Team:Waterloo/Poster

Poster: Waterloo

REMINE: Closing the loop for heavy metal waste
Presented by Team Waterloo 2020

Alex Chan, Alina Arvisais, Alisha D'souza, Ana Fernandez, Ananya Muralidharan, Anthony Dang, Braeden MacDougall, Christian Singh, Clare Reid, Clare Wei, Daniel Matlin, Dylan Perera, François-Guillaume Lemesre, Genevieve Belford, Gerald Lee, Helen Engelhardt, Hillary Leung, James Stapleton, Jeriann Hsiao, Jessica Zhang, Jessy Song, Joshua Hanneson, Katherine Walker, Kingsley Wong, Lorenzo Pérez, Michael Astwood, Michael Lam, Morgan Cordell, Paige Aldridge, Patrick Thomas, Renessa Gomes, Riley Henderson, Sarah Hardy, Serena Hacker, Sergiu Pocol, Shiv Naik, Taran Layal

Abstract

REMINE is a packed column bioreactor containing metal-binding proteins which remove and recover toxic but valuable heavy metals from electronic manufacturing wastewater. The REMINE system can be customized to target specific metals by increasing the metal affinity of the proteins using molecular dynamics and protein engineering tools. Process engineering methods will be used to design the packed column reactor and optimise it to specific waste streams and regulatory constraints. With REMINE, the electronic industry can continue to grow while reducing its impact on our environment and health.
Problem
The exponential growth displayed by the electronics industry is adored by consumers as it increases the amount of available products in the market! However, as production increases, the volume of heavy metal contaminated wastewater generated by this industry has deleterious consequences to the environment, ecosystems and human health.

From an electronic product’s conception to its eventual discard, by-products such as chromium, nickel, and copper are released into local ecosystems, which often results in irreversible damage.1

Copper, in particular, is incredibly valuable to the electronics industry. 61% percent of all copper mined is turned into some sort of electric conductor.2 This prompted our process design to account for recoverability; if we can recover the metal ions filtered out of the wastewater, we will possess an asset that can be re-sold to those in the metals market. Copper has extensive physical properties as a conductor, and as a result, its high demand in the electronic industry is not going away any time soon.

There are multidimensional contributing factors of copper pollution, resulting in a cumulative negative impact. An aspect of key importance to Waterloo iGEM is the consideration of economic and social incentives for REMINE, and its integration to the overall implementation of our project.

Our technology is highly modular and can be applied to many situations. As a demonstration, we will consider dissolved Cu2+ waste from a semiconductor manufacturing facility.

  • 1.48 M tonnes of copper containing waste produced each year3
  • 30 mg/L dissolved Cu2+ in the waste4
  • USEPA regulations state that no more than 1.3 mg/L dissolved Cu2+ may be released to the environment5


In order to successfully treat the semiconductor facility’s waste stream, our technology must be able to treat 1.48 M tonnes of waste per year, and reduce the copper concentration in that waste from 30 mg/L to 1.3 mg/L.



References

1 Annual Operating Statistics. (2019). Retrieved October 16, 2020, from https://www.cumtn.com/operations/copper-mountain-mine/annual-operating-statistics/

2 Met-Chem. (2020, October 02). Metal Plating Wastewater Treatment - Finishing & Surfacing Retrieved October 16, 2020, from https://metchem.com/metal-finishing-wastewater-treatment-plating-finishing-surfacing/

3 TSMC Corporate Social Responsibility Report 2019. 2019. Retrieved from https://csr.tsmc.com/download/csr/2019-csr-report/english/pdf/e-all.pdf

4 Chiu, H.S.S., Tsang, K.L., and Lee, R.M.L. 1984. Treatment of electroplating wastes. Water Sanit. Asia Pacific Proc. 10th WEDC Conf.: 115–119.

5 Al-Saydeh, S.A., El-Naas, M.H., and Zaidi, S.J. 2017. Copper removal from industrial wastewater: A comprehensive review. J. Ind. Eng. Chem. 56: 35–44. The Korean Society of Industrial and Engineering Chemistry. doi:10.1016/j.jiec.2017.07.026.
Solution
In order to address the inefficiency found within current industrial standards for wastewater treatment, Waterloo iGEM proposed REMINE.

REMINE is a packed column bioreactor containing metal-binding proteins which remove and recover toxic but valuable heavy metals from electronic manufacturing wastewater. The REMINE system is highly modular and can be customized for specific metals, industries, and local regulations. We have used protein modelling and molecular dynamics to improve our proteins’ metal affinity and process engineering tools to design an efficient large-scale bioreactor. With REMINE, the electronic industry can continue to grow while reducing its impact on our environment and health. REMINE is currently designed to bind Cu2+ ions in solution.

Once our packed column reactor is saturated with metal, we can release the trapped metal ions by changing the chemical environment of the reactor using an eluent solution. The recovered metal can then be re-used for manufacturing other products. This reduces the need to mine and purify new metal, which is both economically and environmentally advantageous.
Protein Design: Goal
Use protein engineering tools to design improved Cu2+-binding proteins for our bioreactor and validate them using molecular dynamics.
Protein Design: Method
Of the many Cu2+-binding proteins that exist, Mst-CopC was chosen for use in our packed column reactor. Mst-CopC is small, monomeric, soluble and has a single Cu2+ binding site. This makes it easy to engineer, express and purify.



Selecting mutations
  • Literature and structural examination in PyMOL were used to choose mutations that would improve Mst-CopC’s copper affinity
  • Some mutations are inside the copper binding site and change the amino acids that coordinate the copper
  • Other mutations are located elsewhere and change the protein’s conformation, affecting active site size and shape


Making mutations
  • Mutations were implemented using the protein modelling software Rosetta
  • Rosetta energy scores were computed for each candidate, with low scores indicating high copper affinity and vice versa
  • This selects the most promising candidates so that they can be investigated further
  • For example, the mutation H85D has a lower energy score than the original Mst-CopC, meaning it should be investigated further
  • Rosetta also allows us to make proteins with multiple mutations and estimate their copper affinity


Protein Design: Results
In order to test whether our protein candidates really bind copper more strongly than the original, we used molecular dynamics. Molecular dynamics simulates chemical systems at an atomic resolution, allowing us to compute estimates of the interaction energy between copper and the protein candidate. We used the software GROMACS along with the Charmm36 forcefield parameters.





Many of our designed proteins had higher interaction energies than the original CopC, indicating greater copper affinity. The mutant Y34F-F3H-S81D-H85D had the highest interaction energy, over 3 times that of the original Mst-CopC, meaning that we succeeded in increasing copper affinity.
Fusion Design: Goal
To develop a fusion protein system wherein the metal binding protein is fused to a cellulose binding module for immobilization.
Fusion Design: Method
  1. Selection of cellulose binding module (CBM) and metal binding components for the fusion based on affinity, specificity, published sequences, monomeric quaternary structure, and irreversible binding (for CBM). Lead to the selection of CBM2a-Xyn10a (BBa_K863101) and Mst-CopC. The full criteria for selection are provided below:
  2. Removed signal peptide from Mst-CopC, added a flexible linker, HIS tag, and TEV cleavage site for the his tag.
  3. Modelled the fusion using UCSF Chimera. This is to provide a rough estimate of the fusion protein and ensure binding sites are still accessible.
  4. Chose pET11a (IPTG inducible) as a vector and E. coli BL21 (DE3) as a chassis for expression and developed a cloning plan.
  5. Determined measurement and validation protocols for copper and cellulose binding using spectroscopy. These protocols were chosen and modified since they provide a simple and robust way to measure binding affinities. Additionally, the metal binding procedure can be used with different metal binding proteins and ions with small modifications.
Fusion Design: Results
  1. Contributed literature data on CBM2a to the parts registry (BBa_K863101).
    • Shared structural and biochemical information about this domain that were found while doing extensive literature searches. This should help other teams when decided to use this part, especially as an immobilization tag.
  2. Engineered sequences for Mst-CopC (BBa_K3381002), Mst-CopC + CBM2a (BBa_K3381005), and improved Mst-CopC + CBM2a (BBa_K3381006).
  3. Improved the CBM2a part by adding a flexible linker (highlighted in green in the figure below) for use in fusions to it (BBa_K3381007).
    • The flexible linker is added to better enable the CBM2a domain from acting independently from a secondary (or tertiary, or etc.) in a fusion protein. This will hopefully enable future teams to build more effective fusions with CBM2a.
Process Design: Goal
Use industrial process modelling approaches to design a packed column reactor that will allow our fusion protein to be useful at a large scale.
Process Design: Method
  • After considering possible reactor designs, a packed column was determined to be the most suitable for our application
  • Our reactor will have a large chamber filled with cellulose, onto which our fusion protein will be immobilized
  • Reactor operation will occur in two stages:
  • Stage #1: as wastewater flows through the reactor, Cu2+ ions are trapped by the fusion protein
  • Stage #2: Once the reactor has been saturated with copper, the bound copper ions will be released with a small volume of eluent solution. This will give a pure and concentration copper solution that can be recycled for other manufacturing applications.


The reactor can be modelled by a reaction-convection equation, which is given by the following system of Partial Differential Equations. \( \frac{dm}{dt} + \vec{v}\cdot \nabla m - D\nabla^2 m = -(\frac{a}{f}) (k_a m (Q-q) - k_d q) \) \( \frac{dq}{dt} = k_a m (Q-q) - k_d q \)

In the first equation, the terms on the left hand side represent transport of the copper, and the terms on the right hand side represent the interaction of the copper with the protein.

The pressure in the reactor can be calculated using the Ergun equation: \( \frac{\Delta P}{L} = \frac{72 \mu \tau (1 - \epsilon)^2 v_s}{D^2_P \epsilon^3} + \frac{3 \tau (1 - \epsilon) \rho v^2_s \left(\frac{3}{2} + \frac{1}{\beta^4} - \frac{5}{2 \beta^2} \right)}{4 \epsilon^3 D_p} \)
Process Design: Results
Our results from this model show that a reactor with flow speed sufficiently slower than the reaction rate will reduce the concentration to <0.1 mg/L Cu2+, much lower than the requirement of 1.3 mg/L. With this in mind, we calculated that the reactor must be roughly 12.8 m in length and 1.28 m in diameter.
  • In an industrial setting, this packed column reactor would be preceded by pre-treatment steps to remove other components that could damage the reactor
  • The Mst-CopC fusion protein would bind Cu2+ best at pH 7.2, so the waste’s pH should be adjusted using concentrated acid or base
  • The reactor can treat about 850 000 L of semiconductor manufacturing waste over a 5 hour period before becoming saturated with copper
  • Once saturated, the trapped Cu2+ will be eluted with a pH 4.8 eluent solution, leaving a concentrated and pure copper solution
  • This timeline allows 4 reactor cycles a day, allowing 1.48 M tonnes of semiconductor manufacturing waste to be treated each year


Our technology therefore succeeds at treating our example semiconductor manufacturing waste stream.

Acknowledgements + Sponsors
Our project would not have been possible without the help, support, and advice of our advisors, the people we consulted with, and our team members.

Advisors: Dr. Brian Ingalls, Dr. Trevor Charles, Dr. Marc Aucoin, Dr. Barbara Moffat, Dr. Valerie Ward, Vivian Cheung, Dr. Andrew Doxey, Dr. Forbes Burkowski

Consultations: Dr. Susan Baldwin, Lauren Lunquist, Patrick Diep, Dr. Subha Kalyaanamoorthy, Brian Montgomery, Rolando F. Velasquez, Jo-Ann Livingston, Kate Granstrom

Sponsors