Rapid evolutionary change in trait correlations of single proteins.

Many organismal traits are genetically determined and covary in evolving populations. The resulting trait correlations can either help or hinder evolvability - the ability to bring forth new and adaptive phenotypes. The evolution of evolvability requires that trait correlations themselves must be able to evolve, but we know little about this ability. To learn more about it, we here study two evolvable systems, a yellow fluorescent protein and the antibiotic resistance protein VIM-2 metallo beta-lactamase. We consider two traits in the fluorescent protein, namely the ability to emit yellow and green light, and three traits in our enzyme, namely the resistance against ampicillin, cefotaxime, and meropenem. We show that correlations between these traits can evolve rapidly through both mutation and selection on short evolutionary time scales. In addition, we show that these correlations are driven by a protein's ability to fold, because single mutations that alter foldability can dramatically change trait correlations. Since foldability is important for most proteins and their traits, mutations affecting protein folding may alter trait correlations mediated by many other proteins. Thus, mutations that affect protein foldability may also help shape the correlations of complex traits that are affected by hundreds of proteins.

Measuring differential fitness costs and interactions between genetic cassettes using fluorescent spectrophotometry.

In this article, we present a method for designing, executing, and analyzing data from a microbial competition experiment. We use fluorescent reporters to label different competing strains and resolve individual growth curves using a fluorescent spectrophotometer. Our comprehensive data analysis pipeline integrates multiple experiments to simultaneously infer sources of variation, extract selection coefficients, and estimate the genetic contributions to fitness for various synthetic genetic cassettes (SGCs). To demonstrate the method, we employ a synthetic biological system based on Escherichia coli. Strains carry 1 of 10 different plasmids and one of three genomically integrated fluorescent markers. All strains are co-cultured to obtain real-time measurements of optical density (total population density) and fluorescence (sub-population densities). We identify challenges in calibrating between fluorescence and density and of fluorescent proteins maturing at different rates. To resolve these issues, we compare two methods of fluorescence calibration and correct for maturation by measuring in vivo maturation times. We provide evidence of genetic interactions occurring between our SGCs and further show how to use our statistical model to test some hypotheses about microbial growth and the costs of protein expression.IMPORTANCEFluorescently labeled co-cultures are becoming increasingly popular. The approach proposed here offers a high standard for experimental design and data analysis to measure selection coefficients and growth rates in competition. Measuring competitive differences is useful in many laboratory studies, allowing for fitness cost-correction of growth rates and ecological interactions and testing hypotheses in synthetic biology. Using time-resolved growth curves, rather than endpoint measurements, for competition assays allows us to construct a detailed scientific model that can be used to ask questions about fine-grained phenomena, such as bacterial growth dynamics, as well as higher-level phenomena, such as the interactions between synthetic cassette expression.

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.

Genetic Perturbation Alters Functional Substates in Alkaline Phosphatase.

Enzymes inherently exhibit molecule-to-molecule heterogeneity in their conformational and functional states, which is considered to be a key to the evolution of new functions. Single-molecule enzyme assays enable us to directly observe such multiple functional states or functional substates. Here, we quantitatively analyzed functional substates in the wild-type and 69 single-point mutants of Escherichia coli alkaline phosphatase by employing a high-throughput single-molecule assay with a femtoliter reactor array device. Interestingly, many mutant enzymes exhibited significantly heterogeneous functional substates with various types, while the wild-type enzyme showed a highly homogeneous substate. We identified a correlation between the degree of functional substates and the level of improvement in promiscuous activities. Our work provides much comprehensive evidence that the functional substates can be easily altered by mutations, and the evolution toward a new catalytic activity may involve the modulation of the functional substates.

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.

Evolution of ß-lactamase-mediated cefiderocol resistance.

BACKGROUND: Cefiderocol is a novel siderophore ß-lactam with improved hydrolytic stability toward ß-lactamases, including carbapenemases, achieved by combining structural moieties of two clinically efficient cephalosporins, ceftazidime and cefepime. Consequently, cefiderocol represents a treatment alternative for infections caused by MDR Gram-negatives. OBJECTIVES: To study the role of cefiderocol on resistance development and on the evolution of ß-lactamases from all Ambler classes, including KPC-2, CTX-M-15, NDM-1, CMY-2 and OXA-48. METHODS: Directed evolution, using error-prone PCR followed by selective plating, was utilized to investigate how the production and the evolution of different ß-lactamases cause changes in cefiderocol susceptibility determined using microbroth dilution assays (MIC and IC50). RESULTS: We found that the expression of blaOXA-48 did not affect cefiderocol susceptibility. On the contrary, the expression of blaKPC-2, blaCMY-2, blaCTX-M-15 and blaNDM-1 substantially reduced cefiderocol susceptibility by 4-, 16-, 8- and 32-fold, respectively. Further, directed evolution on these enzymes showed that, with the acquisition of only 1-2 non-synonymous mutations, all ß-lactamases were evolvable to further cefiderocol resistance by 2- (NDM-1, CTX-M-15), 4- (CMY-2), 8- (OXA-48) and 16-fold (KPC-2). Cefiderocol resistance development was often associated with collateral susceptibility changes including increased resistance to ceftazidime and ceftazidime/avibactam as well as functional trade-offs against different ß-lactam drugs. CONCLUSIONS: The expression of contemporary ß-lactamase genes can potentially contribute to cefiderocol resistance development and the acquisition of mutations in these genes results in enzymes adapting to increasing cefiderocol concentrations. Resistance development caused clinically important cross-resistance, especially against ceftazidime and ceftazidime/avibactam.

Adventures on the Routes of Protein Evolution-In Memoriam Dan Salah Tawfik (1955-2021).

Understanding how proteins evolved not only resolves mysteries of the past, but also helps address challenges of the future, particularly those relating to the design and engineering of new protein functions. Here we review the work of Dan S. Tawfik, one of the pioneers of this area, highlighting his seminal contributions in diverse fields such as protein design, high throughput screening, protein stability, fundamental enzyme-catalyzed reactions and promiscuity, that underpin biology and the origins of life. We discuss the influence of his work on how our models of enzyme and protein function have developed and how the main driving forces of molecular evolution were elucidated. The discovery of the rugged routes of evolution has enabled many practical applications, some which are now widely used.

The adaptive landscape of a metallo-enzyme is shaped by environment-dependent epistasis.

Enzymes can evolve new catalytic activity when environmental changes present them with novel substrates. Despite this seemingly straightforward relationship, factors other than the direct catalytic target can also impact adaptation. Here, we characterize the catalytic activity of a recently evolved bacterial methyl-parathion hydrolase for all possible combinations of the five functionally relevant mutations under eight different laboratory conditions (in which an alternative divalent metal is supplemented). The resultant adaptive landscapes across this historical evolutionary transition vary in terms of both the number of "fitness peaks" as well as the genotype(s) at which they are found as a result of genotype-by-environment interactions and environment-dependent epistasis. This suggests that adaptive landscapes may be fluid and molecular adaptation is highly contingent not only on obvious factors (such as catalytic targets), but also on less obvious secondary environmental factors that can direct it towards distinct outcomes.

Evolution of ß-lactamases and enzyme promiscuity.

ß-Lactamases represent one of the most prevalent resistance mechanisms against ß-lactam antibiotics. Beyond their clinical importance, they have also become key models in enzymology and evolutionary biochemistry. A global understanding of their evolution and sequence and functional diversity can therefore aid a wide set of different disciplines. Interestingly, ß-lactamases have evolved multiple times from distinct evolutionary origins, with ancestries that reach back billions of years. It is therefore no surprise that these enzymes exhibit diverse structural features and enzymatic mechanisms. In this review, we provide a bird's eye view on the evolution of ß-lactamases within the two enzyme superfamilies-i.e. the penicillin-binding protein-like and metallo-ß-lactamase superfamily-through phylogenetics. We further discuss potential evolutionary origins of each ß-lactamase class by highlighting signs of evolutionary connections in protein functions between ß-lactamases and other enzymes, especially cases of enzyme promiscuity.

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.

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.

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.

Accessing unexplored regions of sequence space in directed enzyme evolution via insertion/deletion mutagenesis.

Insertions and deletions (InDels) are frequently observed in natural protein evolution, yet their potential remains untapped in laboratory evolution. Here we introduce a transposon-based mutagenesis approach (TRIAD) to generate libraries of random variants with short in-frame InDels, and screen TRIAD libraries to evolve a promiscuous arylesterase activity in a phosphotriesterase. The evolution exhibits features that differ from previous point mutagenesis campaigns: while the average activity of TRIAD variants is more compromised, a larger proportion has successfully adapted for the activity. Different functional profiles emerge: (i) both strong and weak trade-off between activities are observed; (ii) trade-off is more severe (20- to 35-fold increased kcat/KM in arylesterase with 60-400-fold decreases in phosphotriesterase activity) and (iii) improvements are present in kcat rather than just in KM, suggesting adaptive solutions. These distinct features make TRIAD an alternative to widely used point mutagenesis, accessing functional innovations and traversing unexplored fitness landscape regions.

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.

Author Correction: Higher-order epistasis shapes the fitness landscape of a xenobiotic-degrading enzyme.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Comprehensive exploration of the translocation, stability and substrate recognition requirements in VIM-2 lactamase.

Metallo-ß-lactamases (MBLs) degrade a broad spectrum of ß-lactam antibiotics, and are a major disseminating source for multidrug resistant bacteria. Despite many biochemical studies in diverse MBLs, molecular understanding of the roles of residues in the enzyme's stability and function, and especially substrate specificity, is lacking. Here, we employ deep mutational scanning (DMS) to generate comprehensive single amino acid variant data on a major clinical MBL, VIM-2, by measuring the effect of thousands of VIM-2 mutants on the degradation of three representative classes of ß-lactams (ampicillin, cefotaxime, and meropenem) and at two different temperatures (25°C and 37°C). We revealed residues responsible for expression and translocation, and mutations that increase resistance and/or alter substrate specificity. The distribution of specificity-altering mutations unveiled distinct molecular recognition of the three substrates. Moreover, these function-altering mutations are frequently observed among naturally occurring variants, suggesting that the enzymes have continuously evolved to become more potent resistance genes.

Higher-order epistasis shapes the fitness landscape of a xenobiotic-degrading enzyme.

Characterizing the adaptive landscapes that encompass the emergence of novel enzyme functions can provide molecular insights into both enzymatic and evolutionary mechanisms. Here, we combine ancestral protein reconstruction with biochemical, structural and mutational analyses to characterize the functional evolution of methyl-parathion hydrolase (MPH), an organophosphate-degrading enzyme. We identify five mutations that are necessary and sufficient for the evolution of MPH from an ancestral dihydrocoumarin hydrolase. In-depth analyses of the adaptive landscapes encompassing this evolutionary transition revealed that the mutations form a complex interaction network, defined in part by higher-order epistasis, that constrained the adaptive pathways available. By also characterizing the adaptive landscapes in terms of their functional activities towards three additional organophosphate substrates, we reveal that subtle differences in the polarity of the substrate substituents drastically alter the network of epistatic interactions. Our work suggests that the mutations function collectively to enable substrate recognition via subtle structural repositioning.

Exploring the sequence, function, and evolutionary space of protein superfamilies using sequence similarity networks and phylogenetic reconstructions.

Integrative computational methods can facilitate the discovery of new protein functions and enzymatic reactions by enabling the observation and investigation of complex sequence-structure-function and evolutionary relationships within protein superfamilies. Here, we highlight the use of sequence similarity networks (SSNs) and phylogenetic reconstructions to map the functional divergence and evolutionary history of protein superfamilies. We exemplify this approach using the nitroreductase (NTR) flavoenzyme superfamily, demonstrating that SSN investigations can provide a rapid and effective means to classify groups of proteins, expose sequence similarity relationships across the global scale of a protein superfamily, and efficiently support detailed phylogenetic analyses. Integration of such approaches with systematic experimental characterization will expand our understanding of the functional diversity of enzymes, their evolution, and their associated physiological roles.