MEASUREMENT
If we had access to our lab, we would want to quantify our fusion proteins’ ability to bind copper ions in solution so that we could feed the data back into our process design model and confirm whether our modified fusion proteins have improved binding affinity to our target metal. We have researched multiple methods to do so as described below.
An article by Arnesano et al. (2002) established a method for calculating the affinity constant of CopC by adding CuSO4 stepwise to a sample. The researchers found that the absorption that appears at \( \lambda_{max} = 616 nm \) increases in intensity as the concentration of copper (II) increases (Arnesano, Banci, Bertini & Thompson, 2002). This increase in intensity and concentration of copper was used to determine the affinity constant for Cu(II) binding to CopC.
A paper by Wijekoon et al. (2015) determined the Cu(II) binding affinities of a CopC protein from Pseudomonas fluorescens via a ligand competition assay. The ligands were fluorescent probes that emit strong fluorescence but do not fluoresce when bound to Cu(II) (Wijekoon, Young, Wedd and Xiao, 2015). The Cu(II) binding affinities, expressed as dissociation constants, were determined based on the competition between the ligand and the target protein for Cu(II) (Wijekoon, Young, Wedd and Xiao, 2015).
Wilkinson-White and Easterbrook-Smith (2008) used a Cu(II)-selective dye to estimate the binding affinity of copper to various proteins based on the change in their absorbance spectra. Interestingly, the specific dye used, 2-(5-bromo-2-pyridylaxo)-5-(N-propyl-N-sulfopropylamino) aniline (5-Br-PSAA), has been used in flow cell-based assays for metal ions in industrial wastewater previously (Wilkinson-White and Easterbrook-Smith, 2008). This is promising for our project application. To calculate the affinity constant of Cu(II) to a protein, the visible spectra of solutions containing Cu(II) and 5-Br-PSAA with varying pH were first recorded (Wilkinson-White and Easterbrook-Smith, 2008). These visible spectra allowed the researchers to obtain the concentration of the Cu(II):5-Br-PSAA complex (Wilkinson-White and Easterbrook-Smith, 2008). Then the equilibrium constant of the complex could be calculated through regression. Next, the protein was titrated into solutions containing Cu(II) and 5-Br-PSAA and the new concentration of the Cu(II):5-Br-PSAA complex was found (Wilkinson-White and Easterbrook-Smith, 2008). By analyzing the change in concentration, the affinity constant of the Cu(II):protein complex could be estimated (Wilkinson-White and Easterbrook-Smith, 2008). The authors mentioned that possible limitations of this method include the formation of ternary complexes, but concluded that the experimental data does not show it occurs (Wilkinson-White and Easterbrook-Smith, 2008). They also concluded that it may be inappropriate for characterizing proteins with multiple Cu(II) binding sites (Wilkinson-White and Easterbrook-Smith, 2008). However, the variation of CopC that we are using from Methylosinus trichosporium OB3b only has one, so this limitation is not a concern for us (Lawton et al., 2016).
From these three papers, we would choose to employ the first method described by Arnesano et al. (2002) because it is the most straight-forward and feasible within our financial and equipment constraints.
Future Metal Binding
We would also choose to employ this method described by Arnesano et al. (2002) because it is transferable to finding the binding affinity of proteins for future metals that we would want to target in our system. For example, Katoh et al. (2001) and Badarau et al. (2008) utilized variations of this titration process to investigate the binding affinities of the iron-binding proteins FutA1 and FutA2. However, Mills and Marletta (2005) emphasized the importance of changing the buffer solution accordingly depending on the magnitude of the expected binding constants of the metal-binding proteins.
To quantify the effectiveness of our cellulose binding column, we need to be able to measure the binding affinity of our cellulose-binding modules (CBMs) to cellulose. Qualitative measurements of the cellulose binding can be done through methods like SDS-PAGE electrophoresis; however, further research was needed to develop a quantitative method for measuring CBM binding.
Goldstein et al. (1993) measured the binding affinity of the cellulose-binding domain (CBD) found in cellulose-binding protein A. Yang et al. (2017) measured the binding of CBDs to cellulosic substrates to test the effects of specific amino acids on the surface of the binding domains. Based on these papers, a general procedure for characterizing the binding capacity of CBMs was developed using a combination of solid state binding assays, fluorescent spectroscopic analysis, and titration calorimetry.
After cloning and purifying the CBM using standard protocols, it can then be added to a centrifuge with a buffer and the cellulose competitors and then spun until the cellulose and protein complexes form a sediment. The resulting pellet should then be washed and re-suspended in a buffer where a Bicinchoninic acid kit can be used to determine the protein concentration. A spectrophotometer can then be used to determine the bound protein concentration. This resulting ratio of total protein / bound protein can be used to determine a free protein concentration and then a dissociation constant for the CBM (Goldstein et al., 1993; Yang et al., 2017).
In addition to these methods for measuring copper-protein binding strength, it is also important to have a method for measuring the concentration of dissolved copper. Such a method would be useful when testing and running an industrial bioreactor. It would be necessary to regularly monitor the concentration of copper flowing into and out of the reactor so that the reactor’s performance could be monitored over time. This method would also be useful for testing and improving a small-scale reactor.
Although many methods exist for quantifying dissolved copper, one simple method involves mixing the copper-containing solution with porphyrin \( \alpha, \beta, \gamma, \delta \)-tetraphenylporphine trisulfonate (TPPS) (Itoh et al., 1975). This compound forms a complex with copper, and the concentration of this complex can be measured by absorbance at 413 nm (Itoh et al., 1975).
References
Arnesano, F., Banci, L., Bertini, I., & Thompsett, A. R. (2002). Solution Structure of CopC: A Cupredoxin-like Protein Involved in Copper Homeostasis. Structure, 10(10), 1337–1347. https://doi.org/10.1016/S0969-2126(02)00858-4
Goldstein, M.A., Takagi, M., Hashida, S., Shoseyov, O., Doi, R. H., & Segel, I. H. (1993). Characterization of the Cellulose-Binding Domain of the Clostridium cellulovorans Cellulose-Binding Protein A. Journal of Bacteriology, 175(18), 5762-5768. https://dx.doi.org/10.1128%2Fjb.175.18.5762-5768.1993
Itoh, J.I., Yotsuyanagi, T., & Aomura, K. 1975. Spectrophotometric determination of copper with tetraphenylporphine trisulfonate. Analytica Chimica Acta, 74(1), 53–60. https://doi.org/10.1016/S0003-2670(01)82778-1
Lawton, T. J., Kenney, G. E., Hurley, J. D., & Rosenzweig, A. C. (2016). The CopC Family: Structural and Bioinformatic Insights into a Diverse Group of Periplasmic Copper Binding Proteins. Biochemistry, 55(15), 2278-2290. doi:10.1021/acs.biochem.6b00175
Mills, S.A. & Marletta, M. A. (2005). Metal binding characteristics and role of iron oxidation in the ferric uptake regulator from Escherichia coli. Biochemistry, 44(41), 13553-9. https://doi.org/10.1021/bi0507579
Wijekoon, C. J. K., Young, T. R., Wedd, A. G., & Xiao, Z. (2015). CopC Protein from Pseudomonas fluorescens SBW25 Features a Conserved Novel High-Affinity Cu(II) Binding Site. Inorganic Chemistry, 54(6), 2950–2959. https://doi.org/10.1021/acs.inorgchem.5b00031
Wilkinson-White, L. E. & Easterbrook-Smith, S. B. (2008). A dye-binding assay for measurement of the binding of Cu(II) to proteins. Journal of Inorganic Biochemistry, 102(10), 1831-1838. https://doi.org/10.1016/j.jinorgbio.2008.06.008
Yang, J., Xiong, W., Chen, F., Xu, L., & Han, Z. (2017). Aromatic amino acids in the cellulose binding domain of Penicillium crustosum endoglucanase EGL1 differentially contribute to the cellulose affinity of the enzyme. PLoS ONE, 12(5): e0176444. https://doi.org/10.1371/journal.pone.0176444