iGEM 2023 — Team tuebingen

{% extends "layout.html" %}
{% block title %}Notebook{% endblock %}
{% block lead %}Document the dates you worked on your project. This should be a detailed account of the work done each day for your project.{% endblock %}
{% block page\_content %}

## Week 1

Winter break.

## Week 2

11.1 weekly Team meeting, Research Project ideas.

## Week 3

18.1 weekly Team meeting , Research Project ideas , division into subteams, 21.2 Project finding day

## Week 4

25.1 weekly Team meeting Formed groups to look into 4 Project ideas

## Week 5

01.2. Project finding day 2 – Selected Project

## Week 6

08.2 weekly Team meeting, Experimental Design Team starts, First social media meeting

## Week 7

15.2 weekly Team meeting First Human Practices meetings, start on Portfolio.

## Week 8

22.2 weekly Team meeting, combined social media & Design meeting

## Week 9

01.3 weekly Team meeting, 27.2 First team building meetup Asmara, 2.3 First Finance meeting, 4.3 Design meeting- brainstorms Logo & colorplate

## Week 10

08.3 weekly Team meeting, 10.3. First Drylab meeting, 7.3. Human practices meeting

## Week 11

15.3 weekly Team meeting, 16.3 Social media Meeting, Finance meeting, Drylab initial research on protein families

## Week 12

22.3 weekly Team meeting, 25.3 Team building at the ice rink, 24.4 Finance meeting, Drylab research on AA3

## Week 13

29.3 weekly Team meeting, 30.3 Design meeting, 31.3 Photoshoot for member photos, 1.5 Team building at Hills burgers, Drylab does first docking experiments

## Week 14

05.4 weekly Team meeting, Drylab enzyme research on AA3, research on AA3 mechanism

## Week 15

12.4 weekly Team meeting, 16.4 First Wetlab meeting, 15.4 Design meeting, drylab research on transplanting of FAD cofactor to alphafold structures

## Week 16

19.4 weekly Team meeting, 21.4 Design meeting- final Logo Design, 21.4 2nd Photoshoot, drylab research on transplanting of FAD cofactor to alphafold structures using machine learning

## Week 17

26.4 weekly Team meeting, 24.4 Stura approved sponsoring request, drylab reevaluates other protein families

## Week 18

03.5 weekly Team meeting, 4.5. Design meeting - start on Portfolio, 7.5 Wetlab meeting, drylab research on AA5

## Week 19

10.5 weekly Team meeting, drylab research on AA5 mechanism

## Week 20

17.5 weekly Team meeting, 15.5 start of Memberposts, 17.5 merged Design & Social Media teams, 20.3 Start of the Smart Saturday Posts, 17.5 Meeting with Prof Jansen, drylab research on AA5 known homologues and ligands

## Week 21

24.5 weekly Team meeting, 23.5 applied for Promos sponsoring, 25.5 Design&Social Media meeting, 26.5 iGEM gift box arrived, drylab research on phylogeny and structure space

## Week 22

31.5 weekly Team meeting, 29.5 Human Practices meeting, drylab redocking of experimental structures, identification of distance to copper ion as metric for catalysis

## Week 23

07.6 weekly Team meeting, 6.5 Wetlab meeting, drylab test docking experiments with Glide, refinement of phylogenetic tree

## Week 24

14.6 weekly Team meeting, 15.6 received Promega grand, 18.6 applied for impact grand, selection of docking ligand library, improvement of prescreening pipeline

## Week 25

21.6 weekly Team meeting, 20.6. Wetlab meeting, 24.6 BW Meetup, drylab molecular docking screen

## Week 26

28.6 weekly Team meeting, drylab molecular docking screen

## Week 27

05.7 weekly Team meeting, drylab identifies potential enzymes for expression

## Week 28

12.7 weekly Team meeting, 16.7. Wetlab meeting

## Week 29

19.7 weekly Team meeting, 19.7. Meeting with Prof. Nussbaum, 21.7 NMR meeting

## Week 30

26.7 weekly Team meeting, design of sequences for gene synthesis

## Week 31

02.8 weekly Team meeting

## Week 32

09.8 weekly Team meeting, 10.8 Moving Labstuff, Grand Jambore meeting, 11.8 Wetlab meeting

## Week 33

16.8 weekly Team meeting, 15.8. Finance meeting

## Week 34

23.8 weekly team meeting, 22.8 Safety instruction for the Lab, start Lab work

## Week 35

30.8 weekly Team meeting, Lab work

## Week 36

06.9 weekly Team meeting, Lab work

## Week 37

13.9 weekly Team meeting, Lab work

## Week 38

20.9 weekly Team meeting, Lab work, 23.9 Team building

## Week 39

27.9 weekly Team meeting, Work in the Lab

## Week 40

04.10 weekly Team meeting, Work in the Lab, work on wiki

## Week 41

11.10 weekly Team meeting, Lab work, work on wiki

{% endblock %}

{% extends "layout.html" %}
{% block title %}Engineering Success{% endblock %}
{% block lead %}Demonstrate engineering success in a part of your project by going through at least one iteration of the engineering design cycle.{% endblock %}
{% block page\_content %}

# General Design

Our goal in the beginning was to modify Blood Antigens A and B to 0 to alleviate blood conserve shortages. In our literature search we found a paper proved efficient conversion of A to 0.
We decided to try to convert Antigen B molecules into Antigen A, as efficient conversion from A to 0 is already possible[[1]](#cit1), and the general conversion repertoire would thus be expanded to include conversion from B to AB, B to A and AB to A, making tailored blood types possible.

For this reaction no known enzymes existed yet. Because of this we had the idea of using a screening method to identify potential candidate enzymes. As a cost and time effective screening method, we decided to employ AlphaFold 2 structures of enzymes belonging to promising enzyme families, which were screened for general ligand fit using state of the art molecular docking approaches, which we planned to validate using wetlab experiments. This in silico screening approach allowed us to start with hundreds of candidate enzyme sequences, of which no known experimental crystallographic structures were known, and only test the most promising candidates in the wetlab.

Furthermore, we decided to investigate whether a family of proteins, the so-called carbohydrate binding modules, (CBMs) could increase the affinity of enzymes to the surfaces of erythrocytes. CBMs were shown to fold independently from an enzyme's catalytic domain and can localize an enzyme to a specific molecule or surface. [[2]](#cit2).

![generalized overview scheme](https://static.igem.wiki/teams/4834/wiki/scheme-drylab1.png)

Fig.1 - generalized overview scheme

# Drylab

We designed a funnel like screening pipeline, getting rid of as many enzymes as early as possible in the screening, as the complexity of employed algorithm steadily increases. This process consisted of multiple design cycles gradually expanding the pipeline from a brute force search of the structural space to a pre screening pipeline that allowed to compare more sequences with less compute time in the end.

### Build of screening pipeline

First, suitable enzyme families, that were in theory capable of modifying the correct hydroxy group were researched in literature. For this, multiple families of monooxygenases were evaluated on the criteria of known characterized homologues, their likelihood of ligand binding, the ease of purification, known homologue structures as a control for AlphaFold structures and docking experiments, as well as the complexity of binding pocket and known, similar, ligands.

The following enzyme families were considered on the above mentioned criteria:

[CAZY Family AA5](http://www.cazy.org/AA5.html), which are copper radical oxidases, that are known to oxidize sugar substrates, and even more specifically the 6th hydroxy group of galactose.

[CAZY Family AA3](http://www.cazy.org/AA3.html), which are flavoprotein oxidoreductases. They are known to oxidize sugar substrates, for example the second hydroxy group of glucose.

[CAZY Family AA10](http://www.cazy.org/AA10.html), which are copper lytic monooxygenases. As these enzymes are catalyzing oxidative cleavages of polysaccharides, this family was ruled out very early in our research.

Initially, Family AA3 was selected due to one enzyme, called Pyranose 2 Oxidase, which according to literature, is capable of catalyzing reactions involving certain pyranoses and disaccharides, making this family a promising one for screening of enyzmes specific to terminal galactose containing glycans. Other criteria were favorable as well, such as known experimental structures, catalytic mechanism and other characterized enzmyes in this family.
However, the flavin cofactor is quite large and hard to model accurately, as AlphaFold is only capable of modelling protein structures without any cofactors. After attempts to transplant the cofactor from known experimental structures proved too work intensive for larger scale screening, we decided to start another design cycle and rebuild the pipeline using the initially discarded Family AA5, due to its very high structural conservation, copper ion cofactor that is comparatively easy to model and insert, as well as its known catalytic mechanism, number of characterized enzymes in the family, and the number of experimentally solved structures in this family.

A phylogenetic tree of the Family AA5 was constructed using protein sequences from Cazy and UniProt, especially focusing on bacterial homologues for ease of expression in E.coli.
Conserved domains were used to identify clades of potentially different function. This was further validated using structural alignments of the enzyme structures, in addition to the sequence alignment used for construction of the phylogenetic tree. Samples from each clade of different structure were selected for further analysis using Molecular docking.

Structures were docked against a library of selected blood glycan fragments, ranging from mono- to tetrasaccharides. This served to test, if docking behavior observed in monosaccharides could be generalized to larger fragments as well, thereby giving a first indication of the required size of our glycan models. It was found, that if the larger fragment was capable of being docked well to the enyzme, so were the monosaccharides of the terminal fragment sugar and that there was little difference in binding pose between terminal fragment sugar and its corresponding monosaccharide.
This screening library contained known substrates of control enzyme structures, like galactose as a known substrate of the enyzme galactose oxidase and glucose which is known to be virtually not acted upon by galactose oxidase.
We screened against a collection of different known blood antigens to ensure specificity of our selected enzymes. We selected enzymes based on the computed euclidian distance of docked ligands hydroxy groups to the enzymes active site, as it was observed that for a comparison of galactose and glucose docked to GOX, that not binding strength determined by molecular mechanics, was an indicator of catalytic activity on this substrate, but instead distance of the docked ligand to the active site. As the mechanism for this family proposes a covalent bond of the hydroxy group to the copper, we modeled our distance calculations on coper oxygen bonds, a distance between 2 and 3 Angstroms, with a lower distance being better.

### Testing

The phylogenetic tree was validated using known biological information like conserved domains, as well as information obtained from literature research.
Clades were designated and validated using structural alignment of the enzymes.
AlphaFold 2 Structures were tested using experimentally solved crystal structures of GlxA and GOX by performing a structural alignment of predicted and ground truth structure.
Molecular docking was validated using known structures and ligands and performing redocking on these structures.
The next step in the design cycle is testing our predictions in the wetlab and refining our molecular docking predictions based on wetlab results.

### Learn

During this process, we expanded the screening pipeline to include as much prior knowledge from different sources as possible. Initially, the pipeline did not include any preselection steps, and instead we tried to brute force dock all structures in the database.
This would have been a more exhaustive way to explore the entire structural space, but it would also have taken a long time and therefore we wouldn’t have been able to explore as much of the structural space as we wanted in the time we had. Therefore, we decided to construct a preselection pipeline to more efficiently search the structural space instead. At first , this led to the construction of phylogenetic trees and then the selection of clades of hypothesized similar function.

We realized that, at that point, we would be able to screen a lot more structures than initially expected, therefore we expanded the database using more distantly related homologues. We decided to start a new design cycle to build, test and learn from the expanded database.
After conversations with our advisor Dr. Thales Kronenberger, we decided to switch our docking software from Autodock to Glide, as Autodock is not capable of docking involving metal ions. Because our enzymes are metalloenzymes with an active center copper ion, this could have lead led to inaccurate docking results.
This allowed for refinement of the docking using the copper cofactor in the simulations, which was done by transplantation of copper ions into the AlphaFold structure using homology modeling and manual review for each docked structure.

The next design cycle would be to incorporate the results of wetlab experiments. If the wetlab results showed that the predictions were accurate, then a next step could be to improve the system for time efficiency by training a machine learning algorithm on predicting which enzyme can bind which ligand. However, if the wetlab experiments proved the predictions as inaccurate, a next step could be to refine the docking using flexible sidechains or to relax the structures using molecular dynamics.

# Wetlab

### Design of Enzymes

The sequences for expression were designed based on structures selected from our drylab screening. DNA sequences were codon optimized for E. coli and synthesized by Twist Bioscience.
Plasmids containing the sequences of a control enzyme (GlxA, an AA5 Family enzyme from Streptomyces lividans with soluble and membrane anchor containing sequence) were supplied by Dr. Xiaobo Zhong from the University of Leiden and Professor Jonathan Worrall .from the University of Essex.

The CBM domain was selected based on literature and was adapted from the sequence reported in [[3]](#cit3), in which the authors found that the domain bound to blood antigen B. A fusion protein of this domain and a GFP Tag was designed, the sequence was codon optimized for expression in e.coli and synthesized by commercial supplier IDT.

### Build

The first step of our wetlab building stage was to assemble the plasmids containing our selected sequences.
First, we transformed the empty plasmid into Stellar E. coli, purified the plasmid and linearized the plasmid using PCR. Then we amplified the linearized gene fragments of our inserts using PCR, creating the required Gibson overhangs.
For assembly we decided to use Gibson Assembly due to its high probability of success and restriction site independent method of assembly. The assembled plasmids were transformed into Stellar E. coli, from which plasmids were purified and transformed into Nova blue E. coli for expression.

### Test

After transformation, we screened the colonies for inserts using Colony PCR. From the positive colonies, a few were sent for sanger sequencing to confirm that the insert sequence was correct and free of mutations. Unfortunately, we only had a very limited amount of time to purify and test our enzymes, as we had problems during our wetlab building phase and only managed to perform one purification and did not have enough time to troubleshoot the purification.

For the CBM domain gene construct, GFP fluorescence was tested on the expressing E.coli using a fluorescence microscope without purification of the protein.

The next steps in the testing phase were to express and purify the enzyme, and afterwards to test the oxidase activity on different ligands using a peroxidase assay. Due to time constraints we only managed to test it on Galactose. Protein purification was done using a His6¬ tag and a Ni-NTA based resin. For this, the gene construct was induced using IPTG and lysis was performed using sonification. Protein concentration was checked with a Bradford assay and the process of the purification was documented with an SDS Page. As the protein was predicted to produce hydrogen peroxide during catalysis, based on homologues, we expected to measure peroxide production over time after the addition of multiple predicted substrates as a proxy for catalytic efficiency. We were planning to measure hydrogen peroxide production using a peroxidase assay. But only managed to perform the assay once.

### Learn

Several setbacks in the wetlab have shown us what to improve. First, we had issues with availability of supervision and lab space, which meant that we started quite late in the year. This coupled with further issues during the Wetlab, we learned that everything takes a lot longer than originally planned, especially experiments.

We had a lot of issues with amplification of the linearized plasmid using Pfu Polymerase, as this polymerase tended to produce wrong fragments. We tried a range of annealing temperatures using gradient PCR, as well as a buffer for high GC sequences. When this did not work, we tried different primers, suspecting unspecific primer binding to be the issue. After none of the above mentioned changes to the PCR reaction worked, we next tried the reaction using Q5 Polymerase, which in the end produced the correct fragment on the first try. From this we have learned a lot about PCR troubleshooting techniques and that the selection of the correct Polymerase can be crucial to PCR success.

Unfortunately, we were only barely able to fully complete one engineering cycle in the wetlab, and did not get a chance to improve on the experiments or figure mistakes out. The next engineering cycle would depend on the results of the peroxidase assay done multiple times and would most likely start with another drylab engineering cycle of improving the predictions of our screening approach.

### References

[1] Rahfeld, P., Sim, L., Moon, H. et al. An enzymatic pathway in the human gut microbiome that converts A to universal O type blood. Nat Microbiol 4, 1475 - 1485 (2019).

[2] Armenta, S., Moreno-Mendieta, S., Sánchez-Cuapio, Z., Sánchez, S. and Rodríguez-Sanoja, R. (2017), Advances in molecular engineering of carbohydrate-binding modules. Proteins, 85: 1602-1617.

[3] Takura Wakinaka, Masashi Kiyohara, Shin Kurihara, Akiko Hirata, Thida Chaiwangsri, Takayuki Ohnuma, Tamo Fukamizo, Takane Katayama, Hisashi Ashida, Kenji Yamamoto, Bifidobacterial α-galactosidase with unique carbohydrate-binding module specifically acts on blood group B antigen, Glycobiology, Volume 23, Issue 2, February 2013, Pages 232–240

{% endblock %}

{% extends "layout.html" %}
{% block title %}Experiments{% endblock %}
{% block lead %}Describe the research, experiments, and protocols you used in your iGEM project.{% endblock %}
{% block page\_content %}

## DNA Transformation

1. Thaw all reagents completly on ice
2. Add 1 ul of ligation reaction to thawed competent cells (ecoli NovaBlue) and gently mix by tapping tube
3. Incubate on ice for 30 min
4. Heatshock for 45s at 42 C in Heatblock
5. Incubate 2 min on ice
6. Fill to 500 ul with LB medium
7. Incubate at 37 C and shake at 250 rpm for 1 h
8. EITHER Transfer into more LB medium and let grow overnight at 37 C while shaking
9. OR spread on selection plate and incubate overnight at 37 C

## Plasmid Isolation with Plasmid Miniprep kit (Monarch NEB)

1. Pellet 1–5 ml (not to exceed 15 OD units) bacterial culture by centrifugation for 30 seconds. Discard supernatant. 1.5 ml of culture is sufficient for most applications. Ensure cultures are not overgrown (12-16 hours is ideal).
2. Resuspend pellet in 200 μl Plasmid Resuspension Buffer (B1) . Vortex or pipet to ensure cells are completely resuspended. There should be no visible clumps.
3. Add 200 μl Plasmid Lysis Buffer (B2) , gently invert tube 5–6 times, and incubate at room temperature for 1 minute. Color should change to dark pink, and solution will become transparent and viscous. Do not vortex.
4. Add 400 μl of Plasmid Neutralization Buffer (B3) , gently invert tube until neutralized, and incubate at room temperature for 2 minutes. Sample is neutralized when color is uniformly yellow and precipitate forms. Do not vortex.
5. Centrifuge lysate for 2–5 minutes. For best results, and especially for culture volumes > 1 ml, we recommend a 5 minute spin to ensure efficient RNA removal by RNase A. Pellet should be compact; spin longer if needed. continued on back → For a detailed protocol or to download the full manual, visit www.neb.com/T1010. Monarch® Plasmid Miniprep Kit Protocol Card
6. Carefully transfer supernatant to the spin column and centrifuge for 1 minute. Discard flow-through.
7. Re-insert column in the collection tube and add 200 μl of Plasmid Wash Buffer 1. Centrifuge for 1 minute. Discarding the flow-through is optional.
8. Add 400 μl of Plasmid Wash Buffer 2 and centrifuge for 1 minute.
9. Transfer column to a clean 1.5 ml microfuge tube. Use care to ensure that the tip of the column does not come into contact with the flow-through. If there is any doubt, re-spin the column for 1 minute.
10. Add ≥ 30 μl DNA Elution Buffer to the center of the matrix. Wait for 1 minute, then spin for 1 minute to elute DNA. Nucleasefree water (pH 7-8.5) can also be used to elute the DNA. Yield may slightly increase if a larger volume of DNA Elution Buffer is used, but the DNA will be less concentrated. For larger size DNA, (≥ 10 kb), heating the elution buffer to 50°C prior to use can improve yield.

## Glycerol Stock Preparation

1. Prepare a liquid culture of the bacteria by incubating a bacterial sample in 5-10 ml LB Medium overnight
2. Dilute Glycerol with distilled water to creat a 50% Glycerol solution
3. Transfer 750 ul of the glycerol solution into a microfuge tube
4. Add 750 ul of bacterial culture to microfuge tube
5. Close lid and mix gently
6. Freeze at –80 C

## Cast & Run electrophoresis gel

1 L 50x TAE Buffer:

1. Tris base 2M (242 g)
2. Acetic acid 1M (57 ml)
3. EDTA 0.05 M (100 ml 0.5 M)
4. Fill up to 1 L with MilliQ H2O

Dilute 50x TAE to 1x TAE for use.

1. Cast 50 ml 1% agarose gel: (1g agarose, fill up to 100 ml with 1x TAE buffer)
2. Load gel, including at least one lane for a DNA ladder
3. Run gel at 120V for 45 min

## DNA Gel Extraction

Gel extraction using QIAgen DNA Gel extraction kit, https://www.qiagen.com/us/resources/resourcedetail?id=a72e2c07-7816-436f-b920-98a0ede5159a⟨=en

## Q5 Polymerase DNA amplification using PCR

PCR mix:

| Component | Volume | Final Conc |
| --- | --- | --- |
| 5X Q5 Reaction Buffer (NEB) | 10 µl | 1X |
| dNTP Mix, 10 mM each | 1 µl | 0.2 mM each dNTP |
| Fwd primer | 2.5 µl | 0.5 µM |
| Rev primer | 2.5 µl | 0.5 µM |
| Q5® High-Fidelity DNA Polymerase (NEB) | 0.5 µl | 0,02 u |
| DNA to be amplified | 1 µl | < 1,000 ng |
| ddH2O | 32.5 µl | 32.5 µl |
| Total | 50 µl | - |

PCR program:

| Step | Temp/°C | Duration/sec | n repeats |
| --- | --- | --- | --- |
| Denaturation | 98 | 30 | 1 |
| Denaturation | 98 | 10 | 30 |
| Annealing | depends on primers | 30 | 30 |
| Extension | 72 | 120 | 30 |
| Extension | 72 | 120 | 1 |
| Cooling | 7 | 120 | 1 |

## Colony PCR

Q5 reaction mix

| Component | Volume | Final Conc |
| --- | --- | --- |
| 5X Q5 Reaction Buffer (NEB) | 10 µl | 1X |
| dNTP Mix, 10 mM each | 1 µl | 0.2 mM each dNTP |
| Fwd primer | 2.5 µl | 0.5 µM |
| Rev primer | 2.5 µl | 0.5 µM |
| Q5® High-Fidelity DNA Polymerase (NEB) | 0.5 µl | 0,02 u |
| ddH2O | 33.5 µl | 33.5 µl |
| Total | 50 µl | - |

1. Mix reaction mix for each colony to be analyzed
2. Pick colony using disposable pipette tip
3. Stab pipette tip onto replica plate and note number
4. Mix pipette tip in PCR mix
5. Run PCR (program see below)
6. Analyze PCR using agarose gel to test if insert of expected size was amplified
7. Incubate replica plate overnight

PCR program:

| Step | Temp/°C | Duration/sec | n repeats |
| --- | --- | --- | --- |
| Denaturation | 94 | 300 | 1 |
| Denaturation | 94 | 60 | 34 |
| Annealing | depends on primers | 30 | 34 |
| Extension | 72 | 60 | 34 |
| Extension | 72 | 60 | 1 |
| Cooling | 7 | 120 | 1 |

## Protein Purification

1. Inoculate liquid overnight cultures in 500ml LB Medium (+Amp), for the negative control Kanamycin was added instead of Ampicillin.
2. Let grow at 37°C and shaking until an OD600 of about 0,6 is reached (2-3 h)
3. Take a 1 ml Sample before induction
4. Induce expression with 1mM IPTG
5. Let Cultures incubate at 25 °C overnight
6. Cells were centrifuged for 20 min at 4 °C, supernatant was discarded afterwards
7. resuspend in a 50mM Tris/HCl, 500 mM NaCl (ph 8) Buffer A with DNase and Protein inhibitor
8. Cells were lysed using a Sonicator for 12 min each
9. Lysate was centrifuged at 4°C for 20 min
10. Lysate was filtered using a Syringe

Purification with Ni Column

1. Add 10 ml ddH20 to column
2. Add 10 ml Wash Buffer (Buffer A+ 20 mM Imidazol)
3. Add 25 ml Celllysate, collect 1 ml Flowthrough for analysis
4. Add 15 ml Wash Buffer
5. 14 x 1 ml Elutionbuffer (Buffer A + 500 mM Imidazol), catch elute in 1.5 ml reaction tubes
6. Add 15 ml Wash Buffer
7. To rejuvinate Column:
8. Add 15 ml 50 mM EDTA
9. Add 15 ml Wash Buffer
10. Add 15ml 0.1M NiSo4
11. Add 10 ml wash buffer
12. Add 15ml 20% EtOH

## Peroxidase Assay (ROS Glo System, Promega)

1. Add ≤80µl of Enzyme Reaction Mix per well to a white opaque 96-well plate. Note: Less than 80µl may be applied to accommodate an added volume of test compounds (e.g., 70µl enzyme reaction mix plus 10µl of test compound).
2. Add test compounds (such as drugs or other small molecules or vehicle) to controls without a test compound (e.g., DMSO in same concentration as present in wells with test compounds).
3. Incubate enzyme reaction at desired temperature (e.g., 37°C or room temperature) for the desired length of time. Note: Various methods of initiating and terminating enzyme reactions may be employed. For example, reactions may be initiated by addition of an essential reaction component and stopped by addition of an enzyme inhibitor. The final volume of the reaction should be 80µl to allow for addition of H2 O2 Substrate solution.
4. After the enzyme reaction incubation, add 20µl of H2 O2 Substrate solution and mix.
5. Incubate the reaction for 60 minutes at room temperature (approximately 22°C).
6. Add 100µl ROS-Glo™ Detection Solution
7. Incubate 20 minutes at room temperature.
8. Read relative luminescent values (RLU) using a plate reading luminometer.

## Bradford assay

1. Prepare dilution sequences of the Protein Fraktion and one control group with BSA
   BSA Dilutionsequence in NaCl, Tris Puffer: 1 mg/ml, 0,5 mg/ml, 0,25 mg/ml, 0,125 mg/ml, 0,0625 mg/ml, 0 mg/ml
   Fraktion Dilutionsequence: 1:1 diluted, 1:5 diluted, 1:10 diluted, 1:100 diluted
2. Add 196 μl of Bradford Reagent and 4 μl of Sample to a well Plate
3. Measure with a spectrometer and use control as reference

## SDS-Page

Materials- pre-made 10% SDS gel
- Protein Marker
- 1x SDS runnning buffer
- electrophoresis chamber
- Coomassie Staining colution
Procedure

1. add buffer to sample
2. heatshock at 95°C for 10 min
3. load gel with samples and protein marker and run at 150 V for 60 min
4. rinse gel with VE water, then incubated with Coomassie Staining colution while shaking
5. rinse the gel twice with VE water

{% endblock %}

{% extends "layout.html" %}
{% block title %}Results{% endblock %}
{% block lead %}You can describe the results of your project and your future plans here.{% endblock %}
{% block page\_content %}

# Results iGEM 2023 Tübingen

In the face of tackling the blood shortage crisis, we were able to contribute in the following ways. Via events and social media, we educated people on the problems of blood shortage the world is currently facing. We presented not just solutions to help solve this problem on a big scale, such as converting blood types to the universal O-antigen blood, but also showed how every single person can contribute to solving this shortage.
We facilitated a bioinformatics-based workflow to screen for and assist in designing novel enzymes that in theory can specifically modify ligands, such as saccharides, on antigens or other proteins. We demonstrated this by designing candidate enzymes that specifically convert a galactose/ fucose residue to a keto-galactose residue on the type B blood antigen using publicly available software and scripts. This workflow has the potential to support researchers in their design of substrate modifying enzymes for pharmaceutical purposes. However, we feel obliged to note that this workflow currently lacks the proper wetlab-based proof of concept. To prove or dispute this workflow, we challenge ourselves as well as other scientists to make use of this toolchain and computational foundation we have provided and report on its accuracy and usefulness.

### Drylab

We chose AA5 with the type enzyme Galactose Oxidase (GOX) as family to search for a suitable enzyme that could be capable of catalyzing the oxidation of blood antigen B, due to the number of well characterized members, solved structures, theknown reaction mechanism, as well as its simple active site.

![GOX Mechanism](https://static.igem.wiki/teams/4834/wiki/cro-mechanism.png)

Fig.1 - mechanism of GOX, from https://www.cazypedia.org/index.php/File:CRO\_mechanism.png (CC BY 4.0)

The GOX mechanism suggests that the substrate and active site copper share a covalent bond as intermediate, suggesting a minimal distance to the copper ion as suitable parameter for predicting if an enzyme will be active on a given docked ligand. This mechanism also suggests that it is possible to catalyze any sugar hydroxy group given, that it is capable of forming a copper covalent bond.

In order to analyze if molecular docking is a meaningful model for our analyses of finding enzymes that could potentially act on specific ligands, we tested docking the known substrate galactose to an experimentally solved structure of GOX, as well as glucose, which was known not to be a substrate of GOX. This docking was performed using Glide (as part of maestro).

![GOX docked with Galactose](https://static.igem.wiki/teams/4834/wiki/1gog-gal.png)

Fig.2 - Galactose docked to GOX

Docking of galactose to GOX showed that Glide docked the ligand inside the active site, therefore suggesting that docking potentially is a biologically meaningful model.

![GOX docked with Glucose](https://static.igem.wiki/teams/4834/wiki/1gog-gluc.png)

Fig.3 - Glucose docked to GOX

Docking of glucose to GOX showed that Glide docked the ligand inside the active site, but with a worse fit compared to galactose, approximately 0.4 Ångström further away from the copper ion, suggesting fit into the active site to be worse for glucose.

We also investigated if modelling ligand binding strength was a suitable model for prediction of ligand activity for GOX using molecular mechanics with generalised Born and surface area solvation (MMGBSA) using Maestro.

![MMGBSA Simulation results on Galactose and Glucose bound to GOX](https://static.igem.wiki/teams/4834/wiki/fig-mmgbsa.png)

Fig.4 - MMGBSA Simulation results on Galactose and Glucose bound to GOX

Using MMGBSA simulations of glucose and galactose we were unable to show a difference in binding energy of glucose and galactose to GOX, although glucose has a very high variance of binding energy between docked poses (10 Simulations per ligand, ligands were first docked using Glide and docked poses were then scored on binding energy using MMGBSA).

As GOX is effectively inactive with glucose as the substrate, but turns over Galactose [[1]](#cit1), this is suggesting that molecular mechanics predicting ligand binding strength is either not a biologically meaningful model, or binding strength is less relevant to predicting ligand activity than active site fit, and that instead active site fit and distance to the copper ion is a more meaningful metric to judge likelihood of a ligand being able to be a substrate of an AA5 family enzyme.

In order to analyze the structural, as well as the presumed functional diversity of our enzyme database, which would allow us to search the structural space easier by excluding similar enzymes, we integrated data from structural alignments of generated alphafold structures with a phylogenetic tree (phyml), as well as data on conserved domains found in the enzyme sequences (CDD/SPARCLE).

![Hierarchical Clustering Diagram of Root Mean Square Deviation of Alphafold structures computed from pairwise RMSD](https://static.igem.wiki/teams/4834/wiki/hierarchical-clustering.png)

Fig.5 - Hierarchical Clustering Diagram of Root Mean Square Deviation of Alphafold structures computed from pairwise RMSD

![Phylogenetic Tree of AA5](https://static.igem.wiki/teams/4834/wiki/final-tree.png)

Fig.6 - Phylogenetic tree of AA5 bacterial homologues with added schema of conserved domains (blue (kelch motif), yellow (C-terminal Early set domain associated with the catalytic domain of galactose oxidase), brown (Carbohydrate binding module families), aswell as colored in using by the colors and groups derived by hierarchical clustering as described above.

The phylogenetic tree of AA5 shows clades. These clades are comprised of enzymes with different conserved domains and different active site geometries of the AlphaFold structures of it s members, of which derived groups match up with observed clades in the phylogenetic tree. This suggests difference in function, which is supported by the differing conserved domains, which are most likely due to differing functional interactions, roles or substrates of the enzymes, as well as differing enzyme active site geometry, all of which in this case suggests a difference in ligands that can potentially be catalyzed by the enzyme.
Enzymes A0A0A1TMB5 (TMB5) and A0A178E5X4 (E5X4), belonging to the clade1 (dark green), have docking results of the tetrasaccharide model of Antigen B with < 3 Å distance (OH 3 for TMB5) to the copper ion, which, in theory means that a covalent bond might be possible.

![TMB5 active site with Antigen B](https://static.igem.wiki/teams/4834/wiki/tmb5-b.png)

Fig.7 - Active site of TMB5 with docked antigen B tetrasaccharide.

TMB5 has a low distance of the second (2.91 Å) and third (2.89 Å) hydroxy group of the terminal galactose to the active site and we wanted to see if there were any activity, how selective the activity was for each of these groups.

![E5X4 active site with Antigen B](https://static.igem.wiki/teams/4834/wiki/e5x4-b.png)

Fig.8 - E5X4 active site with docked antigen B tetrasaccharide.

E5X4 has a small distance (2.69 Å) of the fith hydroxy group of the fucose to the copper ion, which is also an interesting modification that we wanted to explore along TMB5, for potential other modifications of fucose containing blood antigens, for example glycan tagging.

### Wetlab

In our experimentes we aimed to assemble our final plasmid via gibbson assembly, transform the plasmid into E. coli, induce and purify the protein for use in a peroxidase assay, in which we wanted to test the amount of peroxide production on different substrates. Peroxide is a sideproduct of the reaction these enzymes catalyze and can therefore be used to test for activity of the enzyme.

### DNA fragment amplification (PCR)

The gene fragments were synthesized by a commercial supplier (twist bioscience and IDT). Gene fragments were first amplified by PCR using taq polymerase.
The Plasmid, which we used for our cloning was pXZ11, which was a gift by Dr. Xiaobo Zhong. This plasmid was also amplified by PCR using Q5 polymerase to intoduce Gibbson overhangs and linearized the plasmid for gibbson assembly.

![Gel PCR Inserts](https://static.igem.wiki/teams/4834/wiki/insert-pcr.png)

Fig.9 - Amplified DNA fragments recieved from twist bioscience of our inserts. Both fragments (TMB5 left, E5X4 right) were successfully amplified and are approximately 1.7 kb long.

![Gel PCR Inserts](https://static.igem.wiki/teams/4834/wiki/plasmid.png)

Fig.10 - Amplified linearized plasmid with gibbson overhangs added by PCR. All lanes contain the same product, amplified plasmid pXZ11.

### Plasmid assembly

The Plasmid was assembled using Gibson assembly. Two plasmids were assembled, one with TMB5 as the insert, one with E5X4 as the insert. Both sequences contained an added C terminal His­6- tag.

### Transformation into E.coli and screening

The assembled plasmids were transformed into stellar E. coli ,due to their outstanding transformation efficacy. The colonies were screened for inserts using colony PCR.
![Gel Colony PCR TMB5](https://static.igem.wiki/teams/4834/wiki/colony-tmb5.png)

Fig.11 - Colony PCR of 9 colonies of insert TMB5, which is approximately 1.5 kb long. All colonies except 3, 5 and 7 contained the insert.

![Gel Colony PCR TMB5](https://static.igem.wiki/teams/4834/wiki/colony-e5x4.png)

Fig.12 - Colony PCR of 9 colonies of insert E5X4, which is approximately 1.5 kb long. All colonies except for 7 contained the insert

The Plasmids were isolated via miniprep and sequenced using sanger sequencing.

![Gel Colony PCR TMB5](https://static.igem.wiki/teams/4834/wiki/sds-page.jpg)

Fig.13 - SDS-Page of samples taken during the protein purification test
vI – before induction with IFPG
nI after induction with IFPG
Lysate - after Sonification
FT – Flow through
F1&2 – Fraction 1&2
10 & 20 referes to the GFP taged fusion proteins synthesized by IDT
T 1,9 referes to Tmb5-1, the Plasmid that contains our target protein. The target Protein has a molecular weight of 52,8 kDa (marked yellow)

The target protein has a molecular weight of 52,8 kDa and should be visible in the area marked yellow in the picture. From the picture it is visible that a protein with the right molecular mass was present until the eluation, but disappears here. Furthermore there are too many proteins visible in the eluation, leading to the conclusion that the purification failed. There is no protein present in the other fractions. It is unknown why the purification failed and due to time constraints not possible to repeat the experiment, leading to an inconclusive result. the next step would be to troubleshoot the protein purification and attempt it again.

### Conclusion

We have developed an easy to use approach for searching a large space of protein structures for the purposes of molecular docking, which in future might prove helpful for other projects and teams looking to search a wide space of possible proteins. We have also successfully employed molecular docking to find plausible candidate enzymes that allowed us to formulate a hypothesis about their reactivity and ligand specificity, which, however, we were unable to fully test in the wetlab in time, although we were able to produce all the needed materials for such a test, which will hopefully be performed a few weeks after wiki freeze and then finally test our hypothesis, allowing us to either finetune and expand our molecular docking based modelling approaches, or allows us to start anew in the next design cycle and come up with a modelling approach that better fits biological reality.

### References

[1] ChemBioChem2002 WILEY-VCH-Verlag GmbH 1439-4227/02/03/08 Modification of Galactose Oxidase to Introduce Glucose 6-Oxidase Activity Lianhong Sun,Thomas Bulter,Miguel Alcalde,Ioanna P. Petrounia and Frances H. Arnold

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