{% extends "layout.html" %} {% block title %}DESCRIPTION{% endblock %} {% block lead %}OUR PROJECT DESCRIPTION AND THE DEPTHS OF PFAS{% endblock %} {% block page_content %}

Our Approach to PFAS

PFAS are a large and diverse family of synthetic chemicals manufactured for industrial and consumer products beginning in the 1950s. These chemicals all have at least one fully fluorinated carbon bond that gives them a great resistance to breakdown in the environment. Originally developed for their water- and grease-resistant properties, PFAS are found in products that range from nonstick cookware to food wrappings, water-repellent fabrics, and firefighting foams. As they are found in these products, they are serious health and environmental concerns since they might be toxic and persist in the environment. They also tend to bioaccumulate over time without degradation. Of the many PFAS compounds, some like PFOA (Perfluorooctanoic Acid) and PFOS (Perfluorooctane Sulfonate) have been linked to serious health problems such as cancer, liver damage, and developmental problems for children. While both PFOA and PFOS have been largely phased out of commercial use in the United States, they continue to persist in the environment. Newer alternatives, such as GenX, have been developed but also carry risks; studies have linked them to liver and kidney damage. Other PFAS chemicals include the use of PFBS and PFHxS, though most of those remain under scrutiny over health effects. The problem is that its overwhelming application in industries contaminated drinking water, soil, and even the atmosphere. This calls for regulatory authorities like the EPA to set a regulation aimed at reducing the environmental and health risks caused by these chemicals. However, due to the very low thresholds for toxicity, detection of PFAS is extremely expensive and inaccessible to most.


In this project, we aim to create a more accessible method to detect PFAS. The current standard is liquid chromatography/mass spectroscopy, whicih requires extremely expensive machines that are usually exclusive to large research institutions. Since PFAS often endangers rural and agricultural areas that are far from such machines, it is important for PFAS testing methods to be more accessible.

We combined wet lab approaches with dry lab modeling to tackle the problem of PFAS detection.

Part design

To approach the issue of PFAS, we ultimately created 3 approaches. Last year, our team utilized a gene circuit that relied on the inducible promoter, prmA, from Rhodococcus jostii and a positive feedback loop to try and detect PFAS. However, we weren’t able to get significant results. This year, our team decided to move one step back and test the efficacy of the prmA promoter in Eschecheria coli. To test this, our first construct simply contained a superfolder GFP gene under the influence of the prmA promoter; if the promoter was effective, the E. coli would fluoresce when exposed to a high enough concentration of PFAS.

construct 1 illustration

Our second construct utilized a FAB-GFP conjugate molecule created by Dr. Berger from the University of Virginia. This molecule was originally developed to react to fatty acids; when fatty acids was present, the molecule would change confirmation to activate the GFP portion of the conjugate. We had previously seen, through reverse screening of databases, that PFAS had a likely chance of binding to fatty acid receptors in the cell. Thus, we decided to try the FAB-GFP conjugate molecule with PFAS to see if a response would occur. In this construct, we had the FAB-GFP gene under a constitutive promoter, which allowed for the constant creation of the conjugated molecule; in the presence of different PFOA concentrations, the FAB-GFP would theoretically change confirmation and fluoresce.

construct-2-illustration

Our final construct utilized a synthetic transcription factor to trigger a hybrid gene. Dr. Dossani and his colleagues created this transcription factor in Saccharomyces cerevisiae, using a protein called LexA combined with a viral activator domain VP16. This transcription factor was meant to be activated by estradiol, which would then allow the transcription factor to enter the nucleus of S. cerevisiae and attach to a hybrid promoter; this hybrid promoter was created by finding new operator regions for existing promoters that would allow for the synthetic transcription factor to bind. Once again, in our reverse screening research, we found that it was highly likely that PFAS interacted with estradiol receptors. Thus, we wanted to test whether the synthetic transcription factor would respond to PFOA as well. This construct required two plasmids because of its length; one of the plasmids housed the synthetic transcription factor, which was put downstream of a constitutive promoter. The second plasmid contained the hybrid promoter and a superfolder GFP gene under its influence. We wanted to test whether the transcription factor would work in E. coli rather than the original host and to what extent it would detect PFOA.

construct 3 illustration

To test our constructs, we would transform them into E. coli and incubate them in varying levels of PFOA (perfluorooctanoic acid) in 96-well plates. Fluorescence readings were taken of each well at 90 minute time intervals and recorded. More information can be seen on the Experiments and Results page.

Modeling

To better understand how our constructs would work, we employed two types of modeling: stochastic kinetic modeling with Virtual Cell (VCell) and Molecualr Dyanmics

Kinetic Modeling

We used VCell to model how our genetic circuits behaved over time. The simulations could tell us how each circuit behaves when in contact with different amounts of PFAS over time.

Virtual Cell, or VCell, is a software platform used to model cellular systems. We are using VCell to model the four primary constructs(names listed in experiments) we researched this year to detect PFAS, as well as other pathways. VCell is a valuable platform because it allows us to run simulations on the constructs we built. Additionally, VCell is user-friendly and easy to learn, as most functions are self-explanatory. VCell allows us to simulate reaction rates either stochastically or deterministically. Deterministic simulations are based on partial differential equations. Stochastic simulations are based on the Gibson-Bruck solver, which essentially probabilistically samples individual reactions to occur and the expected time between reactions. Stochastic simulations are more accurate at the single-cellular level because they take into account singular molecules.

vcell logo

Molecular Dynamics

Molecular dynamics simulates the energetics of proteins in solution and of ligands interacting with proteins. This allows us to find where a ligand binds to a protein and the relative contributions of different amino acids to the strength of binding, which could allow us to determine which protein residues could be mutated to increase binding affinities.

Human Practices

To ensure that our project would have a positive impact, we reached out to stakeholders in various areas affected by PFAS. We interviewed a KY state representative, water quality professionals, and contacted other students within KY that had first hand experience with PFAS. Through our contacts, we learned that our project idea would be useful to the world and we made modifications to our project plan to best fit what is needed.

References


  • https://academic.oup.com/milmed/article/186/Supplement_1/801/6119513
  • https://pubmed.ncbi.nlm.nih.gov/33499536/
  • https://pubs.acs.org/doi/abs/10.1021/acs.est.8b02912
  • https://2020.igem.org/Team:Stockholm
  • https://2019.igem.org/Team:USAFA
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5873372/
  • https://www.nature.com/articles/s41598-023-41953-1
  • https://www.frontiersin.org/articles/10.3389/fmicb.2015.00393/full
  • https://pubs.acs.org/doi/pdf/10.1021/es5060034
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