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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Assessing the impact of substrate-level enzyme regulations limiting ethanol titer in Clostridium thermocellum using a core kinetic model

Clostridium thermocellum is a promising candidate for consolidated bioprocessing because it can directly ferment cellulose to ethanol. Despite significant efforts, achieved yields and titers fall below industrially relevant targets. This implies that there still exist unknown enzymatic, regulatory, and/or possibly thermodynamic bottlenecks that can throttle back metabolic flow. By (i) elucidating internal metabolic fluxes in wild-type C. thermocellum grown on cellobiose via 13 C-metabolic flux analysis ( 13 C-MFA), (ii) parameterizing a core kinetic model, and (iii) subsequently deploying an ensemble-docking workflow for discovering substrate-level regulations, this paper aims to reveal some of these factors and expand our knowledgebase governing C. thermocellum metabolism. Generated 13 C labeling data were used with 13 C-MFA to generate a wild-type flux distribution for the metabolic network. Notably, flux elucidation through MFA alluded to serine generation via the mercaptopyruvate pathway. Using the elucidated flux distributions in conjunction with batch fermentation process yield data for various mutant strains, we constructed a kinetic model of C. thermocellum core metabolism (i.e. k-ctherm138). Subsequently, we used the parameterized kinetic model to explore the effect of removing substrate-level regulations on ethanol yield and titer. Upon exploring all possible simultaneous (up to four) regulation removals we identified combinations that lead to many-fold model predicted improvement in ethanol titer. In addition, by coupling a systematic method for identifying putative competitive inhibitory mechanisms using K-FIT kinetic parameterization with the ensemble-docking workflow, we flagged 67 putative substrate-level inhibition mechanisms across central carbon metabolism supported by both kinetic formalism and docking analysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Metabolic engineering of Synechococcus elongatus 7942 for enhanced sucrose biosynthesis

The capability of cyanobacteria to produce sucrose from CO 2 and light has a remarkable societal and biotechnological impact since sucrose can serve as a carbon and energy source for a variety of heterotrophic organisms and can be converted into value-added products. However, most metabolic engineering efforts have focused on understanding local pathway alterations that drive sucrose biosynthesis and secretion in cyanobacteria rather than analyzing the global flux re-routing that occurs following induction of sucrose production by salt stress. Here, we investigated global metabolic flux alterations in a sucrose-secreting (cscB-overexpressing) strain relative to its wild-type Synechococcus elongatus 7942 parental strain. Here we used targeted metabolomics, 13 C metabolic flux analysis (MFA), and genome-scale modeling (GSM) as complementary approaches to elucidate differences in cellular resource allocation by quantifying metabolic profiles of three cyanobacterial cultures - wild-type S. elongatus 7942 without salt stress (WT), wild-type with salt stress (WT/NaCl), and the cscB-overexpressing strain with salt stress (cscB/NaCl) - all under photoautotrophic conditions. We quantified the substantial rewiring of metabolic fluxes in WT/NaCl and cscB/NaCl cultures relative to WT and identified a metabolic bottleneck limiting carbon fixation and sucrose biosynthesis. This bottleneck was subsequently mitigated through heterologous overexpression of glyceraldehyde-3-phosphate dehydrogenase in an engineered sucrose-secreting strain. Our study also demonstrates that combining 13 C-MFA and GSM is a useful strategy to both extend the coverage of MFA beyond central metabolism and to improve the accuracy of flux predictions provided by GSM.

09 BIOMASS FUELS↗
DOE OSTI2024

Machine-learning-assisted deciphering of microstructural effects on ionic transport in composite materials: A case study of Li 7 La 3 Zr 2 O 12 -LiCoO 2

The effective diffusivity of ionic species in multiphase materials is critical for the design and function of composite materials for electrochemical energy storage. In practice, effective diffusivity depends sensitively not only on the intrinsic diffusivities of constituting materials but also on their topological arrangement; nevertheless, these coupled contributions are oversimplified in most analytical models. Here, we combine atomistically informed mesoscale modeling and machine learning (ML) analysis to unravel how such features affect effective diffusivity in two-phase composites. Using the Li 7 La 3 Zr 2 O 12 -LiCoO 2 composite solid-state battery cathode as a model system, we compute effective diffusivity for 600 distinct dense polycrystalline microstructures with different topological configurations of grains, grain boundaries, and heterointerfaces. We verify that in addition to atomic-scale variabilities, microstructural feature diversity can significantly impact effective transport properties. Across the ensemble of test microstructures, this often results in bimodal distributions of effective diffusivity that encompass two qualitatively distinct operating mechanisms, which we identify via flux analysis. An ML approach reveals that the most critical determining factors for effective diffusivity are the connectivity of bulk phases and their heterointerfaces. The role of ionic mobility at the heterointerfaces is also discussed. These insights highlight the combined importance of microstructure and interface engineering in tuning the transport properties of ionic species in composite materials. In conclusion, our framework can also be extended for understanding generic microstructure-property relationships in other complex multiphase materials.

25 ENERGY STORAGE↗
DOE OSTI2022

Role of carboxysomes in cyanobacterial CO 2 assimilation: CO 2 concentrating mechanisms and metabolon implications

Many carbon-fixing organisms have evolved CO 2 concentrating mechanisms (CCMs) to enhance the delivery of CO 2 to RuBisCO, while minimizing reactions with the competitive inhibitor, molecular O 2 . These distinct types of CCMs have been extensively studied using genetics, biochemistry, cell imaging, mass spectrometry, and metabolic flux analysis. Highlighted in this paper, the cyanobacterial CCM features a bacterial microcompartment (BMC) called ‘carboxysome’ in which RuBisCO is co-encapsulated with the enzyme carbonic anhydrase (CA) within a semi-permeable protein shell. Further, the cyanobacterial CCM is capable of increasing CO 2 around RuBisCO, leading to one of the most efficient processes known for fixing ambient CO 2 . The carboxysome life cycle is dynamic and creates a unique subcellular environment that promotes activity of the Calvin–Benson (CB) cycle. The carboxysome may function within a larger cellular metabolon, physical association of functionally coupled proteins, to enhance metabolite channelling and carbon flux. In light of CCMs, synthetic biology approaches have been used to improve enzyme complex for CO 2 fixations. Research on CCM-associated metabolons has also inspired biologists to engineer multi-step pathways by providing anchoring points for enzyme cascades to channel intermediate metabolites towards valuable products.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Metabolic Pathway Engineering

Modern microbial and enzyme engineering and their advancement are increasingly dependent on the marriage of a wide range of sophisticated technologies. For students entering the field of biotechnology, the outlook is indeed daunting. Expertise at levels beyond that of simple familiarity will be needed to conduct competitive research. It goes without saying that to be competitive, all new researchers in this field will need basic preparation in molecular biology, biochemistry, and genetics. Further, experience working with concepts and experimental tools in enzyme biochemistry and kinetics, gene editing, computational metabolic pathway modeling, experimental pathway flux analysis, and computational clustering tools to process complex data sets will be vital for success. We speculate that most biotechnology researchers in early career at this time will build teams of collaborators to address these disparate science fields rather than attempt to become experts in one lab.

BASIC BIOLOGICAL SCIENCES,BIOMASS FUELS↗
DOE OSTI2026

Acetate-based biological platforms: Bridging carbon dioxide utilization and high-value bioproduct production in oleaginous yeasts

Acetate is emerging as a promising two-carbon substrate in the circular bioeconomy, bridging the gap between single-carbon sources and high-value biofuels and bioproducts. This review examines the key pathways for acetate production, including the electrochemical reduction of carbon dioxide, syngas fermentation, and biological acetogenesis. It focuses on acetate metabolism in oleaginous yeasts, such as Yarrowia lipolytica and Rhodotorula toruloides, which efficiently convert acetate-derived acetyl-CoA units into diverse bioproducts such as lipids, fatty alcohols, triacetic acid lactone, and carotenoids. Recent advances in metabolic engineering, transcriptomics, and metabolic flux analysis have improved the understanding of acetate assimilation in these organisms, thereby increasing their potential for industrial applications. In addition, the feasibility of a biological gas-to-liquid platform that utilizes acetate as a central intermediate for scalable biomanufacturing is discussed. Integrating acetate utilization with sustainable production strategies offers a promising path to advance the bio-based economy. Using acetate as a versatile metabolic intermediate enables the conversion of industrial emissions into biofuels and bioproducts while avoiding the energetic and toxicity constraints associated with direct fermentation of gaseous substrates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The bright frontiers of microbial metabolic optogenetics

In recent years, light-responsive systems from the field of optogenetics have been applied to several areas of metabolic engineering with remarkable success. By taking advantage of light's high tunability, reversibility, and orthogonality to host endogenous processes, optogenetic systems have enabled unprecedented dynamical controls of microbial fermentations for chemical production, metabolic flux analysis, and population compositions in co-cultures. In this article, we share our opinions on the current state of this new field of metabolic optogenetics. Furthermore, we make the case that it will continue to impact metabolic engineering in increasingly new directions, with the potential to challenge existing paradigms for metabolic pathway and strain optimization as well as bioreactor operation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

An experimental and kinetic modeling study of the ignition of 2-methyl decane

Ignition delay times (IDTs) of 2-methyl decane (C 11 H 24 -2) are measured in a high-pressure shock tube and in a rapid compression machine at equivalence ratios in the range 0.5–2.0 at 90 % dilution, at temperatures in the range 600–1430 K and at pressures of 15 and 30 bar. To clarify the effect of the branched methyl group on fuel oxidation, IDTs of n-undecane (nC 11 H 24 ) are also measured at similar conditions to those measured for C 11 H 24 -2. A new chemical kinetic mechanism, using C3MechV4.0.1 as the core chemistry, is developed and validated against the new experimental data. The thermodynamic properties of the fuel (RH), alkyl (Ṙ), alkyl peroxy (RȮ 2 ), hydroperoxy-alkyl (Q̇OOH), and peroxy hydroperoxy alkyl (Ȯ 2 QOOH) radicals are updated in both the C 11 H 24 -2 and nC 11 H24 models using THERM25. A reaction path flux analysis for C 11 H 24 -2 at different temperatures was conducted. Compared to nC 11 H 24 , C 11 H 24 -2 shows slower reactivity. At low and intermediate temperatures, the chain propagation pathway Q̇OOH ↔ C 11 cyclic ether + ȮH is favored for C 11 H 24 -2, while the chain branching pathway Q̇OOH ↔ Ȯ 2 QOOH ↔ C 11 carbonyl hydroperoxide (KHP) + ȮH is suppressed, leading to lower reactivity compared to nC 11 H 24 . At high temperatures, the presence of the branched methyl group inhibits the direct decomposition of the fuel, resulting in reduced C 2 H 4 formation, which in turn suppresses the reactivity of the fuel.

2-methyl decane↗
DOE OSTI2026

Methyl formate oxidation kinetics up to 100 atm

Methyl formate (MF, CH3OCHO), the simplest ester, is a representative oxygenated fuel with high oxygen content, and low sooting tendency. However, its oxidation behavior under high-pressure and intermediate-temperature conditions remains insufficiently understood, especially where low-temperature peroxy radical chemistry, methanol chemistry, and pressure-dependent reaction pathways play a critical role. In this study, MF oxidation experiments were conducted in the Princeton supercritical-pressure jet-stirred reactor (SP-JSR) at 20 and 100 atm over the temperature range of 400–950 K under both fuel-lean and fuel-rich conditions. Based on the experimental results, an updated HP-Mech was developed by incorporating previous MF sub-mechanisms, expanded low-temperature peroxy pathways, and evaluated pressure-dependent decomposition kinetics. The newly updated HP-Mech shows greatly improved performance in predicting the onset temperature, the key intermediate species fractions, methanol formation, and the progression of MF oxidation across all the experimental conditions. Path flux analysis indicates that MF consumption at the onset stage is dominated by H-abstraction at the methyl site, forming CH2OCHO radicals that lead to the formation and isomerization of O2CH2OCHO, driving low-temperature chain propagation. Moreover, H-abstraction at the formate site forms CH3OCO radicals that preferentially decompose to CH3, initiating the methanol formation pathway linked to CH3O2 and HO2 chemistry. At the same time, HO2 formation is strongly coupled to MF oxidation through multiple MF-derived radical pathways. HCO originates from MF oxidation and acts as a key coupling species linking fuel consumption to HO2 buildup, especially under high-pressure and intermediate-temperature conditions. In addition to this dominant channel, supplementary HO2 formation pathways involving CH3, CH3O, CH2OH, and CH3O2 reacting with O2 further connect methanol chemistry and oxygenated radical chemistry to the HO2 pool, indicating the central role of HO2 in governing MF oxidation. Sensitivity analysis identifies MF with OH/HO2/CH3O2 reactions and the HO2/H2O2/OH sequence as the key factors controlling reactivity in the high-pressure and intermediate-temperature regime. MF directly reacts with OH/HO2/CH3O2 to consume the fuel and produce reactive radicals like CH2OCHO and CH3OCO that undergo subsequent oxidation pathways. Moreover, HO2 recombination suppresses oxidation at lower temperatures, while thermal decomposition of H2O2 accelerates OH production and promotes fuel consumption as temperature increases. The direct formation of active OH from HO2 radicals further completes the mechanism, improving its prediction especially during the oxidation onset stage.

Low-temperature Chemistry↗
DOE OSTI2020

Modeling Riverine Dissolved and Particulate Organic Carbon Fluxes from Two Small Watersheds in the Northeastern United States

The coupled carbon (C) cycle across terrestrial and aquatic environments at the watershed scale has been identified as an important, but poorly constrained component of the global carbon budget. Here, we extended Soil and Water Assessment Tool (SWAT) with coupled riverine particulate organic carbon (POC) and dissolved organic carbon (DOC) modules (referred to as SWAT-C hereafter). Results show that SWAT-C reproduced daily POC and DOC fluxes well in two watersheds in the Northeastern United States. We found that SWAT-C tended to underestimate high flows and peak DOC and POC fluxes. Uncertainty analysis indicated flux uncertainties associated with POC and DOC simulation were larger than those for flow simulation. Sensitive parameters controlling POC and DOC biogeochemical processes were identified along with how these parameters influence mechanisms underlying C cycling. We anticipate that the tool developed and applied here will inform C related ecosystem services in watershed assessment and planning.

Dissolved organic carbon, Particulate organic carb↗
DOE OSTI2020

An improved detailed chemical kinetic model for C3-C4 linear and iso-alcohols and their blends with gasoline at engine-relevant conditions

Propanol and butanol isomers have received significant research attention as promising fuel additives or neat biofuels. Robust chemical kinetic models are needed that can provide accurate and efficient predictions of combustion performance across a wide range of engine relevant conditions. Herein, this study seeks to improve the understanding of ignition and combustion behavior of pure C3-C4 linear and iso-alcohols, and their blends with gasoline at engine-relevant conditions. In this work, a kinetic model with improved thermochemistry and reaction kinetics was developed based on recent theoretical calculations of H-atom abstraction and peroxy radical reaction rates. Kinetic model validations are reported, and the current model reproduces the ignition delay times of the C3 and C4 alcohols well. Variations in reactivity over a wide range of temperatures and other operating conditions are also well predicted by the current model. Recent ignition delay time measurements from a rapid compression machine of neat iso-propanol and iso-butanol [Cheng et al., Proc. Combust Inst. (2020)] and blends with a research grade gasoline [Goldsborough et al., Proc. Combust Inst. (2020)] at elevated pressure (20–40 bar) and intermediate temperatures (780–950 K) were used to demonstrate the accuracy of the current kinetic model at conditions relevant to boosted spark-ignition engines. The effects of alcohol blending with gasoline on the autoignition behavior are discussed. The current model captures the suppression of reactivity in the low-temperature and negative-temperature-coefficient (NTC) region when either isopropanol and isobutanol are added to a research grade gasoline. Sensitivity and reaction flux analysis were performed to provide insights into the relevant fuel chemistry of the C3-C4 alcohols.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Mitochondrial ATP generation is more proteome efficient than glycolysis

Metabolic efficiency profoundly influences organismal fitness. Nonphotosynthetic organisms, from yeast to mammals, derive usable energy primarily through glycolysis and respiration. Although respiration is more energy efficient, some cells favor glycolysis even when oxygen is available (aerobic glycolysis, Warburg effect). A leading explanation is that glycolysis is more efficient in terms of ATP production per unit mass of protein (that is, faster). Through quantitative flux analysis and proteomics, we find, however, that mitochondrial respiration is actually more proteome efficient than aerobic glycolysis. This is shown across yeast strains, T cells, cancer cells, and tissues and tumors in vivo. Instead of aerobic glycolysis being valuable for fast ATP production, it correlates with high glycolytic protein expression, which promotes hypoxic growth. Aerobic glycolytic yeasts do not excel at aerobic growth but outgrow respiratory cells during oxygen limitation. Here, we accordingly propose that aerobic glycolysis emerges from cells maintaining a proteome conducive to both aerobic and hypoxic growth.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

maranasgroup/yeastsMFA

The parameterization of kinetic models requires measurement of fluxes and/or metabolite levels for a base strain and a few genetic perturbations thereof. Unlike stoichiometric models that are mostly invariant to the specific strain, it remains unclear whether kinetic models constructed for different strains of the same species have similar or significantly different kinetic parameters. This important question underpins the applicability range and prediction limits of kinetic reconstructions. To this end, herein we parameterize two separate large-scale kinetic models using K-FIT with genome-wide coverage corresponding to two distinct strains of Saccharomyces cerevisiae: CEN.PK 113-7D strain (model k-sacce306-CENPK), and growth-deficient BY4741 (isogenic to S288c; model k-sacce306-BY4741). The metabolic network for each model contains 306 reactions, 230 metabolites, and 119 substrate-level regulatory interactions. The two models (for CEN.PK and BY4741) recapitulate, within one standard deviation, 77% and 75% of the fitted dataset fluxes, respectively, determined by 13C metabolic flux analysis for wild-type and eight single-gene knockout mutants of each strain. Strain-specific kinetic parameterization results indicate that key enzymes in the TCA cycle, glycolysis, and arginine and proline metabolism drive the metabolic differences between these two strains of S. cerevisiae. Our results suggest that although kinetic models cannot be readily used across strains as stoichiometric models, they can capture species-specific information through the kinetic parameterization process.

Dinh, Hoang↗
DOE OSTI2023

maranasgroup/k-sacce306

The parameterization of kinetic models requires measurement of fluxes and/or metabolite levels for a base strain and a few genetic perturbations thereof. Unlike stoichiometric models that are mostly invariant to the specific strain, it remains unclear whether kinetic models constructed for different strains of the same species have similar or significantly different kinetic parameters. This important question underpins the applicability range and prediction limits of kinetic reconstructions. To this end, herein we parameterize two separate large-scale kinetic models using K-FIT with genome-wide coverage corresponding to two distinct strains of Saccharomyces cerevisiae: CEN.PK 113-7D strain (model k-sacce306-CENPK), and growth-deficient BY4741 (isogenic to S288c; model k-sacce306-BY4741). The metabolic network for each model contains 306 reactions, 230 metabolites, and 119 substrate-level regulatory interactions. The two models (for CEN.PK and BY4741) recapitulate, within one standard deviation, 77% and 75% of the fitted dataset fluxes, respectively, determined by 13C metabolic flux analysis for wild-type and eight single-gene knockout mutants of each strain. Strain-specific kinetic parameterization results indicate that key enzymes in the TCA cycle, glycolysis, and arginine and proline metabolism drive the metabolic differences between these two strains of S. cerevisiae. Our results suggest that although kinetic models cannot be readily used across strains as stoichiometric models, they can capture species-specific information through the kinetic parameterization process.

Dinh, Hoang↗
DOE OSTI2024

yihuishen/metabolic_flux_regulation

Metabolic efficiency profoundly influences organismal fitness. Heterotrophs, from yeast to mammals, derive usable energy primarily through glycolysis and respiration. While respiration is more energy-efficient, some cells favor glycolysis even when oxygen is available (aerobic glycolysis, Warburg effect). A leading explanation is that glycolysis is more efficient in terms of ATP production per unit mass of protein (i.e. faster). Through quantitative flux analysis and proteomics, we find however that mitochondrial respiration is actually more proteome-efficient than aerobic glycolysis. This is shown across yeasts, T cells, cancer cells, and tissues and tumors in vivo. Instead of aerobic glycolysis being valuable for fast ATP production, it correlates with high glycolytic protein expression, which is valuable for hypoxic growth. Aerobic glycolytic yeasts do not excel at aerobic growth, but outgrow respiratory cells in oxygen limitation. Thus, aerobic glycolysis emerges from cells maintaining a proteome conducive to both aerobic and hypoxic growth.

Shen, Yihui↗
DOE OSTI2024

yihuishen/T_cell_MFA

Metabolic efficiency profoundly influences organismal fitness. Heterotrophs, from yeast to mammals, derive usable energy primarily through glycolysis and respiration. While respiration is more energy-efficient, some cells favor glycolysis even when oxygen is available (aerobic glycolysis, Warburg effect). A leading explanation is that glycolysis is more efficient in terms of ATP production per unit mass of protein (i.e. faster). Through quantitative flux analysis and proteomics, we find however that mitochondrial respiration is actually more proteome-efficient than aerobic glycolysis. This is shown across yeasts, T cells, cancer cells, and tissues and tumors in vivo. Instead of aerobic glycolysis being valuable for fast ATP production, it correlates with high glycolytic protein expression, which is valuable for hypoxic growth. Aerobic glycolytic yeasts do not excel at aerobic growth, but outgrow respiratory cells in oxygen limitation. Thus, aerobic glycolysis emerges from cells maintaining a proteome conducive to both aerobic and hypoxic growth.

Shen, Yihui↗
DOE OSTI2026

Data for Mitochondrial ATP Generation is More Proteome Efficient than Glycolysis

Metabolic efficiency profoundly influences organismal fitness. Heterotrophs, from yeast to mammals, derive usable energy primarily through glycolysis and respiration. While respiration is more energy-efficient, some cells favor glycolysis even when oxygen is available (aerobic glycolysis, Warburg effect). A leading explanation is that glycolysis is more efficient in terms of ATP production per unit mass of protein (i.e. faster). Through quantitative flux analysis and proteomics, we find however that mitochondrial respiration is actually more proteome-efficient than aerobic glycolysis. This is shown across yeasts, T cells, cancer cells, and tissues and tumors in vivo. Instead of aerobic glycolysis being valuable for fast ATP production, it correlates with high glycolytic protein expression, which is valuable for hypoxic growth. Aerobic glycolytic yeasts do not excel at aerobic growth, but outgrow respiratory cells in oxygen limitation. Thus, aerobic glycolysis emerges from cells maintaining a proteome conducive to both aerobic and hypoxic growth.

Metabolomics↗