Machine learning reveals sequence-function relationships in family 7 glycoside hydrolases

Trends in the development and current perspective of thermostable bacterial hemicellulases with their industrial endeavors: A review

Hemicellulases are enzymes that hydrolyze hemicelluloses, common polysaccharides in nature. Thermophilic hemicellulases, derived from microbial strains, are extensively studied as natural biofuel sources due to the complex structure of hemicelluloses. Recent research aims to elucidate the catalytic principles, mechanisms and specificity of hemicellulases through investigations into their high-temperature stability and structural features, which have applications in biotechnology and industry. This review article targets to serve as a comprehensive resource, highlighting the significant progress in the field and emphasizing the vital role of thermophilic hemicellulases in eco-friendly catalysis. The primary goal is to improve the reliability of hemicellulase enzymes obtained from thermophilic bacterial strains. Additionally, with their ability to break down lignocellulosic materials, hemicellulases hold immense potential for biofuel production. Despite their potential, the commercial viability is hindered by their high enzyme costs, necessitating the development of efficient bioprocesses involving waste pretreatment with microbial consortia to overcome this challenge.

Engineering of glycoside hydrolase family 7 cellobiohydrolases directed by natural diversity screening

Protein engineering and screening of processive fungal cellobiohydrolases (CBHs) remain challenging due to limited expression hosts, synergy-dependency, and recalcitrant substrates. In particular, glycoside hydrolase family 7 (GH7) CBHs are critically important for the bioeconomy and typically difficult to engineer. Here, we target the discovery of highly active natural GH7 CBHs and engineering of variants with improved activity. Using experimentally assayed activities of genome mined CBHs, we applied sequence and structural alignments to top performers to identify key point mutations linked to improved activity. From ∼1500 known GH7 sequences, an evolutionarily diverse subset of 57 GH7 CBH genes was expressed in Trichoderma reesei and screened using a multiplexed activity screening assay. Ten catalytically enhanced natural variants were identified, produced, purified, and tested for efficacy using industrially relevant conditions and substrates. Three key amino acids in CBHs with performance comparable or superior to Penicillium funiculosum Cel7A were identified and combinatorially engineered into P. funiculosum cel7a, expressed in T. reesei, and assayed on lignocellulosic biomass. The top performer generated using this combined approach of natural diversity genome mining, experimental assays, and computational modeling produced a 41% increase in conversion extent over native P. funiculosum Cel7A, a 55% increase over the current industrial standard T. reesei Cel7A, and 10% improvement over Aspergillus oryzae Cel7C, the best natural GH7 CBH previously identified in our laboratory.

The crystal structure of RsSymEG1 reveals a unique form of smaller GH7 endoglucanases alongside GH7 cellobiohydrolases in protist symbionts of termites

Glycoside hydrolase family 7 (GH7) cellulases are key enzymes responsible for carbon cycling on earth through their role in cellulose degradation and constitute highly important industrial enzymes as well. Although these enzymes are found in a wide variety of evolutionarily distant organisms across eukaryotes, they exhibit remarkably conserved features within two groups: exo-acting cellobiohydrolases and endoglucanases. However, recently reports have emerged of a separate clade of GH7 endoglucanases from protist symbionts of termites that are 60-80 amino acids shorter. In this work, we describe the first crystal structure of a short GH7 endoglucanase, RsSymEG1, from a symbiont of the lower termite Reticulitermes speratus. A more open flat surface and shorter loops around the non-reducing end of the cellulose-binding cleft indicate enhanced access to cellulose chains on the surface of cellulose microfibrils. Additionally, when comparing activities on polysaccharides to a typical fungal GH7 endoglucanase (Trichoderma longibrachiatum Cel7B), RsSymEG1 showed significantly faster initial hydrolytic activity. We also examine the prevalence and diversity of GH7 enzymes that the symbionts provide to the termite host, compare overall structures and substrate binding between cellobiohydrolase and long and short endoglucanase, and highlight the presence of similar short GH7s in other organisms.

Machine-Learning-Guided Engineering of an NADH-Dependent 7β-Hydroxysteroid Dehydrogenase for Economic Synthesis of Ursodeoxycholic Acid

Enzymatic synthesis of ursodeoxycholic acid (UDCA) catalyzed by an NADH-dependent 7β-hydroxysteroid dehydrogenase (7β-HSDH) is more economic compared with an NADPH-dependent 7β-HSDH when considering the much higher cost of NADP+/NADPH than that of NAD+/NADH. However, the poor catalytic performance of NADH-dependent 7β-HSDH significantly limits its practical applications. Herein, machine-learning-guided protein engineering was performed on an NADH-dependent Rt7β-HSDHM0 from Ruminococcus torques. We combined random forest, Gaussian Naïve Bayes classifier, and Gaussian process regression with limited experimental data, resulting in the best variant Rt7β-HSDHM3 (R40I/R41K/F94Y/S196A/Y253F) with improvements in specific activity and half-life (40 °C) by 4.1-fold and 8.3-fold, respectively. The preparative biotransformation using a "two stage in one pot" sequential process coupled with Rt7β-HSDHM3 exhibited a space-time yield (STY) of 192 g L-1 d-1, which is so far the highest productivity for the biosynthesis of UDCA from chenodeoxycholic acid (CDCA) with NAD+ as a cofactor. More importantly, the cost of raw materials for the enzymatic production of UDCA employing Rt7β-HSDHM3 decreased by 22% in contrast to that of Rt7β-HSDHM0, indicating the tremendous potential of the variant Rt7β-HSDHM3 for more efficient and economic production of UDCA.

Engineering cellulases for conversion of lignocellulosic biomass

Lignocellulosic biomass is a renewable source of energy, chemicals and materials. Many applications of this resource require the depolymerization of one or more of its polymeric constituents. Efficient enzymatic depolymerization of cellulose to glucose by cellulases and accessory enzymes such as lytic polysaccharide monooxygenases is a prerequisite for economically viable exploitation of this biomass. Microbes produce a remarkably diverse range of cellulases, which consist of glycoside hydrolase (GH) catalytic domains and, although not in all cases, substrate-binding carbohydrate-binding modules (CBMs). As enzymes are a considerable cost factor, there is great interest in finding or engineering improved and robust cellulases, with higher activity and stability, easy expression, and minimal product inhibition. This review addresses relevant engineering targets for cellulases, discusses a few notable cellulase engineering studies of the past decades and provides an overview of recent work in the field.

Sourcing thermotolerant poly(ethylene terephthalate) hydrolase scaffolds from natural diversity

Enzymatic deconstruction of poly(ethylene terephthalate) (PET) is under intense investigation, given the ability of hydrolase enzymes to depolymerize PET to its constituent monomers near the polymer glass transition temperature. To date, reported PET hydrolases have been sourced from a relatively narrow sequence space. Here, we identify additional PET-active biocatalysts from natural diversity by using bioinformatics and machine learning to mine 74 putative thermotolerant PET hydrolases. We successfully express, purify, and assay 51 enzymes from seven distinct phylogenetic groups; observing PET hydrolysis activity on amorphous PET film from 37 enzymes in reactions spanning pH from 4.5-9.0 and temperatures from 30-70 °C. We conduct PET hydrolysis time-course reactions with the best-performing enzymes, where we observe differences in substrate selectivity as function of PET morphology. We employed X-ray crystallography and AlphaFold to examine the enzyme architectures of all 74 candidates, revealing protein folds and accessory domains not previously associated with PET deconstruction. Overall, this study expands the number and diversity of thermotolerant scaffolds for enzymatic PET deconstruction.

Heterogeneous catalysis mediated by light, electricity and enzyme via machine learning: Paradigms, applications and prospects

Energy crisis and environmental pollution have become the bottleneck of human sustainable development. Therefore, there is an urgent need to develop new catalysts for energy production and environmental remediation. Due to the high cost caused by blind screening and limited valuable computing resources, the traditional experimental methods and theoretical calculations are difficult to meet with the requirements. In the past decades, computer science has made great progress, especially in the field of machine learning (ML). As a new research paradigm, ML greatly accelerates the theoretical calculation methods represented by first principal calculation and molecular dynamics, and establish the physical picture of heterogeneous catalytic processes for energy and environment. This review firstly summarized the general research paradigms of ML in the discovery of catalysts. Then, the latest progresses of ML in light-, electricity- and enzyme-mediated heterogeneous catalysis were reviewed from the perspective of catalytic performance, operating conditions and reaction mechanism. The general guidelines of ML for heterogeneous catalysis were proposed. Finally, the existing problems and future development trend of ML in heterogeneous catalysis mediated by light, electricity and enzyme were summarized. We highly expect that this review will facilitate the interaction between ML and heterogeneous catalysis, and illuminate the development prospect of heterogeneous catalysis.

Insights into promiscuous chitosanases: the known and the unknown

Chitosanase, a glycoside hydrolase (GH), catalyzes the cleavage of β-1,4-glycosidic bonds in polysaccharides and is widely distributed in nature. Many organisms produce chitosanases, and numerous chitosanases in the GH families have been intensely studied. The reported chitosanases mainly cleaved the inter-glucosamine glycosidic bonds, while substrate specificity is not strictly unique due to the existence of bifunctional or multifunctional activity profiles. The promiscuity of chitosanases is essential for the different pathways of biomass polysaccharide conversion and understanding of the chitosanase evolutionary process. However, the reviews for this aspect are completely unknown. This review provides an overview of the promiscuous activities, also considering the substrate and product specificity of chitosanases observed to date. These contribute to important implications for the future discovery and research of promiscuous chitosanases and applications related to biomass conversion. KEY POINTS: • The promiscuity of chitosanases is reviewed for the first time. • The current review provides insights into the substrate specificity of chitosanases. • The mode-product relationship and prospect of promiscuous chitosanases are highlighted.

Fungal cellulases: protein engineering and post-translational modifications

Enzymatic degradation of lignocelluloses into fermentable sugars to produce biofuels and other biomaterials is critical for environmentally sustainable development and energy resource supply. However, there are problems in enzymatic cellulose hydrolysis, such as the complex cellulase composition, low degradation efficiency, high production cost, and post-translational modifications (PTMs), all of which are closely related to specific characteristics of cellulases that remain unclear. These problems hinder the practical application of cellulases. Due to the rapid development of computer technology in recent years, computer-aided protein engineering is being widely used, which also brings new opportunities for the development of cellulases. Especially in recent years, a large number of studies have reported on the application of computer-aided protein engineering in the development of cellulases; however, these articles have not been systematically reviewed. This article focused on the aspect of protein engineering and PTMs of fungal cellulases. In this manuscript, the latest literatures and the distribution of potential sites of cellulases for engineering have been systematically summarized, which provide reference for further improvement of cellulase properties. KEY POINTS: •Rational design based on virtual mutagenesis can improve cellulase properties. •Modifying protein side chains and glycans helps obtain superior cellulases. •N-terminal glutamine-pyroglutamate conversion stabilizes fungal cellulases.