Gregory D. Friedland

Optimization of a heterologous mevalonate pathway through the use of variant HMG-CoA reductases

Expression of foreign pathways often results in suboptimal performance due to unintended factors such as introduction of toxic metabolites, cofactor imbalances or poor expression of pathway components. In this study we report a 120% improvement in the production of the isoprenoid-derived sesquiterpene, amorphadiene, produced by an engineered strain of Escherichia coli developed to express the native seven-gene mevalonate pathway from Saccharomyces cerevisiae (Martin et al. 2003). This substantial improvement was made by varying only a single component of the pathway (HMG-CoA reductase) and subsequent host optimization to improve cofactor availability. We characterized and tested five variant HMG-CoA reductases obtained from publicly available genome databases with differing kinetic properties and cofactor requirements. The results of our in vitro and in vivo analyses of these enzymes implicate substrate inhibition of mevalonate kinase as an important factor in optimization of the engineered mevalonate pathway. Consequently, the NADH-dependent HMG-CoA reductase from Delftia acidovorans, which appeared to have the optimal kinetic parameters to balance HMG-CoA levels below the cellular toxicity threshold of E. coli and those of mevalonate below inhibitory concentrations for mevalonate kinase, was identified as the best producer for amorphadiene (54% improvement over the native pathway enzyme, resulting in 2.5mM or 520 mg/L of amorphadiene after 48 h). We further enhanced performance of the strain bearing the D. acidovorans HMG-CoA reductase by increasing the intracellular levels of its preferred cofactor (NADH) using a NAD(+)-dependent formate dehydrogenase from Candida boidinii, along with formate supplementation. This resulted in an overall improvement of the system by 120% resulting in 3.5mM or 700 mg/L amorphadiene after 48 h of fermentation. This comprehensive study incorporated analysis of several key parameters for metabolic design such as in vitro and in vivo kinetic performance of variant enzymes, intracellular levels of protein expression, in-pathway substrate inhibition and cofactor management to enable the observed improvements. These metrics may be applied to a broad range of heterologous pathways for improving the production of biologically derived compounds.

A Ras-induced conformational switch in the Ras activator Son of sevenless

The Ras-specific guanine nucleotide-exchange factors Son of sevenless (Sos) and Ras guanine nucleotide-releasing factor 1 (RasGRF1) transduce extracellular stimuli into Ras activation by catalyzing the exchange of Ras-bound GDP for GTP. A truncated form of RasGRF1 containing only the core catalytic Cdc25 domain is sufficient for stimulating Ras nucleotide exchange, whereas the isolated Cdc25 domain of Sos is inactive. At a site distal to the catalytic site, nucleotide-bound Ras binds to Sos, making contacts with the Cdc25 domain and with a Ras exchanger motif (Rem) domain. This allosteric Ras binding stimulates nucleotide exchange by Sos, but the mechanism by which this stimulation occurs has not been defined. We present a crystal structure of the Rem and Cdc25 domains of Sos determined at 2.0-Å resolution in the absence of Ras. Differences between this structure and that of Sos bound to two Ras molecules show that allosteric activation of Sos by Ras occurs through a rotation of the Rem domain that is coupled to a rotation of a helical hairpin at the Sos catalytic site. This motion relieves steric occlusion of the catalytic site, allowing substrate Ras binding and nucleotide exchange. A structure of the isolated RasGRF1 Cdc25 domain determined at 2.2-Å resolution, combined with computational analyses, suggests that the Cdc25 domain of RasGRF1 is able to maintain an active conformation in isolation because the helical hairpin has strengthened interactions with the Cdc25 domain core. These results indicate that RasGRF1 lacks the allosteric activation switch that is crucial for Sos activity.

A correspondence between solution-state dynamics of an individual protein and the sequence and conformational diversity of its family.

Conformational ensembles are increasingly recognized as a useful representation to describe fundamental relationships between protein structure, dynamics and function. Here we present an ensemble of ubiquitin in solution that is created by sampling conformational space without experimental information using “Backrub” motions inspired by alternative conformations observed in sub-Angstrom resolution crystal structures. Backrub-generated structures are then selected to produce an ensemble that optimizes agreement with nuclear magnetic resonance (NMR) Residual Dipolar Couplings (RDCs). Using this ensemble, we probe two proposed relationships between properties of protein ensembles: (i) a link between native-state dynamics and the conformational heterogeneity observed in crystal structures, and (ii) a relation between dynamics of an individual protein and the conformational variability explored by its natural family. We show that the Backrub motional mechanism can simultaneously explore protein native-state dynamics measured by RDCs, encompass the conformational variability present in ubiquitin complex structures and facilitate sampling of conformational and sequence variability matching those occurring in the ubiquitin protein family. Our results thus support an overall relation between protein dynamics and conformational changes enabling sequence changes in evolution. More practically, the presented method can be applied to improve protein design predictions by accounting for intrinsic native-state dynamics.

A simple model of backbone flexibility improves modeling of side-chain conformational variability

The considerable flexibility of side-chains in folded proteins is important for protein stability and function, and may have a role in mediating allosteric interactions. While sampling side-chain degrees of freedom has been an integral part of several successful computational protein design methods, the predictions of these approaches have not been directly compared to experimental measurements of side-chain motional amplitudes. In addition, protein design methods frequently keep the backbone fixed, an approximation that may substantially limit the ability to accurately model side-chain flexibility. Here, we describe a Monte Carlo approach to modeling side-chain conformational variability and validate our method against a large dataset of methyl relaxation order parameters derived from nuclear magnetic resonance (NMR) experiments (17 proteins and a total of 530 data points). We also evaluate a model of backbone flexibility based on Backrub motions, a type of conformational change frequently observed in ultra-high-resolution X-ray structures that accounts for correlated side-chain backbone movements. The fixed-backbone model performs reasonably well with an overall rmsd between computed and predicted side-chain order parameters of 0.26. Notably, including backbone flexibility leads to significant improvements in modeling side-chain order parameters for ten of the 17 proteins in the set. Greater accuracy of the flexible backbone model results from both increases and decreases in side-chain flexibility relative to the fixed-backbone model. This simple flexible-backbone model should be useful for a variety of protein design applications, including improved modeling of protein-protein interactions, design of proteins with desired flexibility or rigidity, and prediction of correlated motions within proteins.

Biochemical and structural studies of NADH-dependent FabG used to increase the bacterial production of fatty acids under anaerobic conditions.

ABSTRACT Major efforts in bioenergy research have focused on producing fuels that can directly replace petroleum-derived gasoline and diesel fuel through metabolic engineering of microbial fatty acid biosynthetic pathways. Typically, growth and pathway induction are conducted under aerobic conditions, but for operational efficiency in an industrial context, anaerobic culture conditions would be preferred to obviate the need to maintain specific dissolved oxygen concentrations and to maximize the proportion of reducing equivalents directed to biofuel biosynthesis rather than ATP production. A major concern with fermentative growth conditions is elevated NADH levels, which can adversely affect cell physiology. The purpose of this study was to identify homologs of Escherichia coli FabG, an essential reductase involved in fatty acid biosynthesis, that display a higher preference for NADH than for NADPH as a cofactor. Four potential NADH-dependent FabG variants were identified through bioinformatic analyses supported by crystallographic structure determination (1.3- to 2.0-Å resolution). In vitro assays of cofactor (NADH/NADPH) preference in the four variants showed up to ∼35-fold preference for NADH, which was observed with the Cupriavidus taiwanensis FabG variant. In addition, FabG homologs were overexpressed in fatty acid- and methyl ketone-overproducing E. coli host strains under anaerobic conditions, and the C. taiwanensis variant led to a 60% higher free fatty acid titer and 75% higher methyl ketone titer relative to the titers of the control strains. With further engineering, this work could serve as a starting point for establishing a microbial host strain for production of fatty acid-derived biofuels (e.g., methyl ketones) under anaerobic conditions.

Designing ensembles in conformational and sequence space to characterize and engineer proteins.

Computational protein design - the search for amino acids that adopt defined structures and functions - has achieved significant successes in recent years. Design is often approached from the perspective of targeting the design objective one structure-sequence pair at a time. Here we summarize studies that take an alternate approach, considering design solutions from the perspective of conformational and sequence ensembles. We argue that this strategy both more closely mimics the properties of naturally occurring proteins and drives progress in engineering. We discuss benchmarks for evaluating design methods, highlight recent advances, and project how the evolving capabilities of gene sequencing, gene synthesis, and genome editing may change the design field.

Tracing Determinants of Dual Substrate Specificity in Glycoside Hydrolase Family 5

Background: Glycoside hydrolase family 5 (GH5) comprises enzymes with a wide range of activities critical for the deconstruction of lignocellulose. Results: Concurrent glucan and mannan specificity in over 70 members of GH5 can be ascribed to a conserved active site motif. Conclusion: Single domain multispecific hydrolases are widely prevalent. Significance: This finding has potential applications in improved enzyme mixture design or microbes engineered for consolidated bioprocessing of lignocellulose. Enzymes are traditionally viewed as having exquisite substrate specificity; however, recent evidence supports the notion that many enzymes have evolved activities against a range of substrates. The diversity of activities across glycoside hydrolase family 5 (GH5) suggests that this family of enzymes may contain numerous members with activities on multiple substrates. In this study, we combined structure- and sequence-based phylogenetic analysis with biochemical characterization to survey the prevalence of dual specificity for glucan- and mannan-based substrates in the GH5 family. Examination of amino acid profile differences between the subfamilies led to the identification and subsequent experimental confirmation of an active site motif indicative of dual specificity. The motif enabled us to successfully discover several new dually specific members of GH5, and this pattern is present in over 70 other enzymes, strongly suggesting that dual endoglucanase-mannanase activity is widespread in this family. In addition, reinstatement of the conserved motif in a wild type member of GH5 enhanced its catalytic efficiency on glucan and mannan substrates by 175 and 1,600%, respectively. Phylogenetic examination of other GH families further indicates that the prevalence of enzyme multispecificity in GHs may be greater than has been experimentally characterized. Single domain multispecific GHs may be exploited for developing improved enzyme cocktails or facile engineering of microbial hosts for consolidated bioprocessing of lignocellulose.

Phylogenomically Guided Identification of Industrially Relevant GH1 β-Glucosidases through DNA Synthesis and Nanostructure-Initiator Mass Spectrometry

Harnessing the biotechnological potential of the large number of proteins available in sequence databases requires scalable methods for functional characterization. Here we propose a workflow to address this challenge by combining phylogenomic guided DNA synthesis with high-throughput mass spectrometry and apply it to the systematic characterization of GH1 β-glucosidases, a family of enzymes necessary for biomass hydrolysis, an important step in the conversion of lignocellulosic feedstocks to fuels and chemicals. We synthesized and expressed 175 GH1s, selected from over 2000 candidate sequences to cover maximum sequence diversity. These enzymes were functionally characterized over a range of temperatures and pHs using nanostructure-initiator mass spectrometry (NIMS), generating over 10,000 data points. When combined with HPLC-based sugar profiling, we observed GH1 enzymes active over a broad temperature range and toward many different β-linked disaccharides. For some GH1s we also observed activity toward laminarin, a more complex oligosaccharide present as a major component of macroalgae. An area of particular interest was the identification of GH1 enzymes compatible with the ionic liquid 1-ethyl-3-methylimidazolium acetate ([C2mim][OAc]), a next-generation biomass pretreatment technology. We thus searched for GH1 enzymes active at 70 °C and 20% (v/v) [C2mim][OAc] over the course of a 24-h saccharification reaction. Using our unbiased approach, we identified multiple enzymes of different phylogentic origin with such activities. Our approach of characterizing sequence diversity through targeted gene synthesis coupled to high-throughput screening technologies is a broadly applicable paradigm for a wide range of biological problems.

Differences in Flexibility Underlie Functional Differences in the Ras Activators Son of Sevenless and Ras Guanine Nucleotide Releasing Factor 1

The Ras-specific nucleotide exchange factor Son of sevenless (Sos) is inactive without Ras bound to a distal allosteric site. In contrast, the catalytic domain of Ras guanine nucleotide releasing factor 1 (RasGRF1) is active intrinsically. By substituting residues from RasGRF1 into Sos, we have generated mutants of Sos with basal activity, partially relieved of their dependence on allosteric activation. We have performed molecular dynamics simulations showing how Ras binding to the allosteric site leads to a bias toward the active conformation of Sos. The trajectories show that Sos fluctuates between active and inactive conformations in the absence of Ras and that the activating mutations favor conformations of Sos that are more permissive to Ras binding at the catalytic site. In contrast, unliganded RasGRF1 fluctuates primarily among active conformations. Our results support the premise that the catalytic domain of Sos has evolved an allosteric activation mechanism that extends beyond the simple process of membrane recruitment.