Biology subjects

Spence, M. A.

Publications and source records attributed to Spence, M. A..

8 recordsLinked to original sources

bioRxiv2025

Fitness Landscape Ruggedness Arises from Biophysical Complexity

The ruggedness of a proteins fitness landscape constrains how it can evolve and how effectively it can be engineered. What determines whether a fitness landscape is rugged, and where in sequence space that ruggedness concentrates, remains poorly understood. Existing measures of ruggedness rely on complete combinatorial datasets and cannot be applied to landscapes in which only a fraction of possible sequences have been characterized. Here, we introduce a graph-based measure of ruggedness based on how quickly fitness differences diffuse across a landscape, which can be applied to sparse datasets. Applying this measure to 64 protein domains and several experimental systems with characterized folding and binding constraints, we show that ruggedness is not uniformly distributed but concentrates at regions where the dominant constraint on fitness changes. These results establish that the composition of individually simple constraints can generate localized ruggedness, providing a mechanistic basis for the complexity of protein fitness landscapes.

evolutionary biology↗

bioRxiv2025

Enthalpy-entropy trade-offs in the evolution of ligand specificity in a superfamily of transcription factors

Proteins operate through ligand and solvent interactions governed by thermodynamics, yet the enthalpy-entropy trade-offs that guide their functional evolution remain poorly understood. The LacI/GalR family (LGF) of transcription factors provides a system for examining how these trade-offs evolve over billions of years but has seldom been studied from a full thermodynamic perspective. While the evolution of ligand specificity has been well-studied, the thermodynamic determinants underlying the changes in specificity is not well understood - especially how proteins alter thermodynamic strategies to optimize affinity. By reconstructing LGF ancestors, we reveal a shift from entropy-driven binding in the most distant ancestor, to enthalpy-driven binding in the most recent ancestor and extant LacI. The most distant ancestor is characterized by the ability to bind its ligand in an open and dynamic conformation, and we propose that entropically-driven binding is driven by the presence of entropic reservoirs. This thermodynamic binding trade-off between the most distant and most recent ancestor is in accordance with the concept of ancient life that existed in a hot Earth environment, where higher temperatures enhanced entropically-driven binding. This suggests that molecular binding mechanisms evolved not just for ligand specificity, but to adapt to environmental pressures such as cooling Earth temperatures where enthalpic binding modes are favored.

biochemistry↗

bioRxiv2024

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

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.

biochemistry↗

bioRxiv2023

Leveraging ancestral sequence reconstruction for protein representation learning

Protein language models (PLMs) convert amino acid sequences into the numerical representations required to train machine learning (ML) models. Many PLMs are large (>600 M parameters) and trained on a broad span of protein sequence space. However, these models have limitations in terms of predictive accuracy and computational cost. Here, we use multiplexed Ancestral Sequence Reconstruction (mASR) to generate small but focused functional protein sequence datasets for PLM training. Compared to large PLMs, this local ancestral sequence embedding (LASE) produces representations 10-fold faster and with higher predictive accuracy. We show that due to the evolutionary nature of the ASR data, LASE produces smoother fitness landscapes in which protein variants that are closer in fitness value become numerically closer in representation space. This work contributes to the implementation of ML-based protein design in real-world settings, where data is sparse and computational resources are limited.

bioinformatics↗

bioRxiv2022

A broad-spectrum macrocyclic peptide inhibitor of the SARS-CoV-2 spike protein

The ongoing COVID-19 pandemic has had great societal and health consequences. Despite the availability of vaccines, infection rates remain high due to immune evasive Omicron sublineages. Broad-spectrum antivirals are needed to safeguard against emerging variants and future pandemics. We used mRNA display under a reprogrammed genetic code to find a spike-targeting macrocyclic peptide that inhibits SARS-CoV-2 Wuhan strain infection and pseudoviruses containing spike proteins of SARS-CoV-2 variants or related sarbecoviruses. Structural and bioinformatic analyses reveal a conserved binding pocket between the receptor binding domain, N-terminal domain and S2 region, distal to the ACE2 receptor-interaction site. Our data reveal a hitherto unexplored site of vulnerability in sarbecoviruses that peptides and potentially other drug-like molecules can target. Significance statementThis study reports on the discovery of a macrocyclic peptide that is able to inhibit SARS-CoV-2 infection by exploiting a new vulnerable site in the spike glycoprotein. This region is highly conserved across SARS-CoV-2 variants and the subgenus sarbecovirus. Due to the inaccessability and mutational contraint of this site, it is anticipated to be resistant to the development of resistance through antibody selective pressure. In addition to the discovery of a new molecule for development of potential new peptide or biomolecule therapeutics, the discovery of this broadly active conserved site can also stimulate a new direction of drug development, which together may prevent future outbreaks of related viruses.

biochemistry↗

bioRxiv2022

The rugged DNA-binding sequence-fitness landscape of the LacI/GalR Family is a product of asymmetry in the operator:repressor complex

How a proteins function influences the shape of its fitness landscape, smooth or rugged, is a fundamental question in evolutionary biochemistry. Smooth landscapes arise when incremental mutational steps lead to a progressive change in function, as commonly seen in enzymes and binding proteins. On the other hand, rugged landscapes are poorly understood because of the inherent unpredictability of how sequence changes affect function. Here, we experimentally characterize the entire sequence phylogeny, comprising 1158 extant and ancestral sequences, of the DNA-binding domain (DBD) of the LacI/GalR transcriptional repressor family. Our analysis revealed an extremely rugged landscape with rapid switching of specificity even between adjacent nodes. Further, the ruggedness arises due to the necessity of the repressor to simultaneously evolve specificity for asymmetric operators and disfavors potentially adverse regulatory crosstalk. Our study provides fundamental insight into evolutionary, molecular, and biophysical rules of genetic regulation through the lens of fitness landscapes.

biochemistry↗

bioRxiv2022

Comprehensive phylogenetic analysis of the ribonucleotide reductase family reveals an ancestral clade and the role of insertions and extensions in diversification

Ribonucleotide reductases (RNRs) are used by all organisms and many viruses to catalyze an essential step in the de novo biosynthesis of DNA precursors. RNRs are remarkably diverse by primary sequence and cofactor requirement, while sharing a conserved fold and radical-based mechanism for nucleotide reduction. Here, we structurally aligned the diverse RNR family by the conserved catalytic barrel to reconstruct the first large-scale phylogeny consisting of 6,779 sequences that unites all extant classes of the RNR family and performed evo-velocity analysis to independently validate our evolutionary model. With a robust phylogeny in-hand, we uncovered a novel, phylogenetically distinct clade that is placed as ancestral to the classes I and II RNRs, which we have termed clade O. We employed small-angle X-ray scattering (SAXS), cryogenic-electron microscopy (cryo-EM), and AlphaFold2 to investigate a member of this clade from Synechococcus phage S-CBP4 and report the most minimal RNR architecture to-date. Using the catalytic barrel as a starting point for diversification, we traced the evolutionarily relatedness of insertions and extensions that confer the diversity observed in the RNR family. Based on our analyses, we propose an evolutionary model of diversification in the RNR family and delineate how our phylogeny can be used as a roadmap for targeted future study.

bioinformatics↗

bioRxiv2020

A comprehensive phylogenetic analysis of the serpin superfamily

Serine protease inhibitors (serpins) are found in all kingdoms of life and play essential roles in multiple physiological processes. Owing to the diversity of the superfamily, phylogenetic analysis is challenging and prokaryotic serpins have been speculated to have been acquired from Metazoa through horizontal gene transfer (HGT) due to their unexpectedly high homology. Here we have leveraged a structural alignment of diverse serpins to generate a comprehensive 6000-sequence phylogeny that encompasses serpins from all kingdoms of life. We show that in addition to a central "hub" of highly conserved serpins, there has been extensive diversification of the superfamily into many novel functional clades. Our analysis indicates that the hub proteins are ancient and are similar because of convergent evolution, rather than the alternative hypothesis of HGT. This work clarifies longstanding questions in the evolution of serpins and provides new directions for research in the field of serpin biology.

bioinformatics↗