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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 OSTI2025

Challenges in spatial metabolomics and proteomics for functional tissue unit and single-cell resolution

While transcriptomics is the most broadly applied technology for global spatial and single cell measurements in healthy and diseased tissues. Transcripts are often used as a proxy for protein and even metabolite measurements, but it has become commonly accepted that extrapolating this kind of information is a poor proxy and not a substitute for direct measurement. Within the last decade advanced developments of mass spectrometry-based assays have made these direct measurements not only possible, but routine. Where mass spectrometry has become an enabling technology, and various methods can now detect hundreds of metabolites and thousands of proteins from samples. Not only can this be performed within bulk measurements, but much effort has been directed into translating these measurements to single cells and tissues at cellular resolution. The information obtained from mass spectrometry is now able to trace metabolic events and decipher feedback loops across anatomical regions, connecting genetic and metabolic networks that define phenotypes. Herein, we will broadly overview developments in the field over the past decade, leading into several case studies which highlight the direct measurement of metabolites, proteins, and proteoforms from thinly sliced tissues. Much of this work is feasible due to multidisciplinary team science, and we offer brief perspective on paths forward and the challenges that persist with adoption and application of spatial omics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Potential virus-mediated nitrogen cycling in oxygen-depleted oceanic waters

Viruses play an important role in the ecology and biogeochemistry of marine ecosystems. Beyond mortality and gene transfer, viruses can reprogram microbial metabolism during infection by expressing auxiliary metabolic genes (AMGs) involved in photosynthesis, central carbon metabolism, and nutrient cycling. While previous studies have focused on AMG diversity in the sunlit and dark ocean, less is known about the role of viruses in shaping metabolic networks along redox gradients associated with marine oxygen minimum zones (OMZs). Here, we analyzed relatively quantitative viral metagenomic datasets that profiled the oxygen gradient across Eastern Tropical South Pacific (ETSP) OMZ waters, assessing whether OMZ viruses might impact nitrogen (N) cycling via AMGs. Identified viral genomes encoded six N-cycle AMGs associated with denitrification, nitrification, assimilatory nitrate reduction, and nitrite transport. The majority of these AMGs (80%) were identified in T4-like Myoviridae phages, predicted to infect Cyanobacteria and Proteobacteria, or in unclassified archaeal viruses predicted to infect Thaumarchaeota. Four AMGs were exclusive to anoxic waters and had distributions that paralleled homologous microbial genes. Together, these findings suggest viruses modulate N-cycling processes within the ETSP OMZ and may contribute to nitrogen loss throughout the global oceans thus providing a baseline for their inclusion in the ecosystem and geochemical models.

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

Unnatural biosynthesis by an engineered microorganism with heterologously expressed natural enzymes and an artificial metalloenzyme

Synthetic biology enables microbial hosts to produce complex molecules from organisms that are rare or difficult to cultivate, but the structures of these molecules are limited to those formed by reactions of natural enzymes. The integration of artificial metalloenzymes (ArMs) that catalyse unnatural reactions into metabolic networks could broaden the cache of molecules produced biosynthetically. Here, in this work, we report an engineered microbial cell expressing a heterologous biosynthetic pathway, containing both natural enzymes and ArMs, that produces an unnatural product with high diastereoselectivity. We engineered Escherichia coli with a heterologous terpene biosynthetic pathway and an ArM containing an iridium–porphyrin complex that was transported into the cell with a heterologous transport system. We improved the diastereoselectivity and product titre of the unnatural product by evolving the ArM and selecting the appropriate gene induction and cultivation conditions. This work shows that synthetic biology and synthetic chemistry can produce, by combining natural and artificial enzymes in whole cells, molecules that were previously inaccessible to nature.

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

Molecular Transformation and Metabolic Insights of Microbial Electrolysis Treatment and Valorization of Post-hydrothermal Liquefaction Wastewater

Hydrothermal liquefaction (HTL) presents a promising approach for the conversion of wet waste into biocrude and biofuels. However, the post-hydrothermal liquefaction wastewater (PHW) poses significant challenges for treatment and valorization due to its high concentration and complex nature. In this study, we investigated the conversion pathways of major organic contaminants within the microbial electrolytic treatment of PHW from food waste HTL. To achieve this, we employed high-performance liquid chromatography (HPLC) and 2D nuclear magnetic resonance (NMR). Our findings demonstrate volatile fatty acids (VFAs) and monohydric and polyhydric alcohols were effectively transformed through the synergistic metabolism of fermentative and electroactive bacteria, which led to over 70% COD removal of the recalcitrant compounds and a record high H2 production rate (1.62 L L -1 d -1 ). We also employed the liquid-state 15N NMR on wastewater samples for the first time and revealed that the nitrogen-containing heteroaromatics were persistent to microbial electrochemical treatment. By integrating the chemical profiles with bioanode community profiles, we constructed a metabolic network that provides insights for enhancing treatment efficiency and facilitating resource recovery.

08 HYDROGEN↗
DOE OSTI2024

Clocking out and letting go to unleash green biotech applications in a photosynthetic host

Cyanobacteria are photosynthetic bacteria whose gene expression patterns are globally regulated by their circadian (daily) clocks. Due to their ability to use sunlight as their energy source, they are also attractive hosts for “green” production of pharmaceuticals, renewable fuels, and chemicals. However, despite the application of traditional genetic tools such as the identification of strong promoters to enhance the expression of heterologous genes, cyanobacteria have lagged behind other microorganisms such as Escherichia coli and yeast as economically efficient cell factories. The previous approaches have ignored large-scale constraints within cyanobacterial metabolic networks on transcription, predominantly the pervasive control of gene expression by the circadian (daily) clock. Here, we show that reprogramming gene expression by releasing circadian repressor elements in the transcriptional regulatory pathways coupled with inactivation of the central oscillating mechanism enables a dramatic enhancement of expression in cyanobacteria of heterologous genes encoding both catalytically active enzymes and polypeptides of biomedical significance.

Science & Technology - Other Topics↗
DOE OSTI2021

The metabolic origins of non-photorespiratory CO 2 release during photosynthesis: a metabolic flux analysis

Respiration in the light (R L ) releases CO 2 in photosynthesizing leaves and is a phenomenon that occurs independently from photorespiration. Since R L lowers net carbon fixation, understanding R L could help improve plant carbon-use efficiency and models of crop photosynthesis. Although R L was identified more than 75 years ago, its biochemical mechanisms remain unclear. To identify reactions contributing to R L , we mapped metabolic fluxes in photosynthesizing source leaves of the oilseed crop and model plant camelina (Camelina sativa). We performed a flux analysis using isotopic labeling patterns of central metabolites during 13 CO 2 labeling time course, gas exchange, and carbohydrate production rate experiments. To quantify the contributions of multiple potential CO 2 sources with statistical and biological confidence, we increased the number of metabolites measured and reduced biological and technical heterogeneity by using single mature source leaves and quickly quenching metabolism by directly injecting liquid N 2 ; we then compared the goodness-of-fit between these data and data from models with alternative metabolic network structures and constraints. Our analysis predicted that R L releases 5.2 μmol CO2 g –1 FW h –1 of CO 2 , which is relatively consistent with a value of 9.3 μmol CO 2 g –1 FW h –1 measured by CO 2 gas exchange. The results indicated that ≤10% of R L results from TCA cycle reactions, which are widely considered to dominate R L . Further analysis of the results indicated that oxidation of glucose-6-phosphate to pentose phosphate via 6-phosphogluconate (the G6P/OPP shunt) can account for >% of CO 2 released by R L .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

The promising role of proteomes and metabolomes in defining the single-cell landscapes of plants

The plant community has a strong track-record of RNA sequencing technology deployment, which combined with the recent advent of spatial platforms (e.g., 10x genomics), has resulted in an explosion of outstanding single cell and nuclei datasets that can be put in an in situ context within tissues (e.g., a cell atlas)1. In the genomics era, application of proteomics technologies in the plant sciences has always trailed behind that of RNA sequencing technologies, largely due to accessibility, ease-of-use and access to expertise along with depth of analysis benefits. On the other hand, the use of early analytical tools for characterizing small molecules (metabolites) from plant systems predates nucleic acid sequencing and proteomics analysis2, as the search for plant-based natural products has played a significant role in improving human health throughout history. However, the employment of proteomics and metabolomics assays for characterizing plant cell processes now remains significantly behind transcriptional approaches, even though both provide a direct functional readout of cell states and phenotypes.

Anderton, Christopher R. [BATTELLE (PACIFIC NW LAB↗
DOE OSTI2022

Metagenome-Assembled Genomes from a Microbiome Grown in Dairy Manure Hydrolysate

Anaerobic microbiomes can be used to recover the chemical energy in agroindustrial and municipal wastes as useful products. Here, we report a total of 109 draft metagenome-assembled genomes from a bioreactor-fed carbohydrate-rich dairy manure hydrolysate. Studying these genomes will aid us in deciphering the metabolic networks in anaerobic microbiomes.

Ingle, Abel T.↗
DOE OSTI2024

maranasgroup/KETCHUP

Repository for Kinetic Estimation Tool Capturing Heterogeneous Datasets Using Pyomo (KETCHUP), a flexible parameter estimation tool that leverages a primal-dual interior-point algorithm to solve a nonlinear programming (NLP) problem that identifies a set of parameters capable of recapitulating the steady-state fluxes and concentrations in wild-type and perturbed metabolic networks.

Suthers, Patrick↗
DOE OSTI2022

Syntrophic Co-Cultures of Clostridium Organisms to Produce Higher Alcohols & Other C6-C8 Metabolites (Final Report)

The goal of this project was to advance the systems biology understanding and predictive modeling of synthetic & syntrophic Clostridium microbial consortia, focusing on elucidation of metabolic networks and environmental signals in the consortia. The project has direct applicability to lignocellulosic-biomass based production of higher alcohols as advanced biofuels and C6-C8 metabolites, that can be used as chemicals or serve as biofuel precursors. This project studied and optimized three synthetic syntrophic systems. It examined the population dynamics using flow-cytometry, time-lapse microscopy and PCR analysis. 13C-based tracer analyses was used to examine the metabolite exchange between the syntrophic cell populations and the impact of those interactions on the transcriptome of the individual populations. To enhance our analytical and predictive capabilities, genome-scale models (GSMs) for these syntrophies was developed. RNAseq data for these syntrophic coculture systems were acquired to enable a molecular level understanding of the syntrophies aiming to identify the genetic networks of each organism in the co-culture and compare those against the networks of pure cultures.

09 BIOMASS FUELS↗
DOE OSTI2025

Moisture Metaphenome Incubation Analysis Results

The Birch effect, a pulse of CO2 release that occurs when dry soil is rewet, is commonly observed, yet the underlying biogeochemistry remains elusive. Using multi-omics data, real-time mass spectrometry and modeling approaches, we investigated the molecular response to rewetting of a soil microbiome exposed to drought for one and two weeks. The microbiome response was evaluated through analysis of transcript, protein, metabolite, and respiration profiles and metabolic modeling using an enhanced version of the Metabolite Expression Metabolic Network Integration for Pathway Identification and Selection (MEMPIS) algorithm (Roy Chowdhury et al, mSystems, 2019).

Lipton, Mary S [Pacific Northwest National Laborat↗
DOE OSTI2022

Chemotaxonomic patterns in intracellular metabolites of marine microbial plankton

Most biological diversity on Earth is contained within microbial communities. In the ocean, these communities dominate processes related to carbon fixation and nutrient recycling. Yet, specific factors that determine community composition and metabolic activity are difficult to resolve in complex microbial populations, complicating predictions of microbial processes in a changing ocean. Microbial metabolism generates small organic molecules that reflect both the biochemical and physiological diversity as well as the taxonomic specificity of these biological processes. These small molecules serve as the conduit for taxon-specific signaling and exchange. Here, we use liquid chromatography-mass spectrometry (LC-MS)-based metabolomics to taxonomically categorize 111 metabolites that include small molecules in central and secondary metabolism across 42 taxa representing numerically dominant and metabolically important lineages of microbial autotrophs and heterotrophs. Patterns in metabolite presence-absence broadly reflected taxonomic lineages. A subset of metabolites that includes osmolytes, sulfur-containing metabolites, sugars, and amino acid derivatives provided chemotaxonomic information among phytoplankton taxa. A variety of phytohormones and signaling molecules were predominantly found in the heterotrophic bacteria and archaea, expanding knowledge of metabolites implicated in modulating interactions between microbes. This chemotaxonomic inventory of marine microbial metabolites is a key step in deciphering metabolic networks that influence ocean biogeochemical cycles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Catalytic Bias of NADH-Dependent Reduced Ferredoxin: NADP+ Oxidoreductase (Nfn) and its Relevance to Ethanol Production in Thermoanaerobacterium Saccharolyticum

NADH-dependent reduced ferredoxin: NADP+ oxidoreductase (Nfn) enzyme catalyzes an energy-conserving flavin-based electron bifurcation (FBEB) reaction. In microbial metabolism, Nfn links redox pools of three electron carriers - ferredoxin (Fd), NAD(H), and NADP(H) - through the following FBEB reaction: 2 NADPH + NAD+ + 2 Fdox 2 NADP+ + NADH + 2 Fdred + H+ The forward reaction is termed electron bifurcation, and the reverse reaction is electron confurcation. Catalytic bias describes an enzyme's tendency to favor one direction of a reversible reaction over the other and is expressed as the ratio of activities in the two directions. Thermoanaerobacterium saccharolyticum (Tsac) is a thermophilic, ethanologenic bacterium that ferments hemicellulose to ethanol at yields above 90%. Its Nfn enzyme is known to support ethanol production, presumably by operating in the confurcating direction to balance cellular cofactors, but this has not previously been demonstrated. To investigate the Tsac Nfn further, we heterologously expressed, purified, and reconstituted the proteins NfnS (NfnA), NfnL (NfnB), and the putative partner Fd with iron-sulfur cluster and/or FAD cofactors. Activity assays monitoring the oxidation or reduction of Fd showed that, across pH 5-10, Tsac Nfn is catalytically biased towards the confurcating direction, favoring NADPH generation over NADPH oxidation by at least fivefold. Using protein electrochemistry, we also determined the reduction potentials of the cofactors in NfnL and Fd. These results indicate that the energetic landscape of FBEB in Tsac Nfn is similar to that in an ortholog. However, Tsac Fd has redox properties distinct from previously assayed Fds, suggesting that the identity and redox properties of Fd may help determine the catalytic bias of Nfn. Additionally, we confirmed the standalone ferredoxin: NADP+ oxidoreductase (FNOR) activity of NfnL but found it to be low and likely insignificant for in vivo redox conversion. We also show how the catalytic bias of Nfn integrates with the hydrogen cycling mechanism proposed in Tsac to better explain cofactor balancing for ethanol production. Our work advances the understanding of electron transfer processes within metabolic networks for the generation of valuable bioproducts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Kinetics Modeling and Reactor Design Study of Glucose-to-Terpenes Cell-Free Conversion

Cell-free systems offer many advantages over traditional biological conversion by eliminating biological growth constraints. It also offers easy manipulation and finetuning of the reaction conditions for each individual enzyme. The conversion of cellulosic glucose to Limonene, a terpene, is a promising pathway for producing fuels and chemicals. Recent advances in developing cell-free systems focuses on bench scale optimization of terpene yield and to demonstrate its feasibility towards commercialization [1,2]. There is significant knowledge gap regarding reaction kinetics of these cell-free systems to further study how it will perform at larger scale. We present here, our studies on reaction kinetics and reactor design implications of cell-free glucose to Limonene conversion to facilitate the further development and commercialization of this process. We developed a novel kinetic model based on the metabolic-network structure of the cell-free system with multi-substrate reversible Michaelis-Menten rate law. To estimate kinetic parameters for this system of rate equations, we employed Bayesian optimization to perform global search with the assistance of gaussian processes to balance exploration and exploitation. The model parameters estimated showed good results compared with experimental data. The estimated parameters were used to perform sensitivity analysis. We found that Hexokinase is one of the most critical enzymes that affect the conversion of the glucose. We also observed that abundance of co-factors is also critical to the conversion of glucose to limonene. We investigated packed bed reactors with enzymes immobilized on the surface of particles to convert glucose stream into Limonene for larger scale production. The reactor design such as particle size, enzyme loading, and flow rate are found to be critical for improving yields. [1] Dudley, Q.M., Nash, C.J. and Jewett, M.C., 2019. Synthetic Biology, 4(1), p.ysz003. [2] Korman, T.P., Opgenorth, P.H. and Bowie, J.U., 2017. Nature communications, 8(1), p.15526.

09 BIOMASS FUELS↗
DOE OSTI2020

Integrated network modeling approach defines key metabolic responses of soil microbiomes to perturbations

The soil environment is constantly changing due to shifts in soil moisture, nutrient availability and other conditions. To contend with these changes, soil microorganisms have evolved a variety of ways to adapt to environmental perturbations, including regulation of gene expression. However, it is challenging to untangle the complex phenotypic response of the soil to environmental change, partly due to the absence of predictive modeling frameworks that can mechanistically link molecular-level changes in soil microorganisms to a community’s functional phenotypes (or metaphenome). Towards filling this gap, we performed a combined analysis of metabolic and gene co-expression networks to explore how the soil microbiome responded to changes in soil moisture and nutrient conditions and to determine which genes were expressed under a given condition. Our integrated modeling approach revealed previously unknown, but critically important aspects of the soil microbiomes’ response to environmental perturbations. Incorporation of metabolomic and transcriptomic data into metabolic reaction networks identified condition-specific signature genes that are uniquely associated with dry, wet, and glycine-amended conditions. A subsequent gene co-expression network analysis revealed that drought-associated genes occupied more central positions in a network model of the soil community, compared to the genes associated with wet, and glycine-amended conditions. These results indicate the occurrence of system-wide metabolic coordination when soil microbiomes cope with moisture or nutrient perturbations. Importantly, the approach that we demonstrate here to analyze large-scale multi-omics data from a natural soil environment is applicable to other microbiome systems for which multi-omics data are available.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Design patterns of biological cells

Design patterns are generalized solutions to frequently recurring problems. They were initially developed by architects and computer scientists to create a higher level of abstraction for their designs. Here, we extend these concepts to cell biology to lend a new perspective on the evolved designs of cells' underlying reaction networks. We present a catalog of 21 design patterns divided into three categories: creational patterns describe processes that build the cell, structural patterns describe the layouts of reaction networks, and behavioral patterns describe reaction network function. Applying this pattern language to the E. coli central metabolic reaction network, the yeast pheromone response signaling network, and other examples lends new insights into these systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Optimization of Energy Flow through Synthetic Metabolic Modules and Regulatory Networks in a Model Photosynthetic Eukaryotic Microbe

Photosynthetic organisms have recently gained considerable attention for a role in development of renewable energy sources. Genome-enabled systems biology methods, coupled with functional and synthetic genomics, present opportunities to develop sustainable and economical applications such as fuel production within the next 10 to 15 years. However, optimization of light-driven metabolism for biomass or biofuel production will require a detailed systems biology understanding of photosynthetic processes and cellular metabolism. Genome-scale metabolic models (GEMs) are at the core of systems analysis of cellular processes and form a common organizational framework for analyses of data resulting from functional genomics experimental work and computational studies. Therefore, there is a clear demand for high quality photosynthetic model organisms and the appropriate computational tools that enable systems analysis of light-driven metabolism. Through research conducted we expanded the currently available repertoire of photosynthetic GEMs to include the commercially valuable model diatom Phaeoctylum tricornutum. Diatoms have a peculiar and distinct evolutionary footprint and represent a major eukaryotic lineage that is taxonomically and functionally distinct from green and red algae and vascular plants. Therefore, the true potential for light-driven metabolism aimed at biofuel production remains poorly understood at a systems level for a large subset of the global diversity of photosynthetic organisms. The metabolic capabilities of P. tricornutum were comparatively modeled with those from other photosynthetic groups in order to elucidate the occurrence of metabolic traits within and between phototrophs. Additionally, this research resulted in significant extension of the COnstraints Based Reconstruction and Analysis (COBRA) Toolbox to accommodate the crucial need for infrastructure required for ‘omics data integration and analysis in the context of genome-scale models. Therefore, the proposed research achieved two important goals. First, within the broad scope of photosynthetic organisms, we functionally compared and, as a result, identified cellular processes that require optimization in order to enable deployment as biofuel feedstock. Second, the proposed research resulted in development of key computational infrastructure, which can be further extended to other biological systems, that is currently lacking but necessary for multiple ‘omics data integration.

59 BASIC BIOLOGICAL SCIENCES↗