The enzymatic degradation of polyethylene terephthalate (PET) is a promising method of advanced plastic recycling. Traditional protein engineering methods often fall short in exploring protein sequence space for optimal enzymes due to structural and rational design limitations. Our study addresses this by using multiplexed ancestral sequence reconstruction (mASR) to explore the evolutionary sequence space of PET-degrading cutinases. With a dataset of 397 cutinase sequences, we created a diverse library of ancestral sequences. Experimental characterization of 48 ancestral sequences revealed a wide range of PETase activities, highlighting the value of mASR in uncovering functional variants when compared to traditional ASR. Our results showed that PETase activity in cutinases evolved through diverse pathways involving distal mutations to the active site, and is readily accessible within this family. Additionally, our analysis of the PETase fitness landscape using one-hot encoding (OHE) and local ancestral sequence embedding (LASE) highlighted the effectiveness of LASE in capturing sequence features relevant to activity. This work emphasizes the utility of mASR as a protein engineering tool for identifying enhanced PET-degrading enzymes, and the advantages of the LASE embedding scheme in mapping the PETase fitness landscape.

Ancestral reconstruction of polyethylene terephthalate degrading cutinases reveals a rugged and unexplored sequence-fitness landscape