Ancestral Sequence Reconstruction Research Articles

The importance of input sequence set to consensus-derived proteins and their relationship to reconstructed ancestral proteins.

A protein sequence encodes its energy landscape-all the accessible conformations, energetics, and dynamics. The evolutionary relationship between sequence and landscape can be probed phylogenetically by compiling a multiple sequence alignment of homologous sequences and generating common ancestors via Ancestral Sequence Reconstruction or a consensus protein containing the most common amino acid at each position. Both ancestral and consensus proteins are often more stable than their extant homologs-questioning the differences between them and suggesting that both approaches serve as general methods to engineer thermostability. We used the Ribonuclease H family to compare these approaches and evaluate how the evolutionary relationship of the input sequences affects the properties of the resulting consensus protein. While the consensus protein derived from our full Ribonuclease H sequence alignment is structured and active, it neither shows properties of a well-folded protein nor has enhanced stability. In contrast, the consensus protein derived from a phylogenetically-restricted set of sequences is significantly more stable and cooperatively folded, suggesting that cooperativity may be encoded by different mechanisms in separate clades and lost when too many diverse clades are combined to generate a consensus protein. To explore this, we compared pairwise covariance scores using a Potts formalism as well as higher-order sequence correlations using singular value decomposition (SVD). We find the SVD coordinates of a stable consensus sequence are close to coordinates of the analogous ancestor sequence and its descendants, whereas the unstable consensus sequences are outliers in SVD space.

Structure, mechanism, and evolution of the last step in vitamin C biosynthesis

Photosynthetic organisms, fungi, and animals comprise distinct pathways for vitamin C biosynthesis. Besides this diversity, the final biosynthetic step consistently involves an oxidation reaction carried out by the aldonolactone oxidoreductases. Here, we study the origin and evolution of the diversified activities and substrate preferences featured by these flavoenzymes using molecular phylogeny, kinetics, mutagenesis, and crystallographic experiments. We find clear evidence that they share a common ancestor. A flavin-interacting amino acid modulates the reactivity with the electron acceptors, including oxygen, and determines whether an enzyme functions as an oxidase or a dehydrogenase. We show that a few side chains in the catalytic cavity impart the reaction stereoselectivity. Ancestral sequence reconstruction outlines how these critical positions were affixed to specific amino acids along the evolution of the major eukaryotic clades. During Eukarya evolution, the aldonolactone oxidoreductases adapted to the varying metabolic demands while retaining their overarching vitamin C-generating function.

Enhancing PET Degrading Enzymes: A Combinatory Approach.

Plastic waste has become a substantial environmental issue. A potential strategy to mitigate this problem is to use enzymatic hydrolysis of plastics to depolymerize post-consumer waste and allow it to be reused. Over the last few decades, the use of enzymatic PET-degrading enzymes has shown promise as a great solution for creating a circular plastic waste economy. PsPETase from Piscinibacter sakaiensis has been identified as an enzyme with tremendous potential for such applications. But to improve its efficiency, enzyme engineering has been applied aiming at enhancing its thermal stability, enzymatic activity, and ease of production. Here, we combine different strategies such as structure-based rational design, ancestral sequence reconstruction and machine learning to engineer a more highly active Combi-PETase variant with a melting temperature of 70 °C and optimal performance at 60 °C. Furthermore, this study demonstrates that these approaches, commonly used in other works of enzyme engineering, are most effective when utilized in combination, enabling the improvement of enzymes for industrial applications.

Evolution of the catalytic mechanism at the dawn of the Baeyer-Villiger monooxygenases

Enzymes are crucial for the emergence and sustenance of life on earth. How they became catalytically activeduring their evolution is still an open question. Two opposite explanations are plausible: acquiring a mechanism in a series of discrete steps or all at once in a single evolutionary event. Here, we use molecular phylogeny, ancestral sequence reconstruction, and biochemical characterization to follow the evolution of a specialized group of flavoprotein monooxygenases, the bacterial Baeyer-Villiger monooxygenases (BVMOs). These enzymes catalyze an intricate chemical reaction relying on three different elements: a reduced nicotinamide cofactor, dioxygen, and a substrate. Characterization of ancestral BVMOs shows that the catalytic mechanism evolved in a series of steps starting from a FAD-binding protein and further acquiring reactivity and specificity toward each of the elements participating in the reaction. Together, the results of our work portray how an intrinsically complex catalytic mechanism emerged during evolution.

Computational scoring and experimental evaluation of enzymes generated by neural networks.

In recent years, generative protein sequence models have been developed to sample novel sequences. However, predicting whether generated proteins will fold and function remains challenging. We evaluate a set of 20 diverse computational metrics to assess the quality of enzyme sequences produced by three contrasting generative models: ancestral sequence reconstruction, a generative adversarial network and a protein language model. Focusing on two enzyme families, we expressed and purified over 500 natural and generated sequences with 70-90% identity to the most similar natural sequences to benchmark computational metrics for predicting in vitro enzyme activity. Over three rounds of experiments, we developed a computational filter that improved the rate of experimental success by 50-150%. The proposed metrics and models will drive protein engineering research by serving as a benchmark for generative protein sequence models and helping to select active variants for experimental testing.

Improving the Quality of Wheat Flour Bread by a Thermophilic Xylanase with Ultra Activity and Stability Reconstructed by Ancestral Sequence and Computational-Aided Analysis.

Xylanase is an essential component used to hydrolyze the xylan in wheat flour to enhance the quality of bread. Presently, cold-activated xylanase is popularly utilized to aid in the development of dough. In this study, ancestral sequence reconstruction and molecular docking of xylanase and wheat xylan were used to enhance the activity and stability of a thermophilic xylanase. The results indicated that the ancestral enzyme TmxN3 exhibited significantly improved activity and thermal stability. The Vmax increased by 2.7 times, and the catalytic efficiency (Kcat/Km) increased by 1.7 times in comparison to TmxB. After being incubated at 100 °C for 120 min, it still retained 87.3% of its activity, and the half-life in 100 °C was 330 min, while the wild type xylanase was only 55 min. This resulted in an improved shelf life of bread, while adding TmxN3 considerably enhanced its quality with excellent volume and reduced hardness, chewiness, and gumminess. The results showed that the hardness was reduced by 55.2%, the chewiness was reduced by 40.11%, and the gumminess was reduced by 53.52%. To facilitate its industrial application, we further optimized the production conditions in a 5L bioreactor, and the xylanase activity reached 1.52 × 106 U/mL culture.

Structure and Activity of Reconstructed Pseudo-Ancestral Cyclotides.

Cyclotides are cyclic peptides that are promising scaffolds for the design of drug candidates and chemical tools. However, despite there being hundreds of reported cyclotides, drug design studies have commonly focussed on a select few prototypic examples. Here, we explored whether ancestral sequence reconstruction could be used to generate new cyclotides for further optimization. We show that the reconstructed 'pseudo-ancestral' sequences, named Ancy-m (for the ancestral cyclotide of the Möbius sub-family) and Ancy-b (for the bracelet sub-family), have well-defined structures like their extant members, comprising the core structural feature of a cyclic cystine knot. This motif underpins efforts to re-engineer cyclotides for agrochemical and therapeutic applications. We further show that the reconstructed sequences are resistant to temperatures approaching boiling, bind to phosphatidyl-ethanolamine lipid bilayers at micromolar affinity, and inhibit the growth of insect cells at inhibitory concentrations in the micromolar range. Interestingly, the Ancy-b cyclotide had a higher oxidative folding yield than its comparator cyclotide cyO2, which belongs to the bracelet cyclotide subfamily known to be notoriously difficult to fold. Overall, this study provides new cyclotide sequences not yet found naturally that could be valuable starting points for the understanding of cyclotide evolution and for further optimization as drug leads.

Emergence of fractal geometries in the evolution of a metabolic enzyme

Fractals are patterns that are self-similar across multiple length-scales1. Macroscopic fractals are common in nature2–4; however, so far, molecular assembly into fractals is restricted to synthetic systems5–12. Here we report the discovery of a natural protein, citrate synthase from the cyanobacterium Synechococcus elongatus, which self-assembles into Sierpiński triangles. Using cryo-electron microscopy, we reveal how the fractal assembles from a hexameric building block. Although different stimuli modulate the formation of fractal complexes and these complexes can regulate the enzymatic activity of citrate synthase in vitro, the fractal may not serve a physiological function in vivo. We use ancestral sequence reconstruction to retrace how the citrate synthase fractal evolved from non-fractal precursors, and the results suggest it may have emerged as a harmless evolutionary accident. Our findings expand the space of possible protein complexes and demonstrate that intricate and regulatable assemblies can evolve in a single substitution.

Ancestral sequence reconstruction dissects structural and functional differences among eosinophil ribonucleases

Evolutionarily conserved structural folds can give rise to diverse biological functions, yet predicting atomic-scale interactions that contribute to the emergence of novel activities within such folds remains challenging. Pancreatic-type ribonucleases illustrate this complexity, sharing a core structure that has evolved to accommodate varied functions. In this study, we used ancestral sequence reconstruction to probe evolutionary and molecular determinants that distinguish biological activities within eosinophil members of the RNase 2/3 subfamily. Our investigation unveils functional, structural, and dynamical behaviors that differentiate the evolved ancestor AncRNase from its contemporary eosinophil RNase orthologs. Leveraging the potential of ancestral reconstruction for protein engineering, we used AncRNase predictions to design a minimal 4-residue variant that transforms human RNase 2 into a chimeric enzyme endowed with the antimicrobial and cytotoxic activities of RNase 3 members. This work provides unique insights into mutational and evolutionary pathways governing structure, function, and conformational states within the eosinophil RNase subfamily, offering potential for targeted modulation of RNase-associated functions.

Engineering Biocatalysts for the C−H Activation of Fatty Acids by Ancestral Sequence Reconstruction**

AbstractSelective, one‐step C−H activation of fatty acids from biomass is an attractive concept in sustainable chemistry. Biocatalysis has shown promise for generating high‐value hydroxy acids, but to date enzyme discovery has relied on laborious screening and produced limited hits, which predominantly oxidise the subterminal positions of fatty acids. Herein we show that ancestral sequence reconstruction (ASR) is an effective tool to explore the sequence‐activity landscape of a family of multidomain, self‐sufficient P450 monooxygenases. We resurrected 11 catalytically active CYP116B ancestors, each with a unique regioselectivity fingerprint that varied from subterminal in the older ancestors to mid‐chain in the lineage leading to the extant, P450‐TT. In lineages leading to extant enzymes in thermophiles, thermostability increased from ancestral to extant forms, as expected if thermophily had arisen de novo. Our studies show that ASR can be applied to multidomain enzymes to develop active, self‐sufficient monooxygenases as regioselective biocatalysts for fatty acid hydroxylation.

Engineering Biocatalysts for the C-H Activation of Fatty Acids by Ancestral Sequence Reconstruction.

Selective, one-step C-H activation of fatty acids from biomass is an attractive concept in sustainable chemistry. Biocatalysis has shown promise for generating high-value hydroxy acids, but to date enzyme discovery has relied on laborious screening and produced limited hits, which predominantly oxidise the subterminal positions of fatty acids. Herein we show that ancestral sequence reconstruction (ASR) is an effective tool to explore the sequence-activity landscape of a family of multidomain, self-sufficient P450 monooxygenases. We resurrected 11 catalytically active CYP116B ancestors, each with a unique regioselectivity fingerprint that varied from subterminal in the older ancestors to mid-chain in the lineage leading to the extant, P450-TT. In lineages leading to extant enzymes in thermophiles, thermostability increased from ancestral to extant forms, as expected if thermophily had arisen de novo. Our studies show that ASR can be applied to multidomain enzymes to develop active, self-sufficient monooxygenases as regioselective biocatalysts for fatty acid hydroxylation.

The Origin and Evolution of Sex Peptide and Sex Peptide Receptor Interactions.

Post-mating responses play a vital role in successful reproduction across diverse species. In fruit flies, sex peptide binds to the sex peptide receptor, triggering a series of post-mating responses. However, the origin of sex peptide receptor predates the emergence of sex peptide. The evolutionary origins of the interactions between sex peptide and sex peptide receptor and the mechanisms by which they interact remain enigmatic. In this study, we used ancestral sequence reconstruction, AlphaFold2 predictions, and molecular dynamics simulations to study sex peptide-sex peptide receptor interactions and their origination. Using AlphaFold2 and long-time molecular dynamics simulations, we predicted the structure and dynamics of sex peptide-sex peptide receptor interactions. We show that sex peptide potentially binds to the ancestral states of Diptera sex peptide receptor. Notably, we found that only a few amino acid changes in sex peptide receptor are sufficient for the formation of sex peptide-sex peptide receptor interactions. Ancestral sequence reconstruction and molecular dynamics simulations further reveal that sex peptide receptor interacts with sex peptide through residues that are mostly involved in the interaction interface of an ancestral ligand, myoinhibitory peptides. We propose a potential mechanism whereby sex peptide-sex peptide receptor interactions arise from the preexisting myoinhibitory peptides-sex peptide receptor interface as well as early chance events both inside and outside the preexisting interface that created novel sex peptide-specific sex peptide-sex peptide receptor interactions. Our findings provide new insights into the origin and evolution of sex peptide-sex peptide receptor interactions and their relationship with myoinhibitory peptides-sex peptide receptor interactions.

Extant Sequence Reconstruction: The Accuracy of Ancestral Sequence Reconstructions Evaluated by Extant Sequence Cross-Validation

Ancestral sequence reconstruction (ASR) is a phylogenetic method widely used to analyze the properties of ancient biomolecules and to elucidate mechanisms of molecular evolution. Despite its increasingly widespread application, the accuracy of ASR is currently unknown, as it is generally impossible to compare resurrected proteins to the true ancestors. Which evolutionary models are best for ASR? How accurate are the resulting inferences? Here we answer these questions using a cross-validation method to reconstruct each extant sequence in an alignment with ASR methodology, a method we term “extant sequence reconstruction” (ESR). We thus can evaluate the accuracy of ASR methodology by comparing ESR reconstructions to the corresponding known true sequences. We find that a common measure of the quality of a reconstructed sequence, the average probability, is indeed a good estimate of the fraction of correct amino acids when the evolutionary model is accurate or overparameterized. However, the average probability is a poor measure for comparing reconstructions from different models, because, surprisingly, a more accurate phylogenetic model often results in reconstructions with lower probability. While better (more predictive) models may produce reconstructions with lower sequence identity to the true sequences, better models nevertheless produce reconstructions that are more biophysically similar to true ancestors. In addition, we find that a large fraction of sequences sampled from the reconstruction distribution may have fewer errors than the single most probable (SMP) sequence reconstruction, despite the fact that the SMP has the lowest expected error of all possible sequences. Our results emphasize the importance of model selection for ASR and the usefulness of sampling sequence reconstructions for analyzing ancestral protein properties. ESR is a powerful method for validating the evolutionary models used for ASR and can be applied in practice to any phylogenetic analysis of real biological sequences. Most significantly, ESR uses ASR methodology to provide a general method by which the biophysical properties of resurrected proteins can be compared to the properties of the true protein.

Evolutionary divergence of TLR9 through ancestral sequence reconstruction.

The transmembrane pattern recognition receptor, Toll-like receptor (TLR), are best known for their roles in innate immunity via recognition of pathogen and initiation of signaling response. Mammalian TLRs recognize molecular patterns associated with pathogens and initiate innate immune response. We have studied the evolutionary diversity of mammalian TLR genes for differences in immunological response. Reconstruction of ancestral sequences is a key aspect of the molecular evolution of TLR to track changes across the TLR genes. The comprehensive analysis of mammalian TLRs revealed a distinct pattern of evolution of TLR9. Various sequence-based features such as amino acid usage, hydrophobicity, GC content, and evolutionary constraints are found to influence the divergence of TLR9 from other TLRs. Ancestral sequence reconstruction analysis also revealed that the gradual evolution of TLR genes in several ancestral lineages leads to the distinct pattern of TLR9. It demonstrates evolutionary divergence with the progressive accumulation of mutations results in the distinct patternof TLR9.

Stability Increase of Phenolic Acid Decarboxylase by a Combination of Protein and Solvent Engineering Unlocks Applications at Elevated Temperatures.

Enzymatic decarboxylation of biobased hydroxycinnamic acids gives access to phenolic styrenes for adhesive production. Phenolic acid decarboxylases are proficient enzymes that have been applied in aqueous systems, organic solvents, biphasic systems, and deep eutectic solvents, which makes stability a key feature. Stabilization of the enzyme would increase the total turnover number and thus reduce the energy consumption and waste accumulation associated with biocatalyst production. In this study, we used ancestral sequence reconstruction to generate thermostable decarboxylases. Investigation of a set of 16 ancestors resulted in the identification of a variant with an unfolding temperature of 78.1 °C and a half-life time of 45 h at 60 °C. Crystal structures were determined for three selected ancestors. Structural attributes were calculated to fit different regression models for predicting the thermal stability of variants that have not yet been experimentally explored. The models rely on hydrophobic clusters, salt bridges, hydrogen bonds, and surface properties and can identify more stable proteins out of a pool of candidates. Further stabilization was achieved by the application of mixtures of natural deep eutectic solvents and buffers. Our approach is a straightforward option for enhancing the industrial application of the decarboxylation process.

Evolution of Phosphorylase Activity in an Ancestral Glycosyltransferase.

The reconstruction of ancestral sequences can offer a glimpse into the fascinating process of molecular evolution by exposing the adaptive pathways that shape the proteins found in nature today. Here, we track the evolution of the carbohydrate-active enzymes responsible for the synthesis and turnover of mannogen, a critical carbohydrate reserve in Leishmania parasites. Biochemical characterization of resurrected enzymes demonstrated that mannoside phosphorylase activity emerged in an ancestral bacterial mannosyltransferase, and later disappeared in the process of horizontal gene transfer and gene duplication in Leishmania. By shuffling through plausible historical sequence space in an ancestral mannosyltransferase, we found that mannoside phosphorylase activity could be toggled on through various combinations of mutations at positions outside of the active site. Molecular dynamics simulations showed that such mutations can affect loop rigidity and shield the active site from water molecules that disrupt key interactions, allowing α-mannose 1-phosphate to adopt a catalytically productive conformation. These findings highlight the importance of subtle distal mutations in protein evolution and suggest that the vast collection of natural glycosyltransferases may be a promising source of engineering templates for the design of tailored phosphorylases.

Evolution and diversification of carboxylesterase-like [4+2] cyclases in aspidosperma and iboga alkaloid biosynthesis

Monoterpene indole alkaloids (MIAs) are a large and diverse class of plant natural products, and their biosynthetic construction has been a subject of intensive study for many years. The enzymatic basis for the production of aspidosperma and iboga alkaloids, which are produced exclusively by members of the Apocynaceae plant family, has recently been discovered. Three carboxylesterase (CXE)-like enzymes from Catharanthus roseus and Tabernanthe iboga catalyze regio- and enantiodivergent [4+2] cycloaddition reactions to generate the aspidosperma (tabersonine synthase, TS) and iboga (coronaridine synthase, CorS; catharanthine synthase, CS) scaffolds from a common biosynthetic intermediate. Here, we use a combined phylogenetic and biochemical approach to investigate the evolution and functional diversification of these cyclase enzymes. Through ancestral sequence reconstruction, we provide evidence for initial evolution of TS from an ancestral CXE followed by emergence of CorS in two separate lineages, leading in turn to CS exclusively in the Catharanthus genus. This progression from aspidosperma to iboga alkaloid biosynthesis is consistent with the chemotaxonomic distribution of these MIAs. We subsequently generate and test a panel of chimeras based on the ancestral cyclases to probe the molecular basis for differential cyclization activity. Finally, we show through partial heterologous reconstitution of tabersonine biosynthesis using non-pathway enzymes how aspidosperma alkaloids could have first appeared as "underground metabolites" via recruitment of promiscuous enzymes from common protein families. Our results provide insight into the evolution of biosynthetic enzymes and how new secondary metabolic pathways can emerge through small but important sequence changes following co-option of preexisting enzymatic functions.

Conservation of Affinity Rather Than Sequence Underlies a Dynamic Evolution of the Motif-Mediated p53/MDM2 Interaction in Ray-Finned Fishes.

The transcription factor and cell cycle regulator p53 is marked for degradation by the ubiquitin ligase MDM2. The interaction between these 2 proteins is mediated by a conserved binding motif in the disordered p53 transactivation domain (p53TAD) and the folded SWIB domain in MDM2. The conserved motif in p53TAD from zebrafish displays a 20-fold weaker interaction with MDM2, compared to the interaction in human and chicken. To investigate this apparent difference, we tracked the molecular evolution of the p53TAD/MDM2 interaction among ray-finned fishes (Actinopterygii), the largest vertebrate clade. Intriguingly, phylogenetic analyses, ancestral sequence reconstructions, and binding experiments showed that different loss-of-affinity changes in the canonical binding motif within p53TAD have occurred repeatedly and convergently in different fish lineages, resulting in relatively low extant affinities (KD = 0.5 to 5 μM). However, for 11 different fish p53TAD/MDM2 interactions, nonconserved regions flanking the canonical motif increased the affinity 4- to 73-fold to be on par with the human interaction. Our findings suggest that compensating changes at conserved and nonconserved positions within the motif, as well as in flanking regions of low conservation, underlie a stabilizing selection of "functional affinity" in the p53TAD/MDM2 interaction. Such interplay complicates bioinformatic prediction of binding and calls for experimental validation. Motif-mediated protein-protein interactions involving short binding motifs and folded interaction domains are very common across multicellular life. It is likely that the evolution of affinity in motif-mediated interactions often involves an interplay between specific interactions made by conserved motif residues and nonspecific interactions by nonconserved disordered regions.

Substitution Models of Protein Evolution with Selection on Enzymatic Activity.

Substitution models of evolution are necessary for diverse evolutionary analyses including phylogenetic tree and ancestral sequence reconstructions. At the protein level, empirical substitution models are traditionally used due to their simplicity, but they ignore the variability of substitution patterns among protein sites. Next, in order to improve the realism of the modeling of protein evolution, a series of structurally constrained substitution models were presented, but still they usually ignore constraints on the protein activity. Here, we present a substitution model of protein evolution with selection on both protein structure and enzymatic activity, and that can be applied to phylogenetics. In particular, the model considers the binding affinity of the enzyme-substrate complex as well as structural constraints that include the flexibility of structural flaps, hydrogen bonds, amino acids backbone radius of gyration, and solvent-accessible surface area that are quantified through molecular dynamics simulations. We applied the model to the HIV-1 protease and evaluated it by phylogenetic likelihood in comparison with the best-fitting empirical substitution model and a structurally constrained substitution model that ignores the enzymatic activity. We found that accounting for selection on the protein activity improves the fitting of the modeled functional regions with the real observations, especially in data with high molecular identity, which recommends considering constraints on the protein activity in the development of substitution models of evolution.

FEZF2 and AIRE1: An Evolutionary Trade-off in the Elimination of Auto-reactive T Cells in the Thymus.

Autoimmune Regulator 1 (AIRE1) and Forebrain Embryonic Zinc Finger-Like Protein 2 (FEZF2) play pivotal roles in orchestrating the expression of tissue-restricted antigens (TRA) to facilitate the elimination of autoreactive T cells. AIRE1's presence in the gonads of various vertebrates has raised questions about its potential involvement in gene expression control for germline cell selection. Nevertheless, the evolutionary history of these genes has remained enigmatic, as has the rationale behind their apparent redundancy in vertebrates. Furthermore, the origin of the elimination process itself has remained elusive. To shed light on these mysteries, we conducted a comprehensive evolutionary analysis employing a range of tools, including multiple sequence alignment, phylogenetic tree construction, ancestral sequence reconstruction, and positive selection assessment. Our investigations revealed intriguing insights. AIRE1 homologs emerged during the divergence of T cells in higher vertebrates, signifying its role in this context. Conversely, FEZF2 exhibited multiple homologs spanning invertebrates, lampreys, and higher vertebrates. Ancestral sequence reconstruction demonstrated distinct origins for AIRE1 and FEZF2, underscoring that their roles in regulating TRA have evolved through disparate pathways. Furthermore, it became evident that both FEZF2 and AIRE1 govern a diverse repertoire of genes, encompassing ancient and more recently diverged targets. Notably, FEZF2 demonstrates expression in both vertebrate and invertebrate embryos and germlines, accentuating its widespread role. Intriguingly, FEZF2 harbors motifs associated with autophagy, such as DKFPHP, SYSELWKSSL, and SYSEL, a process integral to cell selection in invertebrates. Our findings suggest that FEZF2 initially emerged to regulate self-elimination in the gonads of invertebrates. As organisms evolved toward greater complexity, AIRE1 likely emerged to complement FEZF2's role, participating in the regulation of cell selection for elimination in both gonads and the thymus. This dynamic interplay between AIRE1 and FEZF2 underscores their multifaceted contributions to TRA expression regulation across diverse evolutionary contexts.