Making Waves: Biocatalysis and Biosorption: Opportunities and Challenges Associated with a New Protein-Based Toolbox for Water and Wastewater Treatment

Abstract

New water and wastewater treatment technologies are required to meet the demands created by emerging contaminants and resource recovery needs, yet technology development is a slow and uncertain process. Through evolution, nature has developed highly selective and fast-acting proteins that could help address these issues, but research and application have been limited, often due to assumptions about stability and economic feasibility. Here we highlight the potential advantages of cell-free, protein-based water and wastewater treatment processes (biocatalysis and biosorption), evaluate existing information about their economic feasibility, consider when a protein-based treatment process might be advantageous, and highlight key research needs.

Keywords: Biocatalysis; Biosorption; Perchlorate; Perchlorate reductase; Phosphate-binding protein.

Graphical abstract

Fig. 1

Biocatalyst and Biosorption Decision Tree: To identify applications where the long-term prospects of biosorption and biocatalytic technologies are promising, the context of existing technologies and markets is important.

Fig. 2

Biocatalytic and Biosorption Treatment Landscapes. a) Biocatalytic activity was calculated using the Michaelis-Menten kinetics equations, published kinetic parameters of V_max and K_m, and environmentally relevant contaminant concentrations. b) Biosorption was evaluated based on the amount of biosorbent required to remove the contaminants at a flow rate of 1 million liters per day. This amount was calculated using environmentally relevant contaminant concentrations, established regulatory limits, protein-specific dissociation constants (K_d), and a Langmuir isotherm. Contaminants were selected based on the availability of enzyme kinetic information (biocatalysis) or binding affinity (biosorption) and their classification as contaminants of emerging concern, the presence of a U.S. EPA regulation, and/or their economic value. Environmentally relevant concentration ranges were developed based on published measurements from surface and groundwaters or wastewater influent. The low end of the contaminant range was further refined based on published health advisory limits available in the literature. For both graphs, to account for the data uncertainty (e.g., standard deviations), Monte Carlo simulations (200 for biocatalysts and 2000 for biosorbents) were performed with Latin Hyper Cube Sampling. In cases where standard deviations were not available, a uniform distribution +/- 10% of the reported values was used. The full datasets and associated references can be found in the Mendeley data repository http://dx.doi.org/10.17632/wt4mm84xv2.1. Code used to analyze data and create figures is available at https://github.com/jhutchku/2021_03_MakingWaves.git.