Judging

BEST PART: BBa_25NDL8N0 Progerin codon optimised for S. cerevisiae

1. What Makes It New

Our work introduces a yeast-based model for Hutchinson–Gilford Progeria Syndrome (HGPS), built upon a fully standardized and Saccharomyces cerevisiae optimized version of human progerin.
This is the first time that the complete progerin sequence has been designed according to RFC10 and RFC1000 standards and codon-optimized for yeast expression, ensuring full compatibility with iGEM’s BioBrick assembly frameworks.
In addition to the full-length gene, we also generated two functional C-terminal fragments (aa 430–614 and aa 545–614) derived from our optimized construct, designed to study protein–protein interactions in isolation.
Together, these components establish the first modular toolkit for modeling progeria in yeast, offering a tractable, standardized system to study nuclear lamina dysfunction and age-related cellular stress in a eukaryotic model.

2. How it works and how we test it

The optimized progerin sequence was cloned into the pYES2 expression vector (BBa_K555009), enabling galactose-dependent expression under the GAL1 promoter in S. cerevisiae strain CEN.PK.
The plasmid carries the URA3 auxotrophy marker, allowing selection in uracil-deficient media, and replicates in bacteria via the ColE1 origin, enabling efficient amplification and ampicillin-based selection during cloning.
After transformation, Western blot analysis confirmed successful progerin expression, validating both the construct design and the inducible expression system. Functionally, spot assays and growth curve analyses in SD–glucose medium revealed a clear growth impairment in progerin-expressing yeast compared to controls, mirroring the cytotoxicity observed in mammalian cells.
This dual confirmation, at both molecular and phenotypic levels, demonstrates that our construct successfully reproduces the deleterious effects of progerin in yeast, creating a new and reliable model system for HGPS within a simple eukaryotic framework.

3. How it enables future teams

This part represents a new platform for studying progeria and other laminopathies in yeast, providing a simplified yet powerful system to dissect how mutant lamins affect cell physiology.

• Investigate progerin-induced stress, nuclear integrity, and aging-related mechanisms;
• Perform Yeast Two-Hybrid (Y2H) or degradation assays with our C-terminal fragments to identify new interactors;
• Test therapeutic or compensatory mechanisms in a fast, low-cost, and genetically tractable organism.

By transforming S. cerevisiae into a synthetic model of human progeria, our standardized part bridges disease biology and synthetic biology — providing the community with a foundational tool for exploring aging, cellular resilience, and protein homeostasis in eukaryotic systems.

For more details about the part characterization of the construct see the registry (BBa_25NDL8N0) and the validation in mammalian cells Experiment results

Our modeling work represents an innovative and comprehensive approach to one of the major challenges in structural biology: designing selective binders for intrinsically disordered regions (IDRs).
We developed a multi-layered AI-based pipeline integrating AlphaFold3, RFdiffusion, ProteinMPNN, and NeuroBind, combined with HADDOCK and ClusPro docking simulations. This workflow was designed to predict and optimize peptide interactors targeting the disordered C-terminal region of progerin, the pathogenic isoform of lamin A responsible for Hutchinson–Gilford Progeria Syndrome.

Our approach integrates structure prediction, sequence design, docking, and binding affinity estimation to model protein–peptide interactions at atomic resolution. The resulting models provided quantitative data on the dissociation constants (Kd) of each interactor toward progerin and lamin A, allowing us to identify the sequences involved for selective recognition.

Starting from the primary sequences of progerin and lamin A, structures were predicted with AlphaFold3, refined using AMBER and Rosetta Relax, and validated through PDBFixer and MolProbity. Binding affinities were estimated via PRODIGY, and a Kd ratio quantified selectivity between the two isoforms. This integrated workflow offers a robust and generalizable framework for designing peptide binders against intrinsically disordered targets.

The modeling outcomes were not merely predictive but decisive for experimental prioritization. These AI-predictions directly guided the selection of interactors for synthesis and cloning, the design of RING–interactor fusion constructs, and the planning of wet-lab assays (NanoBiT, ELISA, and Western blot).

Beyond the specific case of progerin, our AI-integrated pipeline is modular, transparent, and reproducible, making it a valuable resource for the iGEM community. By modifying input sequences and docking constraints, it can be adapted to design selective binders for any protein of interest—ordered or disordered. In summary, our modeling effort advances the field of de novo protein engineering, combining methodological innovation, biological relevance, and community impact.

For more details about the model navigate our Model wiki page

“The Inclusivity Award is for teams who have explored ways to make scientific research (iGEM, synthetic biology, or STEM more broadly) inclusive of people with diverse backgrounds and identities.”
— iGEM Judge Handbook, 2025

Our team has worked to make inclusivity not just a side initiative, but a core part of our mission. From this vision, we created E.A.S.Y. – Easy Accessible Science for You, a long-term project born entirely within our team and designed to continue growing beyond this year’s competition. E.A.S.Y. aims to make scientific communication accessible to university students and young adults with reading or comprehension difficulties, learning disorders (such as dyslexia), ADHD, and other forms of neurodivergence. By improving comprehension for neurodivergent readers, E.A.S.Y. effectively broadens participation in scientific dialogue, allowing more people to engage with and contribute to synthetic biology. What started as a simple idea became a structured research program dedicated to studying and improving cognitive simplification guidelines for scientific texts, specifically focusing on scientific articles and educational materials, for the first time ever!

All the results, tools, and recommendations developed through this project are freely available to the iGEM community. Any team can adopt or adapt them to improve their own wiki accessibility, outreach materials, or even scientific publications.

Beyond the E.A.S.Y. project, inclusivity has guided every step of our iGEM journey. We sought to include underrepresented groups in scientific research, asking ourselves not only how to simplify science, but for whom we were simplifying it. Our process was deeply participatory: through interviews, surveys, and direct collaboration with neurodivergent individuals, we shaped our guidelines by listening to those most affected. Inclusivity, for us, means sharing agency — building tools with people, not just for them.

Inclusivity also guided the very heart of our biological project. By choosing to focus on Hutchinson-Gilford Progeria Syndrome (HGPS) — a rare and underrepresented disease — we gave visibility to a community often left unheard. We reached out directly to patients and families, learning from their experiences to shape our scientific goals.

Our outreach efforts brought science to those most distant from the laboratory, reaffirming that science belongs to everyone. Finally, inclusivity is something we practice every day within our team. We strive to maintain a welcoming, respectful, and open environment, recognizing that diversity — in identity, perspective, and experience — is our greatest strength. We are also aware of our privilege as members of the scientific community, and we believe it is our responsibility to share that privilege by opening the doors of science to all.

For more details about the model navigate our Inclusivity wiki page.