Staple subunit: GCN4

GCN4 is a yeast transcription factor belonging to the bZip family of DNA-binding proteins. We used GCN4 to study DNA-binding kinetics in our "Mini staples" that bring two DNA target sites into proximity by binding them simultaneously.

Figure 1: How our part collection can be used to engineer new staples

Next to the well-studied linear DNA sequence, the 3D spatial organization of DNA plays a crucial role in gene regulation, cell fate, disease development and more. However, the tools to precisely manipulate this genomic architecture remain limited, rendering it challenging to explore the full potential of the 3D genome in synthetic biology. We - iGEM Team Heidelberg 2024 - have developed PICasSO, a powerful molecular toolbox based on various DNA-binding proteins to address this issue.

The PICasSO part collection offers a comprehensive, modular platform for precise manipulation and re-programming of DNA-DNA interactions using protein staples in living cells, enabling researchers to recreate natural 3D genomic interactions, such as enhancer hijacking, or to design entirely new spatial architectures for gene regulation. Specifically, the fusion of two DNA binding proteins enables to artifically bring distant genomic loci into proximty. To unlock the system's full potential, we introduce versatile chimeric CRISPR/Cas complexes, connected either on the protein or the guide RNA level. These1 complexes are reffered to as protein- or Cas staples. Beyond its versatility, PICasSO includes robust assay systems to support the engineering, optimization, and testing of new staples, ensuring functionality in vitro and in vivo. We took special care to include parts crucial for testing every step of the cycle (design, build, test, learn) when engineering new parts.

At its heart, the PICasSO part collection consists of three categories.
(i) Our DNA-binding proteins include our finalized enhancer hijacking Cas staple as well as half staples that can be used by scientists to compose entirely new Cas staples in the future. We also include our Simple staples that serve as controls for successful stapling and can be further engineered to create alternative, simpler and more compact staples.
(ii) As functional elements, we list additional parts that enhance the functionality of our Cas and Basic staples. These consist of protease-cleavable peptide linkers and inteins that allow condition-specific, dynamic stapling in vivo. Besides staple functionality, we also include the parts to enable the efficient delivery of PICasSO's constructs with our interkingdom conjugation system.
(iii) As the final category of our collection, we provide parts that support the use of our custom readout systems. These include components of our established FRET-based proximity assay system, enabling users to confirm accurate stapling. Additionally, we offer a complementary, application-oriented testing system for functional readouts via a luciferase reporter, which allows for straightforward experimental simulation of enhancer hijacking in mammalian cells.

The following table gives a comprehensive overview of all parts in our PICasSO toolbox. The highlighted parts showed exceptional performance as described on our iGEM wiki and can serve as a reference. The other parts in the collection are versatile building blocks designed to provide future iGEMers with the flexibility to engineer their own custom Cas staples, enabling further optimization and innovation.

Our part collection includes:

1. Sequence overview

2. Usage and Biology

GCN4 is a yeast transcription factor from the bZip family of DNA-binding proteins, first discovered by McKnight and co-workers in 1988. The bZip motif features a coiled-coil leucine zipper dimerization domain paired with a highly charged basic region that binds to DNA. GCN4 binds specifically to the cyclic AMP response element (CRE) DNA sequence (5' ATGACGTCAT 3') in the promoter regions of target genes, primarily through its basic residues at the N-terminus.

In our project we fused GCN4 to rGCN4 (BBa_K5237008) to create a 150 amino aci "Mini staple" that can bring two DNA target sites into close proximity.

The DNA-binding properties of GCN4 were tested using an electrophoretic mobility shift assay (EMSA) to quantify binding affinity and calculate kinetics. EMSA is a widely adopted method to study DNA-protein interactions. It works on the principle that nucleic acids bound to proteins exhibit reduced electrophoretic mobility compared to unbound nucleic acids (Hellman & Fried, 2007). EMSA can be employed both qualitatively, to assess DNA-binding capabilities, and quantitatively, to determine critical parameters such as binding stoichiometry and the apparent dissociation constant (K_d) (Fried, 1989).

3. Assembly and part evolution

The GCN4 amino acid sequence was taken from literature (Hollenbeck et al. 2001) and codon optimized for E. coli. A FLAG-tag (DYKDDDDK) was added to the N-terminus for protein purification. The FLAG-tag can be cleaved off using an Enterokinase, if necessary. The FLAG-GCN4 sequence was cloned into a T7 expression vector and expressed using E. coli BL21 (DE3) cells.

4. Results

4.1 Protein expression and purification

The FLAG-GCN4 protein could be readily expressed in E. coli. The protein was purified using an anti-FLAG resin. Fractions taken during purification were analyzed by SDS-PAGE and the protein concentration of the eluted protein determined with a lowry protein assay. A yield of 1.18 mg/mL was obtained, corresponding to 153 µM of monomeric FLAG-GCN4.

Figure 2: SDS-PAGE analysis of FLAG-GCN4 purification Fractions analysed for each protein are the raw lysate, flow through and eluate. Depicted is GCN4 (this part), rGCN4 (BBa_K5237008), and bGCN4 (BBa_K5237009). Protein size is indicated next to construct name and purified band with protein of interest highlighted by a red box.

4.2 Electrophoretic Mobility shift assay

Figure 3: Overview Image of Electrophoretic Mobility Shift Assay (EMSA)

The Electrophoretic mobility shift assay (EMSA) is a widely adopted method used to study DNA-protein interactions. EMSA functions on the basis that nucleic acids bound to proteins have reduced electrophoretic mobility, compared to their counterpart. (Hellman & Fried, 2007). Mobility-shift assays can both be used to qualitatively assess DNA binding capabilities or quantitatively to determine binding stoichiometry and kinetics such as the apparent dissociation constant (K_d) (Fried, 1989).

To analyze the binding DNA affinity an EMSA was performed, in which GCN4 was incubated in binding buffer with a 20 bp DNA probe containing the CRE GCN4 binding sequence (5' ATGACGTCAT 3') until equilibration. Subsequently the formed protein-DNA complexes were loaded on a native PAGE. Afterwards the DNA bands were stained with SYBR-safe.
To further analyze DNA binding, quantitative shift assays were performed for GCN4 and rGCN4 (BBa_K5237008). 0.5 µM DNA were incubated with varying concentrations of protein until equilibration. After electrophoresis, bands were stained with SYBR-Safe and quantified based on pixel intensity. The obtained values were fitted to equation 1, describing formation of a 2:1 protein-DNA complex:

Θ_app = Θ_min + (Θ_max - Θ_min) × (K_a² [L]_tot²) / (1 + K_a² [L]_tot²) Equation 1

Here [L]_tot describes the total protein monomer concentration, K_a corresponds to the apparent monomeric equilibration constant. The Θ_min/max values are the experimentally determined site saturation values (For this experiment 0 and 1 were chosen for min and max respectively).

Figure 4: Quantitative assessment of binding affinity for GCN4 and rGCN4. Proteins of different concentrations were incubated with 0.5 µM DNA until equilibrium and fraction bound analyzed, after gel electrophoresis, by dividing pixel intensity of bound fraction with pixel intensity of bound and unbound fraction. At least three separate measurements were conducted for each data point. Values are presented as mean +/- SD.

GCN4 binds to its optimal DNA binding motif with an apparent dissociation constant K_D of (0.293 ± 0.033) × 10^-6 M, which is almost identical to the rGCN4 dissociation constant to INVii a K_D of (0.298 ± 0.030) × 10^-6 M. Comparing them to literature values, our dissociation constants are approximately a factor 10 higher then those described in literature ((96) × 10^-8 M for GCN4 and (2.90.8) × 10^-8 M for rGCN4) (Hollenbeck et al., 2001). The differences could be due to the lower sensitivity of SYBR-Safe staining compared to radio-labeled oligos. Most likely, the protein concentration was miscalculated due to the presence of additional (lower intensity) bands in the SDS-PAGE analysis, indicating co-purification of small amounts of unspecific proteins.

The FLAG-tag fusion to the N-terminus of proteins could potentially decrease binding affinity, likely due to steric hindrance affecting the interaction with DNA. Interestingly, the differences in binding affinity between GCN4 and rGCN4 appear negligible. Since GCN4 binds to DNA via its N-terminus and rGCN4 binds C-terminally, the FLAG-tag likely does not directly influence DNA binding. However, it may influence the dimerization of the proteins, which is necessary for DNA binding. To further investigate this, the FLAG-tag can be cleaved using an enterokinase and potential changes in binding affinity analyzed. Furthermore, coiled coil formation, and the amount of dimeric and monomeric proteins could be further analyzed with circular dichroism spectroscopy (Greenfield, 2006).

4.3 In Silico Characterization using DaVinci

We developed the in silico model DaVinci for rapid engineering and development of our PiCasSO system. DaVinci acts as a digital twin to PiCasSO, designed to understand the forces acting on our system, refine experimental parameters, and find optimal connections between protein staples and target DNA. We calibrated DaVinci with literature and our own experimental affinity data obtained via EMSA assays and purified proteins.
DaVinci is divided into three phases: static structure prediction, all-atom dynamics simulation, and long-ranged dna dynamics simulation. We applied the first two to our parts, characterizing structure and dynamics of the dna-binding interaction.

In our efforts to create a bivalent DNA binding protein with minimal size, we created a Mini staple (BBa_K5237009) consisting of GCN4 fused with an GSG-linker to rGCN4 (BBa_K5237008). The structure and binding affinity of GCN4 were predicted and calculated. Furthermore different possible linkers were tested.
We assessed the flexibility and rigidity of our constructs through the pLDDT values assigned during the predictions. Figure 2 illustrates the variation in linkers using the ('GGGGS')_n sequence for flexible linkers and the ('EAAAK')_n sequence for rigid linkers (Arai et al., 2001). The predictions are colored by their pLDDT scores, which act as a surrogate measure of chain rigidity (Akdel et al., 2022; Guo et al., 2022). The construct C (Fig. 5) was tested as part BBa_K5237009 in the Wetlab - it did not bind DNA on any side as the structure is to rigid which hinders dimerisation of the two subunits

Figure 5: Variation of linkers connecting our mini staples. Panels A (BBa_K5237007) and B (BBa_K5237008) show orientations of the leucine zipper, each bound to DNA. Panels C to I display linker variations colored by their pLDDT confidence score, which serves as a surrogate for chain flexibility (Akdel et al., 2022). Note that panels H and I are not bound to the second DNA strand. All structures were predicted using the AlphaFold server (Google DeepMind, 2024).

5. References

Fried, M. G. (1989). Measurement of protein-DNA interaction parameters by electrophoresis mobility shift assay. ELECTROPHORESIS, 10(5-6), 366-376. https://doi.org/10.1002/elps.1150100515

Akdel, M., Pires, D. E. V., Pardo, E. P., Janes, J., Zalevsky, A. O., Meszaros, B., Bryant, P., Good, L. L., Laskowski, R. A., Pozzati, G., Shenoy, A., Zhu, W., Kundrotas, P., Serra, V. R., Rodrigues, C. H. M., Dunham, A. S., Burke, D., Borkakoti, N., Velankar, S., … Beltrao, P. (2022). A structural biology community assessment of AlphaFold2 applications. Nat Struct Mol Biol, 29(11), 1056–1067. https://doi.org/10.1038/s41594-022-00849-w

Arai, R., Ueda, H., Kitayama, A., Kamiya, N., & Nagamune, T. (2001). Design of the linkers which effectively separate domains of a bifunctional fusion protein. Protein Engineering, Design and Selection, 14(8), 529–532. https://doi.org/10.1093/protein/14.8.529

Chen, X., Zaro, J. L., & Shen, W.-C. (2013). Fusion protein linkers: Property, design and functionality. Advanced Drug Delivery Reviews, 65(10), 1357–1369. https://doi.org/10.1016/j.addr.2012.09.039

Google DeepMind. (2024). AlphaFold Server. https://alphafoldserver.com/terms

Greenfield, N. J. (2006). Using circular dichroism spectra to estimate protein secondary structure. Nature Protocols, 1(6), 2876–2890. https://doi.org/10.1038/nprot.2006.202

Guo, H.-B., Perminov, A., Bekele, S., Kedziora, G., Farajollahi, S., Varaljay, V., Hinkle, K., Molinero, V., Meister, K., Hung, C., Dennis, P., Kelley-Loughnane, N., & Berry, R. (2022). AlphaFold2 models indicate that protein sequence determines both structure and dynamics. Scientific Reports, 12(1), 10696. https://doi.org/10.1038/s41598-022-14382-9

Hellman, L. M., & Fried, M. G. (2007). Electrophoretic mobility shift assay (EMSA) for detecting protein-nucleic acid interactions. Nature Protocols, 2(8), 1849-1861. https://doi.org/10.1038/nprot.2007.249

Hollenbeck, J. J., Gurnon, D. G., Fazio, G. C., Carlson, J. J., & Oakley, M. G. (2001). A GCN4 Variant with a C-Terminal Basic Region Binds to DNA with Wild-Type Affinity. Biochemistry, 40(46), 13833-13839.

Hollenbeck, J. J., & Oakley, M. G. (2000). GCN4 Binds with High Affinity to DNA Sequences Containing a Single Consensus Half-Site. Biochemistry, 39(21), 6380-6389. https://doi.org/10.1021/bi992705n