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At least 37 records · Page 2

Data for "Metabolic Engineering Strategies to Produce Medium-Chain Oleochemicals via Acyl-ACP:CoA Transacylase Activity"

Microbial lipid metabolism is an attractive route for producing oleochemicals. The predominant strategy centers on heterologous thioesterases to synthesize desired chain-length fatty acids. To convert acids to oleochemicals (e.g., fatty alcohols, ketones), the narrowed fatty acid pool needs to be reactivated as coenzyme A thioesters at cost of one ATP per reactivation – an expense that could be saved if the acyl-chain was directly transferred from ACP- to CoA-thioester. Here, we demonstrate such an alternative acyl-transferase strategy by heterologous expression of PhaG, an enzyme first identified in Pseudomonads, that transfers 3-hydroxy acyl-chains between acyl-carrier protein and coenzyme A thioester forms for creating polyhydroxyalkanoate monomers. We use it to create a pool of acyl-CoA’s that can be redirected to oleochemical products. Through bioprospecting, mutagenesis, and metabolic engineering, we develop three strains of Escherichia coli capable of producing over 1 g/L of medium-chain free fatty acids, fatty alcohols, and methyl ketones.

Bioproducts↗

Small Changes With Big Consequences: Swapping Two Atoms In Side Chains Changes Phenylene‐Ethynylene Packing And Fluorescence

Abstract Engineering the properties of conjugated materials in the solid state is an unsolved, ongoing challenge important to fundamental understanding of how non‐covalent interactions dictate packing and key properties, as well as the development of technologies based in organic optoelectronics. The most common design paradigm of such materials divide them into a “main chain” with extended conjugation, the chemical structure of which determines optoelectronic properties, and “side chains” not conjugated to the backbone, which provide solubility when they are long alkyl chains. This paper describes comparisons between phenylene‐ethynylene molecules in which slight changes to the structure of “side chains”—swapping hydrogen and fluorine atomic position on an aromatic ring—results in unexpectedly large changes in the solid‐state optical properties. In a pair of anisyl‐terminated three‐ring phenylene‐ethynylenes, switching the side chain arenes of benzyl esters from 2,4,6‐trifluoro to 2,3,6‐trifluoro results in a shift in fluorescence emission spectra of over 100 nm, as well as the opposite direction of force‐induced shifting of emission. Through a combination X‐ray crystal structures, electronic structure calculations, and comparisons with other derivatives, we describe how the 2,4,6‐trifluorinated side chains yield cofacial fluoroarene‐arene stacking interactions that twist the PE backbone out of conjugation, while the 2,3,6‐trifluoro side chains do not stack, instead yielding more coplanar PE backbones that form intermolecular aggregates. Overall, this work demonstrates how slight modifications to parts of conjugated materials normally considered ancillary to optoelectronic properties can determine their solid‐state properties, epitomizing the challenge of rational design but at the same time offering opportunities for materials discovery and improved understanding of non‐covalent interactions.

Sharber, Seth A.↗

Comparative Study on the Machine Learning-Based Prediction of Adsorption Energies for Ring and Chain Species on Metal Catalyst Surfaces

Computation of adsorption and transition state energies for a large number of surface intermediates for numerous active site models pose significant computational overhead in computational screening of catalysts. Machine learning (ML) techniques can be used to predict part of these energies. To predict the energies, ML models need to be fed appropriate metal and species descriptors. For complex surface chemistries, the structures of the intermediate species can vary greatly. In this paper, working with the hydrodeoxygenation of succinic acid on six different metal surfaces, we have studied the effect of linear and non-linear ML models used along with pen-and-paper based species descriptors and two categories of metal descriptors on two different categories of intermediate species: chain and ring. More specifically, our computations include the prediction of chain species when trained on only chain species and also when trained on both chain and ring species. Similar computations were performed for predictions of ring species. In each case, results of linear ML models were compared with kernel based non-linear models. Our results indicate that ring species data does not improve the prediction of chain species. Similarly, chain species data does not improve the prediction of ring species. The use of non-linear ML models, however, did help to minimize the prediction errors compared to the linear models. Furthermore, the study also shows that electronic or adsorption energy based metal descriptors along with bond count based species fingerprints can achieve a mean absolute error (MAE) of less than 0.2 eV for complex chain molecules when used with an appropriate machine learning model.

Adsorption↗

Demand Shocks and Supply Chain Resilience: An Agent Based Modelling Approach and Application to the Potato Supply Chain

The food supply chain has experienced major disruptions from both demand and supply sides during the COVID-19 pandemic. While some consequences such as food waste are directly caused by the disruption due to supply chain inefficiency, others are indirectly caused by a change in consumer’s preferences. As a result, evaluating food supply chain resilience is a difficult task. With an attempt to understand impacts of demand on the food supply chain, we developed an agent-based model based on the case of Idaho’s potato supply chain. Results showed that not only the magnitude but also the timing of the demand shock will have different impacts on various stakeholders of the supply chain. Our contribution to the literature is twofold. First, the model helps explain why food waste and shortages may occur with dramatic shifts in consumer demand. Second, this paper provides a new angle on evaluating the various mitigation strategies and policy responses to disruptions beyond COVID-19.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Polymer Chain Diffusion in All-Polymer Nanocomposites: Confinement vs Chain Acceleration

All-polymer nanocomposites, in which soft, polymer-based nanoparticles are dispersed in the polymer matrix, have received great interest lately due to their potential use in a range of applications, including drug delivery and self-healing materials. However, the impact of this new class of nanoparticles on the dynamics of a linear polymer matrix in an all-polymer nanocomposite is still largely unknown. In this work, we report that the addition of polystyrene soft nanoparticles accelerates the diffusion of high molecular weight linear PS chains over a range of nanoparticle loadings. Our results show that at nanoparticle loadings below 1%, the diffusion of the linear matrix increases, presumably via a constraint release mechanism. At loadings above 1%, the increase in diffusion is mitigated by confinement effects of the nanoparticles. Thus, the response of these all-polymer nanocomposites is dominated by the balance of entropic confinement of the chain, which slows diffusion and a constraint release mechanism that speeds up the diffusion. However, the diffusion of the linear chain in the all-polymer nanocomposite is faster than that of the same chain in the melt at all loadings, diverging from the behavior of most nanocomposites with hard, impenetrable nanoparticles. Thus, the mechanism that accelerates the chain diffusion dominates in these systems. This behavior is unusual and fundamentally different than what has been reported for nanocomposites with hard inorganic nanoparticles, indicating that new perspectives are needed for these materials where the control of loading can either accelerate or decelerate the dynamics of the matrix in a distinctive manner.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Endoglucanase Peripheral Loops Facilitate Complexation of Glucan Chains on Cellulose via Adaptive Coupling to the Emergent Substrate Structures

We examine how the catalytic domain of a glycoside hydrolase family 7 endoglucanase catalytic domain (Cel7B CD) facilitates complexation of cellulose chains from a crystal surface. With direct relevance to the science of biofuel production, this problem also represents a model system of biopolymer processing by proteins in Nature. Interactions of Cel7B CD with a cellulose microfibril along different paths of complexation are characterized by mapping the atomistic fluctuations recorded in free-energy simulations onto the parameters of a coarse-grain model. The resulting patterns of protein-biopolymer couplings also uncover the sequence signatures of the enzyme in peeling off glucan chains from the microfibril substrate. We show that the semiopen active site of Cel7B CD exhibits similar barriers and free energies of complexation over two distinct routes; namely, scooping of a chain into the active-site cleft and threading from the chain end into the channel. On the other hand, the complexation energetics strongly depends on the surface packing of the targeted chain and the resulting interaction sites with the enzyme. A revealed principle is that Cel7B CD facilitates cellulose deconstruction via adaptive coupling to the emergent substrate. The flexible, peripheral segments of the protein outside of the active-site cleft are able to accommodate the varying features of cellulose along the simulated paths of complexation. The general strategy of linking physics-based molecular interactions to protein sequence could also be helpful in elucidating how other protein machines process biopolymers.

Environmental Molecular Sciences Laboratory↗

High-resolution studies of the Majorana atomic chain platform

Ordered assemblies of magnetic atoms on the surface of conventional superconductors can be used to engineer topological superconducting phases and realize Majorana fermion quasiparticles (MQPs) in a condensed matter setting. Recent experiments have shown that chains of Fe atoms on Pb generically have the required electronic characteristics to form a one-dimensional topological superconductor and have revealed spatially resolved signatures of localized MQPs at the ends of such chains. Here we report higher-resolution measurements of the same atomic chain system performed using a dilution refrigerator scanning tunnelling microscope (STM). With significantly better energy resolution than previous studies, we show that the zero-bias peak (ZBP) in Fe chains has no detectable splitting from hybridization with other states. The measurements also reveal that the ZBP exhibits a distinctive ‘double eye’ spatial pattern on nanometre length scales. Theoretically we show that this is a general consequence of STM measurements of MQPs with substantial spectral weight in the superconducting substrate, a conclusion further supported by measurements of Pb overlayers deposited on top of the Fe chains. Lastly, we report experiments performed with superconducting tips in search of the particle–hole symmetric MQP signature expected in such measurements.

Electronic properties and materials↗

Comparison of several classical density functional theories for the adsorption of flexible chain molecules into cylindrical nanopores

Adsorption of flexible oligomers into narrow cylindrical pores has been studied by means of several versions of classical density functional theory (CDFT) and Monte Carlo simulation. The adsorption process is interesting to study due to the competition between the entropic depletion of oligomers from the pores and the wall–oligomer attraction. It is also challenging to describe using current CDFTs, which tend to overestimate the amount of the adsorbed fluid. From a comparison of several different CDFT approaches, we find that this is due to the assumption of ideal or freely jointed chain conformations. Moreover, it is demonstrated that it is impossible to obtain a reasonable description of the adsorption isotherms without taking into account accurate contact values in the distribution functions describing the structure of the reference monomer fluid. At low densities, more accurate result are obtained in comparison with Monte Carlo simulation data when accurate contact values are incorporated into the theory rather than the more commonly used hard-sphere contact value. However, even the CDFT with accurate contact values still overestimates the amount of the adsorbed fluid due to the ideal or freely jointed chain approximation, used for the description of chain conformations in most CDFT approaches. We find that significant improvement can achieved by employing self-consistent field theory, which samples self-avoiding chain conformations and decreases the number of possible chain conformations, and, consequently, the amount of the adsorbed fluid.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Y-Type Non-Fullerene Acceptors with Outer Branched Side Chains and Inner Cyclohexane Side Chains for 19.36% Efficiency Polymer Solar Cells

Raising the lowest unoccupied molecular orbital (LUMO) energy level of Y-type non-fullerene acceptors can increase the open-circuit voltage (V oc ) and thus the photovoltaic performance of the current top performing polymer solar cells (PSCs). One of the viable routes is demonstrated by the successful Y6 derivative of L8-BO with the branched alkyl chains at the outer side. This will introduce steric hindrance and reduce intermolecular aggregation, thus open up the bandgap and raise the LUMO energy level. To take further advantages of the steric hindrance influence on optoelectronic properties of Y6 derivatives, two Y-type non-fullerene acceptors of BTP-Cy-4F and BTP-Cy-4Cl are designed and synthesized by adopting outer branched side chains and inner cyclohexane side chains. An outstanding V oc of 0.937 V is achieved in the D18:BTP-Cy-4F binary blend devices along with a power conversion efficiency (PCE) of 18.52%. With the addition of BTP-eC9 to extend the absorption spectral coverage, a remarkable PCE of 19.36% is realized finally in the related ternary blend devices, which is one of the highest values for single-junction PSCs at present. The results illustrate the great potential of cyclohexane side chains in constructing high-performance non-fullerene acceptors and their PSCs.

36 MATERIALS SCIENCE↗

Enhancing the Solubility of Semiconducting Polymers in Eco-Friendly Solvents with Carbohydrate-Containing Side Chains

Semiconducting polymers are at the forefront of next-generation organic electronics due to their robust mechanical and optoelectronic properties. However, their extended π-conjugation often leads to materials with low solubilities in common organic solvents, thus requiring processing in high-boiling-point and toxic halogenated solvents to generate thin-film devices. To address this environmental concern, a natural product-inspired side-chain engineering approach was used to incorporate galactose-containing moieties into semiconducting polymers toward improved processability in greener solvents. Novel isoindigo-based polymers with different ratios of galactose-containing side chains were synthesized to improve the solubilities of the organic semiconductors in alcohol-based solvents. The addition of carbohydrate-containing side chains to π-conjugated polymers was found to considerably impact the intermolecular aggregation of the materials and their microstructures in the solid state as confirmed by atomic force microscopy and grazing-incidence wide-angle X-ray scattering. The charge transport characteristics of the new semiconductors were evaluated by the fabrication of organic field-effect transistors prepared from both toxic halogenated and greener alcohol-based solvents. Importantly, the incorporation of carbohydrate-containing side chains was shown to have very little detrimental impact on the electronic properties of the polymer when processed from green solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Understanding the Role of Populus ECERIFERUM2-Likes in the Biosynthesis of Very-Long-Chain Fatty Acids for Cuticular Waxes

Cuticular waxes are derived from very-long-chain fatty acid (VLCFA) precursors made by the concerted action of four enzymes that form the fatty acid (FA) elongation complex. Here, the condensing enzyme of the complex confers specificity to substrates of different chain lengths, yet on its own cannot account for the biosynthesis of VLCFAs longer than 28 carbons (C28). Recent evidence from Arabidopsis thaliana points to a synergistic role of clade II BAHD acyltransferases and condensing enzymes in the elongation of VLCFAs beyond C28. In Populus trichocarpa, clade II is composed of seven uncharacterized paralogous genes (PtCER2-like1–7). In the present study, five of these genes were heterologously expressed in yeast and their respective FA profiles were determined. PtCER2-likes differentially altered the accumulation of C28 and C30 FAs when expressed in the presence of the condensing enzyme AtCER6. Among these, PtCER2-like5 produced the highest levels of C28 FAs in yeast and its expression was localized to the epidermis in β-glucuronidase-reporter poplar lines, consistent with a role in cuticular wax biosynthesis. Complementation of the A. thaliana cer2-5 mutant with PtCER2-like5 increased the levels of C28-derived cuticular waxes at the expense of C30-derived components. Together, these results demonstrate that the role of CER2-likes in cuticular wax biosynthesis is conserved in Populus clade II BAHD acyltransferases.

59 BASIC BIOLOGICAL SCIENCES↗