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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 OSTI2023

Activity‐Based Protein Profiling – Enabling Phenotyping of Host‐Associated and Environmental Microbiomes

Abstract Host‐associated and environmental microbiomes play central roles in human health, biogeochemical cycling, response to ecosystem change, and agriculture. Scientific approaches that can reveal the functional activities that contribute to observed phenotypes are needed in microbiome research. Broad characterization of the functional activity of microbes within microbiomes is currently hampered by approaches that rely on inference of function from metagenomes or indirect measurements. Activity‐based protein profiling is uniquely positioned to overcome these challenges and reveal the protein‐level mechanisms associated with microbiome phenotypes. In this review we describe the progress made to date using ABPP in gut microbiome, plant‐microbe interaction, and soil microbiome research, and suggest how ABPP data can be coupled with advanced computational methods to enable phenotype prediction and bioengineering of microbiomes for applied purposes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Rational Design Principles for the Transport and Subcellular Distribution of Nanomaterials into Plant Protoplasts

The ability to control the subcellular localization of nanoparticles within living plants offers unique advantages for targeted biomolecule delivery and enables important applications in plant bioengineering. However, the mechanism of nanoparticle transport past plant biological membranes is poorly understood. Here, a mechanistic study of nanoparticle cellular uptake into plant protoplasts is presented. An experimentally validated mathematical model of lipid exchange envelope penetration mechanism for protoplasts, which predicts that the subcellular distribution of nanoparticles in plant cells is dictated by the particle size and the magnitude of the zeta potential, is advanced. The mechanism is completely generic, describing nanoparticles ranging from quantum dots, gold and silica nanoparticles, nanoceria, and single-walled carbon nanotubes (SWNTs). In addition, the use of imaging flow cytometry to investigate the influence of protoplasts' morphological characteristics on nanoparticle uptake efficiency is demonstrated. Using DNA-wrapped SWNTs as model nanoparticles, it is found that glycerolipids, the predominant lipids in chloroplast membranes, exhibit stronger lipid–nanoparticle interaction than phospholipids, the major constituent in protoplast membrane. This work can guide the rational design of nanoparticles for targeted delivery into specific compartments within plant cells without the use of chemical or mechanical aid, potentially enabling various plant engineering applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Topological Assembly of a Deployable Hoberman Flight Ring from DNA

Deployable geometries are finite auxetic structures that preserve their overall shapes during expansion and contraction. The topological behaviors emerge from intricately arranged elements and their connections. Despite the considerable utility of such configurations in nature and in engineering, deployable nanostructures have never been demonstrated. In this paper, a deployable flight ring, a simplified planar structure of Hoberman sphere is shown, using DNA origami. The DNA flight ring consists of topologically assembled six triangles in two layers that can slide against each other, thereby switching between two distinct (open and closed) states. The origami topology is a trefoil knot, and its auxetic reconfiguration results in negative Poisson’s ratios. This work shows the feasibility of deployable nanostructures, providing a versatile platform for topological studies and opening new opportunities for bioengineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Genome-Scale 13 C Fluxomics Modeling for Metabolic Engineering of Saccharomyces cerevisiae .

Synthetic biology is a rapidly developing field that pursues the application of engineering principles and development approaches to biological engineering. Synthetic biology is poised to change the way biology is practiced, and has important practical applications: for example, building genetically engineered organisms to produce biofuels, medicines, and other chemicals. Traditionally, synthetic biology has focused on manipulating a few genes (e.g., in a single pathway or genetic circuit), but its combination with systems biology holds the promise of creating new cellular architectures and constructing complex biological systems from the ground up. Enabling this merge of synthetic and systems biology will require greater predictive capability for modeling the behavior of cellular systems, and more comprehensive data sets for building and calibrating these models. The so-called "-omics" data sets can now be generated via high throughput techniques in the form of genomic, proteomic, transcriptomic, and metabolomic information on the engineered biological system. Of particular interest with respect to the engineering of microbes capable of producing biofuels and other chemicals economically and at scale are metabolomic datasets, and their insights into intracellular metabolic fluxes. Metabolic fluxes provide a rapid and easy to understand picture of how carbon and energy flow throughout the cell. Furthermore, we present a detailed guide to performing metabolic flux analysis and modeling using the open source JBEI Quantitative Metabolic Modeling (jQMM) library. This library allows the user to transform metabolomics data in the form of isotope labeling data from a 13 C labeling experiment into a determination of cellular fluxes that can be used to develop genetic engineering strategies for metabolic engineering.The jQMM library presents a complete toolbox for performing a range of different tasks of interest in metabolic engineering. Various different types of flux analysis and modeling can be performed such as flux balance analysis, 13 C metabolic flux analysis, and two-scale 13 C metabolic flux analysis (2S- 13 C MFA). 2S- 13 C MFA is a novel method that determines genome-scale fluxes without the need of every single carbon transition in the metabolic network. In addition to several other capabilities, the jQMM library can make model based predictions for how various genetic engineering strategies can be incorporated toward bioengineering goals: it can predict the effects of reaction knockouts on metabolism using both the MoMA and ROOM methodologies. In this chapter, we will illustrate the use of the jQMM library through a step-by-step demonstration of flux determination and knockout prediction in a complex eukaryotic model organism: Saccharomyces cerevisiae ( S. cerevisiae ). Included with this chapter is a digital Jupyter Notebook file that provides a computable appendix showing a self-contained example of jQMM usage, which can be changed to fit the user's specific needs. As an open source software project, users can modify and extend the code base to make improvements at will, allowing them to share their development work and contribute back to the jQMM modeling community.

-Omics data↗
DOE OSTI2022

Compartment-specific energy requirements of photosynthetic carbon metabolism in Camelina sativa leaves

Abstract Main conclusion The oxidative pentose phosphate pathway provides cytosolic NADPH yet reduces carbon and energy use efficiency. Repressing this pathway and introducing cytosolic NADPH-dependent malate dehydrogenase may increase crop yields by ≈5%. Abstract Detailed knowledge about plant energy metabolism may aid crop improvements. Using published estimates of flux through central carbon metabolism, we phenotype energy metabolism in illuminated Camelina sativa leaves (grown at 22 °C, 500 µmol photons m −2 s −1 ) and report several findings. First, the oxidative pentose phosphate pathway (OPPP) transfers 3.3% of the NADPH consumed in the Calvin–Benson cycle to the cytosol. NADPH supply proceeds at about 10% of the rate of net carbon assimilation. However, concomitantly respired CO 2 accounts for 4.8% of total rubisco activity. Hence, 4.8% of the flux through the Calvin–Benson cycle and photorespiration is spent on supplying cytosolic NADPH, a significant investment. Associated energy requirements exceed the energy output of the OPPP. Thus, autotrophic carbon metabolism is not simply optimised for flux into carbon sinks but sacrifices carbon and energy use efficiency to support cytosolic energy metabolism. To reduce these costs, we suggest bioengineering plants with a repressed cytosolic OPPP, and an inserted cytosolic NADPH-dependent malate dehydrogenase tuned to compensate for the loss in OPPP activity (if required). Second, sucrose cycling is a minor investment in overall leaf energy metabolism but a significant investment in cytosolic energy metabolism. Third, leaf energy balancing strictly requires oxidative phosphorylation, cofactor export from chloroplasts, and peroxisomal NADH import. Fourth, mitochondria are energetically self-sufficient. Fifth, carbon metabolism has an ATP/NADPH demand ratio of 1.52 which is met if ≤ 21.7% of whole electron flux is cyclic. Sixth, electron transport has a photon use efficiency of ≥ 62%. Last, we discuss interactions between the OPPP and the cytosolic oxidation–reduction cycle in supplying leaf cytosolic NADPH.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Evaluating the contribution of plant metabolic pathways in the light to the ATP:NADPH demand using a meta-analysis of isotopically non-stationary metabolic flux analyses

Abstract Balancing the ATP: NADPH demand from plant metabolism with supply from photosynthesis is essential for preventing photodamage and operating efficiently, so understanding its drivers is important for integrating metabolism with the light reactions of photosynthesis and for bioengineering efforts that may radically change this demand. It is often assumed that the C3 cycle and photorespiration consume the largest amount of ATP and reductant in illuminated leaves and as a result mostly determine the ATP: NADPH demand. However, the quantitative extent to which other energy consuming metabolic processes contribute in large ways to overall ATP: NADPH demand remains unknown. Here, we used the metabolic flux networks of numerous recently published isotopically non-stationary metabolic flux analyses (INST-MFA) to evaluate flux through the C3 cycle, photorespiration, the oxidative pentose phosphate pathway, the tricarboxylic acid cycle, and starch/sucrose synthesis and characterize broad trends in the demand of energy across different pathways and compartments as well as in the overall ATP:NADPH demand. These data sets include a variety of species including Arabidopsis thaliana , Nicotiana tabacum , and Camelina sativa as well as varying environmental factors including high/low light, day length, and photorespiratory levels. Examining these datasets in aggregate reveals that ultimately the bulk of the energy flux occurred in the C3 cycle and photorespiration, however, the energy demand from these pathways did not determine the ATP: NADPH demand alone. Instead, a notable contribution was revealed from starch and sucrose synthesis which might counterbalance photorespiratory demand and result in fewer adjustments in mechanisms which balance the ATP deficit.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Handling Gene and Protein Names in the Age of Bioinformatics: The Special Challenge of Secreted Multimodular Bacterial Enzymes such as the cbhA/cbh9A Gene of Clostridium thermocellum

An increasing number of researchers working in biology, biochemistry, biotechnology, bioengineering, bioinformatics and other related fields of science are using biological molecules. As the scientific background of the members of different scientific communities is more diverse than ever before, the number of scientists not familiar with the rules for non-ambiguous designation of genetic elements is increasing. However, with biological molecules gaining importance through biotechnology, their functional and unambiguous designation is vital. Unfortunately, naming genes and proteins is not an easy task. In addition, the traditional concepts of bioinformatics are challenged with the appearance of proteins comprising different modules with a respective function in each module. This article highlights basic rules and novel solutions in designation recently used within the community of bacterial geneticists, and we discuss the present-day handling of gene and protein designations. As an example we will utilize a recent mischaracterization of gene nomenclature. We make suggestions for better handling of names in future literature as well as in databases and annotation projects. Our methodology emphasizes the hydrolytic function of multi-modular genes and extracellular proteins from bacteria.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

MALDI-MS screening of microbial colonies with isomer resolution to select fatty acid desaturase variants

Creating controlled lipid unsaturation locations in oleochemicals can be a key to many bioengineered products. However, evaluating the effects of modifications to the acyl-ACP desaturase on lipid unsaturation is not currently amenable to high-throughput assays, limiting the scale of redesign efforts to <200 variants. Here, we report a rapid MS assay for profiling the positions of double bonds on membrane lipids produced by Escherichia coli colonies after treatment with ozone gas. By MS measurement of the ozonolysis products of Δ6 and Δ8 isomers of membrane lipids from colonies expressing recombinant Thunbergia alata desaturase, we screened a randomly mutagenized library of the desaturase gene at 5 s per sample. Two variants with altered regiospecificity were isolated, indicated by an increase in 16:1 Δ8 proportion. We also demonstrated the ability of these desaturase variants to influence the membrane composition and fatty acid distribution of E. coli strains deficient in the native acyl-ACP desaturase gene, fabA. Lastly, we used the fabA deficient chassis to concomitantly express a non-native acyl- ACP desaturase and a medium-chain thioesterase from Umbellularia californica, demonstrating production of only saturated free fatty acids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Functional and phenotypic flow cytometry characterization of Picochlorum soloecismus

Multiple physiological traits essential for efficient cellular function are important when considering the selection and engineering of algal species for biofuel and bioproduct generation. Bioengineering methods have become more ubiquitous producing several novel algal lines with potentially enhanced traits. Complex metabolic interactions, however, require greater depth in characterizing cellular responses to delineate mechanistic understanding. Here, we have developed fluorescence-based high-throughput flow cytometry protocols to facilitate characterization of cell morphology, membrane permeability, metabolic activity, cell viability, intracellular pH, and reactive oxygen species in isolates derived from the species Picochlorum soloecismus. Flow cytometry parameters were optimized for each assay. This suite of molecular flow cytometry probes and procedures can be utilized for rapid screening of optimal phenotypes in microalgae under various environmental conditions as new technical strategies for improving algae strain productivity are established.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Description of a novel extremophile green algae, Chlamydomonas pacifica , and its potential as a biotechnology host

We present the comprehensive characterization of a newly identified microalga, Chlamydomonas pacifica , originally isolated from a soil sample in San Diego, CA, USA. This species showcases remarkable biological versatility, including a broad pH range tolerance (6–11.5), high thermal tolerance (up to 42 °C), and salinity resilience (up to 2 % NaCl). Its amenability to genetic manipulation and sexual reproduction via mating, particularly between the two opposing strains CC-5697 & CC-5699, now publicly available through the Chlamydomonas Resource Center, underscores its potential as a biotechnological chassis. The biological assessment of C. pacifica revealed versatile metabolic capabilities, including diverse nitrogen assimilation capability, motility and phototaxis. Genomic and transcriptomic analyses identified 17,829 genes within a 121 Mb genome, featuring a GC content of 61 %. The codon usage of C. pacifica closely mirrors that of C. reinhardtii , indicating a conserved genetic architecture that supports a trend in codon preference with minor variations. Phylogenetic analyses position C. pacifica within the core-Reinhardtinia clade yet distinct from known Volvocales species. The lipidomic data revealed an abundance of triacylglycerols (TAGs), promising for biofuel applications and lipids for health-related benefits. Our investigation lays the groundwork for exploiting C. pacifica in biotechnological applications, from biofuel generation to synthesizing biodegradable plastics, positioning it as a versatile host for future bioengineering endeavors.

Alkali tolerant↗
DOE OSTI2018

Development of xeno-free epithelial differentiation media for adherent, non-expanded adipose stromal vascular cell cultures

Reconstruction of respiratory epithelium is critical for the fabrication of bioengineered airway implants. Epithelial differentiation is typically achieved using bovine pituitary extract (BPE). Due to the xenogenic nature and undefined composition of BPE, an alternative for human clinical applications, devoid of BPE, must be developed. The goal of this study was to develop two different BPE-free media, with and without select pituitary hormone (PH), which could initiate epithelial differentiation for use in human implantation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Intracellular cellobiose metabolism and its applications in lignocellulose-based biorefineries

Complete hydrolysis of cellulose has been noted as a key characteristic of biomass technology due to the limitation of industrial production hosts to use cellodextrin, the partial hydrolysis product of cellulose. Cellobiose, a β-1,4-linked glucose dimer, is a major cellodextrin of the enzymatic hydrolysis (via endoglucanase and exoglucanase) of cellulose. Conversion of cellobiose to glucose is executed by β-glucosidase. The complete extracellular hydrolysis of celluloses has several critical barriers in biomass technology. An alternative bioengineering strategy to make the bioprocessing less challenging is to engineer microbes with the abilities to hydrolyze and assimilate the cellulosic-hydrolysate cellodextrin. Microorganisms engineered to metabolize cellobiose rather than the monomeric glucose can provide several advantages for lignocellulose-based biorefineries. This review describes the recent advances and challenges in engineering efficient intracellular cellobiose metabolism in industrial hosts. This review also describes the limitations of and future prospectives in engineering intracellular cellobiose metabolism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

From clutter to clarity: Emergent neural operators via questionnaire metrics

Real-world datasets in chemical engineering and bioengineering processes—such as those from catalytic reactors, multiphase flows, polymerization reactors, bioreactors, and clinical trials—can often be unlabeled or disorganized, rendering the training of existing supervised learning models ineffective at learning the underlying dynamics. To salvage these datasets for decision-making, we first seek to obtain clarity from the cluttered data. Here, we present a framework for developing “structural” generative models, discovering emergent equations, and constructing efficient emulators from scrambled datasets by integrating unsupervised organizational learning techniques (Questionnaires) with advanced deep learning architectures (Deep Hidden Physics Models and Deep Operator Networks). Our approach is demonstrated on two illustrative model systems: (a) a 1D advection–diffusion partial differential equation representing a winding underground pipe and (b) an ensemble of Stuart–Landau oscillators, an agent-based system of coupled ordinary differential equations. In both cases, we successfully reconstruct meaningful spatial, temporal, and parameter embeddings from scrambled data, enabling good predictions of system dynamics. As a result, we highlight the framework’s potential for broader applications, enabling data-driven system identification in fields with inherently disorganized or hidden parameter spaces.

42 ENGINEERING↗
DOE OSTI2019

Transplanting the pathway engineering toolbox to methanogens

Biological methanogenesis evolved early in Earth’s history and was likely already a major process by 3.5 Ga. Modern methanogenesis is now a key process in virtually all anaerobic microbial communities, such as marine and lake sediments, wetland and rice soils, and human and cattle digestive tracts. Owing to their long evolution and extensive adaptations to various habitats, methanogens possess enormous metabolic and physiological diversity. Not only does this diversity offers unique opportunities for biotechnology applications, but also reveals their direct impact on the environment, agriculture, and human and animal health. These efforts are facilitated by an advanced genetic toolbox, emerging new molecular tools, and systems-level modelling for methanogens. Further developments and convergence of these technical advancements provide new opportunities for bioengineering methanogens.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Getting back to the grass roots: harnessing specialized metabolites for improved crop stress resilience

Roots remain understudied as the site of complex and important biological interactions mediating plant productivity. In grain and bioenergy crops, grass root specialized metabolites (GRSM) are central to key interactions, yet our basic knowledge of the chemical language remains fragmentary. Continued improvements in plant genome assembly and metabolomics are enabling large-scale advances in the discovery of specialized metabolic pathways as a means of regulating root-biotic interactions. Metabolomics, transcript coexpression analyses, forward genetic studies, gene synthesis and heterologous expression assays drive efficient pathway discoveries. Functional genetic variants identified through genome wide analyses, targeted CRISPR/Cas9 approaches, and both native and non-native overexpression studies critically inform novel strategies for bioengineering metabolic pathways to improve plant traits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Perspectives for self-driving labs in synthetic biology

Self-driving labs (SDLs) combine fully automated experiments and data collection with artificial intelligence (AI) and control algorithms that decide not only the set of parameters for the next experiment, but also potentially which scientific hypotheses to test. Taken to their ultimate expression, SDLs could usher a new paradigm of scientific research, where the world is probed, interpreted, and explained by machines for human benefit. Whereas there are functioning SDLs in the fields of chemistry and materials science, we contend that synthetic biology provides a unique opportunity since the genome provides a single, easily accessible, target for affecting the incredibly wide repertoire of biological cell behavior. Since they can provide large amounts of high-quality data, SDLs can be a platform for AI to develop approaches to systematically convert data into scientific knowledge systems. These knowledge systems can be used both to understand the biological world and to design bioengineered systems to fit a desired specification (inverse design). However, the level of investment required for the creation of biological SDLs is only warranted if directed towards solving difficult and enabling biological questions. Here, we discuss challenges and opportunities in creating SDLs for synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

ToF-SIMS spectral data analysis of Paenibacillus sp. 300A biofilms and planktonic cells

Analysis of bacterial biofilms is particularly challenging and important with diverse applications from systems biology to biotechnology. Among the variety of techniques that have been applied, time-of-flight secondary ion mass spectrometry (ToF-SIMS) has many promising features in studying the surface characteristics of biofilms. ToF-SIMS offers high spatial resolution and high mass accuracy, which permit surface sensitive analysis of biofilm components. Thus, ToF-SIMS provides a powerful solution to addressing the challenge of bacterial biofilm analysis. This dataset covers ToF-SIMS analysis of Paenibacillus sp. 300A (300A) isolated from the Hanford site in Richland, WA. The strain is known to have metal and sulfur reducing properties and can be used for bioremediation, wastewater treatment, bioengineering and technology development. There is a current need to identify small molecules and fragments produced from bacterial biofilms. Static ToF-SIMS spectra of 300A were obtained using an IONTOF TOF-SIMS V instrument equipped with a 25 keV Bi 3 + metal ion gun. Identified molecules and molecular fragments are compared against known biological databases and the reported peaks have at least 65 ppm mass accuracy. These molecules range from lipids and fatty acids to flavonoids, quinolones, and other naturally occurring organic compounds. It is anticipated that the spectral identification of key peaks will assist detection of metabolites, extracellular polymeric substance molecules like polysaccharides, and biologically relevant small molecules using ToF-SIMS in future surface and interface research of bacterial biofilms.

Biofilms↗