Fitness landscape of substrate-adaptive mutations in evolved amino acid-polyamine-organocation transporters

The emergence of new protein functions is crucial for the evolution of organisms. This process has been extensively researched for soluble enzymes, but it is largely unexplored for membrane transporters, even though the ability to acquire new nutrients from a changing environment requires evolvability of transport functions. Here, we demonstrate the importance of environmental pressure in obtaining a new activity or altering a promiscuous activity in members of the amino acid-polyamine-organocation (APC)-type yeast amino acid transporters family. We identify APC members that have broader substrate spectra than previously described. Using in vivo experimental evolution, we evolve two of these transporter genes, AGP1 and PUT4, toward new substrate specificities. Single mutations on these transporters are found to be sufficient for expanding the substrate range of the proteins, while retaining the capacity to transport all original substrates. Nonetheless, each adaptive mutation comes with a distinct effect on the fitness for each of the original substrates, illustrating a trade-off between the ancestral and evolved functions. Collectively, our findings reveal how substrate-adaptive mutations in membrane transporters contribute to fitness and provide insights into how organisms can use transporter evolution to explore new ecological niches.

Effects of selection stringency on the outcomes of directed evolution

Directed evolution makes mutant lineages compete in climbing complicated sequence-function landscapes. Given this underlying complexity it is unclear how selection stringency, a ubiquitous parameter of directed evolution, impacts the outcome. Here we approach this question in terms of the fitnesses of the candidate variants at each round and the heterogeneity of their distributions of fitness effects. We show that even if the fittest mutant is most likely to yield the fittest mutants in the next round of selection, diversification can improve outcomes by sampling a larger variety of fitness effects. We find that heterogeneity in fitness effects between variants, larger population sizes, and evolution over a greater number of rounds all encourage diversification.

Ancestral terpene cyclases: From fundamental science to applications in biosynthesis

Terpenes constitute one of the largest family of natural products with potent applications as renewable platform chemicals and medicines. The low activity, selectivity and stability displayed by terpene biosynthetic machineries can constitute an obstacle towards achieving expedient biosynthesis of terpenoids in processes that adhere to the 12 principles of green chemistry. Accordingly, engineering of terpene synthase enzymes is a prerequisite for industrial biotechnology applications, but obstructed by their complex catalysis that depend on reactive carbocationic intermediates that are prone to undergo bifurcation mechanisms. Rational redesign of terpene synthases can be tedious and requires high-resolution structural information, which is not always available. Furthermore, it has proven difficult to link sequence space of terpene synthase enzymes to specific product profiles. Herein, the author shows how ancestral sequence reconstruction (ASR) can favorably be used as a protein engineering tool in the redesign of terpene synthases without the need of a structure, and without excessive screening. A detailed workflow of ASR is presented along with associated limitations, with a focus on applying this methodology on terpene synthases. From selected examples of both class I and II enzymes, the author advocates that ancestral terpene cyclases constitute valuable assets to shed light on terpene-synthase catalysis and in enabling accelerated biosynthesis.

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.

High temperature delays and low temperature accelerates evolution of a new protein phenotype

Since the origin of life, temperatures on earth have fluctuated both on short and long time scales. How such changes affect the rate at which Darwinian evolution can bring forth new phenotypes remains unclear. On the one hand, high temperature may accelerate phenotypic evolution because it accelerates most biological processes. On the other hand, it may slow phenotypic evolution, because proteins are usually less stable at high temperatures and therefore less evolvable. Here, to test these hypotheses experimentally, we evolved a green fluorescent protein in E. coli towards the new phenotype of yellow fluorescence at different temperatures. Yellow fluorescence evolved most slowly at high temperature and most rapidly at low temperature, in contradiction to the first hypothesis. Using high-throughput population sequencing, protein engineering, and biochemical assays, we determined that this is due to the protein-destabilizing effect of neofunctionalizing mutations. Destabilization is highly detrimental at high temperature, where neofunctionalizing mutations cannot be tolerated. Their detrimental effects can be mitigated through excess stability at low temperature, leading to accelerated adaptive evolution. By modifying protein folding stability, temperature alters the accessibility of mutational paths towards high-fitness genotypes. Our observations have broad implications for our understanding of how temperature changes affect evolutionary adaptations and innovations.

Effects of environmental feedback on species with finite population

In an unchanging environment, natural selection always selects species with high fitness. In this study, we build a co-evolutionary system to study the interaction between stochasticity in finite populations and environmental feedback. Positive feedback between species and environment is detrimental to the invasion success, whereas negative feedback is beneficial to invasion since feedback makes population size important enough to revise natural selection's preference. In competition scenario, positive and negative feedback will benefit the initially inferior species. When selection intensity is high, negative feedback may even cause natural selection to favor the initially inferior species. All of these effects are caused by feedback that allows the initially inferior species to have greater fitness than the initially dominant species. Our results emphasize that the effects of stochasticity in evolutionary path can be reinforced by feedback with environment and then reverse the preference of natural selection.

Molecular mechanisms and evolutionary robustness of a color switch in proteorhodopsins

Proteorhodopsins are widely distributed photoreceptors from marine bacteria. Their discovery revealed a high degree of evolutionary adaptation to ambient light, resulting in blue- and green-absorbing variants that correlate with a conserved glutamine/leucine at position 105. On the basis of an integrated approach combining sensitivity-enhanced solid-state nuclear magnetic resonance (ssNMR) spectroscopy and linear-scaling quantum mechanics/molecular mechanics (QM/MM) methods, this single residue is shown to be responsible for a variety of synergistically coupled structural and electrostatic changes along the retinal polyene chain, ionone ring, and within the binding pocket. They collectively explain the observed color shift. Furthermore, analysis of the differences in chemical shift between nuclei within the same residues in green and blue proteorhodopsins also reveals a correlation with the respective degree of conservation. Our data show that the highly conserved color change mainly affects other highly conserved residues, illustrating a high degree of robustness of the color phenotype to sequence variation.

Red fluorescent proteins engineered from green fluorescent proteins

Fluorescent proteins (FPs) form a fluorophore through autocatalysis from three consecutive amino acid residues within a polypeptide chain. The two major groups, green FPs (GFPs) and red FPs (RFPs), have distinct fluorophore structures; RFPs have an extended π-conjugation system with an additional double bond. However, due to the low sequence homology between the two groups, amino acid residues essential for determining the different fluorophore structures were unclear. Therefore, engineering a GFP into an RFP has been challenging, and the exact mechanism of how GFPs and RFPs achieve different autocatalytic reactions remained elucidated. Here, we show the conversion of two coral GFPs, AzamiGreen (AG) and mcavGFP, into RFPs by defined mutations. Structural comparison of AG and AzamiRed1.0, an AG-derived RFP, revealed that the mutations triggered drastic rearrangements in the interaction networks between amino acid residues around the fluorophore, suggesting that coordinated multisite mutations are required for the green-to-red conversion. As a result of the structural rearrangements, a cavity suitable for the entry of an oxygen molecule, which is necessary for the double bond formation of the red fluorophores, is created in the proximity of the fluorophore. We also show that a monomeric variant of AzamiRed1.0 can be used for labeling organelles and proteins in mammalian cells. Our results provide a structural basis for understanding the red fluorophore formation mechanism and demonstrate that protein engineering of GFPs is a promising way to create RFPs suitable for fluorescent tags.

High-Accuracy Prediction of Stabilizing Surface Mutations to the Three-Helix Bundle, UBA(1), with EmCAST

The accurate modeling of energetic contributions to protein structure is a fundamental challenge in computational approaches to protein analysis and design. We describe a general computational method, EmCAST (empirical Cα stabilization), to score and optimize the sequence to the structure in proteins. The method relies on an empirical potential derived from the database of the Cα dihedral angle preferences for all possible four-residue sequences, using the data available in the Protein Data Bank. Our method produces stability predictions that naturally correlate one-to-one with the experimental results for solvent-exposed mutation sites. EmCAST predicted four mutations that increased the stability of a three-helix bundle, UBA(1), from 2.4 to 4.8 kcal/mol by optimizing residues in both helices and turns. For a set of eight variants, the predicted and experimental stabilizations correlate very well (R2 = 0.97) with a slope near 1 and with a 0.16 kcal/mol standard error for EmCAST predictions. Tests against literature data for the stability effects of surface-exposed mutations show that EmCAST outperforms the existing stability prediction methods. UBA(1) variants were crystallized to verify and analyze their structures at an atomic resolution. Thermodynamic and kinetic folding experiments were performed to determine the magnitude and mechanism of stabilization. Our method has the potential to enable the rapid, rational optimization of natural proteins, expand the analysis of the sequence/structure relationship, and supplement the existing protein design strategies.

Evolvability-enhancing mutations in the fitness landscapes of an RNA and a protein

Can evolvability-the ability to produce adaptive heritable variation-itself evolve through adaptive Darwinian evolution? If so, then Darwinian evolution may help create the conditions that enable Darwinian evolution. Here I propose a framework that is suitable to address this question with available experimental data on adaptive landscapes. I introduce the notion of an evolvability-enhancing mutation, which increases the likelihood that subsequent mutations in an evolving organism, protein, or RNA molecule are adaptive. I search for such mutations in the experimentally characterized and combinatorially complete fitness landscapes of a protein and an RNA molecule. I find that such evolvability-enhancing mutations indeed exist. They constitute a small fraction of all mutations, which shift the distribution of fitness effects of subsequent mutations towards less deleterious mutations, and increase the incidence of beneficial mutations. Evolving populations which experience such mutations can evolve significantly higher fitness. The study of evolvability-enhancing mutations opens many avenues of investigation into the evolution of evolvability.

Marginal specificity in protein interactions constrains evolution of a paralogous family

The evolution of novel functions in biology relies heavily on gene duplication and divergence, creating large paralogous protein families. Selective pressure to avoid detrimental cross-talk often results in paralogs that exhibit exquisite specificity for their interaction partners. But how robust or sensitive is this specificity to mutation? Here, using deep mutational scanning, we demonstrate that a paralogous family of bacterial signaling proteins exhibits marginal specificity, such that many individual substitutions give rise to substantial cross-talk between normally insulated pathways. Our results indicate that sequence space is locally crowded despite overall sparseness, and we provide evidence that this crowding has constrained the evolution of bacterial signaling proteins. These findings underscore how evolution selects for "good enough" rather than optimized phenotypes, leading to restrictions on the subsequent evolution of paralogs.

Improving ethanol tolerance of ethyl carbamate hydrolase by diphasic high pressure molecular dynamic simulations

Ethyl carbamate (EC) is mainly found in fermented foods and fermented alcoholic beverages, which could cause carcinogenic potential to humans. Reducing EC is one of the key research priorities to address security of fermented foods. Enzymatic degradation of EC with EC hydrolase in food is the most reliable and efficient method. However, poor tolerance to ethanol severely hinders application of EC hydrolase. In this study, the mutants of EC hydrolase were screened by diphasic high pressure molecular dynamic simulations (dHP-MD). The best variant with remarkable improvement in specific activity and was H68A/K70R/S325N, whose specific activity was approximately 3.42-fold higher than WT, and relative enzyme activity under 20% (v/v) was 5.02-fold higher than WT. Moreover, the triple mutant increased its stability by acquiring more hydration shell and forming extra hydrogen bonds. Furthermore, the ability of degrading EC of the immobilized triple mutant was both detected in mock wine and under certain reaction conditions. The stability of immobilized triple mutant and WT were both improved, and immobilized triple mutant degraded nearly twice as much EC as that of immobilized WT. Overall, dHP-MD was proved to effectively improve enzyme activity and ethanol tolerance for extent application at industrial scale.

Global Analysis of Multi-Mutants to Improve Protein Function

The identification of amino acid substitutions that both enhance the stability and function of a protein is a key challenge in protein engineering. Technological advances have enabled assaying thousands of protein variants in a single high-throughput experiment, and more recent studies use such data in protein engineering. We present a Global Multi-Mutant Analysis (GMMA) that exploits the presence of multiply-substituted variants to identify individual amino acid substitutions that are beneficial for the stability and function across a large library of protein variants. We have applied GMMA to a previously published experiment reporting on >54,000 variants of green fluorescent protein (GFP), each with known fluorescence output, and each carrying 1-15 amino acid substitutions (Sarkisyan et al., 2016). The GMMA method achieves a good fit to this dataset while being analytically transparent. We show experimentally that the six top-ranking substitutions progressively enhance GFP. More broadly, using only a single experiment as input our analysis recovers nearly all the substitutions previously reported to be beneficial for GFP folding and function. In conclusion, we suggest that large libraries of multiply-substituted variants may provide a unique source of information for protein engineering.

Adaptive Evolution and Metabolic Engineering Boost Lycopene Production in Saccharomyces cerevisiae via Enhanced Precursors Supply and Utilization

Lycopene is a red carotenoid with remarkable antioxidant activity, which has been widely used in food, cosmetics, medicine, and other industries. Production of lycopene in Saccharomyces cerevisiae provides an economic and sustainable means. Many efforts have been done in recent years, but the titer of lycopene seems to reach a ceiling. Enhancing the supply and utilization of farnesyl diphosphate (FPP) is generally regarded as an efficient strategy for terpenoid production. Herein, an integrated strategy by means of atmospheric and room-temperature plasma (ARTP) mutagenesis combined with H₂O₂-induced adaptive laboratory evolution (ALE) was proposed to improve the supply of upstream metabolic flux toward FPP. Enhancing the expression of CrtE and introducing an engineered CrtI mutant (Y160F&N576S) increased the utilization of FPP toward lycopene. Consequently, the titer of lycopene in the strain harboring the Ura3 marker was increased by 60% to 703 mg/L (89.3 mg/g DCW) at the shake-flask level. Eventually, the highest reported titer of 8.15 g/L of lycopene in S. cerevisiae was achieved in a 7 L bioreactor. The study highlights an effective strategy that the synergistic complementarity of metabolic engineering and adaptive evolution facilitates natural product synthesis.

Deep mutational scanning of essential bacterial proteins can guide antibiotic development

Deep mutational scanning is a powerful approach to investigate a wide variety of research questions including protein function and stability. Here, we perform deep mutational scanning on three essential E. coli proteins (FabZ, LpxC and MurA) involved in cell envelope synthesis using high-throughput CRISPR genome editing, and study the effect of the mutations in their original genomic context. We use more than 17,000 variants of the proteins to interrogate protein function and the importance of individual amino acids in supporting viability. Additionally, we exploit these libraries to study resistance development against antimicrobial compounds that target the selected proteins. Among the three proteins studied, MurA seems to be the superior antimicrobial target due to its low mutational flexibility, which decreases the chance of acquiring resistance-conferring mutations that simultaneously preserve MurA function. Additionally, we rank anti-LpxC lead compounds for further development, guided by the number of resistance-conferring mutations against each compound. Our results show that deep mutational scanning studies can be used to guide drug development, which we hope will contribute towards the development of novel antimicrobial therapies.

Genetic complementation fosters evolvability in complex fitness landscapes

The ability of natural selection to optimize traits depends on the topology of the genotype-fitness map (fitness landscape). Epistatic interactions produce rugged fitness landscapes, where adaptation is constrained by the presence of low-fitness intermediates. Here, we used simulations to explore how evolvability in rugged fitness landscapes is influenced by genetic complementation, a process whereby different sequence variants mutually compensate for their deleterious mutations. We designed our model inspired by viral populations, in which genetic variants are known to interact frequently through coinfection. Our simulations indicate that genetic complementation enables a more efficient exploration of rugged fitness landscapes. Although this benefit may be undermined by genetic parasites, its overall effect on evolvability remains positive in populations that exhibit strong relatedness between interacting sequences. Similar processes could operate in contexts other than viral coinfection, such as in the evolution of ploidy.

Exploring the expanse between theoretical questions and experimental approaches in the modern study of evolvability

Despite several decades of computational and experimental work across many systems, evolvability remains on the periphery with regards to its status as a widely accepted and regularly applied theoretical concept. Here we propose that its marginal status is partly a result of large gaps between the diverse but disconnected theoretical treatments of evolvability and the relatively narrower range of studies that have tested it empirically. To make this case, we draw on a range of examples-from experimental evolution in microbes, to molecular evolution in proteins-where attempts have been made to mend this disconnect. We highlight some examples of progress that has been made and point to areas where synthesis and translation of existing theory can lead to further progress in the still-new field of empirical measurements of evolvability.

DHFR Mutants Modulate Their Synchronized Dynamics with the Substrate by Shifting Hydrogen Bond Occupancies

Antibiotic resistance is a global health problem in which mutations occurring in functional proteins render drugs ineffective. The working mechanisms of the arising mutants are seldom apparent; a methodology to decipher these mechanisms systematically would render devising therapies to control the arising mutational pathways possible. Here we utilize C_α-C_β bond vector relaxations obtained from moderate length MD trajectories to determine conduits for functionality of the resistance conferring mutants of Escherichia coli dihydrofolate reductase. We find that the whole enzyme is synchronized to the motions of the substrate, irrespective of the mutation introducing gain-of-function or loss-of function. The total coordination of the motions suggests changes in the hydrogen bond dynamics with respect to the wild type as a possible route to determine and classify the mode-of-action of individual mutants. As a result, nine trimethoprim-resistant point mutations arising frequently in evolution experiments are categorized. One group of mutants that display the largest occurrence (L28R, W30G) work directly by modifying the dihydrofolate binding region. Conversely, W30R works indirectly by the formation of the E139-R30 salt bridge which releases energy resulting from tight binding by distorting the binding cavity. A third group (D27E, F153S, I94L) arising as single, resistance invoking mutants in evolution experiment trajectories allosterically and dynamically affects a hydrogen bonding motif formed at residues 59-69-71 which in turn modifies the binding site dynamics. The final group (I5F, A26T, R98P) consists of those mutants that have properties most similar to the wild type; these only appear after one of the other mutants is fixed on the protein structure and therefore display clear epistasis. Thus, we show that the binding event is governed by the entire enzyme dynamics while the binding site residues play gating roles. The adjustments made in the total enzyme in response to point mutations are what make quantifying and pinpointing their effect a hard problem. Here, we show that hydrogen bond dynamics recorded on sub-μs time scales provide the necessary fingerprints to decipher the various mechanisms at play.

Bacterial Hsp90 predominantly buffers but does not potentiate the phenotypic effects of deleterious mutations during fluorescent protein evolution

Chaperones facilitate the folding of other ("client") proteins and can thus affect the adaptive evolution of these clients. Specifically, chaperones affect the phenotype of proteins via two opposing mechanisms. On the one hand, they can buffer the effects of mutations in proteins and thus help preserve an ancestral, premutation phenotype. On the other hand, they can potentiate the effects of mutations and thus enhance the phenotypic changes caused by a mutation. We study that how the bacterial Hsp90 chaperone (HtpG) affects the evolution of green fluorescent protein. To this end, we performed directed evolution of green fluorescent protein under low and high cellular concentrations of Hsp90. Specifically, we evolved green fluorescent protein under both stabilizing selection for its ancestral (green) phenotype and directional selection toward a new (cyan) phenotype. While Hsp90 did only affect the rate of adaptive evolution transiently, it did affect the phenotypic effects of mutations that occurred during adaptive evolution. Specifically, Hsp90 allowed strongly deleterious mutations to accumulate in evolving populations by buffering their effects. Our observations show that the role of a chaperone for adaptive evolution depends on the organism and the trait being studied.

Protein-Glutaminase Engineering Based on Isothermal Compressibility Perturbation for Enhanced Modification of Soy Protein Isolate

Protein-glutaminase plays a significant role in future food (e.g., plant-based meat) processing as a result of its ability to improve the solubility, foaming, emulsifying, and gel properties of plant-based proteins. However, poor stability, activity, high pressure, and high shear processing environments hinder its application. Therefore, we developed an application-oriented method isothermal compressibility perturbation engineering strategy to improve enzyme performance by simulating the high-pressure environment. The best variant with remarkable improvement in specific activity and half-time, N16M/Q21H/T113E, exhibited a 4.28-fold increase compared to the wild type in specific activity (117.18 units/mg) and a 1.23-fold increase in half-time (472 min), as one of the highest comprehensive performances ever reported. The solubility of the soy protein isolate deaminated by the N16M/Q21H/T113E mutant was 55.74% higher than that deaminated by the wild type, with a tinier particle size and coarser texture. Overall, this strategy has the potential to improve the functional performance of enzymes under complex food processing conditions.

Adaptive evolvability through direct selection instead of indirect, second-order selection

Can evolvability itself be the product of adaptive evolution? To answer this question is challenging, because any DNA mutation that alters only evolvability is subject to indirect, "second order" selection on the future effects of this mutation. Such indirect selection is weaker than "first-order" selection on mutations that alter fitness, in the sense that it can operate only under restrictive conditions. Here I discuss a route to adaptive evolvability that overcomes this challenge. Specifically, a recent evolution experiment showed that some mutations can enhance both fitness and evolvability through a combination of direct and indirect selection. Unrelated evidence from gene duplication and the evolution of gene regulation suggests that mutations with such dual effects may not be rare. Through such mutations, evolvability may increase at least in part because it provides an adaptive advantage. These observations suggest a research program on the adaptive evolution of evolvability, which aims to identify such mutations and to disentangle their direct fitness effects from their indirect effects on evolvability. If evolvability is itself adaptive, Darwinian evolution may have created more than life's diversity. It may also have helped create the very conditions that made the success of Darwinian evolution possible.

Nramp: Deprive and conquer?

Solute carriers 11 (Slc11) evolved from bacterial permease (MntH) to eukaryotic antibacterial defense (Nramp) while continuously mediating proton (H⁺)-dependent manganese (Mn²⁺) import. Also, Nramp horizontal gene transfer (HGT) toward bacteria led to mntH polyphyly. Prior demonstration that evolutionary rate-shifts distinguishing Slc11 from outgroup carriers dictate catalytic specificity suggested that resolving Slc11 family tree may provide a function-aware phylogenetic framework. Hence, MntH C (MC) subgroups resulted from HGTs of prototype Nramp (pNs) parologs while archetype Nramp (aNs) correlated with phagocytosis. PHI-Blast based taxonomic profiling confirmed MntH B phylogroup is confined to anaerobic bacteria vs. MntH A (MA)’s broad distribution; suggested niche-related spread of MC subgroups; established that MA-variant MH, which carries ‘eukaryotic signature’ marks, predominates in archaea. Slc11 phylogeny shows MH is sister to Nramp. Site-specific analysis of Slc11 charge network known to interact with the protonmotive force demonstrates sequential rate-shifts that recapitulate Slc11 evolution. 3D mapping of similarly coevolved sites across Slc11 hydrophobic core revealed successive targeting of discrete areas. The data imply that pN HGT could advantage recipient bacteria for H⁺-dependent Mn²⁺ acquisition and Alphafold 3D models suggest conformational divergence among MC subgroups. It is proposed that Slc11 originated as a bacterial stress resistance function allowing Mn²⁺-dependent persistence in conditions adverse for growth, and that archaeal MH could contribute to eukaryogenesis as a Mn²⁺ sequestering defense perhaps favoring intracellular growth-competent bacteria.

A Trait-Based Approach to Predicting Viral Host-Range Evolvability

Predicting the evolution of virus host range has proven to be extremely difficult, in part because of the sheer diversity of viruses, each with unique biology and ecological interactions. We have not solved this problem, but to make the problem more tractable, we narrowed our focus to three traits intrinsic to all viruses that may play a role in host-range evolvability: mutation rate, recombination rate, and phenotypic heterogeneity. Although each trait should increase evolvability, they cannot do so unbounded because fitness trade-offs limit the ability of all three traits to maximize evolvability. By examining these constraints, we can begin to identify groups of viruses with suites of traits that make them especially concerning, as well as ecological and environmental conditions that might push evolution toward accelerating host-range expansion.

Phenotypic mutations contribute to protein diversity and shape protein evolution

Errors in DNA replication generate genetic mutations, while errors in transcription and translation lead to phenotypic mutations. Phenotypic mutations are orders of magnitude more frequent than genetic ones, yet they are less understood. Here, we review the types of phenotypic mutations, their quantifications, and their role in protein evolution and disease. The diversity generated by phenotypic mutation can facilitate adaptive evolution. Indeed, phenotypic mutations, such as ribosomal frameshift and stop codon readthrough, sometimes serve to regulate protein expression and function. Phenotypic mutations have often been linked to fitness decrease and diseases. Thus, understanding the protein heterogeneity and phenotypic diversity caused by phenotypic mutations will advance our understanding of protein evolution and have implications on human health and diseases.

Experimental exploration of a ribozyme neutral network using evolutionary algorithm and deep learning

A neutral network connects all genotypes with equivalent phenotypes in a fitness landscape and plays an important role in the mutational robustness and evolvability of biomolecules. In contrast to earlier theoretical works, evidence of large neutral networks has been lacking in recent experimental studies of fitness landscapes. This suggests that evolution could be constrained globally. Here, we demonstrate that a deep learning-guided evolutionary algorithm can efficiently identify neutral genotypes within the sequence space of an RNA ligase ribozyme. Furthermore, we measure the activities of all 2¹⁶ variants connecting two active ribozymes that differ by 16 mutations and analyze mutational interactions (epistasis) up to the 16th order. We discover an extensive network of neutral paths linking the two genotypes and reveal that these paths might be predicted using only information from lower-order interactions. Our experimental evaluation of over 120,000 ribozyme sequences provides important empirical evidence that neutral networks can increase the accessibility and predictability of the fitness landscape.

Neutral networks, which are sets of genotypes connected via single mutations that share the same phenotype, are important for evolvability. Here, the authors provide experimental evidence of a neutral network in an RNA enzyme using a high-throughput assay and deep learning.

Low protein expression enhances phenotypic evolvability by intensifying selection on folding stability

Protein abundance affects the evolution of protein genotypes, but we do not know how it affects the evolution of protein phenotypes. Here we investigate the role of protein abundance in the evolvability of green fluorescent protein (GFP) towards the novel phenotype of cyan fluorescence. We evolve GFP in E. coli through multiple cycles of mutation and selection and show that low GFP expression facilitates the evolution of cyan fluorescence. A computational model whose predictions we test experimentally helps explain why: lowly expressed proteins are under stronger selection for proper folding, which facilitates their evolvability on short evolutionary time scales. The reason is that high fluorescence can be achieved by either few proteins that fold well or by many proteins that fold less well. In other words, we observe a synergy between a protein's scarcity and its stability. Because many proteins meet the essential requirements for this scarcity-stability synergy, it may be a widespread mechanism by which low expression helps proteins evolve new phenotypes and functions.

Protective effect of the stressed supernatant from Lactococcus lactis subsp. lactis and its metabolic analysis

There are numerous factors restricting wide application of lactic acid bacteria (LAB) in dairy industry, causing urgent demands for novel bioprotectants. Protective effects and metabolites of Lactococcus lactis subsp. lactis (L. lactis) from ultraviolet (UV)-induced supernatant were investigated and the protective mechanism was explored. The strain viability of the group treated with the supernatant of continuous UV irradiation (V1) and the group with intermittent UV irradiation (V2) was 8.45 and 14.13 times of the control group, respectively. Further exploration on the protective of L. lactis supernatant, under different dose of UV treatment, showed it was dose-dependent. The condition for the supernatant with best protective effect was vertical distance 50.00 cm, horizontal distance 25.00 cm, intermittent UV irradiation (30 s interval 30 s) for 4.5 min (V2), which was chose for untargeted metabolite analysis. And that in V1 was for comparative study. There were 181 up-regulated metabolites in V1 and 161 up-regulated metabolites in V2, respectively. Most of the up-regulated metabolites were related to secondary metabolite synthesis, environmental microbial metabolism, antibiotic synthesis and amino acid biosynthesis. Notably, production of dithiothreitol (DTT) in V2 was 65.2-fold higher than that in the control group. Trehalose in ABC transporter pathway was also up-regulated in the metabolites induced by UV. Results indicated that L. lactis could adapt to the UV stress by adjusting metabolic pathways and producing special metabolites to protect itself. This research offers the basis for robust strain development and contributes to initial study on potential bioprotectant.

Thermoadaptation in an Ancestral Diterpene Cyclase by Altered Loop Stability

Thermostability is the key to maintain the structural integrity and catalytic activity of enzymes in industrial biotechnological processes, such as terpene cyclase-mediated generation of medicines, chiral synthons, and fine chemicals. However, affording a large increase in the thermostability of enzymes through site-directed protein engineering techniques can constitute a challenge. In this paper, we used ancestral sequence reconstruction to create a hyperstable variant of the ent-copalyl diphosphate synthase PtmT2, a terpene cyclase involved in the assembly of antibiotics. Molecular dynamics simulations on the μs timescale were performed to shed light on possible molecular mechanisms contributing to activity at an elevated temperature and the large 40 °C increase in melting temperature observed for an ancestral variant of PtmT2. In silico analysis revealed key differences in the flexibility of a loop capping the active site, between extant and ancestral proteins. For the modern enzyme, the loop collapses into the active site at elevated temperatures, thus preventing biocatalysis, whereas the loop remains in a productive conformation both at ambient and high temperatures in the ancestral variant. Restoring a Pro loop residue introduced in the ancestral variant to the corresponding Gly observed in the extant protein led to reduced catalytic activity at high temperatures, with only moderate effects on the melting temperature, supporting the importance of the flexibility of the capping loop in thermoadaptation. Conversely, the inverse Gly to Pro loop mutation in the modern enzyme resulted in a 3-fold increase in the catalytic rate. Despite an overall decrease in maximal activity of ancestor compared to wild type, its increased thermostability provides a robust backbone amenable for further enzyme engineering. Our work cements the importance of loops in enzyme catalysis and provides a molecular mechanism contributing to thermoadaptation in an ancestral enzyme.

Co-evolution of interacting proteins through non-contacting and non-specific mutations

Proteins often accumulate neutral mutations that do not affect current functions but can profoundly influence future mutational possibilities and functions. Understanding such hidden potential has major implications for protein design and evolutionary forecasting but has been limited by a lack of systematic efforts to identify potentiating mutations. Here, through the comprehensive analysis of a bacterial toxin-antitoxin system, we identified all possible single substitutions in the toxin that enable it to tolerate otherwise interface-disrupting mutations in its antitoxin. Strikingly, the majority of enabling mutations in the toxin do not contact and promote tolerance non-specifically to many different antitoxin mutations, despite covariation in homologues occurring primarily between specific pairs of contacting residues across the interface. In addition, the enabling mutations we identified expand future mutational paths that both maintain old toxin-antitoxin interactions and form new ones. These non-specific mutations are missed by widely used covariation and machine learning methods. Identifying such enabling mutations will be critical for ensuring continued binding of therapeutically relevant proteins, such as antibodies, aimed at evolving targets.

Secretory quality control constrains functional selection-associated protein structure innovation

Biophysical models suggest a dominant role of structural over functional constraints in shaping protein evolution. Selection on structural constraints is linked closely to expression levels of proteins, which together with structure-associated activities determine in vivo functions of proteins. Here we show that despite the up to two orders of magnitude differences in levels of C-reactive protein (CRP) in distinct species, the in vivo functions of CRP are paradoxically conserved. Such a pronounced level-function mismatch cannot be explained by activities associated with the conserved native structure, but is coupled to hidden activities associated with the unfolded, activated conformation. This is not the result of selection on structural constraints like foldability and stability, but is achieved by folding determinants-mediated functional selection that keeps a confined carrier structure to pass the stringent eukaryotic quality control on secretion. Further analysis suggests a folding threshold model which may partly explain the mismatch between the vast sequence space and the limited structure space of proteins.

The mismatch in the conserved structure but different expression levels of C-reactive protein (CRP) in distinct species is reconciled by functional selection on hidden activities of unfolded CRPs.

GroEL/S overexpression helps to purge deleterious mutations and reduce genetic diversity during adaptive protein evolution

Chaperones are proteins that help other proteins fold. They also affect the adaptive evolution of their client proteins by buffering the effect of deleterious mutations and increasing the genetic diversity of evolving proteins. We study how the bacterial chaperone GroE (GroEL + GroES) affects the evolution of green fluorescent protein (GFP). To this end we subjected GFP to multiple rounds of mutation and selection for its color phenotype in four replicate E. coli populations, and studied its evolutionary dynamics through high-throughput sequencing and mutant engineering. We evolved GFP both under stabilizing selection for its ancestral (green) phenotype, and to directional selection for a new (cyan) phenotype. We did so both under low and high expression of the chaperone GroE. In contrast to previous work, we observe that GroE does not just buffer but also helps purge deleterious (fluorescence reducing) mutations from evolving populations. In doing so, GroE helps reduce the genetic diversity of evolving populations. In addition, it causes phenotypic heterogeneity in mutants with the same genotype, helping to enhance their fluorescence in some cells, and reducing it in others. Our observations show that chaperones can affect adaptive evolution in more than one way.

Heterogeneity of the GFP fitness landscape and data-driven protein design

Studies of protein fitness landscapes reveal biophysical constraints guiding protein evolution and empower prediction of functional proteins. However, generalisation of these findings is limited due to scarceness of systematic data on fitness landscapes of proteins with a defined evolutionary relationship. We characterized the fitness peaks of four orthologous fluorescent proteins with a broad range of sequence divergence. While two of the four studied fitness peaks were sharp, the other two were considerably flatter, being almost entirely free of epistatic interactions. Mutationally robust proteins, characterized by a flat fitness peak, were not optimal templates for machine-learning-driven protein design - instead, predictions were more accurate for fragile proteins with epistatic landscapes. Our work paves insights for practical application of fitness landscape heterogeneity in protein engineering.

Rational Design of Protein-Specific Folding Modifiers

Protein-folding can go wrong in vivo and in vitro, with significant consequences for the living organism and the pharmaceutical industry, respectively. Here we propose a design principle for small-peptide-based protein-specific folding modifiers. The principle is based on constructing a "xenonucleus", which is a prefolded peptide that mimics the folding nucleus of a protein. Using stopped-flow kinetics, NMR spectroscopy, Förster resonance energy transfer, single-molecule force measurements, and molecular dynamics simulations, we demonstrate that a xenonucleus can make the refolding of ubiquitin faster by 33 ± 5%, while variants of the same peptide have little or no effect. Our approach provides a novel method for constructing specific, genetically encodable folding catalysts for suitable proteins that have a well-defined contiguous folding nucleus.

AMaLa: Analysis of Directed Evolution Experiments via Annealed Mutational Approximated Landscape

We present Annealed Mutational approximated Landscape (AMaLa), a new method to infer fitness landscapes from Directed Evolution experiments sequencing data. Such experiments typically start from a single wild-type sequence, which undergoes Darwinian in vitro evolution via multiple rounds of mutation and selection for a target phenotype. In the last years, Directed Evolution is emerging as a powerful instrument to probe fitness landscapes under controlled experimental conditions and as a relevant testing ground to develop accurate statistical models and inference algorithms (thanks to high-throughput screening and sequencing). Fitness landscape modeling either uses the enrichment of variants abundances as input, thus requiring the observation of the same variants at different rounds or assuming the last sequenced round as being sampled from an equilibrium distribution. AMaLa aims at effectively leveraging the information encoded in the whole time evolution. To do so, while assuming statistical sampling independence between sequenced rounds, the possible trajectories in sequence space are gauged with a time-dependent statistical weight consisting of two contributions: (i) an energy term accounting for the selection process and (ii) a generalized Jukes-Cantor model for the purely mutational step. This simple scheme enables accurately describing the Directed Evolution dynamics and inferring a fitness landscape that correctly reproduces the measures of the phenotype under selection (e.g., antibiotic drug resistance), notably outperforming widely used inference strategies. In addition, we assess the reliability of AMaLa by showing how the inferred statistical model could be used to predict relevant structural properties of the wild-type sequence.

Rate-Perturbing Single Amino Acid Mutation for Hydrolases: A Statistical Profiling

Hydrolases are a critical component for modern chemical, pharmaceutical, and environmental sciences. Identifying mutations that enhance catalytic efficiency presents a roadblock to design and to discover new hydrolases for broad academic and industrial uses. Here, we report the statistical profiling for rate-perturbing mutant hydrolases with a single amino acid substitution. We constructed an integrated structure-kinetics database for hydrolases, IntEnzyDB, which contains 3907 k_cats, 4175 K_Ms, and 2715 Protein Data Bank IDs. IntEnzyDB adopts a relational architecture with a flattened data structure, enabling facile and efficient access to clean and tabulated data for machine learning uses. We conducted statistical analyses on how single amino acids mutations influence the turnover number (i.e., k_cat) and efficiency (i.e., k_cat/K_M), with a particular emphasis on profiling the features for rate-enhancing mutations. The results show that mutation to bulky nonpolar residues with a hydrocarbon chain involves a higher likelihood for rate acceleration than to other types of residues. Linear regression models reveal geometric descriptors of substrate and mutation residues that mediate rate-perturbing outcomes for hydrolases with bulky nonpolar mutations. On the basis of the analyses of the structure-kinetics relationship, we observe that the propensity for rate enhancement is independent of protein sizes. In addition, we observe that distal mutations (i.e., >10 Å from the active site) in hydrolases are significantly more prone to induce efficiency neutrality and avoid efficiency deletion but involve similar propensity for rate enhancement. The studies reveal the statistical features for identifying rate-enhancing mutations in hydrolases, which will potentially guide hydrolase discovery in biocatalysis.

Natural variation in the consequences of gene overexpression and its implications for evolutionary trajectories

Copy number variation through gene or chromosome amplification provides a route for rapid phenotypic variation and supports the long-term evolution of gene functions. Although the evolutionary importance of copy-number variation is known, little is understood about how genetic background influences its tolerance. Here, we measured fitness costs of over 4000 overexpressed genes in 15 Saccharomyces cerevisiae strains representing different lineages, to explore natural variation in tolerating gene overexpression (OE). Strain-specific effects dominated the fitness costs of gene OE. We report global differences in the consequences of gene OE, independent of the amplified gene, as well as gene-specific effects that were dependent on the genetic background. Natural variation in the response to gene OE could be explained by several models, including strain-specific physiological differences, resource limitations, and regulatory sensitivities. This work provides new insight on how genetic background influences tolerance to gene amplification and the evolutionary trajectories accessible to different backgrounds.

Ribose-Binding Protein Mutants With Improved Interaction Towards the Non-natural Ligand 1,3-Cyclohexanediol

Bioreporters consist of genetically modified living organisms that respond to the presence of target chemical compounds by production of an easily measurable signal. The central element in a bioreporter is a sensory protein or aptamer, which, upon ligand binding, modifies expression of the reporter signal protein. A variety of naturally occurring or modified versions of sensory elements has been exploited, but it has proven to be challenging to generate elements that recognize non-natural ligands. Bacterial periplasmic binding proteins have been proposed as a general scaffold to design receptor proteins for non-natural ligands, but despite various efforts, with only limited success. Here, we show how combinations of randomized mutagenesis and reporter screening improved the performance of a set of mutants in the ribose binding protein (RbsB) of Escherichia coli, which had been designed based on computational simulations to bind the non-natural ligand 1,3-cyclohexanediol (13CHD). Randomized mutant libraries were constructed that used the initially designed mutants as scaffolds, which were cloned in an appropriate E. coli bioreporter system and screened for improved induction of the GFPmut2 reporter fluorescence in presence of 1,3-cyclohexanediol. Multiple rounds of library screening, sorting, renewed mutagenesis and screening resulted in 4.5-fold improvement of the response to 1,3-cyclohexanediol and a lower detection limit of 0.25 mM. All observed mutations except one were located outside the direct ligand-binding pocket, suggesting they were compensatory and helping protein folding or functional behavior other than interaction with the ligand. Our results thus demonstrate that combinations of ligand-binding-pocket redesign and randomized mutagenesis can indeed lead to the selection and recovery of periplasmic-binding protein mutants with non-natural compound recognition. However, current lack of understanding of the intermolecular movement and ligand-binding in periplasmic binding proteins such as RbsB are limiting the rational production of further and better sensory mutants.

Mistranslation reduces mutation load in evolving proteins through negative epistasis with DNA mutations

Translational errors during protein synthesis cause phenotypic mutations that are several orders of magnitude more frequent than DNA mutations. Such phenotypic mutations may affect adaptive evolution through their interactions with DNA mutations. To study how mistranslation may affect the adaptive evolution of evolving proteins, we evolved populations of green fluorescent protein (GFP) in either high-mistranslation or low-mistranslation Escherichia coli hosts. In both hosts, we first evolved GFP under purifying selection for the ancestral phenotype green fluorescence, and then under directional selection toward the new phenotype yellow fluorescence. High-mistranslation populations evolved modestly higher yellow fluorescence during each generation of evolution than low-mistranslation populations. We demonstrate by high-throughput sequencing that elevated mistranslation reduced the accumulation of deleterious DNA mutations under both purifying and directional selection. It did so by amplifying the fitness effects of deleterious DNA mutations through negative epistasis with phenotypic mutations. In contrast, mistranslation did not affect the incidence of beneficial mutations. Our findings show that phenotypic mutations interact epistatically with DNA mutations. By reducing a population’s mutation load, mistranslation can affect an important determinant of evolvability.

Structurally distributed surface sites tune allosteric regulation

Our ability to rationally optimize allosteric regulation is limited by incomplete knowledge of the mutations that tune allostery. Are these mutations few or abundant, structurally localized or distributed? To examine this, we conducted saturation mutagenesis of a synthetic allosteric switch in which Dihydrofolate reductase (DHFR) is regulated by a blue-light sensitive LOV2 domain. Using a high-throughput assay wherein DHFR catalytic activity is coupled to E. coli growth, we assessed the impact of 1548 viable DHFR single mutations on allostery. Despite most mutations being deleterious to activity, fewer than 5% of mutations had a statistically significant influence on allostery. Most allostery disrupting mutations were proximal to the LOV2 insertion site. In contrast, allostery enhancing mutations were structurally distributed and enriched on the protein surface. Combining several allostery enhancing mutations yielded near-additive improvements to dynamic range. Our results indicate a path toward optimizing allosteric function through variation at surface sites.

Many proteins exhibit a property called ‘allostery’. In allostery, an input signal at a specific site of a protein – such as a molecule binding, or the protein absorbing a photon of light – leads to a change in output at another site far away. For example, the protein might catalyze a chemical reaction faster or bind to another molecule more tightly in the presence of the input signal. This protein ‘remote control’ allows cells to sense and respond to changes in their environment. An ability to rapidly engineer new allosteric mechanisms into proteins is much sought after because this would provide an approach for building biosensors and other useful tools. One common approach to engineering new allosteric regulation is to combine a ‘sensor’ or input region from one protein with an ‘output’ region or domain from another.

When researchers engineer allostery using this approach of combining input and output domains from different proteins, the difference in the output when the input is ‘on’ versus ‘off’ is often small, a situation called ‘modest allostery’. McCormick et al. wanted to know how to optimize this domain combination approach to increase the difference in output between the ‘on’ and ‘off’ states.

More specifically, McCormick et al. wanted to find out whether swapping out or mutating specific amino acids (each of the individual building blocks that make up a protein) enhances or disrupts allostery. They also wanted to know if there are many possible mutations that change the effectiveness of allostery, or if this property is controlled by just a few amino acids. Finally, McCormick et al. questioned where in a protein most of these allostery-tuning mutations were located.

To answer these questions, McCormick et al. engineered a new allosteric protein by inserting a light-sensing domain (input) into a protein involved in metabolism (a metabolic enzyme that produces a biomolecule called a tetrahydrofolate) to yield a light-controlled enzyme. Next, they introduced mutations into both the ‘input’ and ‘output’ domains to see where they had a greater effect on allostery.

After filtering out mutations that destroyed the function of the output domain, McCormick et al. found that only about 5% of mutations to the ‘output’ domain altered the allosteric response of their engineered enzyme. In fact, most mutations that disrupted allostery were found near the site where the ‘input’ domain was inserted, while mutations that enhanced allostery were sprinkled throughout the enzyme, often on its protein surface. This was surprising in light of the commonly-held assumption that mutations on protein surfaces have little impact on the activity of the ‘output’ domain. Overall, the effect of individual mutations on allostery was small, but McCormick et al. found that these mutations can sometimes be combined to yield larger effects.

McCormick et al.’s results suggest a new approach for optimizing engineered allosteric proteins: by introducing mutations on the protein surface. It also opens up new questions: mechanically, how do surface sites affect allostery? In the future, it will be important to characterize how combinations of mutations can optimize allosteric regulation, and to determine what evolutionary trajectories to high performance allosteric ‘switches’ look like.

Structural genomics approach to investigate deleterious impact of nsSNPs in conserved telomere maintenance component 1

Conserved telomere maintenance component 1 (CTC1) is an important component of the CST (CTC1-STN1-TEN1) complex, involved in maintaining the stability of telomeric DNA. Several non-synonymous single-nucleotide polymorphisms (nsSNPs) in CTC1 have been reported to cause Coats plus syndrome and Dyskeratosis congenital diseases. Here, we have performed sequence and structure analyses of nsSNPs of CTC1 using state-of-the-art computational methods. The structure-based study focuses on the C-terminal OB-fold region of CTC1. There are 11 pathogenic mutations identified, and detailed structural analyses were performed. These mutations cause a significant disruption of noncovalent interactions, which may be a possible reason for CTC1 instability and consequent diseases. To see the impact of such mutations on the protein conformation, all-atom molecular dynamics (MD) simulations of CTC1-wild-type (WT) and two of the selected mutations, R806C and R806L for 200 ns, were carried out. A significant conformational change in the structure of the R806C mutant was observed. This study provides a valuable direction to understand the molecular basis of CTC1 dysfunction in disease progression, including Coats plus syndrome.

Protecting P-type plasma membrane H+-ATPases from ROS

P-type ATPase are ubiquitous transport proteins across all kingdoms of life. These proteins share a common mechanism involving phosphorylation of an invariant aspartate to facilitate movement of substrates from protons to phospholipids across cellular membranes. In this issue of the Biochemical Journal, Welle et al. identify a conserved cysteine near the functionally critical aspartate of P-type plasma membrane H+-ATPases that protects the protein from reactive oxygen species.

Mutational and biophysical robustness in a prestabilized monobody

The fibronectin type III (FN3) monobody domain is a promising non-antibody scaffold, which features a less complex architecture than an antibody while maintaining analogous binding loops. We previously developed FN3Con, a hyperstable monobody derivative with diagnostic and therapeutic potential. Prestabilization of the scaffold mitigates the stability–function trade-off commonly associated with evolving a protein domain toward biological activity. Here, we aimed to examine if the FN3Con monobody could take on antibody-like binding to therapeutic targets, while retaining its extreme stability. We targeted the first of the Adnectin derivative of monobodies to reach clinical trials, which was engineered by directed evolution for binding to the therapeutic target VEGFR2; however, this function was gained at the expense of large losses in thermostability and increased oligomerization. In order to mitigate these losses, we grafted the binding loops from Adnectin-anti-VEGFR2 (CT-322) onto the prestabilized FN3Con scaffold to produce a domain that successfully bound with high affinity to the therapeutic target VEGFR2. This FN3Con-anti-VEGFR2 construct also maintains high thermostability, including remarkable long-term stability, retaining binding activity after 2 years of storage at 36 °C. Further investigations into buffer excipients doubled the presence of monomeric monobody in accelerated stability trials. These data suggest that loop grafting onto a prestabilized scaffold is a viable strategy for the development of monobody domains with desirable biophysical characteristics and that FN3Con is therefore well-suited to applications such as the evolution of multiple paratopes or shelf-stable diagnostics and therapeutics.

Kinase Function of Brassinosteroid Receptor Specified by Two Allosterically Regulated Subdomains

Plants acquire the ability to adapt to the environment using transmembrane receptor-like kinases (RLKs) to sense the challenges from their surroundings and respond appropriately. RLKs perceive a variety of ligands through their variable extracellular domains (ECDs) that activate the highly conserved intracellular kinase domains (KDs) to control distinct biological functions through a well-developed downstream signaling cascade. A new study has emerged that brassinosteroid-insensitive 1 (BRI1) family and excess microsporocytes 1 (EMS1) but not GASSHO1 (GSO1) and other RLKs control distinct biological functions through the same signaling pathway, raising a question how the signaling pathway represented by BRI1 is specified. Here, we confirm that BRI1-KD is not functionally replaceable by GSO1-KD since the chimeric BRI1-GSO1 cannot rescue bri1 mutants. We then identify two subdomains S1 and S2. BRI1 with its S1 and S2 substituted by that of GSO1 cannot rescue bri1 mutants. Conversely, chimeric BRI1-GSO1 with its S1 and S2 substituted by that of BRI1 can rescue bri1 mutants, suggesting that S1 and S2 are the sufficient requirements to specify the signaling function of BRI1. Consequently, all the other subdomains in the KD of BRI1 are functionally replaceable by that of GSO1 although the in vitro kinase activities vary after replacements, suggesting their functional robustness and mutational plasticity with diverse kinase activity. Interestingly, S1 contains αC-β4 loop as an allosteric hotspot and S2 includes kinase activation loop, proposedly regulating kinase activities. Further analysis reveals that this specific function requires β4 and β5 in addition to αC-β4 loop in S1. We, therefore, suggest that BRI1 specifies its kinase function through an allosteric regulation of these two subdomains to control its distinct biological functions, providing a new insight into the kinase evolution.