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At least 919 records · Page 51

Biosensor for branched-chain amino acid metabolism in yeast and applications in isobutanol and isopentanol production

Abstract Branched-chain amino acid (BCAA) metabolism fulfills numerous physiological roles and can be harnessed to produce valuable chemicals. However, the lack of eukaryotic biosensors specific for BCAA-derived products has limited the ability to develop high-throughput screens for strain engineering and metabolic studies. Here, we harness the transcriptional regulator Leu3p from Saccharomyces cerevisiae to develop a genetically encoded biosensor for BCAA metabolism. In one configuration, we use the biosensor to monitor yeast production of isobutanol, an alcohol derived from valine degradation. Small modifications allow us to redeploy Leu3p in another biosensor configuration that monitors production of the leucine-derived alcohol, isopentanol. These biosensor configurations are effective at isolating high-producing strains and identifying enzymes with enhanced activity from screens for branched-chain higher alcohol (BCHA) biosynthesis in mitochondria as well as cytosol. Furthermore, this biosensor has the potential to assist in metabolic studies involving BCAA pathways, and offers a blueprint to develop biosensors for other products derived from BCAA metabolism.

59 BASIC BIOLOGICAL SCIENCES↗

Systems Engineering of Rhodococcus opacus to Enable Production of Drop-in Fuels from Lignocellulose

Production of drop-in fuels from lignocellulose using Rhodococcus opacus PD630 (hereafter R. opacus) is a challenging goal. During the grant period we have pushed the field forward significantly in several areas of research. Towards the end goal of accelerating the adoption of R. opacus in biofuel production, during the grant period we have expanded the phenotypic characterization of R. opacus grown in single aromatic (model lignocellulosic) compounds or their mixtures, modeling the growth conditions in lignocellulosic biomass. Harnessing the power of adaptive evolution, we produced evolved R. opacus isolates with superior lignin valorization capabilities and identified differentially expressed genes and pathways after adaptation. We used next generation multi-omic techniques such as genomic, transcriptomic, and metabolomic analyses, to identify the catabolic pathways used by R. opacus to degrade aromatic compounds and funnel these degradation products into central metabolism, as well as the aromatic transport genes required for increased tolerance and utilization. Taking this information one step further, we identified endogenous transcription factors and regulatory mechanisms important for degradation of five model aromatic compounds. To accurately estimate R. opacus growth and consumption on model lignin compounds we pioneered the use of novel extraction procedures prior to GC-MS analysis. Alongside 13 C-metabolic flux analysis, we have elucidated the metabolic routes preferred by Rhodococcus opacus during aromatic compound degradation. Finally, we used in tandem lipidomics and high-resolution mass spectrometry to identify the modulation of mycolic acids and phospholipid membrane composition modification as a strategy for aromatic tolerance in R. opacus. Being a non-model organism, R. opacus lacks the breadth of tools and technical foundation which drive biofuel research in more well-understood microbes such as Escherichia coli. To reduce this burden for use, we designed and produced new tools for genomic manipulation and engineering in R. opacus. These engineering breakthroughs support efficient genomic editing, enabling gene overexpression, repression, and genetic alteration. Using these tools, we have generated synthetically engineered strains with increased lipogenesis and growth, both positive traits required for increased lignin valorization. Optimizing engineered strains for biofuel production from lignocellulose requires extremely sophisticated synthetic rewiring of metabolism. To facilitate systems-level reorganization of metabolism in R. opacus, we created a genome-scale model that accurately predicts metabolic flux and growth rates on the aromatic compound phenol. Lignin requires extensive pre-treatment before biological degradation by R. opacus. Towards an eventual goal of degrading real-world lignin, we developed new depolymerization processes to generate lignin breakdown products (LBP). We optimized LBP storage and composition analysis techniques, enabling accurate prediction of specific LBP compound integration into cell wall components. Overall, through the work funded by this grant we generated 20 manuscripts (17 published, 3 in review/preparation), methods for increased accuracy in metabolomics of aromatic compounds, multiple genetic tools for altering the R. opacus genome, genome scale models for predicting flux through metabolic pathways, as well as multi-omic data for community use. The work funded by this grant has increased the knowledge of aromatic degradation in bacteria and advanced our efforts to optimize R. opacus for lignin valorization.

09 BIOMASS FUELS↗

Including Physics-Informed Atomization Constraints in Neural Networks for Reactive Chemistry

Machine learning interatomic potentials (MLIPs) have emerged as powerful tools for investigating atomistic systems with high accuracy and a relatively low computational cost. However, a common and unaddressed challenge with many current neural network (NN) MLIP models is their limited ability to accurately predict the relative energies of systems containing isolated or nearly isolated atoms, which appear in various reactive processes. To address this limitation, we present a mathematical technique for modifying any existing atom-centered NN architecture to account for the energies of isolated atoms. The result produces a consistent prediction of the atomization energy (AE) of a system using minimal constraints on the model. Using this technique, we build a model architecture that we call hierarchically interacting particle neural network (HIP-NN)-AE, an AE-constrained version of the HIP-NN, as well as ANI-AE, the AE-constrained version of the accurate NN engine for molecular energies (ANI). Our results demonstrate AE consistency of AE-constrained models, which drastically improves the AE predictions for the models. We compare the AE-constrained approach to unconstrained models as well as models from the literature in other scenarios, such as bond dissociation energies, bond dissociation pathways, and extensibility tests. These results show that the constraints improve the model performance in some of these tasks and do not negatively affect the performance on any tasks. The AE constraint approach thus offers a robust solution to the challenges posed by isolated atoms in energy prediction tasks.

74 ATOMIC AND MOLECULAR PHYSICS↗

Chemical Vapor Transformation of Lithium Metal: Mechanism and Enhanced Stability

Constructing a stable solid electrolyte interface (SEI) with high productivity and scalability is essential for the practical application of thin Li metal anodes. Here, in this work, we report a chemical vapor transformation (CVT) strategy in which Li metal is exposed to trimethylaluminum (TMA), inducing a rapid and spontaneous surface reaction that forms a robust, multilayered SEI. In situ quartz crystal microbalance (QCM) and quadrupole mass spectrometry (QMS), combined with ex situ X-ray photoelectron spectroscopy (XPS), UV Raman spectroscopy, and density functional theory (DFT) calculations, reveal that TMA removes the native passivation layer, reacts with Li metal, and drives a coupled bulk-surface transformation involving Li–Al interdiffusion. The resulting SEI exhibits a chemically graded structure consisting of an inner Li–Al alloy and an outer amorphous carbon layer formed via demethylation and ligand-exchange pathways. This modified surface exhibits significantly enhanced stability compared to that of bare Li in electrochemical cycling using liquid and solid-state electrolytes. This work unveils a unique surface-mediated bulk transformation mechanism for lithium metal and establishes CVT as a scalable and fundamentally distinct approach for the interfacial engineering of reactive metals.

Li metal↗

Photostability of Ambient-Processed, Conjugated Polymer Electrochromic Devices Encapsulated by Bioderived Barrier Films

Polymer-based electrochromic devices (ECDs) are a promising technology for enabling low-voltage, disposable displays, yet are currently limited by photo-oxidative bleaching of the active materials. Here, renewable barrier films composed of cellulose and chitin are presented as an alternative to poly(ethylene terephthalate) (PET) for encapsulating ECDs. To assess barrier film effectiveness, lateral ECDs composed of poly(3,4-propylenedioxythiophene-(CH 2 OEtHx) 2 ) (P(ProDOT)) active layers were constructed and encapsulated with a multilayer barrier consisting of chitin nanofibers and cellulose nanocrystals spray cast onto a cellulose acetate substrate (oxygen transmission rate (OTR) = 29 cm 3 m –2 day –1 ), a commercially available PET film (OTR = 8.5 cm 3 m –2 day –1 ), and a high-performance PET-Al 2 O 3 multilayer barrier film (OTR < 1 cm 3 m –2 day –1 ). The photodegradation of the P(ProDOT) active layer was determined by measuring the evolution of the colorimetric contrast (ΔE*) and switching speeds as a function of light exposure (100 mW cm –2 , AM 1.5 G light). Photodegradation was found to proceed at a similar rate for all encapsulated devices (roughly 10 times more slowly than unencapsulated devices), highlighting the opportunity for replacing petroleum packaging with bioderived barrier films. Analysis of the switching kinetics, the shifts in optical absorbance, and evidence of chemical degradation indicate that both photochemical breakdown of the electrolyte and cross-linking of the P(ProDOT) active material are key drivers for loss of device performance when oxygen flux to the active material is limited. Furthermore, pathways toward better understanding photodegradation are then proposed with sustainability in mind for future ECD design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Achieving strength-ductility synergy in hierarchical aluminum metal matrix composites via friction extrusion

We report the fabrication of aluminum metal matrix composites (Al-MMCs) with hierarchical architectures via friction extrusion (FE), a scalable, single-step, solid-phase processing technique. Precursor pucks containing 0–15 vol% Al₂O₃ particles were extruded into fully dense AA6061-based composite rods. The FE induced a tree-ring-like architecture of concentric particle-rich and particle-lean bands, yielding refined grains in particle-rich regions and coarser grains elsewhere. At the nanoscale, magnesium in AA6061 selectively reacted with Al₂O₃ particles to form virus-like nodes, improving particle–matrix bonding. This multi-scale design strategy, combining mesoscale architecture, microscale grain refinement, and nanoscale interface engineering overcome the conventional strength–ductility trade-off. Tensile testing showed substantial increases in yield and ultimate tensile strengths while retaining high ductility ( > 20%). Enhanced strain hardening, driven by the accumulation of geometrically necessary dislocations at interfaces, contributed to the performance. The hierarchical microstructure produced by FE demonstrates a promising pathway for scalable fabrication of lightweight MMCs for structural applications requiring a combined high strength and ductility.

Kalsar, Rajib [Pacific Northwest National Laborato↗

Technoeconomic Cost Analysis of NREL Concentrating Solar Power Gen3 Liquid Pathway

The National Renewable Energy Laboratory is leading the liquid (molten salt) power tower pathway for the U.S. Department of Energy's concentrating solar power Gen3 initiative. The Gen3 liquid pathway required updated designs to three major components: the tower and receiver, the thermal energy storage tanks, and the power cycle. We assume a 100 MWe net system output and used the System Advisor Model (SAM) to complete a technoeconomic cost analysis of the Gen3 liquid pathway design and estimate its levelized cost of electricity. This paper summarizes the methodology and results of that analysis.

chloride salt↗

Enhanced Resistance Pines for Improved Renewable Biofuel and Chemical Production (Technical Report)

We completed phenotyping constitutive and inducible oleoresin flow across two seasons, constitutive resin canal number and density and wood terpene content in our ADEPT2 and CCLONES populations. We completed genetic association between 19 oleoresin phenotypes and a total of 523,192 SNP markers from ADEPT2 and 13,883 SNP markers in CCLONES using four mixed linear models. A total of 293 significant SNPs (FDR = 0.20) were identified. We used the MENTOR tool to mine mechanistic connections from a multiplex network constructed from poplar multi-omic data to construct a conceptual model for a subset of these significant SNPs. Our model contains 6 transcriptional regulators in addition to 3 monoterpene synthases. To generate more lines of evidence for these significant SNPs, we completed a time course RNAseq experiment after inducing vascular zone cells to differentiate into new resin canals with a methyl jasmonate treatment, a single nuclei RNAseq that identified differentiating resin canal epithelial cells and are completing analysis for a QTL study in a hybrid pine population. The time course identified 4634 significantly down and 1890 significantly up regulated transcripts after treatment with methyl jasmonate, an inducer of new resin canal formation in the vascular cambial meristem. To analyze this large set of differentially regulated genes, we created a predictive expression network and analyzed it with random walk restart using 6 seed genes coding for transcription factors regulating xylem differentiation in poplar. Of the top ranked 200 transcripts, 119 transcripts were significant differentially expressed supporting these transcripts as potential candidates regulating resin canal formation. Analysis of single nuclei sequencing of shoot tips that contain differentiating resin canals, identified 10 clusters. One cluster was highly enriched in transcripts coding for 9 of the enzymes in the MEP pathway 3 prenyl synthetases, and 3 monoterpene synthases strongly suggesting that this cluster represents resin canal epithelial cells. We are mining the additional transcripts to create a trajectory analysis. In summary, we have identified > 10 novel genes that are strongly supported candidates for further analysis in breeding lines and for genetic engineering over- and under- expressing lines to increase wood terpene content to improve resistance to insect and fungal pathogens while simultaneously increasing terpene supplies for renewable chemicals and biofuels.

59 BASIC BIOLOGICAL SCIENCES↗

Characterization of the Aerosol Source Term in Dry Storage Canisters

As long-term dry storage of used nuclear fuel at independent spent fuel storage installations (ISFSI) trends toward the de facto back end of the US fuel cycle, it becomes appropriate to investigate potential degradation and dispersion scenarios for suitable risk mitigation purposes. Pitting and subsequent stress corrosion cracking of the canister wall is currently viewed as a potential scenario leading to a through-wall pathway for contamination to be transferred from within the storage container to the surrounding environment. While stress corrosion cracking measurements are currently underway to further characterize this scenario, a parallel effort endeavors to perform a consequence analysis of conditions in which through wall cracks are indeed formed. This effort consists of engineering scale modeling using the GOTHIC and MELCOR software packages along with experimental depletion and penetration tests.

spent fuel storage, aerosol deposition, Stress Cor↗

Promoting Fast Ion Conduction in Li-Argyrodite through Lithium Sublattice Engineering

Fundamental understanding of ionic transport plays a pivotal role in designing and optimizing fast ionic conductors. Here, through a systematic neutron scattering and theoretical investigation, we discovered new insights about how anion sublattice affects Li + distribution and transport in Li-argyrodite. We found that the promotion of Li + conductivities is strongly correlated with a previously overlooked Li + interstitial site (16e), which is critical for realizing intercage Li + migration. More isotropic Li + migration pathways with higher Li + occupancies on the interstitial 16e site are found to be the underlying reason for the much higher Li + conductivity in Li 6 PS 5 Cl relative to the Br- and I-based analogues. We further confirm that they are also the universal driving force for the ultrahigh Li + conductivities in both anion-substituted Li-poor (Li 6–a PS 5–a X a, X = Cl and Br) and cation-substituted Li-rich argyrodite (e.g., Li 6+a GeaP 1–a S 5 I and Li 6+a SiaSb 1–a S 5 I). In conclusion, it is expected this strategy can be generally adopted to improve the ionic conductivity of the broad family of Li-rich argyrodite and beyond.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Engineering an increase in ethanol production by altering cofactor specificity

The present invention provides for the manipulation of cofactor usage in a recombinant host cell to increase the formation of desirable products. In some embodiments, the invention provides for a recombinant microorganism comprising a mutation in one or more native enzymes such that their cofactor specificity is altered in such a way that overall cofactor usage in the cell is balanced for a specified pathway and there is an increase in a specific product formation within the cell. In some embodiments, endogenous enzymes are replaced by enzymes with an alternate cofactor specificity from a different species.

09 BIOMASS FUELS↗

Learning Nonlinear Reduced Models from Data with Operator Inference

This review discusses Operator Inference, a nonintrusive reduced modeling approach that incorporates physical governing equations by defining a structured polynomial form for the reduced model, and then learns the corresponding reduced operators from simulated training data. The polynomial model form of Operator Inference is sufficiently expressive to cover a wide range of nonlinear dynamics found in fluid mechanics and other fields of science and engineering, while still providing efficient reduced model computations. The learning steps of Operator Inference are rooted in classical projection-based model reduction; thus, some of the rich theory of model reduction can be applied to models learned with Operator Inference. This connection to projection-based model reduction theory offers a pathway toward deriving error estimates and gaining insights to improve predictions. Furthermore, through formulations of Operator Inference that preserve Hamiltonian and other structures, important physical properties such as energy conservation can be guaranteed in the predictions of the reduced model beyond the training horizon. This review illustrates key computational steps of Operator Inference through a large-scale combustion example.

Mechanics↗

raogroupuiuc/lipo11557_growth

Project: Systems analysis of Lipomyces starkeyi during growth on various plant-based sugars Authors: Anshu Deewan*, Jing-Jing Liu*, Sujit Sadashiv Jagtap, Eun Ju Yun, Hanna E Walukiewicz, Yong-Su Jin, Christopher V Rao (* - co-authors) Abstract : Oleaginous yeasts have received significant attention due to their substantial lipids storage capability. The accumulated lipids can be utilized directly or processed into various bioproducts and biofuels. Lipomyces starkeyi is an oleaginous yeast capable of using multiple plant-based sugars, such as glucose, xylose, and cellobiose. It is, however, a relatively unexplored yeast due to limited knowledge about its physiology. In this study, we have evaluated the growth of L. starkeyi on different sugars and performed transcriptomic and metabolomic analyses to understand the underlying mechanisms of sugar metabolism. Principal component analysis showed clear differences resulting from growth on different sugars. We have further reported various metabolic pathways activated during growth on these sugars. We also observed non-specific regulation in L. starkeyi and have updated the gene annotations for the NRRL Y-11557 strain. This analysis provides a foundation for understanding the metabolism of these plant-based sugars and potentially valuable information to guide the metabolic engineering of L. starkeyi to produce bioproducts and biofuels.

Deewan, Anshu↗

Data for System Analysis of Lipomyces starkeyi During Growth on Various Plant‑Based Sugars

Oleaginous yeasts have received significant attention due to their substantial lipid storage capability. The accumulated lipids can be utilized directly or processed into various bioproducts and biofuels. Lipomyces starkeyi is an oleaginous yeast capable of using multiple plant-based sugars, such as glucose, xylose, and cellobiose. It is, however, a relatively unexplored yeast due to limited knowledge about its physiology. In this study, we have evaluated the growth of L. starkeyi on different sugars and performed transcriptomic and metabolomic analyses to understand the underlying mechanisms of sugar metabolism. Principal component analysis showed clear differences resulting from growth on different sugars. We have further reported various metabolic pathways activated during growth on these sugars. We also observed non-specific regulation in L. starkeyi and have updated the gene annotations for the NRRL Y-11557 strain. This analysis provides a foundation for understanding the metabolism of these plant-based sugars and potentially valuable information to guide the metabolic engineering of L. starkeyi to produce bioproducts and biofuels.

Conversion↗

Initial Assessment of TeF 6 Adsorption

Research and development that supports the management of off-gases from nuclear fuel reprocessing has historically been focused on the off-gas streams that arise from aqueous reprocessing technology. However, as Gen-IV reactor development pathways move toward deployment, alternative spent nuclear fuel (SNF) processing and disposition pathways have been considered more actively. This work is focused upon aspects of fluoride volatility (FV) processing. The versatility of this method for deployment against multiple types of spent fuel encourages the continued advancement of both the primary separations processes and the secondary processes, including waste treatment, material control and accountability, and engineering designs. Recent work noted that TeF 6 , the most highly volatile fluorinated compound produced during FV processing, did not have a clear abatement technology recommended in the literature. Thus, this work performed scoping tests on activated alumina and copper shot to assess whether they could be used to remove TeF 6 from gas streams that bear F 2 . Previous work on this topic was not well described in the literature and was not performed with excess F 2 in the stream as would be typical of spent fuel processing via FV. To support an understanding of the concentration of TeF 6 contacting the adsorbent beds, a series of preliminary testing identified the TeF 6 production rate and the equilibrium concentration of TeF 6 in the gas stream contacting the adsorbent. Excess F 2 was determined to not affect the ability of activated alumina to remove TeF 6 from the gas stream quickly and completely. A determination of whether excess F 2 affected the distribution depth of Te in the sorbent bed is still pending analysis of the used sorbent. Literature suggests that when activated alumina is near saturation, TeF 6 could migrate from the sorbent bed. Future testing should investigate this possibility. Copper metal did not adsorb TeF 6 in the presence of F 2 across the sorbent temperature range of 50 to 335°C. F 2 was fully removed by the copper bed. Although preliminary thermodynamics would indicate adsorption to be energetically favorable, other factors that impact adsorption (e.g., slow kinetics, excess fluorine on the copper surface, an unfavorable transition state) are likely preventing the adsorption of TeF 6 at an easily measurable rate. The work also investigated TeF 6 production from multiple forms of Te in the temperature range of 100 to 250°C. No previous study had assessed the initial reaction rates for this process. A carefully designed study allowed determination of the activation energy for the production of TeF 6 from Te metal. The substantial amount of data collected during this study merits analysis beyond what is described here. A more in-depth kinetic analysis will be pursued. Additional analytical results will provide the ability to benchmark adsorption coefficients for TeF 6 , understand the distribution of TeF 6 within the alumina bed, and better understand the effect of F 2 partial pressure on Te fluorination. The data from this report, as supplemented by these additional analyses, will be submitted to a peer-reviewed journal.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Doping of Cr in Graphene Using Electron Beam Manipulation for Functional Defect Engineering

Chromium atoms in graphene have been proposed to exhibit magnetic moments and spin-selective conducting states depending on the local bonding geometry within the graphene structure, which could lead to interesting applications in spintronics. Despite this interest, there are few direct experimental reports of Cr dopants in graphene even though it is theorized to be stable. Here, we demonstrate the introduction of single Cr dopant atoms into the graphene lattice and onto graphene edges through the controlled use of a focused electron beam in a scanning transmission electron microscope. Here, we show local control of doping locations, and when coupled with targeted in situ milling during scanning of the e-beam, these strategies demonstrate an important component of the fabrication of tailored nanostructured devices in the electron microscope. The approach is validated with first-principles calculations to understand synthesis pathways during fabrication and reveal the energetics and local properties of Cr atoms embedded in graphene; for example, Cr doping can convert graphene into a magnetic and semiconducting material, which suggests Cr-doped graphene can be used as a building block for potential electronic devices and a means to construct them.

36 MATERIALS SCIENCE↗

Electro-strengthening of the additively manufactured Ti–6Al–4V alloy

Structure-property-processing relationship has been studied in additively manufactured Ti–6Al–4V alloy. The processing was performed using in-situ electron microscope (EM) at a moderate current density of 5 × 105 A/cm2 applied for 5 min, and by suppressing Joule heating with massive heat sinks such that the temperature rise was <180 °C and the mechanical properties were not compromised. Overall, the results show that while the grain size increased by ~15%, the nanohardness increased by 16%. This is attributed to the pronounced dislocation generation, regeneration, and clustering as well as defect healing. Ultimately, there is a reduction in the residual strain and a significant increase in the intrinsic strength as evidenced by the high Taylor factor of the electric current processed specimen. This novel processing technique represents an alternative pathway for active controlling of microstructure and internal defects for parts that might be sensitive to high-temperature processing or conventional methods.

36 MATERIALS SCIENCE↗