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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Application of the metabolic modeling pipeline in KBase to categorize reactions, predict essential genes, and predict pathways in an isolate genome

The DOE Systems Biology Knowledgebase (KBase) platform offers a range of powerful tools for the reconstruction, refinement, and analysis of genome-scale metabolic models built from microbial isolate genomes. In this chapter, we describe and demonstrate these tools in action with an analysis of isoprene production in the Bacillus subtilis DSM genome. Two different methods are applied to build initial metabolic models for the DSM genome, then the models are gapfilled in three different growth conditions. Next, flux balance analysis (FBA) and flux variability analysis (FVA) techniques are applied to both study the growth of these models in minimal media and classify reactions within each model based on essentiality and functionality. The models are applied with the FBA method to predict essential genes, which are then compared to an updated list of essential genes obtained for B. subtilis 168, a very similar strain to the DSM isolate. The models are also applied to simulate Biolog growth conditions, and these results are compared with Biolog data collected for B. subtilis 168. Finally, the DSM metabolic models are applied to explore the pathways and genes responsible for producing isoprene in this strain. These studies demonstrate the accuracy and utility of models generated from the KBase pipelines, as well as exploring the tools available for analyzing these models.

DOE knowledgebase↗
DOE OSTI2021

Application of the Metabolic Modeling Pipeline in KBase to Categorize Reactions, Predict Essential Genes, and Predict Pathways in an Isolate Genome

The DOE Systems Biology Knowledgebase (KBase) platform offers a range of powerful tools for the reconstruction, refinement, and analysis of genome-scale metabolic models built from microbial isolate genomes. In this chapter, we describe and demonstrate these tools in action with an analysis of isoprene production in the Bacillus subtilis DSM genome. Two different methods are applied to build initial metabolic models for the DSM genome, then the models are gapfilled in three different growth conditions. Next, flux balance analysis (FBA) and flux variability analysis (FVA) techniques are applied to both study the growth of these models in minimal media and classify reactions within each model based on essentiality and functionality. The models are applied with the FBA method to predict essential genes, which are then compared to an updated list of essential genes obtained for B. subtilis 168, a very similar strain to the DSM isolate. The models are also applied to simulate Biolog growth conditions, and these results are compared with Biolog data collected for B. subtilis 168. Finally, the DSM metabolic models are applied to explore the pathways and genes responsible for producing isoprene in this strain. These studies demonstrate the accuracy and utility of models generated from the KBase pipelines, as well as exploring the tools available for analyzing these models.

Allen, Benjamin↗
DOE OSTI2020

Investigation of a Novel Salt Stress-Responsive Pathway Mediated by Arabidopsis DEAD-Box RNA Helicase Gene AtRH17 Using RNA-Seq Analysis

Previously, we reported that overexpression of AtRH17, an Arabidopsis DEAD-box RNA helicase gene, confers salt stress-tolerance via a pathway other than the well-known salt stress-responsive pathways. To decipher the salt stress-responsive pathway in AtRH17-overexpressing transgenic plants (OXs), we performed RNA-Sequencing and identified 397 differentially expressed genes between wild type (WT) and AtRH17 OXs. Among them, 286 genes were upregulated and 111 genes were downregulated in AtRH17 OXs relative to WT. Gene ontology annotation enrichment and KEGG pathway analysis showed that the 397 upregulated and downregulated genes are involved in various biological functions including secretion, signaling, detoxification, metabolic pathways, catabolic pathways, and biosynthesis of secondary metabolites as well as in stress responses. Genevestigator analysis of the upregulated genes showed that nine genes, namely, LEA4-5, GSTF6, DIN2/BGLU30, TSPO, GSTF7, LEA18, HAI1, ABR, and LTI30, were upregulated in Arabidopsis under salt, osmotic, and drought stress conditions. In particular, the expression levels of LEA4-5, TSPO, and ABR were higher in AtRH17 OXs than in WT under salt stress condition. Taken together, our results suggest that a high AtRH17 expression confers salt stress-tolerance through a novel salt stress-responsive pathway involving nine genes, other than the well-known ABA-dependent and ABA-independent pathways.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Divide and conquer towards synthetic autotrophy

With climate change concerns deepening, CO 2 fixation pathways to produce value-added chemicals are currently of interest. In this work, synthetic biology and machine learning help developing such a pathway across modules that have been tested in vivo in Escherichia coli for the production of acetyl coenzyme A.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Towards using bacterial microcompartments as a platform for spatial metabolic engineering in the industrially important and metabolically versatile Zymomonas mobilis

Advances in synthetic biology have enabled the incorporation of novel biochemical pathways for the production of high-value products into industrially important bacterial hosts. However, attempts to redirect metabolic fluxes towards desired products often lead to the buildup of toxic or undesirable intermediates or, more generally, unwanted metabolic cross-talk. The use of shells derived from self-assembling protein-based prokaryotic organelles, referred to as bacterial microcompartments (BMCs), as a scaffold for metabolic enzymes represents a sophisticated approach that can both insulate and integrate the incorporation of challenging metabolic pathways into industrially important bacterial hosts. Here we took a synthetic biology approach and introduced the model shell system derived from the myxobacterium Haliangium ochraceum (HO shell) into the industrially relevant organism Zymomonas mobilis with the aim of constructing a BMC-based spatial scaffolding platform. SDS-PAGE, transmission electron microscopy, and dynamic light scattering analyses collectively demonstrated the ability to express and purify empty capped and uncapped HO shells from Z. mobilis . As a proof of concept to internally load or externally decorate the shell surface with enzyme cargo, we have successfully targeted fluorophores to the surfaces of the BMC shells. Overall, our results provide the foundation for incorporating enzymes and constructing BMCs with synthetic biochemical pathways for the future production of high-value products in Z. mobilis .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Reverse β-oxidation pathways for efficient chemical production

Abstract Microbial production of fuels, chemicals, and materials has the potential to reduce greenhouse gas emissions and contribute to a sustainable bioeconomy. While synthetic biology allows readjusting of native metabolic pathways for the synthesis of desired products, often these native pathways do not support maximum efficiency and are affected by complex regulatory mechanisms. A synthetic or engineered pathway that allows modular synthesis of versatile bioproducts with minimal enzyme requirement and regulation while achieving high carbon and energy efficiency could be an alternative solution to address these issues. The reverse β-oxidation (rBOX) pathways enable iterative non-decarboxylative elongation of carbon molecules of varying chain lengths and functional groups with only four core enzymes and no ATP requirement. Here, we describe recent developments in rBOX pathway engineering to produce alcohols and carboxylic acids with diverse functional groups, along with other commercially important molecules such as polyketides. We discuss the application of rBOX beyond the pathway itself by its interfacing with various carbon-utilization pathways and deployment in different organisms, which allows feedstock diversification from sugars to glycerol, carbon dioxide, methane, and other substrates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Newly developed sugarbeet lines with altered postharvest respiration rates differ in transcription factor and glycolytic enzyme expression

Respiration is the principal cause for postharvest sucrose loss in sugarbeet (Beta vulgaris L.) roots. Although reductions in respiration rate could mitigate these losses, developing sugarbeet cultivars and storage procedures that reduce respiration are hindered by a lack of knowledge of the genetic and metabolic factors that control storage respiration rate. Research was conducted to identify genes and gene products that affect storage respiration rate by creating two sugarbeet lines that differ in respiration rate and characterizing gene expression differences between these lines. Sugarbeet lines F1056 and F1057, which differ by up to 42% in respiration rate, were created by divergent selection of a sugarbeet population using root respiration rate after 30 d in storage as the principal selection criterion. RNA sequencing identified 287 differentially expressed genes (DEGs) between these lines on the day of harvest and after 28-d storage. Of these DEGs, nine encoded transcription factors and five encoded enzymes involved in the respiratory pathway. Other DEGs contributed to a variety of biological and molecular functions based on gene ontology classifications. Of respiratory pathway DEGS, genes for NAD+- and NADP+-dependent forms of glyceraldehyde-3-phosphate dehydrogenase were of note due to their high upregulation in the high respiring line and for their established role in glycolysis, a pathway identified as a likely bottleneck in respiratory substrate production. Overall, lines F1056 and F1057 provide new tools for investigating genetic and physiological differences in storage respiration rate, and their DEGs identify candidates for genes affecting sugarbeet root respiration rate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Biosensor-driven strain engineering reveals key cellular processes for maximizing isoprenol production in Pseudomonas putida

Synthetic biology generates vast combinatorial designs, yet high-throughput analytical methods to screen them are poorly matched to interrogate this search space. We address this challenge by developing a biosensor-driven, growth-coupled selection strategy in Pseudomonas putida for isoprenol, a potential aviation fuel precursor. We found and characterized a noncanonical signaling pathway, revealing a functional and physical complex between a hybrid histidine kinase and an alcohol dehydrogenase, whose activity is tuned by heterodimerization. Leveraging this biosensor in a pooled CRISPRi library selection, we identified key host limitations. Iterative combinatorial strain engineering derived from these hits yielded a 36-fold titer increase to ~900 milligrams per liter. Integrated omics analysis revealed that metabolic rewiring toward amino acid catabolism was crucial for this improvement. This observation was found to be beneficial by technoeconomic analysis. Our modular workflow provides a powerful strategy for optimizing complex heterologous pathways and uncovering emergent host biology.

CRISPRi↗
DOE OSTI2023

Signal Transduction Pathways of Chloroplast Quality Control (Final Report)

Chloroplasts (photosynthetic plastids) of higher plants contain about 3000 proteins of which more than 95% are encoded by nuclear genes. To avoid the accumulation of reactive oxygen species that are the inherent by-product of photosynthesis, gene expression of these spatially separated genomes is regulated by two-way signaling. Thus, while plastid differentiation and development are largely under nuclear control, developmentally arrested or damaged plastids can regulate expression of nuclear genes via retrograde signaling pathways. In previous years of DOE-funded study, we performed a number of genetic screens that implicated the chloroplast-localized tetrapyrrole biosynthesis pathway as the source of both positive and stress-related retrograde signals. Using that work as a foundation, we have recently uncovered a new type of retrograde signal that leads to the selective removal of damaged chloroplasts from the cell. However, the mechanisms of such a chloroplast quality control pathway are not well characterized or understood.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Revisiting Theoretical Tools and Approaches for the Valorization of Recalcitrant Lignocellulosic Biomass to Value-Added Chemicals

Biorefinery processes for converting lignocellulosic biomass to fuels and chemicals proceed via an integrated series of steps. Biomass is first pretreated and deconstructed using chemical catalysts and/or enzymes to liberate sugar monomers and lignin fragments. Deconstruction is followed by a conversion step in which engineered host organisms assimilate the released sugar monomers and lignin fragments, and produce value-added fuels and chemicals. Over the past couple of decades, a significant amount of work has been done to develop innovative biomass deconstruction and conversion processes that efficiently solubilize biomass, separate lignin from the biomass, maximize yields of bioavailable sugars and lignin fragments and convert the majority of these carbon sources into fuels, commodity chemicals, and materials. Herein, we advocate that advanced in silico approaches provide a theoretical framework for developing efficient processes for lignocellulosic biomass valorization and maximizing yields of sugars and lignin fragments during deconstruction and fuel and chemical titers during conversion. This manuscript surveys the latest developments in lignocellulosic biomass valorization with special attention given to highlighting computational approaches used in process optimization for lignocellulose pretreatment; enzyme engineering for enhanced saccharification and delignification; and prediction of the genome modification necessary for desired pathway fine-tuning to upgrade products from biomass deconstruction into value-added products. Physics-based modeling approaches such as density functional theory calculations and molecular dynamics simulations have been most impactful in studies aimed at exploring the molecular level details of solvent-biomass interactions, reaction mechanisms occurring in biomass-solvent systems, and the catalytic mechanisms and engineering of enzymes involved in biomass degradation. More recently, with ever increasing amounts of data from, for example, advanced mutli-omics experiments, machine learning approaches have begun to make important contributions in synthetic biology and optimization of metabolic pathways for production of biofuels and chemicals.

09 BIOMASS FUELS↗
DOE OSTI2021

Metabolic engineering strategies for sesquiterpene production in microorganism

Sesquiterpenes are a large variety of terpene natural products, widely existing in plants, fungi, marine organisms, insects, and microbes. Value-added sesquiterpenes are extensively used in industries such as: food, drugs, fragrances, and fuels. With an increase in market demands and the price of sesquiterpenes, the biosynthesis of sesquiterpenes by microbial fermentation methods from renewable feedstocks is acquiring increasing attention. Synthetic biology provides robust tools of sesquiterpene production in microorganisms. This review presents a summary of metabolic engineering strategies on the hosts and pathway engineering for sesquiterpene production. Advances in synthetic biology provide new strategies on the creation of desired hosts for sesquiterpene production. Especially, metabolic engineering strategies for the production of sesquiterpenes such as: amorphadiene, farnesene, bisabolene, and caryophyllene are emphasized in: Escherichia coli , Saccharomyces cerevisiae , and other microorganisms. Herein, challenges and future perspectives of the bioprocess for translating sesquiterpene production into practical industrial work are also discussed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Systematic Analysis of Metabolic Bottlenecks in the Methylerythritol 4-Phosphate (MEP) Pathway of Zymomonas mobilis

Engineered microorganisms have the potential to convert renewable substrates into biofuels and valuable bioproducts, which offers an environmentally sustainable alternative to fossil-fuel-derived products. Isoprenoids are a diverse class of biologically derived compounds that have commercial applications as various commodity chemicals, including biofuels and biofuel precursor molecules.

isoprene↗
DOE OSTI2022

Thioester synthesis by a designed nickel enzyme models prebiotic energy conversion

The formation of carbon–carbon bonds from prebiotic precursors such as carbon dioxide represents the foundation of all primordial life processes. In extant organisms, this reaction is carried out by the carbon monoxide dehydrogenase (CODH)/acetyl coenzyme A synthase (ACS) enzyme, which performs the cornerstone reaction in the ancient Wood–Ljungdahl metabolic pathway to synthesize the key biological metabolite, acetyl-CoA. Despite its significance, a fundamental understanding of this transformation is lacking, hampering efforts to harness analogous chemistry. To address these knowledge gaps, we have designed an artificial metalloenzyme within the azurin protein scaffold as a structural, functional, and mechanistic model of ACS. We demonstrate the intermediacy of the Ni I species and requirement for ordered substrate binding in the bioorganometallic carbon–carbon bond-forming reaction from the one-carbon ACS substrates. The electronic and geometric structures of the nickel-acetyl intermediate have been characterized using time-resolved optical, electron paramagnetic resonance, and X-ray absorption spectroscopy in conjunction with quantum chemical calculations. Moreover, we demonstrate that the nickel-acetyl species is chemically competent for selective acyl transfer upon thiol addition to biosynthesize an activated thioester. Drawing an analogy to the native enzyme, a mechanism for thioester generation by this ACS model has been proposed. The fundamental insight into the enzymatic process provided by this rudimentary ACS model has implications for the evolution of primitive ACS-like proteins. Ultimately, these findings offer strategies for development of highly active catalysts for sustainable generation of liquid fuels from one-carbon substrates, with potential for broad applications across diverse fields ranging from energy storage to environmental remediation.

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

Isotopically nonstationary metabolic flux analysis of plants: recent progress and future opportunities

Metabolic flux analysis (MFA) is a valuable tool for quantifying cellular phenotypes and to guide plant metabolic engineering. By introducing stable isotopic tracers and employing mathematical models, MFA can quantify the rates of metabolic reactions through biochemical pathways. Recent applications of isotopically nonstationary MFA (INST–MFA) to plants have elucidated nonintuitive metabolism in leaves under optimal and stress conditions, described coupled fluxes for fast–growing algae, and produced a synergistic multi–organ flux map that is a first in MFA for any biological system. Finally, these insights could not be elucidated through other approaches and show the potential of INST–MFA to correct an oversimplified understanding of plant metabolism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Cell-free prototyping enables implementation of optimized reverse β-oxidation pathways in heterotrophic and autotrophic bacteria

Abstract Carbon-negative synthesis of biochemical products has the potential to mitigate global CO 2 emissions. An attractive route to do this is the reverse β-oxidation (r-BOX) pathway coupled to the Wood-Ljungdahl pathway. Here, we optimize and implement r-BOX for the synthesis of C4-C6 acids and alcohols. With a high-throughput in vitro prototyping workflow, we screen 762 unique pathway combinations using cell-free extracts tailored for r-BOX to identify enzyme sets for enhanced product selectivity. Implementation of these pathways into Escherichia coli generates designer strains for the selective production of butanoic acid (4.9 ± 0.1 gL −1 ), as well as hexanoic acid (3.06 ± 0.03 gL −1 ) and 1-hexanol (1.0 ± 0.1 gL −1 ) at the best performance reported to date in this bacterium. We also generate Clostridium autoethanogenum strains able to produce 1-hexanol from syngas, achieving a titer of 0.26 gL −1 in a 1.5 L continuous fermentation. Our strategy enables optimization of r-BOX derived products for biomanufacturing and industrial biotechnology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Leveraging public AI tools to explore systems biology resources in mathematical modeling

Predictive mathematical modeling is an essential part of systems biology and is interconnected with information management. Systems biology information is often stored in specialized formats to facilitate data storage and analysis. These formats are not designed for easy human readability and thus require specialized software to visualize and interpret results. Therefore, comprehending modeling and underlying networks and pathways is contingent on mastering systems biology tools, which is particularly challenging for users with no or little background in data science or system biology. To address this challenge, we investigated the usage of public Artificial Intelligence (AI) tools in exploring systems biology resources in mathematical modeling. We tested public AI’s understanding of mathematics in models, related systems biology data, and the complexity of model structures. Our approach can enhance the accessibility of systems biology for non-system biologists and help them understand systems biology without a deep learning curve.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Development of Scalable Reactive Transport Framework for PFAS

Research on PFAS chemicals is extensive and covers all aspects, including analytical quantification, determination of properties, toxicology, ex situ treatment, and in situ remediation. PFAS chemicals are very stable and thus persistent/recalcitrant in the environment. Although there are many unknowns about PFAS chemicals, degradation pathways, reaction rates, etc., many different sorption, oxidation, reduction, biological, and innovative treatment approaches are being developed. Sorption with activated carbon is currently the only fully available in situ treatment technology for PFAS-impacted groundwater. Given the wide array of PFAS chemicals and transformation products, remediation may need multi-step treatment trains to fully address the PFAS contamination. The work here provides kinetic reaction modules that represent an initial cut at functionality representing PFAS migration and reaction in groundwater aquifer flow and transport models. One reaction kinetics module provides a method to model kinetically limited adsorption using a mass transfer model. The second reaction module represents biological transformation of 8:2 FTOH and daughter species, illustrating how a complex reaction pathway network can be represented. Both reaction modules allow for spatially variable parameter values so that a variety of remediation approaches (e.g., a PRB or volumetric treatment or variations in geochemical conditions) can be simulated. The intent with these PFAS reaction modules is to provide tools for practitioners to aid in the selection, design, and assessment of potential in situ PFAS remediation strategies. It is anticipated that, as PFAS remediation technologies and scientific understanding advances, these modules would be refined or replaced to match new knowledge.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗