacob O. Fierer, Tom A. Rapoport, Mark Howarth, Structural Analysis and Optimization of the Covalent Association between SpyCatcher and a Peptide Tag, Journal of Molecular Biology, Volume 426, Issue 2 (2014), pp 309-317.<https://doi.org/10.1016/j.jmb.2013.10.021>
* [2] Andrew S. Dixon, Marie K. Schwinn, Mary P. Hall, Kris Zimmerman, Paul Otto, Thomas H. Lubben, Braeden L. Butler, Brock F. Binkowski, Thomas Machleidt, Thomas A. Kirkland, Monika G. Wood, Christopher T. Eggers, Lance P. Encell, Keith V. Wood. NanoLuc Complementation Reporter Optimized for Accurate Measurement of Protein Interactions in Cells. ACS Chemical Biology, Volume 11, Issue 2 (2016), pp. 400–408. <https://doi.org/10.1021/acschembio.5b00753>
* [3] Amit Chhabra, George Bashirians, Christos J. Petropoulos, Terri Wrin, Yuvika Paliwal, Peter V. Henstock, Suryanarayan Somanathan, Candida da Fonseca Pereira, Ian Winburn, John E.J. Rasko. Global seroprevalence of neutralizing antibodies against adeno-associated virus serotypes used for human gene therapies. Molecular Therapy - Methods & Clinical Development. Volume 32, Issue 3. (2024) <https://doi.org/10.1016/j.omtm.2024.101273>.

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