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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Loop engineering reveals the importance of active-site-decorating loops and gating residue in substrate affinity modulation of arginine deiminase (an anti-tumor enzyme)

Highlights: • Loop engineering on the active-site-decorating loops yielded several PpADI variants with low S{sub 0.5} values. • Several amino acid positions in active-site-decorating loops essential for the substrate affinity of PpADI were identified. • High loop flexibility (especially the gating residue Arg400) is beneficial for the substrate affinity of PpADI. Protein engineering of enzyme loop regions is an effective strategy to improve enzymatic properties. Previous studies that aimed to boost the activity of PpADI (an arginine deiminase from Pseudomonas plecoglossicida) under physiological conditions yielded several significantly improved variants that harbor substitutions predominantly located in active-site-decorating loops. A multi-site saturation mutagenesis at four positions in loop 1 (37, 38, 42, and 43) and three positions in loop 4 (402, 403, and 404) was performed to elucidate the importance of these loops in modulating the substrate affinity of PpADI. The identified “best” variant (M6-L1-4) showed a decreased S{sub 0.5} (‘K{sub M}’) of 0.48 mM compared with the parent M6 (0.81 mM). Subsequently, a rational design to recombine beneficial substitutions within loops 1 and 4 yielded variant L6 with a substantially decreased S{sub 0.5} value (0.17 mM). A comprehensive simulation analysis resulted in a conclusion that high loop flexibility (especially the gating residue Arg400) is beneficial for substrate affinity due to less efficient blocking of the active site.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Synthetic Microbial Consortium for Biological Breakdown and Conversion of Lignin

The plant polymer lignin is the most abundant renewable source of aromatics on the planet and conversion of it to valuable fuels and chemicals is critical to the economic viability of a lignocellulosic biofuels industry and to meeting the DOE’s 2022 goal of $\$2.50$/gallon mean biofuel selling price. Presently, there is no efficient way of converting lignin into valuable commodities. Current biological approaches require mixtures of expensive ligninolytic enzymes and engineered microbes. This project was aimed at circumventing these problems by discovering commensal relationships among fungi and bacteria involved in biological lignin utilization and using this knowledge to engineer microbial communities capable of converting lignin into renewable fuels and chemicals. Essentially, we aimed to learn from, mimic and improve on nature. We discovered fungi that synergistically work together to degrade lignin, engineered fungal systems to increase expression of the required enzymes and engineered organisms to produce products such as biodegradable plastics precursors.

09 BIOMASS FUELS↗
DOE OSTI2025

Controlled Enzyme Cargo Loading in Engineered Bacterial Microcompartment Shells

Bacterial microcompartments (BMCs) are nanometer-scale organelles with a protein-based shell that serve to colocalize and encapsulate metabolic enzymes. They may provide a range of benefits to improve pathway catalysis, including substrate channeling and selective permeability. Several groups are working toward using BMC shells as a platform for enhancing engineered metabolic pathways. The microcompartment shell of Haliangium ochraceum (HO) has emerged as a versatile and modular shell system that can be expressed and assembled outside its native host and with non-native cargo. Further, the HO shell has been modified to use the engineered protein conjugation system SpyCatcher–SpyTag for non-native cargo loading. Here, we used a model enzyme, triose phosphate isomerase (Tpi), to study non-native cargo loading into four HO shell variants and begin to understand maximal shell loading levels. We also measured activity of Tpi encapsulated in the HO shell variants and found that activity was determined by the amount of cargo loaded and was not strongly impacted by the predicted permeability of the shell variant to large molecules. All shell variants tested could be used to generate active, Tpi-loaded versions, but the simplest variants assembled most robustly. We propose that the simple variant is the most promising for continued development as a metabolic engineering platform.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Revisiting metabolic engineering strategies for microbial synthesis of oleochemicals

Microbial production of oleochemicals from renewable feedstocks remains an attractive route to produce high-energy density, liquid transportation fuels and high-value chemical products. Metabolic engineering strategies have been applied to demonstrate production of a wide range of oleochemicals, including free fatty acids, fatty alcohols, esters, olefins, alkanes, ketones, and polyesters in both bacteria and yeast. The majority of these demonstrations synthesized products containing long-chain fatty acids. These successes motivated additional effort to produce analogous molecules comprised of medium-chain fatty acids, molecules that are less common in natural oils and therefore of higher commercial value. Substantial progress has been made towards producing a subset of these chemicals, but significant work remains for most. The other primary challenge to producing oleochemicals in microbes is improving the performance, in terms of yield, rate, and titer, of biocatalysts such that economic large-scale processes are feasible. Common metabolic engineering strategies include blocking pathways that compete with synthesis of oleochemical building blocks and/or consume products, pulling flux through pathways by removing regulatory signals, pushing flux into biosynthesis by overexpressing rate-limiting enzymes, and engineering cells to tolerate the presence of oleochemical products. In this review, we describe the basic fundamentals of oleochemical synthesis and summarize advances since 2013 towards improving performance of heterotrophic microbial cell factories.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Engineering PHL7 for Improved Poly(Ethylene Terephthalate) Depolymerization via Rational Design and Directed Evolution

Enzymatic depolymerization of poly(ethylene terephthalate) (PET) has emerged as a promising approach for polyester recycling, and, to date, many natural and engineered PET hydrolase enzymes have been reported. For industrial use, PET hydrolases must achieve high depolymerization extent and exhibit excellent thermostability. Here, we engineered a natural PET hydrolase, Polyester Hydrolase Leipzig #7 (PHL7), through rational design and directed evolution using a high-throughput screening platform. Four new enzymes were engineered with enhanced properties compared with the parent enzyme, wild-type PHL7 (PHL7-WT), and other benchmark PET hydrolases, under the tested conditions. In bioreactors, the exemplary engineered enzyme, PHL7-Jemez, exhibited improved ability to depolymerize amorphous PET film compared with PHL7-WT at 2.9% and 20% substrate loadings, with 37% and 270% higher hydrolysis, respectively, after 48 h. This study develops several state-of-the-art PET hydrolases and demonstrates a directed evolution platform to engineer high-performance enzymes, which can accelerate enzyme discovery toward improved biocatalytic recycling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Enzyme property prediction using artificial intelligence

Artificial intelligence (AI)-driven enzyme property prediction enables rapid discovery and engineering of enzymes for a wide range of biotechnological and therapeutic applications. Here, we first introduce the key components in AI model development, including enzyme datasets, protein representation methods, and model architectures. We then highlight a variety of AI tools developed for the prediction of enzyme properties and functional annotations, including enzyme structure, kinetic parameters, substrate specificity, thermostability, solubility, Enzyme Commission number, and Gene Ontology term. Moreover, we describe representative downstream applications enabled by these AI tools. Finally, we discuss some challenges and opportunities as well as future prospects.

Yuan, Le [University of Illinois at Urbana-Champai↗
DOE OSTI2014

Functional characterization of cytochromes P450 2B from the desert woodrat Neotoma lepida

Mammalian detoxification processes have been the focus of intense research, but little is known about how wild herbivores process plant secondary compounds, many of which have medicinal value or are drugs. cDNA sequences that code for three enzymes of the cytochrome P450 (CYP) 2B subfamily, here termed 2B35, 2B36, and 2B37 have been recently identified from a wild rodent, the desert woodrat (Malenke et al., 2012). Two variant clones of each enzyme were engineered to increase protein solubility and to facilitate purification, as reported for CYP2B enzymes from multiple species. When expressed in Escherichia coli each of the woodrat proteins gave the characteristic maximum at 450 nm in a reduced carbon monoxide difference spectrum but generally expressed at lower levels than rat CYP2B1. Two enzymes, 2B36 and 2B37, showed dealkylation activity with the model substrates 7-ethoxy-4-(trifluoromethyl)coumarin and 7-benzyloxyresorufin, whereas 2B35 was inactive. Binding of the monoterpene (+)-α-pinene produced a Type I shift in the absorbance spectrum of each enzyme. Mutation of 2B37 at residues 114, 262, or 480, key residues governing ligand interactions with other CYP2B enzymes, did not significantly change expression levels or produce the expected functional changes. In summary, two catalytic and one ligand-binding assay are sufficient to distinguish among CYP2B35, 2B36, and 2B37. Differences in functional profiles between 2B36 and 2B37 are partially explained by changes in substrate recognition site residue 114, but not 480. The results advance our understanding of the mechanisms of detoxification in wild mammalian herbivores and highlight the complexity of this system. - Highlights: • Three CYP2B enzymes from Neotoma lepida were cloned, engineered, and expressed. • A mix of catalytic and binding assays yields unique results for each enzyme. • Mutational analysis indicates CYP{sub 2}B substrate recognition remains to be clarified. • Reported N. lepida gene sequences allow for larger scale analyses of CYP{sub 2}B enzymes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

Chapter 3.03 - Multifunctional Enzyme Systems for Plant Cell Wall Degradation

Multifunctional enzymes refer to proteins that consist of two or more catalytic modules. Many microorganisms use multifunctional enzymes to efficiently break down the recalcitrant polymeric networks that constitute plant cell walls. Future applications of multifunctional enzymes may represent a potential solution to the problem of high enzyme cost for processing lignocellulosic biomass into fermentable sugars. Currently, commercial enzyme mixtures used in simultaneous saccharification fermentation process for biofuel production are derived primarily from free enzyme systems produced by fungi. In this context, we have analyzed the modular structures of 16 937 genes corresponding to 34 glycoside hydrolase families putatively related to the degradation of lignocellulose in the Carbohydrate Active enZyme (CAZy) database. Among these genes, 64 gene sequences have been identified to putatively encode multifunctional enzymes, and up to five catalytic modules have been found in a single polypeptide. Based on their deduced polypeptide sequences, they can be classified into four types, that is, cellulase-cellulase, cellulase-hemicellulase, hemicellulase-hemicellulase, and hemicellulase-carbohydrate esterase. The compositional modules and architectural structures of these enzymes are analyzed here, and their putative activities on breaking down cell walls are discussed. We further discuss the predicted intramolecular synergistic mechanisms between the catalytic modules, including substrate channeling, which is a mechanism often proposed for carbohydrate-binding modules residing in multifunctional enzymes. Furthermore, the potential applications of native and engineered multifunctional enzymes for biomass conversion technology are also reviewed.

..beta..-d-glucosidases↗
DOE OSTI2017

Differential catalytic promiscuity of the alkaline phosphatase superfamily bimetallo core reveals mechanistic features underlying enzyme evolution

Members of enzyme superfamilies specialize in different reactions but often exhibit catalytic promiscuity for one another's reactions, consistent with catalytic promiscuity as an important driver in the evolution of new enzymes. Wanting to understand how catalytic promiscuity and other factors may influence evolution across a superfamily, we turned to the well-studied alkaline phosphatase (AP) superfamily, comparing three of its members, two evolutionarily distinct phosphatases and a phosphodiesterase. Here, we mutated distinguishing active-site residues to generate enzymes that had a common Zn 2+ bimetallo core but little sequence similarity and different auxiliary domains. We then tested the catalytic capabilities of these pruned enzymes with a series of substrates. A substantial rate enhancement of ~1011-fold for both phosphate mono- and diester hydrolysis by each enzyme indicated that the Zn 2+ bimetallo core is an effective mono/di-esterase generalist and that the bimetallo cores were not evolutionarily tuned to prefer their cognate reactions. In contrast, our pruned enzymes were ineffective sulfatases, and this limited promiscuity may have provided a driving force for founding the distinct one-metal-ion branch that contains all known AP superfamily sulfatases. Finally, our pruned enzymes exhibited 10 7 –10 8 -fold phosphotriesterase rate enhancements, despite absence of such enzymes within the AP superfamily. We speculate that the superfamily active-site architecture involved in nucleophile positioning prevents accommodation of the additional triester substituent. Overall, we suggest that catalytic promiscuity, and the ease or difficulty of remodeling and building onto existing protein scaffolds, have greatly influenced the course of enzyme evolution. Uncovering principles and properties of enzyme function, promiscuity, and repurposing provides lessons for engineering new enzymes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Near-complete depolymerization of polyesters with nano-dispersed enzymes

Successfully interfacing enzymes and biomachinery with polymers affords on-demand modification and/or programmable degradation during the manufacture, utilization and disposal of plastics, but requires controlled biocatalysis in solid matrices with macromolecular substrates. Embedding enzyme microparticles speeds up polyester degradation, but compromises host properties and unintentionally accelerates the formation of microplastics with partial polymer degradation. Here we show that by nanoscopically dispersing enzymes with deep active sites, semi-crystalline polyesters can be degraded primarily via chain-end-mediated processive depolymerization with programmable latency and material integrity, akin to polyadenylation-induced messenger RNA decay. It is also feasible to achieve processivity with enzymes that have surface-exposed active sites by engineering enzyme-protectant-polymer complexes. Poly(caprolactone) and poly(lactic acid) containing less than 2 weight per cent enzymes are depolymerized in days, with up to 98 per cent polymer-to-small-molecule conversion in standard soil composts and household tap water, completely eliminating current needs to separate and landfill their products in compost facilities. Furthermore, oxidases embedded in polyolefins retain their activities. However, hydrocarbon polymers do not closely associate with enzymes, as their polyester counterparts do, and the reactive radicals that are generated cannot chemically modify the macromolecular host. This study provides molecular guidance towards enzyme-polymer pairing and the selection of enzyme protectants to modulate substrate selectivity and optimize biocatalytic pathways. Furthermore, the results also highlight the need for in-depth research in solid-state enzymology, especially in multi-step enzymatic cascades, to tackle chemically dormant substrates without creating secondary environmental contamination and/or biosafety concerns.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

A comparative study of ethanol production using dilute acid, ionic liquid and AFEX™ pretreated corn stover

In a biorefinery producing cellulosic biofuels, biomass pretreatment will significantly influence the efficacy of enzymatic hydrolysis and microbial fermentation. Comparison of different biomass pretreatment techniques by studying the impact of pretreatment on downstream operations at industrially relevant conditions and performing comprehensive mass balances will help focus attention on necessary process improvements, and thereby help reduce the cost of biofuel production. An on-going collaboration between the three US Department of Energy (DOE) funded bioenergy research centers (Great Lakes Bioenergy Research Center (GLBRC), Joint BioEnergy Institute (JBEI) and BioEnergy Science Center (BESC)) has given us a unique opportunity to compare the performance of three pretreatment processes, notably dilute acid (DA), ionic liquid (IL) and ammonia fiber expansion (AFEX TM ), using the same source of corn stover. Separate hydrolysis and fermentation (SHF) was carried out using various combinations of commercially available enzymes and engineered yeast (Saccharomyces cerevisiae 424A) strain. The optimal commercial enzyme combination (Ctec2: Htec2: Multifect Pectinase, percentage total protein loading basis) was evaluated for each pretreatment with a microplate-based assay using milled pretreated solids at 0.2% glucan loading and 15 mg total protein loading/g of glucan. The best enzyme combinations were 67:33:0 for DA, 39:33:28 for IL and 67:17:17 for AFEX. The amounts of sugar (kg) (glucose: xylose: total gluco- and xylo-oligomers) per 100 kg of untreated corn stover produced after 72 hours of 6% glucan loading enzymatic hydrolysis were: DA (25:2:2), IL (31:15:2) and AFEX (26:13:7). Additionally, the amounts of ethanol (kg) produced per 100 kg of untreated corn stover and the respective ethanol metabolic yield (%) achieved with exogenous nutrient supplemented fermentations were: DA (14.0, 92.0%), IL (21.2, 93.0%) and AFEX (20.5, 95.0%), respectively. The reason for lower ethanol yield for DA is because most of the xylose produced during the pretreatment was removed and not converted to ethanol during fermentation. Compositional analysis of the pretreated biomass solids showed no significant change in composition for AFEX treated corn stover, while about 85% of hemicellulose was solubilized after DA pretreatment, and about 90% of lignin was removed after IL pretreatment. As expected, the optimal commercial enzyme combination was different for the solids prepared by different pretreatment technologies. Due to loss of nutrients during the pretreatment and washing steps, DA and IL pretreated hydrolysates required exogenous nutrient supplementation to ferment glucose and xylose efficiently, while AFEX pretreated hydrolysate did not require nutrient supplementation.

09 BIOMASS FUELS↗
DOE OSTI2025

Evaluating the limitations of Bayesian metabolic control analysis

AbstractBayesian Metabolic Control Analysis (BMCA) has emerged as a promising framework for inferring metabolic control coefficients in data-limited scenarios by integrating Bayesian inference with linlog rate laws. However, its predictive accuracy and limitations remain underexplored. This study systematically evaluates BMCA’s ability to infer elasticity values, flux control coefficients (FCCs), and concentration control coefficients (CCCs) under varying data availability conditions using three synthetic metabolic network models. Our findings highlight the strengths and weaknesses of BMCA, guiding its application in metabolic engineering and emphasizing the need for methodological refinements.Author summaryUnderstanding how enzymes control metabolic pathways is crucial for optimizing biomanufacturing and synthetic biology applications. Bayesian Metabolic Control Analysis (BMCA) is a promising computational method that integrates Bayesian inference with metabolic control analysis to estimate key control parameters, even in cases with limited experimental data. However, the accuracy and limitations of BMCA remain unclear. In this study, we systematically evaluate BMCA using three synthetic metabolic networks to determine how different types of physiological data impact its predictive performance. We find that BMCA requires flux and enzyme concentration data for accurate predictions, while external metabolite concentrations contribute little. Additionally, BMCA fails to predict elasticity values beyond a magnitude of 1.5 and reliably infer allosteric regulation, even when strong regulatory interactions exist. In addition, BMCA does not accurately rank metabolic control points, which may limit its utility in identifying key enzymes in engineered pathways. Our work provides practical insights into when and how BMCA can be applied, guiding future research in metabolic modeling and control analysis.

Shin, Janis (ORCID:0000000216572455)↗
DOE OSTI2017

Probing Small-Molecule Degradation to Counter Enzyme Promiscuity

Enzymes that degrade specific small molecules could save lives by neutralizing threats from chemical agents in the blood or environment, or by starving pathogenic cells, but promiscuous interactions with other molecules typically limit their effectiveness by blocking the enzyme active site. An obvious solution would be to re-engineer the enzyme to enhance catalytic fidelity, but lack of understanding about how enzymes discriminate between molecules remains a formidable challenge to this approach. Our recent work in collaboration with the University of Texas (UT) suggested a new approach and a model system for understanding enzyme specificity. Asparaginase enzymes catalyze degradation of asparagine, which forms the basis of a medical treatment. Competition by the abundant and chemically similar molecule, glutamine, interferes with asparagine decomposition, thus hindering enzyme efficacy. Asparaginase is advantageous as a model degradation enzyme because variants that demonstrate different binding affinities and catalytic rates can be compared. Here, we leveraged Sandia and the University of Maryland's strengths in molecular simulation, and UT experimental expertise in asparaginase modification and functional assays, to understand asparaginase specificity. Our results advanced a new hypothesis about asparaginase catalytic mechanism that explains for the first time why proximity between the substrate's alpha-carboxyl and carboxamide is absolutely required for catalysis. Based on those insights, we developed the first mutant (Q59L) asparaginase from E. coli that lacks activity toward glutamine. We used that mutant to show that glutaminase activity is required to kill cancer cells that have asparagine synthetase enzymes (ASNS), but not ASNS-negative cancer cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Extensive site-directed mutagenesis reveals interconnected functional units in the alkaline phosphatase active site

Enzymes enable life by accelerating reaction rates to biological timescales. Conventional studies have focused on identifying the residues that have a direct involvement in an enzymatic reaction, but these so-called ‘catalytic residues’ are embedded in extensive interaction networks. Although fundamental to our understanding of enzyme function, evolution, and engineering, the properties of these networks have yet to be quantitatively and systematically explored. We dissected an interaction network of five residues in the active site of Escherichia coli alkaline phosphatase. Analysis of the complex catalytic interdependence of specific residues identified three energetically independent but structurally interconnected functional units with distinct modes of cooperativity. From an evolutionary perspective, this network is orders of magnitude more probable to arise than a fully cooperative network. From a functional perspective, new catalytic insights emerge. Further, such comprehensive energetic characterization will be necessary to benchmark the algorithms required to rationally engineer highly efficient enzymes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The role of binding modules in enzymatic poly(ethylene terephthalate) hydrolysis at high-solids loadings

In nature, enzymes that deconstruct biological polymers, such as cellulose and chitin, often exhibit multi-domain architectures, comprising a catalytic domain and a non-catalytic binding module; the latter serves to increase the enzyme concentration at the substrate surface. This multi-domain architecture has been shown to improve the hydrolysis of poly(ethylene terephthalate) (PET) using engineered cutinase enzymes. Here, we examine the role of accessory binding modules at industrially relevant PET solids loadings necessary for cost-effective enzymatic recycling. Using a thermostable variant of leaf compost cutinase (LCC), we produced synthetic fusion constructs of LCC with five type A carbohydrate-binding modules (CBMs). At solids loadings below 10 wt%, the CBMs improve aromatic monomer yield from PET, but above this threshold, conversion extents up to 97% are reached with no added benefits from the presence of CBM fusions. This suggests that fusion constructs with the herein studied CBMs are not necessary for industrial enzymatic PET recycling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

The importance of sourcing enzymes from non-conventional fungi for metabolic engineering and biomass breakdown

A wealth of fungal enzymes has been identified from nature, which continue to drive strain engineering and bioprocessing for a range of industries. However, while a number of clades have been investigated, the vast majority of the fungal kingdom remains unexplored for industrial applications. In this study, we discuss selected classes of fungal enzymes that are currently in biotechnological use, and explore more basal, non-conventional fungi and their underexploited biomass-degrading mechanisms as promising agents in the transition towards a bio-based society. Of special interest are anaerobic fungi like the Neocallimastigomycota, which were recently found to harbor the largest diversity of biomass-degrading enzymes among the fungal kingdom. Enzymes sourced from these basal fungi have been used to metabolically engineer substrate utilization in yeast, and may offer new paths to lignin breakdown and tunneled biocatalysis. We also contrast classic enzymology approaches with emerging ‘omics’-based tools to decipher function within novel fungal isolates and identify new promising enzymes. Recent developments in genome editing are expected to accelerate discovery and metabolic engineering within these systems, yet are still limited by a lack of high-resolution genomes, gene regulatory regions, and even appropriate culture conditions. Lastly, we present new opportunities to harness the biomass-degrading potential of undercharacterized fungi via heterologous expression and engineered microbial consortia.

09 BIOMASS FUELS↗
DOE OSTI2016

Structure of Type IIL Restriction-Modification Enzyme MmeI in Complex with DNA Has Implications for Engineering New Specificities

The creation of restriction enzymes with programmable DNA-binding and -cleavage specificities has long been a goal of modern biology. The recently discovered Type IIL MmeI family of restriction-and-modification (RM) enzymes that possess a shared target recognition domain provides a framework for engineering such new specificities. However, a lack of structural information on Type IIL enzymes has limited the repertoire that can be rationally engineered. We report here a crystal structure of MmeI in complex with its DNA substrate and an S-adenosylmethionine analog (Sinefungin). The structure uncovers for the first time the interactions that underlie MmeI-DNA recognition and methylation (5’-TCCRAC-3’; R = purine) and provides a molecular basis for changing specificity at four of the six base pairs of the recognition sequence (5’-TCCRAC-3’). Surprisingly, the enzyme is resilient to specificity changes at the first position of the recognition sequence (5’-TCCRAC-3’). Collectively, the structure provides a basis for engineering further derivatives of MmeI and delineates which base pairs of the recognition sequence are more amenable to alterations than others.

59 BASIC BIOLOGICAL SCIENCES↗