Pervasive epistasis exposes intramolecular networks in adaptive enzyme evolution.

Enzyme evolution is characterized by constant alterations of the intramolecular residue networks supporting their functions. The rewiring of these network interactions can give rise to epistasis. As mutations accumulate, the epistasis observed across diverse genotypes may appear idiosyncratic, that is, exhibit unique effects in different genetic backgrounds. Here, we unveil a quantitative picture of the prevalence and patterns of epistasis in enzyme evolution by analyzing 41 fitness landscapes generated from seven enzymes. We show that >94% of all mutational and epistatic effects appear highly idiosyncratic, which greatly distorted the functional prediction of the evolved enzymes. By examining seemingly idiosyncratic changes in epistasis along adaptive trajectories, we expose several instances of higher-order, intramolecular rewiring. Using complementary structural data, we outline putative molecular mechanisms explaining higher-order epistasis along two enzyme trajectories. Our work emphasizes the prevalence of epistasis and provides an approach to exploring this phenomenon through a molecular lens.

Molecular determinants of protein evolvability.

The plethora of biological functions that sustain life is rooted in the remarkable evolvability of proteins. An emerging view highlights the importance of a protein's initial state in dictating evolutionary success. A deeper comprehension of the mechanisms that govern the evolvability of these initial states can provide invaluable insights into protein evolution. In this review, we describe several molecular determinants of protein evolvability, unveiled by experimental evolution and ancestral sequence reconstruction studies. We further discuss how genetic variation and epistasis can promote or constrain functional innovation and suggest putative underlying mechanisms. By establishing a clear framework for these determinants, we provide potential indicators enabling the forecast of suitable evolutionary starting points and delineate molecular mechanisms in need of deeper exploration.

Insertions and Deletions (Indels): A Missing Piece of the Protein Engineering Jigsaw.

Over the years, protein engineers have studied nature and borrowed its tricks to accelerate protein evolution in the test tube. While there have been considerable advances, our ability to generate new proteins in the laboratory is seemingly limited. One explanation for these shortcomings may be that insertions and deletions (indels), which frequently arise in nature, are largely overlooked during protein engineering campaigns. The profound effect of indels on protein structures, by way of drastic backbone alterations, could be perceived as "saltation" events that bring about significant phenotypic changes in a single mutational step. Should we leverage these effects to accelerate protein engineering and gain access to unexplored regions of adaptive landscapes? In this Perspective, we describe the role played by indels in the functional diversification of proteins in nature and discuss their untapped potential for protein engineering, despite their often-destabilizing nature. We hope to spark a renewed interest in indels, emphasizing that their wider study and use may prove insightful and shape the future of protein engineering by unlocking unique functional changes that substitutions alone could never achieve.

Epistasis and intramolecular networks in protein evolution.

Proteins are molecular machines composed of complex, highly connected amino acid networks. Their functional optimization requires the reorganization of these intramolecular networks by evolution. In this review, we discuss the mechanisms by which epistasis, that is, the dependence of the effect of a mutation on the genetic background, rewires intramolecular interactions to alter protein function. Deciphering the biophysical basis of epistasis is crucial to our understanding of evolutionary dynamics and the elucidation of sequence-structure-function relationships. We featured recent studies that provide insights into the molecular mechanisms giving rise to epistasis, particularly at the structural level. These studies illustrate the convoluted and fascinating nature of the intramolecular networks co-opted by epistasis during the evolution of protein function.

Statistical analysis of mutational epistasis to reveal intramolecular interaction networks in proteins.

Epistasis occurs when the combined effect of two or more mutations differs from the sum of their individual effects, and reflects molecular interactions that affect the function and fitness of a protein. Epistasis is widely recognized as a key phenomenon that drives the dynamics of evolution. It can profoundly affect our ability to understand sequence-structure-function relationships, and thus has important implications for protein engineering and design. Characterizing higher-order epistasis, i.e., interactions between three or more mutations, can unveil hidden intramolecular interaction networks that underlie essential protein functions and their evolution. For this chapter, we developed an analytical pipeline that can standardize the study of intramolecular epistasis. We describe the generation and characterization of a combinatorial library, the statistical analysis of mutational epistasis, and finally, the depiction of epistatic networks on the 3D structure of a protein. We anticipate that this pipeline will benefit the increasing number of scientists that are interested in the functional characterization of mutational libraries to provide a deeper understanding of the molecular mechanisms of protein evolution.

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 coadministration 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 examine 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 coadministered (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.IMPORTANCE There 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 examined the mechanisms of action and basis of innate Gram-negative resistance for the anthelmintic drug niclosamide and subsequently exploited 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.

A mechanistic view of enzyme evolution.

New enzyme functions often evolve through the recruitment and optimization of latent promiscuous activities. How do mutations alter the molecular architecture of enzymes to enhance their activities? Can we infer general mechanisms that are common to most enzymes, or does each enzyme require a unique optimization process? The ability to predict the location and type of mutations necessary to enhance an enzyme's activity is critical to protein engineering and rational design. In this review, via the detailed examination of recent studies that have shed new light on the molecular changes underlying the optimization of enzyme function, we provide a mechanistic perspective of enzyme evolution. We first present a global survey of the prevalence of activity-enhancing mutations and their distribution within protein structures. We then delve into the molecular solutions that mediate functional optimization, specifically highlighting several common mechanisms that have been observed across multiple examples. As distinct protein sequences encounter different evolutionary bottlenecks, different mechanisms are likely to emerge along evolutionary trajectories toward improved function. Identifying the specific mechanism(s) that need to be improved upon, and tailoring our engineering efforts to each sequence, may considerably improve our chances to succeed in generating highly efficient catalysts in the future.

Cryptic genetic variation shapes the adaptive evolutionary potential of enzymes.

Genetic variation among orthologous proteins can cause cryptic phenotypic properties that only manifest in changing environments. Such variation may impact the evolvability of proteins, but the underlying molecular basis remains unclear. Here, we performed comparative directed evolution of four orthologous metallo-ß-lactamases toward a new function and found that different starting genotypes evolved to distinct evolutionary outcomes. Despite a low initial fitness, one ortholog reached a significantly higher fitness plateau than its counterparts, via increasing catalytic activity. By contrast, the ortholog with the highest initial activity evolved to a less-optimal and phenotypically distinct outcome through changes in expression, oligomerization and activity. We show how cryptic molecular properties and conformational variation of active site residues in the initial genotypes cause epistasis, that could lead to distinct evolutionary outcomes. Our work highlights the importance of understanding the molecular details that connect genetic variation to protein function to improve the prediction of protein evolution.

Evolutionary repurposing of a sulfatase: A new Michaelis complex leads to efficient transition state charge offset.

The recruitment and evolutionary optimization of promiscuous enzymes is key to the rapid adaptation of organisms to changing environments. Our understanding of the precise mechanisms underlying enzyme repurposing is, however, limited: What are the active-site features that enable the molecular recognition of multiple substrates with contrasting catalytic requirements? To gain insights into the molecular determinants of adaptation in promiscuous enzymes, we performed the laboratory evolution of an arylsulfatase to improve its initially weak phenylphosphonate hydrolase activity. The evolutionary trajectory led to a 100,000-fold enhancement of phenylphosphonate hydrolysis, while the native sulfate and promiscuous phosphate mono- and diester hydrolyses were only marginally affected (≤50-fold). Structural, kinetic, and in silico characterizations of the evolutionary intermediates revealed that two key mutations, T50A and M72V, locally reshaped the active site, improving access to the catalytic machinery for the phosphonate. Measured transition state (TS) charge changes along the trajectory suggest the creation of a new Michaelis complex (E•S, enzyme-substrate), with enhanced leaving group stabilization in the TS for the promiscuous phosphonate (ßleavinggroup from -1.08 to -0.42). Rather than altering the catalytic machinery, evolutionary repurposing was achieved by fine-tuning the molecular recognition of the phosphonate in the Michaelis complex, and by extension, also in the TS. This molecular scenario constitutes a mechanistic alternative to adaptation solely based on enzyme flexibility and conformational selection. Instead, rapid functional transitions between distinct chemical reactions rely on the high reactivity of permissive active-site architectures that allow multiple substrate binding modes.

How mutational epistasis impairs predictability in protein evolution and design.

There has been much debate about the extent to which mutational epistasis, that is, the dependence of the outcome of a mutation on the genetic background, constrains evolutionary trajectories. The degree of unpredictability introduced by epistasis, due to the non-additivity of functional effects, strongly hinders the strategies developed in protein design and engineering. While many studies have addressed this issue through systematic characterization of evolutionary trajectories within individual enzymes, the field lacks a consensus view on this matter. In this work, we performed a comprehensive analysis of epistasis by analyzing the mutational effects from nine adaptive trajectories toward new enzymatic functions. We quantified epistasis by comparing the effect of mutations occurring between two genetic backgrounds: the starting enzyme (for example, wild type) and the intermediate variant on which the mutation occurred during the trajectory. We found that most trajectories exhibit positive epistasis, in which the mutational effect is more beneficial when it occurs later in the evolutionary trajectory. Approximately half (49%) of functional mutations were neutral or negative on the wild-type background, but became beneficial at a later stage in the trajectory, indicating that these functional mutations were not predictable from the initial starting point. While some cases of strong epistasis were associated with direct interaction between residues, many others were caused by long-range indirect interactions between mutations. Our work highlights the prevalence of epistasis in enzyme adaptive evolution, in particular positive epistasis, and suggests the necessity of incorporating mutational epistasis in protein engineering and design to create highly efficient catalysts.

Ultrahigh-throughput discovery of promiscuous enzymes by picodroplet functional metagenomics.

Unculturable bacterial communities provide a rich source of biocatalysts, but their experimental discovery by functional metagenomics is difficult, because the odds are stacked against the experimentor. Here we demonstrate functional screening of a million-membered metagenomic library in microfluidic picolitre droplet compartments. Using bait substrates, new hydrolases for sulfate monoesters and phosphotriesters were identified, mostly based on promiscuous activities presumed not to be under selection pressure. Spanning three protein superfamilies, these break new ground in sequence space: promiscuity now connects enzymes with only distantly related sequences. Most hits could not have been predicted by sequence analysis, because the desired activities have never been ascribed to similar sequences, showing how this approach complements bioinformatic harvesting of metagenomic sequencing data. Functional screening of a library of unprecedented size with excellent assay sensitivity has been instrumental in identifying rare genes constituting catalytically versatile hubs in sequence space as potential starting points for the acquisition of new functions.