Difference between revisions of "Part:BBa K3934004"

 
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<b>Name:</b> FGF2 Q54K
 
<b>Name:</b> FGF2 Q54K
<br><b>Base Pairs:</b> 828 bp
+
<br><b>Base Pairs:</b> 468 bp
 
<br><b>Origin:</b> Escherichia Coli, synthetic
 
<br><b>Origin:</b> Escherichia Coli, synthetic
<br><b>Parts:</b> FGF2 Q54K, RBS, promotor, terminator
 
 
<br><b>Properties:</b> Bovine growth factor FGF2 designed to increase affinity to the FGFR2 receptor, making it induce cell proliferation. with higher efficiency.
 
<br><b>Properties:</b> Bovine growth factor FGF2 designed to increase affinity to the FGFR2 receptor, making it induce cell proliferation. with higher efficiency.
  
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<h1>Design</h1>
 
<h1>Design</h1>
  
To optimize FGF2, mutations to improve the binding affinity between the protein and its receptor were designed through rational design. PyMOL [7] was used to visually view FGF2 bound to FGFR2. Distances and angles between residues in the binding region were analyzed to find potential sites where a different amino acid could create a stronger or new bond. Literature on other FGFs was also used and the binding to their receptors analyzed to find potential amino acids which could improve the binding between the FGF2-FGFR2 complex. 10 potential mutation sites were found this way and site saturation was performed on them using FoldX [8] to identify the amino acids resulting in the lowest binding free energy and thus, the highest binding affinity. Free energy perturbation (FEP) was performed using the molecular dynamics software package Q [9] to evaluate the effects of these single point mutations in silico. Three mutations were found to make FGF2 bind with higher affinity to FGFR2: Q54K, V88I & L98M. Read more about FGF2 V88I, FGF2 L98M and FGF2 V88I+L98M on their registry pages. To learn more about the modeling process read our modeling wiki page (https://2021.igem.org/Team:Uppsala/Model). For Q54K a more energetically favourable binding can occur (figure 3).
+
To optimize FGF2, mutations to improve the binding affinity between the protein and its receptor were designed through rational design. PyMOL [7] was used to visually view FGF2 bound to FGFR2. Distances and angles between residues in the binding region were analyzed to find potential sites where a different amino acid could create a stronger or new bond. Literature on other FGFs was also used and the binding to their receptors analyzed to find potential amino acids which could improve the binding between the FGF2-FGFR2 complex. 10 potential mutation sites were found this way and site saturation was performed on them using FoldX [8] to identify the amino acids resulting in the lowest binding free energy and thus, the highest binding affinity. Free energy perturbation (FEP) was performed using the molecular dynamics software package Q [9] to evaluate the effects of these single point mutations in silico. Three mutations were found to make FGF2 bind with higher affinity to FGFR2: Q54K, V88I & L98M. Read more about <html><a href="https://parts.igem.org/Part:BBa_K3934006" target="_blank"><b>FGF2 V88I</b></a></html>, <html><a href="https://parts.igem.org/Part:BBa_K3934003" target="_blank"><b>FGF2 L98M</b></a></html> and <html><a href="https://parts.igem.org/Part:BBa_K3934005" target="_blank"><b>FGF2 Q54K+L98M</b></a></html> on their registry pages. To learn more about the modeling process read our <html><a style="padding-right:0;" href="https://2021.igem.org/Team:Uppsala/Model" target="_blank">modeling wiki page</a></html>. For Q54K a more energetically favourable binding can occur (figure 3).
  
  
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[[File:T--Uppsala--overexpression_Q54K.jpg|300px]]
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[[File:T--Uppsala--overexpression_Q54K.jpg|400px]]
  
 
<b>Figure 5.</b> SDS-PAGE gel of  FGF2 Q54K protein expressed in E. coli (DE3) cells by induction with IPTG. From the left: un-induced FGF2 Q54K, IPTG induced FGF2 Q54K, other FGF2 variant, other FGF2 variant, protein ladder. Bands corresponding to the size of FGF2 Q54K (30.8 kDa) are visible for induced cells but not for un-induced cells.
 
<b>Figure 5.</b> SDS-PAGE gel of  FGF2 Q54K protein expressed in E. coli (DE3) cells by induction with IPTG. From the left: un-induced FGF2 Q54K, IPTG induced FGF2 Q54K, other FGF2 variant, other FGF2 variant, protein ladder. Bands corresponding to the size of FGF2 Q54K (30.8 kDa) are visible for induced cells but not for un-induced cells.
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       meat,” The Good Food Institute, Feb. 09, 2020. Accessed on: Okt. 04, 2021. [Online].  
 
       meat,” The Good Food Institute, Feb. 09, 2020. Accessed on: Okt. 04, 2021. [Online].  
 
Available:    https://gfi.org/wp-content/uploads/2021/01/clean-meat-production-volume-and-medium-cost.pdf
 
Available:    https://gfi.org/wp-content/uploads/2021/01/clean-meat-production-volume-and-medium-cost.pdf
 +
<br>[7] The PyMOL Molecular Graphics System, Version 2.0 Schrödinger, LLC.
 +
<br>[8] Joost Schymkowitz, Jesper Borg, Francois Stricher, Robby Nys, Frederic Rousseau, Luis Serrano, The FoldX web server:
 +
an online force field, Nucleic Acids Research, Volume 33, Issue suppl_2, 1 July 2005, Pages W382–W388, https://doi.org/10.1093/nar/gki387
 +
<br>[9] QresFEP: An Automated Protocol for Free Energy Calculations of Protein Mutations in Q
 +
      Willem Jespers, Geir V. Isaksen, Tor A.H. Andberg, Silvana Vasile, Amber van Veen,
 +
      Johan Åqvist, Bjørn Olav Brandsdal, and Hugo Gutiérrez-de-Terán
 +
      Journal of Chemical Theory and Computation 2019 15 (10), 5461-5473
 +
      DOI: 10.1021/acs.jctc.9b00538
 
</p>
 
</p>

Latest revision as of 19:36, 20 October 2021

Bovine growth factor FGF2 designed to have increased affinity to the FGFR2 receptor

Profile

Name: FGF2 Q54K
Base Pairs: 468 bp
Origin: Escherichia Coli, synthetic
Properties: Bovine growth factor FGF2 designed to increase affinity to the FGFR2 receptor, making it induce cell proliferation. with higher efficiency.


Sequence & Features


Assembly Compatibility:
  • 10
    COMPATIBLE WITH RFC[10]
  • 12
    INCOMPATIBLE WITH RFC[12]
    Illegal NheI site found at 277
  • 21
    COMPATIBLE WITH RFC[21]
  • 23
    COMPATIBLE WITH RFC[23]
  • 25
    COMPATIBLE WITH RFC[25]
  • 1000
    COMPATIBLE WITH RFC[1000]


Usage & Biology

Fibroblast growth factor 2 (FGF2) is one of 19 known members of the mammalian FGF family, involved in morphogenesis, development, angiogenesis and wound healing [1]. It is a mitogen and was first isolated in 1974, from the bovine pituitary and in 1988 human FGF2 was described for the first time [2]. There are four different FGF receptor tyrosine kinases (FGFR), to which FGFs bind and induce cell signaling. FGF2 binds FGFR1 and FGFR2 to induce proliferation [3]. FGFR2 consists of an extracellular domain, a transmembrane helix, and a catalytic intracellular tyrosine kinase domain [1]. The extracellular domain of the receptor consists of three immunoglobulin-like domains. FGF2 binds to domain 2 (D2) and domain 3 (D3), and the linker region connects the two domains [1] (figure1).


Stillbild complex lines.png

Figure 1. Crystal structure of FGF2 (green) bound to FGFR2 (cyan). PDB: 1EV2.

When FGF2 binds to the extracellular part of the receptor it causes the receptor to dimerise with another FGF-bound FGFR2, leading to conformational changes which activates the receptor in its intracellular domain and cell signaling is initiated [4]. Through an intracellular signaling cascade gene regulation occurs in favour of cell proliferation, resulting in cell growth [4] (figure 2).


T--Uppsala--signaling.png

Figure 2. Schematic of FGF2 receptor binding cell signaling induction.

Inducing cell growth through FGF2 signaling is utilized in the field of cellular agriculture, where the growth factor is used in the serum-free growth medium for cultivating meat. Similar to in a biological system, FGF2 induces cell growth when cultivating meat in a bioreactor. However, growth media is expensive, 55-95% of the production cost of cultivated meat comes from the growth medium [5]. To make serum-free media economically feasible on an industrial scale, the medium needs to be optimized. Being one of the most important and most expensive components, FGF2 is one of the targets for improvement [6].


Design

To optimize FGF2, mutations to improve the binding affinity between the protein and its receptor were designed through rational design. PyMOL [7] was used to visually view FGF2 bound to FGFR2. Distances and angles between residues in the binding region were analyzed to find potential sites where a different amino acid could create a stronger or new bond. Literature on other FGFs was also used and the binding to their receptors analyzed to find potential amino acids which could improve the binding between the FGF2-FGFR2 complex. 10 potential mutation sites were found this way and site saturation was performed on them using FoldX [8] to identify the amino acids resulting in the lowest binding free energy and thus, the highest binding affinity. Free energy perturbation (FEP) was performed using the molecular dynamics software package Q [9] to evaluate the effects of these single point mutations in silico. Three mutations were found to make FGF2 bind with higher affinity to FGFR2: Q54K, V88I & L98M. Read more about FGF2 V88I, FGF2 L98M and FGF2 Q54K+L98M on their registry pages. To learn more about the modeling process read our modeling wiki page. For Q54K a more energetically favourable binding can occur (figure 3).


T--Uppsala--Q54K wt.pngT--Uppsala--Q54K mut.png

Figure 2. Crystal structures showing FGF2 (green) and FGFR2 (cyan) interface, the yellow dotted lines represent amino acid distances to FGFR2 D320 & T321. To the left: FGF2 Q54. To the right: Q54K mutated FGF2. PDB: 1EV2


Experimental results

Biobrick Assembly

The FGF2 biobrick part was designed inside a pUC plasmid together with the basic parts T7 promoter (BBa_J64997), Lac operator (BBa_K3599001) T7 RBS (BBa_K3257011), T7 T_phi terminator (BBa_B0016). To increase solubility of the protein during expression and purification, the FGF2 gene was fused with thioredoxin (BBa_K3934008), and to enable protein purification a 6xHis-tag (BBa_K3934015) was added. An enterokinase site (BBa_K3934016) was added to cleave off the 6xHis-tag and thioredoxin. The pUC plasmid also contains a gene for ampicillin resistance. The design was ordered from Integrated DNA Technologies (IDT).

The biological system used for biobrick assembly was E. coli DH5α competent cells. A T_phi terminator, an NdeI restriction site and an PstI restriction site were added to the 5’ end and the 3’ end of the FGF2 construct using PCR primers. The restriction sites and terminator were part of the primer overhang sequences. The PCR modified construct was treated with NdeI and PstI and ligated into a pET vector containing an IPTG inducible T7 promoter, a Lac operator, an RBS and a kanamycin resistance gene. The plasmid was re-ligated using DNA ligase and transformed into E. coli DH5α. To remove the risk of religation of the pET vector, the restriction enzyme treated pET was run through gel electrophoresis and the band corresponding to the part of the plasmid to use was extracted with gel purification. The properly assembled plasmid (figure 4) was verified using Sanger sequencing Mix2Seq Kit from Eurofins Genomics and then transformed into E. coli BL21 (DE3) pLysS competent cells from Promega which are optimized for protein expression. Transformation was also done using NEB BL21 (DE3) cells.


T--Uppsala--pET wt.png

Figure 4. Assembled biobrick vector.

PCR mutagenesis

Phosphorylated primers containing the Q54K mutation were used for PCR mutagenesis to mutate the FGF2wt gene. The amplicon contained the entire plasmid and was ligated using DNA ligase. To confirm successful mutagenesis the amplicon was sequenced using Sanger sequencing. The plasmid was then transformed into E. coli BL21 (DE3) competent cells from NEB which are good at expressing protein.

Overexpression

To overexpress the plasmid, overnight cultures of BL21 (DE3) pLysS cells containing the FGF2 plasmid were inoculated in 37 °C with 150 rpm shaking in LB medium with 50µg kanamycin until OD600 reached 0.5-0.6. To induce expression, 1 mM Isopropyl-β-D-thiogalactopyranoside (IPTG) was added to the cultures, one culture received no IPTG induction and served as a negative control. The cultures were inoculated in the same conditions as previously for 6 h. The cells were then boiled in sample buffer (125 mM Tris HCl pH 6.8, 20% glycerol, 4% SDS, 10% β-mercaptoethanol, 0.5 mg/mL bromophenol blue) to lyse the cells, and the protein expression was analysed using SDS-PAGE to confirm successful overexpression of FGF2. A 12% polyacrylamide gel containing the samples was submitted to 200 V and 0.04 A for 90 minutes. A band corresponding to the size of FGF2 Q54K (30.8 kDa) was visible on the gel, and no band was seen for the uninduced sample, which confirms successful overexpression of FGF2 Q54K (figure 5).


T--Uppsala--overexpression Q54K.jpg

Figure 5. SDS-PAGE gel of FGF2 Q54K protein expressed in E. coli (DE3) cells by induction with IPTG. From the left: un-induced FGF2 Q54K, IPTG induced FGF2 Q54K, other FGF2 variant, other FGF2 variant, protein ladder. Bands corresponding to the size of FGF2 Q54K (30.8 kDa) are visible for induced cells but not for un-induced cells.


References

[1] A. N. Plotnikov, S. R. Hubbard, J. Schlessinger, and M. Mohammadi, ‘Crystal Structures of Two FGF-FGFR Complexes Reveal the Determinants of Ligand-Receptor Specificity’, Cell, vol. 101, no. 4, pp. 413–424, May 2000, doi: 10.1016/S0092-8674(00)80851-X.
[2] L. Benington, G. Rajan, C. Locher, and L. Y. Lim, ‘Fibroblast Growth Factor 2—A Review of Stabilisation Approaches for Clinical Applications’, Pharmaceutics, vol. 12, no. 6, p. 508, Jun. 2020, doi: 10.3390/pharmaceutics12060508.
[3] W. Lim, H. Bae, F. W. Bazer, and G. Song, ‘Stimulatory effects of fibroblast growth factor 2 on proliferation and migration of uterine luminal epithelial cells during early pregnancy’, Biol. Reprod., vol. 96, no. 1, pp. 185–198, Jan. 2017, doi: 10.1095/biolreprod.116.142331.
[4] Y. Xie et al., ‘FGF/FGFR signaling in health and disease’, Signal Transduct. Target. Ther., vol. 5, no. 1, pp. 1–38, Sep. 2020, doi: 10.1038/s41392-020-00222-7.
[5] E. Swartz. “Meeting the Needs of the Cell-Based Meat Industry,” American Institute of Chemical Engineers (AIChE), Okt. 2019. Accessed on: Okt. 04, 2021. [Online]. Available: https://gfi.org/wp-content/uploads/2021/01/Cell-Based_Meat_CEP_Oct2019.pdf
[6] L. Specht. “An analysis of culture medium costs and production volumes for cultivated meat,” The Good Food Institute, Feb. 09, 2020. Accessed on: Okt. 04, 2021. [Online]. Available: https://gfi.org/wp-content/uploads/2021/01/clean-meat-production-volume-and-medium-cost.pdf
[7] The PyMOL Molecular Graphics System, Version 2.0 Schrödinger, LLC.
[8] Joost Schymkowitz, Jesper Borg, Francois Stricher, Robby Nys, Frederic Rousseau, Luis Serrano, The FoldX web server: an online force field, Nucleic Acids Research, Volume 33, Issue suppl_2, 1 July 2005, Pages W382–W388, https://doi.org/10.1093/nar/gki387
[9] QresFEP: An Automated Protocol for Free Energy Calculations of Protein Mutations in Q Willem Jespers, Geir V. Isaksen, Tor A.H. Andberg, Silvana Vasile, Amber van Veen, Johan Åqvist, Bjørn Olav Brandsdal, and Hugo Gutiérrez-de-Terán Journal of Chemical Theory and Computation 2019 15 (10), 5461-5473 DOI: 10.1021/acs.jctc.9b00538