Difference between revisions of "Part:BBa K5237007"
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<section id="4.3"> | <section id="4.3"> | ||
<h2>4.3 <i>In Silico</i> Characterization using DaVinci</h2> | <h2>4.3 <i>In Silico</i> Characterization using DaVinci</h2> | ||
+ | <div class="thumb tright" style="margin:0;"> | ||
+ | <div class="thumbinner" style="width:300px;"> | ||
+ | <iframe style="width:99%;" class="thumbimage" title="Heidelberg: GCN4-MD (2024)" width="560" height="315" | ||
+ | src="https://video.igem.org/videos/embed/36edba03-5fef-4b19-9b2f-2c802e126660?loop=1&title=0&warningTitle=0" | ||
+ | frameborder="0" allowfullscreen="" | ||
+ | sandbox="allow-same-origin allow-scripts allow-popups allow-forms"></iframe> | ||
+ | <div class="thumbcaption"> | ||
+ | <i><b>Figure 5: Molecular dynamics simulation of GCN4</b> | ||
+ | </div> | ||
+ | </div> | ||
+ | </div> | ||
<p> | <p> | ||
We developed DaVinci, an in silico model, for rapid engineering and optimization of our PiCasSO system. DaVinci | We developed DaVinci, an in silico model, for rapid engineering and optimization of our PiCasSO system. DaVinci | ||
Line 485: | Line 496: | ||
DaVinci operates in three phases: static structure prediction, all-atom dynamics simulation, and long-range DNA | DaVinci operates in three phases: static structure prediction, all-atom dynamics simulation, and long-range DNA | ||
dynamics simulation. We applied the first two phases to our components, allowing us to characterize the structure | dynamics simulation. We applied the first two phases to our components, allowing us to characterize the structure | ||
− | and dynamics of the DNA-binding interactions. | + | and dynamics of the DNA-binding interactions. |
<br> | <br> | ||
− | For our bivalent DNA-binding Mini Staple (<a href="https://parts.igem.org/Part:BBa_K5237009">BBa_K5237009</a>), consisting of GCN4 fused via a GSG-linker to rGCN4 | + | For our bivalent DNA-binding Mini Staple (<a href="https://parts.igem.org/Part:BBa_K5237009">BBa_K5237009</a>), |
− | (<a href="https://parts.igem.org/Part:BBa_K5237008">BBa_K5237008</a>), we predicted the structure and binding affinity and tested various linker options. We evaluated | + | consisting of GCN4 fused via a GSG-linker to rGCN4 |
+ | (<a href="https://parts.igem.org/Part:BBa_K5237008">BBa_K5237008</a>), we predicted the structure and binding | ||
+ | affinity and tested various linker options. We evaluated | ||
the flexibility and rigidity of the constructs using pLDDT values from the predictions. Flexible linkers, like | the flexibility and rigidity of the constructs using pLDDT values from the predictions. Flexible linkers, like | ||
('GGGGS')n, and rigid linkers, like ('EAAAK')n, were assessed (Arai et al., 2001). Predictions were colored by | ('GGGGS')n, and rigid linkers, like ('EAAAK')n, were assessed (Arai et al., 2001). Predictions were colored by | ||
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style="width:99%;" /> | style="width:99%;" /> | ||
<div class="thumbcaption"> | <div class="thumbcaption"> | ||
− | <i><b>Figure | + | <i><b>Figure 6: Variation of linkers connecting our mini staples.</b> |
Panels A (BBa_K5237007) and B (BBa_K5237008) show | 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 | orientations of the leucine zipper, each bound to DNA. Panels C to I display linker variations colored by | ||
Line 532: | Line 545: | ||
<p>Arai, R., Ueda, H., Kitayama, A., Kamiya, N., & Nagamune, T. (2001). Design of the linkers which effectively | <p>Arai, R., Ueda, H., Kitayama, A., Kamiya, N., & Nagamune, T. (2001). Design of the linkers which effectively | ||
separate domains of a bifunctional fusion protein. <i>Protein Engineering, Design and Selection, 14</i>(8), 529–532. | separate domains of a bifunctional fusion protein. <i>Protein Engineering, Design and Selection, 14</i>(8), 529–532. | ||
− | <a href="https://doi.org/10.1093/protein/14.8.529" target="_blank">https://doi.org/10.1093/protein/14.8.529</a></p> | + | <a href="https://doi.org/10.1093/protein/14.8.529" target="_blank">https://doi.org/10.1093/protein/14.8.529</a> |
+ | </p> | ||
<p>Chen, X., Zaro, J. L., & Shen, W.-C. (2013). Fusion protein linkers: Property, design and functionality. | <p>Chen, X., Zaro, J. L., & Shen, W.-C. (2013). Fusion protein linkers: Property, design and functionality. | ||
<i>Advanced Drug Delivery Reviews, 65</i>(10), 1357–1369. <a href="https://doi.org/10.1016/j.addr.2012.09.039" | <i>Advanced Drug Delivery Reviews, 65</i>(10), 1357–1369. <a href="https://doi.org/10.1016/j.addr.2012.09.039" | ||
− | target="_blank">https://doi.org/10.1016/j.addr.2012.09.039</a></p> | + | target="_blank">https://doi.org/10.1016/j.addr.2012.09.039</a> |
+ | </p> | ||
<p>Google DeepMind. (2024). AlphaFold Server. <a href="https://alphafoldserver.com/terms" | <p>Google DeepMind. (2024). AlphaFold Server. <a href="https://alphafoldserver.com/terms" |
Revision as of 03:11, 2 October 2024
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.
Contents
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:
DNA-binding proteins: The building blocks for engineering of custom staples for DNA-DNA interactions with a modular system ensuring easy assembly. | ||
BBa_K5237000 | fgRNA Entry vector MbCas12a-SpCas9 | Entryvector for simple fgRNA cloning via SapI |
BBa_K5237001 | Staple subunit: dMbCas12a-Nucleoplasmin NLS | Staple subunit that can be combined with sgRNA or fgRNA and dCas9 to form a functional staple |
BBa_K5237002 | Staple subunit: SV40 NLS-dSpCas9-SV40 NLS | Staple subunit that can be combined witha sgRNA or fgRNA and dCas12avto form a functional staple |
BBa_K5237003 | Cas Staple: SV40 NLS-dMbCas12a-dSpCas9-Nucleoplasmin NLS | Functional Cas staple that can be combined with sgRNA or fgRNA to bring two DNA strands into close proximity |
BBa_K5237004 | Staple subunit: Oct1-DBD | Staple subunit that can be combined to form a functional staple, for example with TetR. Can also be combined with a fluorescent protein as part of the FRET proximity assay |
BBa_K5237005 | Staple subunit: TetR | Staple subunit that can be combined to form a functional staple, for example with Oct1. Can also be combined with a fluorescent protein as part of the FRET proximity assay |
BBa_K5237006 | Simple staple: TetR-Oct1 | Functional staple that can be used to bring two DNA strands in close proximity |
BBa_K5237007 | Staple subunit: GCN4 | Staple subunit that can be combined to form a functional staple, for example with rGCN4 |
BBa_K5237008 | Staple subunit: rGCN4 | Staple subunit that can be combined to form a functional staple, for example with rGCN4 |
BBa_K5237009 | Mini staple: bGCN4 | Assembled staple with minimal size that can be further engineered | Functional elements: Protease-cleavable peptide linkers and inteins are used to control and modify staples for further optimization for custom applications |
BBa_K5237010 | Cathepsin B-cleavable Linker: GFLG | Cathepsin B-cleavable peptide linker that can be used to combine two staple subunits to make responsive staples |
BBa_K5237011 | Cathepsin B Expression Cassette | Expression Cassette for the overexpression of cathepsin B |
BBa_K5237012 | Caged NpuN Intein | A caged NpuN split intein fragment that undergoes protein trans-splicing after protease activation. Can be used to create functionalized staples units |
BBa_K5237013 | Caged NpuC Intein | A caged NpuC split intein fragment that undergoes protein trans-splicing after protease activation. Can be used to create functionalized staples units |
BBa_K5237014 | fgRNA processing casette | Processing casette to produce multiple fgRNAs from one transcript, that can be used for multiplexed 3D genome reprograming |
BBa_K5237015 | Intimin anti-EGFR Nanobody | Interkindom conjugation between bacteria and mammalian cells, as alternative delivery tool for large constructs |
BBa_K4643003 | incP origin of transfer | Origin of transfer that can be cloned into the plasmid vector and used for conjugation as a means of delivery | Readout Systems: FRET and enhancer recruitment to measure proximity of stapled DNA in bacterial and mammalian living cells enabling swift testing and easy development for new systems |
BBa_K5237016 | FRET-Donor: mNeonGreen-Oct1 | FRET Donor-Fluorpohore fused to Oct1-DBD that binds to the Oct1 binding cassette. Can be used to visualize DNA-DNA proximity |
BBa_K5237017 | FRET-Acceptor: TetR-mScarlet-I | Acceptor part for the FRET assay binding the TetR binding cassette. Can be used to visualize DNA-DNA proximity |
BBa_K5237018 | Oct1 Binding Casette | DNA sequence containing 12 Oct1 binding motifs, compatible with various assays such as the FRET proximity assay |
BBa_K5237019 | TetR Binding Cassette | DNA sequence containing 12 Oct1 binding motifs, can be used for different assays such as the FRET proximity assay | BBa_K5237020 | Cathepsin B-Cleavable Trans-Activator: NLS-Gal4-GFLG-VP64 | Readout system that responds to protease activity. It was used to test cathepsin B-cleavable linker |
BBa_K5237021 | NLS-Gal4-VP64 | Trans-activating enhancer, that can be used to simulate enhancer hijacking | BBa_K5237022 | mCherry Expression Cassette: UAS, minimal Promotor, mCherry | Readout system for enhancer binding. It was used to test cathepsin B-cleavable linker |
BBa_K5237023 | Oct1 - 5x UAS binding casette | Oct1 and UAS binding cassette, that was used for the simulated enhancer hijacking assay |
BBa_K5237024 | TRE-minimal promoter- firefly luciferase | Contains Firefly luciferase controlled by a minimal promoter. It was used as a luminescence readout for simulated enhancer hijacking |
1. Sequence overview
- 10COMPATIBLE WITH RFC[10]
- 12COMPATIBLE WITH RFC[12]
- 21COMPATIBLE WITH RFC[21]
- 23COMPATIBLE WITH RFC[23]
- 25COMPATIBLE WITH RFC[25]
- 1000COMPATIBLE WITH RFC[1000]
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 (Kd)
(Fried, 1989).
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.
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.
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.
GCN4 binds to its optimal DNA binding motif with an apparent dissociation
constant KD of (0.293 ± 0.033) × 10-6 M, which is almost identical to the
rGCN4 dissociation constant
to INVii a KD 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.
We developed DaVinci, an in silico model, for rapid engineering and optimization of our PiCasSO system. DaVinci
serves as a digital twin to PiCasSO, analyzing the forces acting on the system, refining experimental parameters,
and identifying optimal interactions between protein staples and target DNA. The model was calibrated using
literature data and experimental affinity results from rGCN4 EMSA assays with purified proteins.
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/bi992705n2. Usage and Biology
3. Assembly and part evolution
4. Results
4.1 Protein expression and purification
4.2 Electrophoretic Mobility shift assay
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:
Θapp = Θmin + (Θmax - Θmin) ×
(Ka2 [L]tot2) / (1 + Ka2
[L]tot2)
Equation 1
Here [L]tot describes the total protein monomer concentration, Ka
corresponds
to the apparent monomeric equilibration constant. The Θmin/max values are the
experimentally
determined site saturation values (For this experiment 0 and 1 were chosen for min and max
respectively).
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
DaVinci operates in three phases: static structure prediction, all-atom dynamics simulation, and long-range DNA
dynamics simulation. We applied the first two phases to our components, allowing us to characterize the structure
and dynamics of the DNA-binding interactions.
For our bivalent DNA-binding Mini Staple (BBa_K5237009),
consisting of GCN4 fused via a GSG-linker to rGCN4
(BBa_K5237008), we predicted the structure and binding
affinity and tested various linker options. We evaluated
the flexibility and rigidity of the constructs using pLDDT values from the predictions. Flexible linkers, like
('GGGGS')n, and rigid linkers, like ('EAAAK')n, were assessed (Arai et al., 2001). Predictions were colored by
pLDDT scores, providing insights into chain rigidity (Akdel et al., 2022; Guo et al., 2022). Construct C (Fig. 5)
was tested in the wet lab as part of BBa_K5237009, but it failed to bind DNA due to excessive rigidity, which
inhibited subunit dimerization.
5. References