Ancestral Resurrection and Directed Evolution of Fungal Mesozoic Laccases

Ancestral Reconstruction and the Evolution of Protein Energy Landscapes

A protein's sequence determines its conformational energy landscape. This, in turn, determines the protein's function. Understanding the evolution of new protein functions therefore requires understanding how mutations alter the protein energy landscape. Ancestral sequence reconstruction (ASR) has proven a valuable tool for tackling this problem. In ASR, one phylogenetically infers the sequences of ancient proteins, allowing characterization of their properties. When coupled to biophysical, biochemical, and functional characterization, ASR can reveal how historical mutations altered the energy landscape of ancient proteins, allowing the evolution of enzyme activity, altered conformations, binding specificity, oligomerization, and many other protein features. In this article, we review how ASR studies have been used to dissect the evolution of energy landscapes. We also discuss ASR studies that reveal how energy landscapes have shaped protein evolution. Finally, we propose that thinking about evolution from the perspective of an energy landscape can improve how we approach and interpret ASR studies.

An Inferred Ancestral CotA Laccase with Improved Expression and Kinetic Efficiency

Laccases are widely used in industrial production due to their broad substrate availability and environmentally friendly nature. However, the pursuit of laccases with superior stability and increased heterogeneous expression to meet industry demands appears to be an ongoing challenge. To address this challenge, we resurrected five ancestral sequences of laccase BsCotA and their homologues. All five variants were successfully expressed in soluble and functional forms with improved expression levels in Escherichia coli. Among the five variants, three exhibited higher catalytic rates, thermal stabilities, and acidic stabilities. Notably, AncCotA2, the best-performing variant, displayed a k_cat/K_M of 7.5 × 10⁵ M^-1·s^-1, 5.2-fold higher than that of the wild-type BsCotA, an improved thermo- and acidic stability, and better dye decolorization ability. This study provides a laccase variant with high application potential and presents a new starting point for future enzyme engineering.

Improved laccase production by Trametes versicolor using Copper-Glycyl-L-Histidyl-L-Lysine as a novel and high-efficient inducer

A highly efficient strategy using Copper-Glycyl-L-Histidyl-L-Lysine (GHK-Cu) as a novel inducer was developed to enhance laccase production by Trametes versicolor. After medium optimization, laccase activity increased by 12.77-fold compared to that without GHK-Cu. The laccase production of 1113.8 U L-1 was obtained by scaling-up culture in 5-L stirring tank. The laccase production induced by CuSO4 was poorer than that of GHK-Cu at the same mole concentration. GHK-Cu could increase the permeability of cell membrane with less damage, and it facilitated the adsorption, accumulation, and utilization of copper by fungal cells, which was beneficial for laccase synthesis. GHK-Cu induced better expression of laccase related genes than that of CuSO4, resulting in higher laccase production. This study provided a useful method for induced production of laccase by applying GHK chelated metal ion as a non-toxic inducer, which reduced the safety risk of laccase broth and provided the potential application of crude laccase in food industry. In addition, GHK can be used as the carrier of different metal ions to enhance the production of other metalloenzymes.

Role of distal sites in enzyme engineering

The limitations associated with natural enzyme catalysis have triggered the rise of the field of protein engineering. Traditional rational design was based on the analysis of protein structural information and catalytic mechanisms to identify key active sites or ligand binding sites to reshape the substrate pocket. The role and significance of functional sites in the active center have been studied extensively. With a deeper understanding of the structure-catalysis relationship map, the entire protein molecule can be filled with residues that play a substantial role in its structure and function. However, the catalytic mechanism underlying distal mutations remains unclear. The aim of this review was to highlight the criticality of the distal site in enzyme engineering based on the following three aspects: What can distal mutations exert on function from mutability landscape? How do distal sites influence enzyme function? How to predict and design distal mutations? This review provides insights into the catalytic mechanism of enzymes from the global interaction network, knowledge from sequence-structure-dynamics-function relationships, and strategies for distal mutation-based protein engineering.

Enzymatic Conjugation of Modified RNA Fragments by Ancestral RNA Ligase AncT4_2

Oligonucleotide therapeutics have great potential as a next-generation approach to treating intractable diseases. Large quantities of modified DNA/RNA containing xenobiotic nucleic acids (XNAs) must be synthesized before clinical application. In this study, the ancestral RNA ligase AncT4_2 was designed by ancestral sequence reconstruction (ASR) to perform the conjugation reaction of modified RNA fragments. AncT4_2 had superior properties to native RNA ligase 2 from T4 phage (T4Rnl2), including high productivity, a >2.5-fold-higher turnover number, and >10°C higher thermostability. One remarkable point is the broad substrate selectivity of AncT4_2; the activity of AncT4_2 toward 17 of the modified RNA fragments was higher than that of T4Rnl2. The activity was estimated by measuring the conjugation reaction of two RNA strands, 3'-OH (12 bp) and 5'-PO₄ (12 bp), in which the terminal and penultimate positions of the 3'-OH fragment and the first and second positions of the 5'-PO₄ fragment were substituted by 2'-fluoro, 2'-O-methyl, 2'-O-methoxyethyl, and 2'-H, respectively. The enzymatic properties of AncT4_2 allowed the enzyme to conjugate large quantities of double-stranded RNA coding for patisiran (>400 μM level), which was formed by four RNA fragments containing 2'-OMe-substituted nucleic acids. Structural analysis of modeled AncT4_2 suggested that protein dynamics were changed by mutation to Gly or indel during ASR and that this may positively impact the conjugation of modified RNA fragments with the enzyme. AncT4_2 is expected to be a key biocatalyst in synthesizing RNA therapeutics by an enzymatic reaction. IMPORTANCE RNA therapeutics is one of the next-generation medicines for treating various diseases. Our designed ancestral RNA ligase AncT4_2 exhibited excellent enzymatic properties, such as high thermal stability, productivity, specific activity, and broad substrate selectivity compared to native enzymes. These advantages create the potential for AncT4_2 to be applied in conjugating the modified RNA fragments containing various xenobiotic nucleic acids. In addition, patisiran, a known polyneuropathy therapeutic, could be synthesized from four fragmented oligonucleotides at a preparative scale. Taken together, these findings indicate AncT4_2 could open the door to synthesizing RNA therapeutics by enzymatic reaction at large-scale production.

Ancestral sequence reconstruction as a tool to study the evolution of wood decaying fungi

The study of evolution is limited by the techniques available to do so. Aside from the use of the fossil record, molecular phylogenetics can provide a detailed characterization of evolutionary histories using genes, genomes and proteins. However, these tools provide scarce biochemical information of the organisms and systems of interest and are therefore very limited when they come to explain protein evolution. In the past decade, this limitation has been overcome by the development of ancestral sequence reconstruction (ASR) methods. ASR allows the subsequent resurrection in the laboratory of inferred proteins from now extinct organisms, becoming an outstanding tool to study enzyme evolution. Here we review the recent advances in ASR methods and their application to study fungal evolution, with special focus on wood-decay fungi as essential organisms in the global carbon cycling.

Efficient Base-Catalyzed Kemp Elimination in an Engineered Ancestral Enzyme

The routine generation of enzymes with completely new active sites is a major unsolved problem in protein engineering. Advances in this field have thus far been modest, perhaps due, at least in part, to the widespread use of modern natural proteins as scaffolds for de novo engineering. Most modern proteins are highly evolved and specialized and, consequently, difficult to repurpose for completely new functionalities. Conceivably, resurrected ancestral proteins with the biophysical properties that promote evolvability, such as high stability and conformational diversity, could provide better scaffolds for de novo enzyme generation. Kemp elimination, a non-natural reaction that provides a simple model of proton abstraction from carbon, has been extensively used as a benchmark in de novo enzyme engineering. Here, we present an engineered ancestral β-lactamase with a new active site that is capable of efficiently catalyzing Kemp elimination. The engineering of our Kemp eliminase involved minimalist design based on a single function-generating mutation, inclusion of an extra polypeptide segment at a position close to the de novo active site, and sharply focused, low-throughput library screening. Nevertheless, its catalytic parameters (k_cat/K_M~2·10⁵ M⁻¹ s⁻¹, k_cat~635 s⁻¹) compare favorably with the average modern natural enzyme and match the best proton-abstraction de novo Kemp eliminases that are reported in the literature. The general implications of our results for de novo enzyme engineering are discussed.

Learning Strategies in Protein Directed Evolution

Synthetic biology is a fast-evolving research field that combines biology and engineering principles to develop new biological systems for medical, pharmacological, and industrial applications. Synthetic biologists use iterative "design, build, test, and learn" cycles to efficiently engineer genetic systems that are reliable, reproducible, and predictable. Protein engineering by directed evolution can benefit from such a systematic engineering approach for various reasons. Learning can be carried out before starting, throughout or after finalizing a directed evolution project. Computational tools, bioinformatics, and scanning mutagenesis methods can be excellent starting points, while molecular dynamics simulations and other strategies can guide engineering efforts. Similarly, studying protein intermediates along evolutionary pathways offers fascinating insights into the molecular mechanisms shaped by evolution. The learning step of the cycle is not only crucial for proteins or enzymes that are not suitable for high-throughput screening or selection systems, but it is also valuable for any platform that can generate a large amount of data that can be aided by machine learning algorithms. The main challenge in protein engineering is to predict the effect of a single mutation on one functional parameter-to say nothing of several mutations on multiple parameters. This is largely due to nonadditive mutational interactions, known as epistatic effects-beneficial mutations present in a genetic background may not be beneficial in another genetic background. In this work, we provide an overview of experimental and computational strategies that can guide the user to learn protein function at different stages in a directed evolution project. We also discuss how epistatic effects can influence the success of directed evolution projects. Since machine learning is gaining momentum in protein engineering and the field is becoming more interdisciplinary thanks to collaboration between mathematicians, computational scientists, engineers, molecular biologists, and chemists, we provide a general workflow that familiarizes nonexperts with the basic concepts, dataset requirements, learning approaches, model capabilities and performance metrics of this intriguing area. Finally, we also provide some practical recommendations on how machine learning can harness epistatic effects for engineering proteins in an "outside-the-box" way.

Laccases as green and versatile biocatalysts: from lab to enzyme market-an overview

Laccases are multi-copper oxidase enzymes that catalyze the oxidation of different compounds (phenolics and non-phenolics). The scientific literature on laccases is quite extensive, including many basic and applied research about the structure, functions, mechanism of action and a variety of biotechnological applications of these versatile enzymes. Laccases can be used in various industries/sectors, from the environmental field to the cosmetics industry, including food processing and the textile industry (dyes biodegradation and synthesis). Known as eco-friendly or green enzymes, the application of laccases in biocatalytic processes represents a promising sustainable alternative to conventional methods. Due to the advantages granted by enzyme immobilization, publications on immobilized laccases increased substantially in recent years. Many patents related to the use of laccases are available, however, the real industrial or environmental use of laccases is still challenged by cost-benefit, especially concerning the feasibility of producing this enzyme on a large scale. Although this is a compelling point and the enzyme market is heated, articles on the production and application of laccases usually neglect the economic assessment of the processes. In this review, we present a description of laccases structure and mechanisms of action including the different sources (fungi, bacteria, and plants) for laccases production and tools for laccases evolution and prediction of potential substrates. In addition, we both compare approaches for scaling-up processes with an emphasis on cost reduction and productivity and critically review several immobilization methods for laccases. Following the critical view on production and immobilization, we provide a set of applications for free and immobilized laccases based on articles published within the last five years and patents which may guide future strategies for laccase use and commercialization.