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Optogenetic approaches are transforming quantitative studies of cell-signaling systems. A recently developed photoswitchable mitogen-activated protein kinase kinase 1 (MEK1) enzyme (psMEK) short-circuits the highly conserved Extracellular Signal-Regulated Kinase (ERK)-signaling cascade at the most proximal step of effector kinase activation. However, since this optogenetic tool relies on phosphorylation-mimicking substitutions in the activation loop of MEK, its catalytic activity is predicted to be substantially lower than that of wild-type MEK that has been phosphorylated at these residues. Here, we present evidence that psMEK indeed has suboptimal functionality in vivo and propose a strategy to circumvent this limitation by harnessing gain-of-function, destabilizing mutations in MEK. Specifically, we demonstrate that combining phosphomimetic mutations with additional mutations in MEK, chosen for their activating potential, restores maximal kinase activity in vitro. We establish that this modification can be tuned by the choice of the destabilizing mutation and does not interfere with reversible activation of psMEK in vivo in both Drosophila and zebrafish. To illustrate the types of perturbations enabled by optimized psMEK, we use it to deliver pulses of ERK activation during zebrafish embryogenesis, revealing rheostat-like responses of an ERK-dependent morphogenetic event.
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The inner workings of an enzyme
Predictive understanding for how a particular amino acid sequence encodes enzymatic function is a grand challenge in molecular biology, with profound impacts in fields ranging from industrial biotechnology, computational protein design, and agriculture to predictive identification of disease mutations ( 1 ) and medicinal chemistry. Innovative methods for high-throughput and quantitative measurements of different aspects of enzymatic function are needed to achieve this goal. On page 411 of this issue, Markin et al. ( 2 ) describe a laboratory-on-a-chip platform called High-Throughput Microfluidic Enzyme Kinetics (HT-MEK) as a step in this direction. The technique allows high-fidelity in vitro biochemical and biophysical characterization of more than 1000 mutants of the model enzyme PafA (phosphate-irrepressible alkaline phosphatase of Flavobacterium). HT-MEK identifies partially overlapping yet distinct networks of amino acids that undergird individual reaction steps of PafA, illuminating the mechanistic basis of catalysis for this enzyme.
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- Award ID(s):
- 2030221
- PAR ID:
- 10345161
- Date Published:
- Journal Name:
- Science
- Volume:
- 373
- Issue:
- 6553
- ISSN:
- 0036-8075
- Page Range / eLocation ID:
- 391 to 392
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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null (Ed.)The relationship between protein motions (i.e., dynamics) and enzymatic function has begun to be explored in β-lactamases as a way to advance our understanding of these proteins. In a recent study, we analyzed the dynamic profiles of TEM-1 (a ubiquitous class A β-lactamase) and several ancestrally reconstructed homologues. A chief finding of this work was that rigid residues that were allosterically coupled to the active site appeared to have profound effects on enzyme function, even when separated from the active site by many angstroms. In the present work, our aim was to further explore the implications of protein dynamics on β-lactamase function by altering the dynamic profile of TEM-1 using computational protein design methods. The Rosetta software suite was used to mutate amino acids surrounding either rigid residues that are highly coupled to the active site or to flexible residues with no apparent communication with the active site. Experimental characterization of ten designed proteins indicated that alteration of residues surrounding rigid, highly coupled residues, substantially affected both enzymatic activity and stability; in contrast, native-like activities and stabilities were maintained when flexible, uncoupled residues, were targeted. Our results provide additional insight into the structure-function relationship present in the TEM family of β-lactamases. Furthermore, the integration of computational protein design methods with analyses of protein dynamics represents a general approach that could be used to extend our understanding of the relationship between dynamics and function in other enzyme classes.more » « less
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Zhang, George (Ed.)Abstract We investigated the flowering plant salicylic acid methyl transferase (SAMT) enzyme lineage to understand the evolution of substrate preference change. Previous studies indicated that a single amino acid replacement to the SAMT active site (H150M) was sufficient to change ancestral enzyme substrate preference from benzoic acid to the structurally similar substrate, salicylic acid (SA). Yet, subsequent studies have shown that the H150M function-changing replacement did not likely occur during the historical episode of enzymatic divergence studied. Therefore, we reinvestigated the origin of SA methylation preference here and additionally assessed the extent to which epistasis may act to limit mutational paths. We found that the SAMT lineage of enzymes acquired preference to methylate SA from an ancestor that preferred to methylate benzoic acid as previously reported. In contrast, we found that a different amino acid replacement, Y267Q, was sufficient to change substrate preference with others providing small positive-magnitude epistatic improvements. We show that the kinetic basis for the ancestral enzymatic change in substate preference by Y267Q appears to be due to both a reduced specificity constant, kcat/KM, for benzoic acid and an improvement in KM for SA. Therefore, this lineage of enzymes appears to have had multiple mutational paths available to achieve the same evolutionary divergence. While the reasons remain unclear for why one path was taken, and the other was not, the mutational distance between ancestral and descendant codons may be a factor.more » « less
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As educators and researchers, we often enjoy enlivening classroom discussions by including examples of cutting-edge high-throughput (HT) technologies that propelled scientific discovery and created repositories of new information. We also call for the use of evidence-based teaching practices to engage students in ways that promote equity and learning. The complex datasets produced by HT approaches can open the doors to discovery of novel genes, drugs, and regulatory networks, so students need experience with the effective design, implementation, and analysis of HT research. Nevertheless, we miss opportunities to contextualize, define, and explain the potential and limitations of HT methods. One evidence-based approach is to engage students in realistic HT case studies. HT cases immerse students with messy data, asking them to critically consider data analysis, experimental design, ethical implications, and HT technologies.The NSF HITS (High-throughput Discovery Science and Inquiry-based Case Studies for Today’s Students) Research Coordination Network in Undergraduate Biology Education seeks to improve student quantitative skills and participation in HT discovery. Researchers and instructors in the network learn about case pedagogy, HT technologies, publicly available datasets, and computational tools. Leveraging this training and interdisciplinary teamwork, HITS participants then create and implement HT cases. Our initial case collection has been used in >15 different courses at a variety of institutions engaging >600 students in HT discovery. We share here our rationale for engaging students in HT science, our HT cases, and network model to encourage other life science educators to join us and further develop and integrate HT complex datasets into curricula.more » « less
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null (Ed.)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 .more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1126/science.abj8346
