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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Development of a clostridia-based cell-free system for prototyping genetic parts and metabolic pathways

Gas fermentation by autotrophic bacteria, such as clostridia, offers a sustainable path to numerous bioproducts from a range of local, highly abundant, waste and low-cost feedstocks, such as industrial flue gases or syngas generated from biomass or municipal waste. Unfortunately, designing and engineering clostridia remains laborious and slow. The ability to prototype individual genetic part function, gene expression patterns, and biosynthetic pathway performance in vitro before implementing designs in cells could help address these bottlenecks by speeding up design. Unfortunately, a high-yielding cell-free gene expression (CFE) system from clostridia has yet to be developed. Here in this paper, we report the development and optimization of a high-yielding (236 ± 24 μg/mL) batch CFE platform from the industrially relevant anaerobe, Clostridium autoethanogenum. A key feature of the platform is that both circular and linear DNA templates can be applied directly to the CFE reaction to program protein synthesis. We demonstrate the ability to prototype gene expression, and quantitatively map aerobic cell-free metabolism in lysates from this system. We anticipate that the C. autoethanogenum CFE platform will not only expand the protein synthesis toolkit for synthetic biology, but also serve as a platform in expediting the screening and prototyping of gene regulatory elements in non-model, industrially relevant microbes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Curating a comprehensive set of enzymatic reaction rules for efficient novel biosynthetic pathway design

Enzyme substrate promiscuity has significant implications for metabolic engineering. The ability to predict the space of possible enzymatic side reactions is crucial for elucidating underground metabolic networks in microorganisms, as well as harnessing novel biosynthetic capabilities of enzymes to produce desired chemicals. Reaction rule-based cheminformatics platforms have been implemented to computationally enumerate possible promiscuous reactions, relying on existing knowledge of enzymatic transformations to inform novel reactions. However, past versions of curated reaction rules have been limited by a lack of comprehensiveness in representing all possible transformations, as well as the need to prune rules to enhance computational efficiency in pathway expansion. To this end, we curated a set of 1224 most generalized reaction rules, automatically abstracted from atom-mapped MetaCyc reactions and verified to uniquely cover all common enzymatic transformations. Additionally, we developed a framework to systematically identify and correct redundancies and errors in the curation process, resulting in a minimal, yet comprehensive, rule set. These reaction rules were capable of reproducing more than 85% of all reactions in the KEGG and BRENDA databases, for which a large fraction of reactions is not present in MetaCyc. Our rules exceed all previously published rule sets for which reproduction was possible in this coverage analysis, which allows for the exploration of a larger space of known enzymatic transformations. By leveraging the entire knowledge of possible metabolic reactions through generalized enzymatic reaction rules, we are able to better utilize underground metabolic pathways and accelerate novel biosynthetic pathway design to enable bioproduction towards a wider range of new molecules.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Advances in systems metabolic engineering of autotrophic carbon oxide-fixing biocatalysts towards a circular economy

High levels of anthropogenic CO 2 emissions are driving the warming of global climate. If this pattern of increasing emissions does not change, it will cause further climate change with severe consequences for the human population. On top of this, the increasing accumulation of solid waste within the linear economy model is threatening global biosustainability. The magnitude of these challenges requires several approaches to capture and utilize waste carbon and establish a circular economy. Microbial gas fermentation presents an exciting opportunity to capture carbon oxides from gaseous and solid waste streams with high feedstock flexibility and selectivity. Here we discuss available microbial systems and review in detail the metabolism of both anaerobic acetogens and aerobic hydrogenotrophs and their ability to utilize C1 waste feedstocks. More specifically, we provide an overview of the systems-level understanding of metabolism, key metabolic pathways, scale-up opportunities and commercial successes, and the most recent technological advances in strain and process engineering. Finally, we also discuss in detail the gaps and opportunities to advance the understanding of these autotrophic biocatalysts for the efficient and economically viable production of bioproducts from recycled carbon.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Machine-learning from Pseudomonas putida KT2440 transcriptomes reveals its transcriptional regulatory network

Bacterial gene expression is orchestrated by numerous transcription factors (TFs). Elucidating how gene expression is regulated is fundamental to understanding bacterial physiology and engineering it for practical use. In this study, a machine-learning approach was applied to uncover the genome-scale transcriptional regulatory network (TRN) in Pseudomonas putida KT2440, an important organism for bioproduction. We performed independent component analysis of a compendium of 321 high-quality gene expression profiles, which were previously published or newly generated in this study. We identified 84 groups of independently modulated genes (iModulons) that explain 75.7% of the total variance in the compendium. With these iModulons, we (i) expand our understanding of the regulatory functions of 39 iModulon associated TFs (e.g., HexR, Zur) by systematic comparison with 1993 previously reported TF-gene interactions; (ii) outline transcriptional changes after the transition from the exponential growth to stationary phases; (iii) capture group of genes required for utilizing diverse carbon sources and increased stationary response with slower growth rates; (iv) unveil multiple evolutionary strategies of transcriptome reallocation to achieve fast growth rates; and (v) define an osmotic stimulon, which includes the Type VI secretion system, as coordination of multiple iModulon activity changes. Taken together, this study provides the first quantitative genome-scale TRN for P. putida KT2440 and a basis for a comprehensive understanding of its complex transcriptome changes in a variety of physiological states.

09 BIOMASS FUELS↗
DOE OSTI2023

A dynamic kinetic model captures cell-free metabolism for improved butanol production

Cell-free systems are useful tools for prototyping metabolic pathways and optimizing the production of various bioproducts. Mechanistically-based kinetic models are uniquely suited to analyze dynamic experimental data collected from cell-free systems and provide vital qualitative insight. However, to date, dynamic kinetic models have not been applied with rigorous biological constraints or trained on adequate experimental data to the degree that they would give high confidence in predictions and broadly demonstrate the potential for widespread use of such kinetic models. In this work, we construct a large-scale dynamic model of cell-free metabolism with the goal of understanding and optimizing butanol production in a cell-free system. Using a combination of parameterization methods, the resultant model captures experimental metabolite measurements across two experimental conditions for nine metabolites at timepoints between 0 and 24 hours. Here, we present analysis of the model predictions, provide recommendations for butanol optimization, and identify the aldehyde/alcohol dehydrogenase as the primary bottleneck in butanol production. Sensitivity analysis further reveals the extent to which various parameters are constrained, and our approach for probing valid parameter ranges can be applied to other modeling efforts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

RB-TnSeq identifies genetic targets for improved tolerance of Pseudomonas putida towards compounds relevant to lignin conversion

We report lignin-derived mixtures intended for bioconversion commonly contain high concentrations of aromatic acids, aliphatic acids, and salts. The inherent toxicity of these chemicals places a significant bottleneck upon the effective use of microbial systems for the valorization of these mixtures. Pseudomonas putida KT2440 can tolerate stressful quantities of several lignin-related compounds, making this bacterium a promising host for converting these chemicals to valuable bioproducts. Nonetheless, further increasing P. putida tolerance to chemicals in lignin-rich substrates has the potential to improve bioprocess performance. Accordingly, we employed random barcoded transposon insertion sequencing (RB-TnSeq) to reveal genetic determinants in P. putida KT2440 that influence stress outcomes during exposure to representative constituents found in lignin-rich process streams. The fitness information obtained from the RB-TnSeq experiments informed engineering of strains via deletion or constitutive expression of several genes. Namely, ΔgacAS, ΔfleQ, ΔlapAB, ΔttgR::P tac :ttgABC, Ptac:PP_1150:PP_1152, ..delta..relA, and ΔPP_1430 mutants showed growth improvement in the presence of single compounds, and some also exhibited greater tolerance when grown using a complex chemical mixture representative of a lignin-rich chemical stream. Overall, this work demonstrates the successful implementation of a genome-scale screening tool for the identification of genes influencing stress tolerance against notable compounds within lignin-enriched chemical streams, and the genetic targets identified herein offer promising engineering targets for improving feedstock tolerance in lignin valorization strains of P. putida KT2440.

09 BIOMASS FUELS↗
DOE OSTI2023

Evaluating proteome allocation of Saccharomyces cerevisiae phenotypes with resource balance analysis

Saccharomyces cerevisiae is an important model organism and a workhorse in bioproduction. Here, we reconstructed a compact and tractable genome-scale resource balance analysis (RBA) model (i.e., named scRBA) to analyze metabolic fluxes and proteome allocation in a computationally efficient manner. Resource capacity models such as scRBA provide the quantitative means to identify bottlenecks in biosynthetic pathways due to enzyme, compartment size, and/or ribosome availability limitations. ATP maintenance rate and in vivo apparent turnover numbers (k app ) were regressed from metabolic flux and protein concentration data to capture observed physiological growth yield and proteome efficiency and allocation, respectively. Estimated parameter values were found to vary with oxygen and nutrient availability. Altogether, this work (i) provides condition-specific model parameters to recapitulate phenotypes corresponding to different extracellular environments, (ii) alludes to the enhancing effect of substrate channeling and post-translational activation on in vivo enzyme efficiency in glycolysis and electron transport chain, and (iii) reveals that the Crabtree effect is underpinned by specific limitations in mitochondrial proteome capacity and secondarily ribosome availability rather than overall proteome capacity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Fluctuating pH for efficient photomixotrophic succinate production

Cyanobacteria are attracting increasing attention as a photosynthetic chassis organism for diverse biochemical production, however, photoautotrophic production remains inefficient. Photomixotrophy, a method where sugar is used to supplement baseline autotrophic metabolism in photosynthetic hosts, is becoming increasingly popular for enhancing sustainable bioproduction with multiple input energy streams. In this study, the commercially relevant diacid, succinate, was produced photomixotrophically. Succinate is an important industrial chemical that can be used for the production of a wide array of products, from pharmaceuticals to biopolymers. In this system, the substrate, glucose, is transported by a proton symporter and the product, succinate, is hypothesized to be transported by another proton symporter, but in the opposite direction. Thus, low pH is required for the import of glucose and high pH is required for the export of succinate. Succinate production was initiated in a pH 7 medium containing bicarbonate. Glucose was efficiently imported at around neutral pH. Utilization of bicarbonate by CO 2 fixation raised the pH of the medium. As succinate, a diacid, was produced, the pH of the medium dropped. By repeating this cycle with additional pH adjustment, those contradictory requirements for transport were overcome. pH affects a variety of biological factors and by cycling from high pH to neutral pH processes such as CO 2 fixation rates and CO 2 solubility can vary. In this study the engineered strains produced succinate during fluctuating pH conditions, achieving a titer of 5.0gL -1 after 10 days under shake flask conditions. Finally, these results demonstrate the potential for photomixotrophic production as a viable option for the large-scale production of succinate.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Identification of a specific exporter that enables high production of aconitic acid in Aspergillus pseudoterreus

Aconitic acid is an unsaturated tricarboxylic acid that is attractive for its potential use in the manufacture of biodegradable and biocompatible polymers, plasticizers, and surfactants. Previously Aspergillus pseudoterreus was engineered as a platform to produce aconitic acid by deleting the cadA (cis-aconitic acid decarboxylase) gene in the itaconic acid biosynthetic pathway. In this study aconitic acid transporter gene (aexA) was identified using comparative global discovery proteomics analysis between the wild-type and cadA deletion strains. Deletion of aexA almost eliminated aconitic acid secretion, while its overexpression led to a significant increase in aconitic acid production. Transportation of aconitic acid across the plasma membrane is a key limiting step. In vitro proteoliposome transport assay further validated AexA’s function and its substrate specificity. This research provides new approaches to efficiently pinpoint and characterize exporters of fungal organic acids and accelerate the metabolic engineering to improve secretion capability and lower cost for bioproduction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Development of Corynebacterium glutamicum as a monoterpene production platform

Monoterpenes are commonly known for their role in the flavors and fragrances industry and are also gaining attention for other uses like insect repellant and as potential renewable fuels for aviation. Corynebacterium glutamicum, a Generally Recognized as Safe microbe, has been a choice organism in industry for the annual million ton-scale bioproduction of amino acids for more than 50 years; however, efforts to produce monoterpenes in C. glutamicum have remained relatively limited. In this study, we report a further expansion of the C. glutamicum biosynthetic repertoire through the development and optimization of a mevalonate-based monoterpene platform. In the course of our plasmid design iterations, we increased flux through the mevalonate-based bypass pathway, measuring isoprenol production as a proxy for monoterpene precursor abundance and demonstrating the highest reported titers in C. glutamicum to date at 1504.6 mg/L. Our designs also evaluated the effects of backbone, promoter, and GPP synthase homolog origin on monoterpene product titers. Monoterpene production was further improved by disrupting competing pathways for isoprenoid precursor supply and by implementing a biphasic production system to prevent volatilization. With this platform, we achieved 321.1 mg/L of geranoids, 723.6 mg/L of 1,8-cineole, and 227.8 mg/L of linalool. Furthermore, we determined that C. glutamicum first oxidizes geraniol through an aldehyde intermediate before it is asymmetrically reduced to citronellol. Additionally, we demonstrate that the aldehyde reductase, AdhC, possesses additional substrate promiscuity for acyclic monoterpene aldehydes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

The oleaginous yeast Rhodosporidium toruloides engineered for biomass hydrolysate-derived (E)-α-bisabolene production

The oleaginous yeast Rhodosporidium toruloides has been exploited for many bioproducts, including several terpenes, owing to its oleaginous nature and biomass inhibitor tolerance. Here, we built upon previous (E)-a-bisabolene work by iteratively stacking the complete mevalonate pathway from Saccharomyces cerevisiae onto a multicopy bisabolene synthase parent strain. Metabolomics and proteomics verified heterologous pathway expression and identified metabolic bottlenecks at three intermediate steps, with candidate feedback-resistant mevalonate kinases screening improving titers 15%. Subtle differences in codon optimization, and preliminary attenuation of competing flux toward lipids resulted in 6-fold, 7-fold higher titers relative to controls, respectively. Media optimization led to modest improvements, with zinc identified as the most promising at 10% titer improvement. Ultimately, high-performance strains were cultivated with corn-stover biomass hydrolysate in microtiter plates at 300g/L total sugar, achieving 20.8g/L bisabolene, the highest reported titer in the literature. A 2L glucose minimal medium bioreactor achieved 19.3 g/L bisabolene and a literature-high productivity of 0.11 g/L/h.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Metabolic flux and resource balance in the oleaginous yeast Rhodotorula toruloides

The yeast Rhodotorula toruloides is a promising bioproduction organism due to its high lipid yields and ability to grow on cheap and abundant substrates. Quantitative, systems-level assessment of its metabolic activity is accordingly merited. Resource-balance analysis (RBA) models capture not only reaction stoichiometry but also enzyme requirements for catalysis, providing valuable tools for understanding metabolic trade-offs and optimizing metabolic engineering strategies. Here, in this work, we present systems-level measurements of R. toruloides metabolic flux based on isotope tracing and metabolic flux analysis. In combination with new proteomic measurements, these flux data are used to parameterize a genome-scale resource balance model rtRBA. We find that S. cerevisiae and R. toruloides grow at nearly indistinguishable rates using similar biosynthetic but dramatically different central metabolic programs. R. toruloides consumes one-fifth as much glucose, which it metabolizes primarily via the pentose phosphate pathway and TCA cycle unlike primarily glycolysis in S. cerevisiae . Overall, across these two divergent yeasts, protein abundances aligned more closely than metabolic flux. Resource balance modeling of these metabolic programs predicts superior theoretical yields but lower productivities in R. toruloides than S. cerevisiae for industrial chemicals, highlighting the value of rapid glucose uptake for productivity but respiratory metabolism for yields.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Atomistic Simulations of Polydisperse Lignin Melts Using Simple Polydisperse Residue Input Generator

Understanding the physics of lignin will help rationalize its function in plant cell walls as well as aiding practical applications such as deriving biofuels and bioproducts. Here, in this work, we present SPRIG (Simple Polydisperse Residue Input Generator), a program for generating atomic-detail models of random polydisperse lignin copolymer melts i.e., the state most commonly found in nature. Using these models, we use all-atom molecular dynamics (MD) simulations to investigate the conformational and dynamic properties of polydisperse melts representative of switchgrass (Panicum virgatum L.) lignin. Polydispersity, branching and monolignol sequence are found to not affect the calculated glass transition temperature, T g . The Flory–Huggins scaling parameter for the segmental radius of gyration is 0.42 ± 0.02, indicating that the chains exhibit statistics that lie between a globular chain and an ideal Gaussian chain. Below T g the atomic mean squared displacements are independent of molecular weight. In contrast, above T g , they decrease with increasing molecular weight. Therefore, a monodisperse lignin melt is a good approximation to this polydisperse lignin when only static properties are probed, whereas the molecular weight distribution needs to be considered while analyzing lignin dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Machine Learning Reduced Order Model for Cost and Emission Assessment of a Pyrolysis System

Biomass pyrolysis is a promising approach for producing economic and environmentally-friendly fuels and bioproducts. Biomass pyrolysis experiments show that feedstock properties have a significant impact on product yields and composition. Scientists are developing detailed chemical reaction mechanisms to capture the relationships between biomass composition and pyrolysis yields. These mechanisms can be computationally intensive. In this study, we investigate the use of a machine learning reduced order model (ROM) for assessing the costs and emissions of a pyrolysis biorefinery. Here, we developed a Kriging-based ROM to predict pyrolysis yields of 314 feedstock samples based on the results of a detailed chemical kinetic pyrolysis mechanism. The ROM is integrated into a chemical process model for calculating mass and energy yields in a commercial-scale (2000 tonne/day) biorefinery. The ROM estimated biofuel yields of 65 to 130 gallons per ton of dry biomass. This results in biofuel minimum fuel-selling prices of $2.62 to $5.43 per gallon and emissions of -13.62 to 145 kg of CO 2 per MJ. The ROM achieved an average mean square error of 1.8e-20 and a mean absolute error of 0.53%. These results suggest that ROMs can facilitate rapid feedstock screening for biorefinery systems.

09 BIOMASS FUELS↗
DOE OSTI2020

Recycling of Nutrients from Dairy Wastewater by Extremophilic Microalgae with High Ammonia Tolerance

This study explored the possibility of incorporating extremophilic algal cultivation into dairy wastewater treatment by characterizing a unique algal strain. Results showed that extremophilic microalgae Chlorella vulgaris CA1 newly isolated from dairy wastewater tolerated a high level of ammonia nitrogen (2.7 g/L), which was over 20 times the ammonia nitrogen that regular Chlorella sp. could tolerate. The isolate was mixotrophically cultured in dairy effluent treated by anaerobic digestion (AD) for recycling nutrients and polishing the wastewater. The highest biomass content of 13.3 g/L and protein content of 43.4% were achieved in the culture in AD effluent. Up to 96% of the total nitrogen and 79% of the total phosphorus were removed from the dairy AD effluent. The ability of the algae to tolerate a high level of ammonia nitrogen suggests the potential for direct nutrient recycling from dairy wastewater while producing algal biomass and high value bioproducts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Moisture-driven CO 2 direct air capture and delivery for cultivating cyanobacteria

This study demonstrates a low-energy system that passively captures CO₂ from ambient air using reusable solid sorbents and delivers it directly into alkaline cultivation media to support the growth of cyanobacteria, from laboratory flasks to outdoor raceway ponds. While long-term operation revealed challenges including biofouling and sorbent degradation, the results suggest that with improved sorbent durability, this approach could provide a scalable source of atmospheric carbon for producing sustainable fuels, proteins, natural colorants, and other bioproducts.

09 BIOMASS FUELS↗
DOE OSTI2026

Spatial Optimization of Multiscale Biorefinery Deployment for a Diversified Bioeconomy in the United States

Strategic biorefinery siting is critical for a diversified bioeconomy, yet industry, policy, and research often focus on either large-scale biofuel plants or smaller-scale specialty bioproduct facilities, with limited coordination across scales. We address this gap by modeling biorefinery deployment spanning a 28-fold difference in capacity. We developed an open-source, spatially explicit framework integrating techno-economic analysis with logistics and refinery cost surrogate models to evaluate multiscale miscanthus-derived biorefineries across the rainfed U.S. for the production of ethanol, succinic acid, lactic acid, potassium sorbate, and acrylic acid. Overall costs change little as feedstock density increases, while transport distances decrease by ∼30 to 67% (∼100 km) and siting flexibility improves. Specifically, a 5-fold feedstock density increase (2% to 10% of suitable land) reduces minimum selling prices by <10% (e.g., 0.27 USD·gal –1 for ethanol). This limited economic sensitivity suggests dense planting is not required for competitive deployment, particularly for smaller-scale facilities. Representing collection areas as irregular rather than circular expands the feasible space under low-density scenarios. While large-scale refineries anchor regional supply chains, smaller facilities retain spatial flexibility even when large refineries are established. These findings highlight the importance of spatial representation and multiscale coordination for robust, regionally tailored biomanufacturing networks to advance renewable carbon integration without extensive land conversion.

biorefinery siting↗
DOE OSTI2025

Carbon Capture and Storage for Small-to-Medium Biorefineries: Promising Carbon Removal Solution with Economic Challenges

Carbon capture and storage (CCS) integrated with biomass-based fuel production can provide cost-effective biomass carbon removal and storage (BiCRS) and produce high-value bioproducts, such as sustainable aviation fuels. To accelerate BiCRS deployment, it is crucial to quantify the costs of CCS integration, particularly for small- and medium-scale biorefineries that are representative of early-stage deployment. Existing studies tend to focus on plant sizes that are orders-of-magnitude larger than early-stage installations, possibly underestimating CCS costs for small-to-medium biorefineries. We show that the capture, transport, and storage costs to maximize CO 2 removal from a 526 dry tonne per day (tpd) biomass gasification plant (largest existing size) could be 13–47% higher than costs for a typical modeled plant size (2000 dry tpd). The higher cost estimates are driven by less favorable economies of scale and realistic assumptions about the availability of affordable CO 2 transport infrastructure with both drivers broadly applicable to other BiCRS technologies. Compliance and voluntary carbon markets could incentivize biorefinery CCS, but both carry a high degree of uncertainty. In conclusion, these findings highlight that sufficient and reliable financial mechanisms would be essential to unlocking the full CO 2 removal potential of biorefineries and facilitating BiCRS scale-up.

Biological transport↗