The Moderately Efficient Enzyme: Evolutionary and Physicochemical Trends Shaping Enzyme Parameters

Identifying the toxic mechanisms of emerging electronic contaminations liquid crystal monomers and the construction of a priority control list for graded control

Liquid crystal monomers (LCMs) are identified as emerging organic contaminations with largely unexplored health impacts. To elucidate their toxic mechanisms, support the establishment of environmental discharge and management standards, and promote effective LCMs control, this study constructs a database covering 20,545 potential targets of 1431 LCMs, highlighting 9 key toxic target proteins that disrupt the nervous system and metabolic functions. GO and KEGG pathway analysis suggests LCMs severely affect nervous system, linked to neurodegenerative diseases and mental health disorders, with toxicity variations driven by electronegativity and structural complexity of LCM terminal groups. To achieve tiered control of LCMs, construct toxicity risk control lists for 9 key toxic target proteins, suitable for the graded control of LCMs, management recommendations are provided based on toxicity levels. These lists were validated for reliability and offer reliable toxicity predictions for LCMs. SHAP analysis points to electronic properties, molecular shape, and structural characteristics of LCMs as primary health impact factors. As the first study integrating machine learning with computational toxicology to outline LCMs health impacts, it aims to enhance public understanding of LCM toxicity risks and support the development of environmental standards, effective management of LCM production and emissions, and reduction of public exposure risks.

A promiscuous mechanism to phase separate eukaryotic carbon fixation in the green lineage

CO2 fixation is commonly limited by inefficiency of the CO2-fixing enzyme Rubisco. Eukaryotic algae concentrate and fix CO2 in phase-separated condensates called pyrenoids, which complete up to one-third of global CO2 fixation. Condensation of Rubisco in pyrenoids is dependent on interaction with disordered linker proteins that show little conservation between species. We developed a sequence-independent bioinformatic pipeline to identify linker proteins in green algae. We report the linker from Chlorella and demonstrate that it binds a conserved site on the Rubisco large subunit. We show that the Chlorella linker phase separates Chlamydomonas Rubisco and that despite their separation by ~800 million years of evolution, the Chlorella linker can support the formation of a functional pyrenoid in Chlamydomonas. This cross-species reactivity extends to plants, with the Chlorella linker able to drive condensation of some native plant Rubiscos in vitro and in planta. Our results represent an exciting frontier for pyrenoid engineering in plants, which is modelled to increase crop yields.

Biocatalytic approach for the synthesis of chiral alcohols for the development of pharmaceutical intermediates and other industrial applications: A review

Biocatalysis has emerged as a strong tool for the synthesis of active pharmaceutical ingredients (APIs). In the early twentieth century, whole cell biocatalysis was used to develop the first industrial biocatalytic processes, and the precise work of enzymes was unknown. Biocatalysis has evolved over the years into an essential tool for modern, cost-effective, and sustainable pharmaceutical manufacturing. Meanwhile, advances in directed evolution enable the rapid production of process-stable enzymes with broad substrate scope and high selectivity. Large-scale synthetic pathways incorporating biocatalytic critical steps towards >130 APIs of authorized pharmaceuticals and drug prospects are compared in terms of steps, reaction conditions, and scale with the corresponding chemical procedures. This review is designed on the functional group developed during the reaction forming alcohol functional groups. Some important biocatalyst sources, techniques, and challenges are described. A few APIs and their utilization in pharmaceutical drugs are explained here in this review. Biocatalysis has provided shorter, more efficient, and more sustainable alternative pathways toward existing small molecule APIs. Furthermore, non-pharmaceutical applications of biocatalysts are also mentioned and discussed. Finally, this review includes the future outlook and challenges of biocatalysis. In conclusion, Further research and development of promising enzymes are required before they can be used in industry.

An S-methyltransferase that produces the climate-active gas dimethylsulfide is widespread across diverse marine bacteria

Hydrogen sulfide (H2S), methanethiol (MeSH) and dimethylsulfide (DMS) are abundant sulfur gases with roles in biogeochemical cycling, chemotaxis and/or climate regulation. Catabolism of the marine osmolyte dimethylsulfoniopropionate (DMSP) is a major source of DMS and MeSH, but both also result from S-methylation of H2S via MddA, an H2S and MeSH S-methyltransferase whose gene is abundant in soil but scarce in marine environments. Here we identify the S-adenosine methionine (SAM)-dependent MeSH and H2S S-methyltransferase 'MddH', which is widespread in diverse marine bacteria and some freshwater and soil bacteria. mddH is predicted in up to ~5% and ~15% of seawater and coastal sediment bacteria, respectively, which is considerably higher than mddA. Furthermore, marine mddH transcript levels are similar to those for the most abundant DMSP lyase gene dddP. This study implies that the importance of H2S and MeSH S-methylation pathways in marine environments is significantly underestimated.

Kinetic and structural characterization of NUDT15 and NUDT18 as catalysts of isoprene pyrophosphate hydrolysis

Isoprene pyrophosphates play a crucial role in the synthesis of a diverse array of essential nonsterol and sterol biomolecules and serve as substrates for posttranslational isoprenylation of proteins, enabling specific anchoring to cellular membranes. Hydrolysis of isoprene pyrophosphates would be a means to modulate their levels, downstream products, and protein isoprenylation. While NUDIX hydrolases from plants have been described to catalyze the hydrolysis of isoprene pyrophosphates, homologous enzymes with this function in animals have not yet been reported. In this study, we screened an extensive panel of human NUDIX hydrolases for activity in hydrolyzing isoprene pyrophosphates. We found that human nucleotide triphosphate diphosphatase NUDT15 and 8-oxo-dGDP phosphatase NUDT18 efficiently catalyze the hydrolysis of several physiologically relevant isoprene pyrophosphates. Notably, we demonstrate that geranyl pyrophosphate is an excellent substrate for NUDT18, with a catalytic efficiency of 2.1 × 105 m-1·s-1, thus making it the best substrate identified for NUDT18 to date. Similarly, geranyl pyrophosphate proved to be the best isoprene pyrophosphate substrate for NUDT15, with a catalytic efficiency of 4.0 × 104 M-1·s-1. LC-MS analysis of NUDT15 and NUDT18 catalyzed isoprene pyrophosphate hydrolysis revealed the generation of the corresponding monophosphates and inorganic phosphate. Furthermore, we solved the crystal structure of NUDT15 in complex with the hydrolysis product geranyl phosphate at a resolution of 1.70 Å. This structure revealed that the active site nicely accommodates the hydrophobic isoprenoid moiety and helped identify key binding residues. Our findings imply that isoprene pyrophosphates are endogenous substrates of NUDT15 and NUDT18, suggesting they are involved in animal isoprene pyrophosphate metabolism.

Quantum chemical studies of the reaction mechanisms of enzymatic CO2 conversion

Enzymatic capture and conversion of carbon dioxide (CO2) into value-added chemicals are of great interest in the field of biocatalysis and have a positive impact on climate change. The quantum chemical methods, recognized as valuable tools for studying reaction mechanisms, have been widely employed in investigating the reaction mechanisms of the enzymes involved in CO2 utilization. In this perspective, we review the mechanistic studies of representative enzymes that are either currently used or have the potential for converting CO2, utilizing the quantum chemical cluster approach and the quantum mechanical/molecular mechanical (QM/MM) method. We begin by summarizing current trends in enzymatic CO2 conversion, followed by a brief description of the computational details of quantum chemical methods. Then, a series of representative examples of the computational modeling of biocatalytic CO2 conversion are presented, including the reduction of CO2 to C1 species (carbon monoxide and formate), and the fixation of CO2 to form aliphatic and aromatic carboxylic acids. The microscopic views of reaction mechanisms obtained from these studies are helpful in guiding the rational design of current enzymes and the discovery of novel enzymes with enhanced performance in converting CO2. Additionally, they provide key information for the de novo design of new-to-nature enzymes. To conclude, we present a perspective on the potential combination of machine learning with quantum description in the study of enzymatic conversion of CO2.

Enhanced Golden Gate Assembly: evaluating overhang strength for improved ligation efficiency

Molecular cloning, a routine yet essential technique, relies heavily on efficient ligation, which can be significantly improved using Golden Gate Assembly (GGA). A key component of GGA is the use of type IIS enzymes, which uniquely cleave downstream of their recognition sequences to generate various overhangs, including non-palindromic ones. Recent advancements in GGA include the development of newly engineered enzymes with enhanced activity. Additionally, high-throughput GGA assays, which allow for the simultaneous study of all possible overhangs, have identified optimal GGA substrates with high efficiencies and fidelities, greatly facilitating the design of complex assemblies. Interestingly, these assays reveal unexpected correlations between ligation efficiencies and overhang stabilities. One hypothesis for this observation is that newly hydrolyzed DNA fragments with strong overhangs can readily re-ligate, thereby slowing down the overall process. In this paper, we employ a combination of gel electrophoresis and numerical calculations to test this hypothesis, ultimately determining that it does not hold true under the conditions established by conventional GGA assays. Using an assembly of 10 fragments, we demonstrate that strong overhangs yield higher GGA efficiency, while weak overhangs result in lower efficiency. These findings enable us to propose optimal overhangs for efficient GGA assays, significantly increasing yield.

Nature-Inspired Strategies for Sustainable Degradation of Synthetic Plastics

Synthetic plastics have become integral to our daily lives, yet their escalating production, limited biodegradability, and inadequate waste management contribute to environmental contamination. Biological plastic degradation is one promising strategy to address this pollution. The inherent chemical and physical properties of synthetic plastics, however, pose challenges for microbial enzymes, hindering the effective degradation and the development of a sustainable biological recycling process. This Perspective explores alternative, nature-inspired strategies designed to overcome some key limitations in currently available plastic-degrading enzymes. Nature's refined degradation pathways for natural polymers, such as cellulose, present a compelling framework for the development of efficient technologies for enzymatic plastic degradation. By drawing insights from nature, we propose a general strategy of employing substrate binding domains to improve targeting and multienzyme scaffolds to overcome enzymatic efficiency limitations. As one potential application, we outline a multienzyme pathway to upcycle polyethylene into alkenes. Employing nature-inspired strategies can present a path toward sustainable solution to the environmental impact of synthetic plastics.

Glutathione‑iron hybrid nanozyme-based colorimetric sensor for specific and stable detection of thiram pesticide on fruit juices

Given the potential dangers of thiram to food safety, constructing a facile sensor is significantly critical. Herein, we presented a colorimetric sensor based on glutathione‑iron hybrid (GSH-Fe) nanozyme for specific and stable detection of thiram. The GSH-Fe nanozyme exhibits good peroxidase-mimicking activity with comparable Michaelis constant (Km = 0.551 mM) to the natural enzyme. Thiram pesticides can specifically limit the catalytic activity of GSH-Fe nanozyme via surface passivation, causing the change of colorimetric signal. It is worth mentioning that the platform was used to prepare a portable hydrogel kit for rapid qualitative monitoring of thiram. Coupling with an image-processing algorithm, the colorimetric image of the hydrogel reactor is converted into the data information for accurate quantification of thiram with a detection limit of 0.3 μg mL-1. The sensing system has good selectivity and high stability, with recovery rates in fruit juice samples ranging from 92.4% to 106.9%.

A model of time-dependent macromolecular and elemental composition of phytoplankton

Phytoplankton Chl:C:N:P ratios are important from both an ecological and a biogeochemical perspective. We show that these elemental ratios can be represented by a phytoplankton physiological model of low complexity that includes major cellular macromolecular pools. In particular, our model resolves time-dependent intracellular pools of chlorophyll, proteins, nucleic acids, carbohydrates/lipids, and N and P storage. Batch culture data for two diatom and two prasinophyte species are used to constrain parameters that represent specific allocation traits and strategies. A key novelty is the simultaneous estimation of physiological parameters for two phytoplankton groups of such different sizes. The number of free parameters is reduced by assuming (i) allometric scaling for maximum uptake rates, (ii) shared half-saturation constants for synthesis of functional macromolecules, (iii) shared exudation rates of functional macromolecules across the species. The rationale behind this assumption is that across the different species, the same or similar processes, enzymes, and metabolites play a role in key physiological processes. For the turnover numbers of macromolecular synthesis and storage exudation rates, differences between diatoms and prasinophytes need to be taken into account to obtain a good fit. Our model fits suggest that the parameters related to storage dynamics dominate the differences in the C:N:P ratios between the different phytoplankton groups. Since descriptions of storage dynamics are still incomplete and imprecise, predictions of C:N:P ratios by phytoplankton models likely have a large uncertainty.

How does plant chemodiversity evolve? Testing five hypotheses in one population genetic model

Plant chemodiversity, the diversity of plant-specialized metabolites, is an important dimension of biodiversity. However, there are so far few mathematical models to test verbal hypotheses on how chemodiversity evolved. Here, we develop such a model to test predictions of five hypotheses: the 'fluctuating selection hypothesis', the 'dominance reversal hypothesis', the interaction diversity hypothesis, the synergy hypothesis, and the screening hypothesis. We build a population genetic model of a plant population attacked by herbivore species whose occurrence fluctuates over time. We study the model using mathematical analysis and individual-based simulations. As predicted by the 'dominance reversal hypothesis', chemodiversity can be maintained if alleles conferring a defense metabolite are dominant with respect to the benefits, but recessive with respect to costs. However, even smaller changes in dominance can maintain polymorphism. Moreover, our results underpin and elaborate predictions of the synergy and interaction diversity hypotheses, and, to the extent that our model can address it, the screening hypotheses. By contrast, we found only partial support for the 'fluctuating selection hypothesis'. In summary, we have developed a flexible model and tested various verbal models for the evolution of chemodiversity. Next, more mechanistic models are needed that explicitly consider the organization of metabolic pathways.

Efficient derivatization-free monitoring of glycosyltransferase reactions via flow injection analysis-mass spectrometry for rapid sugar analytics

The widespread application of enzymes in industrial chemical synthesis requires efficient process control to maintain high yields and purity. Flow injection analysis-electrospray ionization-mass spectrometry (FIA-ESI-MS) offers a promising solution for real-time monitoring of these enzymatic processes, particularly when handling challenging compounds like sugars and glycans, which are difficult to quickly analyze using liquid chromatography-mass spectrometry due to their physical properties or the requirement for a derivatization step beforehand. This study compares the performance of FIA-MS with traditional hydrophilic interaction liquid chromatography (HILIC)-ultra high-performance liquid chromatography (UHPLC)-mass spectrometry (MS) setups for the monitoring of the enzymatic synthesis of N-acetyllactosamine (LacNAc) using beta-1,4-galactosyltransferase. Our results show that FIA-MS, without prior chromatographic separation or derivatization, can quickly generate accurate mass spectrometric data within minutes, contrasting with the lengthy separations required by LC-MS methods. The rapid data acquisition of FIA-MS enables effective real-time monitoring and adjustment of the enzymatic reactions. Furthermore, by eliminating the derivatization step, this method offers the possibility of being directly coupled to a continuously operated reactor, thus providing a rapid on-line methodology for glycan synthesis as well.

Molecular basis of one-step methyl anthranilate biosynthesis in grapes, sweet orange, and maize

Plants synthesize an array of volatile compounds, many of which serve ecological roles in attracting pollinators, deterring herbivores, and communicating with their surroundings. Methyl anthranilate (MeAA) is an anti-herbivory defensive volatile responsible for grape aroma that is emitted by several agriculturally relevant plants, including citrus, grapes, and maize. Unlike maize, which uses a one-step anthranilate methyltransferase (AAMT), grapes have been thought to use a two-step pathway for MeAA biosynthesis. By mining available transcriptomics data, we identified two AAMTs in Vitis vinifera (wine grape), as well as one ortholog in "Concord" grape. Many angiosperms methylate the plant hormone salicylic acid (SA) to produce methyl salicylate, which acts as a plant-to-plant communication molecule. Because the Citrus sinensis (sweet orange) SA methyltransferase can methylate both anthranilate (AA) and SA, we used this enzyme to examine the molecular basis of AA activity by introducing rational mutations, which identified several active site residues that increase activity with AA. Reversing this approach, we introduced mutations that imparted activity with SA in the maize AAMT, which uncovered different active site residues from those in the citrus enzyme. Sequence and phylogenetic analysis revealed that one of the Vitis AAMTs shares an ancestor with jasmonic acid methyltransferases, similar to the AAMT from strawberry (Frageria sp.). Collectively, these data demonstrate the molecular mechanisms underpinning AA activity across methyltransferases and identify one-step enzymes by which grapes synthesize MeAA.

Best Practices for Development and Validation of Enzymatic Activity Assays to Support Drug Development for Inborn Errors of Metabolism and Biomarker Assessment

Aberrant or dysfunctional cellular enzymes are responsible for a wide range of diseases including cancer, neurodegenerative conditions, and metabolic disorders. Deficiencies in enzyme level or biofunction may lead to intracellular accumulation of substrate to toxic levels and interfere with overall cellular function, ultimately leading to cell damage, disease, and death. Marketed therapeutic interventions for inherited monogenic enzyme deficiency disorders include enzyme replacement therapy and small molecule chaperones. Novel approaches of in vivo gene therapy and ex vivo cell therapy are under clinical evaluation and provide promising opportunities to expand the number of available disease-modifying treatments. To support the development of these different therapeutics, assays to quantify the functional activity of protein enzymes have gained importance in the diagnosis of disease, assessment of pharmacokinetics and pharmacodynamic response, and evaluation of drug efficacy. In this review, we discuss the technical aspects of enzyme activity assays in the bioanalytical context, including assay design and format as well as the unique challenges and considerations associated with assay development, validation, and life cycle management.

Structural basis of divergent substrate recognition and inhibition of human neurolysin

A zinc metallopeptidase neurolysin (Nln) processes diverse bioactive peptides to regulate signaling in the mammalian nervous system. To understand how Nln interacts with various peptides with dissimilar sequences, we determined crystal structures of Nln in complex with diverse peptides including dynorphins, angiotensin, neurotensin, and bradykinin. The structures show that Nln binds these peptides in a large dumbbell-shaped interior cavity constricted at the active site, making minimal structural changes to accommodate different peptide sequences. The structures also show that Nln readily binds similar peptides with distinct registers, which can determine whether the peptide serves as a substrate or a competitive inhibitor. We analyzed the activities and binding of Nln toward various forms of dynorphin A peptides, which highlights the promiscuous nature of peptide binding and shows how dynorphin A (1-13) potently inhibits the Nln activity while dynorphin A (1-8) is efficiently cleaved. Our work provides insights into the broad substrate specificity of Nln and may aid in the future design of small molecule modulators for Nln.

A synthetic cell-free pathway for biocatalytic upgrading of one-carbon substrates

Biotechnological processes hold tremendous potential for the efficient and sustainable conversion of one-carbon (C1) substrates into complex multi-carbon products. However, the development of robust and versatile biocatalytic systems for this purpose remains a significant challenge. In this study, we report a hybrid electrochemical-biochemical cell-free system for the conversion of C1 substrates into the universal biological building block acetyl-CoA. The synthetic reductive formate pathway (ReForm) consists of five core enzymes catalyzing non-natural reactions that were established through a cell-free enzyme engineering platform. We demonstrate that ReForm works in a plug-and-play manner to accept diverse C1 substrates including CO2 equivalents. We anticipate that ReForm will facilitate efforts to build and improve synthetic C1 utilization pathways for a formate-based bioeconomy.

Active-Site Oxygen Accessibility and Catalytic Loop Dynamics of Plant Aromatic Amino Acid Decarboxylases from Molecular Simulations

Aromatic amino acid decarboxylases (AAADs) are pyridoxal-5'-phosphate (PLP)-dependent enzymes that catalyze the decarboxylation of aromatic amino acid l-amino acids. In plants, apart from canonical AAADs that catalyze the straightforward decarboxylation reaction, other members of the AAAD family function as aromatic acetaldehyde synthases (AASs) and catalyze more complex decarboxylation-dependent oxidative deamination. The interconversion between a canonical AAAD and an AAS can be achieved by a single tyrosine-phenylalanine mutation in the large catalytic loop of the enzymes. In this work, we report implicit ligand sampling (ILS) calculations of the canonical l-tyrosine decarboxylase from Papaver somniferum (PsTyDC) that catalyzes l-tyrosine decarboxylation and its Y350F mutant that instead catalyzes the decarboxylation-dependent oxidative deamination of the same substrate. Through comparative analysis of the resulting three-dimensional (3D) O2 free energy profiles, we evaluate the impact of the key tyrosine/phenylalanine mutation on oxygen accessibility to both the wild type and Y350F mutant of PsTyDC. Additionally, using molecular dynamics (MD) simulations of the l-tryptophan decarboxylase from Catharanthus roseus (CrTDC), we further investigate the dynamics of a large catalytic loop known to be indispensable to all AAADs. Results of our ILS and MD calculations shed new light on how key structural elements and loop conformational dynamics underlie the enzymatic functions of different members of the plant AAAD family.

Development of a Zn-Based Single-Atom Nanozyme for Efficient Hydrolysis of Glycosidic Bonds

Hydrolytic enzymes are essential components in second-generation biofuel technology and food fermentation processes. Nanozymes show promise for large-scale industrial applications as replacements for natural enzymes due to their distinct advantages. However, there remains a research gap concerning glycosidase nanozymes. In this study, a Zn-based single-atom nanozyme (ZnN4-900) is developed for efficient glycosidic bond hydrolysis in an aqueous solution. The planar structure of the class-porphyrin N4 material approximatively mimicked the catalytic centers of natural enzymes, facilitating oxidase-like (OXD-like) activity and promoting glycosidic bond cleavage. Theoretical calculations show that the Zn site can act as Lewis acids, attacking the C─O bond in glycosidic bonds. Additionally, ZnN4-900 has the ability to degrade starch and produce reducing sugars that increased yeast cell biomass by 32.86% and ethanol production by 14.56%. This catalyst held promising potential for enhancing processes in ethanol brewing and starch degradation industries.

Interspecific variation in Rubisco CO2/O2 specificity along the leaf economic spectrum across 23 woody angiosperm plants in the Pacific islands

The coordinated interspecific variation in leaf traits and leaf lifespan is known as the leaf economic spectrum (LES). The limitation of CO2 diffusion to chloroplasts within the lamina is significant in C3 photosynthesis, resulting in a shortage of CO2 for Rubisco. Although Rubisco CO2/O2 specificity (SC/O) should be adaptively adjusted in response to the interspecific variation in CO2 concentrations [CO2] associated with Rubisco, SC/O variations across species along the LES remain unknown. We investigated the coordination among leaf traits, including SC/O, CO2 conductance, leaf protein content, and leaf mass area, across 23 woody C3 species coexisting on an oceanic island through phylogenetic correlation analyses. A high SC/O indicates a high CO2 specificity of Rubisco. SC/O was negatively correlated with [CO2] at Rubisco and total CO2 conductance within lamina, while it was positively correlated with leaf protein across species, regardless of phylogenetic constraint. A simulation analysis shows that the optimal SC/O for maximizing photosynthesis depends on both [CO2] at Rubisco sites and leaf protein per unit leaf area. SC/O is a key parameter along the LES axis and is crucial for maximizing photosynthesis across species and the adaptation of woody plants.

MPEK: a multitask deep learning framework based on pretrained language models for enzymatic reaction kinetic parameters prediction

Enzymatic reaction kinetics are central in analyzing enzymatic reaction mechanisms and target-enzyme optimization, and thus in biomanufacturing and other industries. The enzyme turnover number (kcat) and Michaelis constant (Km), key kinetic parameters for measuring enzyme catalytic efficiency, are crucial for analyzing enzymatic reaction mechanisms and the directed evolution of target enzymes. Experimental determination of kcat and Km is costly in terms of time, labor, and cost. To consider the intrinsic connection between kcat and Km and further improve the prediction performance, we propose a universal pretrained multitask deep learning model, MPEK, to predict these parameters simultaneously while considering pH, temperature, and organismal information. Through testing on the same kcat and Km test datasets, MPEK demonstrated superior prediction performance over the previous models. Specifically, MPEK achieved the Pearson coefficient of 0.808 for predicting kcat, improving ca. 14.6% and 7.6% compared to the DLKcat and UniKP models, and it achieved the Pearson coefficient of 0.777 for predicting Km, improving ca. 34.9% and 53.3% compared to the Kroll_model and UniKP models. More importantly, MPEK was able to reveal enzyme promiscuity and was sensitive to slight changes in the mutant enzyme sequence. In addition, in three case studies, it was shown that MPEK has the potential for assisted enzyme mining and directed evolution. To facilitate in silico evaluation of enzyme catalytic efficiency, we have established a web server implementing this model, which can be accessed at http://mathtc.nscc-tj.cn/mpek.

Elucidating the Role of O2 Uncoupling for the Adaptation of Bacterial Biodegradation Reactions Catalyzed by Rieske Oxygenases

Oxygenation of aromatic and aliphatic hydrocarbons by Rieske oxygenases is the initial step of various biodegradation pathways for environmental organic contaminants. Microorganisms carrying Rieske oxygenases are able to quickly adapt their substrate spectra to alternative carbon and energy sources that are structurally related to the original target substrate, yet the molecular events responsible for this rapid adaptation are not well understood. Here, we evaluated the hypothesis that reactive oxygen species (ROS) generated by unproductive activation of O2, the so-called O2 uncoupling, in the presence of the alternative substrate exert a selective pressure on the bacterium for increasing the oxygenation efficiency of Rieske oxygenases. To that end, we studied wild-type 2-nitrotoluene dioxygenase from Acidovorax sp. strain JS42 and five enzyme variants that have evolved from adaptive laboratory evolution experiments with 3- and 4-nitrotoluene as alternative growth substrates. The enzyme variants showed a substantially increased oxygenation efficiency toward the new target substrates concomitant with a reduction of ROS production, while mechanisms and kinetics of enzymatic O2 activation remained unchanged. Structural analyses and docking studies suggest that amino acid substitutions in enzyme variants occurred at residues lining both substrate and O2 transport tunnels, enabling tighter binding of the target substrates in the active site. Increased oxygenation efficiencies measured in vitro for the various enzyme (variant)-substrate combinations correlated linearly with in vivo changes in growth rates for evolved Acidovorax strains expressing the variants. Our data suggest that the selective pressure from oxidative stress toward more efficient oxygenation by Rieske oxygenases was most notable when O2 uncoupling exceeded 60%.

Droplet Differentiation by a Chemical Switch

A fundamental question about biomolecular condensates is how distinct condensates can emerge from the interplay of different components. Here we present a minimal model of droplet differentiation where phase separated droplets demix into two types with different chemical modifications triggered by enzymatic reactions. We use numerical solutions to Cahn-Hilliard equations with chemical reactions and an effective droplet model to reveal the switchlike behavior. Our work shows how condensate identities in cells could result from competing enzymatic actions.

Selection of a promiscuous minimalist cAMP phosphodiesterase from a library of de novo designed proteins

The ability of unevolved amino acid sequences to become biological catalysts was key to the emergence of life on Earth. However, billions of years of evolution separate complex modern enzymes from their simpler early ancestors. To probe how unevolved sequences can develop new functions, we use ultrahigh-throughput droplet microfluidics to screen for phosphoesterase activity amidst a library of more than one million sequences based on a de novo designed 4-helix bundle. Characterization of hits revealed that acquisition of function involved a large jump in sequence space enriching for truncations that removed >40% of the protein chain. Biophysical characterization of a catalytically active truncated protein revealed that it dimerizes into an α-helical structure, with the gain of function accompanied by increased structural dynamics. The identified phosphodiesterase is a manganese-dependent metalloenzyme that hydrolyses a range of phosphodiesters. It is most active towards cyclic AMP, with a rate acceleration of ~109 and a catalytic proficiency of >1014 M-1, comparable to larger enzymes shaped by billions of years of evolution.

Citrate synthase variants improve yield of acetyl-CoA derived 3-hydroxybutyrate in Escherichia coli

BACKGROUND

The microbial chiral product (R)-3-hydroxybutyrate (3-HB) is a gateway to several industrial and medical compounds. Acetyl-CoA is the key precursor for 3-HB, and several native pathways compete with 3-HB production. The principal competing pathway in wild-type Escherichia coli for acetyl-CoA is mediated by citrate synthase (coded by gltA), which directs over 60% of the acetyl-CoA into the tricarboxylic acid cycle. Eliminating citrate synthase activity (deletion of gltA) prevents growth on glucose as the sole carbon source. In this study, an alternative approach is used to generate an increased yield of 3-HB: citrate synthase activity is reduced but not eliminated by targeted substitutions in the chromosomally expressed enzyme.

RESULTS

Five E. coli GltA variants were examined for 3-HB production via heterologous overexpression of a thiolase (phaA) and NADPH-dependent acetoacetyl-CoA reductase (phaB) from Cupriavidus necator. In shake flask studies, four variants showed nearly 5-fold greater 3-HB yield compared to the wild-type, although pyruvate accumulated. Overexpression of either native thioesterases TesB or YciA eliminated pyruvate formation, but diverted acetyl-CoA towards acetate formation. Overexpression of pantothenate kinase similarly decreased pyruvate formation but did not improve 3-HB yield. Controlled batch studies at the 1.25 L scale demonstrated that the GltA[A267T] variant produced the greatest 3-HB titer of 4.9 g/L with a yield of 0.17 g/g. In a phosphate-starved repeated batch process, E. coli ldhA poxB pta-ackA gltA::gltA[A267T] generated 15.9 g/L 3-HB (effective concentration of 21.3 g/L with dilution) with yield of 0.16 g/g from glucose as the sole carbon source.

CONCLUSIONS

This study demonstrates that GltA variants offer a means to affect the generation of acetyl-CoA derived products. This approach should benefit a wide range of acetyl-CoA derived biochemical products in E. coli and other microbes. Enhancing substrate affinity of the introduced pathway genes like thiolase towards acetyl-CoA will likely further increase the flux towards 3-HB while reducing pyruvate and acetate accumulation.

Bottom-up parameterization of enzyme rate constants: Reconciling inconsistent data

Kinetic models of metabolism are promising platforms for studying complex metabolic systems and designing production strains. Given the availability of enzyme kinetic data from historical experiments and machine learning estimation tools, a straightforward modeling approach is to assemble kinetic data enzyme by enzyme until a desired scale is reached. However, this type of 'bottom up' parameterization of kinetic models has been difficult due to a number of issues including gaps in kinetic parameters, the complexity of enzyme mechanisms, inconsistencies between parameters obtained from different sources, and in vitro-in vivo differences. Here, we present a computational workflow for the robust estimation of kinetic parameters for detailed mass action enzyme models while taking into account parameter uncertainty. The resulting software package, termed MASSef (the Mass Action Stoichiometry Simulation Enzyme Fitting package), can handle standard 'macroscopic' kinetic parameters, including Km, kcat, Ki, Keq, and nh, as well as diverse reaction mechanisms defined in terms of mass action reactions and 'microscopic' rate constants. We provide three enzyme case studies demonstrating that this approach can identify and reconcile inconsistent data either within in vitro experiments or between in vitro and in vivo enzyme function. We further demonstrate how parameterized enzyme modules can be used to assemble pathway-scale kinetic models consistent with in vivo behavior. This work builds on the legacy of knowledge on kinetic behavior of enzymes by enabling robust parameterization of enzyme kinetic models at scale utilizing the abundance of historical literature data and machine learning parameter estimates.

Arogenate dehydratase isoforms strategically deregulate phenylalanine biosynthesis in Akebia trifoliata

Arogenate dehydratase (ADT) is key for phenylalanine (Phe) biosynthesis in plants. To examine ADT components and function in Akebia trifoliata, a representative of Ranunculaceae, we first identified eight ADTs (AktADT1-8, encoding sequences varying from 1032 to 1962 bp) in the A. trifoliata reference genome and five proteins (AktADT1, AktADT4, AktADT7, AktADT8 and AktADT8s) with moonlighting prephenate dehydratase (PDT) activity and Km values varying from 0.43 to 2.17 mM. Structurally, two basic residue combinations (Val314/Ala317 and Ala314/Val317) in the PAC domain are essential for the moonlighting PDT activity of ADTs. Functionally, AktADT4 and AktADT8 successfully restored the wild-type phenotype of pha2, a knockout mutant of Saccharomyces cerevisiae. In addition, AktADTs are ubiquitously expressed, but their expression levels are tissue specific, and the half maximal inhibitory concentration (IC50) of Phe for AktADTs ranged from 49.81 to 331.17 μM. Both AktADT4 and AktADT8 and AktADT8s localized to chloroplast stromules and the cytosol, respectively, while the remaining AktADTs localized to the chloroplast stroma. These findings suggest that various strategies exist for regulating Phe biosynthesis in A. trifoliata. This provides a reasonable explanation for the high Phe content and insights for further genetic improvement of the edible fruits of A. trifoliata.

Beyond homogeneity: Assessing the validity of the Michaelis-Menten rate law in spatially heterogeneous environments

The Michaelis-Menten (MM) rate law has been a fundamental tool in describing enzyme-catalyzed reactions for over a century. When substrates and enzymes are homogeneously distributed, the validity of the MM rate law can be easily assessed based on relative concentrations: the substrate is in large excess over the enzyme-substrate complex. However, the applicability of this conventional criterion remains unclear when species exhibit spatial heterogeneity, a prevailing scenario in biological systems. Here, we explore the MM rate law's applicability under spatial heterogeneity by using partial differential equations. In this study, molecules diffuse very slowly, allowing them to locally reach quasi-steady states. We find that the conventional criterion for the validity of the MM rate law cannot be readily extended to heterogeneous environments solely through spatial averages of molecular concentrations. That is, even when the conventional criterion for the spatial averages is satisfied, the MM rate law fails to capture the enzyme catalytic rate under spatial heterogeneity. In contrast, a slightly modified form of the MM rate law, based on the total quasi-steady state approximation (tQSSA), is accurate. Specifically, the tQSSA-based modified form, but not the original MM rate law, accurately predicts the drug clearance via cytochrome P450 enzymes and the ultrasensitive phosphorylation in heterogeneous environments. Our findings shed light on how to simplify spatiotemporal models for enzyme-catalyzed reactions in the right context, ensuring accurate conclusions and avoiding misinterpretations in in silico simulations.

Combining enzyme and metabolic engineering for microbial supply of therapeutic phytochemicals

The history of pharmacology is deeply intertwined with plant-derived compounds, which continue to be crucial in drug development. However, their complex structures and limited availability in plants challenge drug discovery, optimization, development, and industrial production via chemical synthesis or natural extraction. This review delves into the integration of metabolic and enzyme engineering to leverage micro-organisms as platforms for the sustainable and reliable production of therapeutic phytochemicals. We argue that engineered microbes can serve a triple role in this paradigm: facilitating pathway discovery, acting as cell factories for scalable manufacturing, and functioning as platforms for chemical derivatization. Analyzing recent progress and outlining future directions, the review highlights microbial biotechnology's transformative potential in expanding plant-derived human therapeutics' discovery and supply chains.

Study of two glycosyltransferases related to polysaccharide biosynthesis in Rhodococcus jostii RHA1

The bacterial genus Rhodococcus comprises organisms performing oleaginous behaviors under certain growth conditions and ratios of carbon and nitrogen availability. Rhodococci are outstanding producers of biofuel precursors, where lipid and glycogen metabolisms are closely related. Thus, a better understanding of rhodococcal carbon partitioning requires identifying catalytic steps redirecting sugar moieties to storage molecules. Here, we analyzed two GT4 glycosyl-transferases from Rhodococcus jostii (RjoGlgAb and RjoGlgAc) annotated as α-glucan-α-1,4-glucosyl transferases, putatively involved in glycogen synthesis. Both enzymes were produced in Escherichia coli cells, purified to homogeneity, and kinetically characterized. RjoGlgAb and RjoGlgAc presented the "canonical" glycogen synthase activity and were actives as maltose-1P synthases, although to a different extent. Then, RjoGlgAc is a homologous enzyme to the mycobacterial GlgM, with similar kinetic behavior and glucosyl-donor preference. RjoGlgAc was two orders of magnitude more efficient to glucosylate glucose-1P than glycogen, also using glucosamine-1P as a catalytically efficient aglycon. Instead, RjoGlgAb exhibited both activities with similar kinetic efficiency and preference for short-branched α-1,4-glucans. Curiously, RjoGlgAb presented a super-oligomeric conformation (higher than 15 subunits), representing a novel enzyme with a unique structure-to-function relationship. Kinetic results presented herein constitute a hint to infer on polysaccharides biosynthesis in rhodococci from an enzymological point of view.

Ascorbate degradation: pathways, products, and possibilities

A role for l-ascorbate as the precursor of several plant compounds adds to its already broad metabolic utility. There are many examples of plant species in which oxalate and l-threonate are formed from l-ascorbate breakdown, and a number of roles have been proposed for this: structural, physiological, and biochemical. On the other hand, the synthesis of l-tartrate from l-ascorbate remains limited to a very few species, amongst which we must be grateful to count the domesticated grapevine Vitis vinifera and its relatives on which wine production is based. Pathways for the degradation of ascorbate were first proposed ~50 years ago and have formed the basis of more recent biochemical and molecular analyses. The present review seeks to summarize some of these findings and to propose opportunities for future research.

Resource allocation modeling for autonomous prediction of plant cell phenotypes

Predicting the plant cell response in complex environmental conditions is a challenge in plant biology. Here we developed a resource allocation model of cellular and molecular scale for the leaf photosynthetic cell of Arabidopsis thaliana, based on the Resource Balance Analysis (RBA) constraint-based modeling framework. The RBA model contains the metabolic network and the major macromolecular processes involved in the plant cell growth and survival and localized in cellular compartments. We simulated the model for varying environmental conditions of temperature, irradiance, partial pressure of CO2 and O2, and compared RBA predictions to known resource distributions and quantitative phenotypic traits such as the relative growth rate, the C:N ratio, and finally to the empirical characteristics of CO2 fixation given by the well-established Farquhar model. In comparison to other standard constraint-based modeling methods like Flux Balance Analysis, the RBA model makes accurate quantitative predictions without the need for empirical constraints. Altogether, we show that RBA significantly improves the autonomous prediction of plant cell phenotypes in complex environmental conditions, and provides mechanistic links between the genotype and the phenotype of the plant cell.

Proteome allocation and the evolution of metabolic cross-feeding

In a common instance of metabolic cross-feeding (MCF), an organism incompletely metabolizes nutrients and releases metabolites that are used by another to produce energy or building blocks. Why would the former waste edible food, and why does this preferentially occur at specific locations in a metabolic pathway have challenged evolutionary theory for decades. To address these questions, we combine adaptive dynamics with an explicit model of cell metabolism, including enzyme-driven catalysis of metabolic reactions and the cellular constraints acting on the proteome that may incur a cost to expressing all enzymes along a pathway. After pointing out that cells should in principle prioritize upstream reactions when metabolites are restrained inside the cell, we show that the occurrence of permeability-driven MCF is rare and requires that an intermediate metabolite be extremely diffusive. Indeed, only at very high levels of membrane permeability (consistent with those of acetate and glycerol, for instance) and under distinctive sets of parameters should the population diversify and MCF evolve. These results help understand the origins of simple microbial communities, such as those that readily evolve in short-term evolutionary experiments, and may later be extended to investigate how evolution has progressively built up today's extremely diverse ecosystems.

Fluorescence-Based Screens for Engineering Enzymes Linked to Halogenated Tryptophan

Directed evolution is often limited by the throughput of accurate screening methods. Here we demonstrate the feasibility of utilizing a singular transcription factor (TF)-system that can be refactored in two ways (both as an activator and repressor). Specifically, we showcase the use of previously evolved 5-halo- or 6-halo-tryptophan-specific TF biosensors suitable for the detection of a halogenated tryptophan molecule in vivo. We subsequently validate the biosensor's utility for two halogenase-specific halo-tryptophan accumulation screens. First, we isolated 5-tryptophan-halogenase, XsHal, from a mixed pool of halogenases with 100% efficiency. Thereafter, we generated a targeted library of the catalytic residue of 6-tryptophan halogenase, Th-Hal, and isolated functioning halogenases with 100% efficiency. Lastly, we refactor the TF circuit to respond to the depletion of halogenated tryptophan and prototype a high-throughput biosensor-directed evolution scheme to screen for downstream enzyme variants capable of promiscuously converting halogenated tryptophan. Altogether, this work takes a significant step toward the rapid and higher throughput screening of halogenases and halo-tryptophan converting enzymes to further reinforce efforts to enable high-level bioproduction of halogenated chemicals.

The genetic landscape of a metabolic interaction

While much prior work has explored the constraints on protein sequence and evolution induced by physical protein-protein interactions, the sequence-level constraints emerging from non-binding functional interactions in metabolism remain unclear. To quantify how variation in the activity of one enzyme constrains the biochemical parameters and sequence of another, we focus on dihydrofolate reductase (DHFR) and thymidylate synthase (TYMS), a pair of enzymes catalyzing consecutive reactions in folate metabolism. We use deep mutational scanning to quantify the growth rate effect of 2696 DHFR single mutations in 3 TYMS backgrounds under conditions selected to emphasize biochemical epistasis. Our data are well-described by a relatively simple enzyme velocity to growth rate model that quantifies how metabolic context tunes enzyme mutational tolerance. Together our results reveal the structural distribution of epistasis in a metabolic enzyme and establish a foundation for the design of multi-enzyme systems.

ACE-2-like enzymatic activity is associated with immunoglobulin in COVID-19 patients

Many mechanisms responsible for COVID-19 pathogenesis are well-established, but COVID-19 includes features with unclear pathogenesis, such as autonomic dysregulation, coagulopathies, and high levels of inflammation. The receptor for the SARS-CoV-2 spike protein receptor-binding domain (RBD) is angiotensin-converting enzyme 2 (ACE2). We hypothesized that some COVID-19 patients may develop antibodies that have a negative molecular image of RBD sufficiently similar to ACE2 to yield ACE2-like catalytic activity-ACE2-like abzymes. To explore this hypothesis, we studied patients hospitalized with COVID-19 who had plasma samples available obtained about 7 days after admission. ACE2 is a metalloprotease that requires Zn2+ for activity. However, we found that the plasma from some patients studied could specifically cleave a synthetic ACE2 peptide substrate, even though the plasma samples were collected using disodium EDTA anticoagulant. When we spiked plasma with synthetic ACE2, no ACE2 substrate cleavage activity was observed unless Zn2+ was added or the plasma was diluted to decrease EDTA concentration. After processing samples by 100 kDa size exclusion columns and protein A/G adsorption, which depleted immunoglobulin by >99.99%, the plasma samples did not cleave the ACE2 substrate peptide. The data suggest that some patients with COVID-19 develop antibodies with abzyme-like activity capable of cleaving synthetic ACE2 substrate. Since abzymes can exhibit promiscuous substrate specificities compared to the enzyme whose active site image they resemble, and since proteolytic cascades regulate many physiologic processes, anti-RBD abzymes may contribute to some otherwise obscure COVID-19 pathogenesis.

IMPORTANCE

We provide what we believe to be the first description of angiotensin-converting enzyme 2 (ACE2)-like enzymatic activity associated with immunoglobulin in COVID-19 patients. COVID-19 includes many puzzling clinical features that have unclear pathogenesis, including a hyperinflammatory state, abnormalities of the clotting cascade, and blood pressure instability. We hypothesized that some patients with COVID-19 patients may produce antibodies against SARS-CoV-2 with enzymatic activity, or abzymes, that target important proteolytic regulatory cascades. The receptor-binding domain (RBD) of the SARS-CoV-2 spike protein binds ACE2 on the surface of the future host cell. This means that the RBD has a negative molecular image of ACE2. We hypothesized that some antibodies produced against the RBD would have, in turn, a negative molecular image of the RBD sufficiently similar to ACE2 to have ACE2-like catalytic activity. In other words, some anti-RBD antibodies would be ACE2-like abzymes. Abzymes elicited by SARS-CoV-2 infection have the potential to affect host physiology.

Real-time single-molecule imaging of CaMKII-calmodulin interactions

The binding of calcium/calmodulin (CAM) to calcium/calmodulin-dependent protein kinase II (CaMKII) initiates an ATP-driven cascade that triggers CaMKII autophosphorylation. The autophosphorylation in turn increases the CaMKII affinity for CAM. Here, we studied the ATP dependence of CAM association with the actin-binding CaMKIIβ isoform using single-molecule total internal reflection fluorescence microscopy. Rhodamine-CAM associations/dissociations to surface-immobilized Venus-CaMKIIβ were resolved with 0.5 s resolution from video records, batch-processed with a custom algorithm. CAM occupancy was determined simultaneously with spot-photobleaching measurement of CaMKII holoenzyme stoichiometry. We show the ATP-dependent increase of the CAM association requires dimer formation for both the α and β isoforms. The study of mutant β holoenzymes revealed that the ATP-dependent increase in CAM affinity results in two distinct states. The phosphorylation-defective (T287.306-307A) holoenzyme resides only in the low-affinity state. CAM association is further reduced in the T287A holoenzyme relative to T287.306-307A. In the absence of ATP, the affinity of CAM for the T287.306-307A mutant and the wild-type monomer are comparable. The affinity of the ATP-binding impaired (K43R) mutant is even weaker. In ATP, the K43R holoenzyme resides in the low-affinity state. The phosphomimetic mutant (T287D) resides only in a 1000-fold higher-affinity state, with mean CAM occupancy of more than half of the 14-mer holoenzyme stoichiometry in picomolar CAM. ATP promotes T287D holoenzyme disassembly but does not elevate CAM occupancy. Single Poisson distributions characterized the ATP-dependent CAM occupancy of mutant holoenzymes. In contrast, the CAM occupancy of the wild-type population had a two-state distribution with both low- and high-affinity states represented. The low-affinity state was the dominant state, a result different from published in vitro assays. Differences in assay conditions can alter the balance between activating and inhibitory autophosphorylation. Bound ATP could be sufficient for CaMKII structural function, while antagonistic autophosphorylations may tune CaMKII kinase-regulated action-potential frequency decoding in vivo.

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.

Identifying a key spot for electron mediator-interaction to tailor CO dehydrogenase's affinity

Fe‒S cluster-harboring enzymes, such as carbon monoxide dehydrogenases (CODH), employ sophisticated artificial electron mediators like viologens to serve as potent biocatalysts capable of cleaning-up industrial off-gases at stunning reaction rates. Unraveling the interplay between these enzymes and their associated mediators is essential for improving the efficiency of CODHs. Here we show the electron mediator-interaction site on ChCODHs (Ch, Carboxydothermus hydrogenoformans) using a systematic approach that leverages the viologen-reactive characteristics of superficial aromatic residues. By enhancing mediator-interaction (R57G/N59L) near the D-cluster, the strategically tailored variants exhibit a ten-fold increase in ethyl viologen affinity relative to the wild-type without sacrificing the turn-over rate (kcat). Viologen-complexed structures reveal the pivotal positions of surface phenylalanine residues, serving as external conduits for the D-cluster to/from viologen. One variant (R57G/N59L/A559W) can treat a broad spectrum of waste gases (from steel-process and plastic-gasification) containing O2. Decoding mediator interactions will facilitate the development of industrially high-efficient biocatalysts encompassing gas-utilizing enzymes.

Transition Path Sampling Study of Engineered Enzymes That Catalyze the Morita-Baylis-Hillman Reaction: Why Is Enzyme Design so Difficult?

It is hoped that artificial enzymes designed in laboratories can be efficient alternatives to chemical catalysts that have been used to synthesize organic molecules. However, the design of artificial enzymes is challenging and requires a detailed molecular-level analysis to understand the mechanism they promote in order to design efficient variants. In this study, we computationally investigate the mechanism of proficient Morita-Baylis-Hillman enzymes developed using a combination of computational design and directed evolution. The powerful transition path sampling method coupled with in-depth post-processing analysis has been successfully used to elucidate the different chemical pathways, transition states, protein dynamics, and free energy barriers of reactions catalyzed by such laboratory-optimized enzymes. This research provides an explanation for how different chemical modifications in an enzyme affect its catalytic activity in ways that are not predictable by static design algorithms.

Rationalizing the Influence of the Binding Affinity on the Activity of Phosphoserine Phosphatases

The Sabatier principle states that catalytic activity can be maximized when the substrate binding affinity is neither too strong nor too weak. Recent studies have shown that the activity of several hydrolases is maximized at intermediate values of the binding affinity (Michaelis-Menten constant: Km ). However, it remains unclear whether this concept of artificial catalysis is applicable to enzymes in general, especially for those which have evolved under different reaction environments. Herein, we show that the activity of phosphoserine phosphatase is also enhanced at an intermediate Km value of approximately 0.5 mM. Within our dataset, the variation of Km by three orders of magnitude accounted for a roughly 18-fold variation in the activity. Owing to the high phylogenetic and physiological diversity of our dataset, our results support the importance of optimizing Km for enzymes in general. On the other hand, a 77-fold variation in the activity was attributed to other physicochemical parameters, such as the Arrhenius prefactor of kcat , and could not be explained by the Sabatier principle. Therefore, while tuning the binding affinity according to the Sabatier principle is an important consideration, the Km value is only one of many physicochemical parameters which must be optimized to maximize enzymatic activity.

Rubisco is evolving for improved catalytic efficiency and CO2 assimilation in plants

Rubisco is the primary entry point for carbon into the biosphere. However, rubisco is widely regarded as inefficient leading many to question whether the enzyme can adapt to become a better catalyst. Through a phylogenetic investigation of the molecular and kinetic evolution of Form I rubisco we uncover the evolutionary trajectory of rubisco kinetic evolution in angiosperms. We show that rbcL is among the 1% of slowest-evolving genes and enzymes on Earth, accumulating one nucleotide substitution every 0.9 My and one amino acid mutation every 7.2 My. Despite this, rubisco catalysis has been continually evolving toward improved CO2/O2 specificity, carboxylase turnover, and carboxylation efficiency. Consistent with this kinetic adaptation, increased rubisco evolution has led to a concomitant improvement in leaf-level CO2 assimilation. Thus, rubisco has been slowly but continually evolving toward improved catalytic efficiency and CO2 assimilation in plants.

Viscosity-dependent control of protein synthesis and degradation

It has been proposed that the concentration of proteins in the cytoplasm maximizes the speed of important biochemical reactions. Here we have used Xenopus egg extracts, which can be diluted or concentrated to yield a range of cytoplasmic protein concentrations, to test the effect of cytoplasmic concentration on mRNA translation and protein degradation. We find that protein synthesis rates are maximal in ~1x cytoplasm, whereas protein degradation continues to rise to a higher optimal concentration of ~1.8x. We show that this difference in optima can be attributed to a greater sensitivity of translation to cytoplasmic viscosity. The different concentration optima could produce a negative feedback homeostatic system, where increasing the cytoplasmic protein concentration above the 1x physiological level increases the viscosity of the cytoplasm, which selectively inhibits translation and drives the system back toward the 1x set point.

Dinickel enzyme evolved to metabolize the pharmaceutical metformin and its implications for wastewater and human microbiomes

Metformin is the first-line treatment for type II diabetes patients and a pervasive pollutant with more than 180 million kg ingested globally and entering wastewater. The drug's direct mode of action is currently unknown but is linked to effects on gut microbiomes and may involve specific gut microbial reactions to the drug. In wastewater treatment plants, metformin is known to be transformed by microbes to guanylurea, although genes encoding this metabolism had not been elucidated. In the present study, we revealed the function of two genes responsible for metformin decomposition (mfmA and mfmB) found in isolated bacteria from activated sludge. MfmA and MfmB form an active heterocomplex (MfmAB) and are members of the ureohydrolase protein superfamily with binuclear metal-dependent activity. MfmAB is nickel-dependent and catalyzes the hydrolysis of metformin to dimethylamine and guanylurea with a catalytic efficiency (kcat/KM) of 9.6 × 103 M-1s-1 and KM for metformin of 0.82 mM. MfmAB shows preferential activity for metformin, being able to discriminate other close substrates by several orders of magnitude. Crystal structures of MfmAB show coordination of binuclear nickel bound in the active site of the MfmA subunit but not MfmB subunits, indicating that MfmA is the active site for the MfmAB complex. Mutagenesis of residues conserved in the MfmA active site revealed those critical to metformin hydrolase activity and its small substrate binding pocket allowed for modeling of bound metformin. This study characterizes the products of the mfmAB genes identified in wastewater treatment plants on three continents, suggesting that metformin hydrolase is widespread globally in wastewater.

Thioester-Based Coupled Fluorogenic Assays in Microdevice for the Detection of Single-Molecule Enzyme Activities of Esterases with Specified Substrate Recognition

Single-molecule enzyme activity assay is a platform that enables the analysis of enzyme activities at single proteoform level. The limitation of the targetable enzymes is the major drawback of the assay, but the general assay platform is reported to study single-molecule enzyme activities of esterases based on the coupled assay using thioesters as substrate analogues. The coupled assay is realized by developing highly water-soluble thiol-reacting probes based on phosphonate-substituted boron dipyrromethene (BODIPY). The system enables the detection of cholinesterase activities in blood samples at single-molecule level, and it is shown that the dissecting alterations of single-molecule esterase activities can serve as an informative platform for activity-based diagnosis.

Enhancing 2-Pyrone Synthase Efficiency by High-Throughput Mass-Spectrometric Quantification and In Vitro/In Vivo Catalytic Performance Correlation

Engineering efficient biocatalysts is essential for metabolic engineering to produce valuable bioproducts from renewable resources. However, due to the complexity of cellular metabolic networks, it is challenging to translate success in vitro into high performance in cells. To meet such a challenge, an accurate and efficient quantification method is necessary to screen a large set of mutants from complex cell culture and a careful correlation between the catalysis parameters in vitro and performance in cells is required. In this study, we employed a mass-spectrometry based high-throughput quantitative method to screen new mutants of 2-pyrone synthase (2PS) for triacetic acid lactone (TAL) biosynthesis through directed evolution in E. coli. From the process, we discovered two mutants with the highest improvement (46 fold) in titer and the fastest kcat (44 fold) over the wild type 2PS, respectively, among those reported in the literature. A careful examination of the correlation between intracellular substrate concentration, Michaelis-Menten parameters and TAL titer for these two mutants reveals that a fast reaction rate under limiting intracellular substrate concentrations is important for in-cell biocatalysis. Such properties can be tuned by protein engineering and synthetic biology to adopt these engineered proteins for the maximum activities in different intracellular environments.

Droplet microfluidics for time-resolved serial crystallography

Serial crystallography requires large numbers of microcrystals and robust strategies to rapidly apply substrates to initiate reactions in time-resolved studies. Here, we report the use of droplet miniaturization for the controlled production of uniform crystals, providing an avenue for controlled substrate addition and synchronous reaction initiation. The approach was evaluated using two enzymatic systems, yielding 3 µm crystals of lysozyme and 2 µm crystals of Pdx1, an Arabidopsis enzyme involved in vitamin B6 biosynthesis. A seeding strategy was used to overcome the improbability of Pdx1 nucleation occurring with diminishing droplet volumes. Convection within droplets was exploited for rapid crystal mixing with ligands. Mixing times of <2 ms were achieved. Droplet microfluidics for crystal size engineering and rapid micromixing can be utilized to advance time-resolved serial crystallography.

Engineering Rubisco to enhance CO2 utilization

Ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) is a pivotal enzyme that mediates the fixation of CO2. As the most abundant protein on earth, Rubisco has a significant impact on global carbon, water, and nitrogen cycles. However, the significantly low carboxylation activity and competing oxygenase activity of Rubisco greatly impede high carbon fixation efficiency. This review first summarizes the current efforts in directly or indirectly modifying plant Rubisco, which has been challenging due to its high conservation and limitations in chloroplast transformation techniques. However, recent advancements in understanding Rubisco biogenesis with the assistance of chaperones have enabled successful heterologous expression of all Rubisco forms, including plant Rubisco, in microorganisms. This breakthrough facilitates the acquisition and evaluation of modified proteins, streamlining the measurement of their activity. Moreover, the establishment of a screening system in E. coli opens up possibilities for obtaining high-performance mutant enzymes through directed evolution. Finally, this review emphasizes the utilization of Rubisco in microorganisms, not only expanding their carbon-fixing capabilities but also holding significant potential for enhancing biotransformation processes.

Selective cascade activation of polycyclic aromatic hydrocarbons in human cells: Role of enzyme's intrinsic electric field

Polycyclic aromatic hydrocarbons (PAHs) are major environmental organic pollutants. Some metabolites of PAHs show greater toxicity to humans while the others do not. It is highly important to decipher PAHs' regioselective activation mechanism and identify the major metabolites to accurately evaluate their public health risk. Here, we have performed a thorough computational study of benzo[a]anthracene (BA) metabolized by P450 1A1 by employing molecular docking, molecular dynamics simulations, quantum chemical calculation, and quantum mechanics/molecular mechanics calculations. Our findings show that highly-reactive species such as 3,4-epoxide, 8,9-epoxide, 3,4-diol-1,2-epoxide, and 8,9-diol-10,11-epoxide were major metabolites, which can efficiently react with guanine and damage DNA with extremely low energy barrier, therefore, supports the regioselective metabolism of BA. The origin of this selective activation is mainly contributed to both the oxygen‑carbon distance and previously overlooked enzyme's intrinsic electric field. Consequently, based on the resolved activation selectivity of BA. We built a high-throughput strategy to efficiently predict the metabolites of other PAHs. The accuracy of the strategy is validated by studying 16 PAHs on the priority control list. Hopefully this will aid the accurate evaluation of public health risks associated with PAH emissions.

Theoretical Improvements in Enzyme Efficiency Associated with Noisy Rate Constants and Increased Dissipation

Previous studies have revealed the extraordinarily large catalytic efficiency of some enzymes. High catalytic proficiency is an essential accomplishment of biological evolution. Natural selection led to the increased turnover number, kcat, and enzyme efficiency, kcat/KM, of uni-uni enzymes, which convert a single substrate into a single product. We added or multiplied random noise with chosen rate constants to explore the correlation between dissipation and catalytic efficiency for ten enzymes: beta-galactosidase, glucose isomerase, β-lactamases from three bacterial strains, ketosteroid isomerase, triosephosphate isomerase, and carbonic anhydrase I, II, and T200H. Our results highlight the role of biological evolution in accelerating thermodynamic evolution. The catalytic performance of these enzymes is proportional to overall entropy production-the main parameter from irreversible thermodynamics. That parameter is also proportional to the evolutionary distance of β-lactamases PC1, RTEM, and Lac-1 when natural or artificial evolution produces the optimal or maximal possible catalytic efficiency. De novo enzyme design and attempts to speed up the rate-limiting catalytic steps may profit from the described connection between kinetics and thermodynamics.

Cofactorless oxygenases guide anthraquinone-fused enediyne biosynthesis

The anthraquinone-fused enediynes (AFEs) combine an anthraquinone moiety and a ten-membered enediyne core capable of generating a cytotoxic diradical species. AFE cyclization is triggered by opening the F-ring epoxide, which is also the site of the most structural diversity. Previous studies of tiancimycin A, a heavily modified AFE, have revealed a cryptic aldehyde blocking installation of the epoxide, and no unassigned oxidases could be predicted within the tnm biosynthetic gene cluster. Here we identify two consecutively acting cofactorless oxygenases derived from methyltransferase and α/β-hydrolase protein folds, TnmJ and TnmK2, respectively, that are responsible for F-ring tailoring in tiancimycin biosynthesis by comparative genomics. Further biochemical and structural characterizations reveal that the electron-rich AFE anthraquinone moiety assists in catalyzing deformylation, epoxidation and oxidative ring cleavage without exogenous cofactors. These enzymes therefore fill important knowledge gaps for the biosynthesis of this class of molecules and the underappreciated family of cofactorless oxygenases.