Automated in vivo enzyme engineering accelerates biocatalyst optimization

Achieving cost-competitive bio-based processes requires development of stable and selective biocatalysts. Their realization through in vitro enzyme characterization and engineering is mostly low throughput and labor-intensive. Therefore, strategies for increasing throughput while diminishing manual labor are gaining momentum, such as in vivo screening and evolution campaigns. Computational tools like machine learning further support enzyme engineering efforts by widening the explorable design space. Here, we propose an integrated solution to enzyme engineering challenges whereby ML-guided, automated workflows (including library generation, implementation of hypermutation systems, adapted laboratory evolution, and in vivo growth-coupled selection) could be realized to accelerate pipelines towards superior biocatalysts.

Frustration can Limit the Adaptation of Promiscuous Enzymes Through Gene Duplication and Specialisation

Virtually all enzymes catalyse more than one reaction, a phenomenon known as enzyme promiscuity. It is unclear whether promiscuous enzymes are more often generalists that catalyse multiple reactions at similar rates or specialists that catalyse one reaction much more efficiently than other reactions. In addition, the factors that shape whether an enzyme evolves to be a generalist or a specialist are poorly understood. To address these questions, we follow a three-pronged approach. First, we examine the distribution of promiscuity in empirical enzymes reported in the BRENDA database. We find that the promiscuity distribution of empirical enzymes is bimodal. In other words, a large fraction of promiscuous enzymes are either generalists or specialists, with few intermediates. Second, we demonstrate that enzyme biophysics is not sufficient to explain this bimodal distribution. Third, we devise a constraint-based model of promiscuous enzymes undergoing duplication and facing selection pressures favouring subfunctionalization. The model posits the existence of constraints between the catalytic efficiencies of an enzyme for different reactions and is inspired by empirical case studies. The promiscuity distribution predicted by our constraint-based model is consistent with the empirical bimodal distribution. Our results suggest that subfunctionalization is possible and beneficial only in certain enzymes. Furthermore, the model predicts that conflicting constraints and selection pressures can cause promiscuous enzymes to enter a 'frustrated' state, in which competing interactions limit the specialisation of enzymes. We find that frustration can be both a driver and an inhibitor of enzyme evolution by duplication and subfunctionalization. In addition, our model predicts that frustration becomes more likely as enzymes catalyse more reactions, implying that natural selection may prefer catalytically simple enzymes. In sum, our results suggest that frustration may play an important role in enzyme evolution.

Data-Driven Protein Engineering for Improving Catalytic Activity and Selectivity

Protein engineering is essential for altering the substrate scope, catalytic activity and selectivity of enzymes for applications in biocatalysis. However, traditional approaches, such as directed evolution and rational design, encounter the challenge in dealing with the experimental screening process of a large protein mutation space. Machine learning methods allow the approximation of protein fitness landscapes and the identification of catalytic patterns using limited experimental data, thus providing a new avenue to guide protein engineering campaigns. In this concept article, we review machine learning models that have been developed to assess enzyme-substrate-catalysis performance relationships aiming to improve enzymes through data-driven protein engineering. Furthermore, we prospect the future development of this field to provide additional strategies and tools for achieving desired activities and selectivities.

Ultrahigh-Throughput Directed Evolution of Polymer-Degrading Enzymes Using Yeast Display

Enzymes that degrade synthetic polymers have attracted intense interest for eco-friendly plastic recycling. However, because enzymes did not evolve for the cleavage of abiotic polymers, directed evolution strategies are needed to enhance activity for plastic degradation. Previous directed evolution efforts relied on polymer degradation assays that were limited to screening ∼104 mutants. Here, we report a high-throughput yeast surface display platform to rapidly evaluate >107 enzyme mutants for increased activity in cleaving synthetic polymers. In this platform, individual yeast cells display distinct mutants, and enzyme activity is detected by a change in fluorescence upon the cleavage of a synthetic probe resembling a polymer of interest. Highly active mutants are isolated by fluorescence activated cell sorting and identified through DNA sequencing. To demonstrate this platform, we performed directed evolution of a polyethylene terephthalate (PET)-depolymerizing enzyme, leaf and branch compost cutinase (LCC). We identified activity-boosting mutations that substantially increased the kinetics of degradation of solid PET films. Biochemical assays and molecular dynamics (MD) simulations of the most active variants suggest that the H218Y mutation improves the binding of the enzyme to PET. Overall, this evolution platform increases the screening throughput of polymer-degrading enzymes by 3 orders of magnitude and identifies mutations that enhance kinetics for depolymerizing solid substrates.

Biosensor-guided discovery and engineering of metabolic enzymes

A variety of chemicals have been produced through metabolic engineering approaches, and enhancing biosynthesis performance can be achieved by using enzymes with high catalytic efficiency. Accordingly, a number of efforts have been made to discover enzymes in nature for various applications. In addition, enzyme engineering approaches have been attempted to suit specific industrial purposes. However, a significant challenge in enzyme discovery and engineering is the efficient screening of enzymes with the desired phenotype from extensive enzyme libraries. To overcome this bottleneck, genetically encoded biosensors have been developed to specifically detect target molecules produced by enzyme activity at the intracellular level. Especially, the biosensors facilitate high-throughput screening (HTS) of targeted enzymes, expanding enzyme discovery and engineering strategies with advances in systems and synthetic biology. This review examines biosensor-guided HTS systems and highlights studies that have utilized these tools to discover enzymes in diverse areas and engineer enzymes to enhance their properties, such as catalytic efficiency, specificity, and stability.

Enzyme function and evolution through the lens of bioinformatics

Enzymes have been shaped by evolution over billions of years to catalyse the chemical reactions that support life on earth. Dispersed in the literature, or organised in online databases, knowledge about enzymes can be structured in distinct dimensions, either related to their quality as biological macromolecules, such as their sequence and structure, or related to their chemical functions, such as the catalytic site, kinetics, mechanism, and overall reaction. The evolution of enzymes can only be understood when each of these dimensions is considered. In addition, many of the properties of enzymes only make sense in the light of evolution. We start this review by outlining the main paradigms of enzyme evolution, including gene duplication and divergence, convergent evolution, and evolution by recombination of domains. In the second part, we overview the current collective knowledge about enzymes, as organised by different types of data and collected in several databases. We also highlight some increasingly powerful computational tools that can be used to close gaps in understanding, in particular for types of data that require laborious experimental protocols. We believe that recent advances in protein structure prediction will be a powerful catalyst for the prediction of binding, mechanism, and ultimately, chemical reactions. A comprehensive mapping of enzyme function and evolution may be attainable in the near future.

From nature to industry: Harnessing enzymes for biocatalysis

Biocatalysis harnesses enzymes to make valuable products. This green technology is used in countless applications from bench scale to industrial production and allows practitioners to access complex organic molecules, often with fewer synthetic steps and reduced waste. The last decade has seen an explosion in the development of experimental and computational tools to tailor enzymatic properties, equipping enzyme engineers with the ability to create biocatalysts that perform reactions not present in nature. By using (chemo)-enzymatic synthesis routes or orchestrating intricate enzyme cascades, scientists can synthesize elaborate targets ranging from DNA and complex pharmaceuticals to starch made in vitro from CO2-derived methanol. In addition, new chemistries have emerged through the combination of biocatalysis with transition metal catalysis, photocatalysis, and electrocatalysis. This review highlights recent key developments, identifies current limitations, and provides a future prospect for this rapidly developing technology.

Control analysis in the identification of key enzymes driving metabolic adaptations: Towards drug target discovery

Metabolic Control Analysis (MCA) marked a turning point in understanding the design principles of metabolic network control by establishing control coefficients as a means to quantify the degree of control that an enzyme exerts on flux or metabolite concentrations. MCA has demonstrated that control of metabolic pathways is distributed among many enzymes rather than depending on a single rate-limiting step. MCA also proved that this distribution depends not only on the stoichiometric structure of the network but also on other kinetic determinants, such as the degree of saturation of the enzyme active site, the distance to thermodynamic equilibrium, and metabolite feedback regulatory loops. Consequently, predicting the alterations that occur during metabolic adaptation in response to strong changes involving a redistribution in such control distribution can be challenging. Here, using the framework provided by MCA, we illustrate how control distribution in a metabolic pathway/network depends on enzyme kinetic determinants and to what extent the redistribution of control affects our predictions on candidate enzymes suitable as targets for small molecule inhibition in the drug discovery process. Our results uncover that kinetic determinants can lead to unexpected control distribution and outcomes that cannot be predicted solely from stoichiometric determinants. We also unveil that the inference of key enzyme-drivers of an observed metabolic adaptation can be dramatically improved using mean control coefficients and ruling out those enzyme activities that are associated with low control coefficients. As the use of constraint-based stoichiometric genome-scale metabolic models (GSMMs) becomes increasingly prevalent for identifying genes/enzymes that could be potential drug targets, we anticipate that incorporating kinetic determinants and ruling out enzymes with low control coefficients into GSMM workflows will facilitate more accurate predictions and reveal novel therapeutic targets.

Rank-ordering of known enzymes as starting points for re-engineering novel substrate activity using a convolutional neural network

Retro-biosynthetic approaches have made significant advances in predicting synthesis routes of target biofuel, bio-renewable or bio-active molecules. The use of only cataloged enzymatic activities limits the discovery of new production routes. Recent retro-biosynthetic algorithms increasingly use novel conversions that require altering the substrate or cofactor specificities of existing enzymes while connecting pathways leading to a target metabolite. However, identifying and re-engineering enzymes for desired novel conversions are currently the bottlenecks in implementing such designed pathways. Herein, we present EnzRank, a convolutional neural network (CNN) based approach, to rank-order existing enzymes in terms of their suitability to undergo successful protein engineering through directed evolution or de novo design towards a desired specific substrate activity. We train the CNN model on 11,800 known active enzyme-substrate pairs from the BRENDA database as positive samples and data generated by scrambling these pairs as negative samples using substrate dissimilarity between an enzyme's native substrate and all other molecules present in the dataset using Tanimoto similarity score. EnzRank achieves an average recovery rate of 80.72% and 73.08% for positive and negative pairs on test data after using a 10-fold holdout method for training and cross-validation. We further developed a web-based user interface (available at https://huggingface.co/spaces/vuu10/EnzRank) to predict enzyme-substrate activity using SMILES strings of substrates and enzyme sequence as input to allow convenient and easy-to-use access to EnzRank. In summary, this effort can aid de novo pathway design tools to prioritize starting enzyme re-engineering candidates for novel reactions as well as in predicting the potential secondary activity of enzymes in cell metabolism.

Rapid prototyping enzyme homologs to improve titer of nicotinamide mononucleotide using a strategy combining cell-free protein synthesis with split GFP

Engineering biological systems to test new pathway variants containing different enzyme homologs is laborious and time-consuming. To tackle this challenge, a strategy was developed for rapidly prototyping enzyme homologs by combining cell-free protein synthesis (CFPS) with split green fluorescent protein (GFP). This strategy featured two main advantages: (1) dozens of enzyme homologs were parallelly produced by CFPS within hours, and (2) the expression level and activity of each homolog was determined simultaneously by using the split GFP assay. As a model, this strategy was applied to optimize a 3-step pathway for nicotinamide mononucleotide (NMN) synthesis. Ten enzyme homologs from different organisms were selected for each step. Here, the most productive homolog of each step was identified within 24 h rather than weeks or months. Finally, the titer of NMN was increased to 1213 mg/L by improving physiochemical conditions, tuning enzyme ratios and cofactor concentrations, and decreasing the feedback inhibition, which was a more than 12-fold improvement over the initial setup. This strategy would provide a promising way to accelerate design-build-test cycles for metabolic engineering to improve the production of desired products.

Data-driven enzyme engineering to identify function-enhancing enzymes

Identifying function-enhancing enzyme variants is a 'holy grail' challenge in protein science because it will allow researchers to expand the biocatalytic toolbox for late-stage functionalization of drug-like molecules, environmental degradation of plastics and other pollutants, and medical treatment of food allergies. Data-driven strategies, including statistical modeling, machine learning, and deep learning, have largely advanced the understanding of the sequence-structure-function relationships for enzymes. They have also enhanced the capability of predicting and designing new enzymes and enzyme variants for catalyzing the transformation of new-to-nature reactions. Here, we reviewed the recent progresses of data-driven models that were applied in identifying efficiency-enhancing mutants for catalytic reactions. We also discussed existing challenges and obstacles faced by the community. Although the review is by no means comprehensive, we hope that the discussion can inform the readers about the state-of-the-art in data-driven enzyme engineering, inspiring more joint experimental-computational efforts to develop and apply data-driven modeling to innovate biocatalysts for synthetic and pharmaceutical applications.

A designed photoenzyme for enantioselective [2+2] cycloadditions

The ability to program new modes of catalysis into proteins would allow the development of enzyme families with functions beyond those found in nature. To this end, genetic code expansion methodology holds particular promise, as it allows the site-selective introduction of new functional elements into proteins as noncanonical amino acid side chains1-4. Here we exploit an expanded genetic code to develop a photoenzyme that operates by means of triplet energy transfer (EnT) catalysis, a versatile mode of reactivity in organic synthesis that is not accessible to biocatalysis at present5-12. Installation of a genetically encoded photosensitizer into the beta-propeller scaffold of DA_20_00 (ref. 13) converts a de novo Diels-Alderase into a photoenzyme for [2+2] cycloadditions (EnT1.0). Subsequent development and implementation of a platform for photoenzyme evolution afforded an efficient and enantioselective enzyme (EnT1.3, up to 99% enantiomeric excess (e.e.)) that can promote intramolecular and bimolecular cycloadditions, including transformations that have proved challenging to achieve selectively with small-molecule catalysts. EnT1.3 performs >300 turnovers and, in contrast to small-molecule photocatalysts, can operate effectively under aerobic conditions and at ambient temperatures. An X-ray crystal structure of an EnT1.3-product complex shows how multiple functional components work in synergy to promote efficient and selective photocatalysis. This study opens up a wealth of new excited-state chemistry in protein active sites and establishes the framework for developing a new generation of enantioselective photocatalysts.

Oviposition behaviour and biochemical response of an insect pest, Zeugodacus cucurbitae (Coquillett) (Diptera: Tephritidae) to plant phenolic compound phloroglucinol

Phenolic compounds are the secondary metabolites (SMs) present in plants carrying different bioactivities. In the present study, we explored the influence of a phenolic compound namely phloroglucinol on oviposition behaviour and different biochemical entities of an insect pest Zeugodacus cucurbitae (Coquillett) (Diptera: Tephritidae) using artificial diet. Phloroglucinol (IUPAC name: benzene-1,3,5-triol) affected the activity of antioxidant and detoxifying enzymes viz. superoxide dismutases (SOD), catalase (CAT), ascorbate peroxidases (APOX). dehydroascorbate reductase (DHAR), peroxidases (POX), phenol oxidase (PO), glutathione peroxidase (GPOX), glutathione S-transferase peroxidase (GSTpox), glutathione reductase (GR), glutathione S-transferase (GST) and esterases (EST) as well as the biological antioxidants viz. ascorbate content and glutathione. The lipid peroxide content (LP) and hydrogen peroxide content (H₂O₂) were significantly enhanced in the treated larvae indicating oxidative stress in the insect. Significant inhibition in oviposition was observed and effective repellency percentage increased with phloroglucinol treatment as compared to control. The oviposition deterrent activity and toxic effects of phloroglucinol on various biochemical parameters of Z. cucurbitae larvae revealed in the present study clearly confirms its suitability for use in pest management.

Using continuous directed evolution to improve enzymes for plant applications

Continuous directed evolution of enzymes and other proteins in microbial hosts is capable of outperforming classical directed evolution by executing hypermutation and selection concurrently in vivo, at scale, with minimal manual input. Provided that a target enzyme's activity can be coupled to growth of the host cells, the activity can be improved simply by selecting for growth. Like all directed evolution, the continuous version requires no prior mechanistic knowledge of the target. Continuous directed evolution is thus a powerful way to modify plant or non-plant enzymes for use in plant metabolic research and engineering. Here, we first describe the basic features of the yeast (Saccharomyces cerevisiae) OrthoRep system for continuous directed evolution and compare it briefly with other systems. We then give a step-by-step account of three ways in which OrthoRep can be deployed to evolve primary metabolic enzymes, using a THI4 thiazole synthase as an example and illustrating the mutational outcomes obtained. We close by outlining applications of OrthoRep that serve growing demands (i) to change the characteristics of plant enzymes destined for return to plants, and (ii) to adapt ("plantize") enzymes from prokaryotes-especially exotic prokaryotes-to function well in mild, plant-like conditions.

Identification and characterization of unique 5-hydroxyisoflavonoid biosynthetic key enzyme genes in Lupinus albus

5-Hydroxyisoflavonoids, no 5-deoxyisoflavonoids, in Lupinus species, are due to lack of CHRs and Type II CHIs, and the key enzymes of isoflavonoid biosynthetic pathway in white lupin were identified. White lupin (Lupinus albus) is used as food ingredients owing to rich protein, low starch, and rich bioactive compounds such as isoflavonoids. The isoflavonoids biosynthetic pathway in white lupin still remains unclear. In this study, only 5-hydroxyisoflavonoids, but no 5-deoxyisoflavonoids, were detected in white lupin and other Lupinus species. No 5-deoxyisoflavonoids in Lupinus species are due to lack of CHRs and Type II CHIs. We further found that the CHI gene cluster containing both Type I and Type II CHIs possibly arose after the divergence of Lupinus with other legume clade. LaCHI1 and LaCHI2 identified from white lupin metabolized naringenin chalcone to naringenin in yeast and tobacco (Nicotiana benthamiana), and were bona fide Type I CHIs. We further identified two isoflavone synthases (LaIFS1 and LaIFS2), catalyzing flavanone naringenin into isoflavone genistein and also catalyzing liquiritigenin into daidzein in yeast and tobacco. In addition, LaG6DT1 and LaG6DT2 prenylated genistein at the C-6 position into wighteone. Two glucosyltransferases LaUGT1 and LaUGT2 metabolized genistein and wighteone into its 7-O-glucosides. Taken together, our study not only revealed that exclusive 5-hydroxyisoflavonoids do exist in Lupinus species, but also identified key enzymes in the isoflavonoid biosynthetic pathway in white lupin.

H2S aids osmotic stress resistance by S-sulfhydration of melatonin production-related enzymes in Arabidopsis thaliana

Hydrogen sulfide closed Arabidopsis thaliana stomata by increasing the transcription of melatonin-producing enzymes and the post-translational modification levels to combat osmotic stress. Hydrogen sulfide (H₂S) and melatonin (MEL) reportedly have similar functions in many aspects of plant growth, development and stress response. They regulate stomatal movement and enhance drought resistance. However, their physiological relationship is not well understood. Here, their crosstalk involved in osmotic stress resistance in Arabidopsis thaliana was studied. Exogenous H₂S and MEL closed stomata under normal or osmotic stress conditions and increased the relative water contents of plants under osmotic stress conditions. At the same time, exogenous H₂S and MEL responded to osmotic stress by increasing the content of proline and soluble sugar, and reducing malondialdehyde (MDA) content and relative conductivity. Using mutants in the MEL-associated production of serotonin N-acetyltransferase (snat), caffeic acid O-methyltransferase (comt1) and N-acetylserotonin methyltransferase (asmt), we determined that H₂S was partially dependent on MEL to close stomata. Additionally, the overexpression of ASMT promoted stomatal closure. Exogenous H₂S increased the transcription levels of SNAT, ASMT and COMT1. Furthermore, exogenous H₂S treatments increased the endogenous MEL content significantly. At the post-translational level, H₂S sulfhydrated the SNAT and ASMT, but not COMT1, enzymes associated with MEL production. Thus, H₂S appeared to promote stomatal closure in response to osmotic stress by increasing the transcription levels of MEL synthesis-related genes and the sulfhydryl modification of the encoded enzymes. These results increased our understanding of H₂S and MEL functions and interactions under osmotic stress conditions.

Transcriptional and physiological data revealed cold tolerance in a photo-thermo sensitive genic male sterile line Yu17S

BACKGROUND

Rice is highly sensitive to chilling stress during the seedling stage. However, the adaptable photo-thermo sensitive genic male sterile (PTGMS) rice line, Yu17S, exhibits tolerance to low temperatures. Currently, the molecular characteristics of Yu17S are unclear.

RESULTS

To evaluate the molecular mechanisms behind cold responses in rice seedlings, a comparative transcriptome analysis was performed in Yu17S during seedling development under normal temperature and low temperature conditions. In total, 9317 differentially expressed genes were detected. Gene ontology and pathway analyses revealed that these genes were involved mostly in photosynthesis, carotenoid biosynthesis, carbohydrate metabolism and plant hormone signal transduction. An integrated analysis of specific pathways combined with physiological data indicated that rice seedlings improved the performance of photosystem II when exposed to cold conditions. Genes involved in starch degradation and sucrose metabolism were activated in rice plants exposed to cold stress treatments, which was accompanied by the accumulation of soluble sugar, trehalose, raffinose and galactinol. Furthermore, chilling stress induced the expression of phytoene desaturase, 15-cis-ζ-carotene isomerase, ζ-carotene desaturase, carotenoid isomerase and β-carotene hydroxylase; this was coupled with the activation of carotenoid synthase activity and increases in abscisic acid (ABA) levels in rice seedlings.

CONCLUSIONS

Our results suggest that Yu17S exhibited better tolerance to cold stress with the activation of carotenoid synthase activity and increasing of ABA levels, and as well as the expression of photosynthesis-related genes under cold condition in rice seedlings.

Computational Enzyme Design at Zymvol

Directed evolution is the most recognized methodology for enzyme engineering. The main drawback resides in its random nature and in the limited sequence exploration; both require screening of thousands (if not millions) of variants to achieve a target function. Computer-driven approaches can limit laboratorial screening to a few hundred candidates, enabling and accelerating the development of industrial enzymes. In this book chapter, the technology adopted at Zymvol is described. An overview of the current development and future directions in the company is also provided.

A low-cost and open-source protocol to produce key enzymes for molecular detection assays

Here, we describe a detailed step-by-step protocol for the expression, purification, quantification, and activity determination of key enzymes for molecular detection of pathogens. Based on previous reports, we optimized the protocol for LbCas12a, Taq DNA polymerase, M-MLV reverse transcriptase, and TEV protease to make it compatible with minimal laboratory equipment, broadly available in low- and middle-income countries. The enzymes produced with this protocol have been successfully used for molecular detection applications. For complete details on the use and execution of this protocol, please refer to Alcántara et al. (2021a, 2021b).

Emerging Role of TCA Cycle-Related Enzymes in Human Diseases

The tricarboxylic acid (TCA) cycle is the main source of cellular energy and participates in many metabolic pathways in cells. Recent reports indicate that dysfunction of TCA cycle-related enzymes causes human diseases, such as neurometabolic disorders and tumors, have attracted increasing interest in their unexplained roles. The diseases which develop as a consequence of loss or dysfunction of TCA cycle-related enzymes are distinct, suggesting that each enzyme has a unique function. This review aims to provide a comprehensive overview of the relationship between each TCA cycle-related enzyme and human diseases. We also discuss their functions in the context of both mitochondrial and extra-mitochondrial (or cytoplasmic) enzymes.

Droplet Microfluidics and Directed Evolution of Enzymes: An Intertwined Journey

Evolution is essential to the generation of complexity and ultimately life. It relies on the propagation of the properties, traits, and characteristics that allow an organism to survive in a challenging environment. It is evolution that shaped our world over about four billion years by slow and iterative adaptation. While natural evolution based on selection is slow and gradual, directed evolution allows the fast and streamlined optimization of a phenotype under selective conditions. The potential of directed evolution for the discovery and optimization of enzymes is mostly limited by the throughput of the tools and methods available for screening. Over the past twenty years, versatile tools based on droplet microfluidics have been developed to address the need for higher throughput. In this Review, we provide a chronological overview of the intertwined development of microfluidics droplet-based compartmentalization methods and in vivo directed evolution of enzymes.

Overexpression of AtDREB1 and BcZAT12 genes confers drought tolerance by reducing oxidative stress in double transgenic tomato (Solanum lycopersicum L.)

Double transgenic tomato developed by AtDREB1A and BcZAT12 genes pyramiding showed significant drought tolerance by reducing oxidative stress with enhanced yield. Although a large number of efforts have been made by different researchers to develop abiotic stress tolerance tomato for improving yield using single gene, however, no reports are available which targets AtDREB1 and BcZAT12 genes together. Hence, in the present study, double transgenic plants were developed using AtDREB1 and BcZAT12 genes to improve yield potential with better drought tolerance. Double transgenic (DZ1-DZ5) tomato lines showed enhanced drought tolerance than their counterpart non-transgenic and single transgenic plants at 0, 07, 14, and 21 days of water deficit, respectively. Double transgenic plants showed increased activity of antioxidant enzymes, like catalase (CAT), superoxide dismutase (SOD), glutathione reductase (GR), ascorbate peroxidase (APX), dehydroascorbate reductase (DHAR), monodehydroascorbate reductase (MDHAR) and guaiacol peroxidase (POD), and accumulation of non-enzymatic antioxidants like ascorbic acid, glutathione as compared to non-transgenic and single transgenic. Additionally, the transcript analysis of antioxidant enzymes revealed the increased level of gene expression in double transgenic tomato lines. Developed double-transgenic tomato plants co-over-expressing both genes exhibited more enzymatic and non-enzymatic anti-oxidative activities as compared to the non-transgenic and single transgenic control, respectively. This is the preliminary report in tomato, which forms the basis for a multigene transgenic approach to cope with drought stress.

Overexpression of AtDREB1 and BcZAT12 genes confers drought tolerance by reducing oxidative stress in double transgenic tomato (Solanum lycopersicum L.)

Double transgenic tomato developed by AtDREB1A and BcZAT12 genes pyramiding showed significant drought tolerance by reducing oxidative stress with enhanced yield. Although a large number of efforts have been made by different researchers to develop abiotic stress tolerance tomato for improving yield using single gene, however, no reports are available which targets AtDREB1 and BcZAT12 genes together. Hence, in the present study, double transgenic plants were developed using AtDREB1 and BcZAT12 genes to improve yield potential with better drought tolerance. Double transgenic (DZ1-DZ5) tomato lines showed enhanced drought tolerance than their counterpart non-transgenic and single transgenic plants at 0, 07, 14, and 21 days of water deficit, respectively. Double transgenic plants showed increased activity of antioxidant enzymes, like catalase (CAT), superoxide dismutase (SOD), glutathione reductase (GR), ascorbate peroxidase (APX), dehydroascorbate reductase (DHAR), monodehydroascorbate reductase (MDHAR) and guaiacol peroxidase (POD), and accumulation of non-enzymatic antioxidants like ascorbic acid, glutathione as compared to non-transgenic and single transgenic. Additionally, the transcript analysis of antioxidant enzymes revealed the increased level of gene expression in double transgenic tomato lines. Developed double-transgenic tomato plants co-over-expressing both genes exhibited more enzymatic and non-enzymatic anti-oxidative activities as compared to the non-transgenic and single transgenic control, respectively. This is the preliminary report in tomato, which forms the basis for a multigene transgenic approach to cope with drought stress.

Alfalfa (Medicago sativa L.) MsCML46 gene encoding calmodulin-like protein confers tolerance to abiotic stress in tobacco

KEY MESSAGE

MsCML46 enhances tolerance to abiotic stresses through alleviating osmotic stress and oxidative damage by regulating the expression of stress-related genes to optimize osmolytes levels and antioxidant enzyme activity in transgenic tobacco. Abiotic stresses are major environmental factors that constraint crop productivity worldwide. Various stimuli regulate intracellular calcium levels and calcium-mediated signal transduction, and cellular responses. Ca2+ signals are perceived by different Ca2+ receptors. Calmodulin-like protein (CML) is one of the best-characterized Ca2+ sensors which shares sequence similarity with highly conserved calmodulin (CaM) ubiquitously expressed in plants. Currently, the molecular and physiological functions of CMLs are largely unknown. In this study, the MsCML46 was characterized in alfalfa (Medicago sativa cv. Zhaodong) under freezing stress. Results showed that MsCML46 was localized to the cytoplasm of Arabidopsis, and its expression was strongly elevated by cold, drought, salt, saline-alkali, and ABA treatments. Overexpressing MsCML46 in tobacco enhanced tolerance to freezing, drought, and salt stresses as evidenced by improved contents of osmotic regulatory solutes and antioxidant enzyme activity but decreased reactive oxygen species (ROS) accumulation. Furthermore, cold, drought, and salt stresses increased the expression of stress-related genes in transgenic tobacco. MsCML46 binds free Ca2+ to promote signal transduction and maintain higher K+/Na+ ratio. In this way, it protects intracellular homeostasis under sodium ion toxicity. These results suggest that MsCML46 plays a crucial role in resisting abiotic stresses and can be exploited in genetic engineering for crops.

Dendrimers as Non-Viral Vectors in Gene-Directed Enzyme Prodrug Therapy

Gene-directed enzyme prodrug therapy (GDEPT) has been intensively studied as a promising new strategy of prodrug delivery, with its main advantages being represented by an enhanced efficacy and a reduced off-target toxicity of the active drug. In recent years, numerous therapeutic systems based on GDEPT strategy have entered clinical trials. In order to deliver the desired gene at a specific site of action, this therapeutic approach uses vectors divided in two major categories, viral vectors and non-viral vectors, with the latter being represented by chemical delivery agents. There is considerable interest in the development of non-viral vectors due to their decreased immunogenicity, higher specificity, ease of synthesis and greater flexibility for subsequent modulations. Dendrimers used as delivery vehicles offer many advantages, such as: nanoscale size, precise molecular weight, increased solubility, high load capacity, high bioavailability and low immunogenicity. The aim of the present work was to provide a comprehensive overview of the recent advances regarding the use of dendrimers as non-viral carriers in the GDEPT therapy.

Extensive regulation of enzyme activity by phosphorylation in Escherichia coli

Protein serine/threonine/tyrosine (S/T/Y) phosphorylation is an essential and frequent post-translational modification in eukaryotes, but historically has been considered less prevalent in bacteria because fewer proteins were found to be phosphorylated and most proteins were modified to a lower degree. Recent proteomics studies greatly expanded the phosphoproteome of Escherichia coli to more than 2000 phosphorylation sites (phosphosites), yet mechanisms of action were proposed for only six phosphosites and fitness effects were described for 38 phosphosites upon perturbation. By systematically characterizing functional relevance of S/T/Y phosphorylation in E. coli metabolism, we found 44 of the 52 mutated phosphosites to be functional based on growth phenotypes and intracellular metabolome profiles. By effectively doubling the number of known functional phosphosites, we provide evidence that protein phosphorylation is a major regulation process in bacterial metabolism. Combining in vitro and in vivo experiments, we demonstrate how single phosphosites modulate enzymatic activity and regulate metabolic fluxes in glycolysis, methylglyoxal bypass, acetate metabolism and the split between pentose phosphate and Entner-Doudoroff pathways through mechanisms that include shielding the substrate binding site, limiting structural dynamics, and disrupting interactions relevant for activity in vivo.

Antioxidant Effects of Elderberry Anthocyanins in Human Colon Carcinoma Cells: A Study on Structure-Activity Relationships

SCOPE

Glycosylation is a way to increase structure-stability of anthocyanins, yet compromises their bioactivity. The study investigates the antioxidant activity of purified cyanidin (Cy)-based anthocyanins and respective degradation products in Caco-2 clone C2BBe1 aiming to identify structure-activity relationships.

RESULTS AND METHODS

Cyanidin 3-O-glucoside (Cy-3-glc) and cyanidin 3-O-sambubioside (Cy-3-sam) proved to be most potent regarding antioxidant properties and protection against hydrogen peroxide (H2 O2 )-induced reactive oxygen species (ROS)-levels measured with the dichloro-fluorescein (DCF) assay. Cyanidin 3-O-sambubioside-5-O-glucoside (Cy-3-sam-5-glc) and cyanidin 3-O-rutinoside (Cy-3-rut) were less efficient and not protective, reflecting potential differences in uptake and/or degradation. Following ranking in antioxidant efficiency is suggested: (concentrations ≤10 × 10-6  M) Cy-3-glc ≥ Cy-3-sam > Cy-3-sam-5-glc ≈ Cy-3-rut ≈ Cy; (concentrations ≥50 × 10-6  M) Cy-3-glc ≈ Cy-3-sam ≥ Cy > Cy-3-sam-5-glc ≈ Cy-3-rut. Cy and protocatechuic acid (PCA) reduced ROS-levels as potent as the mono- and di-glycoside, whereas phloroglucinol aldehyde (PGA) displayed pro-oxidant properties. None of the degradation products protected from oxidative stress. Gene transcription analysis of catalase (CAT), superoxide-dismutase (SOD), glutathione-peroxidase (GPx), heme-oxygenase-1 (HO-1), and glutamate-cysteine-ligase (γGCL) suggest no activation of nuclear factor erythroid 2-related factor 2 (Nrf2).

CONCLUSION

More complex residues and numbers of sugar moieties appear to be counterproductive for antioxidant activity. Other mechanisms than Nrf2-activation should be considered for protective effects.

Combining functional metagenomics and glycoanalytics to identify enzymes that facilitate structural characterization of sulfated N-glycans

BACKGROUND

Sulfate modification of N-glycans is important for several biological functions such as clearance of pituitary hormones or immunoregulation. Yet, the prevalence of this N-glycan modification and its functions remain largely unexplored. Characterization of N-glycans bearing sulfate modifications is hampered in part by a lack of enzymes that enable site-specific detection of N-glycan sulfation. In this study, we used functional metagenomic screening to identify enzymes that act upon sulfated N-acetylglucosamine (GlcNAc). Using multiplexed capillary gel electrophoresis with laser-induced fluorescence detection (xCGE-LIF) -based glycoanalysis we proved their ability to act upon GlcNAc-6-SO4 on N-glycans.

RESULTS

Our screen identified a sugar-specific sulfatase that specifically removes sulfate from GlcNAc-6-SO4 when it is in a terminal position on an N-glycan. Additionally, in the absence of calcium, this sulfatase binds to the sulfated glycan but does not remove the sulfate group, suggesting it could be used for selective isolation of sulfated N-glycans. Further, we describe isolation of a sulfate-dependent hexosaminidase that removes intact GlcNAc-6-SO4 (but not asulfated GlcNAc) from a terminal position on N-glycans. Finally, the use of these enzymes to detect the presence of sulfated N-glycans by xCGE-LIF is demonstrated.

CONCLUSION

The present study demonstrates the feasibility of using functional metagenomic screening combined with glycoanalytics to discover enzymes that act upon chemical modifications of glycans. The discovered enzymes represent new specificities that can help resolve the presence of GlcNAc-6-SO4 in N-glycan structural analyses.

Virus-induced plant volatiles mediate the olfactory behaviour of its insect vectors

Plant viruses can manipulate their hosts to release odours that are attractive or repellent to their insect vectors. However, the volatile organic compounds (VOCs), either individually or as mixtures, which play a key role in the olfactory behaviour of insect vectors remains largely unknown. Our study focused on green rice leafhoppers (GRLHs) vectoring rice dwarf virus (RDV) revealed that RDV infection significantly induced the emission of (E)-β-caryophyllene and 2-heptanol by rice plants, which influenced the olfactory behaviour of both non-viruliferous and viruliferous GRLHs. (E)-β-caryophyllene attracted non-viruliferous GRLHs to settle on RDV-infected plants, but neither attracted nor repelled viruliferous GRLHs. In contrast, 2-heptanol repelled viruliferous GRLHs to settle on RDV-infected plants, but neither repelled nor attracted non-viruliferous GRLHs. Suppression of (E)-β-caryophyllene synthase OsCAS via CRISPR-Cas9 to generate oscas-1 plants enabled us to confirm the important role played by (E)-β-caryophyllene in modulating the virus-vector-host plant interaction. These novel results reveal the role of these virus-induced VOCs in modulating the behaviour of its GRLH insect vector and may facilitate the design of new strategies for disease control through manipulation of plant volatile emissions.

The evolution of the phenylpropanoid pathway entailed pronounced radiations and divergences of enzyme families

Land plants constantly respond to fluctuations in their environment. Part of their response is the production of a diverse repertoire of specialized metabolites. One of the foremost sources for metabolites relevant to environmental responses is the phenylpropanoid pathway, which was long thought to be a land-plant-specific adaptation shaped by selective forces in the terrestrial habitat. Recent data have, however, revealed that streptophyte algae, the algal relatives of land plants, have candidates for the genetic toolkit for phenylpropanoid biosynthesis and produce phenylpropanoid-derived metabolites. Using phylogenetic and sequence analyses, we here show that the enzyme families that orchestrate pivotal steps in phenylpropanoid biosynthesis have independently undergone pronounced radiations and divergence in multiple lineages of major groups of land plants; sister to many of these radiated gene families are streptophyte algal candidates for these enzymes. These radiations suggest a high evolutionary versatility in the enzyme families involved in the phenylpropanoid-derived metabolism across embryophytes. We suggest that this versatility likely translates into functional divergence, and may explain the key to one of the defining traits of embryophytes: a rich specialized metabolism.

Diurnal transcript profiling of the diatom Seminavis robusta reveals adaptations to a benthic lifestyle

Coastal regions contribute an estimated 20% of annual gross primary production in the oceans, despite occupying only 0.03% of their surface area. Diatoms frequently dominate coastal sediments, where they experience large variations in light regime resulting from the interplay of diurnal and tidal cycles. Here, we report on an extensive diurnal transcript profiling experiment of the motile benthic diatom Seminavis robusta. Nearly 90% (23 328) of expressed protein-coding genes and 66.9% (1124) of expressed long intergenic non-coding RNAs showed significant expression oscillations and are predominantly phasing at night with a periodicity of 24 h. Phylostratigraphic analysis found that rhythmic genes are enriched in highly conserved genes, while diatom-specific genes are predominantly associated with midnight expression. Integration of genetic and physiological cell cycle markers with silica depletion data revealed potential new silica cell wall-associated gene families specific to diatoms. Additionally, we observed 1752 genes with a remarkable semidiurnal (12-h) periodicity, while the expansion of putative circadian transcription factors may reflect adaptations to cope with highly unpredictable external conditions. Taken together, our results provide new insights into the adaptations of diatoms to the benthic environment and serve as a valuable resource for the study of diurnal regulation in photosynthetic eukaryotes.

Molecular basis for recognition of the Group A Carbohydrate backbone by the PlyC streptococcal bacteriophage endolysin

Endolysins are peptidoglycan (PG) hydrolases that function as part of the bacteriophage (phage) lytic system to release progeny phage at the end of a replication cycle. Notably, endolysins alone can produce lysis without phage infection, which offers an attractive alternative to traditional antibiotics. Endolysins from phage that infect Gram-positive bacterial hosts contain at least one enzymatically active domain (EAD) responsible for hydrolysis of PG bonds and a cell wall binding domain (CBD) that binds a cell wall epitope, such as a surface carbohydrate, providing some degree of specificity for the endolysin. Whilst the EADs typically cluster into conserved mechanistic classes with well-defined active sites, relatively little is known about the nature of the CBDs and only a few binding epitopes for CBDs have been elucidated. The major cell wall components of many streptococci are the polysaccharides that contain the polyrhamnose (pRha) backbone modified with species-specific and serotype-specific glycosyl side chains. In this report, using molecular genetics, microscopy, flow cytometry and lytic activity assays, we demonstrate the interaction of PlyCB, the CBD subunit of the streptococcal PlyC endolysin, with the pRha backbone of the cell wall polysaccharides, Group A Carbohydrate (GAC) and serotype c-specific carbohydrate (SCC) expressed by the Group A Streptococcus and Streptococcus mutans, respectively.

The steroid metabolome of pregnancy, insights into the maintenance of pregnancy and evolution of reproductive traits

Modes of mammalian reproduction are diverse and not always conserved among related species. Progesterone is universally required to supports pregnancy but sites of synthesis and metabolic pathways vary widely. The steroid metabolome of mid-to late gestation was characterized, focusing on 5α-reduced pregnanes in species representing the Perissodactyla, Cetartiodactyla and Carnivora using mass spectrometry. Metabolomes and steroidogenic enzyme ortholog sequences were used in heirarchial analyses. Steroid metabolite profiles were similar within orders, whales within cetartiodactyls for instance, but with notable exceptions such as rhinoceros clustering with goats, and tapirs with pigs. Steroidogenic enzyme sequence clustering reflected expected evolutionary relationships but once again with exceptions. Human sequences (expected outgroups) clustered with perissodactyl CYP11A1, CYP17A1 and SRD5A1 gene orthologues, forming outgroups only for HSD17B1 and SRD5A2. Spotted hyena CYP19A1 clustered within the Perissodactyla, between rhinoceros and equid orthologues, whereas CYP17A1 clustered within the Carnivora. This variability highlights the random adoption of divergent physiological strategies as pregnancy evolved among genetically similar species.

Recombinant Expression of Trametes versicolor Aflatoxin B1-Degrading Enzyme (TV-AFB1D) in Engineering Pichia pastoris GS115 and Application in AFB1 Degradation in AFB1-Contaminated Peanuts

Aflatoxins seriously threaten the health of humans and animals due to their potential carcinogenic properties. Enzymatic degradation approach is an effective and environmentally friendly alternative that involves changing the structure of aflatoxins. In this study, Trametes versicolor aflatoxin B₁-degrading enzyme gene (TV-AFB₁D) was integrated into the genome of Pichia pastoris GS115 by homologous recombination approach. The recombinant TV-AFB₁D was expressed in engineering P. pastoris with a size of approximately 77 kDa under the induction of methanol. The maximum activity of TV-AFB₁D reached 17.5 U/mL after the induction of 0.8% ethanol (v/v) for 84 h at 28 °C. The AFB₁ proportion of 75.9% was degraded using AFB₁ standard sample after catalysis for 12 h. In addition, the AFB₁ proportion was 48.5% using AFB₁-contaminated peanuts after the catalysis for 18 h at 34 °C. The recombinant TV-AFB₁D would have good practical application value in AFB₁ degradation in food crops. This study provides an alternative degrading enzyme for the degradation of AFB₁ in aflatoxin-contaminated grain and feed via enzymatic degradation approach.

A multi-omics approach to lignocellulolytic enzyme discovery reveals a new ligninase activity from Parascedosporium putredinis NO1

Lignocellulose, the structural component of plant cells, is a major agricultural byproduct and the most abundant terrestrial source of biopolymers on Earth. The complex and insoluble nature of lignocellulose limits its conversion into value-added commodities, and currently, efficient transformation requires expensive pretreatments and high loadings of enzymes. Here, we report on a fungus from the Parascedosporium genus, isolated from a wheat-straw composting community, that secretes a large and diverse array of carbohydrate-active enzymes (CAZymes) when grown on lignocellulosic substrates. We describe an oxidase activity that cleaves the major β-ether units in lignin, thereby releasing the flavonoid tricin from monocot lignin and enhancing the digestion of lignocellulose by polysaccharidase mixtures. We show that the enzyme, which holds potential for the biorefining industry, is widely distributed among lignocellulose-degrading fungi from the Sordariomycetes phylum.

Da-Huang-Xiao-Shi decoction protects against3, 5-diethoxycarbonyl-1,4-dihydroxychollidine-induced chronic cholestasis by upregulating bile acid metabolic enzymes and efflux transporters

ETHNOPHARMACOLOGICAL RELEVANCE

Chronic cholestasis is a usual clinical pathological process in hepatopathy and has few treatment options; it is classified under the category of jaundice in Chinese medicine. Da-Huang-Xiao-Shi decoction (DHXSD) is a classic Chinese prescription which is used to treat jaundice.

AIM OF THE STUDY

We aimed to examine the protective effect of DHXSD on liver and its potential mechanism of action against chronic cholestasis.

MATERIALS AND METHODS

Chronic cholestasis was induced using 3, 5-diethoxycarbonyl-1,4-dihydroxychollidine (DDC) in mice. Mice were then administered DHXSD intragastrically at doses of 3.68, 7.35, and 14.70 g/kg for four weeks followed by further analyses. Serum biochemical indices and liver pathology were explored. Eighteen individual bile acids (BAs) in mice serum and liver were quantified using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). The expression of BA related metabolic enzymes, transporters, along with nuclear receptor farnesoid X receptor (FXR) was detected by real-time qPCR and Western blot.

RESULTS

DHXSD treatment reduced the serum biochemical indices, ameliorated pathological injury, and improved the disordered BA homeostasis. Mice treated with DHXSD showed significantly upregulated expression of the metabolic enzymes, cytochrome P450 2b10 (Cyp2b10), Cyp3a11, and UDP-glucuronosyltransferase 1a1 (Ugt1a1); and the bile acid transporters, multidrug resistance protein 2 (Mdr2), bile salt export pump (Bsep), and multidrug resistance-associated protein 3 (Mrp3). DHXSD treatment also significantly upregulated FXR expression in mice with DDC-induced chronic cholestasis.

CONCLUSIONS

DHXSD exerted protective effects on chronic cholestasis in DDC-treated mice by alleviating the disordered homeostasis of BAs through increased expression of BA related metabolic enzymes and efflux transporters.

Diversity of Conopeptides and Conoenzymes from the Venom Duct of the Marine Cone Snail Conus bayani as Determined from Transcriptomic and Proteomic Analyses

Marine cone snails are predatory gastropods characterized by a well-developed venom apparatus and highly evolved hunting strategies that utilize toxins to paralyze prey and defend against predators. The venom of each species of cone snail has a large number of pharmacologically active peptides known as conopeptides or conotoxins that are usually unique in each species. Nevertheless, venoms of only very few species have been characterized so far by transcriptomic approaches. In this study, we used transcriptome sequencing technologies and mass spectrometric methods to describe the diversity of venom components expressed by a worm-hunting species, Conus bayani. A total of 82 conotoxin sequences were retrieved from transcriptomic data that contain 54 validated conotoxin sequences clustered into 21 gene superfamilies including divergent gene family, 17 sequences clustered to 6 different conotoxin classes, and 11 conotoxins classified as unassigned gene family. Seven new conotoxin sequences showed unusual cysteine patterns. We were also able to identify 19 peptide sequences using mass spectrometry that completely overlapped with the conotoxin sequences obtained from transcriptome analysis. Importantly, herein we document the presence of 16 proteins that include five post-translational modifying enzymes obtained from transcriptomic data. Our results revealed diverse and novel conopeptides of an unexplored species that could be used extensively in biomedical research due to their therapeutic potentials.

tRNA-modifying enzyme mutations induce codon-specific mistranslation and protein aggregation in yeast

Protein synthesis rate and accuracy are tightly controlled by the cell and are essential for proteome homoeostasis (proteostasis); however, the full picture of how mRNA translational factors maintain protein synthesis accuracy and co-translational protein folding are far from being fully understood. To address this question, we evaluated the role of 70 yeast tRNA-modifying enzyme genes on protein aggregation and used mass spectrometry to identify the aggregated proteins. We show that modification of uridine at anticodon position 34 (U34) by the tRNA-modifying enzymes Elp1, Elp3, Sml3 and Trm9 is critical for proteostasis, the mitochondrial tRNA-modifying enzyme Slm3 plays a fundamental role in general proteostasis and that stress response proteins whose genes are enriched in codons decoded by tRNAs lacking mcm5U34, mcm5s2U34, ncm5U34, ncm5Um34, modifications are overrepresented in protein aggregates of the ELP1, SLM3 and TRM9 KO strains. Increased rates of amino acid misincorporation were also detected in these strains at protein sites that specifically mapped to the codons sites that are decoded by the hypomodified tRNAs, demonstrating that U34 tRNA modifications safeguard the proteome from translational errors, protein misfolding and proteotoxic stress.

Genetically Encodable Scaffolds for Optimizing Enzyme Function

Enzyme engineering is an indispensable tool in the field of synthetic biology, where enzymes are challenged to carry out novel or improved functions. Achieving these goals sometimes goes beyond modifying the primary sequence of the enzyme itself. The use of protein or nucleic acid scaffolds to enhance enzyme properties has been reported for applications such as microbial production of chemicals, biosensor development and bioremediation. Key advantages of using these assemblies include optimizing reaction conditions, improving metabolic flux and increasing enzyme stability. This review summarizes recent trends in utilizing genetically encodable scaffolds, developed in line with synthetic biology methodologies, to complement the purposeful deployment of enzymes. Current molecular tools for constructing these synthetic enzyme-scaffold systems are also highlighted.

Molecular biology interventions for activity improvement and production of industrial enzymes

Metagenomics and directed evolution technology have brought a revolution in search of novel enzymes from extreme environment and improvement of existing enzymes and tuning them towards certain desired properties. Using advanced tools of molecular biology i.e. next generation sequencing, site directed mutagenesis, fusion protein, surface display, etc. now researchers can engineer enzymes for improved activity, stability, and substrate specificity to meet the industrial demand. Although many enzymatic processes have been developed up to industrial scale, still there is a need to overcome limitations of maintaining activity during the catalytic process. In this article recent developments in enzymes industrial applications and advancements in metabolic engineering approaches to improve enzymes efficacy and production are reviewed.

System-wide identification and prioritization of enzyme substrates by thermal analysis

Despite the immense importance of enzyme-substrate reactions, there is a lack of general and unbiased tools for identifying and prioritizing substrate proteins that are modified by the enzyme on the structural level. Here we describe a high-throughput unbiased proteomics method called System-wide Identification and prioritization of Enzyme Substrates by Thermal Analysis (SIESTA). The approach assumes that the enzymatic post-translational modification of substrate proteins is likely to change their thermal stability. In our proof-of-concept studies, SIESTA successfully identifies several known and novel substrate candidates for selenoprotein thioredoxin reductase 1, protein kinase B (AKT1) and poly-(ADP-ribose) polymerase-10 systems. Wider application of SIESTA can enhance our understanding of the role of enzymes in homeostasis and disease, opening opportunities to investigate the effect of post-translational modifications on signal transduction and facilitate drug discovery.

Comparative Genomics: Insights on the Pathogenicity and Lifestyle of Rhizoctonia solani

Proper management of agricultural disease is important to ensure sustainable food security. Staple food crops like rice, wheat, cereals, and other cash crops hold great export value for countries. Ensuring proper supply is critical; hence any biotic or abiotic factors contributing to the shortfall in yield of these crops should be alleviated. Rhizoctonia solani is a major biotic factor that results in yield losses in many agriculturally important crops. This paper focuses on genome informatics of our Malaysian Draft R. solani AG1-IA, and the comparative genomics (inter- and intra- AG) with four AGs including China AG1-IA (AG1-IA_KB317705.1), AG1-IB, AG3, and AG8. The genomic content of repeat elements, transposable elements (TEs), syntenic genomic blocks, functions of protein-coding genes as well as core orthologous genic information that underlies R. solani’s pathogenicity strategy were investigated. Our analyses show that all studied AGs have low content and varying profiles of TEs. All AGs were dominant for Class I TE, much like other basidiomycete pathogens. All AGs demonstrate dominance in Glycoside Hydrolase protein-coding gene assignments suggesting its importance in infiltration and infection of host. Our profiling also provides a basis for further investigation on lack of correlation observed between number of pathogenicity and enzyme-related genes with host range. Despite being grouped within the same AG with China AG1-IA, our Draft AG1-IA exhibits differences in terms of protein-coding gene proportions and classifications. This implies that strains from similar AG do not necessarily have to retain similar proportions and classification of TE but must have the necessary arsenal to enable successful infiltration and colonization of host. In a larger perspective, all the studied AGs essentially share core genes that are generally involved in adhesion, penetration, and host colonization. However, the different infiltration strategies will depend on the level of host resilience where this is clearly exhibited by the gene sets encoded for the process of infiltration, infection, and protection from host.

Suppression on postharvest juice sac granulation and cell wall modification by chitosan treatment in harvested pummelo (Citrus grandis L. Osbeck) stored at room temperature

Deposition of both lignin and cellulose accompanied by juice sac granulation is widespread in harvested citrus fruit. Hence, measures to suppress postharvest granulation of 'Majiayou' pummelo is of great importance. The fruit was treated with 1.5% chitosan and then stored at room temperature (20 ± 2 °C) for 150 d. As compared to the control fruits, chitosan coating significantly suppressed granulation index and maintained good quality. Chitosan coating inhibited lignification by suppressing the activities and expression levels of lignin synthesis-related enzymes (PAL, CAD and POD). By contrast, chitosan treatment enhanced the activities and expression levels of cell wall degrading enzymes, including PME, PG, Cx, XTH and β-Gal, which might contribute to the decrease in cellulose. In a nutshell, chitosan coating can effectively suppress juice sac granulation and fruit senescence of pummelo fruits, and play a crucial role in maintaining the cell wall modification.

Computational design of enzymes for biotechnological applications

Enzymes are the natural catalysts that execute biochemical reactions upholding life. Their natural effectiveness has been fine-tuned as a result of millions of years of natural evolution. Such catalytic effectiveness has prompted the use of biocatalysts from multiple sources on different applications, including the industrial production of goods (food and beverages, detergents, textile, and pharmaceutics), environmental protection, and biomedical applications. Natural enzymes often need to be improved by protein engineering to optimize their function in non-native environments. Recent technological advances have greatly facilitated this process by providing the experimental approaches of directed evolution or by enabling computer-assisted applications. Directed evolution mimics the natural selection process in a highly accelerated fashion at the expense of arduous laboratory work and economic resources. Theoretical methods provide predictions and represent an attractive complement to such experiments by waiving their inherent costs. Computational techniques can be used to engineer enzymatic reactivity, substrate specificity and ligand binding, access pathways and ligand transport, and global properties like protein stability, solubility, and flexibility. Theoretical approaches can also identify hotspots on the protein sequence for mutagenesis and predict suitable alternatives for selected positions with expected outcomes. This review covers the latest advances in computational methods for enzyme engineering and presents many successful case studies.

Honey as a Functional Food for Apis mellifera

Although nectar is consumed, primarily as a supplemental food, by a broad range of insects spanning at least five orders, it is processed and stored by only a small number of species, most of which are bees and wasps in the superfamily Apoidea. Within this group, Apis mellifera has evolved remarkable adaptations facilitating nectar processing and storage; in doing so, this species utilizes the end product, honey, for diverse functions with few if any equivalents in other phytophagous insects. Honey and its phytochemical constituents, some of which likely derive from propolis, have functional significance in protecting honey bees against microbial pathogens, toxins, and cold stress, as well as in regulating development and adult longevity. The distinctive properties of A. mellifera honey appear to have arisen in multiple ways, including genome modification; partnerships with microbial symbionts; and evolution of specialized behaviors, including foraging for substances other than nectar. That honey making by A. mellifera involves incorporation of exogenous material other than nectar, as well as endogenous products such as antimicrobial peptides and royal jelly, suggests that regarding honey as little more than a source of carbohydrates for bees is a concept in need of revision.

Intracellular Unnatural Catalysis Enabled by an Artificial Metalloenzyme

Artificial metalloenzymes, constructed by incorporating a synthetic catalyst into the internal spaces of a protein scaffold, can perform noncanonical chemical transformations that are not possible using natural enzymes. The addition of cell-permeable modules to artificial metalloenzymes allows for noncanonical catalysis to be implemented as a function of mammalian cells. In this chapter, we describe a protocol for controlling cellular function through a cascade consisting of an artificial metalloenzyme and a gene-circuit engineered via synthetic biology.

How directed evolution reshapes the energy landscape in an enzyme to boost catalysis

The advent of biocatalysts designed computationally and optimized by laboratory evolution provides an opportunity to explore molecular strategies for augmenting catalytic function. Applying a suite of nuclear magnetic resonance, crystallography, and stopped-flow techniques to an enzyme designed for an elementary proton transfer reaction, we show how directed evolution gradually altered the conformational ensemble of the protein scaffold to populate a narrow, highly active conformational ensemble and accelerate this transformation by nearly nine orders of magnitude. Mutations acquired during optimization enabled global conformational changes, including high-energy backbone rearrangements, that cooperatively organized the catalytic base and oxyanion stabilizer, thus perfecting transition-state stabilization. The development of protein catalysts for many chemical transformations could be facilitated by explicitly sampling conformational substates during design and specifically stabilizing productive substates over all unproductive conformations.

DNA Methylation of Steroidogenic Enzymes in Benign Adrenocortical Tumors: New Insights in Aldosterone-Producing Adenomas

CONTEXT

DNA methylation has been identified among putative regulatory mechanisms for CYP11B2 expression in primary aldosteronism.

OBJECTIVE

The objective of this work is to investigate DNA methylation and expression of genes encoding steroidogenic enzymes in benign adrenocortical tumors.

DESIGN AND SETTING

This cross-sectional study took place at university hospitals.

PATIENTS

We collected fresh-frozen tissues from patients with benign adrenocortical adenomas (n = 48) (nonfunctioning n = 9, autonomous cortisol secretion n = 9, Cushing syndrome n = 17, aldosterone-producing [APA] n = 13) and adrenal cortex adjacent to APA (n = 12). We collected formalin-fixed, paraffin-embedded (FFPE) specimens of paired APA and concurrent aldosterone-producing cell clusters (APCCs) (n = 6).

INTERVENTION

DNA methylation levels were evaluated by quantitative bisulfite next-generation sequencing in fresh-frozen tissues (CYP11A1, CYP11B1, CYP11B2, CYP17A1, CYP21A2, HSD3B1, HSD3B2, NR5A1, STAR, and TSPO) and FFPE APA/APCC paired samples (CYP11B2). CYP11B1, CYP11B2, CYP17, CYP21, and STAR gene expressions were examined by quantitative real-time polymerase chain reaction.

MAIN OUTCOME MEASURE

The main outcome measure was DNA methylation.

RESULTS

CYP11B2 methylation levels were significantly lower in APA than in other adrenal tissues (P < .001). Methylation levels of the remaining genes were comparable among groups. Overall, CYP11B2 expression and DNA methylation were negatively correlated (ρ = -0.379; P = .003). In FFPE-paired APA/APCC samples, CYP11B2 methylation level was significantly lower in APA than in concurrent APCCs (P = .028).

CONCLUSIONS

DNA methylation plays a regulatory role for CYP11B2 expression and may contribute to aldosterone hypersecretion in APA. Lower CYP11B2 methylation levels in APA than in APCCs may suggest an APCC-to-APA switch via progressive CYP11B2 demethylation. Conversely, DNA methylation seems not to be relevant in regulating the expression of genes encoding steroidogenic enzymes other than CYP11B2.