iGEM 2024 — Team nyu-new-york

{% extends "layout.html" %}
{% block title %}Notebook{% endblock %}
{% block lead %}Hi all! Welcome to our Notebook Page. Below is an interactive google calendar where we've added events for all the big tasks we've worked on!{% endblock %}
{% block page\_content %}

{% endblock %}

{% extends "layout.html" %}
{% block title %}Engineering Success{% endblock %}
{% block lead %}{% endblock %}
{% block page\_content %}

## Follow us Through the Engineering Design Cycle!

---

![design cycle](https://static.igem.wiki/teams/5098/engineering-page/edp-model.gif)

Source: Catapult Learning

### Define:

The issue we are addressing is that there are not enough cheap, at-home iron level testing kits that don’t involve drawing blood.

### Ask:

* Approximately 25% of the world population is iron deficient (StatPearls)

+ Women and children are more susceptible and have less access to healthcare on a global scale

* Many people might not have funds or insurance, blood drawing is dangerous for people with anemia, and the current devices are hard-to-use, making them less accessible and reliable
* Many countries have political and human rights issues that prevent women, who are more likely to suffer from anemia, from having easy access to a doctor
* People in lower socioeconomic classes are often the ones most affected by undiagnosed and untreated anemia as they are least likely to test their iron levels due to lack of access to insurance or clinics

### Imagine:

* **Goal:** cheap, electrical, biosensor that detects one specific iron level marker found in saliva.
* **Short Term:** start off with one marker and develop the test to be more accurate
* **Long Term:** detect more iron level markers depending on the data supporting our ability to do so

### Plan:

Our plan is to:

* Find this target marker - **done** - it’s salivary ferritin!
* Gain understanding of different biosensor designs - **in progress**

+ There is so much to learn about biosensors! One of our captains (also wet lab lead) is taking a course right now on biosensors and she’s learning so much from it!

* Find aptamers capable of binding to our marker (ferritin) - **done**

+ After much literature review and computational docking (will go into detail below), we found two!!

* Survey the public to get a better idea of this project’s importance - **in progress**

+ We are trying our best to reach out to more women, people of color, and people from lower socioeconomic backgrounds as their perspective is especially important to making our biosensor accessible.

* Test the aptamers to see what (binding, detection, selectivity, etc) works best - **in progress**

+ We are currently doing direct biotin-streptavidin ELISA to test the aptamers against native ferritin samples.

* Develop biosensor design - **in progress**

+ We can confirm that our goal to make the biosensor cheaper is to make it arduino based.
+ We will potentially be doing a fluorescent signal for detection as the devices necessary to do this are inexpensive.
+ We will be using optical methods to cut out background noise and detect the fluorescent signal

* CAD Modelling the biosensor - **in progress**
* Building the biosensor and testing the aptamer’s stability within in - **in progress**

### Prototype:

Our prototypes include the two aptamers (one peptide, one DNA) we designed through literature review and computational docking (more below on this). Our biosensor prototype is still a work in progress as while we have a hardware casing design and plan for use of optical methods, the hardware is partially dependent on the stability of whichever aptamer we end up selecting after testing. Therefore, our final hardware design is dependent on finalized wet lab data.

### Test:

* Before finalizing our aptamer designs and ordering them, we tested their binding affinity to salivary ferritin using computational docking. After confirming that their binding affinities were reasonably high, we are now testing the physical aptamers against native ferritin (liver specifically - has similar composition to salivary ferritin) through ELISA and DNA shift assay. More details on this are provided below and on our experiments and results pages!
* As our biosensor is still being researched, we are not yet at this prototype’s testing stage. Our tests will mainly consist of usability, how stable the aptamer is within our biosensor, and the accuracy of the data produced.
* We will be testing our hardware portion once we have finalized wet lab data to base it off of. For now, we will continue prototyping the most effective method to pack the components into the casing and creating the necessary code to convert fluorescent signals to readable outputs.

### Improve:

We will continue to improve our overall project’s design as we get more results from our aptamer testing, feedback from our surveying, and later on, results from our biosensor testing. We recognize that a project like this is definitely not one that can be finished quickly (especially since we are unable to commit to it 24/7). Creating more accessible diagnostics is a strong cause that our team is passionate about, so we hope to reach a point where we can hand off the project to another research team at our school to truly take to the next level.

{% endblock %}

{% extends "layout.html" %}
{% block title %}Experiments{% endblock %}
{% block lead %}Below is a detailed review of our protocols used for ELISA, DNA shift assay, and computational docking.{% endblock %}
{% block page\_content %}

# **Menu:**

---

* [ELISA](#ELISA)
* [Computational Docking](#CompDock)
* [DNA Shift Assay](#DNA)

# **ELISA:**

---

**Experiment:** Create an Enzyme-Linked Immunosorbent Assay (ELISA) to measure concentration of ferritin using the peptide ligand or DNA aptamer that we found through literature review and computational docking. Find out if peptide ligand/DNA aptamer successfully binds to ferritin. Find out whether peptide or DNA binds more successfully to ferritin.

## **ELISA Protocol Overview:**

---

1. Ferritin is added to 96 well plates at different concentrations.

2. The aptamer (DNA or peptide), tagged with biotin, is added so that it can bind to ferritin.

3. A small protein called Streptavidin conjugated with an HRP enzyme is added and the streptavidin binds to biotin.

4. A substrate is then added to react with the HRP enzyme and produce a chemiluminescent signal proportional to the concentration of ferritin in the well.

5. A plate reader then reads the absorbance of the signal produced by applying a 450nm wavelength, and the ferritin concentration is determined based on a standard curve of absorbance vs concentration generated from standard (known concentrations) ferritin samples.

![elisa-experiment-steps](https://static.igem.wiki/teams/4820/wiki/experiments-page-photos/elisa-experiment-steps.png)

Visual of ELISA Steps Listed Above Made Using Biorender

## **Trial 1:**

---

* We ran two plates.
* Used commercially available ferritin ELISA kit for reagents and standards (to create standard curve).
* ELISA kit contained recombinant ferritin to use as standard and biotinylated rabbit anti-ferritin antibody
* We tested the peptide on our samples in the ELISA (not the standards).
* We used native ferritin for our samples because ferritin in human saliva is native and not recombinant.
* Plate 1

+ Standards: Recombinant ferritin, antibody added.
+ Samples: Native ferritin, peptide added.

* Plate 2:

+ Standards: Native ferritin, antibody added.
+ Samples: Native ferritin, peptide added.

## **Plate Map:**

---

* Ferritin added at concentrations in ng/mL shown below.
* Blank = no ferritin added, control (should result in absorbance reading of 0).

![elisa-trial-1-plate-map](https://static.igem.wiki/teams/4820/wiki/experiments-page-photos/elisa-trial-1-plate-map.png)

Plate Map for Trial 1 (Stadard was recombinant ferritin + antibody for plate 1, native ferritin + antibody for plate 2)

---

# **Computational Docking:**

---

## **Assumptions:**

---

* We ran all computational tests with non-biotinylated peptide and DNA aptamers despite ordering biotinylated aptamers for our wet lab tests - we did this under the assumption that the biotin doesn’t affect the binding affinity much
* We were unable to find a pdb file for the full ferritin multimer. We tested binding affinities between our aptamers and the light and heavy chains of ferritin. We assumed that if our aptamers are able to have a decent binding affinity with these single chains, then the binding affinity will be even better with a macromolecule made up of many of these chains. We are ignoring sterics by doing this, however, so that is something to take into consideration when doing wet lab tests.
* We’re also assuming that the aptamer won’t bind to ferritin multiple times once presented with more than one chain to bind to. This assumption is being made off of the data we found in our literature review and that the thermodynamics of the system will prevent the ligand and protein from binding multiple times.
* While there are a lot of tests backing the peptide and DNA’s binding affinity with ferritin in the papers and they give a decent amount of information on the testing conditions, we don’t have all the details (pH, temperature, pressure, etc) needed to properly simulate the experiment. All of the computational docking tests were run at STP and a pH of 7. This is also good for our biosensor as we hope for it to not need refrigeration.

+ As an add-on to that, we are assuming we can store the final biosensor at room temperature. The peptide and DNA we ordered was pretty stable but genscript did still give lower than room temperature storage conditions for both. We are assuming that the aptamer structures being as they are, especially with DNA being generally stable, they can last at room temperature for testing at least if not general storage.

* For potentially using SimRNA and other sites that give pdb files of RNA secondary structures, we are assuming that RNA will have a similar binding affinity with ferritin as DNA does.

+ In other words, the change from T to U won’t make much difference in binding affinities (still need to verify this, and our first option is still using the oligo single strand DNA instead of RNA)

## **Tools that were used (protocols, results, details on why they were used):**

---

**GROMACS**

We initially tried using GROMACS for ligand-protein binding. We weren't able to, however, as we couldn’t find any full pdb files for ferritin (some residues missing from all files found in protein data bank). We ended up using GROMACS to clean the pdb files and energy minimize the ligands. We mostly followed the GROMACS tutorials to do the protein-ligand complex. Khalid, one of our captains, also guided us on how to use GROMACS on the NYU HPC specifically. This included showing us how to upload files to the HPC, the syntax differences, and how to run batch commands.

**Autodock Vina**

We ended up using Autodock Vina for testing the ligand-ferritin complex. For this software, we just had to input pdb files for both the ligand (peptide aptamer) and macromolecule (ferritin - light or heavy chain), and we did not run into any issues because of one or two missing residues on the ferritin files. Below is the protocol we used. It was developed by Emre Erkanli, a PhD student in Dr. Kim’s lab who uses a lot of computational docking for his research.

**Developed by iGEM Team and Mehmet Emre Erkanli**

+ Open the protein and ligand in Pymol one at a time - clean up (delete unnecessary chains for protein) and save as pdb
+ Open Autodock → Read Molecule → open protein/enzyme (ferritin in our case)

- Edit → delete water molecules
- Edit Hydrogen → selection options: polar, non-bond order, yes
- Edit Charges → add Kollman charge
- Save edited protein as a macromolecule (pdbqt)

+ Open the peptide.pdb as a ligand input and save it as peptide.pdbqt (ligand output)
+ Open the gridbox → adjust spacing to 1.0 → adjust box dimensions until it covers the entire protein (macromolecule) → output grid file as grid.txt
+ Create text file “config.txt” and add which files will be receptor (protein) and ligand (peptide), dimensions (size, center coordinates) of the gridbox from grid.txt, and the energy range and exhaustiveness of the program
+ Run Autodock vina - select file names vina and config.txt for two inputs → run program
+ Command screen should pop up showing progress → will get a table of binding affinities and rmsd’s of the different ligand conformations
+ Can save output file as a pdb and open to view ligand conformations with the macromolecule in Pymol and/or Autodock Vina

Here is the first config.txt we made (ligand that was only energy minimized in Chemdraw + Heavy Chain Ferritin)

![conf.txt](https://static.igem.wiki/teams/4820/wiki/model-page/vina-conf-txt.png)

Here are the results we got on the command screen

![cmd](https://static.igem.wiki/teams/4820/wiki/model-page/no-em-peptide-heavy-chain.png)

Here is the first ligand conformation with ferritin

![autodock](https://static.igem.wiki/teams/4820/wiki/model-page/ligand-conf-1-2fha.png)

**NYU High Performance Computer**

We used NYU’s HPC mainly for GROMACS. The plan was to just submit computational docking tests to the HPC so we wouldn’t be taking up a lot of time on our personal computers. However, we ended up switching to Autodock due to the issues we were facing with GROMACS.

We tried adding Autodock onto the HPC to somehow use it there as each Autodock program ran about 6 hours on a personal computer. We ran into issues, however, getting the Autodock software onto the HPC, as we couldn’t figure out a way to download the software into the HPC. We’re now looking into using Open OnDemand (opening their computer desktop on mine) to install Autodock and add all of our files there. This can cut down on a lot of time if we continue with computational docking for the peptide-ferritin complex. It’s not as much of an issue for the DNA-ferritin tests as Haddock (details below) is a web server that runs its program in the cloud instead of on the computer.

**PyMol**

PyMol was mainly used to open pdb files of the peptides and ferritin in order to view and clean them (see Autodock protocol above for more info). We also tried using PyMol initially to draw the peptide as the software comes with an amino acid building blocks option. The structure wouldn’t maintain after the first few amino acids, however, as it was building somewhat helically and the sterics weren’t allowing us to add more amino acids. There was no real protocol for this as it was just us messing around to see what can be done. Obviously, it didn’t work, so as a result, Amulya drew the peptide organic structure on chemdraw and energy minimized using Chem3D.

Additionally, we tried making the DNA aptamer on PyMol using base pair building blocks. Unfortunately, we were only able to make a helical structure, not a proper secondary structure. When we later tried energy minimizing using Haddock (see below), the structure remained helical. We know this because the conformations we got from the computational docking tests still had a spiral shape and were only slightly bent. We might still use this spiral structure from PyMol and input it into other energy minimization softwares to see if any of them work. This is only if we can’t find any other simple options for getting a pdb file of the DNA secondary structure.

**Chemdraw**

We used Chemdraw to draw the ligand (peptide aptamer) from scratch after the PyMol amino acid building blocks weren’t working. We also used it to do an initial energy minimization of the peptide, but the structure was still very stiff, indicating that the energy minimization didn’t work very well.

Here is an image of our peptide after it was drawn and energy minimized using Chemdraw.

![no_em_chemdraw](https://static.igem.wiki/teams/4820/wiki/model-page/no-em-chemdraw.png)

**Chem3D**

We used Chem3D to do another energy minimization on the peptide as Chemdraw’s EM was not very good. This time, the structure came out much more bent in shape and the Autodock results were a bit better when we retested the peptide with heavy chain ferritin (aka the magnitude of the binding affinity we got for ligand-ferritin complex was a bit bigger).

Here is an image of our peptide after the Chem3D energy minimization in Chem3D.

![em_chem3d](https://static.igem.wiki/teams/4820/wiki/model-page/em-peptide-aptamer-3d.png)

Here is an image of our peptide after the Chem3D energy minimization in Chemdraw.

![em_chemdraw](https://static.igem.wiki/teams/4820/wiki/model-page/em-chemdraw.png)

**Haddock**

Haddock is an online software that we used to energy minimize the single strand DNA aptamers and test the binding affinity of the double strand, 5’-3’ single strand, and 3’-5’ single strand DNA aptamers with ferritin (light and heavy chain). From our literature review, it appeared that the DNA can bind to both heavy and light chains, so we wanted to confirm.

As we were unable to make a good secondary structure for the DNA using Pymol, we tried energy minimizing the DNA using Haddock (as mentioned earlier) to try getting a correct secondary structure. After running the binding test between the three DNA aptamers listed above and the two ferritin chains, we saw that the conformations of DNA were not very different from the original spiral shape. In other words, the Haddock energy minimization didn’t really work.

Unfortunately, the images from this test were not saved properly and the files were corrupted. When we went back to take photos again, we saw that the online tool automatically deletes results from your account after a while. We are currently in the progress of getting a pdb file of the actual DNA secondary structures to test with ferritin. Hopefully, when we run the Haddock test with better DNA structures, we will get better conformations and results to present.

**All of the DNA Secondary Structure Tools**

We’re currently trying to find if there are any other softwares that can create a pdb or sd file of the correct DNA secondary structure. We’ve unfortunately had no luck so far. Our next steps are to either:

+ Try energy minimizing DNA aptamers (5’-3’ strand and 3’-5’ strand) using other softwares like Chem3d to see if this can maybe provide a better secondary structure.
+ Work on just writing the DNA aptamer organic structure from scratch. This will take a while and require a better understanding of how secondary structure linkages and bonds work.

**Vector Builder**

Vector Builder is an online tool that creates a secondary structure png output for a DNA sequence input. It was used to get a secondary structure of DNA. Using this, we had a dot bracket form of the DNA to submit to different softwares if necessary.

![5_3_vector](https://static.igem.wiki/teams/4820/wiki/model-page/5-3-vector-build.png)

5’AACTCCTAAGCCAGTGCCAGAAGAGCCAAGGACAGGT3’ Secondary Structure on Vector Build

![3_5_vector](https://static.igem.wiki/teams/4820/wiki/model-page/3-5-vector-build.png)

3’ TTGAGGATTCGGTCACGGTCTTCTCGGTTCCTGTCCA5’ Secondary Structure on Vector Build

**SimRNA**

This software requires a sequence and secondary structure dot bracket input to give an energy minimized pdb of a secondary structure. However, as the name implies, it only does this for RNA, not DNA. If a DNA sequence is inputted, it converts it to RNA. If we find no other options to get a pdb, along with the options listed previously, we could move forward with SimRNA and assume that the RNA will have a similar binding affinity with ferritin as DNA does.This is one of the assumptions listed at the top of the page in case we move forward with this approach.

## **You may ask, why is continue computational docking?**

---

Since starting computational docking over the Summer, we’ve also ordered the peptide and 5’-3’ DNA sequence with a biotinylated N terminal and 3’ end, respectively, to be tested in the biotin-streptavidin direct ELISA and DNA shift assay (only DNA). So a question could be, “since we’ve moved on to physical testing, why are we still doing comp dock?” The answer can be broken into a few parts:

1. A lot of times, the results we get in the lab can be clear but unexplainable. For example, maybe we’re seeing lower or higher than expected binding rates. Computational docking is a great tool to project and make more educated guesses on why this might be happening. This can allow us to better and more quickly target the issue and solve it rather than wasting time and money doing multiple physical experiments to find the problem.

2. We are also really hoping for the DNA aptamer to work as this would introduce the opportunity of using different technologies like FRET (Fluorescence Resonance Energy Transfer) or SELEX (Systematic evolution of ligands by exponential enrichment)for our biosensor. This would be one of the most straightforward and cheap options for our biosensor, allowing us to make it more accessible and usable. Computational docking would allow us to use FRET by allowing us to see the different ways in which our DNA aptamer changes shape to bind to ferritin. This can help us determine best locations on the aptamer for fluorescent tags to be placed. These locations would be determined by seeing what parts of the DNA are close enough to each other in the binding conformation for a fluorescent signal to be released if a pair of tags were placed there. The option to use FRET is definitely one of the reasons why we’re really hoping the DNA aptamer has some strong data from our tests supporting its binding with ferritin. We also expect the DNA to be a bit more flexible and stable than the peptide, making it a better option for a quick and easily storable biosensor.

+ Here are the issues we are currently facing with this:

- Obviously, as mentioned above, we are struggling to get a pdb or sdf of our DNA’s secondary structure to use in the computational docking software
- We would need to do a lot more extensive modeling by changing out different bp’s and rerunning the simulations to see which sequences work the best. This would be a much more long-term research model and not something easily done in one year, let alone a semester.

## **Pdb Files Pulled From the Protein Data Bank:**

---

In order to test the binding affinities of our aptamers through computational docking, we used pdb files of heavy chain and light chain ferritin. Ideally, we would have used a full ferritin pdb. There weren’t any readily available, however, and it would have taken quite a while to create one. Instead, we made the assumption that sterics would not play too big of a role in limiting the aptamers’ binding with ferritin if there were multiple chains instead of just one. Or rather, we assumed that the aptamer having multiple chain options to bind to would counteract the aptamer having issues reaching some of the chains. The final pdb files we ended up using were [2FHA](https://www.rcsb.org/structure/2fha) (Human Heavy chain ferritin) and [2FFX](https://www.rcsb.org/structure/2FFX) (Human Light Chain Ferritin). Below are images of the two chains in PyMol.

![2fha](https://static.igem.wiki/teams/4820/wiki/model-page/2fha-heavy-chain-photo.png)

Human Heavy Chain Ferritin (2FHA) in Pymol

![2ffx](https://static.igem.wiki/teams/4820/wiki/model-page/2ffx-light-chain-photo.png)

Human Light Chain Ferritin (2FFX) in Pymol

## **Citations and References:**

---

Bank, R. P. D. (n.d.). RCSB PDB - 2FHA: HUMAN H CHAIN FERRITIN. https://www.rcsb.org/structure/2fha

Bank, R. P. D. (n.d.-a). RCSB PDB - 2FFX: Structure of Human Ferritin L. Chain. https://www.rcsb.org/structure/2FFX

De Vries, S. J., Van Dijk, M., & Bonvin, A. M. J. J. (2010). The HADDOCK web server for data-driven biomolecular docking. Nature Protocols, 5(5), 883–897. https://doi.org/10.1038/nprot.2010.32

Eberhardt, J., Santos-Martins, D., Tillack, A.F., Forli, S. (2021). AutoDock Vina 1.2.0: New Docking Methods, Expanded Force Field, and Python Bindings. Journal of Chemical Information and Modeling.

J.A. Lemkul (2018) "From Proteins to Perturbed Hamiltonians: A Suite of Tutorials for the GROMACS-2018 Molecular Simulation Package, v1.0" Living J. Comp. Mol. Sci. 1 (1): 5068.

The PyMOL Molecular Graphics System, Version 2.0 Schrödinger, LLC.

SimRNA: a coarse-grained method for RNA folding simulations and 3D structure prediction. Michał J. Boniecki, Grzegorz Łach, Konrad Tomala, Wayne Dawson, Paweł Łukasz, Tomasz Sołtysiński, Kristian M. Rother, and Janusz M. Bujnicki. Nucleic Acids Res. 2015 Dec 19. doi: 10.1093/nar/gkv1479

---

# **DNA Shift Assay:**

---

**Experiment:** Run a DNA shift assay experiment in order to determine if the DNA aptamer we found through literature review and computational docking successfully binds to ferritin. This experiment uses an agarose gel to visualize the migration pattern of DNA, ferritin, and DNA ferritin complexes. Smaller sized samples migrate further through the gel because they more easily fit through the pores of the gel. Larger sized samples do not migrate through the gel as far as smaller sized samples because they have a harder time moving through the pores of the gel. The samples in the gel are seen as bands under UV light.

## **DNA Shift Assay Protocol Overview:**

---

1. Tris EDTA (TE) buffer is prepared.

2. 1.5% agarose solution in TE buffer is prepared, and ethidium bromide (binds to DNA and ferritin to allow for detection of bands in gel under UV light).

3. The agarose was poured into a gel casting tray in order for the gel to set.

4. Samples were prepared in microtubes.

a. 6 Samples: Ferritin, DNA aptamer, and four different concentrations of ferritin with DNA aptamer added to allow for DNA to bind to ferritin.

b. The goal was to see the difference in migration in the gel between these samples.

i. DNA should migrate the furthest since it is the smallest.

ii. If DNA successfully binds to ferritin, the complex should migrate through the gel more slowly compared to ferritin on its own so the complex will not migrate as far in the gel.

iii. For the ferritin-DNA complex samples, there might also be two bands visible due to excess DNA that did not bind to ferritin.

5. 1x non SDS loading dye was added to each sample to ensure that samples were successfully loaded into the wells of the gel and so that band migration could be visible when running the gel. SDS denatures proteins to allow for each band of the protein to be visible in the gel. We needed an intact native ferritin structure to allow for DNA binding so we did not use SDS.

6. TE buffer was poured into the chamber so that it covered the gel.

7. All six samples were loaded into the wells (six wells total loaded).

8. The electrodes of the electrophoresis chamber were attached to a power source, and the gel was run at 100 Volts for an hour.

9. The gel was then visualized under UV light.

![dna-steps](https://static.igem.wiki/teams/4820/wiki/experiments-page-photos/dna-steps.png)

Visual of DNA Shift Assay Steps Listed Above Made Using Biorender

![chamber-photo](https://static.igem.wiki/teams/4820/wiki/experiments-page-photos/chamber-photo.png)

Photo Taken of Gel Electrophoresis Chamber Set Up

## **Trial 1:**

---

* We ran one gel.
* We prepared and loaded six samples at 30uL per well
* Lane 1: DNA (1ug)
* Lane 2: Native Ferritin (40ug)
* Lane 3: Native Ferritin (5ug) + DNA (20ug)
* Lane 4: Native Ferritin (10ug) + DNA (20ug)
* Lane 5: Native Ferritin (20ug) + DNA (20ug)
* Lane 6: Native Ferritin (30ug) + DNA (20ug)

{% endblock %}

{% extends "layout.html" %}
{% block title %}Results{% endblock %}
{% block lead %}Here are our wet lab and hardware results!{% endblock %}
{% block page\_content %}

## **Hardware Processes:**

---

* Our Team is working on developing an Arduino based platform that can process the data from teh aptamers to allow for veiwing of ferritin levels.
* The current model uses an LED platform that allow for the illumination of a sample, and a photosensor that can determne the absorbance of the aptamer.
* This is coupled with a calibartion curve that removes the optical effects of other components in saliva, to ensure that acurate readings can be made.
* The device at hand has been designed to be both low cost and easy to use, so as to ensure an easy user experience.

## **ELISA Trial 1 Results:**

---

### **Plate 1 Results:**

![elisa-trial-1-plate-1-results](https://static.igem.wiki/teams/4820/wiki/results-page-photos/elisa-plate-1-results.png)

ELISA (ferritin + peptide aptamer) Trial 1 Plate 1 (Standard was recombinant ferritin + antibody)

### **Plate 2 Results:**

![elisa-trial-1-plate-2-results](https://static.igem.wiki/teams/4820/wiki/results-page-photos/elisa-plate-2-results.png)

ELISA (ferritin + peptide aptamer) Trial 1 Plate 2 (Standard was native ferritin + antibody)

### **Notes:**

* Inconclusive results.
* The commercial kit that was used did not come with a blocking buffer, and relied on a sample diluent with some blocking buffer on it. Blocking buffer is needed to prevent nonspecific binding of antibody/peptide, streptavidin-hrp, or substrate on the wells by blocking out empty spots on the wells that ferritin did not bind to. The sample diluent in the commercial kit was ineffective at blocking the plate, so there was a lot of background noise on the plate when absorbance was read.
* This was especially seen in the blank control wells that should have had an absorbance reading of 0, but instead had some high readings of 0.3-0.5.
* Most samples in plate 1 had high absorbance readings, while most samples in plate 2 had very low absorbance readings even though samples on both plates had the same native ferritin concentrations and the concentrations of peptide added were the same as well.
* In addition, it was found that the constructed standard curve of absorbance vs concentration was not linear.

### **Future ELISA Experiments:**

* Use PBS Casein blocking buffer.
* After each incubation, wash more thoroughly to prevent any background noise in absorbance readings.
* Load ferritin at concentrations more similar to average human salivary ferritin levels.
* Try different peptide incubation times to evaluate how quick peptide can bind to ferritin.
* Perform ELISA using DNA aptamer with biotin conjugate.

## **DNA Trial 1 Results:**

---

### **Results Viewed in Regular Lighting:**

* Image of the gel before viewed under UV light.
* Bands are visible due to loading dye.
* 2 bands are visible in the native ferritin + DNA samples.

![DNA-trial-1-daylight-results](https://static.igem.wiki/teams/4820/wiki/results-page-photos/gel-day-1.png)

DNA Shift Assay Results Viewed in Regular Lighting

### **Results Viewed in UV Lighting:**

* Image of gel under UV light.
* The results of this experiment might be successful, but additional runs need to be done to confirm.
* Second band did not show under UV light for the ferritin/UV complexes → the second band is most likely DNA that did not bind to ferritin, and since there is less DNA that did not bind to ferritin it did not show up under the UV light.
* The lane with ferritin loaded by itself (40ug) did not show up on the gel → this might be due to the ethidium bromide not effectively binding to ferritin which prevents UV detection of ferritin.
* The lane with DNA by itself did show up on the gel and is represented by one band. Therefore, we know that the ethidium bromide did successfully bind to the DNA oligo which allowed for UV detection.
* The samples of ferritin/DNA complexes produced 1 band in the gel. Since ferritin by itself was not able to be detected and DNA was able to be detected it is likely that for lanes 3 through 6 (samples that contained both ferritin and DNA), DNA was able to successfully bind to ferritin and that is why it showed up on the gel.
* It is also possible the bands seen in lanes 3-6 are just DNA by itself and ferritin cannot be seen. However, lane 1 shows a pure DNA band that traveled further down the gel compared to the bands shown in lanes 3-6, so it is possible that these bands did not travel as far because DNA was bound to ferritin, and a ferritin DNA complex is bigger than DNA by itself.
* Furthermore, the second band shown in lanes 3-6 in the image taken before the gel was viewed under UV light could show that there some DNA was bound to ferritin, and some did not bind (possibly due to an excess concentration of DNA added compared to ferritin).

![DNA-trial-1-UV-results](https://static.igem.wiki/teams/4820/wiki/results-page-photos/gel-uv-1.png)

DNA Shift Assay Results Viewed in UV Lighting

### **Future DNA Shift Assay Experiments:**

* Load various concentrations of the DNA aptamer on its own to understand the migration pattern of this oligo.
* Load various concentrations of ferritin to understand migration pattern.
* Run a gel with a dye that allows for clear visualization of both ferritin and DNA aptamer.
* Run another gel with a dye known to bind to DNA only and not protein so that only ferritin with bound DNA can be visualized in the gel.
* Load ferritin + DNA samples at different concentrations.
* These future experiments will give us more data to confirm binding of the DNA aptamer to native ferritin.

{% endblock %}