SBIR Phase I: Enzymatic bioremediation of poly and perfluoroalkyl carboxylic acids (PFCAs), a class of toxic and bioaccumulating per- and polyfluoroalkyl substances (PFAS)

The broader impact of this Small Business Innovation Research (SBIR) Phase I project lies in the development of a cost-effective and environmentally benign PFAS bioremediation strategy. This strategy aims to harness microbial enzymes that are capable of breaking strong chemical bonds in these molecules under mild conditions, offering a systematic approach to detoxify per- and polyfluoroalkyl carboxylic acids (PFCAs).

These PFCAs belong to a class of toxic and bioaccumulating per- and polyfluoroalkyl substances (PFAS). While exposure to these toxic molecules is associated with cancer, thyroid disease, childhood obesity and other medical conditions resulting in an estimated economic burden of $5.5-63 billion in the US, current energy intensive PFAS remediation technologies are costly, environmentally unsustainable, significantly contributing to greenhouse gas emissions.

In contrast, the proposed bioremediation technology may provide a scalable and systematic solution to degrade PFAS of varying lengths, effectively remediating environmental contamination. Additionally, adopting this technology allows the US advanced manufacturing sector to continue essential PFAS use for strategically important advanced materials while preventing new PFAS from entering the environment.

The proposed project aims to harness cutting-edge protein engineering techniques to design fluoroacetate dehalogenase enzymes (FADs) capable of fully degrading PFCA (perfluorocarboxylic acids). While existing FADs can break carbon-fluoride bonds in simple fluorinated compounds, no natural FAD has been identified for PFAS degradation. To achieve this, an ultra-efficient protein engineering platform will be leveraged.

Initially, generative AI and quantum mechanics/molecular dynamics (QMD) guide the creation of extensive FAD gene libraries, exploring sequence space to identify variants with enhanced catalytic activity, stability, and broad substrate specificity for C2-C8 PFCA. These large gene libraries are screened on a proprietary droplet microfluidic platform. Subsequently, AI models will be trained based on screening data to design new starting libraries for identifying improved variants with enhanced C2-C8 PFCA activity under industrial conditions.

After iterative cycles of design and screening, it is anticipated that highly active enzyme variantswill be identified, which will be characterized to ensure benign reaction products. The enzymes will be assessed for stability in diverse industrial wastewater conditions, expected temperature ranges, and expression levels in a production host. Successful demonstration of complete enzymatic PFCA degradation through this NSF-SBIR phase I project, would be compelling for industry partners to enter into pilot studies that is required for adoption of this technology.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.