Biology subjects

Miton, C. M.

Publications and source records attributed to Miton, C. M..

5 recordsLinked to original sources

bioRxiv2026

Substrate-dependent epistasis probes active site intramolecular wiring

Enzyme adaptation toward novel substrates involves the rewiring of intramolecular residue networks, yet how this rewiring differs across multiple substrates, and how it underpins functional trade-offs and promiscuity, remains poorly understood. Here, we profile all 64 combinations of six key mutations in a phosphotriesterase across nine structurally diverse substrates spanning three chemical classes (organophosphates, esters, and lactones), thus generating a multi-dimensional map of epistasis and promiscuity within the phosphotriesterases active site. We developed a statistically robust reference-based analysis pipeline incorporating error propagation and significance testing to move beyond global epistatic trends and resolve idiosyncratic, substrate-dependent intramolecular wiring in specific genetic backgrounds. Simulations confirm that this pipeline reliably identifies genuine higher-order epistatic interactions while minimizing false positives. We reveal that intramolecular network wiring varies substantially between substrates - even within the same chemical class - with notable divergences between the adaptive target substrate 2-naphthyl hexanoate and its shorter-chain ester analogs. Key higher-order networks, including d233E/h254R/l271F and l271F/f306I/i313F, exhibit substrate-specific epistatic signatures that discriminate between subtle structural features such as acyl chain length, leaving group identity, and heteroatom substitution. These substrate-dependent rewiring events account for observed functional trade-offs, particularly the strong anti-correlation between the adaptive and native substrates. Collectively, these findings demonstrate that comprehensive cross-substrate epistatic profiling, paired with rigorous statistical analysis, provides a powerful framework for dissecting the molecular basis of enzyme promiscuity and the trade-offs that define adaptive evolution. Significance of the studyEnzymes are biological catalysts whose function depends on precisely coordinated networks of interacting amino acids. Understanding how these networks change as enzymes evolve to recognize new molecules is fundamental to understanding and predicting evolution. Here, we developed a statistical framework to map these networks across multiple molecules simultaneously, revealing how subtle differences in molecular shape drive functional trade-offs during evolution. These insights could inform the rational design of enzymes with tailored specificities for industrial and therapeutic applications.

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↗

bioRxiv2023

Origin Of Evolutionary Bifurcation In An Enzyme

Evolution can lead to significantly distinct outcomes depending on the mutational path taken. Evolutionary bifurcation, in which two mutational trajectories segregate, becoming non-interchangeable over time, is the basis of diversification in all kingdoms of life. Here, we present a detailed molecular description of a bifurcation event that rapidly led to the emergence of two distinct enzymes from a common ancestor. When initiated from two starting points that differed by a single amino acid, the laboratory evolution of a phosphotriesterase (PTE) toward arylester hydrolysis resulted in different genetic and phenotypic outcomes. One trajectory led to a >35,000-fold increase in activity via the reorganization of its active site to achieve exquisite enzyme-substrate complementarity. The second trajectory gave rise to an evolved variant with a [~]500-fold increase in activity, but exhibiting an alternative substrate binding mode resulting from the destabilization of an active site loop. While initial mutations tend to dictate mutational accessibility, we rather observed the gradual divergence and specialisation of each trajectory, following the emergence of distinct molecular interaction networks. Intramolecular epistasis underlay pathway bifurcation by promoting unique synergistic interactions within each trajectory, while restricting the fixation of mutation across pathways. Our results illustrate how distinct molecular outcomes can radiate from a common protein ancestor and give rise to phenotypic diversity.

evolutionary biology↗

bioRxiv2022

Higher-order epistasis creates idiosyncrasy, confounding predictions in protein evolution

Epistasis shapes evolutionary outcomes during protein adaptation. In particular, when the effects of single mutations or mutational interactions are idiosyncratic, that is, unique to a genetic background, the predictability of protein evolution becomes greatly impaired. Here, we unveil a quantitative picture of the prevalence and role of idiosyncrasy in protein evolution by analysing 45 protein fitness landscapes, generated from seven enzymes. We found that mutational effects and epistasis are highly idiosyncratic across the landscapes. Idiosyncrasy obscured functional predictions of mutated proteins when using limited mutational data, and often continued to impair prediction upon incorporation of epistatic information. We show that idiosyncrasy stems from higher-order epistasis, and highlight examples where it permits, or restricts, evolutionary accessibility of certain genotypes. Our work suggests that idiosyncrasy deeply confounds predictions in protein evolution necessitating its incorporation into predictive models and in-depth exploration of its underlying molecular mechanisms.

evolutionary biology↗

bioRxiv2020

Mechanistic understanding enables the rational design of salicylanilide combination therapies for Gram-negative infections

One avenue to combat multidrug-resistant Gram-negative bacteria is the co-administration of multiple drugs (combination therapy), which can be particularly promising if drugs synergize. The identification of synergistic drug combinations, however, is challenging. Detailed understanding of antibiotic mechanisms can address this issue by facilitating the rational design of improved combination therapies. Here, using diverse biochemical and genetic assays, we reveal the molecular mechanisms of niclosamide, a clinically-approved salicylanilide compound, and demonstrate its potential for Gram-negative combination therapies. We discovered that Gram-negative bacteria possess two innate resistance mechanisms that reduce their niclosamide susceptibility: a primary mechanism mediated by multidrug efflux pumps and a secondary mechanism of nitroreduction. When efflux was compromised, niclosamide became a potent antibiotic, dissipating the proton motive force (PMF), increasing oxidative stress and reducing ATP production to cause cell death. These insights guided the identification of diverse compounds that synergized with salicylanilides when co-administered (efflux inhibitors, membrane permeabilizers, and antibiotics that are expelled by PMF-dependent efflux), thus suggesting that salicylanilide compounds may have broad utility in combination therapies. We validate these findings in vivo using a murine abscess model, where we show that niclosamide synergizes with the membrane permeabilizing antibiotic colistin against high-density infections of multidrug-resistant Gram-negative clinical isolates. We further demonstrate that enhanced nitroreductase activity is a potential route to adaptive niclosamide resistance but show that this causes collateral susceptibility to clinical nitro-prodrug antibiotics. Thus, we highlight how mechanistic understanding of mode of action, innate/adaptive resistance, and synergy can rationally guide the discovery, development and stewardship of novel combination therapies. ImportanceThere is a critical need for more effective treatments to combat multidrug-resistant Gram-negative infections. Combination therapies are a promising strategy, especially when these enable existing clinical drugs to be repurposed as antibiotics. We reveal the mechanisms of action and basis of innate Gram-negative resistance for the anthelmintic drug niclosamide, and subsequently exploit this information to demonstrate that niclosamide and analogs kill Gram-negative bacteria when combined with antibiotics that inhibit drug efflux or permeabilize membranes. We confirm the synergistic potential of niclosamide in vitro against a diverse range of recalcitrant Gram-negative clinical isolates, and in vivo in a mouse abscess model. We also demonstrate that nitroreductases can confer resistance to niclosamide, but show that evolution of these enzymes for enhanced niclosamide resistance confers a collateral sensitivity to other clinical antibiotics. Our results highlight how detailed mechanistic understanding can accelerate the evaluation and implementation of new combination therapies.

microbiology↗