Rugged fitness landscapes minimize promiscuity in the evolution of transcriptional repressors

Meger, Anthony T.; Spence, Matthew A.; Sandhu, Mahakaran; Matthews, Dana; Chen, Jackie; Jackson, Colin J.; Raman, Srivatsan

doi:10.1016/j.cels.2024.03.002

Cited by 1 publication

(2 citation statements)

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“…For example, ASR can give insight into the ruggedness (i.e. complexity) of a fitness landscape over large spans of evolutionarily accessible sequence space to reveal fitness peaks that are inaccessible through stepwise mutational approaches 24 . In addition to this, ASR is also frequently used to engineer enzymes with enhanced industrial properties 22,26–28 , making it a valuable tool in both protein engineering and understanding the mechanisms of molecular evolution.…”

Section: Introductionmentioning

confidence: 99%

“…Ancestral sequence reconstruction (ASR), which utilizes a phylogenetic tree and a statistical model of evolution to infer the sequences of extinct, ancestral proteins, can provide critical insights into molecular evolution and functional diversification within protein families 22 . ASR has been useful in studying sequence-function relationships over protein families 23,24 ; such insight can shed light on the topologies of fitness landscapes that dictate the adaptive potential of proteins 25 . For example, ASR can give insight into the ruggedness (i.e.…”

Section: Introductionmentioning

confidence: 99%

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

Vongsouthi,

Georgelin,

Matthews

et al. 2024

Preprint

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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.

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