Engineering indel and substitution variants of diverse and ancient enzymes using Graphical Representation of Ancestral Sequence Predictions (GRASP)

Insertions and Deletions: Computational Methods, Evolutionary Dynamics, and Biological Applications

Insertions and deletions constitute the second most important source of natural genomic variation. Insertions and deletions make up to 25% of genomic variants in humans and are involved in complex evolutionary processes including genomic rearrangements, adaptation, and speciation. Recent advances in long-read sequencing technologies allow detailed inference of insertions and deletion variation in species and populations. Yet, despite their importance, evolutionary studies have traditionally ignored or mishandled insertions and deletions due to a lack of comprehensive methodologies and statistical models of insertions and deletion dynamics. Here, we discuss methods for describing insertions and deletion variation and modeling insertions and deletions over evolutionary time. We provide practical advice for tackling insertions and deletions in genomic sequences and illustrate our discussion with examples of insertions and deletion-induced effects in human and other natural populations and their contribution to evolutionary processes. We outline promising directions for future developments in statistical methodologies that would allow researchers to analyze insertions and deletion variation and their effects in large genomic data sets and to incorporate insertions and deletions in evolutionary inference.

Please Mind the Gap: Indel-Aware Parsimony for Fast and Accurate Ancestral Sequence Reconstruction and Multiple Sequence Alignment Including Long Indels

Despite having important biological implications, insertion, and deletion (indel) events are often disregarded or mishandled during phylogenetic inference. In multiple sequence alignment, indels are represented as gaps and are estimated without considering the distinct evolutionary history of insertions and deletions. Consequently, indels are usually excluded from subsequent inference steps, such as ancestral sequence reconstruction and phylogenetic tree search. Here, we introduce indel-aware parsimony (indelMaP), a novel way to treat gaps under the parsimony criterion by considering insertions and deletions as separate evolutionary events and accounting for long indels. By identifying the precise location of an evolutionary event on the tree, we can separate overlapping indel events and use affine gap penalties for long indel modeling. Our indel-aware approach harnesses the phylogenetic signal from indels, including them into all inference stages. Validation and comparison to state-of-the-art inference tools on simulated data show that indelMaP is most suitable for densely sampled datasets with closely to moderately related sequences, where it can reach alignment quality comparable to probabilistic methods and accurately infer ancestral sequences, including indel patterns. Due to its remarkable speed, our method is well suited for epidemiological datasets, eliminating the need for downsampling and enabling the exploitation of the additional information provided by dense taxonomic sampling. Moreover, indelMaP offers new insights into the indel patterns of biologically significant sequences and advances our understanding of genetic variability by considering gaps as crucial evolutionary signals rather than mere artefacts.

Kinetic, electrochemical and spectral characterization of bacterial and archaeal rusticyanins; unexpected stability issues and consequences for applications in biotechnology

Motivated by the ambition to establish an enzyme-driven bioleaching pathway for copper extraction, properties of the Type-1 copper protein rusticyanin from Acidithiobacillus ferrooxidans (AfR) were compared with those from an ancestral form of this enzyme (N0) and an archaeal enzyme identified in Ferroplasma acidiphilum (FaR). While both N0 and FaR show redox potentials similar to that of AfR their electron transport rates were significantly slower. The lack of a correlation between the redox potentials and electron transfer rates indicates that AfR and its associated electron transfer chain evolved to specifically facilitate the efficient conversion of the energy of iron oxidation to ATP formation. In F. acidiphilum this pathway is not as efficient unless it is up-regulated by an as of yet unknown mechanism. In addition, while the electrochemical properties of AfR were consistent with previous data, previously unreported behavior was found leading to a form that is associated with a partially unfolded form of the protein. The cyclic voltammetry (CV) response of AfR immobilized onto an electrode showed limited stability, which may be connected to the presence of the partially unfolded state of this protein. Insights gained in this study may thus inform the engineering of optimized rusticyanin variants for bioleaching processes as well as enzyme-catalyzed solubilization of copper-containing ores such as chalcopyrite.

Optimal phylogenetic reconstruction of insertion and deletion events

MOTIVATION

Insertions and deletions (indels) influence the genetic code in fundamentally distinct ways from substitutions, significantly impacting gene product structure and function. Despite their influence, the evolutionary history of indels is often neglected in phylogenetic tree inference and ancestral sequence reconstruction, hindering efforts to comprehend biological diversity determinants and engineer variants for medical and industrial applications.

RESULTS

We frame determining the optimal history of indel events as a single Mixed-Integer Programming (MIP) problem, across all branch points in a phylogenetic tree adhering to topological constraints, and all sites implied by a given set of aligned, extant sequences. By disentangling the impact on ancestral sequences at each branch point, this approach identifies the minimal indel events that jointly explain the diversity in sequences mapped to the tips of that tree. MIP can recover alternate optimal indel histories, if available. We evaluated MIP for indel inference on a dataset comprising 15 real phylogenetic trees associated with protein families ranging from 165 to 2000 extant sequences, and on 60 synthetic trees at comparable scales of data and reflecting realistic rates of mutation. Across relevant metrics, MIP outperformed alternative parsimony-based approaches and reported the fewest indel events, on par or below their occurrence in synthetic datasets. MIP offers a rational justification for indel patterns in extant sequences; importantly, it uniquely identifies global optima on complex protein data sets without making unrealistic assumptions of independence or evolutionary underpinnings, promising a deeper understanding of molecular evolution and aiding novel protein design.

AVAILABILITY AND IMPLEMENTATION

The implementation is available via GitHub at https://github.com/santule/indelmip.

A suite of designed protein cages using machine learning and protein fragment-based protocols

Designed protein cages and related materials provide unique opportunities for applications in biotechnology and medicine, but their creation remains challenging. Here, we apply computational approaches to design a suite of tetrahedrally symmetric, self-assembling protein cages. For the generation of docked conformations, we emphasize a protein fragment-based approach, while for sequence design of the de novo interface, a comparison of knowledge-based and machine learning protocols highlights the power and increased experimental success achieved using ProteinMPNN. An analysis of design outcomes provides insights for improving interface design protocols, including prioritizing fragment-based motifs, balancing interface hydrophobicity and polarity, and identifying preferred polar contact patterns. In all, we report five structures for seven protein cages, along with two structures of intermediate assemblies, with the highest resolution reaching 2.0 Å using cryo-EM. This set of designed cages adds substantially to the body of available protein nanoparticles, and to methodologies for their creation.

Chromosome-level genome assembly of Prunella vulgaris L. provides insights into pentacyclic triterpenoid biosynthesis

Prunella vulgaris is one of the bestselling and widely used medicinal herbs. It is recorded as an ace medicine for cleansing and protecting the liver in Chinese Pharmacopoeia and has been used as the main constitutions of many herbal tea formulas in China for centuries. It is also a traditional folk medicine in Europe and other countries of Asia. Pentacyclic triterpenoids are a major class of bioactive compounds produced in P. vulgaris. However, their biosynthetic mechanism remains to be elucidated. Here, we report a chromosome-level reference genome of P. vulgaris using an approach combining Illumina, ONT, and Hi-C technologies. It is 671.95 Mb in size with a scaffold N50 of 49.10 Mb and a complete BUSCO of 98.45%. About 98.31% of the sequence was anchored into 14 pseudochromosomes. Comparative genome analysis revealed a recent WGD in P. vulgaris. Genome-wide analysis identified 35 932 protein-coding genes (PCGs), of which 59 encode enzymes involved in 2,3-oxidosqualene biosynthesis. In addition, 10 PvOSC, 358 PvCYP, and 177 PvUGT genes were identified, of which five PvOSCs, 25 PvCYPs, and 9 PvUGTs were predicted to be involved in the biosynthesis of pentacyclic triterpenoids. Biochemical activity assay of PvOSC2, PvOSC4, and PvOSC6 recombinant proteins showed that they were mixed amyrin synthase (MAS), lupeol synthase (LUS), and β-amyrin synthase (BAS), respectively. The results provide a solid foundation for further elucidating the biosynthetic mechanism of pentacyclic triterpenoids in P. vulgaris.

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.

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.

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.

Opportunities and Challenges for Machine Learning-Assisted Enzyme Engineering

Enzymes can be engineered at the level of their amino acid sequences to optimize key properties such as expression, stability, substrate range, and catalytic efficiency-or even to unlock new catalytic activities not found in nature. Because the search space of possible proteins is vast, enzyme engineering usually involves discovering an enzyme starting point that has some level of the desired activity followed by directed evolution to improve its "fitness" for a desired application. Recently, machine learning (ML) has emerged as a powerful tool to complement this empirical process. ML models can contribute to (1) starting point discovery by functional annotation of known protein sequences or generating novel protein sequences with desired functions and (2) navigating protein fitness landscapes for fitness optimization by learning mappings between protein sequences and their associated fitness values. In this Outlook, we explain how ML complements enzyme engineering and discuss its future potential to unlock improved engineering outcomes.

Development of a Highly Selective NAD+ -Dependent Glyceraldehyde Dehydrogenase and its Application in Minimal Cell-Free Enzyme Cascades

Anthropogenic climate change has been caused by over-exploitation of fossil fuels and CO2 emissions. To counteract this, the chemical industry has shifted its focus to sustainable chemical production and the valorization of renewable resources. However, the biggest challenges in biomanufacturing are technical efficiency and profitability. In our minimal cell-free enzyme cascade generating pyruvate as the central intermediate, the NAD+ -dependent, selective oxidation of D-glyceraldehyde was identified as a key reaction step to improve the overall cascade flux. Successive genome mining identified one candidate enzyme with 24-fold enhanced activity and another whose stability is unaffected in 10 % (v/v) ethanol, the final product of our model cascade. Semi-rational engineering improved the substrate selectivity of the enzyme up to 21-fold, thus minimizing side reactions in the one-pot enzyme cascade. The final biotransformation of D-glucose showed a continuous linear production of ethanol (via pyruvate) to a final titer of 4.9 % (v/v) with a molar product yield of 98.7 %. Due to the central role of pyruvate in diverse biotransformations, the optimized production module has great potential for broad biomanufacturing applications.

Evolution and separation of actinobacterial pyranose and C-glycoside-3-oxidases

FAD-dependent pyranose oxidase (POx) and C-glycoside-3-oxidase (CGOx) are both members of the glucose-methanol-choline superfamily of oxidoreductases and belong to the same sequence space. Pyranose oxidases had been studied for their oxidation of monosaccharides such as D-glucose, but recently, a bacterial C-glycoside-3-oxidase that is phylogenetically related to POx and that reacts with C-glycosides such as carminic acid, mangiferin or puerarin has been described. Since these actinobacterial CGOx enzymes belong to the same sequence space as bacterial POx, they must have evolved from the same ancestor. Here, we performed a phylogenetic analysis of actinobacterial sequences and resurrected seven ancestral enzymes of the POx/CGOx sequence space to study the evolutionary trajectory of substrate preferences for monosaccharides and C-glycosides. Clade I, with its dimeric member POx from Kitasatospora aureofaciens, shows strict preference for monosaccharides (D-glucose and D-xylose) and does not react with any of the glycosides tested. No extant member of clade II has been studied to date. The two extant members of clades III and IV, monomeric POx/CGOx from Pseudoarthrobacter siccitolerans and Streptomyces canus, oxidized both monosaccharides as well as various C-glycosides (homoorientin, isovitexin, mangiferin, and puerarin). Steady-state kinetic parameters of several clades III and IV ancestral enzymes indicate that the generalist ancestor N35 slowly evolved to present-day enzymes with a much higher preference for C-glycosides than monosaccharides. Based on structural predictions of ancestors, we hypothesize that the strict specificity of bacterial clade I POx (and also fungal POx) is the result of oligomerization, which in turn results from the evolution of protein segments that were shown to be important for oligomerization, the arm, and the head domain.IMPORTANCEC-Glycosides often form active compounds in various plants. Breakage of the C-C bond in these glycosides to release the aglycone is challenging and proceeds via a two-step reaction, the oxidation of the sugar and subsequent cleavage of the C-C bond. Recently, an enzyme from a soil bacterium, FAD-dependent C-glycoside-3-oxidase (CGOx), was shown to catalyze the initial oxidation reaction. Here, we show that CGOx belongs to the same sequence space as pyranose oxidase (POx), and that an actinobacterial ancestor of the POx/CGOx family evolved into four clades, two of which show a high preference for C-glycosides.

A Suite of Designed Protein Cages Using Machine Learning Algorithms and Protein Fragment-Based Protocols

Designed protein cages and related materials provide unique opportunities for applications in biotechnology and medicine, while methods for their creation remain challenging and unpredictable. In the present study, we apply new computational approaches to design a suite of new tetrahedrally symmetric, self-assembling protein cages. For the generation of docked poses, we emphasize a protein fragment-based approach, while for de novo interface design, a comparison of computational protocols highlights the power and increased experimental success achieved using the machine learning program ProteinMPNN. In relating information from docking and design, we observe that agreement between fragment-based sequence preferences and ProteinMPNN sequence inference correlates with experimental success. Additional insights for designing polar interactions are highlighted by experimentally testing larger and more polar interfaces. In all, using X-ray crystallography and cryo-EM, we report five structures for seven protein cages, with atomic resolution in the best case reaching 2.0 Å. We also report structures of two incompletely assembled protein cages, providing unique insights into one type of assembly failure. The new set of designed cages and their structures add substantially to the body of available protein nanoparticles, and to methodologies for their creation.

Surface frustration re-patterning underlies the structural landscape and evolvability of fungal orphan candidate effectors

Pathogens secrete effector proteins to subvert host physiology and cause disease. Effectors are engaged in a molecular arms race with the host resulting in conflicting evolutionary constraints to manipulate host cells without triggering immune responses. The molecular mechanisms allowing effectors to be at the same time robust and evolvable remain largely enigmatic. Here, we show that 62 conserved structure-related families encompass the majority of fungal orphan effector candidates in the Pezizomycotina subphylum. These effectors diversified through changes in patterns of thermodynamic frustration at surface residues. The underlying mutations tended to increase the robustness of the overall effector protein structure while switching potential binding interfaces. This mechanism could explain how conserved effector families maintained biological activity over long evolutionary timespans in different host environments and provides a model for the emergence of sequence-unrelated effector families with conserved structures.

Ancestral APOBEC3B Nuclear Localization Is Maintained in Humans and Apes and Altered in Most Other Old World Primate Species

APOBEC3B is an innate immune effector enzyme capable of introducing mutations in viral genomes through DNA cytosine-to-uracil editing. Recent studies have shown that gamma-herpesviruses, such as Epstein-Barr virus (EBV), have evolved a potent APOBEC3B neutralization mechanism to protect lytic viral DNA replication intermediates in the nuclear compartment. APOBEC3B is additionally unique as the only human DNA deaminase family member that is constitutively nuclear. Nuclear localization has therefore been inferred to be essential for innate antiviral function. Here, we combine evolutionary, molecular, and cell biology approaches to address whether nuclear localization is a conserved feature of APOBEC3B in primates. Despite the relatively recent emergence of APOBEC3B approximately 30 to 40 million years ago (MYA) in Old World primates by genetic recombination (after the split from the New World monkey lineage 40 to 50 MYA), we find that the hallmark nuclear localization of APOBEC3B shows variability. For instance, although human and several nonhuman primate APOBEC3B enzymes are predominantly nuclear, rhesus macaque and other Old World primate APOBEC3B proteins are clearly cytoplasmic or cell wide. A series of human/rhesus macaque chimeras and mutants combined to map localization determinants to the N-terminal half of the protein with residues 15, 19, and 24 proving critical. Ancestral APOBEC3B reconstructed from present-day primate species also shows strong nuclear localization. Together, these results indicate that the ancestral nuclear localization of APOBEC3B is maintained in present-day human and ape proteins, but nuclear localization is not conserved in all Old World monkey species despite a need for antiviral functions in the nuclear compartment. IMPORTANCE APOBEC3 enzymes are single-stranded DNA cytosine-to-uracil deaminases with beneficial roles in antiviral immunity and detrimental roles in cancer mutagenesis. Regarding viral infection, all seven human APOBEC3 enzymes have overlapping roles in restricting virus types that require DNA for replication, including EBV, HIV, human papillomavirus (HPV), and human T-cell leukemia virus (HTLV). Regarding cancer, at least two APOBEC3 enzymes, APOBEC3B and APOBEC3A, are prominent sources of mutation capable of influencing clinical outcomes. Here, we combine evolutionary, molecular, and cell biology approaches to characterize primate APOBEC3B enzymes. We show that nuclear localization is an ancestral property of APOBEC3B that is maintained in present-day human and ape enzymes, but not conserved in other nonhuman primates. This partial mechanistic conservation indicates that APOBEC3B is important for limiting the replication of DNA-based viruses in the nuclear compartment. Understanding these pathogen-host interactions may contribute to the development of future antiviral and antitumor therapies.

Evidence linking APOBEC3B genesis and evolution of innate immune antagonism by gamma-herpesvirus ribonucleotide reductases

Viruses have evolved diverse mechanisms to antagonize host immunity such as direct inhibition and relocalization of cellular APOBEC3B (A3B) by the ribonucleotide reductase (RNR) of Epstein-Barr virus. Here, we investigate the mechanistic conservation and evolutionary origin of this innate immune counteraction strategy. First, we find that human gamma-herpesvirus RNRs engage A3B via largely distinct surfaces. Second, we show that RNR-mediated enzymatic inhibition and relocalization of A3B depend upon binding to different regions of the catalytic domain. Third, we show that the capability of viral RNRs to antagonize A3B is conserved among gamma-herpesviruses that infect humans and Old World monkeys that encode this enzyme but absent in homologous viruses that infect New World monkeys that naturally lack the A3B gene. Finally, we reconstruct the ancestral primate A3B protein and demonstrate that it is active and similarly engaged by the RNRs from viruses that infect humans and Old World monkeys but not by the RNRs from viruses that infect New World monkeys. These results combine to indicate that the birth of A3B at a critical branchpoint in primate evolution may have been a driving force in selecting for an ancestral gamma-herpesvirus with an expanded RNR functionality through counteraction of this antiviral enzyme.