Abstract We explore sequence determinants of enzyme activity and specificity in a major enzyme family of terpene synthases. Most enzymes in this family catalyze reactions that produce cyclic terpenes—complex hydrocarbons widely used by plants and insects in diverse biological processes such as defense, communication, and symbiosis. To analyze the molecular mechanisms of emergence of terpene cyclization, we have carried out in-depth examination of mutational space around (E)-β-farnesene synthase, an Artemisia annua enzyme which catalyzes production of a linear hydrocarbon chain. Each mutant enzyme in our synthetic libraries was characterized biochemically, and the resulting reaction rate data were used as input to the Michaelis–Menten model of enzyme kinetics, in which free energies were represented as sums of one-amino-acid contributions and two-amino-acid couplings. Our model predicts measured reaction rates with high accuracy and yields free energy landscapes characterized by relatively few coupling terms. As a result, the Michaelis–Menten free energy landscapes have simple, interpretable structure and exhibit little epistasis. We have also developed biophysical fitness models based on the assumption that highly fit enzymes have evolved to maximize the output of correct products, such as cyclic products or a specific product of interest, while minimizing the output of byproducts. This approach results in nonlinear fitness landscapes that are considerably more epistatic. Overall, our experimental and computational framework provides focused characterization of evolutionary emergence of novel enzymatic functions in the context of microevolutionary exploration of sequence space around naturally occurring enzymes.
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ICEKAT: an interactive online tool for calculating initial rates from continuous enzyme kinetic traces
Abstract Background Continuous enzyme kinetic assays are often used in high-throughput applications, as they allow rapid acquisition of large amounts of kinetic data and increased confidence compared to discontinuous assays. However, data analysis is often rate-limiting in high-throughput enzyme assays, as manual inspection and selection of a linear range from individual kinetic traces is cumbersome and prone to user error and bias. Currently available software programs are specialized and designed for the analysis of complex enzymatic models. Despite the widespread use of initial rate determination for processing kinetic data sets, no simple and automated program existed for rapid analysis of initial rates from continuous enzyme kinetic traces. Results An Interactive Continuous Enzyme Kinetics Analysis Tool (ICEKAT) was developed for semi-automated calculation of initial rates from continuous enzyme kinetic traces with particular application to the evaluation of Michaelis-Menten and EC 50 /IC 50 kinetic parameters, as well as the results of high-throughput screening assays. ICEKAT allows users to interactively fit kinetic traces using convenient browser-based selection tools, ameliorating tedious steps involved in defining ranges to fit in general purpose programs like Microsoft Excel and Graphpad Prism, while still maintaining simplicity in determining initial rates. As a test case, we quickly analyzed over 500 continuous enzyme kinetic traces resulting from experimental data on the response of the protein lysine deacetylase SIRT1 to small-molecule activators. Conclusions ICEKAT allows simultaneous visualization of individual initial rate fits and the resulting Michaelis-Menten or EC 50 /IC 50 kinetic model fits, as well as hits from high-throughput screening assays. In addition to serving as a convenient program for practicing enzymologists, ICEKAT is also a useful teaching aid to visually demonstrate in real-time how incorrect initial rate fits can affect calculated Michaelis-Menten or EC 50 /IC 50 kinetic parameters. For the convenience of the research community, we have made ICEKAT freely available online at https://icekat.herokuapp.com/icekat .
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- Award ID(s):
- 1708829
- NSF-PAR ID:
- 10290446
- Date Published:
- Journal Name:
- BMC Bioinformatics
- Volume:
- 21
- Issue:
- 1
- ISSN:
- 1471-2105
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract The surface display laccase (SDL) biocatalyst, where the enzyme laccase is displayed on the surface of biological cells through synthetic biology, provides a new opportunity to develop sustainable technologies for removal of emerging contaminants from wastewater. This study vigorously characterized biocatalytic properties of the SDL in comparison to free laccase in removing emerging contaminant acetaminophen (APAP), with the aim to understand the effect of surface display on enzyme functionality and identify the strategy to overcome the potential limitation. The SDL could effectively remove APAP. Adding redox mediators substantially improved the removal efficiency. The Michaelis–Menten kinetic analysis showed that the redox mediator 2,2‐azinobis‐3‐ethylbenzothiazoline‐6‐sulfonate could overcome the limitation of APAP accessing the active site of laccase in the SDL biocatalyst. The APAP removal rate catalyzed by the SDL in real secondary wastewater effluent was higher than that in acetate buffer; comprehensive enzyme kinetic analysis provided clear evidence that there were redox mediating compounds in the wastewater. Analysis of transformation products revealed that surface display did not change laccase functionality in terms of APAP transformation mechanism. In addition, the SDL retained 88% of the initial activity after six repeated APAP biotransformation reactions. Results from this study provide a scientific basis for developing and implementing SDL as an innovative biocatalytic material for contaminant treatment applications.
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Absorbance measurements on intact chemolithotrophic microorganisms that respire aerobically on soluble iron are described that used a novel integrating cavity absorption meter to eliminate the effects of light scattering on the experimental results. Steady state kinetic measurements on ferric iron production by intact cells revealed that the Michaelis Menten equation described the initial rates of product formation for at least 8 different chemolithotrophic microorganisms in 6 phyla distributed equally among the archaea and the Gram negative and Gram positive eubacteria. Cell-monitored turnover measurements during aerobic respiration on soluble iron by the same 12 intact microorganisms revealed six different patterns of iron-dependent absorbance changes, suggesting that there may be at least six different sets of prosthetic groups and biomolecules that can accomplish aerobic respiration on soluble iron. Detailed kinetic studies revealed that the 3-component iron respiratory chain of Acidithiobacillus ferrooxidans functioned as an ensemble with a single macroscopic rate constant when the iron-reduced proteins were oxidized in the presence of excess molecular oxygen. The principal member of this 3-component system was a cupredoxin called rusticyanin that was present in the periplasm of At. ferrooxidans at an approximate concentration of 350 mg/mL, an observation that provides new insights into the crowded environments in the periplasms of Gram negative eubacteria that conduct electrons across their periplasm. The ability to conduct direct spectrophotometric measurements under noninvasive physiological conditions represents a new and powerful approach to examine the rates and extents of biological events in situ without disrupting the complexity of the live cellular environment.more » « less
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Abstract Monod and Logistic growth models have been widely used as basic equations to describe cell growth in bioprocess engineering. In the case of the Monod equation, the specific growth rate is governed by a limiting nutrient, with the mathematical form similar to the Michaelis–Menten equation. In the case of the Logistic equation, the specific growth rate is determined by the carrying capacity of the system, which could be growth‐inhibiting factors (i.e., toxic chemical accumulation) other than the nutrient level. Both equations have been found valuable to guide us build unstructured kinetic models to analyze the fermentation process and understand cell physiology. In this work, we present a hybrid Logistic‐Monod growth model, which accounts for multiple growth‐dependent factors including both the limiting nutrient and the carrying capacity of the system. Coupled with substrate consumption and yield coefficient, we present the analytical solutions for this hybrid Logistic‐Monod model in both batch and continuous stirred tank reactor (CSTR) culture. Under high biomass yield (
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Abstract Enzymes provide optimal three-dimensional structures for substrate binding and the subsequent accelerated reaction. Such folding-dependent catalytic behaviors, however, are seldom mechanistically explored with reduced structural complexity. Here, we demonstrate that the α-helix, a much simpler structural motif of enzyme, can facilitate its own growth through the self-catalyzed polymerization of
N -carboxyanhydride (NCA) in dichloromethane. The reversible binding between the N terminus of α-helical polypeptides and NCAs promotes rate acceleration of the subsequent ring-opening reaction. A two-stage, Michaelis–Menten-type kinetic model is proposed by considering the binding and reaction between the propagating helical chains and the monomers, and is successfully utilized to predict the molecular weights and molecular-weight distributions of the resulting polymers. This work elucidates the mechanism of helix-induced, enzyme-mimetic catalysis, emphasizes the importance of solvent choice in the discovery of new reaction type, and provides a route for rapid production of well-defined synthetic polypeptides by taking advantage of self-accelerated ring-opening polymerizations.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1186/s12859-020-3513-y
